Changing Physical Activity Behavior inType 2 DiabetesA systematic review and meta-analysis of behavioral interventions

LEAH AVERY, MSC1

DARREN FLYNN, PHD2

ANNA VAN WERSCH, PHD3

FALKO F. SNIEHOTTA, PHD2

MICHAEL I. TRENELL, PHD1

OBJECTIVEdBehavioral interventions targeting “free-living” physical activity (PA) and exer-cise that produce long-term glycemic control in adults with type 2 diabetes are warranted.However, little is known about how clinical teams should support adults with type 2 diabetesto achieve and sustain a physically active lifestyle.

RESEARCHDESIGNANDMETHODSdWe conducted a systematic review of random-ized controlled trials (RCTs) (published up to January 2012) to establish the effect of behavioralinterventions (compared with usual care) on free-living PA/exercise, HbA1c, and BMI in adultswith type 2 diabetes. Study characteristics, methodological quality, practical strategies for in-creasing PA/exercise (taxonomy of behavior change techniques), and treatment fidelity strategieswere captured using a data extraction form.

RESULTSdSeventeen RCTs fulfilled the review criteria. Behavioural interventions showedstatistically significant increases in objective (standardized mean difference [SMD] 0.45, 95% CI0.21–0.68) and self-reported PA/exercise (SMD 0.79, 95% CI 0.59–0.98) including clinicallysignificant improvements in HbA1c (weighted mean difference [WMD] –0.32%, 95% CI –0.44%to –0.21%) and BMI (WMD –1.05 kg/m2, 95% CI –1.31 to –0.80). Few studies provided detailsof treatment fidelity strategies to monitor/improve provider training. Intervention features (e.g.,specific behavior change techniques, interventions underpinned by behavior change theories/models, and use of $10 behaviour change techniques) moderated effectiveness of behavioralinterventions.

CONCLUSIONSdBehavioral interventions increased free-living PA/exercise and producedclinically significant improvements in long-term glucose control. Future studies should consideruse of theory and multiple behavior change techniques associated with clinically significantimprovements in HbA1c, including structured training for care providers on the delivery ofbehavioural interventions.

Diabetes Care 35:2681–2689, 2012

The global prevalence of diabetes ispredicted to increase from 171 mil-lion individuals (2.8%) in 2000 to

336 million (4.4%) in 2030 (1). Becausethe increase in prevalence is most markedin younger adults, the disease is expectedto inflict a devastating toll on the futureworking-age population in terms of pre-mature coronary heart disease, amputa-tions, and blindness (2). The main causal

risk factor for type 2 diabetes is an imbal-ance between energy expenditure and en-ergy intake through food consumption(3,4). Drug-based interventions are un-likely to provide the solution to this wide-spread problem and interventions aimedat increasing energy expenditure throughphysical activity may provide an effectivealternative, because the majority of peo-ple with type 2 diabetes are physically

inactive when compared with nationalaverages (5).

Physical activity (PA; regular move-ment such as walking) and exercise(structured activities such as running orcycling), along with diet and medication,are the cornerstones of diabetes manage-ment (6). Several reviews (7,8) and meta-analyses (6,9–11) report that increasedPA and/or exercise produce a significantimprovement in glucose control in peoplewith type 2 diabetes, yielding an averageimprovement in hemoglobin A1c (HbA1c)of between 20.4% and 20.6%. Despitethe clear benefits of increased PA and ex-ercise upon glycemic control, little isknown about how clinical care teamsshould support people with diabetes toachieve and sustain a physically activelifestyle. This evidence-practice gap is se-riously hindering the effectiveness of PAand exercise as a therapeutic interventionin routine diabetes care.

Behavioral interventions targeting PAand exercise are heterogeneous in termsof content, implementation, and effec-tiveness. Interventions differ on a range ofdimensions, for example, the theory ofbehavior change used to underpin them;the behavior change techniques used toencourage change (e.g., goal setting, useof follow-up prompts); and delivery of theintervention (e.g., frequency and dura-tion of contact; one-to-one vs. groupdelivery). Working around a theory ormodel of behavior change may assistselecting, sequencing, and communicat-ing relevant behavior change techniques.Techniques, in turn, describe the meansof operationalization, e.g., what interven-tionists do to bring about change, regard-less of the use of explicit theory. Despitethe benefits of behavior change theoryand specific theory-linked behaviorchange techniques (12,13), historicallybehavioral interventions have frequentlyomitted adequate descriptions of the spe-cific theory or model of behavior changeused, explicit details of intervention con-tent, and how this was operationalizedand evaluated (14), limiting the efficacyof the intervention and replication out-side the research setting. Elucidating the

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From the 1Institute of Cellular Medicine, Newcastle University, Newcastle Upon Tyne, U.K.; the 2Institute ofHealth and Society, Newcastle University, Newcastle Upon Tyne, U.K.; and the 3School of Social Sciencesand Law, Teesside University, Middlesbrough, U.K.

Corresponding author: Leah Avery, leah.avery@ncl.ac.uk.Received 16 December 2011 and accepted 8 June 2012.DOI: 10.2337/dc11-2452This article contains Supplementary Data online at http://care.diabetesjournals.org/lookup/suppl/doi:10

.2337/dc11-2452/-/DC1.© 2012 by the American Diabetes Association. Readers may use this article as long as the work is properly

cited, the use is educational and not for profit, and thework is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.

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S Y S T E M A T I C R E V I E W

theory, content, and delivery of interven-tions may help to explain the heterogene-ity in effect sizes usually observed insystematic reviews and, thereby, to iden-tify what works and what does not, whichprovides the evidence needed to directclinical care and research.

