Arts, Faculty of
Psychology, Department of
DSpace
UBCV
Maslany, Anna
Doctor of Philosophy - PhD
University of British Columbia
Emotional events can change attention to “focus on the forest” (I.e., broadened attention scope) or “focus on a tree” (i.e., narrowed attention scope). My dissertation aimed to understand the influence of valence states on attention scope. Experiments 1-3 examined the dominant theories that describe the influence of valence states on attention scope with positive, neutral, and negative states (e.g., Fredrickson, 2001;2004; Gasper & Clore, 2002). Experiment 4 examined the influence of valence states on attention scope further with attractive and repulsive states and explored an alternative theory (e.g., Harmon-Jones & Gable, 2010b). The results of these experiments showed no influence of valence states on attention scope, therefore, Experiments 5 and 6 marked a shift in my dissertation research. In these experiments, I wanted to determine if the tools I was using to pick up changes in attention scope were valid. I examined if the predicted pattern of results would occur on the Eriksen flanker task (Eriksen & Eriksen, 1974) after a broad and narrow attention scope was induced in participants. I also examined several specific variations of the Eriksen flanker task (which varied in terms of font, spacing, and visual angle), to determine if some specific variations were more effective than others at picking up changes in attention scope. In my final experiment, Experiment 7, I used one of the most promising variations of the Eriksen flanker task and I returned to the original aim of my dissertation to understand the influence of valence states on attention scope.
The Influence of Valence States on the Scope of Visual Attention by Anna Maslany B.A. (Hons), University of Regina, 2011 M.A., University of Saskatchewan, 2013 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Psychology) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) April 2023 © Anna Maslany, 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: The Influence of Valence States on the Scope of Visual Attention submitted by Anna Maslany in partial fulfilment of the requirements for the degree of Doctor of Philosophy In Psychology Examining Committee: Peter Graf, Professor, Psychology, UBC Supervisor James Enns, Professor, Psychology, UBC Supervisory Committee Member Jessica Tracy, Professor, Psychology, UBC Supervisory Committee Member Rebecca Todd, Associate Professor, Psychology, UBC University Examiner Lisa Cavanaugh, Associate Professor, Sauder School of Business, UBC University Examiner iii Abstract Emotional events can change attention to “focus on the forest” (I.e., broadened attention scope) or “focus on a tree” (i.e., narrowed attention scope). My dissertation aimed to understand the influence of valence states on attention scope. Experiments 1-3 examined the dominant theories that describe the influence of valence states on attention scope with positive, neutral, and negative states (e.g., Fredrickson, 2001;2004; Gasper & Clore, 2002). Experiment 4 examined the influence of valence states on attention scope further with attractive and repulsive states and explored an alternative theory (e.g., Harmon-Jones & Gable, 2010b). The results of these experiments showed no influence of valence states on attention scope, therefore, Experiments 5 and 6 marked a shift in my dissertation research. In these experiments, I wanted to determine if the tools I was using to pick up changes in attention scope were valid. I examined if the predicted pattern of results would occur on the Eriksen flanker task (Eriksen & Eriksen, 1974) after a broad and narrow attention scope was induced in participants. I also examined several specific variations of the Eriksen flanker task (which varied in terms of font, spacing, and visual angle), to determine if some specific variations were more effective than others at picking up changes in attention scope. In my final experiment, Experiment 7, I used one of the most promising variations of the Eriksen flanker task and I returned to the original aim of my dissertation to understand the influence of valence states on attention scope. iv Lay Summary Emotional events can change attention to “focus on the forest” or “focus on a particular tree”. My dissertation was guided theories that explain the influence of emotional events on the scope of visual attention with valence (e.g., Fredrickson, 2004) or movement propensity (e.g., Gable & Harmon-Jones, 2010b). Valence refers to the positivity or negativity of an emotional event (e.g., Russell et al., 1989) and movement propensity refers to the strength of the tendency to move towards or away from it (e.g.. Gable & Harmon-Jones, 2010b). I conducted five experiments to examine the influence of valence and movement propensity on the scope of attention, as well as two experiments that aimed to develop better instruments to measure the scope of attention. I found no influence of valence or movement propensity on the scope of attention. I conclude that the theories which motivated my research do not hold in certain situations, and ought to be revised to specify the situations in which the influence of valence and movement propensity on attention scope does and does not occur. v Preface This dissertation is an original intellectual product of the author, Anna Maslany. The experiments reported in Chapters 2-5 were covered by UBC Ethics Certificate number H03-80566. The Experiments reported in Chapters 6 and 7 was covered by UBC Ethics Certificate number H19-00609. Anna Maslany was the primary author and presenter for all conference presentations and posters cited in this document. vi Table of Contents Abstract ........................................................................................................................................... iii Lay Summary .................................................................................................................................. iv Preface .............................................................................................................................................. v Table of Contents ………………………………………………………………………………………… vi List of Tables ................................................................................................................................... xi List of Figures ............................................................................................................................... xiv Acknowledgements ..................................................................................................................... xxii Chapter 1: Research Review and Dissertation Goal ..................................................................... 1 1.1: Attention Affects Processing ................................................................................................... 3 1.2. Theoretical Claims About Emotional Events and Attention Scope ......................................... 5 1.2.1: Affect-as-Information Hypothesis .................................................................................... 5 1.2.2: Broaden-and-Build Theory .............................................................................................. 6 1.2.3: Motivational Intensity Theory ........................................................................................... 6 1.2.4: Summary: Differences Between the Theories ................................................................. 7 1.3. Research on the Relationship Between Emotional Events and Attention Scope ................... 8 1.3.3: The Influence of Movement Propensity on Attention Scope ......................................... 21 1.4: Methodological Issues ...................................................................................................... 25 1.5. Definitions ............................................................................................................................. 28 1.6. Overview of Dissertation .................................................................................................. 29 Chapter 2: The Influence of Valence States on the Scope of Attention .................................... 32 vii 2.1: Experiment 1 Method ............................................................................................................ 34 2.1.1: Design and Participants ................................................................................................ 34 2.1.2: Materials ........................................................................................................................ 34 2.1.3: Procedure ...................................................................................................................... 37 2.2: Results and Discussion ........................................................................................................ 40 2.2.1: Data Screening .............................................................................................................. 40 2.2.2: Picture Task Performance ............................................................................................. 41 2.2.3: Navon Task Performance .............................................................................................. 43 2.2.4: Bayesian Analyses ........................................................................................................ 49 2.3: Experiment 1 Conclusion ...................................................................................................... 50 2.4: Experiment 2 ......................................................................................................................... 51 2.4.1: Design and Participants ................................................................................................ 51 2.4.2: Materials ........................................................................................................................ 52 2.4.3: Procedure ...................................................................................................................... 54 2.4.4: Results and Discussion ..................................................................................................... 58 2.4.4.1: Data Preparation ........................................................................................................ 58 2.4.4.2: Picture Ratings ........................................................................................................... 59 2.4.4.3: Eriksen Flanker Task Performance ............................................................................ 61 2.4.4.4: Bayesian Analyses ..................................................................................................... 68 2.6: Experiment 2 Conclusion ...................................................................................................... 69 2.7: Experiments 1 and 2 Conclusion .......................................................................................... 70 viii Chapter 3: Validity of the Affect Induction .................................................................................. 72 3.1: Method .................................................................................................................................. 73 3.1.1: Participants and Design ................................................................................................ 73 3.1.2: Materials ........................................................................................................................ 74 3.1.3: Procedure ...................................................................................................................... 76 3.2: Results and Discussion ........................................................................................................ 78 3.2.1: Data Preparation ........................................................................................................... 78 3.2.2: Russell’s Affect Grid Scores .......................................................................................... 78 .3.2.3: BMIS Scores ................................................................................................................ 80 3.2.4: Picture Task Performance ............................................................................................. 82 3.2.5: Eriksen Flanker Task Performance ............................................................................... 84 3.3: Experiment 3 Conclusion ...................................................................................................... 88 Chapter 4: The Influence of Movement Propensity Sates on the Scope of Attention ............. 90 4.1: Method .................................................................................................................................. 92 4.1.1: Participants and Design ................................................................................................ 92 4.1.2: Materials ........................................................................................................................ 92 4.1.3: Procedure ...................................................................................................................... 94 4.2: Results and Discussion ........................................................................................................ 96 4.2.1: Data Screening .............................................................................................................. 96 4.2.2: Picture Task Performance ............................................................................................. 97 4.3: Experiment 4 Conclusion .................................................................................................... 102 ix Chapter 5: The Validity of the Eriksen Flanker Task ............................................................... 104 5.1. Method ................................................................................................................................ 106 5.1.1: Design and Participants .............................................................................................. 106 5.2.2: Materials ...................................................................................................................... 107 5.3: Procedure ....................................................................................................................... 110 5.4: Results and Discussion ...................................................................................................... 113 5.4.1: Data Screening ............................................................................................................ 113 5.4.2: Navon Induction Task Performance ............................................................................ 113 5.4.3: Eriksen Flanker Task Performance ............................................................................. 115 5.5. Experiment 5 Interim Conclusion ........................................................................................ 127 5.6. Experiment 6 ....................................................................................................................... 127 5.6.1: Design and Participants .............................................................................................. 127 5.6.1: Materials ...................................................................................................................... 128 5.7: Procedure ....................................................................................................................... 129 5.8: Results and Discussion ...................................................................................................... 130 5.8.1: Data Preparation ......................................................................................................... 130 5.10: Chapter 5 Conclusion ....................................................................................................... 143 Chapter 6: The Influence of Emotional Events on the Scope of Attention ............................. 145 6.1: Experiment 7 Method .......................................................................................................... 146 6.1.2: Participants and Design .............................................................................................. 146 6.1.3: Materials ...................................................................................................................... 147 x 6.1.4. Procedure .................................................................................................................... 148 6.2: Results and Discussion ...................................................................................................... 151 6.2.1: Data Preparation ......................................................................................................... 151 6.2.2: Discrete Emotions and Attention Scope ...................................................................... 152 6.2.3: Induced Attentional Set on Attention Scope ................................................................ 158 6.5: Experiment 7 Conclusion .................................................................................................... 160 Chapter 7: General Discussion ................................................................................................... 161 7.1: Limitations of My Research ................................................................................................ 163 7.2: Conclusion .......................................................................................................................... 165 References .................................................................................................................................... 167 Appendicies .................................................................................................................................. 184 Appendix A ................................................................................................................................ 184 Appendix B ................................................................................................................................ 185 xi List of Tables Table 1. 1. An Example of the Stimuli used for the Eriksen Flanker Task. The left column shows the three types of flanker stimuli (i.e., congruent, control, and incongruent). The middle column gives an example with letters (LLLLL; LLXLL; LLTLL) and the right column gives an example with arrows………………………………………………………………………………………..……………………….. 10 Table 2. 1. Valence and Arousal Ratings for IAPS pictures for Experiment 1, with the Selection Criteria and the Properties of the Selected Pictures for Each Valence Level/Bin: Extremely Positive, Positive, Neutral, Negative, and Extremely Negative………………………………………………………………………………. 36 Table 2. 2. Mean Accuracy and Standard Deviation in the Navon task on Global and Local Letters Following the Pictures from Each Valence Level Condition in Experiment 1………………………………... 44 Table 2. 3. Bayes Factors Calculated using a Dependent Samples T-Test for Global and Local Letters in Each Valence Level Condition in Experiment 1………………………………………………………………..... 50 Table 2. 4. Valence and Arousal Ratings for IAPS Pictures for Experiment 2, with the Selection Criteria and the Properties of the Selected Pictures for each Valence Level………………………………………………...53 Table 2. 5. Mean Accuracy and Standard Deviation on the Eriksen Flanker Task for Congruent, Control and Incongruent Stimuli in the No Space and Space Conditions in Experiment 2………………………………... 62 Table 2. 6. Mean Accuracy and Standard Deviation on the Eriksen Flanker Task in Experiment 2 for Congruent, Control and Incongruent Stimuli in each Valence Level Condition: Extremely Negative, Negative, Neutral, Positive, and Extremely Positive…………………………………………………………….. 62 xii Table 2. 7. Mean of Median Response Time and Standard Deviation in the Eriksen Flanker Task on Congruent, Control and Incongruent Stimuli in the No Space and Space Conditions in Experiment 2….... 64 Table 2. 8. Bayes Factors Calculated using a Related Samples T-Test for Congruent and Incongruent Stimuli in Each Valence Level Condition in Experiment 2……………………………………………………… 69 Table 3. 1. Valence and Arousal Ratings for IAPS Pictures for Experiment 3, with the Selection Criteria and the Properties of the Selected Pictures for Each Valence Level/Bin: Positive, Neutral, and Negative……. 75 Table 3. 2. Mean Accuracy and Standard Deviation on the Eriksen flanker task for Congruent, Control and Incongruent Stimuli in Experiment 3…………………………………………………………………………….… 85 Table 3. 3 Mean Accuracy and Standard Deviation on Congruent, Control and Incongruent Stimuli in Each Valence Condition of Experiment 3………………………………………………………………………………. 85 Table 3. 4. Mean Eriksen Flanker Task Response Time to Identify the Middle Letter on Congruent, Control and Incongruent Stimuli in Experiment 3………………………………………………………………………… 86 Table 4. 1. Approach/Avoid and Arousal Ratings of the NAPS Picture Norms Used in Experiment 4. The Selection Criteria and the Properties of the Selected Pictures is Reported for Each Motivation Level/Bin…………………………………………………………………………………………………………... 94 Table 4.2. Mean Eriksen Flanker Task Accuracy on Congruent, Control and Incongruent Stimuli in Each Motivation Level Condition in Experiment 4…………………………………………………………………….. 100 Table 5.1. The Between-Subjects Variables in Experiment 5 were the Attention Scope (Broad and Narrow) and Flanker Property Type (Font, Spacing and Constant Visual Angle). The table shows the number of participants in each condition…………………………………………………………………………………….. 107 xiii Table 5. 1. The Flanker Letter Strings used in Experiment 5, Which Differed in Font Size and in Letter Spacing……………………………………………………………………………………………………………….109 Table 6. 1. Valence and Arousal Ratings of CAP-D Pictures Used in Experiment 7: The Picture Selection Criteria and the Properties of the Selected Pictures in the Experiment is Reported for Each Discrete Emotion Bin………………………………………………………………………………………………………….148 Table 6. 2. Mean Eriksen Flanker Task Accuracy on Congruent, Control and Incongruent Stimuli Following each Discrete Emotion Condition in Experiment 7………………………………………………………………155 Table 6. 3. Mean Eriksen Flanker Task Response Time on Congruent, Control and Incongruent Stimuli in Experiment 7………………………………………………………………………………………………….……. 156 xiv List of Figures Figure 1. 1. Examples of Navon letters. The left side shows the letters H and T as components of an outlined L or F; the right side shows the letters L and F as components of an outlined H or T. In the dissertation, I refer to outline letters as global letters and component letters as local letters………………..11 Figure 1. 2. An example of displays used for the Kimchi and Palmer task. The top shows the target; the bottom shows two comparison figures. The bottom left side shows the figure that shares its global shape with the target. The bottom right side shows the figure that shares its local shapes with the target............ 12 Figure 2. 1. One event sequence in Experiment 1: Each event sequence was composed of the picture task which showed 5 pictures to induce affect, followed by the Navon task which used 8 Navon letters to measure attention scope…………………………………………………………………………………………….39 Figure 2. 2. Mean ratings of the pictures in Experiment 1 in each valence level condition: extremely negative, negative, neutral, positive, and extremely positive pictures. Error bars represent 95% confidence intervals………………………………………………………………………………………………………………..42 Figure 2. 3. Mean of median times required for rating pictures in Experiment 1 in each valence level condition: extremely negative, negative, neutral, positive, and extremely positive. Error bars represent 95% confidence intervals…..………………………………………………………………………………………………43 Figure 2. 4. Mean of median response time on Navon task global and local letters in each valence level condition in Experiment 1. Error bars represent 95% confidence intervals..................................................46 Figure 2. 5. Mean of median response time in Experiment 1 on the first four global and local letters in each valence level condition. Error bars represent 95% confidence intervals. ……………………………….…….47 Figure 2. 6. Mean of median response time to global and local letters in the first half of Experiment 1 in each valence level condition. Error bars are 95% confidence intervals………………………………………. 48 xv Figure 2. 7. Mean of median response time to global and local letters in the first half of Experiment 1, for the first four letters following the pictures from each valence level. Error bars are 95% confidence intervals………………………………………………………………………………………………………..………49 Figure 2. 8. An event sequence in Experiment 2: Each event sequence was composed of 1 hand position preparation task to prepare for the picture task, the picture task with 5 pictures to induce a valence state, followed by 1 hand position preparation task to prepare for the Eriksen flanker task, and then the Eriksen flanker task with 6 flanker stimuli to measure attention scope…………………………………………………..57 Figure 2. 9. Mean ratings of the pictures in Experiment 2 for each valence level condition: extremely negative, negative, neutral, positive, and extremely positive. Error bars are 95% confidence intervals……60 Figure 2. 10. Mean of median times required for rating pictures in Experiment 2 in each valence level condition: extremely negative, negative, neutral, positive, and extremely positive. Error bars are 95% confidence intervals. ………………………………………………………………………………………………. 61 Figure 2. 11. Mean of the median Eriksen flanker task response time in Experiment 2 to identify the middle letter on congruent, control and incongruent stimuli in the no spaced condition for valence level condition: extremely negative, negative, neutral, positive, and extremely positive. Error bars represent 95% confidence intervals…………………………………………………………………………………………………..66 Figure 2. 12. Mean of the median Eriksen flanker task response time in Experiment 2 to identify the middle letter on congruent, control and incongruent flanker stimuli in the spaced condition for each valence level condition: extremely negative, negative, neutral, positive, and extremely positive. Error bars represent 95% confidence intervals…………………………………………………………………………………………………67 xvi Figure 3. 1. Mean Russell’s Affect Grid pleasure score for participants in each valence level condition of Experiment 3. Error bars represent 95% confidence intervals. ..................................................................... 79 Figure 3. 2. Mean Russell’s Affect Grid arousal scores for participants in each valence level condition of Experiment 3. Error bars represent 95% confidence intervals. ..................................................................... 80 Figure 3. 3. Mean pleasant BMIS score for the participants in each valence level condition. Error bars represent 95% confidence intervals. ............................................................................................................. 81 Figure 3. 4. Mean arousal BMIS score for the participants in each valence condition. Error bars represent 95% confidence intervals. ............................................................................................................................. 81 Figure 3. 5. Mean picture ratings for each valence level condition in Experiment 3. Error bars represent 95% confidence intervals. ............................................................................................................................. 83 Figure 3. 6. Mean picture rating times for each valence level condition in Experiment 3. Error bars represent 95% confidence intervals. ........................................................................................................................... 102 Figure 3. 1. Mean of median response time required for identifying the middle letter on congruent, control and incongruent flanker stimuli for each valence level condition. Error bars represent 95% confidence intervals………………………………………………………………………………………………………………. 88 Figure 4. 1. Mean picture ratings in the attractive and repulsive question condition for each motivation level condition in Experiment 4. The blue bars show the attractive question condition, and the orange bars show the repulsive question condition. Error bars are 95% confidence intervals…………………………………... 98 Figure 4. 2. Mean picture rating time in each motivation level condition in Experiment 4. The blue bars show the attractive question condition, and the orange bars show the repulsive question condition…………….. 99 xvii Figure 4. 3. Mean of median response time to identify the middle letter on congruent, control and incongruent stimuli in each motivation level condition in Experiment 4. Error bars represent 95% confidence intervals………………………………………………………………………………………………………………102 Figure 5. 1. The Navon letters used in Experiment 5. The left side of the figure shows the H and F are the component letters that make up a large L or a T, which herein are identified as the global letters. The right side of the figure shows the Ls and Ts as components, which herein are called local letters…………...…108 Figure 5. 2. An example of an event sequence in Experiment 5. Each event sequence was composed 80 Navon letters to induce a broad or narrow attention scope followed by 6 flanker stimuli to measure attention scope……………………………...………………………………………………………………………………...112 Figure 5. 3. Mean of median Navon induction task response time and accuracy on global and local letters in the broad and narrow attention induction conditions. The blue bars are response time means, and the orange line shows mean performance accuracy. Error bars represent the 95% confidence intervals…….115 Figure 5. 4. Mean of median Navon Task performance on congruent, control and incongruent stimuli on the first half of Experiment 5. The blue bars are response time, and the orange line is accuracy. Error bars represent the 95% confidence intervals…………………………………………………………………………..116 Figure 5. 5. Mean of median Eriksen flanker task response time and accuracy to identify the middle letter on the first and second set of congruent, control and incongruent stimuli in the first half of Experiment 5. The blue bars are response time, and the orange line is accuracy. Error bars represent the 95% confidence intervals………………………………………………………………………………………………………………118 Figure 5. 6. Mean of median response time in the broad and narrow attention induction conditions on the first set of congruent, control and incongruent stimuli using the combined data from all flanker type conditions in Experiment 5. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals………………..…….119 xviii Figure 5. 7. Mean of the median response time in the broad and narrow attention induction conditions for each flanker property type (font, spacing and visual angle) on congruent, control and incongruent stimuli in Experiment 5. The red bars show data from the broad attention scope condition, and the blue bars show data from the narrow attention scope condition Error bars represent the 95% confidence intervals………120 Figure 5. 8. Mean of median response time on the Eriksen flanker task on the first half of Experiment 5 on congruent, incongruent flanker stimulus types in all flanker variations of font. Each graph shows the specific flanker variation. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals……………………...122 Figure 5. 9. Mean of median response time on the Eriksen flanker task on the first half of Experiment 5 on congruent, incongruent and control flanker stimulus types in all flanker variations of spacing. Each graph shows the specific flanker variation. The red bars show the data from the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals…………………………………………………………………………………………………………….124 Figure 5. 10. Mean of median response time on the Eriksen flanker task on the first half of Experiment 5 on congruent, incongruent and control flanker stimulus types in all flanker variations of constant visual angle. Each graph shows the specific flanker variation. The red bars are the broad attention induction condition, and the blue bars are the narrow attention induction condition. Error bars represent the 95% confidence intervals……………………………………………………………………………………………………………....126 Figure 5. 11. Navon letter types used in Experiment 6. For the local Navon letter, the A and H are the small letters that make up the shape of an X or a V (left). For the global Navon letter, the A and H are the small letters that make up the shape of an X or a V (left)……………………………………………………………129 xix Figure 5. 12. Mean accuracy for global and local trials in the Navon induction task for the broad and narrow attention induction conditions in Experiment 6. The blue bars are response time, and the orange line is accuracy. Error bars represent the 95% confidence intervals………………………………………………….132 Figure 5. 13. Mean of median Eriksen flanker Task response time and accuracy on congruent, control and incongruent stimuli in the first half of Experiment 6. The blue bars are response time, and the orange line is accuracy. Error bars represent the 95% confidence intervals………………………………………………….133 Figure 5. 14. Mean of median Eriksen flanker task response time to identify the middle letter on the congruent, control and incongruent stimuli in the first half of Experiment 6 in the broad and narrow attention induction conditions. The red bars are the broad attention induction condition, and the blue bars are the narrow attention induction condition. Error bars represent the 95% confidence intervals…………………..134 Figure 5. 15. Mean of median Eriksen flanker response time on the congruent, control and incongruent stimuli in the first half of Experiment 6 for the broad and narrow attention scope conditions. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals…………………………………………………………………....136 Figure 5. 16. Mean of median response time on the Eriksen flanker task in the first half of Experiment 6 to identify the middle letter on congruent, incongruent and control stimuli in the broad and narrow attention scope conditions. This figure shows the 32-point font, 0 space flanker variation. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals……………………………………………………………………………………...138 Figure 5. 17. Mean of median response time on the Eriksen flanker task in the first half of Experiment 6 to identify the middle letter on congruent, incongruent and control stimuli in the broad and narrow attention induction conditions. This figure shows the 43-point font, 0 space flanker variation. The red bars are the xx broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals…………………………………………………………………………..139 Figure 5. 18. Mean of median response time on the Eriksen flanker task on the first half of Experiment 6 to identify the middle letter on congruent, incongruent and control stimuli in the broad and narrow attention scope conditions. This figure shows the 26-point font, 1 space flanker variation. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals……………………………………………………………………………………...141 Figure 5. 19. Mean of median response time on the Eriksen flanker task on the first half of Experiment 6 to identify the middle letter on congruent, incongruent and control stimuli in the broad and narrow attention scope conditions. This figure shows the 26-point font, 2 space flanker variation. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals…………………………………………………………………………………..….143 Figure 6. 1. Mean rating for pictures in each discrete emotion condition in Experiment 7: peaceful, sad, and disgust. Error bars are 95% confidence intervals........................................................................................153 Figure 6. 2. Mean response time to rate the pictures in each discrete emotion bin in Experiment 7: peaceful, sad, and disgust. Error bars are 95% confidence intervals……………………………………………….……154 Figure 6. 3. Mean response time to identify the middle letter on congruent, control and incongruent stimuli following pictures from each discrete emotion bin in Experiment 7: peaceful, sad, and disgust. Error bars are 95% confidence intervals………………………………………………………………………………………157 xxi Figure 6. 4. Mean accuracy on global and local letters in the Navon induction task for the broad and narrow attention scope conditions in Experiment 7. The blue bars are response time, and the orange line is accuracy. Error bars represent 95% confidence intervals………………………………………………..……158 Figure 6. 5. Mean accuracy on global and local letters in the Navon induction task for the broad and narrow attention scope conditions in Experiment 7. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent 95% confidence intervals……..160 xxii Acknowledgements I would like to express my gratitude to my supervisor, Dr. Peter Graf, for his guidance throughout my PhD program and preparation of this dissertation. I would also like to thank my committee members, Dr. James Enns and Dr. Jessica Tracy for their input and questions. I also want to thank my family and friends for their unrelenting support throughout this process. I could not have done it without you. Thank you for believing in me. 1 Chapter 1: Research Review and Dissertation Goal Two events could happen: On a walk by Nordstrom, someone gifts you $100, or you step into a mess of dog feces. These events are similar in some ways, for example, by eliciting a strong emotional response and physiological arousal -- increased heart rate and breathing rate, and both are likely to be vividly remembered. But the two events also differ in many ways: One is experienced as positive and the other as negative; the first will make you like Nordstrom and the second may make you loathe it; the gift certificate triggers an approach response while the dog feces on your shoes do the opposite. Emotional events (in my dissertation, I use the term “event” to refer to an external stimulus or situation, or an internal recollection) are complicated because they elicit covert and overt responses that can vastly differ in strength. The strength of the response elicited by an emotional event is likely to depend on its intensity or magnitude. In the example of receiving a gift card, it seems likely that a $100 certificate will trigger a stronger response than a $5 certificate. Emotional events have three properties that may influence covert and overt responses: valence, arousal, and movement propensity. Valence is the extent to which an event is perceived as positive or negative (Russell, 1980; Russell, 1989). Although valence is a continuous variable, it is often used as a categorical variable, for example, when classifying an object as positive (e.g., a playful puppy) or negative (e.g., a large spider). Arousal is the extent to which an emotional event causes physiological activity, such as a change in blood pressure, heart rate and breathing rate (e.g., Magoun, 1952; Steriade, 1996). Arousal also is a continuous variable ranging from low (i.e., being barely awake and alert) to high (i.e., being fully attentive and focused) (e.g., Russell, 1980). The third component of an emotional event is its movement propensity, defined as the strength of the tendency to move towards (i.e., an attractive force) or away (i.e., a repulsive force) from it. 2 Others use the term motivational intensity for this property of emotional events; I use movement propensity to reduce confusion with the theory by the same name (e.g., Gable & Harmon-Jones, 2010b). Movement propensity, a relatively new concept, is a continuous variable, but it is used as a categorical variable, for example, when classifying emotional events as high (e.g., desirable, energizing) or low (e.g., peaceful, calming) in movement propensity (Harmon-Jones & Gable, 2008a). The influence of an emotional event’s valence, arousal and movement propensity depends on the context in which it occurs (e.g., Ekman & O’Sullivan, 1988; Russell & Fehr, 1987). In line with the earlier example, receiving a $100 gift certificate from Nordstrom, when you do not have the money but need new clothes, is likely to have a different effect than receiving a gift certificate on the day you won the lottery. Research evidence for context influences on the perception of emotional events comes from Russell and Fehr (1987) who investigated participants’ interpretation of neutral facial expressions that appeared in the context of more emotionally salient facial expressions. The context was manipulated by presenting two pictures on each trial, each displaying a different facial expression. The results indicated that a neutral face is perceived as sadder when presented together with a happy face and happier when presented together with a sad face. Arousal and valence are related but distinct properties. While arousal ranges from no arousal to high, valence ranges from positive to negative (Russell et al., 1989). Researchers agree that valence and arousal are related to one another, but the specific relationship between them is not agreed upon (Lang, 1994; Yik, 2022). Arousal and movement propensity are related but distinct properties. Arousal can range from no arousal to high arousal (Russell et al., 1989). Movement propensity can range from attraction to no movement, to repulsion (e.g., Gable & Harmon-Jones, 2010b). The two properties are distinct from one another because arousal can occur without a specific movement towards or away. For example, arousal 3 increases independently when caffeine is ingested (Gable et al., 2012). Research by Campbell (2021) found a moderate relationship between movement propensity and arousal. Emotional events that cause affect to occur are complex by virtue of their properties (i.e., valence, arousal, movement propensity), and how they influence perception, cognition, and behaviour. The overall goal of my dissertation research was to investigate one specific question about how emotional events influence cognition: How do emotional events affect the manner in which we allocate attention? 1.1: Attention Affects Processing Emotional events influence all aspects of cognition: attention (e.g., Öhman et al., 2001; Tyng et al., 2017), decision making (e.g., Lerner, 2015), language (Caffi & Janney, 1994), learning (e.g., Tyng et al., 2017), memory (e.g., Anderson et al., 2006), perception (e.g., Stefanucci et al., 2011), and problem-solving (e.g., Jung, et al., 2014). Although some aspects of cognition can and do occur without attention (e.g., Jennings, 2015; Rock et al., 1992), they unfold differently (e.g.., slower, serially) and have different consequences (e.g., they are more likely to be remembered) when carried out under the control of attentional resources. Attention is commonly portrayed in cognitive psychology as a resource or pool of energy which is harnessed for some types of processing and which alters the consequences of processing (Broadbent, 1958; Kahneman, 1973, Moray, 1967; Wickens, 2020). Perceptual, cognitive, and motor processing can vary along an attention-resource continuum. At one end of this continuum is processing, which is said to be non-attentive, in the sense that it occurs even in the absence of any attentional resources; at the other end is processing, which is attentive, in the sense that it occurs only when sufficient attentional resources are available for coordination. The first type of processing is generally called automatic processing while the latter is called controlled processing (because it is controlled by the availability of attentional resources). Automatic processing is fast, can be carried out in parallel with other processing, and leaves no enduring 4 memory traces. By contrast, controlled processing is slow, serial (carried out alone, in the absence of concurrent processing), and it typically results in lasting memory traces (Schneider et al., 1982). Automatic processing is the default or habitual mode; it is the way we process events that occur commonly in daily life (e.g., how we stop automatically at a red light; how we check for phone messages without conscious awareness). By contrast, emotional events are special, relatively uncommon, and for this reason, it is assumed that their processing is more controlled -- more demanding of attentional resources (e.g., Ellis & Ashbrook, 1988; Meinhardt & Pekrun, 2003). Emotional events do not just influence whether attention is allocated or how much attention is allocated to their processing; emotional events change the manner in which attention is allocated. In the context of vision, the allocation of attention has been described with a variety of different labels, such as attention scope, size of attended-region, breadth of attention, attention spotlight or window, and useful-field- of view (e.g., Balz & Hock, 1997; Bulakowski et al., 2007; Chong & Treisman, 2005; Dale & Arnell, 2015; Fang et al., 2018; Goodhew & Edwards, 2016; Heitz & Engle, 2007; Huttermann et al., 2014). Three metaphors are commonly used for describing the difference in processing that occurs inside and outside of the scope of visual attention. The first metaphor portrays attention scope as a spotlight, like the limited area of a stage that is illuminated while all else remains in the dark and invisible. Consistent with this metaphor, it is assumed that attention resources are allocated for processing only to a subset of all stimulation that is potentially available and anything that is not selected for processing is ignored and has no effect on cognition (Derryberry & Tucker, 1994; Posner et al., 1980). A second metaphor portrays attention scope as a zoom lens (Eriksen & St. James, 1986). By this metaphor, attention also is like a spotlight but the size of the spot or the illuminated area can change from small to large (Goodhew, 2020). Consistent with this metaphor, it is assumed that limited attention resources are allocated for processing stimuli in an area, but the larger the illuminated area is, the more superficially stimuli within it are processed 5 (because limited resources need to be used for processing a larger set of stimuli). A third metaphor is provided by the gradient model which compares attention scope to a response gradient (Downing, 1988; Labarge & Brown, 1989; Mangunn & Hillyard, 1988). Consistent with this metaphor, most processing resources are allocated where attention is focused or fixated, and gradually fewer resources are allocated as you move away from this focus. 1.2. Theoretical Claims About Emotional Events and Attention Scope My dissertation builds on the general idea that processing of available environmental stimulation occurs differently when it is part of a neutral event versus an emotional event. In general, in the context of a neutral event, processing is handled by the default system and is fast and automatic, whereas in the context of an emotional event, processing is attentive and controlled. A number of theoretical accounts give further insight into this switch from default to controlled processing. 1.2.1: Affect-as-Information Hypothesis The Affect-as-Information hypothesis explains the relationship between emotional events and attention scope by asserting that feelings—defined as subjective affective/cognitive states—are evoked by emotional events and they function as sources of information (Gasper & Clore, 2002). Feelings convey information about arousal and valence, with arousal signaling the importance/pertinence or immediate urgency of an event (e.g., do I need to pay attention to this event) and valence informing us about the value of the event (e.g., is it positive/good or negative/bad) (Clore, Gasper & Gavin, 2001). It is assumed that an event that is benign and safe evokes positive feelings tends to elicit curiosity and exploration, resulting in attention allocation to the forest rather than the trees. By contrast, an event that is threatening and dangerous, seeking out the source of the danger, and attention is selectively and narrowly allocated to its processing. The hypothesis states that all positive feelings (e.g., happiness, joy) broaden attention scope 6 by signaling that an event is benign and safe, whereas all negative feelings (e.g., fear, anxiety) narrow attention scope by signaling that an event is dangerous and potentially harmful (Gasper & Clore, 2002). 1.2.2: Broaden-and-Build Theory The Broaden-and-Build theory provides a related but distinctly different explanation for how emotional events influence the scope of visual attention. The theory posits that each emotional event is associated with distinct thought-action repertoires which are automatically activated or primed (Fredrickson, 2001; 2004). Positive and negative emotional events activate different thought-action repertoires. Thought- action repertoires activated by positive emotional events (e.g., explore, integrate, play) broaden thoughts and actions to all parts of the current environment compared to a neutral event; thought-action repertoires activated by negative emotional events (e.g., attack, escape) focus thoughts and actions on their specific parts in order to deal with potential threats and to enhance the chance of survival (e.g., fight-or-flight response). The Broaden-and-Build theory is often tied to evolution (e.g., Easterbrook, 1959). The distinct thought-action repertoires associated with positive, and negative events are assumed to be adaptations due to our evolutionary history. The thought-action repertoires associated with positive events are for building resources, and the thought-action repertoires associated with negative events keep us safe from harm (Fredrickson, 2001). 1.2.3: Motivational Intensity Theory The Motivational Intensity theory provides yet another explanation for the relationship between emotional events and the scope of visual attention, but it focuses on a different property of emotional events: its power to make us move. An emotional event may have focal elements that induces us to move towards them (they attract us) (e.g., water on a hot day) or away from them (they repulse us) (e.g., a bug in 7 your salad), whereas emotionally neutral events have neither the power to attract nor to repulse (e.g., seeing a sunset). According to motivational intensity theory, this property of emotional events is called movement propensity and is defined as the strength of the tendency for us to move towards or away from them (Gable & Harmon-Jones, 2008a; 2010b). Movement propensity can be high (e.g., attraction, repulsion) or low (neutral, peaceful). Emotional events with low movement propensity broaden attention scope and we see the forest, whereas emotional events with high movement propensity narrow it and we focus on specific trees (e.g., Gable & Harmon-Jones, 2008a; 2010a; 2011). Movement propensity and valence are partially overlapping but distinctly different properties of emotional events. Positive emotional events can be high or low in movement propensity. An example of a positive emotional event high in movement propensity is one that is desirable (e.g., cookies). An example of a positive emotional event that is low in movement propensity is one that is peaceful (e.g., a beautiful landscape). Negative emotional events also can be high or low in movement propensity. An example of a negative emotional event high in movement propensity is one that is feared (e.g., a spider). An example of a negative emotional event low in movement propensity is one that makes us sad (e.g., the death of a loved one). 1.2.4: Summary: Differences Between the Theories All theories agree that emotional events trigger intermediary states -- covert and overt responses -- that change the scope of attention. For the Affect-as-Information hypothesis (e.g., Gasper & Clore, 2001), the intermediary states are feelings which provide information, whereas for the Broaden-and-Build theory, the intermediary between events and attention scope are thought-action repertoires (Fredrickson, 2001; 2004), and for Motivational Intensity theory, the intermediary is movement propensities – attractions or repulsions. The theories differ in terms of the property of emotional events that is responsible for the 8 change in attention scope. Affect-as-Information hypothesis and the Broaden-and-Build are similar because they both focus on the valence of emotional events, and stipulate that positive events broaden attention while negative events narrow it [e.g., (Gasper & Clore, 2002; Fredrickson, 2001)]. These theories differ from Motivational Intensity, which focuses on movement propensity and stipulates that many emotional events narrow attention. (Gable & Harmon-Jones, 2008a). The claim that positive valence states broaden the scope of attention and negative valence states narrow it is ubiquitous. The claim that positive valence states broaden attention scope was made by Isen, approximately 30 years ago (Estrada et al., 1997; Isen et al., 1987; Isen, 2000, Ashby, 1999). The claim that negative valence states narrow attention scope was made by Easterbrook (1959). Intuitively, these claims make sense. Negative valence poses a threat (e.g., a predator is chasing us), and our attention automatically tunes to the threat to increase the chances of survival. Positive valence, however, poses no threat, and therefore attention remains broad to attend to our overall environment. Evidence for these claims provides the bases for psychological phenomena like the weapon focus effect, where participants focus on the weapon used in a crime (e.g., a gun) to the detriment of other details in the crime scene (e.g., the perpetrator's description) (Loftus, 1979). My dissertation was primarily guided by the Affect-as-Information hypothesis and the Broaden-and- Build theory (e.g., Fredrickson, 2001; Gasper & Clore, 2002). I used Motivational Intensity theory primarily as a refinement of the valence theories, to specifically examine the influence of attraction and repulsion on the scope of attention (e.g., Gable & Harmon-Jones, 2010b). 1.3. Research on the Relationship Between Emotional Events and Attention Scope This review of research on the relationship between emotional events and their effects on the scope of attention has two parts. Part 1 describes the tasks commonly used for investigating the scope of 9 attention, and Part 2 summarizes what is known about emotional events and their influence on the scope of visual attention. 1.3.1: Attention Scope Task Types A broad range of tasks have been created for measuring the scope of visual attention, but only three are commonly used for investigating how attention scope is influenced by emotional events. These three tasks are the Eriksen Flanker task (Eriksen & Eriksen, 1974), the Navon task (Navon, 1977), and the Kimchi and Palmer Task (Kimchi & Palmer, 1982). The Eriksen flanker task (Eriksen & Eriksen, 1974) makes use of visual displays that are strings of letters (e.g., Rowe et al., 2007) or arrows (e.g., Ridderinkhof et al., 2021) and participants are required to identify the middle letter or the direction of the middle arrow in the string. In Table 1.1, the left side shows an example with letters and the right side shows an example with arrows. The table also shows that each stimulus takes three distinct types: congruent (e.g., LLLLL), control (e.g., XXLXX); and incongruent (e.g., TTLTT). If attention scope is broad, the processing system will pick up a larger proportion of the display and process the middle and surrounding stimuli, and therefore, when presented with incongruent stimuli and needing to decide “Is the middle letter an L or T?”, processing is slower, and more errors occur. If attention scope is narrow, the processing system will pick up a smaller proportion of the display – perhaps only the middle stimulus, and therefore, the system is able to decide quickly and easily, even with incongruent stimuli. 10 Table 1. 2 An Example of the Stimuli used for the Eriksen Flanker Task. The left column shows the three types of flanker stimuli (i.e., congruent, control, and incongruent). The middle column gives an example with letters (LLLLL; LLXLL; LLTLL) and the right column gives an example with arrows. Flanker Stimuli Type Letters Arrows Congruent L L L L L < < < < < Control X X L X X 0 0 < 0 0 Incongruent T T L T T < < > < < The Navon task (Navon, 1977; 1981) also makes use of visual displays, but they are like those shown in Figure 1.1. On the Navon task, participants are required to decide whether a specified letter is present in each display (e.g., “Does the display include an H or a T?” or “Is there an H or a T?”). The specified letter can be the shape of the outline or the components that make up the outline. In Figure 1.1, the left side shows the letters H and T as components of an L or an F; the right side shows the letters L and F as components of an outlined H or T. Participants are asked to respond to as quickly and accurately as possible. It is assumed that if attention scope is broad, the processing system will pick up a larger proportion of the display and focus on the outline, rather than the components, which leads to faster responses to the outline letters. If attention scope is narrow, the processing system will pick up only a smaller proportion of the display and thus process the components rather than the outline, leading to faster responses to the component letters. 11 Figure 1. 1. Examples of Navon letters. The left side shows the letters H and T as components of an outlined L or F; the right side shows the letters L and F as components of an outlined H or T. In the dissertation, I refer to outline letters as global letters and component letters as local letters. The Kimchi and Palmer task (Kimchi & Palmer, 1982) uses visual displays like those in Figure 1.2, and participants are required to make comparisons between specific display parts. In Figure 1.2, the part on the top is called the target, and the parts below are called the comparison displays. Each part of the figure is defined by local elements that have a specific shape (e.g., square, triangle) and the elements are arranged to form a global shape (e.g., a triangle, a square). In Figure 1.2, the target has the same global shape as the comparison display on the lower left, and it has the same local elements as the comparison display on the lower right. When the Kimchi and Palmer task is used for assessing the scope of visual attention, participants are required to decide “which of the comparison displays is more like the target?” It is assumed that if attention scope is broad, the processing system will focus on the figure and process the global shape, and participants choose the visual display on the lower left. If attention scope is narrow, the processing system will focus on the local elements of the display and process the local shapes, and participants choose the visual display on the lower right. 12 Figure 1. 2. An example of displays used for the Kimchi and Palmer task. The top shows the target; the bottom shows two comparison figures. The bottom left side shows the figure that shares its global shape with the target. The bottom right side shows the figure that shares its local shapes with the target. 1.3.2. Review of Research Relevant to Each Attention Scope Task The purpose of this section is to summarize what is currently known from empirical research in psychology about how emotional events affect the scope of visual attention. Researchers have used a variety of different methods to induce specific affective states or affective responses in participants. For example, to induce desired valence states, researchers have exposed participants to positive and negative pictures (e.g., Tidikis et al., 2017; Finucane et al., 2010; Moriya & Nittono, 2011), or positive and negative films (e.g., Fredrickson & Branigan, 2005), or they asked them to retrieve positive (i.e., happy) and negative (i.e., sad) memories (e.g., Gasper & Clore, 2002), and asked them listen to positive (i.e., happy) and negative (i.e., sad) music (e.g., Rowe et al., 2007). To induce distinct movement propensity states, researchers have exposed participants to emotional events like 13 attractive and repulsive pictures (e.g., Gable & Harmon-Jones, 2008a), or to amusing and attractive films (Gable & Harmon-Jones, 2008a; Experiment 1). Researchers may have chosen different emotional events over others because of convenience or assumptions that certain emotional events induce affect more effectively. It is likely that some researchers chose pictures to induce affect in participants, for example, because they are convenient. Standardized, and normed databases with many stimuli are easily accessible. It is likely that some researchers chose films to induce affect in participants because it has long been assumed that films are more effective at inducing affect in participants than other types of emotional events (e.g., Westermann et al., 1996). The use of different methods to induce affect in participants makes comparisons among experiments difficult for four potential reasons. One reason comparisons are difficult is that experiments have different numbers of emotional events [e.g., 32 pictures (Gable & Harmon-Jones, 2008a); one, two or three films (e.g., Fredrickson & Branigan, 2005); one song (Rowe et al., 2007)]. A second reason comparisons are difficult is that experiments vary the number of times each emotional event is presented to participants [e.g., twice (Martin & Kerns, 2011); once (Finucane, 2011)]. A third reason is that in different experiments emotional events are displayed for different durations [e.g., 6 seconds (Gable & Harmon- Jones, 2008a); less than 5 minutes (Finucane, 2011); 9 minutes (Gasper & Clore, 2002]. A fourth reason is that some experiments used emotional events with different pedigrees [(e.g., internet pictures (Noguchi & Tomoike, 2016, Wang et al., 2018), while others use independently standardized and normed emotional events [e.g., IAPS pictures (Tidkis et al., 2017)]. These variations among experiments are likely to influence the results of the experiments and the potential to find an influence on attention scope. Research has compared the scope of visual attention under the influence of three valence states-- positive, neutral, and negative, and valence states have been manipulated both within subjects (e.g., Rowe et al., 2007) and between subjects (e.g., Fredrickson & Branigan, 2005), with each design used about 14 equally often. Research with all three valence states is theoretically most interesting because it speaks to both, the extent of broadening and narrowing of attention scope. Research on the influence of movement propensity on attention scope also has compared three conditions -- high attraction, low/no attraction/repulsion, and high repulsion, and these conditions also have been examined in between subjects (e.g., Gable & Harmon-Jones, 2008a) and within-subject studies (e.g., Threadgill & Gable, 2019). Research with all three movement propensity states allows researchers to examine if the extent of attention scope narrowing is the same for attraction and repulsion, compared to a low/no attraction/repulsion event. More research has compared only two movement propensity states rather than all three. The review of research which follows is organized into two parts: Part 1 is about valence research and Part 2 is about movement propensity research. Within each of these parts, the first section summarizes research on all three properties of emotional events (i.e., three levels of valence; three levels of movement propensity). The second section summarizes research that compared only two properties of emotional events (i.e., two levels of valence; two levels of movement propensity). Within the research examining two valence dimensions, the review includes a segment on the results from studies that compared positive to neutral valence states, negative relative to neutral valence states, and then positive to negative valence states. Within each of these segments, I first cover research that used the Eriksen flanker task (Eriksen & Eriksen, 1974) to measure attention scope, followed by the Navon task (Navon, 1977) and then the Kimchi and Palmer task (Kimchi & Palmer, 1982), mirroring the historical order in which these tasks were developed. 1.3.2.1: Experiments with Positive, Neutral and Negative Valence States A total of ten experiments on how valence states influence the scope of attention have compared all three valence states (i.e., positive, negative, and neutral) and they have used methods that differ in several 15 critical properties: the number of participants; the design (within or between subjects); the type of event used to induce a valence state; the method used for measuring attention scope; etc., as described earlier in this chapter. All the experiments used undergraduate students as participants, but they differed substantially in the number of participants, with a low of as few as 24 (e.g., Rowe et al., 2007) and a high of as many as 270 participants (Tidkis et al., 2017). The valence of the emotional events was manipulated between subjects in seven experiments (Finucane et al., 2010; Fredrickson & Branigan, 2005; Gasper & Clore, 2002; Gasper, 2004; Jäger & Rüsseler, 2016; Johnson et al., 2010), and within subjects in four (Bryneel et al., 2013, Jiang et al., 2011; Moriya & Nittono, 2011; Rowe et al., 2007). Emotional events were instantiated with pictures (Moriya & Nittono, 2011; Tidkis et al., 2017), with a film (Bruyneel et al., 2013, Experiment 3; Fredrickson & Branigan, 2005; Jäger & Rüsseler, 2016; Johnson et al., 2010), by retrieving a memory (Gasper & Clore, 2002; Gasper, 2004), by listening to music (Rowe et al., 2007), or by listening to music while retrieving a memory (Jiang et al., 2011). The number of emotional events administered to participants also differed greatly from one song for each valence state (Rowe et al., 2007) versus 65 pictures for each valence state in an experiment by Tidkis et al., (2017). After inducing valence states with music (Rowe et al., 2007), pictures (Finucane et al., 2010; Moriya & Nittono, 2011) and films (Bruyneel et al., 2013; Experiment 3), four experiments used the Eriksen flanker task (Eriksen & Eriksen, 1974) for measuring the visual attention scope. After inducing valence states by retrieving a memory (Gasper et al., 2004; Gasper & Clore, 2002), or by viewing pictures (Tidkis., et al., 2017) and films (Fredrickson & Branigan, 2005; Jäger & Rüsseler, 2016; Johnson et al., 2010), six experiments used the Kimchi Palmer task (Kimchi & Palmer, 1982) (e.g., Gasper & Clore, 2002), and none used the Navon task (Navon, 1977). In view of the many method differences in previous studies, the findings summarized below must be handled with caution. 16 Using the Eriksen flanker task (Eriksen & Eriksen, 1974), Rowe et al. (2007) used music to induce positive and negative valence states and a neutral valence state, participants retrieved basic facts from memory. The results showed that participants responded slower to incongruent stimuli after listening to positive (i.e., happy) music than after listening to negative (i.e., sad) music, or after retrieving basic facts from memory. The results suggest that the positive valence states broaden attention scope. Experiments by other researchers, however, that used the same task for assessing the scope of attention, failed to replicate this outcome; they found no evidence supporting the expectations that positive valence states broaden the scope of attention and that negative valence states narrow it (Bruyneel., 2013, Experiment 3; Finucane et al., 2010; Moriya & Nittono, 2011). Using the Kimchi Palmer task for measuring the scope of attention (Kimchi & Palmer, 1982), Fredrickson and Branigan (2005) used films to induce distinct emotions in participants that either elicited positive (e.g., happiness, serenity), neutral (e.g., contentment) or negative valence states (e.g., anger, anxiety, sadness). Results showed that participants made more global than local figure choices after positive films, but not after neutral or negative films, which suggests that attention scope broadened following positive valence states. Tidkis et al. (2017) used pictures for inducing positive and negative valence states and did not replicate these results. Results showed no influence of positive versus negative valence states, overall. Experiments by Gasper (2004) and Gasper & Clore (2002), however, asked participants to retrieve positive (e.g., happy), neutral, or negative (i.e., sad) memories and the same task was used for assessing the scope of attention, revealed no evidence that positive valence states broadened the scope of attention, but found evidence that negative valence states narrowed it. Gasper and Clore (2002) and Gasper (2004) showed that participants made more local than global figure choices after retrieving negative memories, but not after retrieving neutral or positive memories. 17 The Affect-as-Information hypothesis (e.g., Gasper & Clore, 2002) and the Broaden-and-Build (e.g., Fredrickson, 2004) predict that positive valence states should broaden the scope of attention and negative valence states should narrow it. The summarized results of experiments with positive, neutral, and negative valence states do not provide clear support for these expectations. Some research suggests that only positive valence states broaden attention scope (e.g., Fredrickson & Branigan, 2005) while other research suggests that only negative valence states narrow attention scope (e.g., Gasper & Clore, 2002). The summarized findings show that evidence for both expectations have not been found within the same experiment. Two reasons for these inconsistent results stand out as possibilities. One reason different results may have occurred is because of the insufficient statistical power of experiments. Experiments with positive, neutral, and negative events may require large sample sizes of participants to be able to generalize findings across different groups. Similarly, they may require large samples of stimuli to be able to generalize findings to other types. A second reason for inconsistent results may be because of differences in research design. The valance of events is sometimes manipulated within subjects (e.g., Bruyneel et al., 2013, Experiment 3; Moriya & Nittono, 2011) and if valence produces carry-over effects, they may be confounded in the results. Exposure to one emotional event may affect how a subsequent emotional event is experienced. For example, a negative event (e.g., a person crying) may be more negative when it is preceded by another negative event (e.g., an injured person). If a negative event is preceded by a positive event (e.g., a smiling couple), it may be less negative. Carryover effects may occur between emotional events. A related research area has explored this possibility (Lerner et al., 2004). Three experiments that have examined positive, neutral, and negative valence states are particularly strong because they used a large number of participants in their experiment and used effective standardized stimuli (Fredrickson & Branigan, 2005; Johnson et al., 2010; Tidkis, 2017). If I consider the 18 results of these experiments alone it would seem to suggest that positive valence states broaden attention scope, but negative valence starts do not narrow it. 1.3.2.2: Experiments with Positive and Neutral Valence States A total of three experiments have focused on how valence states affect the scope of attention and compared positive and neutral valence states. These experiments differ from each other in as many different ways as the experiments that compared positive, neutral and negative valence states. Using the Eriksen flanker task (Eriksen & Eriksen, 1974), Martin and Kerns (2011; Experiment 2) induced valence states with positive and neutral films and showed no difference in response time to congruent, control or incongruent stimuli. These results were replicated in two other experiments. In one experiment, positive valence states were induced with positive music and neutral states were induced by asking participants to retrieve basic facts from memory (Bruyneel et al., 2013; Experiment 2). In another experiment, participants were given false positive feedback about task performance in the positive condition or were given no feedback in the neutral condition (Bruyneel et al., 2013). These results showed positive valence states do not broaden attention scope and negative valence states do not narrow it. Only a few experiments have examined the influence of positive and neutral valence states on attention scope, and they have shown no evidence of changes in attention scope. It may be that strong positive affect is difficult to induce; after all, looking at a picture of a sunset at the beach is different from walking on the beach fully immersed in the experience. A previous meta-analysis by Westermann et al. (1996) examined the effectiveness of a variety of different affect induction methods and found that overall, the effect sizes associated with induced positive valence states were smaller than those associated with induced negative valence states. 