Appendix Table A1.
Meta-analyses included in the meta-review, clustered by primary focus, and, within each cluster, ordered from highest to lowest methodological quality (AMSTAR 2 score).
| Citation | Brief aim(s) (year of literature search) | Intervention type(s) | Population diagnosis | Included studies (k) | Participants (n) | Proportion of AMSTAR 2 items satisfied |
|---|---|---|---|---|---|---|
| Primary Focus: Prevent Risky Behaviours (l = 15) | ||||||
| Chamberlain, O’Mara-Eves, Porter, Coleman, Perlen, Thomas, & McKenzie (2017) | Evaluate psychosocial interventions for smoking cessation in pregnancy; compare intervention strategies (i.e., counselling, health education, feedback, social support, incentives, and exercise). (2015) | Broad | Female smokers or recent quitters who are pregnant or seeking pre-pregnancy consultation | 102 | 30,000 | 0.88 |
| Ebbert, Elrashidi, & Stead (2015) | Assess the effects of behavioural and pharmacotherapeutic interventions to treat smokeless tobacco use. (2015) | Broad | Users of smokeless tobacco | 20 | 9,982 | 0.78 |
| Hajek, Stead, West, Jarvis, Hartmann-Boyce, & Lancaster (2013) | Assess whether specific interventions for relapse prevention reduce the proportion of recent quitters who return to smoking. (2013) | Relapse prevention | Former smokers | 63 | NR | 0.69 |
| Scott-Sheldon, Carey, Elliott, Garey, & Carey (2014) | Evaluate alcohol interventions and identify intervention components that increase their efficacy. (2013) | Broad | First-year university students | 41 | 24,294 | 0.53 |
| Tanner-Smith & Lipsey (2015) | Synthesize brief alcohol interventions and assess whether effects are associated with intervention and participant characteristics; examine persistence of the effects. (2013) | Brief | Adolescents (age 11–18) and young adults (age 19–30) | 185 | NR | 0.47 |
| Cristea, Kok, & Cuijpers (2016) | Evaluate CBM interventions for addiction-related outcomes. (2015) | CBM/ICT | People with addiction(s) | 24 | 3,175 | 0.44 |
| Tanner-Smith, Steinka-Fry, Hennessy, Lipsey, & Winters (2015) | Synthesize brief alcohol-reduction interventions; examine BCTs associated with effects (e.g., decisional balance, goal-setting exercises); evaluate whether intervention duration and follow-up timing matter for effects. (2013) | Brief | Youth aged 11 to 25 who have alcohol and perhaps other drug use problems | 67 | NR | 0.44 |
| Bartlett, Sheeran, & Hawley (2014) | Evaluate BCTs most associated with more effective smoking cessation interventions. (2012) | Broad | Smokers with a diagnosis of COPD | 17 | 7,446 | 0.44 |
| Allom, Mullan, & Hagger (2016) | Evaluate inhibitory training effect and determine what moderators account for unique variance in this effect. (2015) | CBM/ICT | Not restricted to any population or diagnosis | 14 | NR | 0.41 |
| Tyson, Covey, & Rosenthal (2014) | Review interventions informed by the theory of planned behaviour or theory of reasoned action aimed at reducing heterosexual risk behaviours (prevention of STDs and unwanted pregnancies). (2013) | Broad | Not restricted to any population or diagnosis | 32 | NR | 0.39 |
| Spohr, Nandy, Gandhiraj, Vemulapalli, Anne, & Walters (2015) | Evaluate SMS text message-based interventions for individual smoking cessation. (2014) | mHealth/online | Smokers | 13 | 13,626 | 0.34 |
| Onrust, Otten, Lammers, & Smit (2016) | Synthesize school-based universal and targeted prevention programmes, examining which types of programmes are most effective for groups at various developmental stages. (2013) | Broad | Children and adolescents attending school | 241 | 436,180 | 0.28 |
| Song, Huttunen-Lenz, & Holland (2010) | Review RCTs on smoking relapse prevention; examine underlying theories or mechanisms; conduct exploratory meta-analysis. (2009) | Psychological | Former smokers or current smokers who wish to quit | 49 | NR | 0.25 |
| Albarracín, Albarracín, & Durantini (2008) | Evaluate HIV/AIDS prevention interventions. (2005) | Broad | U.S. Latinx and Latin American populations | 142 | 110,092 | 0.08 |
| St. Amand, Bard, & Silovsky (2008) | Evaluate success of treatments for child sexual abuse victims. (NR) | Broad | Outpatient children, 12 years and younger who had experienced a form of sexual abuse | 11 | 1,081 | 0.08 |