Our objective was to conduct a sys-tematic review to answer the followingquestions: are behavioral interventionsmore effective than standard clinical carefor improving “free-living” PA and exer-cise and HbA1c in adults with type 2 di-abetes in clinical or community settings,and what behavior change theories or the-ory-linked behavior change techniques(and other features of behavioral interven-tions) are associated with clinically signifi-cant improvements in HbA1c?

RESEARCH DESIGN ANDMETHODSdThis systematic reviewfollowed a published protocol (15) andthe Preferred Reporting Items for System-atic Reviews and Meta-Analyses (PRISMA)guidelines (16).

Inclusion criteriaStudies were randomized controlled trials(RCTs) of behavioral interventions target-ing free-living PA and exercise in adults(18 years or older) with type 2 diabetes(controlled by diet or oral medication orinsulin therapy) with a minimum follow-up period of 1 month from baseline. In-terventions were delivered in clinical andcommunity settings. Studies also in-cluded the primary outcomes: change inlevel of PA and exercise and change inHbA1c.

Exclusion criteriaStudies were excluded if interventionstargeted PA and exercise and diet, al-though studies were retained if all studyparticipants received a dietary compo-nent that was consistent with usual care.Studies were also excluded if they targetedmultiple chronic diseases; gestationaldiabetes or had no focus on engaging infree-living PA and exercise outside ofsupervised sessions. Studies that includedthe following components were also ex-cluded: combinations of diet or pharma-cological agents with PA and exercise inone arm of the trial; comparisons ofpharmacological agents alongside andagainst PA and exercise; or comparisonsof different behavioral interventions tar-geting PA and exercise that did notinclude a comparison arm that consti-tuted usual care.

Search strategyPsycINFO, Medline, CINAHL, EMBASE,Scopus, and the Cochrane Library weresearched using a combination of MeSHheadings and key words to identify poten-tially relevant literature (SupplementaryTable 1). Searches were completed up toJanuary 23, 2012, and were limited toRCTs published in the English language.Manual searching of reference lists and ci-tation searching of studies fulfilling theeligibility criteria were also conducted.

Selection of studiesTwo authors independently screened thetitles and abstracts of articles. Articlesretained at the first stage were reassessedindependently for inclusion by the sametwo authors using a study selection form,with disagreements resolved via discus-sion with the review team.

Data extractionDetails on the study population, inter-ventions, comparators, and outcomeswere captured using a structured dataextraction form. All included studies un-derwent independent assessment by atleast two of the authors (disagreementswere resolved via discussion). Corre-sponding authors of included studieswere contacted via e-mail to requestadditional data when applicable. TheCochrane Collaboration risk of bias tool(17) was used to appraise methodologicalquality and assess overall risk of bias (low,unclear, or high) within and across stud-ies for each outcome. Data on treatmentfidelity were assessed using publishedguidance (18). Descriptions of interven-tion content were coded into specifictheory-linked behavior change techniquesusing a reliable and comprehensive tax-onomy for intervention techniques target-ing PA (19). Behavior change techniquesutilized in both intervention and usualcare groups were not coded to enableidentification of those techniques thatcould be attributed to changes inoutcomes.

Data synthesisData on changes in PA and exercise,HbA1c, and BMI were synthesized usingmeta-analytic techniques (RevMan v5.1,Cochrane IMS). Studies reporting suffi-cient data to enable calculation of effectsizes were included in meta-analyses.Random effects models were selected toallow for between-group and within-group differences (17). When studies in-cluded multiple trial arms, data on each

intervention arm compared with the usualcare arm were included in meta-analyses.Excessive weightings were controlled instudies with multiple intervention arms,consistent with published guidance (17).Heterogeneity was assessed using I2, withvalues .50% considered heterogeneous(20). Measures of intervention effects onPA and exercise, HbA1c, and BMI are pre-sented as a function of timing of follow-upmeasurements: $1 month to ,6 months(short-term); 6 months (short-term tomedium-term); 12 months (medium-term); and 24 months (long-term). Overallmeasures of effect for interventions repre-sent average effect sizes across these follow-up periods.

To account for variation in the meth-ods used to assess PA and exercise acrossstudies, objective measures (accelero-meter [activity counts and/or minutes spentactive] and pedometer [steps]) were com-bined in meta-analyses. Self-reported dataon PA and exercise were combined ifsufficient information was providedabout the content of the measures (i.e.,7-day recall of PA and conversion of activityintensity into MET values or minutes/hours spent active). Sensitivity analyseswere undertaken by excluding outlyingstudies and any with negative ratings onindices of methodological quality.

Moderator analyses were conductedon characteristics of behavioral interven-tions identified in a minimum of threestudies to explore any impact on changein HbA1c ($20.30% HbAlc as a cutoffvalue for a clinically significant improve-ment). These analyses should be consid-ered exploratory and were undertaken toidentify any potential foci of future re-search and clinical practice.

RESULTSdNineteen articles reporting17 RCTs (21–37) fulfilled the review cri-teria (Supplementary Fig. 1). Two RCTs(27,30) were reported across two articles(38,39). For another four RCTs(21,29,36,37), additional articles wereconsulted to obtain information on inter-vention content (40–47).

Eleven RCTs were conducted in Eu-rope (21,22,24–28,30–32,37), two inAustralia (23,35), three in North America(33,34,36), and one in Asia (29). Authorsof 13 RCTs utilized a theory/model of be-havior change to develop and deliverinterventions: Transtheoretical Model(29–31,37); Social Cognitive Theory(21,22,27,36); and Precede/ProceedModel (35). Four studies stated that inter-ventions were underpinned by multiple

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theories/models: Transtheoretical Modeland Social Cognitive Theory (34); Cogni-tive Behavioral Therapy; Motivational In-terviewing; and Social Cognitive Theory(24–26).