1.3.2.3: Experiments with Neutral and Negative Valence States 19 A total of seven experiments on how valence states affect the scope of attention have compared neutral and negative valence states. Using the Eriksen flanker task (Eriksen & Eriksen, 1974), Finucane (2011) showed that participants responded faster to incongruent stimuli after negative films (i.e., anger and fear) than after a neutral film, which was interpreted as evidence that the negative valence states narrowed attention scope. Bellaera and von Mühlenen, (2017; Experiment 1) replicated these results using the same attention scope task when valence states were induced with negative (i.e., sad films showing car accidents) and neutral films (i.e., cars driving without accidents), each with corresponding background music. Using the Navon task (Navon, 1977), Gable and Harmon-Jones (2010b) showed that participants responded faster to global than local letters following negative pictures (i.e., sad), compared to after neutral pictures, which suggests that negative valence states broadened attention scope. Two experiments did not replicate these response time results. Experiments by von Mühlenen et al. (2018) used sad and neutral pictures (Experiment 1) and sad and neutral films with corresponding background music (Experiment 2), and they found no difference in participants' response time to global and local letters. The results of both experiments, however, showed that participants made fewer errors on global letters, following negative valence states than neutral valence states. Fewer errors on global letters suggest that attention scope broadened following negative valence states. Other experiments by Bellaera and von Mühlenen (2019), Von Mühlenen (2019; Experiment 2) and Wang et al. (2018), however, did not replicate these results, and found no influence of neutral and negative valence states on attention scope. The Affect-as-Information hypothesis (e.g., Gasper & Clore, 2002) and the Broaden-and-Build (e.g., Fredrickson, 2004) predict that negative emotional events narrow the scope of attention. The summarized results of experiments with neutral, and negative events do not provide clear support for the expectation. A potential reason for these inconsistent results may be that affect induction methods used are more effective 20 for some participants, or some participants experience a greater intensity or amount of affect overall than others. Evidence for this assertion comes from a review by Larsen and Diener (1987) which suggests that the intensity with which participants experience affect varies among individuals, with some with some who experience intense affect and others do not. 1.3.2.4: Experiments with Positive and Negative Valence States A total of five experiments on how emotional events affect the scope of attention have compared positive and negative events. Using the Eriksen flanker task (Eriksen & Eriksen, 1974), research suggests that when positive and negative valence states are induced in participants, attention scope does not change. Phaf (2015) induced valence states by asking participants to write about a positive or negative life event while listening to corresponding background music, and the results showed no difference in response time to congruent and incongruent stimuli following positive and negative valence states. These results were replicated when participants were asked to write about a positive and negative life event (Huntsinger et al., 2010; Experiment 1), read a positive or negative story (Huntsinger, Experiment 2; 2012), or watch negative (i.e., anxious) or positive (i.e., happy) films (Wegbreit et al., 2014). The results of research that compare positive and negative valence states are difficult to interpret. A change in attention scope that is found can only be interpreted as a difference between positive and negative valence states, and researchers cannot determine the extent of broadened and/or narrowed attention from each, which is possible when a neutral valence state is included. 1.3.2.5: Conclusions About Research Examining Valence States Based on the current research, it is not clear whether positive valence states broaden attention scope, or if negative valence states narrow it. Some researchers find evidence that is partially consistent with 21 theory (e.g., Rowe et al., 2007), while others find no evidence (e.g., Martin & Kerns, 2011). No research has found evidence that positive valence states broaden attention scope and negative valence states narrow attention scope within the same experiment. 1.3.3: The Influence of Movement Propensity on Attention Scope This section reviews the research on the influence of movement propensity on attention scope. Note that movement propensity research uses a variety of different types of labels to denote different movement propensity states. In the research reviewed below, I make note of each of the specific labels, and I use the labels attraction, neutral and repulsion. Movement propensity can be toward (i.e., attraction), neutral (i.e., no movement), or away from (i.e., repulsion). In research, movement propensity is most often compared to a neutral or no-movement state, but sometimes it is compared to a moderate state (i.e., slight attraction). Therefore, this section is divided into five main parts: experiments with attractive and neutral and repulsive states; experiments with attractive, moderate, and neutral states; experiments with attractive and moderate states; experiments with attractive and neutral states; and experiments with neutral and repulsive states. Little research has focused on repulsive states, perhaps because Motivational Intensity theory (Gable & Harmon-Jones, 2010b), the Broaden-and-Build theory (e.g., Fredrickson, 2004) and the Affect-as- Information hypothesis (e.g., Gasper & Clore, 2002) predict a similar pattern of results. All theories predict that attention scope narrows for repulsive events, but for different reasons. Motivational Intensity theory postulates that attention scope narrows because repulsion is associated with a movement away from a target object, and that this narrows attention. The Broaden-and-Build theory and the Affect-as-Information hypothesis predict that attention scope narrows because repulsion is a negative valence state. 1.3.3.1: Experiments with Attractive, Neutral and Repulsive Movement Propensity States 22 Two experiments have explored the influence of attractive, neutral, and repulsive movement propensity states on attention scope. They used attractive, neutral, and repulsive events (Álvarez-San Millán et al., 2022; Gable et al., 2015), and they differed in terms of the number of participants and the type of affect induced in participants. Experiments used undergraduates as participants, with a small sample of 49 participants in Gable et al., (2015) and 246 participants in a study by Álvarez-San Millán et al., (2022). Both experiments used pictures to induce movement propensity states in participants and each experiment used a similar number of pictures to induce movement propensity states in participants with 30 of each in Álvarez-San Millán et al., (2022) and 32 of each type in Gable et al. (2015). To induce different movement propensity states in participants, Álvarez-San Millán et al. (2022) used cute (attractive), neutral pictures (no movement) and threatening (repulsive) pictures. Gable et al. (2015) compared desirable (attractive) neutral (no movement) and angry (repulsive) pictures and both experiments used the Navon task (Navon, 1977) to measure attention scope. Gable et al. (2015) showed that participants were faster to respond to local letters after attractive and repulsive pictures compared to neutral pictures. Álvarez-San Millán et al. (2022) replicated these results. The results of the experiments suggest that relative to neutral events, attractive and repulsive events narrowed attention to a similar extent. 1.3.3.2: Experiments with Attractive, Moderate and Neutral Movement Propensity States Using a Navon task (Navon, 1977), one experiment, by Domachowska et al., (2016, Experiment 2) used desirable (attractive), landscape (moderate) and neutral (no movement) pictures to induce movement propensity states. The results of this experiment showed that the response time on global letters was slower after desirable than neutral pictures, indicating that attention scope narrowed for attractive pictures than neutral pictures. Participants were faster to respond to local and global letters following after desirable 23 pictures and landscape pictures, which suggests that a moderate movement propensity state narrowed attention to a similar extent as an attractive movement propensity state. Motivational Intensity theory predicts that attention scope narrows to a greater extent following attractive events than moderate events because the latter is associated with a greater amount of movement propensity. The results of Domachowska et al. (2016), however, showed no difference in attention scope between moderate and attractive states. One reason for this may be because the self-reported affect from participants following attractive and moderate states was higher than neutral events, but there was no difference between the two. Participants did not differentiate between them, which may be why attention scope narrowed following both attractive and moderate movement propensity states. 1.3.3.3: Experiments with Attractive and Moderate Movement Propensity States Using the Kimchi Palmer task (Kimchi & Palmer, 1982), one experiment by Gable and Harmon-Jones (2008a; Experiment 1) used films to induce attractive (i.e., desire) and moderate (i.e., amusement) movement propensity states. Results showed that participants made more global figure choices following amusement films than desire films. The results suggest that attention scope changed, however, it is not clear whether attention scope broadened after amusement films or narrowed after desire films because a neutral condition was not included. 1.3.3.4: Experiments with Attractive and Neutral Movement Propensity States A total of thirteen experiments on how emotional events influence the scope of attention have compared attractive and neutral events. Using the Navon task (Navon, 1977), one experiment by Gable and Harmon-Jones (2008a; Experiment 1) induced attractive and neutral movement propensity states in participants with desirable pictures (e.g., chocolate cake, ice cream) and neutral pictures, respectively. Results showed that after desirable pictures 24 participants were faster to respond to local letters than global letters, compared to after neutral pictures; after desirable pictures participants were slower to respond to global letters than they were after neutral pictures. These results suggest that attractive movement propensity states narrowed attention scope. These results were replicated in seven experiments that also used pictures (Gable & Harmon-Jones, 2008a; Experiment 2; Experiment 3; Experiment 4; Gable & Harmon-Jones, 2011, Experiment 1; Jeurgenson & Demaree, 2015; Nittono et al., 2012; Noguchi & Tomoike, 2016). The results were further replicated in two experiments which found that participants' attention scope narrowed to an even greater extent than those who viewed the pictures when they expected to consume the desserts (Gable & Harmon- Jones, 2008a; Experiment 3; Jeurgenson & Demaree, 2015). One experiment, that used similar materials, failed to replicate the results of the seven other experiments. Domachowska et al. (2016) found that participants were slower on global letters than local letters following attractive pictures, and after neutral pictures they were faster on global letters than local letters. Participants were not faster to respond to local letters after the dessert pictures, however, but the slowdown on global letters following attractive pictures may also suggest that attention scope narrowed to some extent. This is because participants have an overall tendency to respond faster to global than local letters (Navon, 1981), which occurred following neutral pictures, but was not present following dessert pictures. The results, however, are not clear because the tendency to respond faster to global than local letters does not always occur (Miller, 1981). 1.3.3.5: Experiments with Neutral and Repulsive Movement Propensity States Using the Navon task, Gable and Harmon-Jones (2010b; Experiment 2) induced repulsive states with repulsive pictures and neutral states with pictures of rocks. Results showed that participants were faster to respond to local letters than global letters after repulsive pictures and faster to respond to global 25 than local letters following neutral pictures. The results suggest that repulsive movement propensity states narrow attention scope. These results are consistent with the Motivational Intensity theory (e.g., Gable & Harmon-Jones, 2010b), the Broaden-and-Build theory (e.g., Fredrickson, 2004) and the Affect-as-Information hypothesis (e.g., Gasper & Clore, 2002). All theories predict that attention scope narrows following repulsive states. 1.3.6: Conclusions About Research Examining Movement Propensity States Based on the current research examining movement propensity states, the evidence seems to mostly support the prediction that attractive and repulsive states narrow attention, relative to a neutral state. The relative consistency across results may have occurred because much of the research used the same type of emotional events (e.g., pictures) to induce movement propensity states in participants. 1.4: Methodological Issues To investigate how emotional events affect the scope of visual attention, it was necessary for me to operationalize valence states, movement propensity states, and attention scope. This section describes several considerations which led me to use carefully normed pictures from large databases (e.g., IAPS, Lang et al., 2008a) for the purpose of inducing different valence states and different movement propensity states in participants, as well as to use the Navon task (Navon, 1977) and the Eriksen flanker task (Eriksen & Eriksen, 1974) for the purpose of measuring the scope of visual attention. Many different options have been used for inducing affect in participants, like viewing attractive pictures or films, retrieving positive or negative memories, listening to happy or sad music, reading positive or negative stories. It is possible that not all stimuli are equally effective for inducing affect. Evidence for this assertion comes from meta-analyses and experimental research (e.g., Lench et al., 2011; Westermann et al., 1996). One meta-analysis by Lench et al. (2011) found that pictures showed the largest effect size and 26 was the most effective method for eliciting affect in participants when compared to films, music, memory retrieval, reading stories, or situational manipulations, among others (see Lench et al., 2011). An experiment by Uhrig et al. (2016) directly compared the effectiveness of pictures and films to elicit affect in participants. In the experiment, participants were presented with pictures and films and then they were asked to report the effectiveness of each affect induction via self-report. The results showed that pictures were more effective than films at inducing affect in participants. Using pictures to induce valence states and movement propensity states is beneficial for two reasons. One reason is convenience: there are a variety of different standardized databases available for researchers. IAPS is the most common affective picture databases that provide standardized valence and arousal norms, for each picture (Lang et al., 2008). The standardized norms across participants to provide an estimate of how participants will respond to each picture (Lench et al., 2011). For example, using pictures from IAPS allows researchers to choose pictures with different valence levels (i.e., positive, neutral, and negative) while at the same time controlling for arousal levels. A second reason pictures are beneficial to use is that they are effective at inducing affect in participants, even when presented for short durations [e.g., presented for 6 seconds, (Uhrig et al., 2016)]. For these reasons, in my dissertation, I chose to use pictures from standardized affective picture databases to induce affect in participants. It is necessary for participants to attend to the affect induction task. It is most common in research for participants to passively view pictures (e.g., Gable & Harmon-Jones, 2008a), however, in my research I wanted to ensure participants were actively engaged with each picture. To ensure engagement, I required participants to complete a task that required them to examine each picture to determine how they felt about each one before they could proceed to the next picture. With this task, however, picture ratings should not be confused with the affective state experienced by participants. 27 It is necessary to ensure that emotional events are presented long enough to produce an affective change in participants. In affect research pictures are commonly presented one at a time for 6 seconds at a time (e.g., Codispoti et al., 2006; Vrana et al., 1988) or 3 pictures of the same type are presented for 2 seconds each (Godinho et al., 2006). To ensure that each picture was presented for an appropriate amount of time to effectively induce affect in my participants, the timing of the pictures is slightly longer than in previous research. In my experiments I presented a series of pictures from the same valence state (e.g., 5 positive pictures) or movement propensity type (e.g., 5 attractive pictures), each of which appeared until the participant responded to it. Therefore, each sequence of pictures appeared for approximately 10 seconds. I used the Eriksen flanker task (Eriksen & Eriksen, 1974) and Navon task (Navon, 1977) in my dissertation research for four reasons. For one, these tasks are commonly used and are considered valid and reliable measures of attention scope (e.g., Eriksen & Yeh, 1985; Goodhew & Plummer, 2019). A second reason is that the Eriksen flanker task and Navon task measure both accuracy and response time, which provides more indices for tracking the influence of affect on attention scope. Research has shown the influence of affect on attention scope may be present in the accuracy data but not the response time data (e.g., Domachowska et al., 2016). A third reason I decided to use the Eriksen flanker task and Navon task is researchers can provide participants with more trials to measure attention scope than is typically possible with the Kimchi and Palmer task. The Kimchi Palmer task often only has a total 24 trials, (8 of which are the critical trials; 16 are filler). Use of the Navon task and Eriksen flanker task allowed me to implement a large number of trials within each experimental session to measure attention scope. A fourth reason I used the Eriksen flanker task and Navon task is that it allowed me to develop a paradigm that could measure changes in attention scope with response time and accuracy, over time, over a specific set of trials. 28 A potential criticism of previous research is that it is most common to measure attention scope one time after emotional events (e.g., Rowe et al., 2007) or after one trial (Gable & Harmon-Jones, 2008a; 2010b). Often the time between the emotional events and the measurement of attention scope is unknown (e.g., Bruyneel et al., 2013; Rowe et al., 2007), which may be problematic because the effects of induced affect may have dissipated by the time participants' attention scope is measured. In my dissertation, the experiments were implemented in a paradigm where sequences of 6 to 8 trials occurred approximately 500 ms after each picture sequence – just enough time to switch tasks -- and attention scope was measured multiple times throughout the experiments. Previous research that has examined the influence of affect on attention scope with the Eriksen flanker task (Eriksen & Eriksen, 1974) measured interference by the difference in response time and accuracy between congruent and incongruent stimuli (e.g., Rowe et al., 2007). In my dissertation research, however, when I used the Eriksen flanker task, I also included control stimuli. Control stimuli were included to measure the extent of broadened and narrowed attention scope relative to those stimuli, which act as a midpoint. Specifically, with control stimuli it is possible measure facilitation (i.e., speed up on congruent stimuli compared to control stimuli) and interference (i.e., slow down on incongruent stimuli compared to control stimuli). 1.5. Definitions The terms affect, mood and emotion are often used interchangeably, but they are distinctly different concepts. I define affect [others have called it ‘core affect’ (e.g., Russell, 2003)] as the neurovisceral component of emotions (e.g., Duncan & Barrett, 2007; Russell, 1999; Russell, 2003). When you encounter an event, such as a piercing scream or a cute puppy, it is likely to influence or affect you in some manner. Consistent with these examples, affect is a general label for an internal state change, a descriptor for the fact that the system has been “affected” by an event (e.g., Russell, 2003). I use the word 29 emotion as label for the subjective state – for the qualitative phenomenological experience -- that can occur upon encountering an event, such as a cute puppy or a piercing scream. Ekman (1999) has identified several such subjective states and has argued that 6 of these states are universal, and are commonly assigned these labels: anger, disgust, fear, sadness, happiness, and fear. Moods are brought on by events, just like emotions, but they are longer lasting and less intense than emotions. They often occur in response to a combination of similar situations and are less specific than emotions (Scherer, 2004). For example, you may be in a bad mood this week because nothing seems to be going right—your car broke down; you lost your keys and failed a midterm exam. 1.6. Overview of Dissertation The main goal of my dissertation was to elucidate the relationship between affect and the scope of attention. My dissertation was primarily guided by the Affect-as-Information hypothesis (e.g., Gasper & Clore, 2002) and the Broaden-and-Build theory (e.g., Fredrickson & Branigan, 2005), as those are the dominant theories in the field. The first part of my dissertation (i.e., Experiments 1, 2 and 3) was guided by these theories to focus specifically on how valence states influence attention scope. The other experiments in my dissertation (i.e., Experiments 4 and 7) examined these theories in addition to Motivational intensity theory to examine the effects of valence states and movement propensity states influence the scope of attention (e.g., Gable & Harmon-Jones, 2010b; Fredrickson, 2001). To achieve this goal, my dissertation uses effective methods to induce affect in participants, and the most common, reliable, and validated attention scope measures. In the chapters that follow, I present a series of experiments that examine the relationship between affect and the scope of visual attention. The main purpose of Experiments 1 and 2 was to find evidence for the assumption that valence states influence attention scope (e.g., Gasper & Clore, 2002; Fredrickson & 30 Branigan, 2005) with high-powered, and controlled experiments. In both experiments, emotional events were induced with pictures, with different degrees of valence (extremely negative, negative, neutral, positive, and extremely positive). Participants were asked to rate how much they liked the pictures and following a set of pictures, attention scope was measured with a Navon task (Navon, 1977) (Experiment 1) and an Eriksen flanker task (Eriksen & Eriksen, 1974) (Experiment 2) at various times throughout the experiments. Experiment 3 was conducted to further examine the relationship between valence states and the scope of attention and ensure that my affect induction method was effective. I also examined the relationship with a between-subject design to examine the possibility of carryover effects of valence states. To induce emotional events, participants were asked how each picture makes them feel and rate the pictures accordingly. To measure the scope of attention, the same Eriksen flanker task (Eriksen & Eriksen, 1974) was used as in Experiment 2. Experiment 4 was conducted to further examine the influence of valence states and the scope of attention, examining if it may occur for attractive and repulsive movement propensity states. Not all positive are the same and not all negative events are the same—some events have a movement propensity associated with them (movement towards or away), while others do not (no movement) (e.g., Gable & Harmon-Jones, 2010b). The procedure was identical to Experiment 2, but pictures were chosen based on the approach and avoidance norms to refine the theories that attempt to explain the influence of valence states on attention scope. Surprisingly, the first 4 experiments of my dissertation revealed no convincing evidence for the relationship between valence states and the scope of attention, which caused my research to take an unexpected turn. At this point in my dissertation, I had two options: I could conclude there is no relation between valence states and the scope of attention, however, I was not ready to do that, so I explored a 31 second option. Experiments 5 and 6 were conducted to determine if performance on the Eriksen flanker task shows the predicted pattern of results following an induced broad and narrow attention scope. I also set out to determine if a specific variation of the Eriksen flanker task is particularly effective in picking up changes in attention scope (both broadening and narrowing). Different variations of the task were implemented by manipulating font size, spacing and visual angle of the letters. Experiment 7, the final experiment, was similar to Experiment 4, however, rather than using approach and avoidance normed pictures to induce affect, I used distinct emotions (each with different valences and movement propensities associated with them). I used a specific variation of the Eriksen Flanker task that was most effective in Experiments 5 and 6. In the final chapter of my dissertation, I summarize the empirical, methodological, and theoretical contributions of my research. I illustrate the implications and limitations of the research presented in the dissertation and suggest avenues for future research. 32 Chapter 2: The Influence of Valence States on the Scope of Attention Part of the research review in Chapter 1 focuses on how different valence states change the scope of attention and highlights the inconclusiveness of the evidence. In contrast to the expectations based on the Broaden-and-Build theory (e.g., Fredrickson, 2004) and the Affect-as-Information Hypothesis (e.g., Gasper & Clore, 2002), the evidence does not show, it fails to show, that the affect induced by positive emotional events broadens the attention scope, and/or that the affect induced by negative emotional events narrows it. It would be premature, however, to draw theoretical conclusions from the current evidence for a variety of reasons, such as the relatively small number of participants in many previous experiments, and many profound differences in the methods used for inducing different valence states and for measuring attention scope. For this reason, the starting point for my research and goal of the work reported in this chapter was to re-test the core theoretical assumption that positive valence broadens the scope of attention and negative valence narrows it, in two experiments with ample power, under conditions known to induce systematic changes in participants’ valence states (Fredrickson, 2001; 2004; Gasper & Clore, 2002). To conduct a valid test of theoretical assumptions about how valence states influence the scope of attention, a method for creating or inducing reliably different valence states is required. The literature review in Chapter 1 listed a large variety of different methods that have been used for this purpose, such as asking participants to recollect positive and negative autobiographical memories (e.g., Gasper & Clore, 2002), watch films (e.g., Fredrickson & Branigan, 2005) or listen to music (e.g., Rowe et al., 2007) that are/is uplifting/positive or depressing/negative. To my knowledge, no research has systematically compared the effectiveness of the methods available for inducing affect in participants. In the absence of guidance from previous research, to create different valence states in my participants, I required them to rate affective pictures, which differed in terms of valence, using pictures which had been independently normed for many populations (Lang et al., 2008). Previous research has shown that picture valence norms 33 matter. For instance, they predict recall performance on memory tests (e.g., Alaifan, 2022) and event- related potential research has shown that different brain activity patterns are produced for positive, neutral, and negative pictures (e.g., Cuthbert et al., 2000). Another factor that is likely to have contributed to the inconclusive results of previous research is the lack of statistical power and a limit on generalizability. As seen in Chapter 1, the literature review emphasized that some experiments used a small number of participants (e.g., 24 in Rowe et al., 2007) and a small number of stimuli (e.g., one stimulus for each emotional event in Fredrickson & Branigan, 2005), and the use of these stimuli for inducing affects was not independently validated (e.g., Wang et al., 2008). One more factor that may have contributed to the inconclusive results of previous research is the variety of different methods that have been used to measure attention scope. The most common measures, discussed in Chapter 1, include the Eriksen flanker task (Eriksen & Eriksen, 1974), the Navon task (Navon, 1977) and the Kimchi Palmer task (Kimchi & Palmer, 1982). I chose to use the Navon task and the Eriksen flanker task in my experiments. Experiment 1 and Experiment 2 differed only terms of the method used for measuring attention scope. Experiment 1 used the Navon task (Navon, 1977) and Experiment 2 used an Eriksen Flanker Task (Eriksen & Eriksen, 1974). Consistent with the Broaden-and-Build theory (e.g., Fredrickson, 2004) and the Affect-as- Information Hypothesis (e.g., Gasper & Clore, 2002), I made the following hypotheses. For Experiment 1 which used the Navon task (Navon, 1977), I hypothesized that relative to the neutral valence level condition, responses would be made faster to global than local letters following exposure to positive pictures, and responses would be faster to local than global letters following negative pictures. For Experiment 2 which used the Eriksen Flanker task (Eriksen & Eriksen, 1974), I hypothesized that relative to neutral pictures, responses would be slower on incongruent stimuli than control and congruent stimuli 34 following exposure to positive pictures; I also predicted that responses would be made equally fast to incongruent, control and congruent stimuli following exposure to negative pictures. 2.1: Experiment 1 Method 2.1.1: Design and Participants The experiment had two within-subject factors: Valence level/bin (extremely positive, positive, neutral, negative, extremely negative) and Navon letter type (global, local). The participants were 141 undergraduate students (115 women) from the University of British Columbia, recruited from the Department of Psychology Human Subject Pool. They received partial course credit for participating. The experiment was conducted with the approval of the University of British Columbia Behavioural Research Ethics Board. To detect the predicted interaction between valence states and attention scope, a power analysis was conducted to determine the number of participants required for detecting a 20 ms difference between response time on global and local letters following positive pictures, versus the same difference following negative pictures. The analysis was based a small effect size (d = .15) and on this assumption, a power analysis using the G*Power computer program (Faul et al., 2007), indicated a total sample of 114 participants would be needed to detect a small effect with .99 power using a repeated measures ANOVA with alpha set at .05. 2.1.2: Materials 2.1.2.1: Pictures One hundred and twenty-five colour pictures (25 from each valence level) were selected according to their valence and arousal ratings from the International Affective Picture System (IAPS) (Lang et al., 2008). In the IAPS, each picture has normative data on valence and arousal collected from samples of 35 men, of women and from the combined sample of men and women. The combined norms were used for selecting pictures for the present study. Table 2.1 shows the selection criteria and the properties of the pictures used in Experiment 1. Pictures varied by valence ratings and were selected to fit into one of five possible valence bins: extremely positive, positive, neutral, negative, and extremely negative, and all pictures were selected to have a medium arousal rating. The table shows the range of the valence and of arousal scores that were used for selecting pictures for each bin; it also shows basic stats on valence and arousal for the pictures selected into each bin. The selected pictures showed human interactions (e.g., a smiling child; a couple fighting), scenes of built and natural environments (e.g., a cityscape; sunset over the mountains) and scenes with animals (e.g., a group of kittens; a horse; a spider). Sexually explicit and culturally inappropriate and extremely repulsive pictures were not selected. Each picture was saved as a 320 x 240 pixel .jpeg file. When displayed in the experiment, each picture subtended a visual angle of approximately 7.6° on its longer side. 36 Table 2. 9 Valence and Arousal Ratings for IAPS pictures for Experiment 1, with the Selection Criteria and the Properties of the Selected Pictures for Each Valence Level/Bin: Extremely Positive, Positive, Neutral, Negative, and Extremely Negative. Picture Selection Criteria Properties of Selected Pictures Valence Level/Bin Valence Arousal Valence Arousal Range Range M SD M SD Extremely Positive 7.50 – 8.50 3.00 – 7.00 7.11 0.48 5.16 0.40 Positive 5.50 – 6.50 3.00 – 7.00 6.17 0.24 5.00 0.35 Neutral 4.50 – 5.50 3.00 – 7.00 4.93 0.39 5.05 0.64 Negative 3.00 – 4.00 3.00 – 7.00 3.70 0.27 5.03 0.29 Extremely Negative 1.50 – 3.00 3.00 – 7.00 2.50 0.29 5.10 0.23 2.1.2.2: Navon Letters Eight Navon letters were adapted from Gable and Harmon Jones (2008). Each consisted of a collection of component letters arranged into a configuration that outlined a large letter, as shown in Figure 1.1. The outline was an L, F, H or T, and the component letters also were Ls, Fs, Hs or Ts. The component letters were in Times New Roman font. For the Navon task, participants are required to decide if the display includes an H or T. For this dissertation, I use the label ‘global letters’ to refer to the H, L, F or T that were outlined by the arrangement of the component letters, and I use ‘local letters’ to refer to the components. 37 2.1.3: Procedure All participants were tested individually in a quiet room equipped with a desktop computer running E-Prime 2.0 (Psychology Software Tools, 2012). Each participant was guided through the consent process before signing the form and beginning the experiment. 2.1.3.1: Event Sequence The experiment consisted of 50 event sequences, each of which included displaying 5 pictures from the same valence level, followed by 8 Navon letters. All stimuli were displayed in the center of the screen on a white background. The arrangement of the trials from each sequence and the timing of each trial are shown in the top portion of Figure 2.1. For each picture display trial, participants were shown a fixation cross (*) for 500 ms, which subtended a 0.1° x 0.1° visual angle. Then a picture appeared, together with an 8-point rating scale, arranged as shown in the figure, and the task was to rate the picture on this scale. The rating scale endpoints were marked ‘Extremely Negative’ and ‘Extremely Positive’ and all parts of the scale were displayed in Arial font, each letter measuring about 0.95° visual angle. Participants were instructed that “People have different perceptions of pictures but what is important is your true perception of the picture so rate it in terms of how much you like it, in terms of what it means to you.” Participants were asked to respond, “According to your gut reaction, and in such a way that if you saw the picture again, you likely would rate it similarly”. As soon as participants responded, the next trial began. The pictures within each valence sequence were randomly presented. The purpose of the picture task was to ensure that participants attended to each picture, and the ratings were used as an indicator of participants' automatic affective response. Immediately after rating the 5 pictures from each valence sequence, the scope of attention was assessed with a Navon letter sequence, also shown in Figure 2.1. Immediately following the sequence of five valenced pictures, participants were shown a fixation cross (*) for 500 ms, which subtended a 0.1° x 38 0.1° visual angle. Next, a Navon letter was displayed. As soon as the participant responded, “Is there an H or a T?”, the next trial began. If the participants saw a T, they were asked to press the left arrow key on a QWERTY keyboard, and if participants saw an H, they were asked to press the right arrow key. Each Navon letter outline had a 4.5° x 4.5° visual angle, and each component letter subtended a visual angle of 0.9° x 0.9°. The letters within each Navon letter sequence were randomly presented. In 50% of the letters, the H or T was the outline letter and in 50% of the H or T was the component letters. The order of each of the Navon letters was random. To practice the picture and Navon tasks, participants completed 2 event sequences as shown in Figure 2.1. During practice, beeps alerted participants to errors. If a beep occurred during practice, the participant was interrupted and instructions to be accurate were repeated. Participants were free to ask questions at any time. To end the experiment, participants completed a funnel interview. The purpose of the interview was to collect feedback on participants’ experience in the experiment. Following the interview, participants were thoroughly debriefed. The experiment took place in one session lasting about 50 minutes. 39 Figure 2. 