| Primary Focus: Promote Healthy Behaviours (l = 30) | ||||||
| O’Brien, McDonald, Araujo-Soares, Lara, Errington, Godfrey, Meyer, Rochester, Mathers, White, & Sniehotta (2015) | Examine whether PA interventions produce long-term effects; examine potential factors that may moderate these effects. | Broad | Free-living, healthy adults, those at risk of chronic disease, aged 55–70 years | 19 | 10,423 | 0.75 |
| Sykes-Muskett, Prestwich, Lawton, & Armitage (2015) | Evaluate evidence for weight-loss-related monetary contingency contracts. (2014) | Broad | Overweight and obese individuals | 30 | NR | 0.63 |
| McEwan, Harden, Zumbo, Sylvester, Kaulius, Ruissen, Dowd, & Beauchamp (2016) | Assess effect of goal setting interventions in relation to individual PA behaviour; examine moderator variables related to characteristics of the study, sample characteristics, and goal attributes. (2015) | Broad | Not restricted to any population or diagnosis | 45 | 5,912 | 0.63 |
| Lim, O’Reilly, Behrens, Skinner, Ellis, Dunbar (2015) | Determine effectiveness of various lifestyle intervention components (intervention type and duration, use of self-monitoring, delivery format, and delivery medium) on weight loss. (2014) | Broad | First year post-partum women | 46 | 4,342 | 0.56 |
| Lin, Liu, Hsu, & Tsai (2017) | Evaluate self-management programs on intradialytic weight gain, self-efficacy, anxiety, depression), and health-related quality of life. (2017) | Self-management | Patients with diagnosis of Stage 1–5 CKD | 18 | 1,647 | 0.53 |
| Jones, Di Lemma, Robinson, Christiansen, Nolan, Tudur-Smith, & Field (2016) | Evaluate laboratory studies of inhibition control training for appetitive behaviour change; investigate candidate mechanisms of action, individual differences that may moderate its effectiveness, and compare it to other psychological interventions. (2014) | CBM/ICT | Adults | 14 | 1,091 | 0.53 |
| Sheeran, Maki, Montanaro, Avishai-Yitshak, Bryan, Klein, Miles, & Rothman (2016) | Evaluate the extent to which changing attitudes, norms, or self-efficacy solely or in combination lead to changes in health-related intentions and behaviour; examine several factors (study quality, theoretical basis of the intervention, sample characteristics, measurement factors, and features of the targeted behaviour) that could moderate such effects. (2015) | Broad | Not restricted to any population or diagnosis | 151 | NR | 0.50 |
| Harkin, Webb, Chang, Prestwich, Conner, Kellar, Benn, & Sheeran (2016) | Evaluate impact of interventions on both the frequency of progress monitoring and rates of goal attainment; determine whether effects hinge on progress monitoring and behaviour changes; evaluate whether effects hinge on dimensions of progress monitoring and other intervention, methodological, and sample characteristics. (NR) | Broad | Not restricted to any population or diagnosis | 138 | 19,951 | 0.47 |
| Lara, Evans, O’Brien, Moynihan, Meyer, Adamson, Errington, Sniehotta, White, & Mathers (2014) | Identify the BCTs associated with more effective dietary interventions (especially for food and vegetable intake); evaluate whether behaviour theories were associated effectiveness. (2013) | Broad | Adults of retirement age | 22 | 63,189 | 0.47 |
| Michie, Abraham, Whittington, McAteer, & Gupta (2009) | Examine whether BCTs differentially relate to self-regulation success. (2008) | Behaviour and/or cognitive change strategies | Adults | 101 | 44,747 | 0.47 |
| Turton, Bruidegom, Cardi, Hirsch, & Treasure (2016) | Compare the effectiveness of methods useful to change eating behaviours (i.e., implementation intentions, food-specific inhibition training, and attention bias modification training). (2014) | CBM/ICT/II | Not restricted to any population or diagnosis | 44 | NR | 0.44 |
| Knittle, Maes, & de Gucht (2010) | Evaluate psychological interventions of increasing PA, as well as of reducing pain, disability, depressive symptoms, and anxiety; see if interventions succeed better if they include more self-regulation theory techniques. (2009) | Broad | Adults with rheumatoid arthritis | 27 | NR | 0.41 |