The studies had a combined totalsample size of 1,975. Eight studies in-cluded approximately equal numbers ofwomen and men (25,27–31,36,37),whereas nine studies had disproportion-ate numbers of women (23,32–35) andmen (21,22,24,26). Participants were,on average, aged between 51 and 55(29,33,36,37), 58 and 59 (21,30), 60and 64 (22,23,26–28,31,32,34,35), or66 and 70 years (25). One study includedparticipants aged 35 to 75 years (24). In-formation on time since diagnosis wasdescribed in 11 studies (21,22,24–27,29,31,32,34,36). Twelve studies (21–23,25–27,29,31,32,35–37) reportedsufficient information on managementof type 2 diabetes (diet, oral medication,and/or insulin therapy). A summary ofthe key characteristics of the 17 RCTscan be found in Supplementary Table 2.

Methodological quality assessmentand treatment fidelitySupplementary Table 3 presents details ofmethodological quality assessment andoverall risk of bias within and across stud-ies for each outcome. Eight studies pro-vided sufficient information to establishthe use of adequate randomization se-quences (21,25,27,28,30,31,33,34). Sixstudies provided sufficient detail on themethods used to conceal allocation se-quences (21,24,25,30,31,33). Seven stud-ies provided explicit detail on the use ofblinding of care providers (22,37) or out-come assessors (21,24,25,31,33). The ma-jority of studies provided sufficient detailto establish the likely absence of selectiveoutcome reporting, incomplete outcomedata, and other potential sources of bias.

Twelve studies reported a power cal-culation (21,22,24–31,33,34), with ninereporting achievement of required samplesizes at final follow-up (21,22,26–31,34).One study had an attrition rate of .20%at final follow-up (36). Eleven studies re-ported using an intention-to-treat anal-ysis (21,22,24–28,30,31,33,34). Theoverall risk of bias for HbA1c, self-reportedPA, and BMI was graded as “unclear,” and“low” for objectively assessed PA.

The treatment fidelity assessment(Supplementary Table 4) identified thatall 17 studies provided sufficient detailto establish the use of treatment fidelitystrategies related to study design (e.g.,

measures taken to ensure length/durationand frequency of contact within interven-tion groups).

Five studies referred to training ofinterventionists (21,25,29–31), althoughonly two studies explicitly describedstrategies for monitoring and improvinginterventionist training (21,25). Fourteenstudies described methods to improvedelivery of interventions (21,22,24–27,29–31,33–37) (e.g., providing frequentsupervision to interventionists, usingscripted intervention protocols, and tak-ing steps to control contamination acrossintervention and usual care groups). All 17studies provided sufficient detail to estab-lish use of strategies to monitor and im-prove the ability of patients to understandthe intervention-related cognitive and be-havioral skills and strategies to monitorand improve enactment of intervention-related skills in relevant real-life settings(e.g., prompting participants to set goals,self-monitoring of progress, conductingfollow-up discussions and telephonecalls, and opportunities for participantsto review the effect of increased PA onblood glucose levels).

Changes in PA and exerciseBehavioral interventions (compared withusual care) showed a statistically signifi-cant increase in levels of objectively as-sessed PA and exercise (standardizedmean difference [SMD] = 0.45, 95%CI = 0.21–0.68, I2 = 55%) based on datafrom six studies (24,25,26,30,31,36)(Fig. 1). With the exception of 6 months,this effect was found for the follow-up pe-riod $1 month to ,6 months (SMD =0.70, CI = 0.36–1.04, I2= 0%) and 12months (SMD = 0.42, CI = 0.04–0.80, I2

= 57%). Sensitivity analyses (exclusion ofone study with a high attrition rate) (36)resulted in a slight decrease in magnitudeof the overall effect (SMD = 0.41, CI =0.15–0.66, I2 = 58%) and at the $1month and ,6 months follow-up period(SMD = 0.59, CI = 0.18–1.00, I2= 0%).

Likewise, the 14 RCTs providing self-reported PA and exercise data showed anoverall significant positive interventioneffect (SMD = 0.79, 95% CI = 0.59–0.98,I2 = 74%) (21–23,25–27,29–35,37) (Sup-plementary Fig. 2). These effects weremaintained across all follow-up periods,with the exception of 24 months.

Changes in HbA1c

Behavioral interventions (compared withusual care) showed statistically and clinicallysignificant improvements in HbA1c

(weighted mean difference [WMD] =20.32%, 95% CI = 20.44 to –0.21%,I2 = 8%) based on data from 17 studies(21–37) (Fig. 2). With the exception of$1 month to,6 months, statistically sig-nificant improvements were found acrossall follow-up periods: 6 months (WMD =20.33%, CI =20.67 to 0.00%, I2 = 38%);12 months (WMD = 20.33%, CI = 20.48to 20.18%, I2 = 0%); and 24 months(WMD =20.56%, CI =20.82 to20.30%,I2= 0%). Removal of a study with a highattrition rate (36) did not change theconclusions regarding the overall effect.

Changes in BMIBehavioral interventions targeting PA andexercise (comparedwith usual care) showedan overall statistically significant reductionin BMI (kg/m2) based on data from11 studies (21–25,27,28,30,31,33,37)(WMD = 21.05 kg/m2, 95% CI = 21.31to20.80, I2 = 2%) (Supplementary Fig. 3).Adecrease in BMIwas evident across follow-up periods: $1 month to ,6 months(WMD = 20.75 kg/m2, CI = 21.22 to20.28, I2 = 0%); 6 months (WMD =20.77 kg/m2, CI = 21.39 to 20.15, I2=20%); 12 months (WMD = 21.32 kg/m2,CI = 21.73 to 20.90, I2 = 0%); and 24months (WMD = 21.52 kg/m2, CI =22.23 to20.81, I2= 0%).

