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Part II - Methods and Processes of Behavior Change: Intervention Development, Application, and Translation

Published online by Cambridge University Press:  04 July 2020

Martin S. Hagger
Affiliation:
University of California, Merced
Linda D. Cameron
Affiliation:
University of California, Merced
Kyra Hamilton
Affiliation:
Griffith University
Nelli Hankonen
Affiliation:
University of Helsinki
Taru Lintunen
Affiliation:
University of Jyväskylä
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Publisher: Cambridge University Press
Print publication year: 2020

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References

Abraham, C., & Graham-Rowe, E. (2009). Are worksite interventions effective in increasing physical activity? A systematic review and meta-analysis. Health Psychology Review, 3, 108144. https://doi.org/10.1080/17437190903151096CrossRefGoogle Scholar
Alayli-Goebbels, A. F. G., Evers, S. M. A. A., Alexeeva, D. et al. (2014). A review of economic evaluations of behavior change interventions: Setting an agenda for research methods and practice. Journal of Public Health, 36, 336344. https://doi.org/10.1093/pubmed/fdt080CrossRefGoogle ScholarPubMed
Albarracín, D., Gillette, J. C., Earl, A. N., Glasman, L. R., Durantini, M. R., & Ho, M.-H. (2005). A test of major assumptions about behavior change: A comprehensive look at the effects of passive and active HIV-prevention interventions since the beginning of the epidemic. Psychological Bulletin, 131, 856897. https://doi.org/10.1037/0033-2909.131.6.856Google Scholar
Austin, J. T., & Vancouver, J. B. (1996). Goal constructs in psychology: Structure, process, and content. Psychological Review, 120, 338375. https://doi.org/10.1037//0033-2909.120.3.338Google Scholar
Bartholomew, L. K., Markham, C. M., Ruiter, R., Fernández, M. E., Kok, G., & Parcel, G. S. (2016). Planning Health Promotion Programmes: An Intervention Mapping Approach. San Francisco, CA: Jossey-Bass.Google Scholar
Barton, H., & Grant, M. (2006). A health map for the local human habitat. The Journal for the Royal Society for the Promotion of Health, 126, 252253. https://doi.org/10.1177/1466424006070466Google Scholar
Blackstock, K. L., Ingram, J., Burton, R., Brown, K. M., & Slee, B. (2010). Understanding and influencing behaviour change by farmers to improve water quality. Science of the Total Environment, 408, 56315638. https://doi.org/10.1016/j.scitotenv.2009.04.029CrossRefGoogle ScholarPubMed
Borek, A., Abraham, C., Greaves, C., & Tarrant, M. (2018). Group-based diet and physical activity weight-loss interventions: A systematic review and meta-analysis of randomised controlled trials. Applied Psychology: Health and Well-Being. 10, 6286. https://doi.org/10.1111/aphw.12121Google Scholar
Borland, R. (2014). Understanding Hard to Maintain Behaviour Change: A Dual Process Approach. Chichester: Wiley & Sons.Google Scholar
Bowen, D. J., Barrington, W. E., & Beresford, S. A. (2015). Identifying the effects of environmental and policy change interventions on healthy eating. Annual Review of Public Health, 36, 289306. https://doi.org/10.1146/annurev-publhealth-032013-182516Google Scholar
Capezuti, E., Zadeh, R. S., Pain, K., Basara, A., Jiang, N. Z., & Krieger, A. C. (2018). A systematic review of non-pharmacological interventions to improve night-time sleep among residents of long-term care settings. BMC Geriatrics, 18, 143. https://doi.org/10.1186/s12877-018-0794-3CrossRefGoogle Scholar
Carver, C. S., & Scheier, M. F. (1982). Control theory: A useful conceptual framework for personality-social, clinical and health psychology. Psychological Bulletin, 92, 111135. https://doi.org/10.1037//0033-2909.92.1.111Google Scholar
CDC (Centers for Disease Control and Prevention). (2017). Overweight and obesity. CDC. Website. www.cdc.gov/obesity/adult/causes.htmlGoogle Scholar
Colagiuri, S., Lee, C. M. Y., Colagiuri, R. et al. (2010). The cost of overweight and obesity in Australia. Australian Medical Journal, 192, 260264. https://doi.org/10.5694/j.1326-5377.2010.tb03503.xGoogle Scholar
Conner, M., Abraham, C., Prestwich, A. et al. (2016). Impact of goal priority and goal conflict on the intention-health behavior relationship: Tests on physical activity and other health behaviors. Health Psychology, 35, 10171026. https://doi.org/10.1037/hea0000340CrossRefGoogle ScholarPubMed
Dantas, L. F., Fleck, J. L., Cyrino Oliveira, F. L., & Hamacher, S. (2018). No-shows in appointment scheduling: A systematic literature review. Health Policy 122, 412421. https://doi.org/10.1016/j.healthpol.2018.02.002Google Scholar
Dean, J. (2013). Making Habits, Breaking Habits. Boston: De Capo Press.Google Scholar
Denford, S., Abraham, C., Campbell, R., & Brusse, H. (2016). A comprehensive review of reviews of school-based interventions to improve sexual-health. Health Psychology Review, 11, 3352. https://doi.org/10.1080/17437199.2016.1240625CrossRefGoogle ScholarPubMed
Evans, D. (2003). Hierarchy of evidence: A framework for ranking evidence evaluating healthcare interventions. Journal of Clinical Nursing, 12, 7784. doi/full/10.1046/j.1365-2702.2003.00662.xCrossRefGoogle ScholarPubMed
Fishbein, M., Triandis, H. C., Kanfer, F. H., Becker, M. H., Middlestadt, S. E., & Eichler, A. (2001). Factors influencing behavior and behavior change. In Baum, A., Revenson, T. R., & Singer, J. E. (Eds.), Handbook of Health Psychology (pp. 317). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Fisher, J. D., & Fisher, W. A. (1992). Changing AIDS-risk behavior. Psychological Bulletin, 111, 455471.Google Scholar
Fisher, J. D., Fisher, W. A., Bryan, A. D., & Misovich, S. J. (2002). Information-motivation-behavioral skills model-based HIV risk behavior change intervention for inner-city high school youth. Health Psychology, 21, 177186. https://doi.org/10.1037/0278-6133.21.2.177Google Scholar
Flay, B. (1986). Efficacy and effectiveness trials (and other phases of research) in the development of health promotion programs. Preventive Medicine, 15, 451474. https://doi.org/10.1016/0091-7435(86)90024-1Google Scholar
Gier, J. (2017). Missed appointments cost the U.S. healthcare system $150B each year. Healthcare Innovation, April 26. www.hcinnovationgroup.com/clinical-it/article/13008175/missed-appointments-cost-the-us-healthcare-system-150b-each-yearGoogle Scholar
Glanz, K., Sallis, J. F., Saelens, B. E., & Frank, L. D. (2005). Healthy nutrition environments: Concepts and measures. American Journal of Health Promotion, 19, 330333. https://doi.org/10.4278/0890-1171-19.5.330Google Scholar