| Brannon & Cushing (2015) | Identify interventions to promote PA and healthy diet. (NR) | mHealth/online | Healthy children and adolescents without chronic illness or obesity | 74 | 75,541 | 0.41 |
| Abraham & Graham-Rowe (2009) | Evaluate effectiveness of worksite interventions to enhance PA. (2007) | Worksite | Working employees | 37 | 16,516 | 0.39 |
| Higgins, Middleton, Winner, & Janelle (2014) | Evaluate PA RCT interventions in terms of PA behaviour and EXSE or BSE; identify intervention characteristics associated with changes in EXSE, BSE, and PA. (2011) | Broad | Healthy adults | 20 | 3,941 | 0.38 |
| Dombrowski, Sniehotta, Avenell, Johnston, MacLennan, & Araújo-Soares (2012) | Examine whether mode of intervention delivery and particular BCTs used relate to intervention success. (2009) | Broad | Mean or median BMI ≥ 30 (plus comorbidity factor for morbidity or possess the risk for one) | 44 | NR | 0.38 |
| Cugelman, Thelwall, & Dawes (2011) | Evaluate online intervention features to guide the development of population-wide campaigns targeting voluntary lifestyle behaviours; evaluate the roles of intervention exposure (dose) and intervention efficacy. (2009) | mHealth/online | Not restricted to any population or diagnosis | 31 | 17,524 | 0.31 |
| Casey, Coote, Shirazipour, Hannigan, Motl, Martin Ginis, & Latimer-Cheung (2017) | Evaluate whether modifiable, individual-level psychosocial constructs in interventions improve PA participation in people with MS. (2015) | Broad | People with MS | 26 | 3,363 | 0.31 |
| Bravata, Smith-Spangler, Sundaram, Gienger, Lin, Lewis, Stave, Olkin, & Sirard (2007) | Evaluate whether pedometer use affects PA (as well as changes in body weight, serum lipid levels, fasting serum glucose and insulin, and blood pressure); evaluate whether setting daily step goals improves health outcomes. (2006) | Other | Outpatient adults | 26 | 2,767 | 0.31 |
| Toli, Webb, & Hardy (2016) | Investigate how implementation intentions affect goal attainment in clinical samples. (2014) | Broad | Clinical samples with DSM-IV/ICD-10 or other standardized clinical diagnosis | 29 | 1,652 | 0.31 |
| Epton, Harris, Kane, van Koningsbruggen, & Sheeran (2015) | Evaluate self-affirmation interventions to promote responsiveness to health-risk information in terms of accepting the information, intentions to adopt the recommended behaviours, and subsequent behaviour. (2013) | Broad | Not restricted to any population or diagnosis | 41 | NR | 0.31 |
| Conn, Hafdahl, & Mehr (2011) | Summarize the effects of interventions designed to increase PA among healthy adults. (NR) | Broad | Healthy adults | 358 | 99,011 | 0.28 |
| Conn, Hafdahl, Brown, & Brown (2008) | Integrate results interventions designed to increase PA and examine whether effects depend on characteristics of interventions, sample, or methodology. (2004) | Broad | Adults with chronic illnesses | 163 | 22,527 | 0.28 |
| van Genugten, Dusseldorp, Webb, & van Empelen (2016) | Evaluate effectiveness of online interventions designed to promote health-related behaviour; develop a taxonomy for coding the usability of online interventions; identify what combinations of BCTs, modes of delivery, and usability factors influence results. (2008) | Broad | Not restricted to any population or diagnosis | 52 | NR | 0.25 |
| Olander, Fletcher, Williams, Lou, Turner, & French (2013) | Identify which BCTs were associated with increases or decreases in self-efficacy for PA and assess whether a BCTs that improved self-efficacy also improved PA. (2011) | Broad | Sample mean BMI ≥ 30 | 58 | NR | 0.25 |
| Bélanger-Gravel, Godin, & Amireault (2013) | Investigate the effectiveness of implementation intentions on PA; explore potential conditions when implementation intentions have significantly increase PA. (2009) | II | Adults aged 18 to 64 | 24 | 6,366 | 0.22 |
| McDermott, Oliver, Iverson, & Sharma (2016) | Evaluate whether changes in intention relate to behaviour; identify BCTs most associated with these changes. (2016) | Broad | Not restricted to any population or diagnosis | 25 | 6,306 | 0.14 |