Moderators of interventioneffects on HbA1c

Twenty-five different behavior changetechniques were identified across the 17studies (Supplementary Table 5). Thestudies used a minimum of two and amaximum of 14 behavior change techni-ques (median 10, IQR 8).

Exploratory moderator analyses com-paring effect size estimates for trials withor without a range of intervention features(i.e., behavior change techniques, modesof delivery, and theory use, Table 1) sug-gested that effects varied considerably. Al-though these differences do not equateto statistical significance reflecting thelimited power based on the current evi-dence, these analyses suggest that utiliza-tion of 10 different behavior changetechniques within behavioral interven-tions may be associated with clinicallysignificant improvements in HbA1c

($0.3% HbA1c): prompting generaliza-tion of a target behavior; use of follow-upprompts; prompt review of behav-ioral goals; provide information onwhere and when to perform PA; plansocial support/social change; goalsetting (behavior); time management;

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prompting focus on past success; barrieridentification/problem-solving; and pro-viding information on the consequencesspecific to the individual.

Clinically significant improvementsin HbA1c were also suggested for studiesutilizing more behavior change techni-ques (median$10), interventions under-pinned by a theory or model of behaviorchange, and durations of $6 months.These analyses also suggested that dif-ferent modes of intervention delivery,interventions utilizing pedometers, inter-ventions of greater intensity (median$14contacts), and inclusion of a supervisedPA and exercise component were notassociated with clinically significant im-provements in HbA1c.

CONCLUSIONSdThere is evidenceto report that behavioral interventions(with low or unclear risk of bias) target-ing increased PA and exercise producea clinically significant improvementin HbA1c in adults with type 2 diabe-tes. Specific behavior change techniquesmay increase the likelihood of clinicallysignificant improvements in HbA1c.Regarding utilization of behavior changetechniques, more might be better.

Other intervention features such as utili-zation of theory and intervention dura-tion may also impact upon interventioneffectiveness.

A strength of this dataset is that allstudies were undertaken in clinical care orcommunity settings, demonstrating po-tential clinical utility. The major implica-tion of this review is that behavioralinterventions have potential to effectivelyreduce HbA1c in adults with type 2 diabe-tes in routine clinical care. The reductionsin HbA1c of 0.21 to 0.44% are consistentwith previous meta-analyses, including awider collection of PA and exercise stud-ies (6–11). Follow-up periods of ,6months failed to show a significant impactonHbA1c. However,,6months durationis not sufficient to elicit an observable ef-fect on HbA1c, highlighting that longerbehavioral interventions are needed ifclinically meaningful changes in HbA1c

are desired. The benefits to glycemic con-trol were sustained for up to 24 months(Fig. 2) and were comparable with com-mon long-term drug or insulin therapy(48,49). Potential limitations of this re-view are the disparate definitions of“usual care” across studies and the possi-bility of selection and/or performance anddetection bias attributable to either

absence or lack of reporting on allocationconcealment and blinding, respectively.However, blinding of participants andstudy personnel is inherently problem-atic in behavioral studies. Publicationbias is possible, although an inspectionof funnel plots for primary outcomesdid not show any substantial asymmetry,indicating a low risk of publication or smallstudy bias.

Critically, all studies reviewed in-volved supporting adults with diabetesto undertake free-living PA and exercise.Despite the focus on PA and exercise,meta-analyses reported significant het-erogeneity for objective (Fig. 1) and self-reported PA (Supplementary Fig. 2).Although there were individual differ-ences in response, the variations in sensi-tivity and specificity in monitoring PA andexercise between the different objectiveand self-reported methods observed willhave contributed to this heterogeneity.The lack of accurate, standardized, andtransparent methods for monitoring PAand exercise remains a significant barrierto accurately determining the efficacy ofinterventions targeting free-living PA andexercise and should be addressed in fu-ture studies. This lack of sensitivity alsomakes describing what participants are

Figure 1dForest plot for objective PA and exercise. (A high-quality color representation of this figure is available in the online issue.)

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doing difficult, limiting discussion aboutwhat type, intensity, and frequency areminimal and optimal to confer benefit.Furthermore, many interventions reportedreductions in BMI (SupplementaryFig. 3). Because PA or exercise alone is

generally insufficient to incur weightloss (50), this suggests an impact of be-havioral interventions targeting PA andexercise on calorie intake, and Hawthorneeffects cannot be ruled out. Further-more, there is a complex relationship

betweenmode and intensity of activity, nu-trition, and the behavioral methods usedto achieve these that is not addressed inthis article. However, the lack of detailabout calorie intake or different modesof PA and exercise should not detract

Figure 2dForest plot for HbA1c. (A high-quality color representation of this figure is available in the online issue.)

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from the reported clinical utility of be-havioral interventions targeting PA andexercise in terms of long-term glucosecontrol.

