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Behaviour change techniques targeting both diet and physical activity in type 2 diabetes: A systematic… Cradock, Kevin A; ÓLaighin, Gearóid; Finucane, Francis M; Gainforth, Heather L; Quinlan, Leo R; Ginis, Kathleen A M Feb 8, 2017

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REVIEW Open AccessBehaviour change techniques targeting bothdiet and physical activity in type 2 diabetes:A systematic review and meta-analysisKevin A. Cradock1,2, Gearóid ÓLaighin2,3, Francis M. Finucane4, Heather L. Gainforth5, Leo R. Quinlan1*and Kathleen A. Martin Ginis6AbstractBackground: Changing diet and physical activity behaviour is one of the cornerstones of type 2 diabetestreatment, but changing behaviour is challenging. The objective of this study was to identify behaviour changetechniques (BCTs) and intervention features of dietary and physical activity interventions for patients with type 2diabetes that are associated with changes in HbA1c and body weight.Methods: We performed a systematic review of papers published between 1975–2015 describing randomisedcontrolled trials (RCTs) that focused exclusively on both diet and physical activity. The constituent BCTs, interventionfeatures and methodological rigour of these interventions were evaluated. Changes in HbA1c and body weightwere meta-analysed and examined in relation to use of BCTs.Results: Thirteen RCTs were identified. Meta-analyses revealed reductions in HbA1c at 3, 6, 12 and 24 months of -1.11 % (12 mmol/mol), -0.67 % (7 mmol/mol), -0.28 % (3 mmol/mol) and -0.26 % (2 mmol/mol) with an overallreduction of -0.53 % (6 mmol/mol [95 % CI -0.74 to -0.32, P < 0.00001]) in intervention groups compared to controlgroups. Meta-analyses also showed a reduction in body weight of -2.7 kg, -3.64 kg, -3.77 kg and -3.18 kg at 3, 6, 12and 24 months, overall reduction was -3.73 kg (95 % CI -6.09 to -1.37 kg, P = 0.002).Four of 46 BCTs identified were associated with >0.3 % reduction in HbA1c: ‘instruction on how to perform abehaviour’, ‘behavioural practice/rehearsal’, ‘demonstration of the behaviour’ and ‘action planning’, as wereintervention features ‘supervised physical activity’, ‘group sessions’, ‘contact with an exercise physiologist’, ‘contactwith an exercise physiologist and a dietitian’, ‘baseline HbA1c >8 %’ and interventions of greater frequency andintensity.Conclusions: Diet and physical activity interventions achieved clinically significant reductions in HbA1c at three andsix months, but not at 12 and 24 months. Specific BCTs and intervention features identified may inform moreeffective structured lifestyle intervention treatment strategies for type 2 diabetes.Keywords: Behaviour change techniques, Diet, Physical activity, Type 2 diabetes, HbA1c, Systematic review,Meta-analysis* Correspondence: leo.quinlan@nuigalway.ie1Physiology, School of Medicine, NUI Galway, University Road, Galway,IrelandFull list of author information is available at the end of the article© The Author(s). 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Cradock et al. International Journal of Behavioral Nutritionand Physical Activity  (2017) 14:18 DOI 10.1186/s12966-016-0436-0BackgroundType 2 diabetes is one of the fastest growing and largestglobal health burdens. In 2015, there were 415 millionpeople with diabetes worldwide (91 % of which weretype 2 diabetes) with figures expected to rise to 642million by the year 2040, [1] which easily surpasses earl-ier predictions of 366 million by 2030 [2]. A 2010 globalanalysis of mortality reported that 1.3 million deathsworldwide were due to diabetes that year, twice as manyas in 1990 [3].Type 2 diabetes is diagnosed based on a fasting plasmaglucose (FPG ≥126 mg/dL [7 mmol/L]) or the two hourplasma glucose value following a 75 g oral glucosetolerance test (>200 mg/DL [11.0 mmol/L]) or having aHbA1c of ≥ 6.5 % according to the American DiabetesAssociation (ADA) [4]. Glycosylated haemoglobin A1c(HbA1c haemoglobin to which glucose is bound, is testedto determine average blood glucose level over the pasttwo to three months) [1] is widely regarded as an accur-ate measurement for diabetes assessment and the ADArecommend that HbA1c testing be performed on all pa-tients with diabetes at initial diagnosis and as part ofcontinuing treatment [4]. HbA1c reduction of 0.5 %(6 mmol/mol) is regarded as clinically significant [5],while other authors suggest 0.3 % (4 mmol/mol) [6, 7]or 0.33 % (4 mmol/mol) [8]. HbA1c was selected as theprimary outcome for this review as it represents themost widely used measure of type 2 diabetes control andtreatment efficacy.Type 2 diabetes is a mulifactorial lifestyle disease,linked to dietary habits and sedentary behaviour [9]. TheADA included ‘support patient behavioural change’ asone of their three key objectives for improving diabetescare and stated that ‘lifestyle changes of increasingphysical activity, eating a healthy diet, cessation of smok-ing, weight loss and coping strategies’ was one of theirkey diabetes treatment foci [4]. Importantly, all threeADA treatment foci revolve around changing patients’behaviour.RCTs and epidemiological data have shown that type 2diabetes can be prevented. However, changing diet andlifestyle behaviour requires change at an individual,environmental, social, and policy level [10]. Previous au-thors have identified as key research recommendationsthe need to investigate the effects of multiple behaviourchanges in people who have been diagnosed with type 2diabetes [11] and multiple BCT use associated with clin-ically significant changes in HbA1c [7].Precise specification of the active ingredients (BCTs)and intervention features of diet and physical activity in-terventions in type 2 diabetes will help build cumulativeevidence towards delivering effective replicable interven-tions. Behaviour change technqiues (BCTs) have beenidentified in previous similar studies of diet and/orphysical activity in type 2 diabetes [7, 12] and other sub-jects [13–16]. Previously identified BCTs associated withsuccess in changing diet and/or physical activity behaviourinclude: ‘instruction on how to perform a behaviour’, ‘be-havioural practice/rehearsal’, ‘demonstration of the behav-iour’, ‘action planning’, ‘problem solving’, ‘feedback onbehaviour’, ‘self-monitoring of behaviour’, ‘goal setting’, ‘goalreview’, ‘social support’, ‘prompt practice’, ‘use of follow upprompts’, and ‘prompting generalisation of a target behav-iour’ [7, 12–15, 17, 18].However, to our knowledge, there has been no system-atic review and meta-analysis identifying the behaviourchange techniques (BCTs) associated with greatest im-provements in HbA1c in interventions combining dietand physical activity in type 2 diabetes