Glasgow, R. E., Vogt, T. M., & Boles, S. M. (1999). Evaluating the public health impact of health promotion interventions: The RE-AIM framework. American Journal of Public Health, 89, 1322–7. https://doi.org/10.2105/ajph.89.9.1322Google Scholar
Gollwitzer, P. M., & Sheeran, P. (2006). Implementation intentions and goal achievement: A meta-analysis of effects and processes. Advances in Experimental Social Psychology, 38, 69121. doi.org/10.1016/S0065-2601(06)38002-1Google Scholar
Grimshaw, J. M., Thomas, R. E., MacLennan, G. et al. (2004). Effectiveness and efficiency of guideline dissemination and implementation strategies. Health Technology Assessment, 8, 6. https://doi.org/10.3310/hta8060CrossRefGoogle ScholarPubMed
Hagger, M. S., Moyers, S., McAnally, K., & McKinley, L. E., (2020). Known knowns and known unknowns on behavior change interventions and mechanisms of action. Health Psychology Review, 14, 199–212. https://doi.org/10.1080/17437199.2020.1719184Google Scholar
Hillier-Brown, F. C., Bambra, C. L., Cairns, J., Kasim, A., Moore, H. J., & Summerbell, C. D. (2014). A systematic review of the effectiveness of individual, community and societal level interventions at reducing socioeconomic inequalities in obesity amongst children. BMC Public Health 14, 834 https://doi.org/10.1186/1471-2458-14-834CrossRefGoogle ScholarPubMed
Hillier-Brown, F. C., Summerbell, C. D., Moore, H. J. et al. (2017). A description of interventions promoting healthier ready-to-eat meals (to eat in, to take away, or to be delivered) sold by specific food outlets in England: a systematic mapping and evidence synthesis. BMC Public Health, 17, 93. https://doi.org/10.1186/s12889-016-3980-2Google Scholar
House of Lords. (2011). Science and Technology Committee – Second Report: Behaviour Change (HL Paper No. 179). London: The Stationery Office. https://publications.parliament.uk/pa/ld201012/ldselect/ldsctech/179/17902.htmGoogle Scholar
Kaplan-Lewis, E., & Percac-Lima, S. (2013). No-show to primary care appointments: Why patients do not come. Journal of Primary Care and Community Health, 4, 251255. https://doi.org/10.1177/2150131913498513CrossRefGoogle Scholar
Kelly, M. P., & Barker, M. (2016). Why is changing health-related behaviour so difficult? Public Health, 136, 109116. https://doi.org/10.1016/j.puhe.2016.03.030Google Scholar
Kessler, D. A. (2009). The End of Overeating: Taking Control of the Insatiable American Appetite. New York: Macmillan.Google Scholar
Kurz, T., Gardner, B., Verplanken, B., & Abraham, C. (2014). Habitual behaviours or patterns of practice? Explaining and changing repetitive climate-relevant actions. Wiley Interdisciplinary Reviews: Climate Change, 6, 113128. https://doi.org/10.1002/wcc.327Google Scholar
Jepson, R. G., Harris, F. M., Platt, S., & Tannahill, C. (2010). The effectiveness of interventions to change six health behaviours: A review of reviews. BMC public Health, 10, 538.Google Scholar
Johnson, M. J., & May, C. R. (2015). Promoting professional behaviour change in healthcare: What interventions work, and why? A theory-led overview of systematic reviews. BMJ Open, 5, e008592. https://doi.org/10.1136/bmjopen-2015-008592CrossRefGoogle Scholar
Lake, A. J., Browne, J. L., Abraham, C. et al. (2018). A tailored intervention to promote uptake of retinal screening among young adults with type 2 diabetes: An intervention mapping approach. BMC Health Services Research. 18, 396. https://doi.org/10.1186/s12913-018-3188-5CrossRefGoogle ScholarPubMed
Lobstein, T., & Davies, S. (2008). Defining and labelling “healthy” and “unhealthy” food Public Health Nutrition: 12, 331340. https://doi.org/10.1017/S1368980008002541Google Scholar
Luszczynska, A., Sobczyk, A., & Abraham, C. (2007). Planning to lose weight: RCT of an implementation intention prompt to enhance weight reduction among overweight and obese women. Health Psychology, 26, 507512. https://doi.org/10.1037/0278-6133.26.4.507Google Scholar
McGuire, J. F., Piacentini, J., Brennan, E. A. et al. (2014). A meta-analysis of behavior therapy for Tourette Syndrome. Journal of Psychiatric Research, 50, 106112. https://doi.org/10.1016/j.jpsychires.2013.12.009Google Scholar
McLaughlin, J. A., & Jordan, G. B. (1999). Logic models a tool for telling your program’s performance story. Evaluation and Program Planning, 11, 6572. https://doi.org/10.1016/s0149-7189(98)00042-1Google Scholar
McQueenie, R., Ellis, D. A., McConnachie, A., Wilson, P., & Williamson, A. E. (2019). Morbidity, mortality and missed appointments in healthcare: A national retrospective data linkage study. BMC Medicine, 17, 2. https://doi.org/10.1186/s12916-018-1234-0Google Scholar
Milstein, B., Wetterhall, S., & CDC Evaluation Working Group. (2000). A framework featuring steps and standards for program evaluation. Health Promotion Practice, 1, 221228. https://doi.org/10.1177/152483990000100304Google Scholar
Molfenter, T. (2013). Reducing appointment no-shows: Going from theory to practice. Substance Use and Misuse, 48, 743749. https://doi.org/10.3109/10826084.2013.787098CrossRefGoogle ScholarPubMed
Moore, G., Audrey, S., Barker, M. et al. (2014). Process Evaluation of Complex Interventions: Medical Research Council Guidance. London: MRC Population Health Science Research Network. https://doi.org/10.1136/bmj.h1258Google Scholar
Municipal Association of Victoria. (2019). Shade Design for Public Places: Selecting Appropriate, Innovative and Cost Effective Shade Measures. Melbourne: Municipal Association of Victoria. www.mav.asn.au/__data/assets/pdf_file/0018/7326/Shade-design-for-public-places.pdfGoogle Scholar
National Highway Traffic Safety Administration. (2018). Summary of Motor Vehicle Crashes: 2006 Data. (Traffic Safety Facts. Report No. DOT HS 812 580). Washington, DC: National Highway Traffic Safety Administration. https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812580Google Scholar
National Institutes of Health. (2017). HIH Clinical research trials and you. National Institutes of Health. Website. www.nih.gov/health-information/nih-clinical-research-trials-you/basicsGoogle Scholar
Nielsen, K., Randall, R., Holten, A., & González, E. R. (2010). Conducting organizational-level occupational health interventions: What works? Work and Stress, 24, 234259. https://doi.org/10.1080/02678373.2010.515393CrossRefGoogle Scholar
O’Loughlin, J. L., Paradis, G., Gray-Donald, K., & Renaud, L. (1999). The impact of a community-based heart disease prevention program in a low-income, inner-city neighborhood. American Journal of Public Health, 89, 18191826. http://doi.org/10.2105/AJPH.89.12.1819Google Scholar