The studies identified used a range ofbehavior change theories and behaviorchange techniques that may moderate theeffectiveness of the behavioral interven-tions. Although effect sizes found inmoderator analyses do not differ signifi-cantly from the main findings, they helpidentify specific candidate behaviorchange techniques most likely to be

effective for future research and as potentialfoci for clinical practice. Ten behaviorchange techniques (19) were associatedwith potential clinically significant im-provements in HbA1c: prompting general-ization of a target behavior (e.g., oncePA is performed in one situation, theindividual is encouraged to try it inanother); use of follow-up prompts (e.g.,telephone calls in place of face-to-face ses-sions to supportmaintenance); prompt re-view of behavioral goals (e.g., reviewwhether PA goals were achieved followed

by revisions or adjustments); providinginformation on where and when to beactive (e.g., tips on places and times toaccess local PA and exercise clubs); plansocial support and social change (e.g.,encourage individuals to elicit social sup-port from others to help achieve a PA-related goal); goal setting (e.g., supportingindividuals to formulate specific, mea-surable, achievable, relevant, and timelyPA-related goals); time management(e.g., making time to be active); prompt-ing focus on past success (e.g., identifying

Table 1dModerating effect of intervention features on HbA1c (%)

Intervention feature

Feature ispresent(absent)

Number ofparticipants inwhom feature ispresent (absent)

Feature present,effect size(95% CI)

Feature absent,effect size(95% CI) Difference

Behavior change techniquePrompting generalization ofa target behavior 5 (18) 190 (1,644) 20.73 (21.16 to 20.31) 20.29 (20.44 to 20.15) 20.44

Use of follow-up prompts 16 (7) 1,056 (778) 20.50 (20.67 to 20.33) 20.14 (20.36 to 0.08) 20.36Goal setting (outcome) 3 (20) 123 (1,711) 20.65 (21.23 to 20.07) 20.32 (20.46 to 20.17) 20.33Prompt rewards contingent oneffort/progress toward behavior 3 (20) 123 (1,711) 20.65 (21.23 to 20.07) 20.32 (20.46 to 20.17) 20.33

Prompt review of behavioral goals 14 (9) 920 (914) 20.50 (20.69 to 20.32) 20.17 (20.40 to 0.05) 20.33Provide information on where andwhen to perform the behavior 10 (13) 747 (1,087) 20.54 (20.74 to 20.34) 20.24 (20.39 to 20.09) 20.30

Plan social support/social change 13 (10) 894 (940) 20.50 (20.69 to 20.32) 20.20 (20.41 to 0.01) 20.30Goal setting (behavior) 17 (6) 1,019 (815) 20.44 (20.61 to 20.27) 20.16 (20.47 to 0.15) 20.28Prompting focus on past success 4 (19) 415 (1,419) 20.54 (20.80 to 20.29) 20.29 (20.44 to 20.13) 20.25Provide information on consequencesof behavior to the individual 5 (18) 476 (1,358) 20.51 (20.75 to 20.28) 20.29 (20.46 to 20.12) 20.22

Barrier identification/problem-solving 15 (8) 1,016 (818) 20.44 (20.61 to 20.26) 20.23 (20.48 to 0.02) 20.21Time management 8 (15) 630 (1,204) 20.47 (20.68 to 20.25) 20.27 (20.44 to 20.11) 20.20Teach to use prompts/cues 4 (19) 231 (1,603) 20.42 (20.86 to 0.03) 20.32 (20.47 to 20.17) 20.10Relapse prevention/coping planning 11 (12) 543 (1,291) 20.33 (20.56 to 20.10) 20.32 (20.52 to 20.12) 20.01Provide feedback on performance 7 (16) 336 (1,498) 20.31 (20.61 to 20.01) 20.33 (20.51 to 20.16) 0.02Provide information on consequencesof behavior in general 10 (13) 417 (1,417) 20.24 (20.50 to 0.02) 20.36 (20.55 to 20.16) 0.12

Provide instruction on how toperform the behavior 15 (8) 1,057 (777) 20.29 (20.47 to 20.10) 20.42 (20.64 to 20.20) 0.13

Action planning 6 (17) 339 (1,495) 20.23 (20.53 to 0.07) 20.37 (20.53 to 20.22) 0.14Set graded tasks 10 (13) 1,252 (582) 20.26 (20.46 to 20.06) 20.42 (20.64 to 20.20) 0.16Motivational interviewing 3 (20) 156 (1,678) 20.19 (20.58 to 0.19) 20.35 (20.51 to 20.19) 0.16Prompt self-monitoring of behavior 16 (7) 656 (1,178) 20.18 (20.38 to 0.02) 20.47 (20.68 to 20.25) 0.29Use $10 behavior change techniques 13 (10) 864 (970) 20.48 (20.67 to 20.30) 20.22 (20.42 to 20.03) 20.26

Mode of deliveryCombination of individual face-to-faceand group sessions 3 (20) 78 (1,756) 20.46 (21.00 to 0.08) 20.32 (20.48 to 20.16) 20.14

Individual face-to-face sessions only 12 (11) 1,428 (406) 20.33 (20.52 to 20.14) 20.32 (20.57 to 20.06) 20.01Group sessions only 7 (16) 270 (1,564) 20.27 (20.64 to 0.09) 20.36 (20.50 to 20.22) 0.09Theory or model of behavior change 18 (5) 1,638 (196) 20.37 (20.49 to 20.25) 20.21 (20.72 to 0.29) 20.16Duration of intervention ($6 months) 12 (11) 1,378 (456) 20.40 (20.53 to 20.26) 20.23 (20.52 to 0.07) 20.17Pedometer 8 (15) 377 (1,457) 20.21 (20.47 to 0.05) 20.38 (20.58 to 20.17) 0.25Intensity of intervention ($14 contacts) 11 (12) 1,052 (782) 20.23 (20.40 to 20.07) 20.46 (20.66 to 20.26) 0.23Supervised PA/exercise component 10 (13) 884 (950) 20.28 (20.48 to 20.07) 20.39 (20.58 to 20.19) 0.11

Moderator analyses include behavior change techniques and intervention features that were present or absent in each intervention arm compared with the usual carearm across all 17 RCTs.