treatment. Wesought to identify which BCTs exclusively change onlythe behaviours of diet and physical activity. Interventionscontaining multiple behaviours or additional behaviourswere not included in this review. Behaviour change hascontributed to the morbidity and mortality associatedwith type 2 diabetes [19] but might also contribute tothe solution [20]. However the effectiveness of behaviourchange interventions varies considerably and theirmechanisms are not fully understood [20]. The overalleffects of diet and physical activity behavioural interven-tions in maintaining weight loss are moderate and futureresearch on increasing effectiveness of interventions isrequired [21].The primary objective of this study was to identify BCTsand intervention features which reduced HbA1c. A second-ary objective was to identify the frequency of use of BCTsin included studies. A third objective was to describechanges in HbA1c and weight at different time points.MethodsA PRISMA (Preferred Reporting Items for SystematicReviews and Meta-Analyses) checklist was createdand PRISMA review guidelines were followed [22](Additional file 1: 1.1).Inclusion criteria(i) Randomised controlled trials (RCTs) of any durationwith a dietary AND physical activity intervention,published in peer-reviewed journals between 1/1/1975 and 1/6/2015.(ii) RCTs with a comparison arm or control group thatconstituted usual care.(iii) Human participants older than 18 years of age withclinically confirmed type 2 diabetes, at time ofrecruitment.(iv) Primary clinical outcome measure was HbA1c,however studies reporting HbA1c results as anoutcome measure were also included. Body weightCradock et al. International Journal of Behavioral Nutrition and Physical Activity  (2017) 14:18 Page 2 of 17was reported as a secondary outcome (because ofthe inconsistency and variety of measures of dietaryand physical activity behaviour used in the RCTs, itwas not possible to compare behavioural outcomesacross trials. Thus, HbA1c was selected as theprimary endpoint).Exclusion criteria(i) RCTs of diabetes prevention OR RCTs of those atrisk of type 2 diabetes.(ii) RCTs that used pharmacological agents exclusivelyto treat type 2 diabetes.(iii) RCTs that targeted multiple chronic diseases,gestational diabetes or type 1 diabetes.(iv) RCTs that used additional interventions beyonddiet and physical activity, or focused on additionalbehaviours other than diet and physical activity.(v) Studies not reported in English.(vi) Studies not reporting HbA1c as an outcomemeasure.Information sources and search strategyCochrane Library, CINAHL, EMBASE, PubMed, PsycINFO,and SCOPUS databases were systematically searched usinga Boolean combination of key words and MeSH headings(Additional file 1: 1.2). Additional records identified throughother sources such as reference lists of relevant reviews andincluded studies were searched for additional studies. Theoriginal search was conducted in April 2014 and repeatedJune 2015. Reference lists of included articles were alsochecked for relevant articles.Article screeningArticles were initially screened by two research teammembers based on titles and abstracts and then full textsof the remaining articles (KC and KMG). The final set ofincluded articles was agreed on by the entire team (seeFig. 1 for search process). Inter-rater agreement byCohen’s Kappa for the full text search results was 0.86.Data extraction processData were extracted using standardised data extractiontemplates and compiled in an Excel file. All data extrac-tion was carried out independently by at least two mem-bers of the team (KC and KMG). If additional studyinformation was required, corresponding authors werecontacted by email using a standardised template, papersreporting on the same trial were sought (e.g. Methodspapers), and when available, supplementary onlineinformation was accessed.Risk of bias and fidelity assessmentRisk of bias in individual studies was assessed using theCochrane Collaboration risk of bias tool, [23] wherebycriteria are applied to seven aspects of trials to yield anappraisal of ‘low risk’, ‘high risk’ or ‘unclear risk’ of bias.RCTs were independently assessed by two members ofthe review team for methodological quality and risk ofbias (KC and KMG). Treatment fidelity was assessedusing Bellg et al.’s [24] criteria, which identify treatmentfidelity strategies for improving and monitoring, pro-vider training, delivery of treatment, receipt of treat-ment, and enactment of treatment skills. Each categorycontains subcategories which were each assigned a scoreof yes, no, or unclear. However, fidelity measures usingthis dichotomous type response don’t capture the degreeof use of fidelity, therefore a continuum type scoring orrating of parameters may provide a more accurate as-sessment of fidelity.Coding of behaviour change techniquesMichie’s v1 BCT taxonomy [25] was used to identify andcode the BCTs reported in each study. This rigorouslydeveloped and validated taxonomy consists of clear defini-tions of 93 different BCTs, divided into 16 different cat-egories. The taxonomy was developed to facilitateconsistent classification and reporting of the use of BCTsby researchers and clinicians. Since its publication, it hasbecome the standard for classifying and reporting BCTs inthe health behaviour change literature. BCTs were codedseparately for physical activity behaviour and for diet be-haviour; a BCT was only coded when it was explicitlymentioned in the intervention methodology. (All studiescoded and associated text are documented in Additionalfile 2). BCTs were coded separately for intervention andcontrol groups. BCTs for diet only and physical activityonly were combined in an excel spreadsheet, if a BCT waspresent in diet only or physical activity only or in both dietand physical activity it is reported as present for combineddiet and physical activity (see Table 1). A coding rubric/rulebook was developed by three authors of this review(KC, LQ and HG) to guide the coding process (Additionalfile 1: 1.3). All included studies were coded independentlyby two authors (KC and LQ) who underwent training inthe use of Michie’s taxonomy [26]. A third master coder(HG) independently assessed the coding results and hadfinal say in the event of disagreements. Cohen’s kappa andPABAK calculations were used to establish inter-coder re-liability of BCTs present and absent. A BCT had to beused in at least three studies to be included in the moder-ator analysis.Coding of intervention featuresRationale for features included was derived from interven-tion features identified previously [27], previous reviewsCradock et al. International Journal of Behavioral Nutrition and Physical Activity  (2017) 14:18 Page 3 of 17[7, 17] and the ‘Theory Coding Scheme’ [28] which guidedtheory coding of intervention content. Interventionfeatures were included under the headings “mode of deliv-ery”, “frequency”, “provider”, “intensity” and “other” (useof theory and baseline HbA1c, number of BCTs included).Intensity for total number of contacts and total number offace-to-face contacts with intervention personnel used themean and median to categorise variables into high (abovemean/median) and low intensity (below mean/median).Frequency of ‘total’ and ‘face -to-face’ contacts also usedabove and below the mean/median to categorise the aver-age number of weeks between contacts as high frequency(below) and low frequency (above). All other interventionfeatures were analysed dichotomously using yes/no to in-dicate presence or absence. Rationale for categorisingbaseline HbA1c levels comes from a large epidemiologystudy which identified that HbA1c levels ≥ 7 % were associ-ated with increased risk of death [29]. We also ran themoderator analysis using above and below 8 % (64 mmol/mol) to categorise high and low HbA1c as standard dia-betes control targets aim to keep HbA1c between 7.0 and7.9 % [29] therefore HbA1c levels >8 % represent poorlycontrolled type 2 diabetes.AnalysisHbA1c reductions of ≥0.3 % were deemed clinically signifi-cant, which follows the precedent set by other authors [6, 7].Meta-analyses were conducted using RevMan (v5.3) on theprimary outcome measure of HbA1c and the secondaryoutcome of body weight. Changes were calculated as thedifference in HbA1c from baseline to a particular time-point(3, 6, 12, and 24 months), and reductions in HbA1c wereFig. 1 PRISMA 2009 Flow diagram of search strategyCradock et al. International Journal of Behavioral Nutrition and Physical Activity  (2017) 14:18 Page 4 of 17Table 1 BCTs used in dietary AND physical activity aspect of interventionBCT no. BCT Label (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) Total4.1 Instruction on how to perform a behaviour ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ 131.4 Action planning ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ 129.1 Credible source ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ 121.1 Goal setting (behaviour) ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ 111.3 Goal setting (outcome) ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ 103.1 Social support (unspecified) ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ 102.3 Self-monitoring of behaviour ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ 92.2 Feedback on behaviour ✓ ✓ ✓ ✓ ✓ ✓ ✓ 76.1 Demonstration of the behaviour ✓ ✓ ✓ ✓ ✓ ✓ ✓ 78.7 Graded tasks ✓ ✓ ✓ ✓ ✓ ✓ ✓ 712.5 Adding objects to the environment ✓ ✓ ✓ ✓ ✓ ✓ ✓ 71.2 Problem solving ✓ ✓ ✓ ✓ ✓ 52.5 Monitoring outcome(s) of behaviour by others without feedback ✓ ✓ ✓ ✓ ✓ 58.1 Behavioural practice/rehearsal ✓ ✓ ✓ ✓ ✓ 512.3 Avoidance/reducing exposure to cues for the behaviour ✓ ✓ ✓ ✓ 41.5 Review behaviour goal(s) ✓ ✓ ✓ 31.7 Review outcome goal(s) ✓ ✓ ✓ 32.4 Self-monitoring of outcome(s) of behaviour ✓ ✓ ✓ 32.7 Feedback on outcome(s) of behaviour ✓ ✓ ✓ 312.1 Restructuring the physical environment ✓ ✓ ✓ 32.1 Monitoring of behaviour by others without feedback ✓ ✓ 23.3 Social support (emotional) ✓ ✓ 25.1 Information about health consequences ✓ ✓ 26.2 Social comparison ✓ ✓ 27.1 Prompts/cues ✓ ✓ 28.2 Behaviour substitution ✓ ✓ 28.6 Generalization of a target behaviour ✓ ✓ 210.3 Non-specific reward ✓ ✓ 210.9 Self-reward ✓ ✓ 215.4 Self-talk ✓ ✓ 21.6 Discrepancy between current behaviour and goal ✓ 1Cradocketal.InternationalJournalofBehavioralNutritionandPhysicalActivity (2017) 14:18 Page5of17Table 1 BCTs used in dietary AND physical activity aspect of intervention (Continued)2.6 Biofeedback ✓ 13.2 Social support (practical) ✓ 17.5 Remove aversive stimulus ✓ 18.3 Habit formation ✓ 19.2 Pros and cons ✓ 110.2 Material reward (behaviour) ✓ 110.4 Social reward ✓ 110.6 Non-specific incentive ✓ 110.7 Self-incentive ✓ 111.2 Reduce negative emotions ✓ 112.2 Restructuring the social environment ✓ 113.1 Identification of self as role model ✓ 113.2 Framing/reframing ✓ 115.1 Verbal persuasion about capability ✓ 115.3 Focus on past success ✓ 1Studies are listed in alphabetical order. (1) [43], (2) [45], (3) [46], (4) [38], (5) [37], (6) [41], (7) [72], (8) [44], (9) [40], (10) ([39], (11) [42], (12) [36], (13) [47]Cradocketal.InternationalJournalofBehavioralNutritionandPhysicalActivity (2017) 14:18 Page6of17calculated as the difference between intervention andcontrol groups. Means and standard deviations (SDs) fromincluded studies were converted to mean differences andSDs of the differences between intervention and controlgroups at 3, 6, 12 and 24 months.Meta-analysisMissing SDs were calculated from SE, t and p values,using the Cochrane guidelines [30]. The mean for onestudy was estimated from the median and range usingHozo’s formula [31]. The SD of the difference in meansfrom baseline to the different time points was calculatedusing the Cochrane guidelines when standard error or95 % confidence intervals were reported. A strategydocumented by previous researchers, which requires acorrelation between baseline and end of interventionmeasurements, was used for the remaining missing data[32, 33]. A correlation of 0.75 was used to calculate themissing SDs for HbA1c data; this value was chosen fol-lowing a sensitivity analysis using correlations of 0.5,0.75 and 0.95, and a previous review and meta-analysis[34]. A correlation of 0.95 was used to calculate themissing SDs for weight loss data, following a further sen-sitivity analysis and previous studies [33, 35]. We alsocalculated the SDs of the difference between baselineand reported time-point means for three studies that re-ported sufficient data to calculate, and this was consist-ent with the correlations we used. As this correlation isonly an estimate as the raw data was unavailable, it isalso suggested that future researchers use the Bayesianprinciple of combining raw data from similar previouslypublished studies to, calculate missing SDs where avail-able and combine these results on similar subjects to im-prove the accuracy of this estimation. It was estimatedthat the HbA1c and weight loss variance is the same atbaseline and reported time points for the control andthe intervention groups when variance was not reported.Effect heterogeneity was assessed using the I2 methodusing the Cochrane guidelines [30]. For the overallmeta-analysis, data reported at the time point closest tothe end of the intervention was used (cf., Avery et al.