Pearson, M., Chilton, R., Wyatt, K., Abraham, C., Ford, T., & Anderson, R. (2015). Implementing health promotion programmes in schools: A realist systematic review of research and experience in the United Kingdom. Implementation Science, 10. https://doi.org/10.1186/s13012-015-0338-6Google Scholar
Peters, G.-J. Y., de Bruin, M., & Crutzen, R. (2015). Everything should be as simple as possible, but no simpler: Towards a protocol for accumulating evidence regarding the active content of health behaviour change interventions. Health Psychology Review, 9, 114. https://doi.org/10.1080/17437199.2013.848409CrossRefGoogle ScholarPubMed
Powers, W. T. (1973). Behavior: The Control of Perception. Chicago: Adline Publishing.Google Scholar
Rodda, S., Merkouris, S., Abraham, C., Hodgins, D. C., Cowlishaw, S., & Dowling, N. (2018). Therapist-delivered and self-help interventions for gambling problems: A review of contents. Journal of Behavioral Addictions, 7, 211226. https://doi.org/10.1556/2006.7.2018.44Google Scholar
Rogers, R. W. (1975). A protection motivation theory of fear appeals and attitude change. The Journal of Psychology, 91, 93114. https://doi.org/abs/10.1080/00223980.1975.9915803Google Scholar
Ruiter, R. A. C., Abraham, C., & Kok, G. (2001). Scary warnings and rational precautions: A review of the psychology of fear appeals. Psychology and Health, 16, 613630. https://doi.org/10.1080/08870440108405863Google Scholar
Sacerdote, C., Fiorini, L., Rosato, R., Audenino, M., Valpreda, M., & Vineis, P. (2005). Randomized controlled trial: Effect of nutritional counselling in general practice. International Journal of Epidemiology, 35, 409415. https://doi.org/10.1093/ije/dyi170Google Scholar
Sheeran, P., Abraham, C., Jones, K. et al. (2019). Promoting physical activity among cancer survivors: Meta-analysis and meta-CART analysis of randomized controlled trials. Health Psychology, 38, 467.CrossRefGoogle ScholarPubMed
Sheeran, P., Aubrey, R., & Kellett, S. (2007). Increasing attendance for psychotherapy: Implementation intentions and the self-regulation of attendance-related negative affect. Journal of Consulting and Clinical Psychology, 75, 853863. https://doi.org/10.1037/0022-006X.75.6.853Google Scholar
Sheeran, P., & Orbell, S. (2000). Using implementation intentions to increase attendance for cervical cancer screening. Health Psychology, 19, 283–289. https://doi.org/10.1037//0278-6133.19.3.283Google Scholar
Strack, F., & Deutsch, R. (2004). Reflective and impulsive determinants of social behavior. Personality and Social Psychology Review, 8, 220247. https://doi.org/10.1207/s15327957pspr0803_1Google Scholar
Suls, J., Mogavero, J. N., Falzon, L., Pescatello, L. S., Hennessy, E. A., & Davidson, K. W. (2020). Health behaviour change in cardiovascular disease prevention and management: Meta-review of behavior change techniques to affect self-regulation. Health Psychology Review, 14, 4365. https://doi.org/10.1080/17437199.2019.1691622Google Scholar
Thaler, R., & Sunstein, C. R. (2008). Nudge: Improving Decisions about Health, Wealth, and Happiness. New Haven, CT: Yale University Press.Google Scholar
van Beurden, S. B., Greaves, C. J., Smith, J. R., & Abraham, C. (2016). Techniques for modifying impulsive processes associated with unhealthy eating: A systematic review. Health Psychology, 35, 793806. https://doi.org/10.1037/hea0000337Google Scholar
VicHealth (2018). Healthy Food and Drink Choices in Community Sport: Building on Success. www.vichealth.vic.gov.au/media-and-resources/publications/healthy-choice-foodGoogle Scholar
Weinstein, N. D., Sandman, P. M., & Roberts, N. E. (1991). Perceived susceptibility and self-protective behavior: A field experiment to encourage home radon testing. Health Psychology, 10, 2533. https://doi.org/10.1037/0278-6133.10.1.25Google Scholar
WHO (World Health Organization). (2016). Consideration of the Evidence on Childhood Obesity for the Commission on Ending Childhood Obesity: Report of the Ad Hoc Working Group on Science and Evidence for Ending Childhood Obesity. Geneva: WHO.Google Scholar
Witte, K., & Allen, M. (2000). A meta-analysis of fear appeals: Implications for effective public health campaigns. Health Education and Behavior, 27, 591615. https://doi.org/10.1177/109019810002700506CrossRefGoogle ScholarPubMed
W. K. Kellogg Foundation. (2004). Using Logic Models to Bring Together Planning, Evaluation, and Action: Logic Model Development Guide. Michigan: W. K. Kellogg Foundation.Google Scholar
Wyatt, K., Lloyd, J., Creanor, S. et al. (2017). Cluster randomised controlled trial, economic and process evaluation to determine the effectiveness and cost effectiveness of a novel intervention (Healthy Lifestyles Programme, HeLP) to prevent obesity in school children. NIHR Public Health Research, 6, 1. www.ncbi.nlm.nih.gov/pubmed/29356471Google Scholar

References

Abraham, C., & Michie, S. (2008). A taxonomy of behavior change techniques used in interventions. Health Psychology, 27, 379387. https://doi.org/10.1037/0278-6133.27.3.379Google Scholar
Adams, M. L., Grandpre, J., Katz, D. L., & Shenson, D. (2019). The impact of key modifiable risk factors on chronic conditions. Preventive Medicine, 120, 113118. https://doi.org/10.1016/j.ypmed.2019.01.006Google Scholar
Bauer, U. E., Briss, P. A., Goodman, R. A., & Bowman, B. A. (2014). Prevention of chronic disease in the 21st century: Elimination of the leading preventable causes of premature death and disability in the USA. The Lancet, 284, 4552. https://doi.org/10.1016/S0140-6736(14)60648-6Google Scholar
Bernard, C. (1957). An Introduction to the Study of Experimental Medicine. New York: Dover Publications. (Originally published in 1865.)Google Scholar
Brewer, N. T., Chapman, G. B., Gibbons, F. X., Gerrard, M., McCaul, K. D., & Weinstein, N. D. (2007). Meta-analysis of the relationship between risk perception and health behavior: The example of vaccination. Health Psychology, 26, 136145. https://doi.org/10.1037/0278-6133.26.2.136Google Scholar
Brewer, N. T., Chapman, G. B., Rothman, A. J., Leask, J., & Kempe, A. (2017). Understanding and increasing vaccination behaviors: Putting psychology into action. Psychological Science in the Public Interest, 18, 149207. https://doi.org/10.1177/1529100618760521Google Scholar
Carey, R. N., Connell, L. E., Johnston, M. et al. (2019). Behaviour change techniques and mechanisms of action: A synthesis of links hypothesised in published intervention literature. Annals of Behavioral Medicine. https://doi.org/10.31234/osf.io/x5372Google Scholar
