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Can we compare mean differences across diverse ethnocultural groups? Wong, Sabrina 2008

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UBC School of NursingCan we compare mean differences across diverse ethnocultural groups?Sabrina T. Wong, RN PhDNexus, April 2008 UBC School of NursingAcknowledgements• Dave Nordstokke-PhD candidate in educational psychology• Steve Gregorich-biostatistician at UCSF• Women who participated in this study• AHRQ: 5P01 HS10856 and NIH RCMAR P30-AG15272UBC School of NursingQuestions for you….• Two groups: students and not-students• Do you want to travel more?• Do you want a nicer car?• Do you want to earn more $$?UBC School of NursingObjectives• Describe the use of quantitative methods to examine if valid group comparisons can be made• Provide an example of an instrument that can be used for meaningful comparisons across groupsUBC School of NursingSocial Support Defined• Processes through which social relationships might promote health and well-being• Multi-dimensional: tangible, emotional/companionship, informationalUBC School of NursingBackground: Social Support and Aging• Social support keeps people healthy and health them recover from illness faster • Emotional support is specifically associated with:– More positive patterns of cognitive aging– Increased social engagement– Decreased levels of depressionUBC School of NursingSocial Support and Ethnocultural Groups• Aging population is becoming increasingly diverse– In US, African Americans, Asians, and Latinos will make-up close to 30% of those aged 65 and older• Can mean social support scores be compared across ethnocultural groups?UBC School of NursingPurpose• Can we make meaningful comparisons of social support across women from four diverse ethnic groups (African American, Latino, Chinese, and Caucasian)UBC School of NursingMethods• Telephone recruitment with face-to-face survey administration • Data collected in English, Spanish, and Chinese (Mandarin and Cantonese)• Multidimensional social support instrument (28-items): tangible, emotional/companionship, financial, information, and language support– Language support not included in this analysis UBC School of NursingAnalysis• Tested for evidence of construct validity using LISREL: – Dimensional invariance– Configural invariance– Metric invariance– Scalar invarianceUBC School of NursingResults• Total sample of 1,074 women– African American (n=159), Chinese (353), Latina (n=236), Caucasian (n=326)– Mean age was 61 years, >50% married– Chinese and Latinas had < high school education– All reported lower household income compared to CaucasianUBC School of NursingResults0.980.065< 0.001176.71326Non-Latino White0.970.07< 0.001164.75236Latino0.980.05< 0.001134.43353Chinese0.980.0570.002108.21159African-American0.990.052< 0.001277.031074Total sampleCFIRMSEApχ2NEthnic GroupUBC School of NursingConfigural Invariance & Metric Invariance (bolded)0.970.0670.0001325.05562Latino vs. Non-Latino White0.970.0590.0001328.9679Chinese vs. Non-Latino White0.970.0610.0001310.62589Chinese vs. Latino0.980.0650.0001299.97485African-American vs. Non-Latino White0.970.0680.0001282.28395African-American vs. Latino0.980.0530.0001252.19512African-American vs. ChineseCFIRMSEApχ2NModelUBC School of NursingDiscussion• Comparative research requires that instruments measure constructs with the same meaning across groups• Apparent differences across groups may be spurious and due to additive response bias• This study suggests that this instrument could be used for comparing social support across ethnic groups with more workUBC School of NursingIdeal vs. Practical• Strict factorial invariance is ideal• Strong invariance is more readily attainable• Metric invariance sufficient if focus is restricted to comparing the strength of corresponding regression parameters across groupsUBC School of NursingUBC Centre for HealthServices and Policy Research and School of NursingAdvancing world-class health services and policy research, training and data resources on issues that matter to Canadians. » www.chspr.ubc.caPutting Scholarship into Practice» www.nursing.ubc.ca

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