[7]). A random effects analysis model using the inversevariance statistical method was used. A repeated mea-sures design was not possible as the raw data were un-available. Statistical significance of the moderator andmeta-analysis was set at p ≤ 0.05.Moderator analysisA moderator analysis was conducted to identify associa-tions between BCTs, intervention features and changesin HbA1c using Comprehensive Meta-Analysis (V3). Allstudies were combined using data reported at the timepoint closest to the end of the intervention. The BCTsused for both diet and physical activity aspects ofinterventions were combined for one meta-analysiswhere BCTs were included if present in diet only orphysical activity only or in both. The moderator analysisused the effect size ‘difference in means’ to assess thedata, and carried out subgroup analysis of the includedstudies, comparing presence or absence of BCTs orintervention features. A separate moderator analyseswere also conducted for dietary BCTs and for physicalactivity BCTs. BCTs present in the control group werenot included in the moderator analysis. A random effectsmodel was used to analyse the data.ResultsStudy selection and study characteristicsThirteen studies met the inclusion/exclusion criteria.Summary characteristics of included studies are outlinedin Additional file 1: 1.4. One study [36] reported data formales and females separately so these data are presentedas a mean of both groups. Average age of participantswas 56.7 (±3.9) years for intervention groups and 56.8(±3.9) years for controls. For intervention and controlgroups respectively, mean duration of diabetes, wherereported, was 6.9 (± 1.2) and 8 years (± 3), mean base-line HbA1c 8.03 % (± 1.21 %) and 8 % (± 0.95 %), weight88.5 kg (± 14.5 kg) and 87.9 kg (± 14.8 kg). Only one ofthe included studies [37] was carried out in a commu-nity centre setting, all remaining studies were carriedout in a clinical setting. All participants included in thethirteen studies were classified as having type 2 diabetes.Risk of bias and treatment fidelityOnly one RCT was judged as low risk of bias in each ofthe seven areas assessed [38]. Nine RCTs were judged tohave a combination of low and unclear risk of bias apartfrom three RCTs which were judged to have a high riskof bias in the ‘other bias’ category, [37, 39] ‘blinding ofparticipants and personnel’ and ‘blinding of outcome as-sessment’ categories [40] (Additional file 1: 1.5, 1.6).Inter-rater agreement (0.86) was determined by Cohen’skappa for risk of bias assessment. Results of the assess-ment of treatment fidelity are presented in Additionalfile 1: 1.7. Overall reported use of treatment fidelitystrategies was very low across all categories apart from‘monitoring and improving enactment of treatmentskills’ where 11 out of 13 studies scored ‘yes’ in the sub-category ‘ensuring participants’ use of behavioural skills’.Coding of all subcategories is more comprehensive,however, fidelity assessment is much lower using thismethod.Meta-analysis of changes in HbA1c and body weightMeta-analyses showed differences in HbA1c between inter-vention and control groups of -1.11 % (12 mmol/mol [95 %CI -1.57 to -0.66, P < 0.00001]), -0.67 % (7 mmol/mol [95 %Cradock et al. International Journal of Behavioral Nutrition and Physical Activity  (2017) 14:18 Page 7 of 17CI -1.09 to -0.24 P = 0.002]), -0.28 % (3 mmol/mol [95 % CI-0.52 to -0.03, P = 0.03]), and -0.26 % (2 mmol/mol [95 %CI -0.39 to -0.14, P < 0.001]), at 3 (n = 4), 6 (n = 6), 12 (n =5) and 24 (n = 2) months respectively (Fig. 2). When allstudies and all time points were included in an overallmeta-analysis, reduction in HbA1c was 0.53 % (6 mmol/mol [95 % CI -0.74 to -0.32, P < 0.00001]) (Fig. 3). Sensitiv-ity analysis showed the magnitude of reduction did notchange whether data from time point closest to end ofintervention or final time point reported was used in ana-lysis. Heterogeneity as measured by I2 was 41 %, 88 %, 84 %and 25 % at 3, 6, 12 and 24 months respectively.The difference in body weight between interventionand control groups was -2.7 kg (-4.14 -1.26, P = 0.06),-3.64 kg (-6.05 to -1.23, P = 0.003), -3.77 kg (-7.77 to0.22, P = 0.06), and -3.18 kg (-7.67 to 1.32, P = 0.17), at 3,6, 12 and 24 months respectively (Additional file 1: 1.8).Overall meta-analysis for body mass showed a reductionof -3.73 kg (-6.09 to -1.37, P = 0.002), (Additional file 1:1.9). Heterogeneity as measured by I2 was 60 %, 91 %,97 % and 98 % at 3, 6, 12 and 24 months respectively.Diet and physical activity content of interventionsThe majority of included studies focused on a reduction ofcalories (10 of 13), three studies did not specify the caloricgoal of their intervention [37, 41, 42]. There was an add-itional focus on low fat [39, 43], low carbohydrate [40, 44]and low glycaemic index [45] in some of the included stud-ies. All of the included studies (n = 13) focused on aerobicexercise of a moderate intensity, three also focused onstrength training [38, 42, 46] (Additional file 1: 1.10).BCTs usedInter-rater agreement determined by Cohen’s kappa was0.79 and PABAK was 0.92 (Additional file 1: 1.11). Atotal of 46 different BCTs were applied in the interven-tion groups. Sixteen of these 46 BCTs were reportedonly once. The number of BCTs used in a single RCTranged from 5 [47] to 42 [38], with a mean of 13.5abcdFig. 2 Meta analyses of HbA1c changes (%) at 3 (a), 6 (b), 12 (c) and 24 (d) monthsCradock et al. International Journal of Behavioral Nutrition and Physical Activity  (2017) 14:18 Page 8 of 17(median 11). Individual BCTs and their frequency of useare reported for combined diet and/or physical activitybehaviour in Table 1. Control group BCTs were codedseparately, four different BCTs were identified with ‘in-struction on how to perform a behaviour’ (n = 6) themost frequently occurring. BCTs coded for diet only andphysical activity only are reported in Additional files 1:1.12 and 1.13. BCT analysis by category and BCTs notused are presented in Additional files 1: 1.14 and 1.15.BCTs coded and text rationale for all studies is docu-mented in Additional file 2.Moderator analysis of BCTsModerator analysis showed four BCTs for both behav-iours associated with > 0.3 % reduction in HbA1c. Pres-ence of the BCTs ‘instruction on how to perform abehaviour’ (-0.549 %), ‘behavioural practice/rehearsal’(-0.417 %), ‘action planning’ (-0.385 %) and ‘demonstra-tion of the behaviour’ (-0.343), were associated with clin-ically significant reductions in HbA1c. Seven other BCTswere associated with reductions in HbA1c with the BCTs‘graded tasks’ (-0.217 %), and ‘feedback on behaviour’(-0.203 %) showing the strongest association but thesewere not clinically or statistically significant (Table 2).When the moderator analysis was run separately fordietary BCTs, the BCT ‘demonstration of the behaviour’was associated with clinical and statistically significantreductions in HbA1c. The BCTs ‘behavioural practice/re-hearsal’ and ‘instruction on how to perform a behaviour’,were associated with clinically significant reductions(Additional file 1: 1.16). Moderator analysis for physicalactivity showed three BCTs associated with clinically sig-nificant reductions in HbA1c, ‘instruction on how to per-form a behaviour’, ‘credible source’ and ‘behaviouralpractice/rehearsal’ (Additional file 1: 1.17). Moderatoranalysis of intervention features are documented inTable 3.DiscussionWe found significant mean reductions in HbA1c at threeand six months but not at 12 or 24 months. Reductionsin body weight were observed at all time points andwere greatest at 12 months. Results revealed four BCTsand nine intervention features associated with clinicallysignificant reductions in HbA1c (> 0.3 %). These findingsare exploratory but lay a foundation for future hypoth-eses with clinical and research implications.Combining diet and physical activityOverall HbA1c results of this review highlight the value ofcombining diet and physical activity and the difficulty inmaintaining initial reductions in HbA1c over time. Dietand physical activity interventions produced superior re-sults in our review (-0.53 %) and other reviews (-0.58 %)[48] compared to physical activity only, [7] dietary treat-ment only, [49] computer based interventions [50] andpsychological interventions [51]. Reviews have shown thatphysical activity was associated with a reduction in HbA1c,but only when combined with diet [48, 52]. Our observedreduction in weight (3.73 kg) is similar to other reviews of3.2 kg [53], 3.0 kg [13] and 3 to 5 kg [52] in those at riskof type 2 diabetes but greater than reviews of diet only:low-carbohydrate (0.69 kg) or Mediterranean diets(1.84 kg) [49]. A meta-analysis reported that a physical ac-tivity and behavioural intervention in addition to a dietintervention lost 3 kg more weight than diet only and evengreater weight losses were achieved with higher intensityphysical activity [34].Most interventions in type 2 diabetes focus on mul-tiple rather than single behaviour change [54], howeverchanging multiple behaviours simultaneously is difficult[55]. Changing multiple behaviours simultaneously ra-ther than changing behaviours individually has beenfound to be more effective in changing at least one be-haviour [55]. The mechanistic basis for this is unclear.The extent to which diet and physical activity interven-tions interact synergistically is also unclear. It has beensuggested that successful behaviour change in one be-haviour can facilitate change in other behaviours and itmay be more appropriate to target behavioural patterns[56]. A qualitative study suggested that physical activityplays a greater supporting role for dietary behaviourchange than dietary behaviour change did for physicalactivity, and should be the first behaviour individuals areFig. 3 Overall meta-analysis of mean difference in HbA1c (%) from baseline. (studies with multiple time points are represented by time point closest tothe end of intervention)Cradock et al. International Journal of Behavioral Nutrition and Physical Activity  (2017) 14:18 Page 9 of 17Table 2 Moderator analysis of HbA1c for diet AND physical activity BCTsEffect size 95 % CI Effect size 95 % CI Subgroup analysisBCT No. BCTs k present (absent) Present Lower limit Upper limit Absent Lower limit Upper limit Q P Difference4.1 Instruction on how to perform a behaviour 13 (0) −0.549 −0.762 −0.337 0 1 −0.5498.1 Behavioural practice/rehearsal 5 (8) −0.833 −1.251 −0.415 −0.416 −0.733 −0.1 2.423 0.12 −0.4171.4 Action planning 12 (1) −0.585 −0.811 −0.36 −0.2 −0.922 0.522 0.996 0.318 −0.3856.1 Demonstration of the behaviour 7 (6) −0.701 −0.997 −0.405 −0.358 −0.702 −0.013 2.201 0.138 −0.3438.7 Graded tasks 7 (6) −0.653 −0.96 −0.346 −0.436 −0.785 −0.087 0.833 0.361 −0.2172.2 Feedback on behaviour 7 (6) −0.641 −0.939 −0.343 −0.438 −0.792 −0.084 0.74 0.39 −0.20312.3 Avoidance/reducing exposure to cues for the behaviour 4 (9) −0.694 −1.209 −0.179 −0.53 −0.848 −0.212 0.283 0.595 −0.1642.3 Self-monitoring of behaviour 9 (4) −0.612 −0.894 −0.329 −0.453 −0.846 −0.06 0.414 0.52 −0.1591.2 Problem solving 5 (8) −0.647 −1.111 −0.183 −0.539 −0.869 −0.208 0.139 0.709 −0.1081.5 Review behaviour goal(s) 3 (10) −0.618 −1.09 −0.145 −0.551 −0.859 −0.242 0.054 0.816 −0.06712.5 Adding objects to the environment 7 (6) −0.565 −0.854 −0.276 −0.542 −0.9 −0.183 0.01 0.921 −0.0231.7 Review outcome goal(s) 3 (10) −0.536 −0.943 −0.129 −0.573 −0.861 −0.284 0.021 0.884 0.0372.7 Feedback on outcome(s) of behaviour 3 (10) −0.53 −0.977 −0.082 −0.585 −0.888 −0.282 0.04 0.841 0.0551.1 Goal setting (behaviour) 11 (2) −0.53 −0.772 −0.289 −0.654 −1.17 −0.138 0.182 0.67 0.12412.1 Restructuring the physical environment 3 (10) −0.47 −1.022 0.081 −0.61 −0.923 −0.297 0.186 0.666 0.142.5 Monitoring outcome(s) of behaviour by others without feedback 5 (8) −0.44 −0.818 −0.061 −0.639 −0.942 −0.336 0.647 0.421 0.1991.3 Goal setting (outcome) 10 (3) −0.472 −0.697 −0.247 −0.908 −1.408 −0.409 2.437 0.118 0.4362.4 Self-monitoring of outcome(s) of behaviour 3 (10) −0.251 −0.633 0.131 −0.714 −0.99 −0.438 3.71 0.054 0.4633.1 Social support (unspecified) 10 (3) −0.45 −0.678 −0.221 −0.92 −1.372 −0.468 3.309 0.069 0.479.1 Credible source 12 (1) −0.491 −0.709 −0.274 −1 −1.627 −0.373 2.254 0.133 0.509Meta-analysis (random effects model was used to assess the data)Cradocketal.InternationalJournalofBehavioralNutritionandPhysicalActivity (2017) 14:18 Page10of17Table 3 Moderator analysis of intervention features for diet and physical activityEffect size 95 % CI Effect size 95 % CI Subgroup analysisIntervention Features k present (absent) Present Lower limit Upper limit Absent Lower limit Upper limit Q P DifferenceModeSupervised physical activity component 5 (8) −0.94 −1.323 −0.558 −0.368 −0.631 −0.106 5.852 0.016 −0.572Individual face to face 6 (7) −0.545 −0.885 −0.204 −0.576 −0.905 −0.247 0.017 0.897 0.031Group sessions only 5 (8) −0.856 −1.218 −0.495 −0.408 −0.643 −0.172 4.16 0.041 −0.448Combination of group and individual sessions 4 (9) −0.545 −1.013 −0.077 −0.588 −0.914 −0.263 0.022 0.881 0.043Individual contact only 4 (9) −0.349 −0.712 0.015 −0.661 −0.93 −0.393 1.841 0.175 0.312FrequencyFrequency of total contacts (median = 1.73)a 7 (6) −0.828 −1.083 −0.574 −0.17 −0.456 0.116 11.358 0.001 −0.658Frequency of total contacts (mean 2.61)a 10 (3) −0.705 −0.932 −0.479 −0.101 −0.469 0.268 7.501 0.006 −0.604Frequency of face to face contacts (median 1.96)a 6 (7) −0.934 −1.316 −0.552 −0.313 −0.627 0.001 6.061 0.014 −0.621Frequency of face to face contacts (mean 3.13)a 8 (5) −0.764 −1.089 −0.438 −0.322 −0.678 0.034 3.224 0.073 −0.442ProviderContact with exercise physiologist, trainer 6 (7) −0.762 −1.124 −0.401 −0.398 −0.73 −0.066 2.12 0.145 −0.364Combination of dietitian and exercise physiologist 4 (9) −0.778 −1.222 −0.334 −0.466 −0.778 −0.155 1.272 0.259 −0.312Contact with dietitian/ nutritionist 10 (3) −0.488 −0.677 −0.219 −0.886 −1.316 −0.455 3.093 0.079 0.398Interventionist other than dietitian, exercisephysiologist, i.e. nurse, doctor4 (9) −0.477 −0.848 −0.046 −0.628 −0.928 −0.327 0.5 0.48 0.151IntensityIntensity: number of face to face contacts (median (16)a 7 (6) −0.804 −1.144 −0.465 −0.32 −0.66 0.02 3.9 0.048 −0.484Intensity: number of face to face contacts (mean (20.2)a 4 (9) −0.784 −1.261 −0.307 −0.481 −0.79 −0.172 1.092 0.296 −0.303Intensity: number of total contacts with interventionpersonnel (median (25.5)a7 (6) −0.609 −0.905 −0.314 −0.479 −0.842 −0.117 0.297 0.585 −0.13Intensity: number of total contacts with interventionpersonnel (mean (29.2)5 (8) −0.75 −1.075 −0.426 −0.39 −0.684 −0.097 2.599 0.107 −0.36OtherUse of theory/model to inform intervention 3 (10) −0.483 −0.994 0.029 −0.567 −0.807 −0.327 0.086 0.769 0.084Baseline HbA1c levels >8%b 5 (8) −0.943 −1.397 −0.49 −0.441 −0.677 −0.205 3.707 0.054 −0.502Baseline HbA1c levels >7%b 12 (1) −0.608 −0.837 −0.379 −0.13 −0.754 0.494 1.983 0.159 −0.478Number of BCT's Median (11)c 6 (7) −0.469 −0.806 −0.131 −0.627 −0.932 −0.323 0.469 0.494 0.158Number of BCT's Mean (14.85)c 4 (9) −0.694 −1.209 −0.179 −0.53 −0.848 −0.212 0.283 0.595 −0.164Meta-analysis (random effects model was used to assess the data)aPresent denotes higher frequency/intensity, absent denotes lower frequency/intensity, above and below mean/medianbPresent denotes high baseline HbA1c, absent denotes lower HbA1c, above and below mean/mediancPresent denotes higher number of BCTs, absent denotes lower number of BCTs, above and below mean/medianCradocketal.InternationalJournalofBehavioralNutritionandPhysicalActivity (2017) 14:18 Page11of17encouraged to change [57], however, a study comparingsequential versus simultaneous delivery concluded thatsimultaneous delivery of diet and physical activity pro-grammes may yield the most effective outcomes [58].BCTsFrequently used and number of BCTsThe most frequently used BCTs in diet and physical ac-tivity interventions may not be the most effective. ElevenBCTs showed a reduction in HbA1c, however only six ofthese were among the ten most frequently used BCTssuggesting that only 60 % of the most frequently usedBCTs were effective which could have important impli-cations for intervention study design, resource utilisationand cost effectiveness. A review of physical activity inter-ventions showed that only 50 % of the most frequentlyused BCTs were associated with reductions in HbA1c[7]. It’s possible that less frequently reported BCTs notincluded in the moderator analysis (n = 26) are associ-ated with reductions in HbA1c. Another possible conclu-sion could be that certain BCTs are necessary but notsufficient elements of interventions and perhaps thepresence of certain BCTs is required for the keyBCTs to work as intended. Our work suggests thatresearchers need to conduct a detailed behaviouraldiagnosis prior to designing their interventions, pos-sibly using a framework such as Michie et al.’s COM-B, to align BCTs with sources of behaviour, interven-tion functions and policy categories as different BCTsmay be more appropriate for certain individuals, be-haviours, personalities, psychological profiles or differ-ent modes of delivery.Improvements in HbA1c were also associated with theuse of a greater number of BCTs in this review also ob-served in other studies using HbA1c [7] and weight lossas outcomes [12, 13]. However, how using a greater orlesser number of BCTs in intervention studies can affectoutcomes remains unclear and requires further investi-gation [13]. The number of BCTs used is inextricablylinked to quality of reporting and the fidelity of use ofBCTs. Greater treatment fidelity and quality reporting ofinterventions will enhance confidence, robustness andstudy power of reported results [59].BCTs associated with reductions in HbA1cWe identified four BCTs associated with clinicallysignificant reductions in HbA1c: ‘instruction on how toperform a behaviour’, ‘behavioural practice/rehearsal’‘action planning’ and ‘demonstration of the behaviour’.These have all been reported previously as having apositive impact on diet and physical activity behaviour[13, 14, 17]. Usually the three BCTs: ‘instruction onhow to perform a behaviour’, ‘behavioural practice/re-hearsal’ and ‘demonstration of the behaviour’ arecoded together when delivered through classes suchas exercise or cookery. This coding principle mightexplain the emergence of these three BCTs as key tochanging diet and physical activity behaviour as it’spossible that these three BCTs work in isolation butmore likely that the presence of all three allows themto work synergistically. This also highlights that someBCTs lend themselves well to certain modes of deliv-ery. Success of these three BCTs might be explained bytheir strong theoretical foundations [60, 61]. The SocialCognitive Theory includes ‘observational learning’ as oneof its five basic capabilities of human functioning [61].The ‘vicarious capability’ suggested in this model outlinesour ability to learn through observation and modeling be-haviour of others and is intertwined in these three BCTsand a review of nutrition counseling strategies suggestedincluding skill development coaching/training and dem-onstration or modeling [18].One BCT from the ‘goals and planning’ category, ‘ac-tion planning’ was associated with clinically significantreductions in HbA1c. This BCT has also been associatedwith successful behaviour change in several other studies[7, 12–15, 18]. The BCT ‘action planning’ facilitates be-haviour change by providing a clear pathway in identify-ing context, frequency, duration and intensity of therequired behaviour change. Constructs from this BCThighlight the importance of self-regulatory processes inbehaviour change [62] and can be seen in several behav-iour change theories [63, 64].Two BCTs from the ‘feedback and monitoring’ category‘feedback on behaviour’ and ‘self-monitoring of behaviour’were associated with reductions in HbA1c. These BCTshave also been associated with successful behaviourchange in other studies [12–16, 18] and similar constructsare described in a theoretical model [61]. BCTs in this cat-egory can help keep the behaviour change on track, allowfor adjustment and self-regulation and may be more im-portant in maintaining than initiating behaviour change asit’s necessary to self-monitor behaviour to self-regulate be-haviour [62]. As motivation decreases and opportunitycosts increase, there is a greater need for self-regulatoryeffort [65]. However, according