Carle, A. C., Riley, W., Hays, R. D., & Cella, D. (2015). Confirmatory factor analysis of the Patient Reported Outcomes Measurement Information System (PROMIS) adult domain framework using item response theory scores. Medical Care, 53, 894900. https://doi.org/10.1097/mlr.0000000000000413Google Scholar
CDC (Centers for Disease Control and Prevention). (1999). Ten great public health achievements: United States, 1900–1999. MMWR. Morbidity and Mortality Weekly Report, 48, 241243.Google Scholar
CDC (Centers for Disease Control and Prevention). (2019). Measles Cases and Outbreaks: Measles Cases in 2019. Atlanta, GA: US Department of Health and Human Services. www.cdc.gov/measles/cases-outbreaks.htmlGoogle Scholar
Collins, L. M. (2018). Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy (MOST). New York: Springer. https://doi.org/10.1007/978-3-319-72206-1_1Google Scholar
Connell, L. E, Carey, R. N., de Bruin, M. et al. (2019). Links between behaviour change techniques and mechanisms of action: An expert consensus study. Annals of Behavioral Medicine. https://doi.org/10.31234/osf.io/fge86Google Scholar
Czajkowski, S. M., Powell, L. H., Adler, N. et al. (2015). From ideas to efficacy: The ORBIT model for developing behavioral treatments for chronic diseases. Health Psychology, 34, 971982. https://doi.org/10.1037/hea0000161Google Scholar
Gardner, B. (2015). A review and analysis of the use of “habit” in understanding, predicting, and influencing health-related behaviour. Health Psychology Review, 9, 277295. https://doi.org/10.1080/17437199.2013.876238Google Scholar
Gifford, R., Kormos, C., & McIntyre, A. (2011). Behavioral dimensions of climate change: Drivers, responses, barriers, and interventions. WIREs Climate Change, 2, 801827. https://doi.org/10.1002/wcc.143CrossRefGoogle Scholar
Gillison, F. B., Rouse, P., Standage, M., Sebire, S. J., & Ryan, R. M. (2019). A meta-analysis of techniques to promote motivation for health behaviour change from a self-determination theory perspective. Health Psychology Review, 13, 110130. http://doi.org/10.1080/17437199.2018.1534071CrossRefGoogle ScholarPubMed
Hamilton, C. M., Strader, L. C., Pratt, J. G. et al. (2011). The PhenX Toolkit: Get the most from your measures. American Journal of Epidemiology, 174, 253260. https://doi.org/10.1093/aje/kwr193CrossRefGoogle ScholarPubMed
Jachimowicz, J. M., Duncan, S., Weber, E. U., & Johnson, E. J. (2019). When and why defaults influence decisions: A meta-analysis of default effects. Behavioural Public Policy, 3, 159186. https://doi.org/10.1017/bpp.2018.43Google Scholar
Johnston, M., Carey, R. N., Connell Bohlen, L. et al. (2019). Development of an online tool for linking behavior change techniques and mechanisms of action based on triangulation of findings from literature synthesis and expert consensus. PsyArXiv. https://doi.org/10.31234/osf.io/ur6kzGoogle Scholar
Knittle, K., Nurmi, J., Crutzen, R., Hankonen, N., Beattie, M., & Dombrowski, S. U. (2018). How can interventions increase motivation for physical activity? A systematic review and meta-analysis. Health Psychology Review, 12, 211230. https://doi.org/10.1080/17437199.2018.1435299CrossRefGoogle ScholarPubMed
Kok, G., Gottlieb, N. H., Peters, G.-J. Y. et al. (2016). A taxonomy of behaviour change methods: An intervention mapping approach. Health Psychology Review, 10, 297312, https://doi.org/10.1080/17437199.2015.1077155CrossRefGoogle ScholarPubMed
Kwasnicka, D., Dombrowski, S. U., White, M., & Sniehotta, F. (2016). Theoretical explanations for maintenance of behavior change: A systematic review of behavior theories. Health Psychology Review, 10, 277296. https://doi.org/10.1080/17437199.2016.1151372CrossRefGoogle Scholar
MacKinnon, D. P. (2008). Introduction to Statistical Mediation Analysis. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
MacLean, P. S., Rothman, A. J., Nicastro, H. L. et al. (2018). The accumulating data to optimally predict obesity treatment (ADOPT) core measures project: Rationale and approach. Obesity, 26, S6S15. https://doi.org/10.1002/oby.22154Google Scholar
McEachan, R. R., Conner, M., Taylor, N. J., & Lawton, R. J. (2011). Prospective prediction of health-related behaviours with the theory of planned behaviour: A meta-analysis. Health Psychology Review, 5, 97144. https://doi.org/10.1080/17437199.2010.521684Google Scholar
Meehl, P. E. (1978). Theoretical risks and tabular asterisks: Sir Karl, Sir Ronald, and the slow progress of soft psychology. Journal of Consulting and Clinical Psychology, 46, 806834. https://doi.org/10.1037//0022-006x.46.4.806Google Scholar
Michie, S., Carey, R. N., Johnston, M. et al. (2018). From theory-inspired to theory-based interventions: A protocol for developing and testing a methodology for linking behaviour change techniques to theoretical mechanisms of action. Annals of Behavioral Medicine, 52, 501512. https://doi.org/10.1007/s12160-016-9816-6Google Scholar
Michie, S., Richardson., M., Johnston, M. et al. (2013). The Behavior Change Technique Taxonomy (v1) of 93 hierarchically clustered techniques: Building an international consensus for the reporting of behavior change interventions. Annals of Behavioral Medicine, 46, 8195. https://doi.org/10.1007/s12160-013-9486-6Google Scholar
Moher, D., Schultz, K. F., Altman, D. G., & the CONSORT Group. (2001). The CONSORT statement: Revised recommendations for improving the quality of reports of parallel-group randomized trials. Lancet, 357, 11911194. https://doi.org/10.1016/s0140-6736(00)04337-3Google Scholar
Munafò, M. R., Nosek, B. A., Bishop, D. V. M. et al. (2017). A manifesto for reproducible science. Nature Human Behavior, 1 (21). https://doi.org/10.1038/s41562-016-0021Google Scholar
Nielsen, L., Riddle, M., King, J. W., & the NIH Science of Behavior Change Implementation Team. (2018). The NIH science of behavior change program: Transforming the science through a focus on mechanisms of change. Behaviour Research and Therapy, 101, 311. https://doi.org/10.1016/j.brat.2017.07.002CrossRefGoogle ScholarPubMed
Nosek, B. A., Ebersole, C. R., DeHaven, A. C., & Mellor, D. T. (2018). The preregistration revolution. Proceedings of the National Academy of Sciences, 115, 26002606. https://doi.org/10.1073/pnas.1708274114Google Scholar
Patel, M., Lee, A. D., Redd, S. B. et al. (2019). Increase in measles cases – United States, January 1–April 26, 2019. MMWR. Morbidity and Mortality Weekly Report, 68, 402404. http://dx.doi.org/10.15585/mmwr.mm6817e1Google Scholar