13. One event sequence in Experiment 1: Each event sequence was composed of the picture task which showed 5 pictures to induce affect, followed by the Navon task which used 8 Navon letters to measure attention scope. Picture and rating scale remained on the screen until response * 1 2 3 4 5 6 7 8 Slightly Negative Slightly Positive Extremely Positive * 1 2 3 4 5 6 7 8 Extremely Negative Slightly Negative Slightly Positive Extremely Positive * 1 2 3 4 5 6 7 8 Extremely Negative Slightly Negative Slightly Positive Extremely Positive * 1 2 3 4 5 6 7 8 Extremely Negative Slightly Negative Slightly Positive Extremely Positive * 1 2 3 4 5 6 7 8 Extremely Negative Slightly Negative Slightly Positive Extremely Positive + + + * + + Fixation cross for 500 ms * + + * Navon letters remained on the screen until response Fixation cross for 500 ms * * * * * Extremely Negative 40 2.2: Results and Discussion The goal of the present study was to test the assumption that the valence states induced by positive pictures lead to faster responses on global than local letters, and that the valence states induced by negative pictures lead to faster responses on local than global letters. The main independent variable was the pictures in each valence level/bin and the dependent variables were the ratings and the rating speeds on the picture task and performance accuracy and speed on the Navon task (Navon, 1977). To make decisions about differences between means 95% confidence intervals were used. When follow-up analysis was required, ANOVAs were conducted. 2.2.1: Data Screening All data were screened for outliers on the picture task and the Navon task (Navon, 1977). On the picture task, 1 participant had a mean median response time of 6971 ms, more than 3 standard deviations above the group mean of 1554 ms. On local letters in the Navon task, 2 participants had a mean accuracy of 70% and 51%, more than 3 standard deviations below the group mean of 97%. On global letters in the Navon task, 3 participants had a mean accuracy of 86%, 87%, and 87% more than 3 standard deviations below the group mean of 97%. On local letters in the Navon task, 1 participant had a mean median response time of 1158 ms, more than three standard deviations above the group mean of 697 ms. On the global letters in the Navon task, 2 participants had a mean median response time of 1068 ms and 1069 ms, more than three standard deviations above the group mean of 696 ms. None of the means from these participants were included in any of the analyses reported below. The results reported below are based on data from the remaining 134 participants. 41 2.2.2: Picture Task Performance Participants’ mean ratings of the pictures from each valence level condition are shown in Figure 2.2. The means indicate participants gave the highest ratings to extremely positive pictures and the lowest ratings to extremely negative pictures, with all others in between. These findings are roughly consistent with the valence ratings from the IAPS norms (e.g., Lang et al., 2008), Some of ratings were unexpected. First, the ratings of the neutral pictures were lower than expected. I used an 8-point scale, but participants rated neutral pictures just below 4, approximately half a point lower than the 4.5 midpoint of the scale, indicating that participants anchored the midpoint of the scale lower than expected (Gehlbach, & Barge, 2012). Second, the extremely positive pictures were rated lower than expected. Even though participants were given instructions to use the whole scale, the extremely positive pictures were rated 6.5, only moderately high, indicating that participants did not use the upper end of the 8-point rating scale. This may have occurred because of participants anchoring lower than expected on the scale, or because of a negativity bias (Vaish et al., 2008). Third, the ratings for extremely negative and negative pictures did not differ. This may have occurred because of participants anchoring lower than expected on the scale and therefore compressed the ratings at the lower end of the scale (i.e., if a negative picture is rated it at the lowest point of the scale, it is impossible to give a lower rating to an extremely negative picture). 42 Figure 2. 14. Mean ratings of the pictures in Experiment 1 in each valence level condition: extremely negative, negative, neutral, positive, and extremely positive pictures. Error bars represent 95% confidence intervals. The means of participants’ median picture rating times are shown in Figure 2.3. The means show that participants were fastest to respond to extremely negative, negative, and extremely positive pictures, which did not significantly differ from each other. Participants were slower to respond to positive pictures but were slowest to respond to neutral pictures. The slow-down on neutral pictures may have occurred because neutral IAPS pictures (Lang et al., 2008) have been found to elicit mixed feelings of positivity and negativity making it difficult for participants to decide how to rate them (Schneider et al., 2016). 1 2 3 4 5 6 7 8 Extremely Negative Negative Neutral Positive Extremely Positive Me an R ati ng (1 -8 ) Valence Level Condition 43 Figure 2. 15. Mean of median times required for rating pictures in Experiment 1 in each valence level condition: extremely negative, negative, neutral, positive, and extremely positive. Error bars represent 95% confidence intervals. 2.2.3: Navon Task Performance For each participant, I computed the mean identification accuracy for the global and local letters. Mean accuracy was similar for the global letters (M = 97%, SD = 0.03) and local letters (M = 97%, SD = 0.03). These results assuage concerns about a speed-accuracy trade-off in performance on the Navon task (Schouten & Bekker 1967; Wickelgren 1977). Accuracy was also similar in all valence level conditions, as shown in Table 2.2. 0 200 400 600 800 1000 1200 1400 1600 1800 2000 Extremely Negative Negative Neutral Positive Extremely Positive Me an R ati ng T im e ( ms ) Valence Level Condition 44 Table 2. 10 Mean Accuracy and Standard Deviation in the Navon task on Global and Local Letters Following the Pictures from Each Valence Level Condition in Experiment 1. For each participant, I computed the mean of the median response time required to identify targets in global and local letters. Across all conditions, the mean median response time was similar for the global letters (M = 701.95, SD = 121.97) and local letters (M = 705.49, SD = 136.31). These results provide no evidence for the global precedence effect, that is, with participants responding faster to global than local letters (Navon, 1977). The absence of a global precedence effect replicates previous research (Miller, 1981). The mean of the median response times to targets in global and local letters in each valence level condition is shown in Figure 2.4. The means show similarities in response time among valence level conditions, particularly between the extremely negative and negative picture valence level conditions, and Valence Level Condition Global Letters Local Letters M SD M SD Extremely Negative 97% 0.03 97% 0.03 Negative 97% 0.03 97% 0.03 Neutral 98% 0.03 97% 0.03 Positive 97% 0.03 97% 0.06 Extremely Positive 97% 0.04 98% 0.03 45 between the positive and extremely positive valence level conditions. Overall, there are small differences among the valence level conditions, with a mean as low as 696 ms to respond to local letters to as high as 720 ms for responding to global letters. The differences in responding were examined with a repeated measures ANOVA, with Navon letter type (global, local) and valence level condition (extremely positive, positive, neutral, negative, and extremely negative), as the within-subjects variables. Mauchly’s test of sphericity was significant for the valence level condition by Navon letter type interaction indicating that sphericity is violated, χ2(9) = 21.884, p =. 009, and thus I used the Greenhouse-Geisser correction. The results revealed no main effects due to either valence level condition or Navon letter type, but the valence level condition by Navon letter type interaction was significant, F(3.655,486.052) = 3.234, p = .012, η2= .024. Based on the predictions of the Broaden-and-Build theory (e.g., Fredrickson, 2001; 2004) and the Affect-as-Information hypothesis (e.g., Gasper & Clore, 2002), I expected an interaction to occur whereby participants were faster on global letters and slower on local letters in the positive valence level conditions, and slower on global letters and faster on local letters in the negative valence level conditions. Guided by these predictions, follow-up pair-wise comparisons comparing each of the Navon letter types in each valence level condition were conducted, but none were significant. The results suggest no relationship between valence states and attention scope (e.g., Gable & Harmon-Jones, 2010b; Huntsinger, 2010; 2012). 46 Figure 2. 16. Mean of median response time on Navon task global and local letters in each valence level condition in Experiment 1. Error bars represent 95% confidence intervals. One possible reason why none of the valence conditions in Experiment 1 produced a difference in performance on global or local letters is that the affective state created by exposure to a picture sequence is relatively short lasting (e.g., Cuthbert et al., 2000), and it might dissipate completely in the time required (approximately 8 seconds) for administering all trials of the Navon task. To explore this possibility, I conducted a separate analysis of the Navon data from the first portion of each test sequence (4 trials). Participants’ mean of median response times on global and local letters in each valence level condition are shown in Figure 2.5. Overall, there are minimal differences between the valence levels, and with a mean as low as 697 ms for responding to local letters and as high as 709 ms for responding to global letters. To examine these differences, I used a repeated measures ANOVA, with Navon letter type (global, local) and valence level condition (extremely positive, positive, neutral, negative, and extremely negative), as the 600 620 640 660 680 700 720 740 760 780 800 Ex tre me ly Ne ga tiv e Ex tre me ly Ne ga tiv e Ne ga tiv e Ne ga tiv e Ne ut ra l Ne ut ra l Po sit ive Po sit ive Ex tre me ly Po sit ive Ex tre me ly Po sit ive Global Local Global Local Global Local Global Local Global Local Me an R es po ns e T im e ( ms ) Navon Letters/ Valence Level Condition 47 within-subjects variables. The ANOVA revealed no significant effects suggesting there is no relationship between valence states and attention scope (e.g., Gable & Harmon-Jones, 2010; Huntsinger, 2010; 2012). Figure 2. 17. Mean of median response time in Experiment 1 on the first four global and local letters in each valence level condition. Error bars represent 95% confidence intervals. A null effect on the Navon task due to the valence level manipulation might have occurred, in part because of the long procedure used in Experiment 1. It is possible that participants became tired or bored as they progressed through the experiment, which may have affected how they responded to the Navon letters. Upon debriefing participants, some expressed that they were fatigued by the second half of the experiment (25 event sequences). A second possible reason for why none of the valence conditions produced a difference in performance may be that the within-subject manipulation of affect may have caused the effects to wash out. To explore these possibilities, I conducted a separate analysis of Navon 600 650 700 750 800 850 900 950 Ex tre me ly Ne ga tiv e Ex tre me ly Ne ga tiv e Ne ga tiv e Ne ga tiv e Ne ut ra l Ne ut ra l Po sit ive Po sit ive Ex tre me ly Po sit ive Ex tre me ly Po sit ive Global Local Global Local Global Local Global Local Global Local Me an R es po ns e T im e ( ms ) Navon Letters/ Valence Level Condition 48 task responding but using data only from the first half of the experiment. Participants’ median response times to the global and local letters in each valence condition in the first half of the experiment are shown in Figure 2.6. Overall, there are minimal differences between valence levels, with a mean as low as 756 ms to respond to local letters and as high as 785 ms to respond to global letters. A repeated measures ANOVA, with Navon letter type (global, local) and valence level condition (extremely positive, positive, neutral, negative, and extremely negative), as the within-subjects variables, shown no significant effects suggesting there is no relationship between valence states and attention scope (e.g., Gable & Harmon-Jones, 2010b). Figure 2. 18. Mean of median response time to global and local letters in the first half of Experiment 1 in each valence level condition. Error bars are 95% confidence intervals. I also examined Navon task responding with the data from the first half of the experiment and only data from the first half of the Navon task (4 trials). Participants’ mean of median response time to global and local letters in each valence level condition related to this analysis are shown in Figure 2.7. A repeated 600 650 700 750 800 850 900 950 Ex tre me ly Ne ga tiv e Ex tre me ly Ne ga tiv e Ne ga tiv e Ne ga tiv e Ne ut ra l Ne ut ra l Po sit ive Po sit ive Ex tre me ly Po sit ive Ex tre me ly Po sit ive Global Local Global Local Global Local Global Local Global Local Me an R es po ns e T im e ( ms ) Navon Letters/ Valence Level Condition 49 measures ANOVA, with Navon letter type (global, local) and valence level condition (extremely positive, positive, neutral, negative, and extremely negative), as the within-subjects variables showed no significant main effects or interactions, suggesting no relationship between valence states and attention scope (e.g., Gable & Harmon-Jones, 2010b). Figure 2. 19. Mean of median response time to global and local letters in the first half of Experiment 1, for the first four letters following the pictures from each valence level. Error bars are 95% confidence intervals. 2.2.4: Bayesian Analyses Given the null results of Experiment 1, I used a Bayes Factor analysis for deciding whether my data support the null hypothesis that the speed of responding would be equally fast for global and local letters. I would expect support for the alternative hypothesis in the positive and negative valence level conditions, because this is where I expect the largest difference between global and local letters to occur. According to SPSS (IBM Corp, 2020) a Bayes’ factor of 3-10 is moderate support for the null hypothesis 600 650 700 750 800 850 900 950 Ex tre me ly Ne ga tiv e Ex tre me ly Ne ga tiv e Ne ga tiv e Ne ga tiv e Ne ut ra l Ne ut ra l Po sit ive Po sit ive Ex tre me ly Po sit ive Ex tre me ly Po sit ive Global Local Global Local Global Local Global Local Global Local Me an R es po ns e T im e ( ms ) Navon Letters/ Valence Level Condition 50 and a factor > 10 is considered strong evidence. A Bayes Factor of 10 in the favor of the null hypothesis (BF10) would suggest that the data obtained are 10 times more likely to occur under the alternative hypothesis than the null hypothesis. An alpha level of .05 was used for the tests. The valence state induced in each valence level condition in Experiment 1 did not significantly differ for global and local letters in Experiment 1. I conducted 5 Bayes’ Factor related samples t-tests. The results are shown in Table 2.3. The analysis shows moderate support for the null hypothesis, indicating that the valence manipulation had no effect. Table 2. 11 Bayes Factors Calculated using a Dependent Samples T-Test for Global and Local Letters in Each Valence Level Condition in Experiment 1. 2.3: Experiment 1 Conclusion The results of Experiment 1 suggest there is no relationship between valence states and the scope of attention of the type predicted by the Broaden-and-Build theory and the Affect-as-Information Hypothesis Valence Level Condition Related Samples T-Test Bayes Factor Extremely Negative 8.218 Negative 8.692 Neutral 9.483 Positive 9.549 Extremely Positive 7.929 51 (e.g., Fredrickson, 2001; 2004; Gasper & Clore, 2002). This result is consistent with past research using the Navon task (Navon, 1977) (e.g., Bellaera & von Mühlenen, 2019, Johnson et al., 2010). It may be that IAPS picture manipulation was too weak to change attention scope (Lang et al., 1997). It is possible that the rating the pictures reduced the valence states experienced by participants, however, I do not think this is the case because of the post-experimental interviews with each participant. Participants expressed that they felt more positive after positive pictures and more negative after negative pictures. It could also be that the Navon task is not sensitive enough to measure attention scope, however, this is unlikely because previous research has found affect influences attention scope using it (e.g., Derryberry & Reed, 1998; Tidkis, et al., 2017; Wang et al., 2018). 2.4: Experiment 2 The purpose of Experiment 2 was the same as Experiment 1, except that I used an Eriksen flanker task to measure attention scope (Eriksen & Eriksen, 1974). Using the Eriksen flanker task provided an opportunity to measure participants’ level of interference caused by the middle and surrounding letters in the letter string. 2.4.1: Design and Participants The experiment had three within-subject variables: valence level/bin (extremely positive, positive, neutral, negative, and extremely negative), flanker stimulus type (congruent, control, incongruent) and spacing of flanker stimulus letters (no space, space). The participants were 124 undergraduate students (111 women) from the University of British Columbia, recruited from the Department of Psychology Human Subject Pool. They received partial course credit for participating. The experiment was conducted with the approval of the University of British Columbia Behavioural Research Ethics Board. 52 To detect the predicted interaction between valence states and attention scope, a power analysis was conducted to determine the number of participants required for detecting a 15 ms difference between congruent and control stimuli following positive pictures, versus the same difference following negative pictures. The analysis was based a small effect size (d = .15) and on this assumption, a power analysis using the G*Power computer program (Faul et al., 2007), indicated a total sample of 114 participants would be needed to detect a small effect with .99 power using a repeated measures ANOVA with alpha set at .05. 2.4.2: Materials 2.4.2.1: Pictures The pictures used in Experiment 2 were similar, but not identical to those used in Experiment 1 for generalizability to a larger stimulus set. As with Experiment 1, One hundred and twenty-five colour pictures, 25 from each of five different valence levels, were selected according to their valence and arousal ratings from the International Affective Picture System (IAPS) (Lang et al., 2008). In the IAPS, each picture is listed with normative data on valence and arousal that were obtained from samples of men, of women as well as data from the combined sample of men and women. The combined norms were used for selecting pictures for the present study. Table 2.4 shows the criteria used for selecting picture stimuli. Pictures were selected to fit into one of five possible valence levels, according to the values in the table: extremely positive, positive, neutral, negative, and extremely negative. All pictures were selected to have a medium arousal rating. Table 2.4 includes the valence and arousal values for the selected pictures, which showed human interactions (e.g., a smiling child; a couple fighting), scenes of built and natural environments (e.g., a cityscape; sunset over the mountains) and scenes with animals (e.g., a group of kittens; a horse; a spider). Sexually explicit and culturally inappropriate or repulsive pictures were not selected. Each picture was saved as a 320 x 240 53 pixel .jpeg file. When displayed during the experiment, each picture subtended a visual angle of approximately 7.6° on its longer side. Table 2. 12 Valence and Arousal Ratings for IAPS Pictures for Experiment 2, with the Selection Criteria and the Properties of the Selected Pictures for each Valence Level/Bin: Extremely Positive, Positive, Neutral, Negative, and Extremely Negative Selection Criteria Selected Pictures Valence Level/Bin Valence Arousal Valence Arousal Range Range M SD M SD Extremely Positive 7.50 – 8.50 3.00 – 7.00 7.99 0.18 4.85 0.88 Positive 5.50 – 6.50 3.00 – 7.00 6.51 0.11 4.90 0.57 Neutral 4.50 – 5.50 3.00 – 7.00 4.99 0.27 4.76 0.91 Negative 3.00 – 4.00 3.00 – 7.00 3.52 0.12 5.04 0.55 Extremely Negative 1.50 – 3.00 3.00 – 7.00 2.20 0.29 5.23 0.55 2.4.2.2: Flanker Stimuli Six flanker stimuli were constructed, two each for the congruent, incongruent and control stimuli, respectively. Each stimulus consisted of a string with 7 letters which were always the capital letters L, T or X. For the congruent stimuli, the string consisted either of all Ls (i.e., LLLLLLL) or all Ts (i.e., TTTTTTT). For the incongruent stimuli, the middle letter was different from the flanking letters (i.e., LLLTLLL; 54 TTTLTTT). For the control stimuli, the middle letter was a T or an L, and the flanking letters were Xs (i.e., XXXTXXX; XXXLXXX). The flanker stimuli were constructed to either had no spaces (i.e., LLLLLLL, TTTTTTT, TTTLTTT, LLLTLLL, XXXLXXX, XXXTXXX) or one space between them (i.e., L L L L L L L, T T T T T T T, T T T L T T T, L L L T L L L, X X X L X X X, X X X T X X X). 2.4.3: Procedure All participants were tested individually in a quiet room equipped with a desktop computer running E-Prime V2.0 (Psychology Software Tools, 2012). Each participant was guided through the consent process before signing the form and beginning the experiment. 2.4.3.1: Event Sequence The experiment unfolded as a series of 50 event sequences (10 of each valence level). The order of the valence levels was random. Each sequence began with the hand position for pictures task, followed by 5 pictures from the same valence level, followed by one hand position preparation Eriksen flanker task, and then 6 flanker stimuli. The hand position for pictures task randomly displayed a number between 1 and 9, the purpose of which was to ensure the participant's hands were on the number keys before a picture appeared. The hand position for the Eriksen flanker task randomly displayed 000L000 or 000T000 and was used was to ensure the participant's hands were on the arrow keys before a picture appeared. All stimuli were displayed in the center of the screen on a white background, and the arrangement as well as timing of the frames for each sequence were as shown in the top portion of Figure 2.8. Each sequence began with a fixation cross (*) for 500 ms, which subtended a 0.1° x 0.1° visual angle, followed by one trial of the hand position preparation for the picture task. Next, participants were shown a fixation cross (*) for 500 ms, and then a picture appeared, together with an 8-point rating scale, arranged as shown in the figure, and the task G lo 55 was to rate the picture on this scale. The rating scale endpoints were marked ‘Extremely Negative’ and ‘Extremely Positive’ and all parts of the scale were displayed in Arial font, each letter measuring about 0.95° visual angle. Participants were instructed that “People have different perceptions of pictures. What is important is your true perception of the picture, so please rate each picture in terms of how much you like it, in terms of what it means to you.” Participants were asked to respond, “According to your gut reaction, and in such a way that if you saw the picture again, you likely would rate it similarly.” As soon as participants responded, the next trial began. Immediately after rating the 5 pictures, there was a fixation cross for 500 ms followed by one trial of the hand position for the Eriksen flanker task. Next, participants were presented with a fixation cross (*) which subtended a 0.1° x 0.1° visual angle. The timing of the fixation cross was randomly presented for 250 or 750 ms. Then the scope of attention was assessed with a flanker stimulus, and this continued until 6 flanker stimuli were presented. For each flanker stimulus, the participant’s task was to decide if the middle letter of the sequence just displayed was an L or a T. Participants were instructed if they saw a T, they were asked to press the left arrow key on a QWERTY keyboard, and if participants saw an L, they were asked to press the right arrow key. In the experiment, each Flanker letter string had a 7° x 1° visual angle, and each letter subtended a visual angle of 1° x 1°. The order of each of the six congruent, control and incongruent flanker stimuli was random. To practice the picture and Navon tasks participants completed 2 event sequences like those shown in Figure 2.8. During practice, beeps occurred on the Eriksen flanker task (Eriksen & Eriksen, 1974) to alert participants to errors (e.g., responding that the middle letter was an L when it was a T). If a beep occurred during practice, the participant was interrupted and instructions to be accurate were repeated. Participants were free to ask questions at any time. 56 At the beginning of the experiment, half of the participants were randomly assigned to the no space condition and half were assigned to the space condition. At the break, the participants switched to the space and no space condition, respectively. The order of the spaced and no spaced conditions was counterbalanced across participants. To end the experiment, participants completed a funnel interview. The purpose of the interview was to collect feedback on participants’ experience in the experiment. Following the interview, participants were thoroughly debriefed. The experiment took place in one session lasting about 55 minutes. 57 Figure 2. 20. An event sequence in Experiment 2: Each event sequence was composed of 1 hand position preparation task to prepare for the picture task, the picture task with 5 pictures to induce a valence state, followed by 1 hand position preparation task to prepare for the Eriksen flanker task, and then the Eriksen flanker task with 6 flanker stimuli to measure attention scope. Picture and rating scale remained on the screen until response Fixation cross for 500 ms LLLLLLL * 000L000 * * LLLTLLL * Fixation cross for 250 ms or 750 ms Flanker stimuli remained on the screen until response XXXLXXX * XXXTXXX TTTTTTT * * * TTTLTTT LLLLLLL Number stayed on screen until participant made a response * 8 * 1 2 3 4 5 6 7 8 Extremely Negative Slightly Negative Slightly Positive Extremely Positive 1 2 3 4 5 6 7 8 Extremely Negative Slightly Negative Slightly Positive Extremely Positive * 1 2 3 4 5 6 7 8 Extremely Negative Slightly Negative Slightly Positive Extremely Positive 1 2 3 4 5 6 7 8 Extremely Negative Slightly Negative Slightly Positive Extremely Positive * 1 2 3 4 5 6 7 8 Extremely Negative Slightly Negative Slightly Positive Extremely Positive Fixation cross for 500 ms Fixation cross for 500 ms * * 58 2.4.4: Results and Discussion The goal of the present study was to test the assumption that the valence states induced by positive pictures lead to slower responses on incongruent stimuli than control and congruent stimuli, and the valence states induced by negative pictures lead to similar responses on congruent, control and incongruent stimuli. The main independent variables were the valence level of the pictures and the spacing of flanker stimuli letters. The dependent variables were the ratings and rating speeds on the picture task and performance accuracy and speed on the Eriksen flanker task (Eriksen & Eriksen, 1974). To make decisions about differences between means 95% confidence intervals were used. When follow-up analysis was required, ANOVAs were conducted. 2.4.4.1: Data Preparation All data were screened for outliers on the picture task and the Eriksen flanker task (Eriksen & Eriksen, 1974). On the picture task, 4 participants took a long time to respond and had a mean median response time of 2552 ms, 2564 ms, 2666 ms, 2944 ms, respectively, and these values were more than 3 standard deviations above the group mean of 1408 ms. On the Eriksen flanker task (Eriksen & Eriksen, 1974), 3 participants had a mean accuracy on incongruent stimuli of 79%, 82% and 84%, respectively, which is 3 standard deviations below the group mean of 96%. An additional participant had a mean accuracy of 86% on congruent stimuli, more than 3 standard deviations below the group mean of 98%. On the Eriksen flanker task, 2 participants took a long time to respond and had a mean median response time on congruent stimuli of 803 ms and 819 ms, respectively, more than 3 standard deviations above the group mean of 521 ms. None of the data from the above participants were included in any of the analyses reported below. The results reported below are based on the remaining 114 participants. 59 2.4.4.2: Picture Ratings Participants’ ratings of the pictures are shown in Figure 2.9. The means indicate participants gave the highest ratings to extremely positive pictures and the lowest ratings to extremely negative pictures, consistent with the valence ratings from the IAPS norms (e.g., Lang et al., 2008). Some of the picture ratings were different than expected. First, the midpoint of the scale was lower than expected. I used an 8-point scale, but participants rated neutral pictures just below 4, approximately half a point lower than the 4.5 scale midpoint, indicating that participants anchored their ratings lower on the scale than expected (Gehlbach, & Barge, 2012). A second surprise results is that the pictures from the extremely positive, positive, neutral, and negative valence bins were rated approximately one point lower than expected by the IAPS norms (Lang et al., 2008). Participants may have rated the pictures lower than expected because of how old and dated the pictures were. The style of the pictures may differ importantly from the style of pictures that was used to norm the IAPS pictures in 2008. 60 Figure 2. 21. Mean ratings of the pictures in Experiment 2 for each valence level condition: extremely negative, negative, neutral, positive, and extremely positive. Error bars are 95% confidence intervals. Participants’ picture rating times is shown in Figure 2.10. The means of medians show participants were the fastest to respond to extremely positive pictures, followed by extremely negative pictures, then negative, positive, and were slowest on neutral pictures. The slow-down on neutral pictures may have occurred because neutral IAPS pictures (Lang et al., 2008) have been found to elicit mixed feelings of positivity and negativity, making it difficult for participants to decide how to rate them (Schneider, et al., 2016). 1 2 3 4 5 6 7 8 Extremely Negative Negative Neutral Positive Extremely Positive Me an R ati ng (1 - 8) Valence Level Condition 61 Figure 2. 22. Mean of median times required for rating pictures in Experiment 2 in each valence level condition: extremely negative, negative, neutral, positive, and extremely positive. Error bars are 95% confidence intervals. 2.4.4.3: Eriksen Flanker Task Performance 2.4.4.3.1: Performance Accuracy For each participant, I computed the mean accuracy of identifying the middle letters in congruent, control and incongruent stimuli. Overall mean accuracy was highest on congruent and control stimuli, followed by incongruent stimuli, and was similar for the no spaced and spaced conditions as shown in Table 2.5. Accuracy was similar in all valence conditions, as shown in Table 2.6. These findings assuage concerns about a speed-accuracy trade-off in performance on the Eriksen flanker task (Rozand et al., 2015). 0 200 400 600 800 1000 1200 1400 1600 1800 Extremely Negative Negative Neutral Positive Extremely Positive Me an R ati ng T im e ( ms ) Valence Level Condition 62 Table 2. 13 Mean Accuracy and Standard Deviation on the Eriksen Flanker Task for Congruent, Control and Incongruent Stimuli in the No Space and Space Conditions in Experiment 2. Table 2. 14 Mean Accuracy and Standard Deviation on the Eriksen Flanker Task in Experiment 2 for Congruent, Control and Incongruent Stimuli in each Valence Level Condition: Extremely Negative, Negative, Neutral, Positive, and Extremely Positive. Space Condition Congruent Stimuli Control Stimuli Incongruent Stimuli M SD M SD M SD No Space 98% 0.03 98% 0.03 97% 0.03 Space 98% 0.03 98% 0.03 97% 0.03 Valence Level Condition Congruent Stimuli Control Stimuli Incongruent Stimuli M SD M SD M SD Extremely Negative 98% 0.04 98% 0.04 96% 0.01 Negative 98% 0.03 98% 0.03 97% 0.01 Neutral 98% 0.04 97% 0.03 97% 0.01 Positive 98% 0.04 98% 0.04 97% 0.01 Extremely Positive 98% 0.03 98% 0.04 97% 0.01 63 2.4.4.3.2: Performance Speed For each participant, I computed the mean of the median response time required to identify the middle letter for congruent, control and incongruent stimuli in the no space and space conditions. Overall, the marginal means indicate participants were faster on congruent stimuli (M = 521.47, SD = 82.01) and control stimuli (M = 520.85, SD = 82.97), than on incongruent stimuli (M = 546.95, SD = 81.24). This pattern of results illustrates a typical inhibition effect on the Eriksen flanker task (e.g., Eriksen & Eriksen, 1974). The mean of the median response times for the congruent, control and incongruent stimuli in the no space and space condition are reported in Table 2.7. In both spacing conditions, participants were slower to respond to incongruent stimuli than control and congruent stimuli. Overall, participants responded more slowly in the no space condition than in the space condition. These observations are supported by the results of a repeated measures ANOVA, with flanker stimulus type (congruent, control, incongruent) and spacing (no space, space), as the within-subjects variables. Mauchly’s test of sphericity was significant for flanker stimulus type indicating that sphericity is violated, χ2(2) = 15.180, p < .001, and therefore, the Greenhouse-Geisser correction is reported. The results revealed a main effect of flanker stimulus type, F(1.775, 200.576) = 95.732, p < .001, η2= .459. Follow-up pair-wise comparisons were conducted to compare each flanker stimulus type and showed that participants were slower on incongruent stimuli, (M = 546.95, 95%CI [532.43, 561.48]), than control (M = 520.85, 95%CI [506.65, 535.05]) p < .001, and congruent stimuli (M = 521.47, 95%CI [506.90, 536.04]) p < .001, but control and congruent stimuli did not differ from one another. There was a main effect of spacing, F(1.00,113.00) = 13.980, p < .001, η2= .110, with faster decisions in the space (M = 523.14, 95%CI [508.57, 537.71]) than no space conditions (M = 536.38, 95%CI [521.65, 551.10]). There was also a significant flanker stimulus type by spacing interaction, F(2,226) = 3.026, p = .05, η2= .026. In the no space condition, participants were slower on incongruent 64 stimuli (M = 555.16, 95%CI [539.77, 570.55]) than congruent (M = 517.14, 95%CI [501.73, 532.54]), p < .001, and control stimuli (M = 513.54, 95%CI [499.12, 527.95]), p < .001. In the space condition, participants were slower on incongruent (M = 538.74, 95%CI [523.98, 553.503] than congruent (M = 517.136, 95%CI [501.73, 532.54]), p < .001, and control stimuli (M = 513.54, 95%CI [499.12, 527.95]), p < .001, but the differences between stimuli were smaller. This is consistent with previous results that manipulated spacing between letter flankers (e.g., Bruyneel et al., 2013; Rowe et al., 2007). Table 2. 15 Mean of Median Response Time and Standard Deviation in the Eriksen Flanker Task on Congruent, Control and Incongruent Stimuli in the No Space and Space Conditions in Experiment 2. . The mean of the median response times for the congruent, control and incongruent stimuli in each valence level condition are shown in Figures 2.11 and 2.12 for the no space and space conditions, respectively. There are minimal differences in response time to identify the middle letter on congruent, control and incongruent stimuli in each valence level condition. Overall, participants were slower to respond to incongruent stimuli than control and congruent stimuli. The results of a repeated measures ANOVA, with flanker stimulus type (congruent, control, incongruent), spacing (no space, space), and valence level/bin (extremely negative, negative, neutral, positive, extremely positive) as the within-subjects variables Space Condition Congruent Stimuli Control Stimuli Incongruent Stimuli M SD M SD M SD No Space 525.80 81.01 528.16 79.82 555.16 82.94 Space 517.14 83.01 513.54 77.69 538.74 79.56 65 confirmed these observations. The Greenhouse-Geisser correction is reported for flanker because Mauchly’s Test of Sphericity was significant, 12.282, p = .002. There was a main effect of flanker stimulus type, F(1.812, 204.735) = 89.067, p < .001, η2= .441. Follow-up pairwise comparisons on each flanker stimulus type showed that participants were slower on incongruent stimuli (M = 545.99, 95%CI [531.51, 560.47]), than congruent (M = 522.33, 95%CI [507.60, 537.05], p < .001 and control stimuli (M = 520.70, 95%CI [506.717, 534.70]), p < .001. This is consistent with previous research using the Eriksen flanker task (Eriksen & Eriksen, 1974). The analysis also showed a main effect for valence level/bin that approached significance, F(14, 452) = 2.372, p = .052, η2= .121. Follow-up pairwise comparisons in each valence level condition were conducted indicating that participants responded faster to flanker stimuli after positive (M = 528.23, 95%CI [513.67, 542.79]), p = .044, and extremely positive pictures, (M = 526.25, 95%CI [512.13, 540.38]), p = .005, compared to extremely negative pictures (M = 533.23, 95%CI [518.59, 547.87]). These differences between valence level conditions are difficult to interpret but they may be an artifact of the data (particularly because it does not appear in other similar analyses). The analysis showed no evidence of the expected interaction between valence level/bin with flanker stimulus type. Based on the predictions of the Broaden-and-Build theory (e.g., Fredrickson, 2001; 2004) and the Affect-as-Information hypothesis (e.g., Gasper & Clore, 2002), I expected an interaction to occur whereby participants were slower to respond to the middle letter in incongruent stimuli than congruent and control stimuli in the positive valence level conditions. I expected participants to respond similarly quickly to the middle letter in congruent, control and incongruent stimuli in the negative valence level conditions. Guided by theoretical predictions, follow-up pair-wise comparisons comparing each of the flanker stimulus types in each valence level condition were conducted, but none were significant. The results suggest there is no influence of valence states on attention scope (e.g., Gable & Harmon-Jones, 2008b). 