to the Control Theory [66]the self-regulation process of how we set and prioritizeour goals is based on a hierarchical structure. It’s alsothought that the self-regulatory process or willpower tosustain behavioural change draws on a mental resource re-quiring energy and one which can be depleted, makingsubsequent tasks more difficult [67].Several authors have highlighted the benefits of usingthe BCTs ‘goal setting’ [7, 12, 18] ‘goal review’, ‘socialsupport’ [12], ‘prompt practice’ [13], ‘use of follow upprompts’ [15, 18] and ‘prompting generalisation of a tar-get behaviour’ [7] to positively affect behaviour changeof diet and/or physical activity. However, these findingsCradock et al. International Journal of Behavioral Nutrition and Physical Activity  (2017) 14:18 Page 12 of 17were not observed in our review, possibly due to limita-tions outlined in this study or limitations in reporting.BCTs not used and other factorsSome of the best established BCTs [25, 26] for behaviourchange were conspicuous in their absence from any of theRCTs in this review. These included ‘behavioural contract’and ‘commitment’. Behaviour change is almost impossiblewithout a high level of commitment. Interventions couldbenefit from assessing levels of commitment prior tointervention. Lesser-used categories ‘Reward and threat’and ‘Identity’ could also represent opportunities for behav-iour change [14, 68] as identity represents one of thestrongest drivers for behaviour change, and has been asso-ciated with positive changes in health outcomes, [68, 69]as did BCTs using automatic process such as ‘habit forma-tion’ and ‘habit reversal’ [70].It is also possible that some BCTs have a negative ef-fect on behaviour. In this review presence of four BCTs‘goal setting (outcome)’, ‘self-monitoring of outcomes ofbehaviour’, ‘social support’ and ‘credible source’, were as-sociated with clinically significant increases in HbA1c.Although the ‘credible source’ BCT data are heavilyskewed by one study, evidence suggests that monitoringoutcomes of behaviour and setting outcome-relatedgoals may negatively affect diet and/or physical activitybehaviour. This finding warrants further investigation.Another factor not considered in this review is thestudy of epigenetics, the complex relationship betweenthe environment and genes [71] and to what extent dietand physical activity behaviours may be genetically de-termined and influenced.Intervention featuresThis review identified nine intervention features associ-ated with clinically significant reductions in HbA1c. In-terventions where the physical activity component wassupervised (n = 5) showed one of the strongest moderat-ing effects with both aerobic [37, 41, 43] and strengthbased activities [42, 72]. Interventions that use ‘group ses-sions only’ were associated with greater effectiveness thanthose with individual sessions only. However, higher fre-quency and intensity of individual contact was associatedwith greater effectiveness. Evidence suggests that femalesmay benefit more from group sessions [73] while malesmay benefit more from individual sessions [74].Our findings suggest that diet and physical activity in-terventions delivered by an exercise physiologist or anexercise physiologist and a dietitian through face-to-facecontact may be the best way to deliver these interven-tions, though cost-effectiveness was not assessed. Inter-ventions delivered by non-diet or exercise specialists(doctor, nurse) were not associated with success, whichsuggests that diet and/or physical activity interventionsneed to be delivered by experts in that area. While appdelivered interventions hold promise, [75] our findingssuggest that frequent personal contact and supervisedphysical activity may enhance effectiveness.A gradual increase in intensity and frequency of contactcould well assist in achieving maintenance of behaviourchange of diet and physical activity as simple tasks in theinitial stages of interventions, gradually progressing inintensity, could help improve participants’ self-efficacy[76, 77]. Three out of four interventions reporting mul-tiple time points reported that initial reductions in HbA1cwere not maintained [38, 43, 46]. The increased effective-ness of gradually increasing interventions may also be ex-plained by their role in tackling habituation, or boredom,or providing increased support as behaviour change be-comes more challenging following the initial stages.Our review suggests that the BCT ‘graded tasks’ was asso-ciated with a reduction in HbA1c, and positive health out-comes in another review [78]. The BCT ‘graded tasks’ canplay a key role in developing habits which is among the fivetheoretical themes suggested for behavioral change mainten-ance [65] and may inform better maintenance of behaviourchange in diet and physical activity interventions.Use of theoryOnly three out of 13 RCTs mentioned use of a theory ormodel in designing intervention [39, 43, 46]. It wasn’tpossible to ascertain to what degree these studies wereguided by theory as fidelity to theory was not reported.One study [43] reported that the behavioural component‘was based on’ the Social Action theory [79], a secondstudy [39] reported that they used ‘concepts’ from thistheory, while another [46] reported that methods usedwere ‘grounded’ in the Social Cognitive Theory [61]. Inevaluating and developing complex interventions, astrong theoretical understanding is required to identifyand strengthen the weakest links in the causal chain[80]. Interventions guided by theory or theoretical con-structs may be more effective in changing a variety of healthbehaviours than studies not using theory [81]. However, astudy of the extent and use of theory in physical activity andhealthy eating interventions suggested that theories werenot used extensively in the development of interventionsand when theory was used the relationship between effect-iveness and extent and use of theory was weak [82] which iscorroborated by data from this review.Study strengths and limitationsWe used the most recent BCT taxonomy (v1) to code inter-ventions. To maximise the quality of the research beingreviewed only RCTs were included. The detailed reportingof outcomes of HbA1c and reduction in body weight at dif-ferent time points allow for investigation of effect size andtrends over time. The systematic detailing of BCT codingCradock et al. International Journal of Behavioral Nutrition and Physical Activity  (2017) 14:18 Page 13 of 17procedures, results, and high inter-rater reliability allows fu-ture researchers to replicate and review methods used in de-tail. The overall risk of bias was low. This review is, to thebest of our knowledge, the first to document key BCTs andintervention features