Rothman, A. J., Baldwin, A. S., Hertel, A. W., & Fuglestad, P. (2011). Self-regulation and behavior change: Disentangling behavioral initiation and behavioral maintenance. In Vohs, K. D. & Baumeister, R. F. (Eds.), Handbook of Self-Regulation: Research, Theory, and Applications (2nd ed., pp. 106122). New York: Guilford Press.Google Scholar
Sheeran, P., Avishai, A., Jones, K., Villegas, M., Wright, C. E., & Brewer, N. T. (2019). Health behavior tasks: Conceptualizing actions to promote health and prevent disease. Unpublished manuscript, University of North Carolina at Chapel Hill.Google Scholar
Sheeran, P., Harris, P. R., & Epton, T. (2014). Does heightening risk appraisals change people’s intentions and behavior? A meta-analysis of experimental studies. Psychological Bulletin, 140, 511543. https://doi.org/10.1037/a0033065Google Scholar
Sheeran, P. S., Klein, W. M. P., & Rothman, A. J. (2017). Health behavior change: Moving from observation to intervention. Annual Review of Psychology, 68, 573600. https://doi.org/10.1146/annurev-psych-010416-044007Google Scholar
Sheeran, P., Maki, A., Montanaro, E. et al. (2016). The impact of changing attitudes, norms, and self-efficacy on health-related intentions and behavior: A meta-analysis. Health Psychology, 35, 11781188. https://doi.org/10.1037/hea0000387Google Scholar
Spencer, S. J., Zanna, M. P., & Fong, G. T. (2005). Establishing a causal chain: Why experiments are often more effective than mediational analyses in examining psychological processes. Journal of Personality and Social Psychology, 89, 845851. http://doi.org/10.1037/0022-3514.89.6.845Google Scholar
Swim, J. K., Clayton, S., & Howard, G. S. (2011). Human behavioral contributions to climate change. American Psychologist, 66, 251264. https://doi.org/10.1037/a0023472Google Scholar
Tannenbaum, M. B., Hepler, J., Zimmerman, R. S. et al. (2015). Appealing to fear: A meta-analysis of fear appeal effectiveness and theories. Psychological Bulletin, 141, 11781204. http://dx.doi.org/10.1037/a0039729Google Scholar
Webb, T. L., & Sheeran, P. (2006). Does changing behavioral intentions engender behavior change? A meta-analysis of the experimental evidence. Psychological Bulletin, 132, 249268. https://doi.org/10.1037/0033-2909.132.2.249Google Scholar
Weinstein, N. D. (2007). Misleading tests of health behavior theories. Annals of Behavioral Medicine, 33, 110.Google Scholar

References

Araújo-Soares, V., Hankonen, N., Presseau, J., Rodrigues, A., & Sniehotta, F. F. (2018). Developing behavior change interventions for self-management in chronic illness: An integrative overview. European Psychologist, 24, 725. https://doi.org/10.1027/1016-9040/a000330Google Scholar
Bartholomew Eldredge, L. K., Markham, C. M., Ruiter, R. A. C., Fernández, M. E., Kok, G., & Parcel, G. S. (2016). Planning Health Promotion Programs: An Intervention Mapping Approach. Hoboken, NJ: John Wiley & Sons.Google Scholar
Bonell, C., Jamal, F., Melendez-Torres, G. J., & Cummins, S. (2015). “Dark logic”: Theorising the harmful consequences of public health interventions. Journal of Epidemiology and Community Health, 69, 9598. https://doi.org/10.1136/jech-2014-204671Google Scholar
Collins, L. M., Murphy, S. A., & Strecher, V. (2007). The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): New methods for more potent eHealth interventions. American Journal of Preventive Medicine, 32, S112S118. https://doi.org/10.1016/j.amepre.2007.01.022Google Scholar
Cook, P. A., Hargreaves, S. C., Burns, E. J. et al. (2018). Communities in charge of alcohol (CICA): A protocol for a stepped-wedge randomised control trial of an alcohol health champions programme. BMC Public Health, 18, 522. https://doi.org/10.1186/s12889-018-5410-0Google Scholar
Craig, P., Dieppe, P., Macintyre, S., Michie, S., Nazareth, I., & Petticrew, M. (2008). Developing and evaluating complex interventions: The new Medical Research Council guidance. BMJ, 337, a1655. https://doi.org/10.1136/bmj.a1655Google Scholar
Davidoff, F., Dixon-Woods, M., Leviton, L., & Michie, S. (2015). Demystifying theory and its use in improvement. BMJ Quality and Safety, 24, 228238. https://doi.org/10.1136/bmjqs-2014-003627Google Scholar
Dombrowski, S. U., Sniehotta, F. F., Avenell, A., Johnston, M., MacLennan, G., & Araújo-Soares, V. (2012). Identifying active ingredients in complex behavioural interventions for obese adults with obesity-related co-morbidities or additional risk factors for co-morbidities: A systematic review. Health Psychology Review, 6, 732. https://doi.org/10.1080/17437199.2010.513298Google Scholar
Evans, R., Brockman, R., Grey, J. et al. (2018). A cluster randomised controlled trial of the Wellbeing in Secondary Education (WISE) Project: An intervention to improve the mental health support and training available to secondary school teachers: protocol for an integrated process evaluation. Trials, 19, 270. https://doi.org/10.1186/s13063-018-2617-4Google Scholar
Gomersall, T. (2018). Complex adaptive systems: A new approach for understanding health practices. Health Psychology Review, 12, 405418. https://doi.org/10.1080/17437199.2018.1488603CrossRefGoogle ScholarPubMed
Hankonen, N., Heino, M. T. J., Araújo-Soares, V. et al. (2016). “Let’s Move It”: A school-based multilevel intervention to increase physical activity and reduce sedentary behaviour among older adolescents in vocational secondary schools: A study protocol for a cluster-randomised trial. BMC Public Health, 16, 451. https://doi.org/10.1186/s12889-016-3094-xGoogle Scholar
Hawe, P. (2015). Lessons from complex interventions to improve health. Annual Review of Public Health, 36, 307323. https://doi.org/10.1146/annurev-publhealth-031912-114421Google Scholar
Heino, M. T. J., Noonan, C., Knittle, K., & Hankonen, N. (2019). Studying behaviour change mechanisms under complexity. Unpublished manuscript, University of Helsinki.Google Scholar
Hoffmann, T. C., Glasziou, P. P., Boutron, I. et al. (2014). Better reporting of interventions: Template for intervention description and replication (TIDieR) checklist and guide. BMJ, 348, g1687. https://doi.org/10.1136/bmj.g1687Google Scholar
Kwasnicka, D., Dombrowski, S. U., White, M., & Sniehotta, F. F. (2015). Data-prompted interviews: Using individual ecological data to stimulate narratives and explore meanings. Health Psychology, 34, 11911194. https://doi.org/10.1037/hea0000234CrossRefGoogle ScholarPubMed
Leykum, L. K., Pugh, J., Lawrence, V. et al. (2007). Organizational interventions employing principles of complexity science have improved outcomes for patients with Type II diabetes. Implementation Science, 2, 28. https://doi.org/10.1186/1748-5908-2-28Google Scholar
Michie, S., Atkins, L., & West, R. (2014). The Behaviour Change Wheel: A Guide to Designing Interventions. London: Silverback Publishing.Google Scholar