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previous successful attempts at PA);barrier identification/problem solving(e.g., identifying potential barriers to PAand ways to overcome them); and pro-viding information on the conse-quences of PA specific to the individual(e.g., information about the benefits andcosts of PA to individuals). This list ofbehavior change techniques is not defini-tive and is limited in terms of statisticalpower by the available body of evidence.More research is needed to determine ef-fectiveness of single or aggregated behav-ior change techniques in randomized trialsand to investigate how clusters of thesetechniques could be individually tailoredfor people with diabetes. To enhance re-producibility, attention should also begiven to highlighting the utilization of spe-cific behavior change techniques, with ref-erence to a reliable taxonomy (19), whendescribing intervention content. BecauseHbA1c is influenced by the type, intensity,and frequency of PA and exercise, it is pos-sible that some of the behavior changetechniques were successful in changingbehavior, but that the level of PA and ex-ercise achieved was insufficient to im-prove glycemic control. The limiteddescription of intervention content instudiesmay also limit the ability to identifythe success of a single behavior changetechnique. As such, caution should begiven to dismissing some of the behaviorchange techniques that, in the current re-view, either were not identified or werenot associated with clinically significantimprovements in HbA1c. Exploratorymoderator analyses suggested that thefollowing intervention features wereassociated with clinically significant im-provements in HbA1c: underpinninginterventions with behavior changetheories/models (although no one modelappeared to hold benefit over others); uti-lizing $10 behavior change techniques;and intervention duration of $6 months.

Further research also is required todetermine what professional training en-ables care providers to effectively deliverbehavioral interventions. Five studies re-ported that individuals delivering theinterventions had been trained for thispurpose, but only two studies providedinformation on mode, content, and utili-zation of strategies for monitoring andimproving delivery of training. Profes-sional training is a crucial component ofbehavioral interventions because it im-proves treatment fidelity and enhancesreproducibility in routine practice. Boththe mode of delivery and pathway of care

provider training have a significantimpact on the cost of delivering theintervention and, as a result, the likeli-hood of implementation in routine care.Future studies, in addition to describingbehavior change theories, behaviorchange techniques and how these wereoperationalized also should report onhow care providers were trained andaspects of treatment fidelity. This in-creased clarity will assist in addressingthe current evidence-practice gap andwillserve to increase the efficacy of PA as amanagement option in routine diabetescare.

Combined, these data reveal that be-havioral interventions targeting increasedPA and exercise in clinical care or commu-nity settings have significant clinical utility.Although these observations are encourag-ing, there remains a pressing need forfurther research to understand how theseshould be optimized and implemented intoroutine clinical care.

AcknowledgmentsdThis study was fundedby the European Union Seventh FrameworkProgramme (FP7/2007-2013) under grantagreement Health-F2-2009-241762 for theproject FLIP. L.A. is supported by a PhDscholarship from the Newcastle Centre forBrain Ageing and Vitality. M.I.T. is supportedby a Senior Fellowship from the National In-stitute of Health Research. F.F.S. is funded byFuse, the Centre for Translational Research inPublic Health, a UK Clinical Research Col-laboration Public Health Research Centre ofExcellence.No conflicts of interest relevant to this ar-

ticle were reported.L.A., D.F., F.F.S., and M.I.T. conceived the

review protocol. F.F.S. and M.I.T. supervisedthe review. L.A., D.F., A.v.W., and F.F.S. de-veloped the search strategy. L.A. performedthe electronic searches. L.A. and D.F. con-ducted the screening of titles and abstracts andevaluated the eligibility of full text articles. L.A.and M.I.T. assessed included studies formethodological quality and overall risk of bias(within and across studies for each outcome).L.A. and D.F. assessed included studies fortreatment fidelity. L.A. conducted the meta-analyses and moderator analyses. All authorsprovided input to the development of themethods, data extraction, data analyses, anddrafting of the manuscript. M.I.T. is theguarantor of this work and, as such, had fullaccess to all data in the study and takes re-sponsibility for the integrity of the data and theaccuracy of the data analysis.Elements of this systematic review were pre-

sented as a poster at the Diabetes UK AnnualProfessional Conference, Glasgow, U.K., 7–9March 2012.

The authors acknowledge the assistance ofLinda Errington, Assistant Librarian, StephanDombrowski, Research Associate, and AndyBryant, ResearchAssistant (Statistician), from theFaculty of Medical Sciences, Newcastle Univer-sity, U.K., for guidance with electronic searchingand meta-analyses. The authors also thank thecorresponding authors of included studies whoresponded to requests for additional data.

References1. Wild S, Roglic G, Green A, Sicree R, King

H. Global prevalence of diabetes: esti-mates for the year 2000 and projectionsfor 2030. Diabetes Care 2004;27:1047–1053

2. Lazar MA. How obesity causes diabetes:not a tall tale. Science 2005;307:373–375

3. Hill JO, Wyatt HR, Reed GW, Peters JC.Obesity and the environment: where dowe go from here? Science 2003;299:853–855

4. Taylor R. Pathogenesis of type 2 diabetes:tracing the reverse route from cure tocause. Diabetologia 2008;51:1781–1789

5. Morrato EH, Hill JO, Wyatt HR,Ghushchyan V, Sullivan PW. Physicalactivity in U.S. adults with diabetes and atrisk for developing diabetes, 2003. Di-abetes Care 2007;30:203–209