associated with reductions in HbA1c indiet and physical activity interventions for type 2 diabetes.Some limitations also warrant mention. Results of thisreview can be considered exploratory as no causality ofBCTs/intervention features associated with clinically sig-nificant reductions in HbA1c can be concluded, and thepresence of a BCTcan only infer association. The strict in-clusion criteria limited the review to 13 studies, and largeheterogeneity reduced study power and robustness of re-sults in elucidating HbA1c effect sizes. Coding of the BCTsdepended on the reporting quality, quantity, and accuracywithin the RCTs themselves, and these varied consider-ably. For instance, regarding the Look Ahead Trial[38, 83], when the RCT results paper was coded, 11 BCTswere identified; when the methodology paper was coded,16 BCTs were identified [84]; however, when all 88 sup-porting documents (https://www.lookaheadtrial.org/) werecoded, 42 BCTs were identified. A study of smoking inter-ventions showed similar results [85]. The majority ofreviewed studies did not reference an associated method-ology paper, rendering it possible that other BCTs wereused but not coded. Fidelity was poorly reported, there-fore, it was not possible to determine if BCTs were deliv-ered, received or enacted as intended. It was not possibleto code the dose, frequency or sequence of use of BCTs orto ascertain which BCTs were associated with initiation ormaintenance of behaviour change. Comparisons drawnbetween this review and previous studies should take intoaccount the different BCT Taxonomies used [25, 86–88].Variation between studies in subject’s duration of diabetesand baseline HbA1c may also have increased heterogen-eity. The majority of the included studies did not reportbehaviour change for diet or physical activity as an out-come measure.Implications and future directionsFrom a research perspective we recommend that a formalassessment of the effectiveness of individual and clusteredBCTs in the initiation and maintenance of behaviourchange should be a scientific priority. The hierarchicalranking of BCTs and the synergistic effect of certain BCTsrequires further investigation. We recommend firstly thatclearly defined and reported behavioural outcome mea-sures are incorporated into diet and or physical activity in-terventions and studies follow TIdieR guidelines [89].Secondly, more transparent and comprehensive descrip-tions of BCTs used, fidelity to intervention protocol andclarity regarding the theoretical constructs and modelsused in published studies is required.From a practice perspective, findings of this manuscriptsuggest support for implementing a graded approach togradually increasing frequency and intensity of interven-tion content, structuring interventions so that the keycomponents are delivered by credible experts (i.e. exercisephysiologists and dietitians) and alignment of behaviourchange techniques to target behaviours following a com-prehensive behavioural diagnosis.ConclusionOur findings show that combined diet and physicalactivity interventions achieved clinically meaningful re-ductions in HbA1c at 3 and 6 months, but these werenot sustained at 12 and 24 months. We identified fourBCTs and nine intervention features associated with re-ductions in HbA1c. These exploratory findings mayguide future research into BCTs such as ‘instruction onhow to perform a behaviour’, ‘behavioural practice/re-hearsal’, ‘action planning’, and ‘demonstration of the be-haviour’ which seemed to be associated with betteroutcomes in type 2 diabetic adults in addition to theintervention features identified.Additional filesAdditional file 1: 1.1. PRISMA. 1.2. Search strategy. 1.3. BCT codingrubric/rules. 1.4. Summary Table of included studies. 1.5. Risk of biasassessment for included studies. 1.6. Methodological quality and risk ofbias of individual studies. 1.7. Treatment fidelity. 1.8. Meta-analyses of bodyweight changes at 3, 6, 12 and 24 months. 1.9. Overall meta-analysis ofbody weight changes. 1.10. Intervention content. 1.11. Cohen’s kappa andPABAK for BCT Coding reliability. 1.12. BCTs used in dietary aspect ofintervention. 1.13. BCTs used in physical activity aspect of intervention. 1.14.Breakdown of frequency of BCTs used by Category for diet and physicalactivity behaviour. 1.15. Breakdown of BCTs ‘NOT’ used by category andindividual BCTs. 1.16. Moderator analysis of diet BCTs. 1.17. Moderatoranalysis of physical activity BCTs. (DOCX 328 kb)Additional file 2: Excel file documenting text for each BCT for allincluded studies. (XLSX 113 kb)AcknowledgmentsWe would like to thank Laraib Sherish and Raymond Khanano for theirassistance with the search process, Desi McEwan for assistance with themoderator analysis; Kylie Mallory for assistance with formatting tables. Wewish to thank the Irish Research Council (IRC) for funding this project.FundingPhD scholarship funding was provided to KC by the Irish Research Council (IRC).Availability of data and materialAll data and material is available.Authors’ contributionsKC, LQ, GOL, FF and KMG formulated the research question, defined thesearch terms. KC carried out the electronic searches. KC and KMG carried outthe search process and the methodological assessment, KC and LQ carriedout the BCT coding, HG guided the BCT coding process and acted as amaster coder. KC carried out the moderator analysis and the meta-analysis.All authors were involved in writing and reviewing the final manuscript. Allauthors read and approved the final manuscript.Cradock et al. International Journal of Behavioral Nutrition and Physical Activity  (2017) 14:18 Page 14 of 17Competing interestsThe authors declare that they have no competing interests.Consent for publicationAll authors give their consent for the content of this work to be published.Ethics approval and consent to participateNot Applicable.Author details1Physiology, School of Medicine, NUI Galway, University Road, Galway,Ireland. 2Electrical & Electronic Engineering, School of Engineering &Informatics, NUI Galway, University Road, Galway, Ireland. 3National Centrefor Biomedical Engineering Science, NUI Galway, University Road, Galway,Ireland. 4Bariatric Medicine Service, Galway Diabetes Research Centre, HRBClinical Research Facility, Galway, Ireland. 5School of Health and ExerciseSciences, Faculty of Health and Social Development, The University of BritishColumbia, ART 129– 1147, Research Road, Kelowna, BC V1V 1 V7, Canada.6School of Health and Exercise Sciences, Faculty of Health and SocialDevelopment, The University of British Columbia, ART 129-1147 ResearchRoad, Kelowna, BC V1V 1 V7, Canada.Received: 18 July 2016 Accepted: 17 October 2016References1. 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