Michie, S., van Stralen, M. M., & West, R. (2011). The behaviour change wheel: A new method for characterising and designing behaviour change interventions. Implementation Science, 6, 42. https://doi.org/10.1186/1748-5908-6-42Google Scholar
Morgan, H., Hoddinott, P., Thomson, G. et al. (2015). Benefits of Incentives for Breastfeeding and Smoking Cessation in Pregnancy (BIBS): A Mixed-Methods Study to Inform Trial Design. Southampton: NIHR Journals Library.Google Scholar
O’Cathain, A., Croot, L., Sworn, K. et al. (2019). Taxonomy of approaches to developing interventions to improve health: A systematic methods overview. Pilot and Feasibility Studies, 5. https://doi.org/10.1186/s40814-019-0425-6Google Scholar
Pawson, R. (2006). Evidence-Based Policy: A Realist Perspective. London: SAGE.Google Scholar
Pears, S., Morton, K., Bijker, M., Sutton, S., Hardeman, W., & VBI Programme Team. (2015). Development and feasibility study of very brief interventions for physical activity in primary care. BMC Public Health, 15, 333. https://doi.org/10.1186/s12889-015-1703-8Google Scholar
Perski, O., Blandford, A., West, R., & Michie, S. (2017). Conceptualising engagement with digital behaviour change interventions: A systematic review using principles from critical interpretive synthesis. Translational Behavioral Medicine, 7, 254267. https://doi.org/10.1007/s13142-016-0453-1Google Scholar
Resnicow, K., & Page, S. E. (2008). Embracing chaos and complexity: A quantum change for public health. American Journal of Public Health, 98, 13821389. https://doi.org/10.2105/AJPH.2007.129460Google Scholar
Sekhon, M., Cartwright, M., & Francis, J. (2017). Acceptability of healthcare interventions: An overview of reviews and development of a theoretical framework. BMC Health Services Research, 17, 88. https://doi.org/10.1186/s12913-017-2031-8Google Scholar
Skivington, K., Matthews, L., Craig, P., Simpson, S., & Moore, L. (2018). Developing and evaluating complex interventions: Updating Medical Research Council guidance to take account of new methodological and theoretical approaches. The Lancet, 392, S2. Meeting abstract: Public Health Science 2018, Belfast, Northern Ireland, November 23, 2018. http://dx.doi.org/10.1016/s0140-6736(18)32865-4Google Scholar
Toomey, E., Hardeman, W., Hankonen, N. et al. (2019). Focusing on fidelity: Recommendations for improving intervention fidelity within trials of health behavioral interventions. Unpublished manuscript, National University of Ireland, Galway.Google Scholar
Tully, M. A., Cunningham, C., Wright, A. et al. (2019). Peer-led walking programme to increase physical activity in inactive 60-to 70-year-olds: Walk with Me pilot RCT. Public Health Research, 7. https://doi.org/10.3310/phr07100Google Scholar
University of Wisconsin. (2008). Developing a logic model: Teaching and training guide. Program Development and Evaluation. Website. https://fyi.extension.wisc.edu/programdevelopment/logic-models/Google Scholar
University of Wisconsin-Extension. (2003). Enhancing program performance with logic models. Program Development and Evaluation. Website. https://fyi.extension.wisc.edu/programdevelopment/designing-programs/Google Scholar
W. K. Kellogg Foundation. (2004). Using Logic Models to Bring Together Planning, Evaluation, and Action: Logic Model Development Guide. Michigan: W. K. Kellogg Foundation.Google Scholar

References

Barnighausen, T., Tugwell, P., Rottingen, J. A. et al. (2017). Quasi-experimental study designs series-paper 4: Uses and value. Journal of Clinical Epidemiology, 89, 2129. https://doi.org/10.1016/j.jclinepi.2017.03.012Google Scholar
Basu, S., Meghani, A., & Siddiqi, A. (2017). Evaluating the health impact of large-scale public policy changes: Classical and novel approaches. Annual Review of Public Health, 38, 351370. https://doi.org/10.1146/annurev-publhealth-031816-044208CrossRefGoogle ScholarPubMed
Bernal, J. L., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: A tutorial. International Journal of Epidemiology, 46, 348355. https://doi.org/10.1093/ije/dyw098Google Scholar
Bonell, C., Allen, E., Warren, E. et al. (2018). Effects of the Learning Together intervention on bullying and aggression in English secondary schools (INCLUSIVE): A cluster randomised controlled trial. The Lancet, 392(10163), 24522464. https://doi.org/10.1016/S0140-6736(18)31782-3Google Scholar
Bonell, C., Fletcher, A., Morton, M., Lorenc, T., & Moore, L. (2012). Realist randomised controlled trials: A new approach to evaluating complex public health interventions. Social Science and Medicine, 75, 22992306. https://doi.org/10.1016/j.socscimed.2012.08.032Google Scholar
Bonell, C., Jamal, F., Melendez-Torres, G. J., & Cummins, S. (2015). “Dark logic”: Theorising the harmful consequences of public health interventions. Journal of Epidemiology and Community Health, 69, 9598. https://doi.org/10.1136/jech-2014-204671Google Scholar
Chapman, L., Sadeghzadeh, C., Koutlas, M., Zimmer, C., & Marco, M. D. (2019). Evaluation of three behavioral economics “nudges” on grocery and convenience store sales of promoted nutritious foods (OR16-05–19). Public Health Nutrition, 22, 32503260. https://doi.org/10.1017/S136898001900179Google Scholar
Collins, L. M., Dziak, J. J., & Li, R. (2009). Design of experiments with multiple independent variables: A resource management perspective on complete and reduced factorial designs. Psychological Methods, 14, 202224. https://doi.org/10.1037/a0015826Google Scholar
Cook, J. A., Julious, S. A., Sones, W. et al. (2018). DELTA2 guidance on choosing the target difference and undertaking and reporting the sample size calculation for a randomised controlled trial. British Medical Journal, 363. https://doi.org/10.1136/bmj.k3750Google Scholar
Craig, P., Cooper, C., Gunnell, D. et al. (2012). Using natural experiments to evaluate population health interventions: New Medical Research Council guidance. Journal of Epidemiology and Community Health, 66, 11821186. https://doi.org/10.1136/jech-2011-200375Google Scholar
Craig, P., Di Ruggiero, E., Frolich, K. L., Mykhalovskiy, E., White, M., & the Canadian Institutes of Health Research (CIHR)–National Institute for Health Research (NIHR) Context Guidance Authors Group. (2018). Taking Account of Context in Population Health Intervention Research: Guidance for Producers, Users and Funders of Research. Southampton: NIHR Journals Library.Google Scholar