66 Figure 2. 23. Mean of the median Eriksen flanker task response time in Experiment 2 to identify the middle letter on congruent, control and incongruent stimuli in the no spaced condition for valence level condition: extremely negative, negative, neutral, positive, and extremely positive. Error bars represent 95% confidence intervals. 300 350 400 450 500 550 600 650 700 Co ng ur en t Co ntr ol Inc on gr ue nt Co ng ru en t Co ntr ol Inc on gr ue nt Co ng ru en t Co ntr ol Inc on gr ue nt Co ng ru en t Co ntr ol Inc on gr ue nt Co ng ru en t Co ntr ol Inc on gr ue nt Extremely Negative Extremely Negative Extremely Negative Negative Negative Negative Neutral Neutral Neutral Positive Positive Positive Extremely Positive Extremely Positive Extremely Positive Me an R es po ns e T im e ( ms ) Flanker Stimuli/ Valence Level Condition 67 Figure 2. 24. Mean of the median Eriksen flanker task response time in Experiment 2 to identify the middle letter on congruent, control and incongruent flanker stimuli in the spaced condition for each valence level condition: extremely negative, negative, neutral, positive, and extremely positive. Error bars represent 95% confidence intervals. 300 350 400 450 500 550 600 650 700 Co ng ur en t Co ntr ol Inc on gr ue nt Co ng ru en t Co ntr ol Inc on gr ue nt Co ng ru en t Co ntr ol Inc on gr ue nt Co ng ru en t Co ntr ol Inc on gr ue nt Co ng ru en t Co ntr ol Inc on gr ue nt Extremely Negative Extremely Negative Extremely Negative Negative Negative Negative Neutral Neutral Neutral Positive Positive Positive Extremely Positive Extremely Positive Extremely Positive Me an R es po ns e T im e ( ms ) Flanker Stimuli / Valence Level Condition 68 2.4.4.4: Bayesian Analyses Given the null results of Experiment 2, Bayesian analyses using the Bayes Factor were computed to test the null hypothesis that there was no difference between congruent and incongruent stimuli in each of the five valence conditions in the no space condition. According to SPSS (IBM Corp., 2020) a Bayes’ factor of 0.33 – 0.10 is moderate support for the alternative hypothesis and 0.03 to 0.01 is considered strong evidence for the alternative hypothesis. I conducted 5 separate Bayes’ Factor related samples t- tests and I chose the no space condition to conduct analyses because if an effect was present, I would expect it to occur in the no space condition because more interference occurs when there is no space between flanker stimuli (Eriksen & Eriksen, 1974). The results are shown in Table 2.8. The analysis shows moderate and strong support for the alternative hypothesis in each valence level condition, indicating that each valence condition shows the typical flanker effect (i.e., in each valence level condition, participants are slower on incongruent than congruent stimuli). The factors in Table 2.8 shown no difference among conditions, however, I would expect a difference in the positive valence conditions, but not in the negative valence conditions if there was a relationship between valence states and attention scope. Specifically, I would expect support for the alternative hypothesis in the positive valence level conditions, because this is where I expect the largest difference between congruent and incongruent stimuli to occur if attention scope broadened. I would expect support for the null hypothesis in the negative valence level conditions because this is where I expect a minimal difference between congruent and incongruent stimuli if attention scope narrowed. 69 Table 2. 16 Bayes Factors Calculated using a Related Samples T-Test for Congruent and Incongruent Stimuli in Each Valence Level Condition in Experiment 2. 2.6: Experiment 2 Conclusion The results of Experiment 2 suggest there is no relationship between valence states and the scope of attention, in contrast to predictions derived from the Broaden-and-Build theory and the Affect-as- Information Hypothesis (Fredrickson, 2001; 2004; Gasper & Clore, 2002). This null result replicates the outcome of Experiment 1; this outcome also is consistent with the report of no evidence of a relationship between valence and attention scope in a study by Bruyneel et al., 2013. Despite these null findings, however, it seems premature to reject the theoretical assumptions guiding this work because it is possible that the IAPS pictures I used -- or perhaps because of the manner in which I used them -- failed to induce the expected affective states in participants. I cannot rule out this possibility (Lang et al., 2008). Valence level Condition Related Samples T-Test Bayes Factor Extremely Negative .107 Negative .000 Neutral .000 Positive .004 Extremely Positive .001 70 2.7: Experiments 1 and 2 Conclusion The goal of Experiments 1 and 2 was to re-examine the relation between affect and the scope of attention posited by the Broaden-and-Build theory (e.g., Fredrickson, 2004) and the Affect-as-Information Hypothesis (e.g., Gasper & Clore, 2002), and to do so by experimentally manipulating valence states, using a large number of standardized stimuli, and common, reliable and valid measures of attention scope, with many participants to ensure statistical power. It is possible that no influence of valence states on attention scope was found in these experiments because Experiments 1 and 2 differ from previous research in terms of design, In Experiments 1 and 2, attention scope was measured with 6 or 8 trials following 5 trials of pictures for affect induction. Typically, when pictures are used to induce affect in participants, one picture is presented, followed by one trial of an attention scope measure (e.g., Gable & Harmon-Jones, 2008). It is unlikely that this would reduce the effects, however, because five trials of emotional events are likely to lead to a stronger affect induction than one picture (e.g., Cuthbert, 2000). There are three other possible reasons why Experiments 1 and 2 showed no influence of valence states on attention scope. One reason is that there may be potential carryover effects from each valence level which caused participants to experience mixed affect overall. The potential for mixed affect may have cancelled out any possible influences on attention scope. Research has shown that the influence of affect on other cognitive tasks may be reduced in within-subject designs (e.g., Waters et al., 2003). In Experiment 3, the effectiveness of valence states to induce affect in participants was further examined by manipulating valence states between subjects to eliminate the possibility of carryover effects. A second reason why the experiments may have shown no influence of valence states on attention scope may be that the affect induction method is not effective. In Experiment 3, I examined the validity of the affect induction method 71 with affect measures (e.g., Russell’s Affect Grid; Russell, 1989). A third reason may be that asking participants how much they “like” a picture, may not be the same as asking how they “feel” about a picture. A related research area has attempted to distinguish between liking and feeling (Murry et al., 1992). In Experiment 3, participants were asked explicitly how they “feel” about each picture. 72 Chapter 3: Validity of the Affect Induction In contrast to the expectations based on the Broaden-and-Build theory (e.g., Fredrickson, 2004) and the Affect-as-Information Hypothesis (e.g., Gasper & Clore, 2002), Experiments 1 and 2 showed no evidence that the affect induced by positive pictures broaden the scope of attention, or that the affect induced by negative pictures narrow it. It would be premature, however, to draw theoretical conclusions from this outcome without first verifying the validity of the affect induction method used in the preceding experiments. For this reason, the primary aim of Experiment 3 was to collect sufficient and reliable evidence that my affect induction method induces the expected changes in participants’ valence states. The method used in Experiment 3 was like that of Experiment 2 except for two differences. One difference was that the question participants were asked about each picture was changed from “How much do you like the picture?” to “How do you feel about the picture?”. This change was made because liking a picture is different than indicating how it makes you feel. The second difference was that valence states were manipulated between subjects. It is possible in the previous experiments that no influence of valence states on attention scope occurred because of carryover effects from one valence state to another (e.g., Zhang et al., 2014). Use of a between-subjects design ensure that each participant is exposed to only one type of emotional event throughout the experiment and therefore the possibility of carryover effects is eliminated. To verify the validity of the affect induction method, I used Russell’s Affect Grid (Russell et al., 1989) and the Brief-Mood Inspection Scale (BMIS) (Mayer & Gaschke, 1988) and I chose these measures for two reasons. One reason is that these measures are commonly used in research, and the BMIS reliability is adequate (Mayer & Gaschke, 1988) and the validity and reliability of Russell’s Affect Grid is considered to be good (Russell et al., 1989). A second reason I chose these measures was that both measures track the valence and arousal of participants’ feelings. Previous research examining the 73 influence of valence states on attention scope has used the Affect Grid (e.g., Bruyneel et al., 2013; Moriya and Nittono, 2011), but to my knowledge, no research in this area has used the BMIS. Consistent with the Broaden-and-Build theory (e.g., Fredrickson, 2004) and the Affect-as- Information Hypothesis (e.g., Gasper & Clore, 2002), I hypothesized that relative to neutral pictures, participants would be slower to respond to incongruent stimuli than control and congruent stimuli, following exposure to positive pictures, and they would respond equally quickly to incongruent, control and congruent stimuli after exposure to negative pictures. 3.1: Method 3.1.1: Participants and Design The experiment had one between-subjects variable: valence level/bin (positive, neutral, negative) and one within-subjects variable: flanker stimulus type (congruent, control, incongruent). The participants were 114 undergraduate students (104 women) from the University of British Columbia, recruited from the Department of Psychology Human Subject Pool. They received partial course credit for participating. Participants were randomly assigned to the valence levels, with 35 (31 women) in the positive valence condition, 42 (37 women) in the neutral valence condition, and 37 (33 women) in the negative valence condition. The experiment was conducted with the approval of the University of British Columbia Behavioural Research Ethics Board. To detect the predicted interaction between valence states and attention scope, a power analysis was conducted based on the assumption that a 15 ms difference will occur between congruent and control stimuli in the positive valence condition. I assumed the same for the negative valence condition. Therefore, the analysis was based on a small effect size (d = .15) and on this assumption, a power analysis using the 74 G*Power computer program (Faul et al., 2007), indicated a total sample of 93 participants would be needed to detect a small effect with .8 power using a repeated measures ANOVA with alpha set at .05. 3.1.2: Materials 3.1.2.1: Pictures The same set of pictures used in Experiment 2 were used in this experiment, but the pictures were divided among 3 valence bins. Table 3.1 shows the criteria for selecting pictures. Pictures were selected to fit into one of three possible valence levels/bins: positive, neutral, and negative. All pictures were selected to have a medium arousal rating. The selected pictures showed human interactions (e.g., a smiling child; a couple fighting), scenes of built and natural environments (e.g., a cityscape; sunset over the mountains) and scenes with animals (e.g., a group of kittens; a horse; a spider). Sexually explicit and culturally inappropriate or repulsive pictures were not selected. Each picture was saved as a 320 x 240 pixel .jpeg file. When displayed in the experiment, each picture subtended a visual angle of approximately 7.6° on its longer side. 75 Table 3. 4 Valence and Arousal Ratings for IAPS Pictures for Experiment 3, with the Selection Criteria and the Properties of the Selected Pictures for Each Valence Level/Bin: Positive, Neutral, and Negative. Selection Criteria Properties of Selected Pictures Valence Level/Bin Valence Arousal Valence Arousal Range Range M SD M SD Positive 6.50 – 8.50 3.00 – 7.00 7.25 0.72 4.90 0.72 Neutral 3.50 – 5.50 3.00 – 7.00 4.79 0.81 4.56 0.81 Negative 1.50 – 3.50 3.00 – 7.00 2.86 0.55 5.13 0.55 3.1.2.2: Flanker Stimulus The flanker stimuli from the no space condition from Experiment 2 were used in Experiment 3. However, the stimulus used for this experiment consisted of strings of 5 letters, rather than 7 letters. I made this change because five letter-strings are more commonly used in the research (e.g., Rowe et al., 2007; Bruyneel et al., 2013; Moriya & Nittono, 2011). 3.1.2.3: Russell Affect Grid The Russell Affect Grid is a single-item measure of the two dimensions of affect: pleasure- displeasure and arousal-sleepiness. It consists of a 9 by 9 grid, and participants mark the one square in this grid that corresponds to their current pleasure and arousal state. The inter-rater reliability of the grid is adequate, and the validity is good (Russell et al., 1989). Russell’s Affect Grid was used primarily for verifying participants' valence state; I was not using it to measure arousal because previous research has 76 suggested that the arousal scale is not as reliable as the pleasure scale, and may contribute little to the differentiations between affect, particularly when differences are small (Killgore, 1998). 3.1.2.4: Brief Mood Introspection Scale The Brief Mood Introspection Scale is a measure with 16 mood adjectives (e.g., happy, sad, lively), and participants use a rating scale to indicate how well each adjective describes their current mood state. The scale also requires a rating of overall mood. The validity of the scale is considered adequate (Mayer & Gaschke, 1988). 3.1.3: Procedure All participants were tested individually in a quiet room equipped with a desktop computer running E-Prime V2.0 (Psychology Software Tools, 2012). Each participant was guided through the consent process before signing the form and beginning the experiment. 3.1.3.1: Event Sequence The same event sequences as used in Experiment 2 (i.e., a series of five pictures from the same valence bin followed by six flanker stimuli) also were used in Experiment 3, with three differences. One difference was the instructions given to participants for rating the pictures. For this experiment, participants were told that “People have different perceptions of pictures but what is important is how you feel about the picture. To more effectively determine how you feel about each picture, think about yourself in a situation like the one presented and rate how it you would make you feel”. Participants were asked to respond, “According to your gut reaction, and in such a way that if you saw the picture again, you likely would rate it similarly”. A second difference is that the tasks used for preparing for the Eriksen Flanker test (Eriksen & Eriksen, 1974) and for making picture ratings were not used. A third difference was the fixation point that occurred prior to each flanker stimulus remained on the screen for 500 ms before the onset of the next trial. G lo 77 3.1.3.2: Experiment Flow The experiment included 40 event sequences. The pictures that were displayed as part of each event sequence were randomly chosen from the sample of 50 pictures per valence level/bin. The 40 event sequences were arranged into 8 blocks each with 5 event sequences. The order of event sequences was random. At the end of each block, participants were required to fill out the Russell’s Affect Grid (Russell, 1989), and they were given an opportunity to rest. They also were reminded of the task instructions, and participants pressed the letter ‘G’ on the keyboard when they were ready to proceed with the next block. To fill out the Russell’s Affect Grid, the computer screen prompted participants to “Please take a moment to fill out the Affect Grid.” Participants were given a printed copy of the grid and required placed an X on the grid that most accurately described how they were feeling at that moment. To practice the tasks, participants completed two event sequences, each for displaying 5 pictures and then 6 flanker stimuli (2 congruent stimuli, 2 control stimuli, and 2 incongruent stimuli). The arrangement of stimuli within the picture task and the Eriksen flanker task (Eriksen & Eriksen, 1974) was random. During practice, beeps occurred to alert participants to errors (i.e., an incorrect response to the middle letter). If a beep occurred during practice, the participant was interrupted and instructions to be accurate were repeated. After the practice sequences, participants filled out the Russell’s Affect Grid (Russel et al. 1989). When the E-Prime program finished, participants were given instructions and asked to fill out the BMIS (Mayer & Gaschke, 1988) to indicate how they were feeling. To end the experiment, participants completed a funnel interview, to collect feedback on their experiences in the experiment. Following the interview, participants were thoroughly debriefed. The experiment took place in one session lasting about 55 minutes. 78 3.2: Results and Discussion The goal of the present study was to test the assumption that the valence states induced by positive pictures lead to slower responses on incongruent stimuli than on control and congruent stimuli, and that the valence states induced by negative pictures lead to similarly fast responses on congruent, control and incongruent stimuli. The main independent variable was the valence level of the pictures, and the main dependent variables were the ratings and rating speeds on the picture task, the scores on the Affect Grid (Russel, 1989) and BMIS (Mayer & Gaschke, 1988), and performance accuracy and speed on the Eriksen flanker task (Eriksen & Eriksen, 1974). To make decisions about differences between means 95% confidence intervals were used. When follow-up analysis was required, ANOVAs were conducted. 3.2.1: Data Preparation All data were screened for outliers. The data from three participants were not available because of recording errors. On the Affect Grid, thirteen participants filled it out incorrectly and therefore their data were excluded from these analyses. On the picture task, 2 participants took a long time to respond to the pictures and had a mean median response time of 2856 ms and 2969 ms, respectively, more than 3 standard deviations above the group mean of 1485 ms. On the Eriksen flanker task (Eriksen & Eriksen, 1974), 3 participants took a long time to respond and had a mean median response time of 900 ms, 975 ms and 992 ms, more than 3 standard deviations above the group mean of 887 ms. All the data from these participants were excluded. The results reported below are based on the data of the remaining 93 participants. 3.2.2: Russell’s Affect Grid Scores Participants’ mean scores on the pleasure scale of the Russell’s Affect Grid (Russell, 1989) are shown in Figure 3.1. The means indicate participants in the positive valence level condition gave the 79 highest ratings and participants in the negative valence level condition gave the lowest ratings, with the neutral valence level condition in the middle. These findings are roughly consistent with the expectations based on the valence ratings from the IAPS norms (e.g., Lang et al., 2008). The differences between the IAPS norms and the results of the Russel’s Affect Grid speak to a difference between these methods. The pleasure score in the neutral condition is consistent with the norms, but in the negative condition it was 1 point higher than expected, and the in positive condition was 1 point lower than expected. It is possible that the ratings are different from the IAPS norms because in this experiment valence states were manipulated between-subjects. Figure 3. 2. Mean Russell’s Affect Grid pleasure score for participants in each valence level condition of Experiment 3. Error bars represent 95% confidence intervals. Participants’ mean scores on the arousal scale of Russell’s Affect Grid (Russell, 1989) are shown in Figure 3.2. The arousal scores across each valence level condition were slightly lower than expected (approximately 0.5). This is may have occurred because participants anchored slightly lower on the scale than the midpoint (Gehlbach, & Barge, 2012) or perhaps the experiment itself was boring for participants-- boredom is thought to reduce arousal (Deckert et al., 2018). The means also show that participants in the 1 2 3 4 5 6 7 8 9 Negative Neutral Positive Me an P lea su re S co re (1 -9 ) Valence Level Condition 80 positive valence level condition rated their arousal slightly higher than the neutral and negative valence level conditions. This difference likely occurred because of the variability of the between-subjects design. Figure 3. 3. Mean Russell’s Affect Grid arousal scores for participants in each valence level condition of Experiment 3. Error bars represent 95% confidence intervals. .3.2.3: BMIS Scores Participants’ mean scores on the pleasure scale of the BMIS (Mayer & Gaschke, 1988) are shown in Figure 3.3. The means show that participants in the positive valence level condition reported higher BMIS scores than participants in the negative and neutral valence level conditions. There was no difference between the neutral and negative valence level conditions. One possibility there is no difference between participants in the neutral and negative valence level conditions is that the BMIS was administered at the end of the experiment and at that point in time the effects of induced affect may have dissipated (e.g., Cuthbert, 2000). 1 2 3 4 5 6 7 8 9 Negative Neutral Positive Me an A ro us al Sc or e ( 1- 9) Valence Level Condition 81 Figure 3. 4. Mean pleasant BMIS score for the participants in each valence level condition. Error bars represent 95% confidence intervals. Figure 3. 5. Mean arousal BMIS score for the participants in each valence condition. Error bars represent 95% confidence intervals. 0 10 20 30 40 50 Negative Neutral PositiveM ea n P lea su re S co re (m ax = 64 ) Valence Level Condition 0 10 20 30 40 50 Negative Neutral Positive Me an A ro us al Sc or e ( ma x = 48 ) Valence Condition 82 Participants’ mean scores on the arousal scale of the BMIS (Mayer & Gaschke, 1988) are shown in Figure 3.4. There were no differences in arousal scores across the three valence conditions, which is consistent with the IAPS arousal norms chosen for the experiment (Lang et al., 2008). 3.2.4: Picture Task Performance Participants’ mean ratings of the pictures are shown in Figure 3.5. The means indicate participants gave the highest ratings to positive pictures and the lowest ratings to negative pictures. These findings are roughly consistent with the valence ratings from the IAPS norms (e.g., Lang et al., 2008). Two aspects of participants' picture ratings were unexpected: positive and neutral pictures were rated approximately 1 point lower than what would be expected from the IAPS norms (Lang et al., 2008). One reason participants may have been anchored lower than expected in the neutral and positive valence level conditions is because of the style of the pictures (Gehlbach, & Barge, 2012). They may have been viewed by participants differently and were less impactful than for the participants under which the norms were originally collected. Another potential reason is that picture type was manipulated in this experiment between subjects, and when the original norms were collected the experiment was within subjects. When participants completed the norms, they were exposed to all the possible pictures in the database, while participants in this experiment were only exposed to one type (i.e., pictures from one valence level/bin). 83 Figure 3. 6. Mean picture ratings for each valence level condition in Experiment 3. Error bars represent 95% confidence intervals. The means of participants’ median picture rating times are shown in Figure 3.6. The mean rating times show that participants were slower to respond to neutral pictures compared to positive and negative pictures. The slow-down on neutral pictures may have occurred because neutral IAPS pictures have been found to elicit mixed feelings in participants, and it would take more time to resolve potential conflicts and respond accordingly (Schneider et al., 2016), 1 2 3 4 5 6 7 8 Negative Neutral Positive Me an P ict ur e R ati ng (1 - 8) Valence Level Condition 84 Figure 3. 7. Mean picture rating times for each valence level condition in Experiment 3. Error bars represent 95% confidence intervals. 3.2.5: Eriksen Flanker Task Performance 3.2.5.1: Performance Accuracy For each participant, I computed the mean accuracy of identifying the middle letters in congruent, control and incongruent stimuli. Accuracy was higher on congruent and control stimuli than incongruent stimuli, as shown in Table 3.2. Mean accuracy was not different across the valence level conditions (see Table 3.3).These findings assuage concerns about a speed-accuracy trade-off in performance on the Eriksen flanker task (Schouten & Bekker, 1967; Wickelgren, 1977). 0 200 400 600 800 1000 1200 1400 1600 1800 2000 Negative Neutral Positive Me an P ict ur e R ati ng T im e ( ms ) Valence Level Condition 85 Table 3. 5 Mean Accuracy and Standard Deviation on the Eriksen flanker task for Congruent, Control and Incongruent Stimuli in Experiment 3. Table 3. 6 Mean Accuracy and Standard Deviation on Congruent, Control and Incongruent Stimuli in Each Valence Condition of Experiment 3. 3.2.5.2: Performance Speed For each participant, I computed the mean of the median response time required to identify the middle letter in congruent, control and incongruent stimuli, using only the data from accurate trials. Overall, the means indicate participants were faster on congruent stimuli and control stimuli, compared to Congruent Stimuli Control Stimuli Incongruent Stimuli M SD M SD M SD 98% 0.03 98% 0.03 96% 0.04 Valence Level Condition Congruent Stimuli Control Stimuli Incongruent Stimuli M SD M SD M SD Negative 99% 0.02 98% 0.02 96% 0.03 Neutral 98% 0.05 97% 0.04 96% 0.05 Positive 98% 0.04 97% 0.03 96% 0.03 86 incongruent stimuli. The difference in response time between congruent and incongruent stimuli is consistent with research using the Eriksen flanker task (Eriksen & Eriksen, 1974; Rowe et al., 2007). The mean of the median response times for the congruent, control and incongruent stimuli are reported in Table 3.4. Table 3. 4 Mean Eriksen Flanker Task Response Time to Identify the Middle Letter on Congruent, Control and Incongruent Stimuli in Experiment 3. The means of the median response times to identify the middle letter of the congruent, control and incongruent stimuli in each valence level condition are shown in Figure 3.7. In the negative and neutral valence level conditions, participants were fastest on congruent stimuli and slowest on incongruent stimuli. Participants seem to respond slightly faster in the positive valence level condition overall, than in the neutral valence level condition. These observations were confirmed by the results of a repeated measures ANOVA, with flanker stimulus type (congruent, control, incongruent) as the within-subjects variable and valence level/bin (negative, neutral, positive) as a between-subjects variable. The Greenhouse-Geisser correction is reported for flanker stimulus type because Mauchly’s Test of Sphericity was significant, 11.288, p = .004. There was Congruent Stimuli Control Stimuli Incongruent Stimuli M SD M SD M SD 547.90 93.51 549.09 95.92 574.26 85.92 87 a main effect of flanker stimulus type, F(1.787, 160.842) = 37.456, p < .001, η2= .294. Follow-up pairwise comparisons on each type of flanker stimulus revealed that participants were slower on incongruent stimuli (M = 573.50, 95%CI [556.16, 590.83]) than congruent (M = 547.48, 95%CI [528.42, 566.53], and control stimuli (M = 548.48, 95%CI [530.574, 566.386]), p < .001. The slowdown on incongruent stimuli is consistent with previous research using the Eriksen flanker task (Eriksen & Eriksen, 1974; Rowe et al., 2007). There was no effect due to valence level/bin, and importantly, no interaction between flanker stimulus type and valence level/bin. Based on the predictions of the Broaden-and-Build theory (e.g., Fredrickson, 2001; 2004) and the Affect-as-Information hypothesis (e.g., Gasper & Clore, 2002), I expected an interaction to occur whereby participants were slower to respond to the middle letter in incongruent stimuli than congruent and control stimuli in the positive valence level condition. Also, I expected participants to respond similarly fast to the middle letter in congruent, control and incongruent stimuli in the negative valence level condition. Guided by theoretical predictions, follow-up pair-wise comparisons comparing each of the flanker stimulus types in each valence level condition were conducted, but none were significant. The results suggest there is no influence of valence states on attention scope (e.g., Harmon-Jones, 2010;2012). 88 Figure 3. 8. Mean of median response time required for identifying the middle letter on congruent, control and incongruent flanker stimuli for each valence level condition. Error bars represent 95% confidence intervals. 3.3: Experiment 3 Conclusion The results of Experiment 3 indicate that the affect induction method is effective. This conclusion is evident based on Russell’s Affect Grid scores (Russell, 1989), and the BMIS scores (Mayer & Gaschke, 1988). Despite the effectiveness of the affect induction method, Experiment 3 did not show evidence of predicted relation between valence states and the scope of attention posited by the Broaden-and-Build theory (e.g., Fredrickson, 2004) and the Affect-as-Information Hypothesis (e.g., Gasper & Clore, 2002). The results of Experiments 1, 2 and 3 together provide evidence for the strong preliminary conclusion that valence states do not influence attention scope. One possibility as to why no influence of valence states on the scope of attention was found is that the valence states induced by the pictures were not strong enough to produce a change in attention scope. For example, viewing a picture of a landscape is not as strong as actually walking upon that landscape and experiencing it in person. 400 450 500 550 600 650 700 Congruent Control Incongruent Congruent Control Incongruent Congruent Control Incongruent Negative Negative Negative Neutral Neutral Neutral Positive Positive Positive Me an R es po ns e T im e ( ms ) Flanker Stimuli/ Valence Level Condition 89 It is possible that picture rating task interfered with the valence states induced by the pictures, however, I do not think this is the case. Post-experimental interviews with participants indicated that participants in the positive condition felt positive, while participants in the negative condition felt negative. Because of ethical concerns, it was not possible use pictures that were more negatively valenced. Each picture was carefully vetted before it was included in the experiment to ensure that they would be appropriate for all participants to view. Another possibility may be that the relationship between valence states and attention scope was not found in the previous experiments in my dissertation because it only occurs for specific types of positive and negative events. The Motivational Intensity theory recognizes that not all positive and negative valenced events are the same. Some positive events cause you to move towards them (e.g., a piece of cake), while others are not (e.g., a sunset). Some negative events cause you to move away from them (e.g., an angry dog), while others do not (e.g., death of a loved one) (e.g., Gable & Harmon-Jones, 2008; Gable & Harmon-Jones, 2010b). Experiment 4 explored the possibility that different types of valenced events—those associated with attraction and repulsion--- change attention scope. 90 Chapter 4: The Influence of Movement Propensity Sates on the Scope of Attention In contrast to expectations based on the Broaden-and-Build theory (e.g., Fredrickson, 2004) and the Affect-as-Information Hypothesis (e.g., Gasper & Clore, 2002), the evidence presented so far has failed to show that the positive valence states induced by positive pictures broaden attention scope, and the negative valence induced by negative pictures states narrow it. This chapter reports my fourth laboratory experiment and was primarily motivated by a refinement of the previous experiments. It is possible that valence states may influence on attention scope, but it may only occur for those events that have high movement propensity state associated with them. Experiment 4 examined the attention scope that accompanies positive-attractive states and negative-repulsive states. Valence and movement propensity are related but distinctly different concepts. Not all positively valenced events, and not all negatively valenced events are the same. The Motivational Intensity theory does a good job of recognizing differences between emotional events; some events, positive or negative, will trigger movement towards or away from an event, while others will not (e.g., Gable & Harmon-Jones, 2008a; 2010b). For example, an event that makes us feel sad (e.g., your dog passed away) is not associated with much movement. Events that make us feel disgusted (e.g., stepping in a pile of garbage) or terrified (e.g., a gun in your face) however, will trigger movement away. Similarly, a peaceful event (e.g., seeing a beautiful view) typically is not associated with much movement either towards or away, but a desirable event (e.g., seeing your best friend) will trigger movement towards it (e.g., Gable & Harmon- Jones, 2008a; 2010b). It is possible that valence states influence attention scope, but only when the valence event triggers movement towards or away from it. As in Chapter 1, I use the term attractive to refer to positive events that cause movement towards, and I use the term repulsive events to refer to negative events that cause movement away. 91 To conduct a valid test of the theoretical assumptions of how movement propensity and valence states influence the scope of attention, a method that establishes reliable movement towards and away is required. Toward this goal, in Experiment 4, participants were required to rate affective pictures, which were specifically selected by their approach and avoidance norms in the Nenki-Affective Picture System (NAPS) (Marchewka et al., 2014). Approach and avoidance are not necessarily synonymous with attraction and repulsion. A repulsive event involves a movement away such as repelling or driving away. An avoidance event involves simply staying away, keeping clear of, or leaving alone. The NAPS norms have been used in previous research to indicate the motivational direction associated with them (e.g., Tomczak & Zjawiony, 2018). I used a refined set of materials, to examine the possibility that specific types of valence states – those that are attractive and repulsive--- influence the scope of attention. The predictions of the valenced and movement propensity theories of attention scope were examined. Consistent with the Broaden-and-Build theory (e.g., Fredrickson, 2004) and the Affect-as- Information Hypothesis (e.g., Gasper & Clore, 2002), I hypothesized that relative to neutral pictures, participants would respond more slowly to incongruent stimuli than control and congruent stimuli after exposure to attractive pictures, and that they would respond equally fast to incongruent, control and congruent stimuli after exposure to repulsive pictures. By contrast, consistent with the Motivational Intensity theory (e.g., Gable & Harmon-Jones, 2010b), I hypothesized that participants would respond more slowly to incongruent stimuli than control and congruent stimuli following exposure to neutral pictures, but that they would respond equally fast to incongruent, control and congruent stimuli following exposure to attractive and repulsive pictures. 