6. Boulé NG, Haddad E, Kenny GP, WellsGA, Sigal RJ. Effects of exercise on glyce-mic control and body mass in type 2diabetes mellitus: a meta-analysis of con-trolled clinical trials. JAMA 2001;286:1218–1227

7. Sigal RJ, Kenny GP, Wasserman DH,Castaneda-Sceppa C. Physical activity/exercise and type 2 diabetes. DiabetesCare 2004;27:2518–2539

8. Zanuso S, Jimenez A, Pugliese G,Corigliano G, Balducci S. Exercise for themanagement of type 2 diabetes: a reviewof the evidence. Acta Diabetol 2010;47:15–22

9. Thomas DE, Elliott EJ, Naughton GA.Exercise for type 2 diabetes mellitus.Cochrane Database Syst Rev 2006;3:CD002968

10. Snowling NJ, Hopkins WG. Effects ofdifferent modes of exercise training onglucose control and risk factors for com-plications in type 2 diabetic patients:a meta-analysis. Diabetes Care 2006;29:2518–2527

11. Umpierre D, Ribeiro PAB, Kramer CK,et al. Physical activity advice only orstructured exercise training and associa-tion with HbA1c levels in type 2 diabetes:a systematic review and meta-analysis.JAMA 2011;305:1790–1799

12. Craig P, Dieppe P, Macintyre S, Michie S,Nazareth I, Petticrew M. Developing andevaluating complex interventions: thenew Medical Research Council Guidance.BMJ 2008;337:a1655

care.diabetesjournals.org DIABETES CARE, VOLUME 35, DECEMBER 2012 2687

Avery and Associates

13. Michie S, Prestwich A. Are interventionstheory-based? Development of a theorycoding scheme. Health Psychol 2010;29:1–8

14. Dombrowski SU, Sniehotta FF, Avenell S.Towards a cumulative science of behav-iour change: do current conduct and re-porting of behavioural interventions fallshort of good practice? Psychol Health2007;22:869–874

15. Avery L, Flynn D, van Wersch A, TrenellMI, Sniehotta FF. A systematic review ofbehaviour change interventions targetingphysical activity, exercise and HbA1c inadults with type 2 diabetes. PROSPERO2011:CRD42011001274,2011. Availablefromhttp://www.crd.york.ac.uk/PROSPERO/full_doc.asp?ID=CRD42011001274. Ac-cessed 5 Dec 2011

16. Moher D, Liberati A, Tetzlaff J, AltmanDG; PRISMA Group. Preferred reportingitems for systematic reviews and meta-analyses: the PRISMA statement. PLoSMed 2009;6:e1000097

17. Higgins JPT, Green S (Eds.). Cochranehandbook for systematic reviews of in-terventions version 5.0.2, The CochraneCollaboration, 2009. Available fromwww.cochrane-handbook.org. Accessed3March2011

18. Bellg AJ, Borrelli B, Resnick B, et al.Treatment FidelityWorkgroup of the NIHBehavior Change Consortium. Enhancingtreatment fidelity in health behaviorchange studies: best practices and rec-ommendations from the NIH BehaviorChange Consortium. Health Psychol 2004;23:443–451

19. Michie S, Ashford S, Sniehotta FF,Dombrowski SU, Bishop A, French DP. Arefined taxonomy of behaviour changetechniques to help people change theirphysical activity and healthy eatingbehaviours: the CALO-RE taxonomy.Psychol Health 2011;26:1479–1498

20. Higgins JPT, Thompson SG, Deeks JJ,Altman DG. Measuring inconsistency inmeta-analyses. BMJ 2003;327:557–560

21. Balducci S, Zanuso S, Nicolucci A, et al.Italian Diabetes Exercise Study (IDES)Investigators. Effect of an intensive exer-cise intervention strategy on modifiablecardiovascular risk factors in subjects withtype 2 diabetes mellitus: a randomizedcontrolled trial: the Italian Diabetes andExercise Study (IDES). Arch Intern Med2010;170:1794–1803

22. Balducci S, Zanuso S, Nicolucci A, et al.Anti-inflammatory effect of exercise train-ing in subjects with type 2 diabetes and themetabolic syndrome is dependent on exer-cise modalities and independent of weightloss. Nutr Metab Cardiovasc Dis 2010;20:608–617

23. Cheung NW, Cinnadaio N, Russo M,Marek S. A pilot randomised controlledtrial of resistance exercise bands in themanagement of sedentary subjects with

type 2 diabetes. Diabetes Res Clin Pract2009;83:e68–e71

24. DeGreefK,Deforche B, Tudor-LockeC,DeBourdeaudhuij I. A cognitive-behaviouralpedometer-based group intervention onphysical activity and sedentary behaviourin individuals with type 2 diabetes. HealthEduc Res 2010;25:724–736

25. De Greef K, Deforche B, Tudor-Locke C,De Bourdeaudhuij I. Increasing physicalactivity in Belgian type 2 diabetes patients:a three-arm randomized controlled trial.Int J Behav Med 2011;18:188–198

26. De Greef KP, Deforche BI, Ruige JB, et al.The effects of a pedometer-based behav-ioral modification programwith telephonesupport on physical activity and sedentarybehavior in type 2 diabetes patients. Pa-tient Educ Couns 2011;84:275–279

27. Di Loreto C, Fanelli C, Lucidi P, et al.Validation of a counseling strategy topromote the adoption and the mainte-nance of physical activity by type 2 di-abetic subjects. Diabetes Care 2003;26:404–408

28. Gram B, Christensen R, Christiansen C,Gram J. Effects of nordic walking andexercise in type 2 diabetes mellitus: a ran-domized controlled trial. Clin J Sport Med2010;20:355–361