| Adriaanse, Vinkers, De Ridder, Hox, & De Wit (2011) | Examine whether implementation intentions help people put their intentions to eat a healthy diet into practice; investigate factors that influence implementation intentions’ effectiveness. (NR) | II | Not restricted to any population or diagnosis | 21 | NR | 0.14 |
| French, Olander, Chisholm, & McSharry (2014) | Identify BCTs that increase self-efficacy and PA; assess whether changes in self-efficacy are also associated with changes in PA. (2012) | Broad | Non-clinical, community-dwelling adults 60-years old or over | 24 | NR | 0.11 |
| Darling & Sato (2017) | Examine use of mHealth technologies on weight status and dietary choices or PA. (2016) | Self-monitoring and mHealth | Children or adolescents who are primary users of mobile technology | 14 | 2,369 | 0.08 |
| Primary Focus: Cardiovascular disease prevention and management (l = 7) | ||||||
| Samdal, Eide, Barth, Williams, & Meland (2017) | Evaluate behavioural interventions to increase PA and healthy eating in short- and long-term contexts; and examine if success depends on BCTs and other study characteristics. (2014) | Behaviour and/or cognitive change strategies | Overweight and obese adults | 48 | 11,183 | 0.78 |
| Janssen, De Gucht, Dusseldorp, & Maes (2012) | Examine whether recent lifestyle modification programmes improve CHD risk factors and related health behaviours, reduce mortality and cardiac recurrences; determine whether efficacy depends on particular BCTs or on aspects of the control condition. (NR) | Broad | CHD patients eligible for cardiac rehabilitation or with particular CHD-related diagnoses. | 38 | 11,085 | 0.66 |
| Goodwin, Ostuzzi, Khan, Hotopf, & Moss-Morris (2016) | Evaluate lifestyle behaviour change RCTs for health behaviours, BP, BMI, and CHD events and mortality (intermediate outcomes) and see whether these depend on particular BCTs and structure (length, format, theoretical basis). (2016) | Broad | CHD patients with varying diagnoses | 22 | 16,766 | 0.56 |
| Fletcher, Hartmann-Boyce, Hinton, & McManus (2015) | Synthesize the literature to determine the effect of self-monitoring of BP on MA, medication persistence, and lifestyle factors in people with hypertension. (2014) | Self-monitoring | Patients with hypertension who were receiving ambulatory or outpatient care | 28 | 7,021 | 0.53 |
| Glynn, Murphy, Smith, Schroeder, & Fahey (2010) | Summarise evidence from non-pharmacological RCT interventions to improve the management of hypertension in primary care. (2008) | Self-manage and broad/other | Patients with essential hypertension in an ambulatory setting | 72 | NR | 0.53 |
| Bray, Holder, Mant, & McManus (2010) | Evaluate evidence for self-monitoring in hypertension compared to usual care (no self-monitoring of blood pressure). (2009) | Self-management and self-monitoring | Not restricted to any population or diagnosis | 25 | 6,278 | 0.47 |
| Chase, Bogener Ruppar, & Conn (2016) | Evaluate effectiveness of MA intervention research; explore potential moderators of intervention effectiveness. (NR) | Broad | Patients with CAD diagnosis | 24 | 18,839 | 0.33 |
| Primary Focus: Diabetes (l = 6) | ||||||
| Malanda, Welschen, Riphagen, Dekker, Nijpel, & Bot (2012) | Evaluate effects of self-monitoring of blood glucose in patients with T2D who are not using insulin. (2011) | Self-management | Patients with noninsulin-treated T2D | 12 | 3,259 | 0.84 |
| Farmer, Perera, Ward, Heneghan, Oke, Barnett, Davidson, Guerci, Coates, Schwedes, & O’Malley (2012) | Evaluate effectiveness of self-monitoring blood glucose level in people with non-insulin treated T2D compared with clinical management without self-monitoring, and to explore the effects in specific patient groups. (2010) | Self-management and self-monitoring | Patients with non-insulin-treated T2D | 6 | 2,552 | 0.69 |
| Zhu, Zhu, & Leung (2016) | Examine how self-monitoring of blood glucose affects diabetes patients in RCTs; investigate whether ethnicity and living environment associates with effects of self-monitoring of blood glucose. (2015) | Self-monitoring | Patients with non-insulin-treated T2D | 15 | 3,383 | 0.66 |
| Bolen, Chandar, Falck-Ytter, Tyler, Perzynski, Gertz, Sage, Lewis, Cobabe, Ye, Menegay, & Windish (2014) | Evaluate the effectiveness and safety of patient-activating interventions for adults with T2D on a range of clinically relevant outcomes. (2011) | Self-management and broad/other | Non-pregnant persons with T2D | 138 | 33,124 | 0.63 |