92 4.1: Method 4.1.1: Participants and Design The experiment had three within-subjects variables: motivation level/bin (attractive, neutral, repulsive), question type (repulsive, attractive), and flanker stimulus type (congruent, control, incongruent). The participants were 109 undergraduate students (79 women) from the University of British Columbia, recruited from the Department of Psychology Human Subject Pool. They received partial course credit for participating. The experiment was conducted with the approval of the University of British Columbia Behavioural Research Ethics Board. I conducted a power analysis as described for Experiment 2 and assumed the picture manipulations used for Experiment 4 (e.g., attraction versus repulsion; attraction versus neutral; repulsion versus neutral) would have only a small effect (d = .15). On this assumption, a power analysis using the G*Power computer program (Faul et al., 2007), indicated a total sample of 96 participants would be needed to detect a very small effect with .9 power using a repeated measures ANOVA with alpha set at .05. 4.1.2: Materials 4.1.2.1: Pictures Two hundred and ten colour pictures (70 from each motivation level/bin) were selected based on the avoid/approach and arousal norms. In the NAPS, each picture has normative data on valence, arousal, and avoid/approach collected from samples of men, of women and of the combined sample of men and women. The combined norms were used for selecting pictures for the present study (Marchewka et al., 2014). 93 In selecting pictures, approach/avoidance and arousal values were deliberately confounded. I chose this option because the database did not permit me to control arousal across the three approach/avoid levels, but it permitted me to manipulate arousal in opposition to approach/avoidance. Table 4.1 shows the selection criteria and the selected properties of the pictures used in Experiment 4. Pictures varied by avoid/approach ratings and were selected to fit into one of three possible motivation levels/bins: attractive, neutral, or repulsive. In the NAPS database, the attractive and repulsive pictures were chosen using the avoidance/approach column in the database, where a lower number indicates avoidance, and a higher number indicates approach. Ideally, I would have liked to control the level of arousal in the pictures, but it was not possible because of the constraints of the database (i.e., the norms associated with approach pictures were low in arousal; the norms associated with avoidance were high in arousal). Therefore, I systematically manipulated arousal and motivation level/bin of the pictures by using the arousal and avoid/approach norms in the NAPS database. The attractive pictures were selected to have a high approach rating and a low arousal rating; the neutral pictures were selected to have a medium approach rating and medium arousal ratings; the repulsive pictures were selected to have a high avoid rating and a high arousal rating. The selected pictures included animals (e.g., spiders, insects), landscapes (e.g., mountains with oceans, cityscapes) objects (e.g., a toy), people (e.g., a man in the street) and faces (e.g., an injury). Sexually explicit and culturally inappropriate, as well as particularly repulsive pictures were not selected. Each picture was saved as a 320 x 240 pixel .jpeg file. When displayed in the experiment, each picture subtended a visual angle of approximately 7.6° on its longer side. 94 Table 4. 2 Approach/Avoid and Arousal Ratings of the NAPS Picture Norms Used in Experiment 4. The Selection Criteria and the Properties of the Selected Pictures is Reported for Each Motivation Level/Bin. Picture Selection Criteria Properties of Selected Pictures Motivation Level/Bin Avoid/Approach Scale Arousal Scale Avoid/Approach Scale Arousal Scale Range Range M SD M SD Attractive 6.00 – 7.00 3.00 – 4.00 6.53 0.29 3.69 0.25 Neutral 4.50 – 5.50 4.50 – 5.50 5.01 0.14 4.98 0.13 Repulsive 3.00 – 4.00 6.00 – 7.00 3.47 0.29 6.48 0.29 4.1.2.2: Flanker Stimuli The flanker stimuli were constructed as described in Chapter 3, however, for this experiment, each stimulus was a string of 7 letters, rather than only 5 letters. 4.1.3: Procedure All participants were tested individually in a quiet room equipped with a desktop computer running E-Prime 2.0 (Psychology Software Tools, 2012). Each participant was guided through the consent process before signing the form and beginning the experiment. 4.1.3.1: Event Sequence The event sequences matched those in Experiment 3 (see Figure 3.1), except for two differences. One difference was the rating question participants were asked when presented with each picture. A G lo 95 second difference was when each flanker stimulus sequence began, participants were shown a fixation cross (*) for 250 or 750 ms before the next stimulus was presented. This change was made to disrupt anticipatory responding on the Eriksen flanker task (Eriksen & Eriksen, 1974). The experiment consisted of 2 blocks, each with 48 event sequences. A break occurred after the first block. The purpose of the break was to allow the participants to rest and for me to remind them of the task instructions. Participants pressed the letter ‘G’ on the keyboard when they were ready to proceed to the next block. The order of the attractive and repulsive question was counterbalanced across participants. On one block, participants were asked, “How attractive do you find this picture?”; and on the other block, participants were asked to rate, “How repulsive do you find this picture?” An 8-point scale was used for both questions. The rating scale endpoints were marked ‘Extremely Repulsive’ and ‘Extremely Attractive’ for the respective conditions. All parts of the scale were displayed in Arial font, each letter measuring about 0.95° visual angle. Participants were instructed that “Rating a picture as attractive indicates that you like it, desire it, and want to move towards it, while rating a picture as repulsive indicates you dislike it, hate it, and want to move away from it. People have different perceptions of pictures but what is important is your true perception of the picture so rate it in terms of what it means to you.” Participants were asked to respond, “According to your gut reaction, and in such a way that if you saw the picture again, you likely would rate it similarly”. As soon as participants responded, the next trial began. Within each event sequence, each picture was randomly chosen out of a total sample of 70 pictures from each motivation bin/level. Like Experiment 3, to practice the event sequences, participants completed 2 event sequences, each with 5 pictures and 6 flanker stimuli. 96 To end the experiment, participants completed a funnel interview. The purpose of the interview was to collect feedback on participants’ experiences in the experiment. Following the interview, participants were thoroughly debriefed. The experiment took place in one session lasting about 40 minutes. 4.2: Results and Discussion The primary goal of the present study was to test the assumption that the influence of valence states on attention scope occurs when they are attractive or repulsive. Based on the valence based theories of attention scope (e.g., Fredrickson, 2004; Gasper & Clore, 2002), if attention scope is broad, participants should respond slower to incongruent stimuli than control and congruent stimuli in the attractive picture condition, and if attention is narrow, participants should respond similarly quickly on incongruent, control and congruent stimuli in the repulsive picture condition. The main independent variable was the picture type in each motivation level and the question type given to participants. The dependent variables were the ratings and rating speeds on the picture task and performance accuracy and speed on the Eriksen flanker task (Eriksen & Eriksen, 1974). To make decisions about differences between means, 95% confidence intervals were used. When follow-up analyses were required, I use ANOVA. 4.2.1: Data Screening All data were screened for outliers. On the picture task, 1 participant had a mean median response time of 2352 ms, more than 3 standard deviations above the group mean of 1252 ms. On the Eriksen flanker task, 3 participants had a mean accuracy on congruent stimuli of 75%, 85% and 86%, respectively, more than 3 standard deviations below the group mean of 97%. On the Eriksen flanker task, 1 participant had a mean accuracy of 7% on incongruent stimuli, more than 3 standard deviations below the group mean of 94%. None of the data from these participants are included in the analyses reported below. The results reported below are based on the data of the remaining 103 participants. 97 4.2.2: Picture Task Performance Participants’ mean ratings of the pictures in the repulsive and attractive question condition are shown in Figure 4.1. The means indicate no difference due to the rating question type; that is, the question asked of participants (i.e., How attractive is this picture? / How repulsive is this picture?) did not impact the ratings There were large differences, however, between picture types. Participants gave the highest ratings to attractive pictures and the lowest ratings to repulsive pictures. These findings are roughly consistent with the avoid/approach ratings from the NAPS norms (e.g., Marchewka et al., 2014). There were two differences in participants' picture ratings compared to the NAPS norms (Marchewka et al., 2014). Participants gave lower ratings overall than what was indicated by the norms, and they rated repulsive pictures particularly low. One potential reason for the lower ratings may be that the question participants were asked in the experiment was different from the question that was asked when the norms were collected. Participants in this experiment were asked about the attractiveness and repulsiveness of the pictures. When the norms were collected, participants were asked about the approach and avoidance of the pictures. 98 Figure 4. 4. Mean picture ratings in the attractive and repulsive question condition for each motivation level condition in Experiment 4. The blue bars show the attractive question condition, and the orange bars show the repulsive question condition. Error bars are 95% confidence intervals. To determine whether participants were faster to rate the pictures in one motivation level condition than the others, the means of participants’ median picture rating times in each motivation level condition are shown in Figure 4.2. The means show that participants were faster to respond to repulsive pictures, than to neutral and attractive pictures. Repulsive pictures may have been easier to place on the scale than neutral or attractive pictures. The repulsive pictures may have elicited more affect in participants than the others because of the negativity bias, and therefore participants were more impacted by them (Baumeister et al., 2001). If participants were more impacted by the repulsive pictures, then it would take less time for participants to decide how the pictures made them feel. 1 2 3 4 5 6 7 8 Attractive Neutral Repisive Me an P ict ur e R ati ng (1 -8 ) Motivation Level Condition/ Question Condition Attractive Question Repulsive Question ulsive 99 Figure 4. 5. Mean picture rating time in each motivation level condition in Experiment 4. The blue bars show the attractive question condition, and the orange bars show the repulsive question condition. 4.2.3: Eriksen Flanker Task Performance 4.2.3.1: Performance Accuracy For each participant, I computed the mean accuracy of identifying the middle letters in congruent, control and incongruent stimuli. Overall mean accuracy was higher on congruent (M = 98%, SD = 0.02) and control stimuli (M = 97%, SD = 0.04), compared to incongruent stimuli (M = 94%, SD = 0.02). Accuracy in each motivation level condition did not differ; they are summarized in Table 4.2. The findings assuage concerns about a speed-accuracy trade-off in performance on the Eriksen flanker task (Schouten & Bekker 1967; Wickelgren 1977). 900 1000 1100 1200 1300 1400 1500 Attractive Neutral Repulsive Me an of M ed ian P ict ur e R ati ng T im e ( ms ) Motivation Level Condition/ Question Condition Attractive Question Repulsive Question 100 Table 4. 3 Mean Eriksen Flanker Task Accuracy on Congruent, Control and Incongruent Stimuli in Each Motivation Level Condition in Experiment 4. 4.4.4.3.2: Performance Speed For each participant, I computed the mean of the median response time required to identify the middle letter in congruent, control and incongruent stimuli. Overall mean response time was faster on congruent (M = 499.51, SD = 63.11) and control stimuli (M = 507.83, SD = 61.95) than incongruent stimuli (M = 537.21, SD = 61.42). The slower responses to incongruent stimuli are consistent with previous research using the Eriksen flanker task (Eriksen & Eriksen, 1974; Finucane, 2011; Rowe et al., 2007). The mean of the median response times on congruent, control and incongruent stimuli in each motivation level condition is shown in Figure 4.3. Participants were faster to identify the middle letter in congruent and control stimuli and slower on incongruent stimuli. The means indicate a similar pattern of speed across all the motivation level conditions. The results of a repeated measures ANOVA, with flanker stimulus type (congruent, control, incongruent) and motivation level/bin (attractive, neutral, repulsive) as within-subjects variables confirmed these observations. The Greenhouse-Geisser correction is reported for Motivation Level Condition Congruent Stimuli Control Stimuli Incongruent Stimuli M SD M SD M SD Attractive 98% 0.02 98% 0.03 94% 0.04 Neutral 97% 0.02 97% 0.03 94% 0.04 Repulsive 98% 0.02 98% 0.02 94% 0.05 101 flanker stimulus type because Mauchly’s Test of Sphericity was significant, 18.579, p < .001. There was no main effect of motivation level/bin or interaction between motivation level/bin and flanker stimulus type. There was a main effect of flanker stimulus type, F(1.708, 170.778) = 155.376, p < .001, η2= .608. Follow- up pairwise comparisons on each flanker stimulus type showed that participants were slower on incongruent stimuli (M = 536.87, 95%CI [524.86,548.885]), than congruent (M = 500.03, 95%CI [487.68, 512.37], p < .001 and control stimuli (M = 508.23, 95%CI [496.04, 520.51]), p < .001. Results are consistent with previous research using the Eriksen flanker task (e.g., Rowe et al., 2007). Despite the absence of an interaction, I used the data to explore the hypotheses that motivated this experiment. Consistent with the predictions of valenced based theories of attention scope (e.g., Fredrickson, 2004; Gasper & Clore, 2002), I wanted to examine if attention scope broadened in the attractive condition and narrowed in the repulsive condition. Follow-up pair-wise comparisons comparing each of the flanker stimulus types in each motivation level condition were conducted, but none were significant. 102 Figure 4. 6. Mean of median response time to identify the middle letter on congruent, control and incongruent stimuli in each motivation level condition in Experiment 4. Error bars represent 95% confidence intervals. 4.3: Experiment 4 Conclusion The picture ratings indicated that participants rated attractive and repulsive pictures in a manner that is consistent with the NAPS norms (Marchewka et al., 2014). Post-experimental interviews with participants indicated that participants felt positively after viewing attractive pictures and negatively after viewing repulsive pictures. The results showed no influence of positive attractive states or negative repulsive states on attention scope—a results that is consistent with the previous experiments in my dissertation. Consistent with the results of Experiments 2 and 3, all conditions show the same pattern of results. The results suggest that attention scope is broad in all conditions, and there is no evidence in any conditions of a narrow attention scope. 300 350 400 450 500 550 600 Congruent Control Incongruent Congruent Control Incongruent Congruent Control Incongruent Attractive Attractive Attractive Neutral Neutral Neutral Repulsive Repulsive Repulsive Me an R es po ns e T im e ( ms ) Flanker Stimuli/ Motivation Type 103 It is possible that the Eriksen flanker task (Eriksen & Eriksen, 1974) is not able to pick up changes in attention scope, and in particular show a pattern of results consistent with narrowed attention scope. It would be interesting to determine if the Eriksen flanker task (Eriksen & Eriksen, 1974) would show the predicted pattern of results when it is known prior to the task that attention scope is broad or narrow. A more direct manipulation of broad and narrow attention scope would be beneficial to determine if the Eriksen flanker task is responding as would be expected under these circumstances. My fifth and sixth experiments explored this methodological possibility. An alternative explanation for the fact that all conditions show evidence of broadening of attention scope (i.e., there is no difference in attention scope between conditions) is that the Eriksen flanker task (Eriksen & Eriksen, 1974) is not a valid measure of attention scope. This may be the case, at least in terms of the specific stimuli variations I have used so far in my dissertation. It may be that I have used specific variations of flanker stimuli that are not sensitive enough to pick up a change in attention scope. If attention scope is narrow, performance on the Eriksen flanker task is assumed not to differ among congruent, control and incongruent stimuli because only the middle letter is being attended to. If attention scope is broad, performance is expected to suffer most in the incongruent stimuli because this is where the most interference is expected because attention scope is attending to the middle letter and the outside letters in the letter string. It could be that only specific stimuli variations of the Eriksen flanker task are effective in picking up a broad and narrow attention scope. My fifth and sixth experiments also explored this possibility. 104 Chapter 5: The Validity of the Eriksen Flanker Task Four powerful experiments that used carefully normed picture stimuli have failed to show any evidence that different valence states influence the scope of visual attention. These experiments used a picture valence manipulation that was effective in creating a difference in self-reported valence states (i.e., positive, neutral & negative), and Experiment 4 showed ratings consistent with participants experiencing different movement propensities (i.e., attraction, neutral, and repulsion). In addition, performance on the Eriksen flanker task showed the expected interference effect (i.e., slower responding to middle letters in incongruent stimuli compared to middle letters in neutral stimuli, although there was no evidence of a facilitation effect (i.e., faster responding to middle letters in congruent stimuli compared to in neutral stimuli) (e.g., Roberts et al., 2010). This combination of findings suggests two possibilities that need careful consideration before reaching any conclusions about the theoretical claim that valence or movement propensity states influence the scope of attention: First, it is possible that the valence manipulation and the movement propensity manipulation did not have the predicted effect on attention, that is, they did not bring about a broadening or narrowing of attention. Second, it also is possible that for methodological reasons, neither the Navon task (Navon, 1977) nor the Eriksen flanker task (Eriksen & Eriksen, 1974) used in the preceding experiments are sufficiently sensitive to pick up the changes in attention scope that are brought about by the valence and movement propensity manipulations used in the preceding experiments. To investigate if Eriksen flanker task (Eriksen & Eriksen, 1974) performance shows the expected outcome when attention is allocated broadly versus narrowly, I directly manipulated the scope of attention in Experiment 5. Rather than manipulating the valence or the movement propensity of pictures to bring about a change in the scope of attention, I used a well-established method for inducing either a broad or narrow attention scope. Specifically, I used the Navon induction method developed by Goodhew and Plummer (2019): a broad or narrow attention scope is induced by having participants respond to a long 105 series of Navon letters. Across two experiments, Goodhew and Plummer (2019) showed that participants responded faster and more accurately to global letters when working with a series of mostly global Navon letter, and they responded faster to local letters when working with a series of mostly local Navon letters. Goodhew and Plummer concluded that their method was effective in inducing, respectively, a broad scope of attention and a narrow scope of attention. Experiment 5 also was an investigation of the Eriksen flanker task (Eriksen & Eriksen, 1974). This task measures attention scope by the extent of interference that is caused when processing the letters within a letter string (e.g., Goodhew, 2020). If attention scope is broad, it is assumed that participants will attend to and process the middle or target letter in a letter string but also the surrounding letters. Therefore, performance is expected to be poorer (i.e., slower, less accurate) on incongruent letter strings because of response competition. If attention scope is narrow, however, it is assumed that participants’ perceptual system picks up only the target in the letter string, and thus, performance is the same on all letter strings because there is no response competition. The ability of the Eriksen flanker task (Eriksen & Eriksen, 1974) to respond differently to broad versus narrow attention scopes is likely to be determined by the foveal size or visual angle of target letters and the letter strings. Eriksen flanker task performance is expected to show no difference in responding to targets in incongruent, control and congruent letter strings. However, for this outcome to occur it is necessary that when the attention scope narrow, the perceptual system will process only the target letter in each string. If the letters that make up each flanker letter string are too close to each other, it is possible that even when the attention scope is narrow, the perceptual system will pick up the target letter along with the surrounding letters. To explore this possibility, I manipulated the font size and the between-letter spacing of the flanker letter strings used in Experiment 5. 106 Experiment 5 was used to test the following hypotheses. On the Navon induction task (Goodhew & Plummer, 2019), I hypothesized that participants in the mostly global letter condition would respond faster to global letters than local letters and I hypothesized that this pattern of results would be reversed in the narrow attention induction condition. I used six flanker letter types (different in spacing and font size) for measuring attention scope in Experiment 5 and expected that with at least one these types, participants in the global condition would be slower to respond to the middle letter in incongruent stimuli than in congruent or control stimuli, and that participants in the narrow attention induction condition would respond similarly fast to target letters in all test conditions (i.e., incongruent, control, congruent). 5.1. Method 5.1.1: Design and Participants The experiment had two between-subjects variables: attention scope (broad, narrow) and flanker property type (font, spacing and constant visual angle). The combination of these variables created the six conditions listed in Table 5.1. Participants were randomly assigned to one of these conditions, for total of two hundred and forty-five participants (202 women). Participants were undergraduate students from the University of British Columbia, recruited from the Department of Psychology Human Subjects Pool. They received partial course credit for participating. The experiment was conducted with the approval of the University of British Columbia Behavioural Research Ethics Board. 107 Table 5. 2 The Between-Subjects Variables in Experiment 5 were the Attention Scope (Broad and Narrow) and Flanker Property Type (Font, Spacing and Constant Visual Angle). The table shows the number of participants in each condition. A power analysis was conducted to focus on that at least one flanker property type would show a 15 ms increase in responding to the middle letter in the letter of incongruent letter strings in the broad attention scope condition. The analysis was based on a small effect size (d = .15) and on this assumption, a power analysis using the G*Power computer program (Faul et al., 2007) indicated a total sample of 162 participants would be needed to detect a small effect with .99 power using a repeated measures ANOVA with alpha set at .05. 5.2.2: Materials 5.2.2.1: Navon Letters Eight Navon letters were adapted from Goodhew and Plummer (2019). Each consisted of a collection of component letters arranged into a configuration that outlined a large letter, as shown in Figure 5.1. The outline letter was an F, L, H or T, and the component letters also were Fs, Ls, Hs or Ts. The component letters were in Arial font. For the Navon induction task, participants were required to decide whether a stimulus outline is an L or T, or if is composed of Ls and Ts. If one of these letters is present in Attention Scope Flanker Property Type Font Letter Spacing Constant Visual Angle Narrow 41 (38 women) 41 (33 women) 42 (35 women) Broad 41 (30 women) 40 (36 women) 40 (37 women) 108 the outline (e.g., the stimuli on the right side of Figure 5.1), the stimulus is categorized as a global Navon letter type; if one of these letters is present as a component (e.g., the stimuli on the left side of Figure 1), the stimulus is categorized as a local Navon letter type. In the experiment, each Navon letter envelop had a 4.5° x 4.5° visual angle, and each component letter subtended a visual angle of 0.9° x 0.9°. Figure 5. 20. The Navon letters used in Experiment 5. The left side of the figure shows the H and F are the component letters that make up a large L or a T, which herein are identified as the global letters. The right side of the figure shows the Ls and Ts as components, which herein are called local letters. 5.2.2.2: Flanker Property Types Each flanker letter stimulus consisted of a row of 5 letters in Arial font, but they differed from each other in font size of the letters, and by the spacing between the letters. Three flanker property types had zero spacing between letters, with the letters in 26, 32 and 43 point-size, respectively. Two additional flanker property types had letters in 26-point font, but the letter spacing was either 1 (1 space between adjacent letters) or 2 (2 spaces between adjacent letters). A final flanker property type had letters in 32- point font spaced 1 apart. By these differences the font sizes and letter spacing, the flanker property types varied in the visual angle required, for example, for perceiving the target letter without any of the adjacent letters. The nine flanker variations are listed in Table 5.2. 109 For each flanker test letter string, three variations were needed, one each for the congruent, incongruent and control condition, respectively. Each stimulus consisted of a string with 5 letters, always the capital letters L, T or X. For the congruent stimuli, the string consisted either of all Ls (i.e., LLLLL) or all Ts (i.e., TTTTT). For the incongruent stimuli, the middle letter was different from the flanking letters (i.e., LLTLL; TTLTT). For the control stimuli, the middle letter was a T or an L, and the flanking letters were Xs (i.e., XXTXX; XXLXX). Table 5. 3. The Flanker Letter Strings used in Experiment 5, Which Differed in Font Size and in Letter Spacing. 5.2.2.3: Handedness Questionnaire A modified version of The Edinburgh Handedness Questionnaire (EHQ) was used as a filler task (Cohen, 2008; Oldfield, 1971). This questionnaire asks about the preferred hand for various activities, including writing, drawing, throwing, using scissors, a toothbrush, knife, spoon, broom, striking a match and opening a box. For each activity the EHQ asks, “Which hand do you prefer for that activity?” and “Do you ever use the other hand for that activity?” Participants indicate if they use their right hand, or left hand, or have no preference, or they ever use the other hand for the activity. Flanker Property Type Flanker Variations Font 26-point font, 0 space 32-point font, 0pace 43-point font, 0 space Spacing 26-point font, 0 space 26-point font, 1 space 26-point font, 2 spaces Constant Visual Angle 43-point font, 0 space 32-point font, 1 space 26-point font, 2 space 110 5.3: Procedure All participants were tested individually in a quiet room equipped with a desktop computer running E-Prime V2.0 (Psychology Software Tools, 2012). Each participant provided written and informed consent at the beginning of the experiment. 5.3.1: Event Sequence The experiment unfolded in a series of 12 event sequences, each composed of 80 Navon letters, followed by 6 Eriksen flaker stimuli. The specific timing within an event sequence is shown in Figure 5.2. All stimuli were in black and displayed in the center of the screen on a white background. At the onset of each of the 80 Navon letters, participants were shown a fixation cross (+) for 500 ms, which subtended a 0.1° x 0.1° visual angle. Then a Navon letter was displayed for 150 ms, followed by a blank screen that remained until the participant responded. As soon as the participant responded, the next trial began. For each Navon letter, the participants’ task was to decide if an L or a T was present on the stimulus just displayed. If the participants saw an L, they were asked to press the “l” on a QWERTY keyboard, and if participants saw a T, they were asked to press the “t” key. Participants were instructed to respond fast but as accurately as possible. To induce a broad attention scope, I used a primarily global set where 80% of the stimuli (64 trials) were global letters, to prime participants’ attention scope to the global level. To induce a narrow attention scope, I used a primarily local set where these percentages were switched (Goodhew & Plummer, 2019). All trials were randomly presented. To ensure participants stayed on task, a beep occurred if they responded inaccurately. Prior to the onset of the flanker stimuli, participants saw a fixation cross (i.e., +) for 500 ms, then a flanker stimulus type occurred, which consisted of a string of 5 letters. Participants had to respond L or T depending on what the middle letter was. Participants were asked to respond as quickly, but as accurately 111 as possible. For the first 3 flanker stimuli, there was 1 congruent, 1 incongruent and 1 control stimuli. The order of the three flanker stimuli was random. The same occurred for the last 3 flanker stimuli. Participants were asked to respond by pressing the “l” on a QWERTY keyboard if the middle letter was an L and the “t” if it was a T. Participants were asked to respond quickly and accurately as possible. The visual angle of the flanker stimuli varied, as described in Table 5.2. 5.3.2: Experiment Flow The 12 experimental sequences were arranged into two blocks, with 6 sequences in each. A break occurred after the first block. Following the first block, participants filled out the handedness questionnaire with paper and pencil. To continue to the second block, participants pressed the letter ‘G’ on the keyboard. The purpose of the break was to allow the participants to rest and remind them of the task instructions. To practice Navon induction task, participants completed one event sequence with 32 Navon letters, and they practiced the Eriksen flanker task (Eriksen & Eriksen, 1974) with 6 flanker stimuli. The Navon induction task was composed of 50% with global letters (16 trials) and 50% with local letters (16 trials), which were randomly presented to participants. This was done to familiarize participants with the task, and without inducing a broad or narrow attention scope (Goodhew & Plummer, 2019). Beeps occurred to alert participants to errors and remind them of the importance of accurate responses. If a beep occurred during practice, the participant was interrupted and instructions to be accurate were repeated. To end the experiment, participants were interviewed and debriefed. In the interview, participants were asked about what their experience was like completing the experiment. The experiment took place in one session lasting about 60 minutes. 112 Figure 5. 21. An example of an event sequence in Experiment 5. Each event sequence was composed 80 Navon letters to induce a broad or narrow attention scope followed by 6 flanker stimuli to measure attention scope. + LLTLL + XXLXX + + + TTTTT … until 80 Navon letters appeared * + + 500 ms 150 ms Until response + + + TTLTT XXTXX 113 5.4: Results and Discussion The goal of this study was to identify a letter string type for use with the Eriksen flanker task (Eriksen & Eriksen, 1974) that can pick up a broad attention scope and a narrow attention scope. I used Navon letters to induce an attention set that is spatially broad or narrow and then measured the induced set with variations of flanker stimuli. The main dependent variables were accuracy and speed on the Navon induction task (Goodhew & Plummer, 2019) and on the Eriksen flanker task. I used 95% confidence intervals for making decisions about differences between the means. When follow-up analyses were required, ANOVAs were conducted. 5.4.1: Data Screening All data were screened for outliers. One participant was excluded because of data recording errors. On the Navon induction task (Goodhew & Plummer, 2019), 2 participants had a mean median response time of 621 ms and 694 ms, more than 3 standard deviations above the sample mean of 338 ms. On the Eriksen flanker task (Eriksen & Eriksen, 1974), 4 participants had a mean median response time of 771 ms, 773 ms, 827 ms and 883 ms, respectively, more than 3 standard deviations above the sample mean of 512 ms. One of the latter participants was also an outlier on the Navon induction task. Next, I examined performance accuracy on the Eriksen flanker task because of concerns of a speed-accuracy trade-off (e.g., Wickelgreen, 1977): 26 participants were excluded because performance in one condition of the Eriksen flanker task was below 75% correct. None of the data from these participants were included in any of the analyses reported below. The results reported below are based on the remaining 212 participants. 5.4.2: Navon Induction Task Performance The Navon induction task required participants to decide about the presence of an L or T in a series of Navon letters, and these series consisted of either or mostly global letters or mostly local letters. 114 I calculated the mean accuracy and speed on the Navon induction task for each participant. The response time analysis was conducted using only accurate responses. For each participant, I computed the mean accuracy to respond to global and local letters, with separate scores for the broad and local attention induction conditions. The accuracy and response time results are presented in Figure 5.3. Accuracy on global and local letters was high indicating that participants followed instructions. The figure shows that as expected decision accuracy was higher on global letters in the global attention induction condition, and on local letters in the narrow attention induction condition. The figure shows that decisions were made faster on global letters in the global attention induction condition, and on local letters in the local attention induction condition. This pattern of results provides evidence of an attentional set induction effect (Goodhew & Plummer, 2019); it suggests that the task was successful in inducing a broad attention scope in the broad attention induction condition and narrow attention scope in the narrow attention induction condition. The 125 ms induction effect in both the broad and narrow attention induction conditions is slightly larger than in previous studies using this method (Goodhew & Plummer, 2019), but it was similar across all flanker property type conditions (see Appendix A). 115 Figure 5. 22. Mean of median Navon induction task response time and accuracy on global and local letters in the broad and narrow attention induction conditions. The blue bars are response time means, and the orange line shows mean performance accuracy. Error bars represent the 95% confidence intervals. 