29. Kim CJ, Kang DH. Utility of a Web-basedintervention for individuals with type 2diabetes: the impact on physical activitylevels and glycemic control. Comput In-form Nurs 2006;24:337–345

30. Kirk A, Mutrie N, MacIntyre P, Fisher M.Effects of a 12-month physical activitycounselling intervention on glycaemiccontrol and on the status of cardiovascularrisk factors in people with Type 2 di-abetes. Diabetologia 2004;47:821–832

31. Kirk A, Barnett J, Leese G, Mutrie N.A randomized trial investigating the 12-month changes in physical activity andhealth outcomes following a physical ac-tivity consultation delivered by a personor in written form in Type 2 diabetes:Time2Act. Diabet Med 2009;26:293–301

32. Ligtenberg PC, Hoekstra JBL, Bol E,Zonderland ML, Erkelens DW. Effects ofphysical training on metabolic control inelderly type 2 diabetes mellitus patients.Clin Sci (Lond) 1997;93:127–135

33. Plotnikoff RC, Eves N, Jung M, Sigal RJ,Padwal R, Karunamuni N. Multicompo-nent, home-based resistance training forobese adults with type 2 diabetes: a ran-domized controlled trial. Int J Obes(Lond) 2010;34:1733–1741

34. Plotnikoff RC, Pickering MA, Glenn N,et al. The effects of a supplemental,theory-based physical activity counselingintervention for adults with type 2 di-abetes. J Phys Act Health 2011;8:944–954

35. Samaras K, Ashwell S, Mackintosh AM,Fleury AC, Campbell LV, Chisholm DJ.Will older sedentary people with non-insulin-dependent diabetes mellitus start

exercising? A health promotion model.Diabetes Res Clin Pract 1997;37:121–128

36. Tudor-Locke C, Bell RC, Myers AM, et al.Controlled outcome evaluation of theFirst Step Program: a daily physical ac-tivity intervention for individuals withtype II diabetes. Int J Obes Relat MetabDisord 2004;28:113–119

37. Wisse W, Rookhuizen MB, de Kruif MD,et al. Prescription of physical activity is notsufficient to change sedentary behaviorand improve glycemic control in type 2diabetes patients. Diabetes Res Clin Pract2010;88:e10–e13

38. Di Loreto C, Fanelli C, Lucidi P, et al.Make your diabetic patients walk: long-term impact of different amounts of physicalactivity on type 2 diabetes. Diabetes Care2005;28:1295–1302

39. Kirk A, Mutrie N, MacIntyre P, Fisher M.Increasing physical activity in people withtype 2 diabetes. Diabetes Care 2003;26:1186–1192

40. Kim CJ, Hwang AR, Yoo JS. The impactof a stage-matched intervention to pro-mote exercise behavior in participantswith type 2 diabetes. Int J Nurs Stud 2004;41:833–841

41. Yoo JS, Hwang AR, Lee HC, Kim CJ.Development and validation of a com-puterized exercise intervention programfor patients with type 2 diabetes mellitusin Korea. Yonsei Med J 2003;44:892–904

42. Tudor-Locke CE, Myers AM, Rodger NW.Development of a theory-based daily ac-tivity intervention for individuals withtype 2 diabetes. Diabetes Educ 2001;27:85–93

43. Tudor-Locke CE, Myers AM, Bell RC,Harris SB, Wilson Rodger N. Preliminaryoutcome evaluation of the First StepProgram: a daily physical activity in-tervention for individuals with type 2diabetes. Patient Educ Couns 2002;47:23–28

44. Tudor-LockeC. Promoting lifestyle physicalactivity: Experiences with the first step pro-gram. Am J Lifestyle Med 2009;3(Suppl):508–548

45. Calfas KJ, Long BJ, Sallis JF, Wooten WJ,Pratt M, Patrick K. A controlled trial ofphysician counseling to promote the adop-tion of physical activity. Prev Med 1996;25:225–233

46. van Sluijs EMF, van Poppel MNM, TwiskJWR, Chin A Paw MJ, Calfas KJ, vanMechelen W. Effect of a tailored physicalactivity intervention delivered in generalpractice settings: results of a randomizedcontrolled trial. Am J Public Health 2005;95:1825–1831

47. Balducci S, Zanuso S, Massarini M, et al.Italian Diabetes Exercise Study (IDES)Group. The Italian Diabetes and ExerciseStudy (IDES): design and methods for aprospective Italian multicentre trial of in-tensive lifestyle intervention in people

2688 DIABETES CARE, VOLUME 35, DECEMBER 2012 care.diabetesjournals.org

Changing physical activity behavior in diabetes

with type 2 diabetes and the metabolicsyndrome. Nutr Metab Cardiovasc Dis2008;18:585–595

48. UK Prospective Diabetes Study (UKPDS)Group. Intensive blood-glucose controlwith sulphonylureas or insulin comparedwith conventional treatment and risk of

complications in patients with type 2 di-abetes (UKPDS 33). Lancet 1998;352:837–853

49. UK Prospective Diabetes Study (UKPDS)Group. Effect of intensive blood-glucosecontrol with metformin on complica-tions in overweight patients with type 2

diabetes (UKPDS 34). Lancet 1998;352:854–865

50. Miller WC, Koceja DM, Hamilton EJ. Ameta-analysis of the past 25 years of weightloss research using diet, exercise or diet plusexercise intervention. Int J Obes RelatMetab Disord 1997;21:941–947

care.diabetesjournals.org DIABETES CARE, VOLUME 35, DECEMBER 2012 2689

Avery and Associates