| Sherifali, Bai, Kenny, Warren, & Ali (2015) | Evaluate the most effective T2D self-management education or support strategies in older adults, as measured by HbA1c, blood pressure, and lipids (total cholesterol, triglycerides, high-density and low-density lipoproteins). (NR) | Self-management and broad/other | Adults with T2D | 13 | 4,517 | 0.53 |
| Cheng, Sit, Choi, Chair, Li, & He (2017) | Evaluate effectiveness of interactive self-management interventions on glycaemic-control and patient-centred outcomes. (2015) | Self-management | Individuals with poorly controlled T2D | 16 | 3,545 | 0.50 |
| Primary Focus: Medical Regimen/Medication Adherence (l = 8) | ||||||
| Lenferink, Brusse-Keizer, van der Valk, Frith, Zwerink, Monninkhof, van der Palen, & Effing (2017) | Evaluate the efficacy of self-management interventions that include an action plan for exacerbations of COPD (vs. usual care) in terms of health-related quality of life, respiratory-related hospital admissions and other health outcomes. (2016) | Self-management and broad/other | Participants with COPD; people with compromised post-bronchodilator forced expiratory volume; none with primary diagnoses of asthma | 22 | 3,854 | 0.88 |
| Luangasanatip, Hongsuwan, Limmathurotsakul, Lubell, Lee, Harbarth, Day, Graves, & Cooper (2015) | Evaluate the relative efficacy of the World Health Organization 2005 campaign and other interventions to promote hand hygiene among healthcare workers in hospital settings and to summarize associated information on use of resources. (2014) | Broad | Healthcare workers in hospital settings | 41 | NR | 0.69 |
| Demonceau, Ruppar, Kristanto, Hughes, Fargher, Kardas, Geest, Dobbels, Lewek, Urquhart, & Vrijens (2013) | Integrate RCTs evaluating interventions to enhance MA to prescribed medications, as assessed by electronic medication-event monitoring methods. (2012) | Broad | Not restricted to any population or diagnosis | 79 | 5,237 | 0.66 |
| Denford, Taylor, Campbell, & Greaves (2014) | Review interventions targeting asthma self-care in adults with asthma; explore BCTs associated with change in asthma morbidity or symptoms, unscheduled health care use, and MA. (2013) | Other | Participants with a diagnosis of asthma | 38 | 7,883 | 0.63 |
| Ruppar, Dunbar-Jacob, Mehr, Lewis, & Conn (2017) | Review interventions to improve MA to BP medications. (2015) | Broad | Black adults with hypertension | 37 | 5,228 | 0.59 |
| Conn, Ruppar, Chase, Enriquez, & Cooper (2015) | Review intervention aimed at increasing MA; examine average effect, whether effects depend sample, study, and intervention characteristics. (NR) | Broad | Participants with hypertension | 101 | 34,272 | 0.44 |
| Conn, Hafdahl, Cooper, Ruppar, Mehr, Russell (2009) | Evaluate effectiveness of interventions to improve MA and whether these relate to participants’ knowledge about their medications, management of medications, disease symptoms, health outcomes, systolic and diastolic blood pressure, health care services utilization, and quality of life; evaluate whether sample demographics, intervention components, and adherence measurement methodologies moderate the effect of interventions on MA. (NR) | Broad | Older adults with a physical health condition and at least one medical prescription | 38 | 11,827 | 0.41 |
| Conn & Ruppar (2017) | Evaluate effects of interventions on MA and see whether these vary depending on study design, sample, and intervention characteristics. (2015) | Broad | Not restricted to any population or diagnosis | 739 | 568,811 | 0.31 |
Note. BSE = barrier self-efficacy. CAD = Coronary Artery Disease. CBM= Cognitive bias modification. CHD = Coronary Heart Disease. CKD = Chronic Kidney Disease. COPD = Chronic Obstructive Pulmonary Disease. EXSE = exercise self-efficacy. ICT = Inhibitory Control Training. II = Implementation Intentions. MA = Medical adherence. MS = Multiple Sclerosis. NR = Not reported. RA = Rheumatoid Arthritis. RCT = Randomised Controlled Trial. SMS = Short message service. T2D = Type 2 Diabetes. PA = Physical activity.