5.4.3: Eriksen Flanker Task Performance During debriefing, many participants commented that the experiment was long and tiring. Therefore, I examined Eriksen flanker task performance separately for only the first half of the experiment. For each participant, I computed the mean accuracy to identify the middle letter on each of the three flanker stimulus types (i.e., congruent, incongruent and control) in the broad and narrow attention induction conditions. The means are displayed in Figure 5.4. The figure shows that participants were most accurate on congruent stimuli (M = 99%, 95% CI [99%, 99%]), followed by control (M = 98% ms, 95% CI [97%, 98%]) and incongruent stimuli (M = 91%, 95% CI [90%, 93%]). For each participant, I then computed the mean median response time required to identify the middle letter in the congruent, incongruent and control stimuli. Only data from correct trials were used for this purpose. Figure 5.2 shows that participants were 90 91 92 93 94 95 96 97 98 99 100 0 100 200 300 400 500 600 Global Letters Local Letters Global Letters Local Letters Global Condition Local Condition Ac cu ra cy (% ) Me an R es po ns e T im e ( ms ) Response Time Accuracy Br ad iti Narrow Condition 116 fastest on congruent stimuli, followed by control, and incongruent stimuli. The magnitude of this effect is consistent with previous research (e.g., Lamers & Roelofs, 2011). Figure 5. 23. Mean of median Navon Task performance on congruent, control and incongruent stimuli on the first half of Experiment 5. The blue bars are response time, and the orange line is accuracy. Error bars represent the 95% confidence intervals. Participants commented that the experiment was very long. Thus, because of worries that performance might have changed in the course of the experiment, I did two separate analyses, one with the data from the first half of the flanker stimuli and the other with the data from the second half. I computed the overall mean accuracy to identify the middle letter in the congruent, incongruent and control stimuli in the first half and second half of the flanker stimuli. The means are displayed in Figure 5.5. The figure shows that on the first half of the flanker stimuli, participants were more accurate on congruent stimuli (M = 99%, 95% CI [99%, 100%]) and control stimuli (M = 98% ms, 95% CI [97%, 99%]) than on incongruent stimuli (M = 92%, 95% CI [90%, 94%]) trials. The figure shows that on the second half of the flanker stimuli, 80 82 84 86 88 90 92 94 96 98 100 0 100 200 300 400 500 600 Congruent Control Incongruent Me an A cc ur ac y ( % ) Me an R es po ns e T im e ( ms ) Response Time Accuracy 117 participants were more accurate on congruent stimuli (M = 99%, 95% CI [99%, 100%]) and control stimuli (M = 98% ms, 95% CI [97%, 99%]) compared to incongruent stimuli (M = 92%, 95% CI [90%, 94%]). Henceforth, I refer to the first half of flanker stimuli as the first set, and the second half of flanker stimuli as the second set. The accuracy on incongruent stimuli is slightly lower than in previous research (e.g., Servant & Logan, 2019). It is possible that participants responded slightly less accurately to incongruent stimuli in particular because of mental fatigue caused by the previous Navon induction task. During debriefing, some participants expressed they were tired by the time the flanker task occurred. For each participant, I computed the mean median response time to identify the middle letter in the congruent, incongruent and control stimuli on the first and second set of flanker stimuli. Only data from accurate trials were used for the analyses. The figure shows that on the first set, participants were fastest to identify the middle letter on congruent stimuli, followed by control and incongruent stimuli. The figure shows the same pattern on the second set, but participants were faster to respond to the middle letter on the second set. It is possible that participants were faster on the second set because they were more used to the task, by the time the last three flanker stimuli occurred. The means are also displayed in Figure 5.5. 118 Figure 5. 24. Mean of median Eriksen flanker task response time and accuracy to identify the middle letter on the first and second set of congruent, control and incongruent stimuli in the first half of Experiment 5. The blue bars are response time, and the orange line is accuracy. Error bars represent the 95% confidence intervals. Using the data from all the flanker type conditions combined, I computed the mean median response time required to identify the middle letter of the first half of the experiment on congruent, control and incongruent stimuli that followed letters in the broad attention induction condition or the narrow attention induction condition. Only accurate trials were used in the analyses. The means are displayed in Figure 5.6. The means show that participants in the broad and narrow attention scope conditions show evidence of a slow down on incongruent stimuli and a speed up on congruent stimuli, relative to control stimuli. When participants are faster on congruent stimuli than control stimuli, I call this a facilitation effect. When participants are slower on incongruent stimuli than control stimuli, I call this an interference effect. The narrow attention scope condition shows an interference effect that is like the broad attention scope 80 82 84 86 88 90 92 94 96 98 100 0 100 200 300 400 500 600 700 Congruent Control Incongruent Congruent Control Incongruent First Set Second Set Me an A cc ur ac y ( % ) Me an R es po ns e T im e ( ms ) Response Time Accuracy 119 condition. The same analysis was conducted on the first and second set of congruent, control and incongruent stimuli and a similar pattern was found. Figure 5. 25. Mean of median response time in the broad and narrow attention induction conditions on the first set of congruent, control and incongruent stimuli using the combined data from all flanker type conditions in Experiment 5. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals. I wanted to determine if one of the specific flanker property types show a different pattern of responding in the broad and narrow attention scope conditions. I did a response time analysis using data from correct trials only. The means are displayed in Figure 5.7. The means show that there is little difference between among any of the flanker property type conditions. Flanker Stimuli 120 Figure 5. 26. Mean of the median response time in the broad and narrow attention induction conditions for each flanker property type (font, spacing and visual angle) on congruent, control and incongruent stimuli in Experiment 5. The red bars show data from the broad attention scope condition, and the blue bars show data from the narrow attention scope condition Error bars represent the 95% confidence intervals. 300 350 400 450 500 550 600 650 700 750 800 Co ng ru en t Co nt ro l Inc on gr ue nt Co ng ru en t Co nt ro l Inc on gr ue nt Co ng ru en t Co nt ro l Inc on gr ue nt Font Spacing Constant Visual Angle Me an R es po ns e T Im e ( ms ) Flanker Stimuli/ Flanker Property 121 5.4.3: Performance in Each Flanker Variations in the Broad and Narrow Attention Scope Conditions I wanted to determine if one of the specific flanker variations shows a different pattern of responding in the broad and narrow attention scope conditions. To further explore the possibility, response time analysis was conducted on each of the nine specific flanker variations. 5.4.3.1: Font To determine if a different pattern of responding occurred in the broad and narrow attention scope conditions, a specific analysis was conducted on each of the three flanker variations within the font flanker property type (i.e., 26-point font, 0 space; 32-point font, 0 space; 43-point font, 0 space). Panel 5.8.1 and 5.8.3 show similar patterns. For 26-point font, 0 space and 43-point font, 0 space, there is a large difference between incongruent stimuli and the average of congruent and control stimuli. By contrast, Panel 5.8.2 shows a different pattern. For 32-point font, 0 space, there is a large difference between incongruent and the average of control and congruent stimuli, but only in the broad attention scope condition. The difference is smaller in the narrow attention scope condition. This pattern of results is in the right direction, but the interaction between the broad and narrow attention scope is not significant. This likely is because of variability in the data (see Appendix B) 122 Figure 5. 27. Mean of median response time on the Eriksen flanker task on the first half of Experiment 5 on congruent, incongruent flanker stimulus types in all flanker variations of font. Each graph shows the specific flanker variation. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals. 123 5.4.3.2: Letter Spacing To determine if a different pattern of responding occurred in the broad and narrow attention scope conditions, a specific analysis was conducted on each of the three flanker variations within the letter spacing flanker property type (i.e., e., 26-point font, 0 space; 26-point font, 1 space; 26-point font, 2 spaces). Panel 5.9.1 shows a difference between incongruent and the average control and congruent stimuli in the broad attention scope condition, but the difference is even larger in the narrow attention scope condition. Panels 5.9.2 and 5.9.3 show a similar pattern of results, there is a small difference between incongruent stimuli and the average of congruent and control stimuli in the broad attention scope condition. There is no difference between congruent and incongruent stimuli in the narrow attention scope condition. The pattern of results for Panel 5.9.2 and 5.9.3 is in the right direction, but the interaction between the broad and narrow attention scope condition is not significant. This likely is because of variability in the data (see Appendix B) 124 Figure 5. 28. Mean of median response time on the Eriksen flanker task on the first half of Experiment 5 on congruent, incongruent and control flanker stimulus types in all flanker variations of spacing. Each graph shows the specific flanker variation. The red bars show the data from the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals. 125 5.4.3.3: Constant Visual Angle To determine if a different pattern of responding occurred in the broad and narrow attention scope conditions, a specific analysis was conducted on each of the three flanker variations within the letter spacing flanker property type (i.e., e., 26-point font, 0 space; 26-point font, 1 space; 26-point font, 2 spaces). Panel 5.10.1 and Panel 5.10.2 show a similar pattern of results. In both panels, there is no difference between incongruent and the average control and congruent stimuli in the broad attention scope condition. Also, in the narrow attention scope condition, there is a small difference between incongruent and the average control and congruent stimuli in the broad attention scope condition. In contrast, Panel 5.10.3 shows a different pattern of results. There is a large difference between the incongruent stimuli and the average of the control and congruent stimuli, and in the narrow attention scope condition, there is no difference between control and incongruent stimuli. The data in Panel 5.10.3 is in the right direction, but the interaction between the broad and narrow attention scope condition is not significant. This likely is because of variability in the data (see Appendix B). 126 Figure 5. 29. Mean of median response time on the Eriksen flanker task on the first half of Experiment 5 on congruent, incongruent and control flanker stimulus types in all flanker variations of constant visual angle. Each graph shows the specific flanker variation. The red bars are the broad attention induction condition, and the blue bars are the narrow attention induction condition. Error bars represent the 95% confidence intervals. 127 5.5. Experiment 5 Interim Conclusion The results of Experiment 5 indicate that with the use of specific flanker stimulus types, results showed a pattern of performance that was expected if attention scope is made narrow or broad, respectively. The most promising Eriksen flanker task stimulus variations were: 26-point font, 1 space; 26- point font, 2 space; 32-point font, 0 space; and 43-pont font, 0 space. These flanker stimulus variations were used in Experiment 6. 5.6. Experiment 6 The purpose of Experiment 6 was to replicate those of Experiment 5 with a modification to the instructions given to participants. Specifically, in Experiment 6, changes were made to the instructions on the Eriksen flanker task (Eriksen & Eriksen, 1974) to emphasize accuracy. This change to instructions was made because accuracy on flanker stimuli was low in Experiment 5. Four variations of flanker property type were used in this experiment. 5.6.1: Design and Participants The experiment had induced attention scope (i.e., broad, narrow) and flanker property types (i.e., spacing, font) as between-subjects variables. The specific flanker variations in the spacing condition were 26-point font, 1 space; 26-point font, 2 space. The specific flanker variations in the font condition were 32- point font, 0 space; and 43-pont font, 0 space. The same induction method used in Experiment 5 was used in Experiment 6. Flanker property types had two levels: font and spacing. The combination of these variables created four conditions: broad spacing, broad font, narrow spacing, and narrow font. Participants were semi-randomly assigned to these conditions, achieving a final count of 204 participants (150 women): There were 49 participants (36 women) in the broad spacing condition, 51 participants (37 women) in the broad font condition, there were 48 participants (36 women) in the narrow spacing condition, 56 participants 128 (43 women) in the narrow font condition. Participants were undergraduate students from the University of British Columbia were recruited from the Paid Studies List. The experiment was conducted with the approval of the University of British Columbia Behavioural Research Ethics Board. Students participated in the experiment in return for a $20 gift card. 5.6.1: Materials 5.6.1.1: Navon Letters I created a new set of stimuli that were all straight letters that were symmetrical, the purpose of which was so that the fixation point that appeared in the center of the screen always appeared in the middle of the letter. In Experiment 5, the letter L for example, is not symmetrical and participants may not have looked at the fixation point when it appeared. Eight Navon letters were adapted from Goodhew & Plummer (2019). Each Navon letter is a large letter – A, H, X or V, that is composed of smaller letters (also A, H, X, or V). They have two types: the identity of the large letter and identity of the small letter. Participants had to look for A or H. For four stimuli, A or H was present at the global level and in four stimuli the A or H was present at the local level. Each Navon letter is a large letter – A, H, X or V, that is composed of smaller letters (also A, H, X, or V) as shown in Figure 5.11. They have two types: the identity of the large letter and identity of the small letter. Participants had to look for A or H. For four stimuli, A or H was present at the global level and in four stimuli the A or H was present at the local level. Local letters were presented in Arial font. Each of the global letters subtended a 4.5° x 4.5° visual angle, and each local letter subtended a 0.9° x 0.9° visual angle. Local letters were presented in Arial font. Each of the global letters subtended a 4.5° x 4.5° visual angle, and each local letter subtended a 0.9° x 0.9° visual angle. 129 Figure 5. 30. Navon letter types used in Experiment 6. For the local Navon letter, the A and H are the small letters that make up the shape of an X or a V (left). For the global Navon letter, the A and H are the small letters that make up the shape of an X or a V (left). 5.6.1.2: Flanker Property Types The same four specific flanker variations that showed a promising pattern of results in Experiment 5 were used (0 space; 26-point font, 1 space; 26-point font, 2 spaces; 32-point font, 0 space; 43-point font, 0 space). For each flanker test letter string, three variations were needed, one each for the congruent, incongruent and control condition, respectively. Each stimulus consisted of a string with 5 letters, always the capital letters A, H or X. For the congruent stimuli, the string consisted either of all As (i.e., AAAAA) or all Hs (i.e., HHHHH). For the incongruent stimuli, the middle letter was different from the flanking letters (i.e., AAHAA; HHAHH). For the control stimuli, the middle letter was an A or an H, and the flanking letters were Xs (i.e., XXAXX; XXHXX). 5.7: Procedure The procedure was identical to Experiment 5 except there were two differences. One difference occurred because of the COVID-19 pandemic, and thus, the experiment was run online through E-Prime Go (Psychology Software, 2021). For the experiment, I created and joined a Zoom session with each 130 participant, with the participants on a desktop or laptop computer in a quiet room of their own choosing. Each participant provided written and informed consent at the beginning of the experiment. A second difference is that I used only 8 event sequences to 8, with each arranged exactly as described in the Method of Experiment 5. 5.8: Results and Discussion The goal of this study was to replicate the difference due to the attention scope manipulation on flanker task performance, which Experiment 5 showed for the four specific flanker stimuli variations used in Experiment 6. To make decisions about differences between means 95% confidence intervals were used. When follow up analysis was required, ANOVAs were conducted. 5.8.1: Data Preparation The data were screened for outliers. One participant was deleted because of a data recording error. On the Navon induction task, 2 participants had a mean median response time of 681 ms and 1212 ms, more than 3 standard deviations above the group mean of 335 ms. On the Eriksen flanker task, 2 participants had a mean response time of 933 ms and 1004 ms, respectively, on control stimuli, more than 3 standard deviations above the group mean of 522 ms. These were the same 2 participants who were excluded on the Navon induction task. Next, I examined performance accuracy on the Eriksen flanker task because of concerns of a speed-accuracy trade-off (e.g., Wickelgreen, 1977): 14 participants were excluded because performance in one condition of the Eriksen flanker task was below 75% correct. None of the data from these participants were included in any of the analyses reported below. The results reported below are based on the remaining 187 participants. Despite shortening the experiment from 12 to 8 event sequences in Experiment 6, during debriefing participants expressed that they were extremely fatigued after the first half of the experiment. 131 Perhaps this fatigue was increased because participants completed the experiment in their own home through video conference, rather than in the lab. During the post-experimental interview, participants expressed that they stopped attending to the tasks in the second half of the experiment. Participants particularly expressed they were tired by the time the Eriksen flanker task (Eriksen & Eriksen, 1974) occurred because it always occurred after a long sequence of Navon letters. Participants fatigue and accurate responding was a concern and therefore, analyses conducted are on the first half of the experiment. 5.8.2: Navon Induction Task Performance I calculated the mean accuracy and speed on the Navon induction task for each participant from the first half of the experiment. The response time analysis was conducted using only accurate responses. For each participant, I computed the mean accuracy to respond to global and local letters, with separate analysis for the broad and narrow attention induction conditions. The accuracy and response time results are presented in Figure 5.12. Accuracy on global and local letters was high indicating that participants have heeded instructions. The figure shows that decision accuracy was higher on global letters in the broad attention induction condition, and on local letters in the narrow attention induction condition. The figure shows that decisions were made faster on global letters in the broad attention induction condition, and on local letters in the narrow attention induction condition. This pattern of results replicates (Goodhew & Plummer, 2019) as well as my findings in Experiment 5, suggesting that the task successfully induced a broad attention scope in the broad attention induction condition and narrow attention scope in the narrow attention induction condition. 132 Figure 5. 31. Mean accuracy for global and local trials in the Navon induction task for the broad and narrow attention induction conditions in Experiment 6. The blue bars are response time, and the orange line is accuracy. Error bars represent the 95% confidence intervals. I computed the mean median flanker stimuli response time and accuracy on congruent, control and incongruent stimuli, using the data from the first half of the experiment. The means are displayed in Figure 5.13. The figure shows that participants were most accurate on congruent stimuli, followed by control and incongruent stimuli. For each participant, I computed the mean median response time to identify the middle letter in the congruent, incongruent and control stimuli. Only data from correct trials were used. The figure shows that participants were about equally fast on congruent and control stimuli, and slower on incongruent stimuli, replicating the outcome of previous research (e.g., Lamers & Roelofs, 2011). 133 Figure 5. 32. Mean of median Eriksen flanker Task response time and accuracy on congruent, control and incongruent stimuli in the first half of Experiment 6. The blue bars are response time, and the orange line is accuracy. Error bars represent the 95% confidence intervals. I combined the data from all four specific flanker variations, to compute the mean median response time required to identify the middle letter of congruent, control and incongruent stimuli in the broad and narrow attention scope conditions in the first half of the experiment. Only correct trials were used in the analyses. The means are displayed in Figure 5.14. In the broad attention scope condition, participants were fastest on congruent stimuli followed by control stimuli, and were slowest on incongruent stimuli, showing an interference effect. In the narrow attention scope condition, the pattern of results was similar. 80 85 90 95 100 0 100 200 300 400 500 600 Congruent Control Incongruent Me an A cc ur ac y ( % ) Me an R es po ns e T im e ( ms ) Flanker Stimuli Response Time Accuracy 134 Figure 5. 33. Mean of median Eriksen flanker task response time to identify the middle letter on the congruent, control and incongruent stimuli in the first half of Experiment 6 in the broad and narrow attention induction conditions. The red bars are the broad attention induction condition, and the blue bars are the narrow attention induction condition. Error bars represent the 95% confidence intervals. I combined the data of each flanker property type, the purpose of which was to test the hypothesis that any of the two flanker letter types could be used to reveal a difference in performance between a broad and narrow attention scope. The means are displayed in Figure 5.15. For the font property type, the pattern of results is similar for the broad and narrow attention scope conditions. Participants are slower to respond to the middle letter in incongruent stimuli than congruent and control stimuli. For the spacing property type, participants in the broad attention scope condition are slower to respond to the middle letter on incongruent stimuli than congruent or control stimuli. Participants in the narrow attention scope condition are experiencing less interference on incongruent stimuli. These observations were confirmed by a repeated measures ANOVA with flanker stimulus type (congruent, control, and incongruent) as a within-subjects variable and attention scope condition (broad, narrow) and flanker property type (font, spacing) as 300 350 400 450 500 550 600 Congruent Control Incongruent Me an R es po ns e T im e ( ms ) Flanker Stimuli 135 between-subjects variables. Mauchly’s test of sphericity was significant for flanker stimulus type indicating that sphericity is violated, χ2(2) = 11.065, p = .004, and therefore, the Greenhouse-Geisser correction is reported. The analysis revealed a main effect of flanker stimulus type, F(1.889, 345.61) = 92.83, p < .001, η2= .337. Follow-up pairwise comparisons revealed that participants were slower to identify the middle letter in incongruent stimuli (M = 566.68 ms, 95% CI [551.40 ms, 581.96 ms]) than in congruent stimuli, (M = 490.33 ms, 95% CI [476.31 ms, 504.36 ms]), p < .001, and control stimuli (M = 519.54 ms, 95% CI [504.27, 534.83 ms]. Participants were also faster to identify the middle letter in congruent than control stimuli, p < .01. The flanker stimulus type by attention scope condition interaction was significant, F(1.889, 345.61) = 5.541, p =.005. Follow-up pairwise comparisons were conducted, and none were significant. The flanker stimulus type by flanker property type interaction was not significant, nor was the interaction between flanker stimulus type, flanker property type and attention scope. 136 Figure 5. 34. Mean of median Eriksen flanker response time on the congruent, control and incongruent stimuli in the first half of Experiment 6 for the broad and narrow attention scope conditions. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals. 5.8.3: Performance in Each of the Specific Flanker Variations in the Broad and Narrow Attention Scope Conditions in the First Half of Experiment 300 350 400 450 500 550 600 650 700 Co ng ru en t Co nt ro l Inc on gr ue nt Co ng ru en t Co nt ro l Inc on gr ue nt Co ng ru en t Co nt ro l Inc on gr ue nt Co ng ru en t Co nt ro l Inc on gr ue nt Global Global Global Local Local Local Global Global Global Local Local Local Font Spacing Me an R es po ns e T im e ( ms ) Flanker Property/ Attention Scope Condition Broad Condition Font Property Type Broad Condition Spacing Property Narrow Condition Spacing Property Broad Condition Font Property Narrow Condition Font Property 137 I conducted separate analysis on each of the four specific flanker variations, the purpose of which was to test the hypothesis that any of the four flanker letter types could be used to reveal a difference in performance between a broad attention scope and a narrow attention scope. 5.8.3.1: Flanker Letters Varying in Font I analyzed flanker letters varying in font. Figure 5.16 shows 32-point font, 0 space and Figure 5.17 shows 43-point font, 0 space. The means show that for 32-point font, 0 space, in the broad attention scope condition, participants were slower on incongruent stimuli than control stimuli—an interference effect. Also, participants were faster on congruent stimuli than control stimuli-- a facilitation effect. In the narrow attention scope condition, the means show the same pattern of results. These observations were confirmed by a repeated measures ANOVA with flanker stimulus type (congruent, control, and incongruent) as a within-subjects variable and attention scope condition (broad, narrow) as a between-subjects variable. The analysis revealed a main effect of flanker stimulus type, F(2, 208) = 17.93, p < .001, η2= .147. Follow-up pairwise comparisons revealed that participants were slower to identify the middle letter in incongruent stimuli (M = 576.51 ms, 95% CI [552.29 ms, 600.74 ms]) than in congruent stimuli, (M = 504.68 ms, 95% CI [483.59 ms, 525.76 ms]), p < .001, and control stimuli (M = 548.26 ms, 95% CI [521.81, 574.71 ms]. Participants were also faster to identify the middle letter in congruent than control stimuli, p < .022. There was no interaction between flanker stimulus type and attention scope condition for the 32-point font, 0 space flanker variation. These results of the 32-point font, 0 space specific flanker variation replicate the results of Experiment 5. 138 Figure 5. 35. Mean of median response time on the Eriksen flanker task in the first half of Experiment 6 to identify the middle letter on congruent, incongruent and control stimuli in the broad and narrow attention scope conditions. This figure shows the 32-point font, 0 space flanker variation. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals. The means show that for 43-point font, 0 space, in the broad attention induction condition, there is an interference effect: Participants were slower on incongruent stimuli than control stimuli. There was also evidence of a facilitation effect: Participants were faster on congruent stimuli than control stimuli. In the narrow attention induction condition, the means show a similar pattern: There is an interference effect and a facilitation effect. There is no evidence of narrow attention scope in the narrow attention induction condition. These observations were confirmed by a repeated measures ANOVA with flanker stimulus type (congruent, control, and incongruent) as a within-subjects variable and attention scope condition (broad, narrow) as a between-subjects variable. The analysis revealed a main effect of flanker stimulus type, F(2, 208) = 21.679, p < .001, η2= .172. Follow-up pairwise comparisons showed that participants were slower 300 350 400 450 500 550 600 650 700 Congruent Control Incongruent Congruent Control Incongruent Broad Condition Broad Condition Broad Condition Narrow Condition Narrow Conditon Narrow Condition Me an R es po ns e T im e ( ms ) Flanker Stimuli/ Attention Scope Condition 32-Point Font, 0 Space 139 on incongruent trials (M = 580.91, 95%CI [557.14,604.66]), than congruent (M = 508.17, 95%CI [484.13,532.22], p < .001 and control trials (M = 548.68, 95%CI [517.69, 567.68]), p < .001. There was no interaction between flanker stimulus type and attention scope condition for the 43-point font, 0 space variation of flanker variation. These results replicate those of Experiment 5. Figure 5. 36. Mean of median response time on the Eriksen flanker task in the first half of Experiment 6 to identify the middle letter on congruent, incongruent and control stimuli in the broad and narrow attention induction conditions. This figure shows the 43-point font, 0 space flanker variation. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals. 5.8.3.2: Flanker Letter Varying in Spacing To reveal a difference in performance between a broad and a narrow attention scope, specific analysis was conducted on each of the two flanker letters varying in spacing (i.e., 26-point font, 1 space; 26-point font, 2 space). Figure 5.18 shows 26-point font, 1 space and Figure 5.19 shows 26-point font, 2 space. 300 350 400 450 500 550 600 650 700 Congruent Control Incongruent Congruent Control Incongruent Broad Condition Broad Condition Broad Condition Narrow Condition Narrow Conditon Narrow Condition Me an R es po ns e T im e ( ms ) Flanker Stimuli/ Attention Scope Condition 43-Point Font, 0 Space 140 The results of the 26-point font, 1 space flanker variation shows that participants were faster in the narrow attention induction condition than the broad attention induction condition and participants in the narrow attention induction condition experienced less interference on incongruent stimuli than those in the broad attention induction condition. These observations were confirmed with a repeated measures ANOVA with flanker stimulus type (congruent, control, incongruent) as a within-subjects variable and attention scope condition (broad, narrow) as a between-subjects variable. The ANOVA on 26-point font, one space revealed a main effect of flanker stimulus type, F(2. 196) = 44.887, p < .001, η2= .314. Pairwise comparisons showed that participants were slower on incongruent trials (M = 584.06, 95%CI [555.79,612.33]), than congruent (M = 488.26, 95%CI [464.20, 555.33], p < .001 and control stimuli (M = 527.98, 95%CI [500.64, 520.51]), p < .001. There was also a flanker stimulus type by attention scope condition interaction, F(2, 196) = 3.204, p = .043. η2= .032. In the broad attention scope condition, participants were slowest on incongruent stimuli (M = 614.09, 95%CI [576.16, 652.03]) compared to congruent stimuli (M = 512.75, 95%CI [480.46, 545.03]), p < .001, and control stimuli (M = 533.49, 95%CI [486.80, 470.18]), p = .001, which did not differ from one another. In the narrow attention scope condition, participants were slower on incongruent stimuli (M = 558.79, 95%CI [537.05, 508.53]) than congruent trials (M = 487.52, 95%CI [467.54, 507.49]), p < .001, and control stimuli (M = 530.12, 95%CI [508.40, 551.85]), p = .001. In the narrow attention scope condition, participants responded to middle letter faster on congruent stimuli (M = 463.78, 95%CI [428.09, 499.47]) than incongruent stimuli (M = 554.03, 95%CI [512.10, 595,97]), p < .001, and control stimuli (M = 522.48 95%CI [481.91, 563.04]), p = < .001, but there was no difference in response time to identify the middle letter in incongruent and control stimuli. These results are like what would be expected if attention scope was narrow in the narrow attention induction condition. Participants are not experiencing as much interference on the incongruent stimuli in the narrow 141 attention scope condition than in the broad attention scope condition. Figure 5. 37. Mean of median response time on the Eriksen flanker task on the first half of Experiment 6 to identify the middle letter on congruent, incongruent and control stimuli in the broad and narrow attention scope conditions. This figure shows the 26-point font, 1 space flanker variation. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals. The results of the 26-point font, 2 space flanker variation shows that participants were faster in the narrow attention scope condition than the broad attention scope condition and participants in the narrow attention condition experienced less interference on incongruent stimuli than those in the broad attention scope condition. These observations were confirmed with a repeated measures ANOVA with flanker stimulus type (congruent, control, incongruent) as a within-subjects variable and attention scope condition (broad, narrow) as a between-subjects variable. The results revealed a main effect of flanker stimulus type, F(2, 196) = 13.674, p < .001, η2= .314. Follow-up pairwise comparisons showed that participants were slower on incongruent stimuli (M = 543.65, 95%CI [517.73,568.57]), than congruent (M = 490.09, 95%CI 300 350 400 450 500 550 600 650 700 Congruent Control Incongruent Congruent Control Incongruent Broad Condition Broad Condition Broad Condition Narrow Condition Narrow Conditon Narrow Condition Me an R es po ns e T im e ( ms ) Flanker Stimuli/ Attention Scope Condition 26-point Font, 1 Space 142 [464.08, 516.11], p < .001 and control stimuli (M = 511.51, 95%CI [490.07, 532.94]), p < .001. The flanker stimulus type by attention scope condition interaction was significant, F(2, 196) = 5.90, p = .003, η2= .057. Follow-up pairwise comparisons revealed that participants in the broad attention scope condition, participants were slower to respond to the middle letter on incongruent stimuli (M = 580.61, 95%CI [545.83, 615.39]) compared to congruent (M = 507.84, 95%CI [472.93, 542.74]), p < .001, and control stimuli (M = 513.09, 95%CI [484.34, 541.85]), p = < .001, which did not differ from one another. In the narrow attention scope condition, participants were faster on congruent stimuli (M = 472.34, 95%CI [433.76, 510.93]) than control (M = 509.92, 95%CI [478.13, 541.71]), p < .006, and incongruent (M = 506.69, 95%CI [468.24, 545.14]), p = .04. Participants, however, took the same time to respond to the middle letter in control and incongruent stimuli. These results are like what would be expected if attention scope was narrow. In the narrow attention scope condition, participants are not experiencing interference on the incongruent stimuli that participants are in the broad attention scope condition. 143 Figure 5. 38. Mean of median response time on the Eriksen flanker task on the first half of Experiment 6 to identify the middle letter on congruent, incongruent and control stimuli in the broad and narrow attention scope conditions. This figure shows the 26-point font, 2 space flanker variation. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent the 95% confidence intervals. 5.10: Chapter 5 Conclusion The experiments reported in this chapter reliably showed that the Navon induction task induced a particular attentional scope in participants with global and local attentional sets, which is consistent with previous research using this paradigm (Goodhew & Plummer, 2019). I was able to find specific variations of the flanker task that showed the expected pattern of results when attention scope was broad or narrow. The two specific variations that were found to be most promising in Experiment 5 --that is, 26-point font, 1 space and 26-point font, 2 space—replicated in Experiment 6. In Experiment 6, the emphasis on accuracy in the instructions to participants helped reduce variability in the data. I use an effective variation going forward in my last experiment (specifically, 26-point 300 350 400 450 500 550 600 650 700 Congruent Control Incongruent Congruent Control Incongruent Broad Condition Broad Condition Broad Condition Narrow Condition Narrow Conditon Narrow Condition Me an R es po ns e T im e ( ms ) Flanker Stimuli/ Attention Scope Condition 26-point Font, 2 Space 144 font, 2 space) and return to main goal of my dissertation to understand the influence of valence states on attention scope with an effective flanker variation. 