Craig, P., Katikireddi, S. V., Leyland, A., & Popham, F. (2017). Natural experiments: An overview of methods, approaches, and contributions to public health intervention research. Annual Review of Public Health, 38, 3956. https://doi.org/10.1146/annurev-publhealth-031816-044327Google Scholar
Davidson, K. W., Peacock, J., Kronish, I. M., & Edmondson, D. (2014). Personalizing behavioral interventions through single-patient (n-of-1) trials. Social and Personality Psychology Compass, 8, 408421. https://doi.org/10.1111/spc3.12121Google Scholar
Deaton, A., & Cartwright, N. (2018). Understanding and misunderstanding randomized controlled trials. Social Science and Medicine, 210, 221. https://doi.org/10.1016/j.socscimed.2017.12.005Google Scholar
Desveaux, L., & Shaw, J. (2018). A mobile app to improve self-management of individuals with type 2 diabetes: Qualitative realist evaluation. Journal of Medical Internet Research, 20, e81. https://doi.org/10.2196/jmir.8712Google Scholar
Egan, M., McGill, E., Anderson de Cuevas, R. et al. (2019). NIHR SPHR Guidance on Systems Approaches to Local Public Health Evaluation. Part 1: Introducing Systems Thinking. London: National Institute for Health Research.Google Scholar
Egan, M., McGill, E., Penney, T. et al. (2019). NIHR SPHR Guidance on Systems Approaches to Local Public Health Evaluation. Part 2: What to Consider When Planning a Systems Evaluation. London: National Institute for Health Research.Google Scholar
Fairhurst, K., & Dowrick, C. (1996). Problems with recruitment in a randomized controlled trial of counselling in general practice: Causes and implications. Journal of Health Services Research and Policy, 1, 7780. https://doi.org/10.1177/135581969600100205Google Scholar
Fichera, E., Gray, E., & Sutton, M. (2016). How do individuals’ health behaviours respond to an increase in the supply of health care? Evidence from a natural experiment. Social Science and Medicine, 159, 170179. https://doi.org/10.1016/j.socscimed.2016.05.005Google Scholar
Fok, C. C., Henry, D., & Allen, J. (2015). Research designs for intervention research with small samples II: Stepped wedge and interrupted time-series designs. Prevention Science, 16, 967977. https://doi.org/10.1007/s11121-015-0569-4Google Scholar
Forbes, L. J., Marchand, C., Doran, T., & Peckham, S. (2017). The role of the Quality and Outcomes Framework in the care of long-term conditions: A systematic review. British Journal of General Practice, 67, e775e784. https://doi.org/10.3399/bjgp17X693077Google Scholar
Glasgow, R. E., Harden, S. M., Gaglio, B. et al. (2019). RE-AIM planning and evaluation framework: Adapting to new science and practice with a 20-year review. Frontiers in Public Health, 7, 64. https://doi.org/10.3389/fpubh.2019.00064Google Scholar
Hahn, S., Puffer, S., Torgerson, D. J., & Watson, J. (2005). Methodological bias in cluster randomised trials. BMC Medical Research Methodology, 5, 10. https://doi.org/10.1186/1471-2288-5-10Google Scholar
Hallingberg, B., Turley, R., Segrott, J. et al. (2018). Exploratory studies to decide whether and how to proceed with full-scale evaluations of public health interventions: A systematic review of guidance. Pilot Feasibility Studies, 4, 104. https://doi.org/10.1186/s40814-018-0290-8Google Scholar
Hemming, K., Eldridge, S., Forbes, G., Weijer, C., & Taljaard, M. (2017). How to design efficient cluster randomised trials. British Medical Journal, 358, j3064. https://doi.org/10.1136/bmj.j3064Google Scholar
Hemming, K., Haines, T. P., Chilton, P. J., Girling, A. J., & Lilford, R. J. (2015). The stepped wedge cluster randomised trial: Rationale, design, analysis, and reporting. British Medical Journal, 350, h391. https://doi.org/10.1136/bmj.h391Google Scholar
Hutchings, J., Bywater, T., Daley, D. et al. (2007). Parenting intervention in Sure Start services for children at risk of developing conduct disorder: Pragmatic randomised controlled trial. British Medical Journal, 334(7595), 678. https://doi.org/10.1136/bmj.39126.620799.55Google Scholar
Kairalla, J. A., Coffey, C. S., Thomann, M. A., & Muller, K. E. (2012). Adaptive trial designs: A review of barriers and opportunities. Trials, 13, 145. https://doi.org/10.1186/1745-6215-13-145CrossRefGoogle ScholarPubMed
Kelly, P. J., Baker, A. L., Deane, F. P. et al. (2015). Study protocol: A stepped wedge cluster randomised controlled trial of a healthy lifestyle intervention for people attending residential substance abuse treatment. BMC Public Health, 15, 465. https://doi.org/10.1186/s12889-015-1729-yGoogle Scholar
Kontopantelis, E., Doran, T., Springate, D. A., Buchan, I., & Reeves, D. (2015). Regression based quasi-experimental approach when randomisation is not an option: Interrupted time series analysis. British Medical Journal, 350, h2750. https://doi.org/10.1136/bmj.h2750Google Scholar
Kraska, M. (2010). Repeated measures design. In Salkind, N. J. (Ed.), Encyclopedia of Research Design. Thousand Oaks, CA: SAGE.Google Scholar
Kwasnicka, D., Inauen, J., Nieuwenboom, W. et al. (2019). Challenges and solutions for N-of-1 design studies in health psychology. Health Psychology Review, 13, 163178. https://doi.org/10.1080/17437199.2018.1564627Google Scholar
Leviton, L. C., & Melichar, L. (2016). Balancing stakeholder needs in the evaluation of healthcare quality improvement. BMJ Quality and Safety, 25, 803807. https://doi.org/10.1136/bmjqs-2015-004814Google Scholar
MacMillan, F., George, E. S., Feng, X. et al. (2018). Do natural experiments of changes in neighborhood built environment impact physical activity and diet? A systematic review. International Journal of Environmental Research and Public Health, 15, 217. https://doi.org/10.3390/ijerph15020217Google Scholar
Matthews, L., Pugmire, J., Moore, L. et al. (2017). Study protocol for the “HelpMeDoIt!” randomised controlled feasibility trial: An app, web and social support-based weight loss intervention for adults with obesity. BMJ Open, 7, e017159. https://doi.org/10.1136/bmjopen-2017-017159Google Scholar
McDonald, S., Quinn, F., Vieira, R. et al. (2017). The state of the art and future opportunities for using longitudinal n-of-1 methods in health behaviour research: A systematic literature overview. Health Psychology Review, 11, 307323. https://doi.org/10.1080/17437199.2017.1316672Google Scholar
Moore, G. F., Audrey, S., Barker, M. et al. (2015). Process evaluation of complex interventions: Medical Research Council guidance. British Medical Journal, 350(h1258), h1258. https://doi.org/10.1136/bmj.h1258Google Scholar
Moore, L., Hallingberg, B., Wight, D. et al. (2018). Exploratory studies to inform full-scale evaluations of complex public health interventions: The need for guidance. Journal of Epidemiology and Community Health, 72, 865866. https://doi.org/10.1136/jech-2017-210414Google Scholar