145 Chapter 6: The Influence of Emotional Events on the Scope of Attention This chapter reports my final experiment, which focused on the main goal of my dissertation and examined differences in attention scope among pictures that differed in valence and movement propensity, and in which I assessed attention scope by using the specific flanker letter stimulus type that showed the most promising results in Experiment 6. With the use of this measure, I can return to the main question of my dissertation: What is the influence of valence states on attention scope? Experiment 7 is very similar to Experiment 4, except that for that in Experiment 7, I used pictures of different types of discrete emotions The pictures were selected to reveal a change in attention scope from valence states if it does indeed occur. I chose pictures from three discrete emotion bins: peaceful, sad, and disgust. These types of pictures were chosen specifically because I can examine changes in attention scope from valence states by examining the difference in attention scope following positively valenced pictures compared to negatively valenced pictures (e.g., peaceful compared to sad pictures). With these picture types I can also examine differences in movement propensity and compare high movement propensity states with low movement propensity states (e.g., sad compared to disgust pictures). To explore the possibility that a stronger affect induction may be necessary to see an influence attention scope, the length of each picture sequence was doubled. Adding to the length of the picture sequences may increase participants overall affective response to the pictures (e.g., Uhrig et al., 2016). If participants are exposed to more of the same type of picture, each picture sequence will last longer, and perhaps elicit a stronger affective response than a shorter sequence of pictures. Consistent with the Broaden-and-Build theory (e.g., Fredrickson, 2004; 2001) and Affect-as- Information (Gasper et al., 2004; Gasper & Clore, 2002), I expected participants to respond slower to incongruent stimuli than congruent than control and congruent flanker stimuli after exposure to peaceful pictures, and respond similarly quickly to congruent, control and incongruent stimuli after sad and disgust 146 pictures. Consistent with the Motivational Intensity theory (e.g., Gable & Harmon-Jones, 2010b), I expect participants to respond slower to incongruent stimuli than congruent and control stimuli after exposure to peaceful and sad pictures and respond similarly quickly to congruent, control and incongruent stimuli after disgust pictures. A secondary goal of Experiment 7 was to replicate the results of Experiment 6. I hypothesized that that after inducing a broad attentional set, I expected participants to be slower to identify the middle letter in incongruent stimuli than control and congruent stimuli on the Eriksen flanker task (Eriksen & Eriksen, 1974). After inducing a narrow attentional set, I expected participants to respond similarly quickly to the middle letter on congruent, control and incongruent stimuli on the Eriksen flanker task. 6.1: Experiment 7 Method 6.1.2: Participants and Design Ninety-two participants were in the experiment. Experiment 7 was conducted in the lab and marked a return to in person participation. Participants were undergraduate students from the University of British Columbia, recruited from the Department of Psychology Human Subject Pool. They received partial course credit for participating. The experiment was conducted with the approval of the University of British Columbia Behavioural Research Ethics Board. I conducted a power analysis as described for Experiment 2 and assumed that the picture manipulations used for Experiment 7 (i.e., sad vs peaceful, sad vs disgust) would have only a small effect (d = .15). On this assumption, a power analysis using the G*Power computer program (Faul et al., 2007) indicated a sample of 84 participants would be needed to detect very small effect with .90 power using a repeated measures ANOVA with alpha set at .05. 147 6.1.3: Materials 6.1.3.1: Pictures One hundred and thirty-five colour pictures (45 from each discrete emotion bin) from the CAP-D were selected. The CAP-D provides discrete emotion categories of a set of pictures from other normative affective picture databases [e.g., NAPS (Marchewka et al., 2013), IAPS (Lang et al., 2008), and The Geneva Affective Picture Database (Dan-Glauser & Scherer, 2011)]. Each picture was chosen according to a discrete emotion category in the CAP-D, as well as their valence and arousal ratings from the original databases (Moyal et al., 2018). Two negative emotions were chosen: sadness and disgust. Sadness has low movement propensity and disgust has high movement propensity (Gable & Harmon-Jones, 2010a). One positive emotion was chosen: peaceful. Peaceful is a positive emotion that has low movement propensity. I would have liked to also include a discrete emotion that was positive and high in movement propensity, however, I was unable to do so because of the constraints of the database. I converted each normative rating out of 10 to compare the valence and arousal ratings of each picture on the same scale. Table 6.1 shows the criteria used for selecting sad, disgust, and peace pictures. The pictures showed human interactions (e.g., a couple holding hands; a sick man in the hospital), scenes of built and natural environments (e.g., sunset, mountains) and scenes with animals (e.g., an injured dog). Sexually explicit and culturally inappropriate or extremely repulsive pictures were not selected. Each picture was saved as a 320 x 240 pixel .jpeg file. Each picture approximately subtended a 7.6° x 7.6° visual angle. G lo 148 Table 6. 4 Valence and Arousal Ratings of CAP-D Pictures Used in Experiment 7: The Picture Selection Criteria and the Properties of the Selected Pictures in the Experiment is Reported for Each Discrete Emotion Bin. Discrete Emotion Bin Picture Selection Criteria Properties of Selected Pictures Valence Arousal Valence Arousal Range Range M SD M SD Sad 3.00 – 4.00 4.00 – 8.00 3.15 1.84 7.10 1.89 Disgust 3.00 – 4.00 4.00 – 8.00 3.15 1.83 7.21 1.88 Peace 8.00 – 9.00 1.00 – 4.00 8.24 1.48 3.75 2.31 6.1.3.2. Flanker Stimulus The Eriksen flanker task stimulus type was a specific flanker stimulus variation of Experiment 5 and 6: two-spaced, font size 26. 6.1.3.3. Navon Letters The same Navon letters used in Experiment 6 were used in this experiment (see Figure 6.1 in Chapter 6). 6.1.4. Procedure All participants were tested individually in a quiet room in the lab that was equipped with a desktop computer running E-Prime V3.0 (Schneider et al., 2002). Each participant provided written and informed consent at the beginning of the experiment. The experiment consisted of two blocks, the order of which was counterbalanced across participants. One block consisted of the Navon induction task (Goodhew & Plummer, 2019) followed by the 149 Eriksen flanker task (Eriksen & Eriksen, 1974). Block two consisted of discrete emotion pictures followed by the Eriksen flanker task. Block one included the Navon induction task (Goodhew & Plummer, 2019) followed by the Eriksen flanker task (Eriksen & Eriksen, 1974) was the same as that used in Experiment 6, except the task was composed of 4 event sequences. The 4 event sequences were arranged into 2 primarily global letter blocks (the target letter was global in 80% of the letters) and two primarily local letter blocks (the target letter was local in 80% of the letters). The order of the global and local blocks was random. A break occurred at the end of each of the 4 event sequences. To proceed to the next sequence, participants pressed “G” on the keyboard. Block two consisted of discrete emotion pictures followed by the Eriksen flanker task (Eriksen & Eriksen, 1974). The block was composed of 12 event sequences (4 of each discrete emotion bin), each which was composed of 10 pictures of the same discrete emotion bin, followed by 6 Eriksen flanker task trials. All stimuli were displayed in the center of the screen on a white background. The picture task was used to induce affect in participants. Prior to each picture in the picture task, participants were shown a fixation cross (*) for 500 ms, which subtended a 0.1° x 0.1° visual angle. For each picture, an 8-point rating scale displayed below it. Instructions to participants emphasized: “People have different perceptions of pictures but what is important is your true perception of the picture so rate it in terms of how much you like it, in terms of what it means to you.” Participants were asked to respond, “According to your gut reaction, and in such a way that if you saw the picture again, you likely would rate it similarly”. The rating scale endpoints were marked ‘Extremely Negative’ and ‘Extremely Positive’ and all parts of the scale were displayed in Arial font, each letter measuring about 0.95° visual angle. Participants were randomly presented with a fixation cross (*) for 500 ms, which subtended a 0.1° x 0.1° visual angle. 150 Next, a flanker stimulus was displayed until the participant made a response. As soon as the participant responded, the next trial began. For each flanker stimulus, the participant’s task was to decide if the middle letter in a letter string was an A or an H. If the participants saw an A, they were asked to press the “a” on a QWERTY keyboard, and if participants saw an H, they were asked to press the “h” key. The Navon letters were randomly presented. Participants were instructed to respond fast but as accurately as possible. To practice the Navon induction task (Goodhew & Plummer, 2019) followed by the Eriksen flanker task (Eriksen & Eriksen, 1974), participants completed one event sequence, with 50% of the trials composed of a global letter and 50% of trials composed of a local letter. The arrangement of stimuli within each task was random. Beeps occurred to alert participants to errors and remind them of accurate responses. If a beep occurred during practice, the participant was interrupted and instructions to be accurate were repeated. Participants were free to ask questions at any time. To practice the discrete emotion pictures followed by the Eriksen flanker task, participants completed one event sequence, each with 10 pictures followed by 6 flanker stimuli (2 congruent, 2 control, 2 incongruent). The arrangement within each task was random. A beep occurred after an error to alert participants and remind them of accurate responses. If a beep occurred during practice, the participant was interrupted and instructions to be accurate were repeated. Participants were free to ask questions at any time. To end the experiment, participants were interviewed and debriefed. In the interview, participants were asked about their experience completing the experiment. The experiment took place in one session lasting about 50 minutes. 151 6.2: Results and Discussion The goal of the present study was to determine If valence states or movement propensity influences attention scope. The main independent variables were the discrete emotions of the pictures, and the main dependent variables were the ratings and rating-speeds on the picture task, performance accuracy and speed on the Eriksen flanker task (Eriksen & Eriksen, 1974) after pictures in each discrete emotion bin. The dependent variables were also and performance accuracy and speed on the Eriksen flanker task after the Navon induction task. To make decisions about differences between means 95% confidence intervals were used. When follow-up analysis was required, ANOVAs were conducted. 6.2.1: Data Preparation On the Navon induction task, 4 participants had a mean median response time of 713, 718, 743 and 776, more than 3 standard deviations above the group mean of 377. On the Eriksen flanker task following the Navon induction task, 2 participants had a mean accuracy of 63% and 63% on incongruent stimuli, less than 75% accuracy and more than three standard deviations below the group mean of 94%. On the Eriksen flanker task following the Navon induction task, 3 participants had a mean response time of 1186, 1132 and 1071 ms, more than three standard deviations above the group mean of 951 ms. On the picture task, 1 participant had a mean median response time of 4408 ms, more than 3 standard deviations above the group mean of 1995 ms. On the Eriksen flanker task following the pictures, all participants were above 75% accuracy. On the Eriksen flanker task following the pictures, 1 participant had a mean response time of 1186, 1132 and 1071 ms, more than 3 standard deviations above the group mean of 1172 ms. None of these participants are used in the analyses. The results reported below are based on the remaining 81 participants. 152 6.2.2: Discrete Emotions and Attention Scope 6.2.2.1: Picture Task Performance Participants’ mean ratings of the pictures are shown in Figure 6.1. The means indicate participants gave the highest ratings to peaceful pictures and the lowest ratings to sad and disgust pictures. These results are roughly consistent with the valence ratings from the CAP-D norms (Moyal et al., 2018). The data reveal one unexpected result of participants picture ratings. Participants rated peaceful, sad and disgust pictures lower than expected from the norms. Overall, pictures may have been rated lower than expected because of a negativity bias. Negative pictures may have caused a larger affective response in this experiment because there were more negative pictures than positive pictures and being exposed to more negative than positive pictures may have lowered participants ratings of the pictures (Vaish, Grossmann, & Woodward, 2008). 153 Figure 6. 6. Mean rating for pictures in each discrete emotion condition in Experiment 7: peaceful, sad, and disgust. Error bars are 95% confidence intervals. The means of participants’ median picture rating times are shown in Figure 6.2. The means show that participants were fastest to respond to disgust pictures and slowest to respond to sad pictures. Disgust pictures may have been easier to place on the scale than the other pictures because they captured more attention than the peaceful or sad pictures, which caused them to be rated the quickest. Research has shown that disgust pictures attract more attention than sad pictures (Wang et al., 2021). 1 2 3 4 5 6 7 8 Peaceful Sad Disgust Me an R ati ng (1 -8 ) Discrete Emotion Condition 154 Figure 6. 7. Mean response time to rate the pictures in each discrete emotion bin in Experiment 7: peaceful, sad, and disgust. Error bars are 95% confidence intervals. 6.2.2.2: Eriksen Flanker Task Performance 6.2.2.2.1: Performance Task Accuracy For each participant, I computed the mean accuracy of identifying the middle letters in congruent, control and incongruent stimuli. Overall mean accuracy was highest on congruent stimuli (M = 99%, SD = 0.02) and control stimuli (M = 99%, SD = 0.04), followed by incongruent stimuli (M = 98%, SD = 0.04). These findings assuage concerns about a speed-accuracy trade-off in performance (Schouten & Bekker, 1967; Wickelgren, 1977). The accuracy across for the flanker stimuli in different valence conditions remained high and did not differ between the discrete emotion conditions, as shown in Table 6.2. 1000 1200 1400 1600 1800 2000 2200 2400 Peaceful Sad Disgust Me an R es po ns e T im e ( ms ) Discrete Emotion Condition 155 Table 6. 5. Mean Eriksen Flanker Task Accuracy on Congruent, Control and Incongruent Stimuli Following each Discrete Emotion Condition in Experiment 7. 6.2.2.2.2: Performance Speed For each participant, I computed the mean of the median response time required to identify the congruent, control and incongruent stimuli using only data from accurate trials. Overall, the marginal means indicate participants were fastest on congruent stimuli followed by control stimuli, and slowest on incongruent stimuli, providing evidence for the typical flanker effect (e.g., Eriksen & Eriksen, 1974). The mean of the median response times for the congruent, control and incongruent stimuli are reported in Table 6.3. Discrete Emotion Condition Congruent Stimuli Control Stimuli Incongruent Stimuli M SD M SD M SD Peaceful 99% 0.04 99% 0.03 99% 0.04 Sad 100% 0.02 99% 0.04 98% 0.05 Disgust 99% 0.02 99% 0.03 97% 0.05 156 Table 6. 6 Mean Eriksen Flanker Task Response Time on Congruent, Control and Incongruent Stimuli in Experiment 7. The mean of the median response times to identify the middle letter in the congruent, control and incongruent stimuli in each discrete emotion condition are shown in Figure 6.3. The figure shows that in each discrete emotion condition, participants were fastest on congruent stimuli, followed by control stimuli and were slowest on incongruent stimuli. The results of a repeated measures ANOVA, with flanker stimulus type (congruent, control, incongruent) and discrete emotion condition (peaceful, sad, disgust) as the within- subject variables revealed a main effect of flanker stimulus type, F(12, 160) = 22.484, p < .001, η2= .219. Pairwise comparisons on the different types of flanker stimuli showed that participants were slower on incongruent stimuli (M = 561.82, 95%CI [533.83,589.82]) than congruent (M = 517.18, 95%CI [489.47, 544.88], p < .001 and control stimuli (M = 522.44, 95%CI [497.73, 547.15]), p < .001. This is consistent with previous research using the Eriksen flanker task (Eriksen & Eriksen, 1974; Lamers & Roelofs, 2011). The interaction between flanker stimulus type and discrete emotion condition was not significant. Despite the absence of an interaction, I used the data to explore the hypothesis. Based on the predictions of the Broaden-and-Build theory (e.g., Fredrickson, 2001; 2004) and the Affect-as-Information hypothesis (e.g., Gasper & Clore, 2002), I expected an interaction to occur whereby participants were Congruent Stimuli Control Stimuli Incongruent Stimuli M SD M SD M SD 576.82 121.02 588.70 117.98 605.47 107.71 157 slower to respond to the middle letter in incongruent stimuli than congruent and control stimuli in the peaceful discrete emotion condition and I expected participants to respond similarly quickly to the middle letter in congruent, control and incongruent stimuli in the disgust and sad discrete emotion conditions. Based on the predictions of Motivational Intensity (e.g., Gable & Harmon-Jones, 2010b), I expected an interaction to occur whereby participants responded similarly fast to congruent, control and incongruent stimuli in the disgust discrete emotion condition, but slower to respond to incongruent than congruent and control stimuli in the sad and peaceful conditions. Guided by theoretical predictions, follow-up pair-wise comparisons comparing each of the flanker stimulus types in each discrete emotion condition were conducted, but none were significant. The data do not support either hypothesis. Figure 6. 8. Mean response time to identify the middle letter on congruent, control and incongruent stimuli following pictures from each discrete emotion bin in Experiment 7: peaceful, sad, and disgust. Error bars are 95% confidence intervals. 400 450 500 550 600 650 Co ng ru en t Co nt ro l Inc on gr ue nt Co ng ru en t Co nt ro l Inc on gr ue nt Co ng ru en t Co nt ro l Inc on gr ue nt Peaceful Peaceful Peaceful Sad Sad Sad Disgust Disgust Disgust Me an R es po ns e T im e ( ms ) Flanker Stimuli/ Discrete Emotion Condition 158 6.2.3: Induced Attentional Set on Attention Scope 6.2.3.1: Navon Induction Task Performance This pattern of results provides evidence of an attention set induction effect (Goodhew & Plummer, 2019) suggesting that the task successfully induced broad attention in the broad attention induction condition and narrowed attention in the narrow attention induction condition. Participants were faster and more accurate when making decisions about letters that were consistent with the induced condition than when it was not. The 75 ms and 100 ms induction effect in both the global and local condition, respectively is consistent with previous studies using this paradigm (Goodhew & Plummer, 2019). The pattern of performance permits inference that broad and narrow attention scope was manipulated effectively because a broad and narrow attentional set was induced successfully. Figure 6. 9. Mean accuracy on global and local letters in the Navon induction task for the broad and narrow attention scope conditions in Experiment 7. The blue bars are response time, and the orange line is accuracy. Error bars represent 95% confidence intervals. 92 93 94 95 96 97 98 99 100 0 50 100 150 200 250 300 350 400 450 500 Global Letters Local Letters Global Letters Local Letters Global Condition Local Condition Me an A cc ur ac y ( % co rre ct) Me an R es po ns e T im e ( ms ) Response Time Accuracy Broad Condition Narrow ondition 159 6.2.3.2: Eriksen Flanker Task Performance I computed the mean median response time required to identify the middle letter of the flanker stimuli for both the broad and narrow attention scope conditions. The means are displayed in Figure 6.5. In the broad attention scope condition, participants were fastest on congruent stimuli followed by control and incongruent stimuli. In the narrow attention scope condition, participants were fastest on congruent stimuli, followed by incongruent stimuli and were slowest on control stimuli. If attention was broad in the broad attention scope condition, I would expect participants to be slower to respond to the middle letter in incongruent stimuli than control stimuli and this is not the case and If attention scope was narrow in the narrow attention scope condition, I would expect participants to take a similar amount of time to respond to the middle letter in congruent, control and incongruent stimuli, but participants are slowest on control stimuli. The results of Experiment 6 did not replicate in a within-subjects design. It is possible that this occurred because the global or local attentional set manipulation was not strong enough after only a few sequences to show performance differences on the Eriksen flanker task (Eriksen & Eriksen, 1974). 160 Figure 6. 10. Mean accuracy on global and local letters in the Navon induction task for the broad and narrow attention scope conditions in Experiment 7. The red bars are the broad attention scope condition, and the blue bars are the narrow attention scope condition. Error bars represent 95% confidence intervals. 6.5: Experiment 7 Conclusion The results of my final experiment of my dissertation show no influence of valence states or movement propensity states and the scope of attention. It could be that the affect that is elicited by exposure to pictures is not strong enough to see changes in attention scope This possibility as well as others, for the results of this experiment and the others in my dissertation will be further discussed in the general discussion. 300 350 400 450 500 550 600 Congruent Control Incongruent Congruent Control Incongruent Broad Condition Broad Condition Broad Condition Narrow Condition Narrow Condition Narrow Condition Me an R es po ns e T im e ( ms ) Flanker Stimuli/ Attention Scope Condition 161 Chapter 7: General Discussion The goal of my dissertation was to examine the influence of valence states on the scope of visual spatial attention. My dissertation specifically examined how valence states influenced attention scope through the lens of the Affect-as-Information hypothesis, the Broaden-and-Build theory, and Motivational Intensity theory (e.g., Gable & Harmon-Jones, 2010b). All theories predict that emotional events trigger intermediary responses which in turn change the scope of attention. The Affect-as-Information Hypothesis and the Broaden-and-Build theory focus on the valence of emotional events and predict that positive valence states broaden the scope of attention and negative valence states narrow it. Motivational Intensity theory focuses on the movement propensity of emotional events and predicts that high movement propensity (i.e., attraction; repulsion) narrows attention scope and low movement propensity (i.e., neutral) broadens it. My dissertation is composed of 7 large-scale experiments, 5 of which specifically examined the influence of valence states on the scope of visual attention. In these five experiments (i.e., Experiments 1, 2, 3, 4 and 7), I induced a desired affective state by manipulating valence, and I manipulated valence together with movement propensity in Experiments 4 and 7. In these experiments I used both the Navon task (Navon, 1977) and the Eriksen flanker task (Eriksen & Eriksen, 1974), two common tasks for assessing the scope of attention. In one experiment (i.e., Experiment 3), I verified the affect induction method was effective in inducing a particular subjective valence state in participants. In two experiments (i.e., Experiments 5 and 6), I explored which specific properties of the stimuli used in the Eriksen flanker task (Eriksen & Eriksen, 1974) need to be instantiated for detecting changes in attention scope. All of the experiments in my dissertation were large in terms of number of participants as well as in the number of stimuli used, and all stimuli were selected from commonly used and carefully normed stimulus sets (e.g., IAPS, Lang et al., 2008). 162 My experiments showed the following major results. In the first four experiments, on influence of valence on attention scope, I found no evidence that valence states influence attention scope. In Experiments 5 and 6, I discovered which specific properties of flanker stimuli need to be instantiated for detecting changes in the scope of visual attention. Specifically, my research identified two flanker-test variations that were able to show a pattern of results that is consistent with a broad and a narrow attention scope. In Experiment 7, I used one of these successful flanker-test variations, but still did not find an influence of valence states on attention scope. To underscore the critical finding that valence states do not influence attention scope, I conducted a further analysis which combined the data from those of my experiments that examined the influence of valence states on attention scope, and that measured attention scope with the Eriksen flanker task (Eriksen & Eriksen, 1974). I compared the difference in speed of responding to congruent and incongruent flanker- test stimuli in the condition in which participants were exposed to positive pictures versus to negative pictures in Experiments 2, 3, 4 and 7. The effect sizes I calculated were weighted by the total number of participants in each experiment. Across the four experiments, I calculated an average effect size (d =0.06), p = .17 (ns), which showed a minimal to no valence effect across the experiments. The finding of no influence due to different valence states on the scope of attention helps to clarify what current research says about the influence of valence states on the scope of visual attention. The literature review of previous research suggests that the results are mixed and ambiguous. The results of my five large-scale, powerful experiments, which used normed stimuli to induce valence states in participants helps to clarify the ambiguity. Based on the results of the five experiments, I conclude that the influence of affect on the scope of attention does not occur under the laboratory conditions of my experiments. 163 The results of my research suggest the extant theories on the influence of affect on attention scope may need to be modified to specify the conditions under which this influence does and does not occur (e.g., Fredrickson, 2004; Gasper & Clore, 2002). It seems this influence does not occur under specific laboratory conditions where pictures are used to induce affect. It is also possible that the influence of affect on attention scope does not occur when undergraduate psychology students are used as participant because they have completed many laboratory experiments as part of their course requirements. It is possible that the influence of valence states on attention scope only occurs when much stronger valence states are induced in participants. Stronger valence states would likely be easier to achieve outside a laboratory setting. The results of the Russell’s Affect Grid (Russell et al., 1989) in Experiment 3 in my dissertation showed large differences between the negative, neutral, and positive valence conditions. Despite the fact that the results showed a strong valence state manipulation was achieved when viewing and rating pictures, is likely that viewing a picture of an emotional event is likely much weaker than experiencing a similar emotional event in real life. For example, the valence state that is induced by viewing and rating a picture of a horrific car accident is likely much weaker than the valence state that would occur when experiencing such an event in real life. 7.1: Limitations of My Research My dissertation research has limitations. One of these is the strength of the valence manipulation that is achievable in a laboratory setting. The valence state manipulations I used could only be so strong for reasons outside of my control. For instance, I was limited by minimal risk ethics and therefore, all of the pictures I used in my experiment were carefully chosen to not induce potentially adverse, lasting effects (e.g. upset, sadness, disgust) in participants. It is possible that the valence state that is induced by pictures in the laboratory may not create the same kind of affect in participants that is evoked by everyday emotional events. For example, presenting 164 participants a picture of a puppy or a delicious dessert likely creates a weaker level of affect then actually brining a new puppy home, or actually eating a delicious dessert that is in front of you (e.g., Gable & Harmon-Jones, 2008, Experiment 4). Similarly, seeing a picture of a large spider is likely to be experienced less intensely than seeing spider on your keyboard. There are several reasons for why the affect induced in a laboratory by means of pictures is weaker than the affect induced by everyday events. One reason may be that in a laboratory setting and with undergraduate students as participants, the normal mapping of affective events to subjective states was suspended in some way. Participants may have treated the pictures like a video game, where the participants know they are in a particular setting, a make-believe or unreal world. Video game research shows that the emotions experienced in a video game are not carried over or similar to the experience when similar events are experienced in everyday life (Sauer et al., 2015). Another potential limitation of my research stems from the picture rating task which was included in all of my experiments; this task may have changed or altered participants’ affective responses to the pictures. I used the rating task to ensure that participants were paying attention to each of the pictures. However, it is possible that this task interfered with participants affect and in turn altered the pictures’ influence on participants’ attention scope. Research has shown that when participants are asked to do certain tasks in a conscious and deliberate manner, this can change learning of to be remembered items for example (Elgort, 2011; Postman & Kruesi, 1977). It is also possible, however, that the picture rating task had no influence because affect is often experienced automatically in response to a stimulus or event (e.g., Russell, 2003). Another limitation of my research may be that undergraduate psychology students were used as participants. Six out of seven of my experiments used undergraduate students as participants exclusively. These participants are a special subset of the population; they are used to experimental procedures and 165 may have completed a large number of similar experiments in exchange for credit towards their psychology courses. A possible limitation of my research is that most of my experiments manipulated affect within subjects. As a result of the within subjects’ manipulation, participants had to switch between different affective states within the experiments. This may have influenced the results of my experiments. Another possible limitation of my research is potential procedural issues for participants. Each experiment also had a large number of event sequences and for each picture within these event sequences, participants were required to rate it. This rating task may have changed how participants perceived and oriented towards the pictures. Together, these tasks may have been exhausting (both cognitively and physically) for participants. It is also possible that measures of attention scope that I used in my experiments were not sufficiently sensitive. For example, it could be that valence states do not change attention scope when it is measured by an Eriksen flanker task (Eriksen & Eriksen, 1974). 7.2: Conclusion I set out to test the influence of valence states on attention scope, and more specifically, the assumptions that the manner in which we allocate attention depends on our current valence state (e.g., Fredrickson, 2004; Fredrickson & Branigan, 2005; Gasper & Clore. 2002; Gasper, 2004), or depends on our current movement propensity state (e.g., Gable & Harmon-Jones, 2008a; 2010b). In five powerful experiments, I found no evidence to support these assumptions. As consequence, I conclude that the relationship between participants’ specific affective state and the scope of attention predicted by the theories which motivated my research does not hold in some situation, like those which characterize laboratory experiments. This may have occurred because participants may have contextualized the laboratory experience in some manner, by suspending the kind of reaction that are typical in daily life, and by recognizing that the laboratory is a safe setting where no emotional harm is likely to occur. Based on this 166 assumption, my research recommends that theories on the relation between affect and the scope of attention ought to be revised; they ought to acknowledge that the relationship between affective state and the scope of attention does not hold in all situations; they ought to specify when this relationship does and does not hold. 167 References Alaifan, N. (2022). Memory for emotional events: Meta-analysis of emotional enhancement on episodic memory for valence pictures [Manuscript in Preparation]. Department of Psychology. The University of British Columbia. Álvarez-San Millán, A., Iglesias, J., Gutkin, A., & Olivares, E. I. (2021). 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Global Letters Broad Font Global Letters Broad Spacing Global Letters Broad Constant Visual Angle Local Letters Narrow Constant Visual Angle Local Letters Broad Spacing Local Letters Broad Font Local Letters Broad Constant Visual Angle Global Letters Narrow Font Global Letters Narrow Spacing Global Letters Narrow Font Local Letters Narrow Font Local Letters Narrow Spacing Attention Induction Condition/ Navon Letters Global Letters Narrow Constant Visual Angle 185 Appendix B ANOVA Summary Table for Each Eriksen Property Type and the Flanker Variations Within Them for Experiment 5. The main effect of flanker stimulus type and Navon Letter Type, as well as the interaction between them, are reported. The flanker variations with the most promising pattern of results are in bold with an asterisk. Flanker Property Type Variation Main Effect of Flanker Stimulus Type Main Effect of Navon letter type Interaction Between Flanker Stimulus Type and Navon letter type Font 26-point font, 0 space F = 18.56 SS = 775120.85 P < .001 F = 0.15 SS = 5418.45 P = 0.697 F = 0.53 SS = 22041.37 P = 0.591 Font* 32-point font, 0 space F = 3.22 SS = 214194.75 P = 0.043 F = 0.29 SS = 15913.05 P = 0.591 F = .45 SS = 40087.75 P = 0.549 Font 43-point font, 0 space F = 14.78 SS = 711280.77 P < .001 F = 0.11 SS = 4558.02 P = .640 F = 0.45 SS = 21536.40 P = .640 Spacing 26-point font, 0 space F = 11.90 SS = 835659.63 P < 0.001 F = 3.06 SS = 170140.59 P = 0.085 F = 0.65 SS = 45682.56 P = 0.524 186 Spacing* 26-point font, 1 space F = 1.37 SS = 91144.38 P = 0.258 F = 1.16 SS = 48290.45 P = 0.286 F = 1.04 SS = 69105.11 P = 0.357 Spacing 26-point font, 2 spaces F = 1.99 SS = 126646.24 P = 1.141 F = 0.03 SS = 0.87 P = .105 F = 1.20 SS = 76116.30 P = 0.306 Constant Visual Angle* 43-point font, 0 space F = 5.541 SS = 462898.895 P = 0.005 F = 2.697 SS = 128109.624 P = 0.105 F = 0.198 SS = 16563.795 P = 0.820 Constant Visual Angle 32-point font, 1 space F = 5.27 SS = 305606.80 P = 0.018 F = 0.29 SS = 15913.05 P = 0.591 F = 0.04 SS = 2055.76 P = 0.965 Constant Visual Angle* 26-point font, 2 space F = 2.80 SS = 227490.31 P = 0.064 F = 4.06 SS = 267567.84 P = 0.035 F = 0.45 SS = 21536.40 P = 0.640
Thesis/Dissertation
eng
Psychology
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Graf, Peter (Professor of psychology)
The influence of valence states on the scope of visual attention
Text