Murad, M. H., Asi, N., Alsawas, M., & Alahdab, F. (2016). New evidence pyramid. BMJ Evidence-Based Medicine, 21, 125127. https://doi.org/10.1136/ebmed-2016-110401Google Scholar
O’Cathain, A., Croot, L., Duncan, E. et al. (2019). Guidance on how to develop complex interventions to improve health and healthcare. BMJ Open, 9, e029954. https://doi.org/10.1136/bmjopen-2019-029954Google Scholar
O’Cathain, A., Murphy, E., & Nicholl, J. (2010). Three techniques for integrating data in mixed methods studies. British Medical Journal, 341, c4587. https://doi.org/10.1136/bmj.c4587Google Scholar
O’Keeffe, A. G., Geneletti, S., Baio, G., Sharples, L. D., Nazareth, I., & Petersen, I. (2014). Regression discontinuity designs: An approach to the evaluation of treatment efficacy in primary care using observational data. British Medical Journal, 349, g5293. https://doi.org/10.1136/bmj.g5293Google Scholar
Paulhus, D. L. (1984). Two-component models of socially desirable responding. Journal of Personality and Social Psychology, 46, 598. https://doi.org/10.1037/0022-3514.46.3.598Google Scholar
Prins, R. G., Panter, J., Heinen, E., Griffin, S. J., & Ogilvie, D. B. (2016). Causal pathways linking environmental change with health behaviour change: Natural experimental study of new transport infrastructure and cycling to work. Preventive Medicine, 87, 175182. https://doi.org/10.1016/j.ypmed.2016.02.042Google Scholar
Public Health England. (2018). Evaluation in Health and Wellbeing. London: Public Health England.Google Scholar
Salkind, N. J. (2010). Encyclopedia of Research Design. Thousand Oaks, CA: SAGE.Google Scholar
Sanson-Fisher, R. W., D’Este, C. A., Carey, M. L., Noble, N., & Paul, C. L. (2014). Evaluation of systems-oriented public health interventions: Alternative research designs. Annual Review of Public Health, 35, 927. https://doi.org/10.1146/annurev-publhealth-032013-182445Google Scholar
Schueller, S. M., Leykin, Y., Pérez-Stable, E. J., & Muñoz, R. F. (2013). Selection of intervention components in an internet stop smoking participant preference trial: Beyond randomized controlled trials. Psychiatry Research, 205, 159164. https://doi.org/10.1016/j.psychres.2012.08.030Google Scholar
Simpson, S. A., Matthews, L., Pugmire, J. et al. (2019). An app, web and social support based weight loss intervention for adults with obesity: The “HelpMeDoIt!” feasibility RCT. Public Health Research.Google Scholar
Skivington, K., Matthews, L., Craig, P., Simpson, S., & Moore, L. (2018). Developing and evaluating complex interventions: Updating Medical Research Council guidance to take account of new methodological and theoretical approaches. The Lancet, 392, S2. Meeting abstract: Public Health Science 2018, Belfast, Northern Ireland, November 23, 2018. http://dx.doi.org/10.1016/s0140-6736(18)32865-4Google Scholar
Torgerson, C., & Torgerson, D. J. (2008). Designing Randomised Trials in Health, Education and the Social Sciences: An Introduction. London: Palgrave Macmillan.Google Scholar
Torgerson, D. J., & Sibbald, B. (1998). Understanding controlled trials: What is a patient preference trial? British Medical Journal, 316, 360. https://doi.org/10.1136/bmj.316.7128.360Google Scholar
Walton, H., Spector, A., Tombor, I., & Michie, S. (2017). Measures of fidelity of delivery of, and engagement with, complex, face-to-face health behaviour change interventions: A systematic review of measure quality. British Journal of Health Psychology, 22, 872903. https://doi.org/10.1111/bjhp.12260Google Scholar
Yang, Y., & Diez-Roux, A. V. (2013). Using an agent-based model to simulate children’s active travel to school. International Journal of Behavioral Nutrition and Physical Activity, 10, 67. https://doi.org/10.1186/1479-5868-10-67Google Scholar
Yoon, S., Schwartz, J. E., Burg, M. M. et al. (2018). Using behavioral analytics to increase exercise: A randomized n-of-1 study. American Journal of Preventive Medicine, 54, 559567.Google Scholar

References

Abraham, C., Johnson, B. T., de Bruin, M., & Luszczynska, A. (2014). Enhancing reporting of behavior change intervention evaluations. Journal of Acquired Immune Deficiency Syndromes, 66, S293S299. https://doi.org/10.1097/QAI.0000000000000231Google Scholar
Bartholomew Eldredge, L. K., Markham, C. M., Ruiter, R. A. C., Fernández, M. E., Kok, G., & Parcel, G. S. (2016). Planning Health Promotion Programs: An Intervention Mapping Approach (4th ed.). San Francisco: Jossey-Bass.Google Scholar
Bauer, M. S., Damschroder, L., Hagedorn, H., Smith, J., & Kilbourne, A. M. (2015). An introduction to implementation science for the non-specialist. BMC Psychology, 3, 32. https://doi.org/10.1186/s40359-015-0089-9Google Scholar
Birken, S. A., Powell, B. J., Shea, C. M. et al. (2017). Criteria for selecting implementation science theories and frameworks: Results from an international survey. Implementation Science, 12, 124. https://doi.org/10.1186/s13012-017-0656-yGoogle Scholar
Cane, J., O’Connor, D., & Michie, S. (2012). Validation of the theoretical domains framework for use in behaviour change and implementation. Implementation Science, 7, 37. https://doi.org/10.1186/1748-5908-7-37Google Scholar
Damschroder, L. J., Aron, D. C., Keith, R. E. et al. (2009). Fostering implementation of health services research findings into practice: A consolidated framework for advancing implementation science. Implementation Science, 4, 50. https://doi.org/10.1186/1748-5908-4-50Google Scholar
Drolet, B. C., & Lorenzi, N. M. (2011). Translational research: Understanding the continuum from bench to bedside. Translational Research, 157, 15. https://doi.org/10.1016/j.trsl.2010.10.002Google Scholar
Eccles, M. P., & Mittman, B. S. (2006). Welcome to implementation science. Implementation Science, 1, 1. https://doi.org/10.1186/1748-5908-1-1Google Scholar
Glasgow, R. E., Klesges, L. M., Dzewaltowski, D. A., Bull, S. S., & Estabrooks, P. (2004). The future of health behavior change research: What is needed to improve translation of research into health promotion practice? Annals of Behavioral Medicine, 27, 312. https://doi.org/10.1207/s15324796abm2701_2Google Scholar
Glasgow, R. E., Vogt, T. M., & Boles, S. M. (1999). Evaluating the public health impact of health promotion interventions: The RE-AIM framework. American Journal of Public Health, 89, 1322–1237.Google Scholar
Graham, I. D., & Logan, J. (2004). Innovations in knowledge transfer and continuity of care. Canadian Journal of Nursing Research, 36, 89103.Google Scholar
Greenhalgh, T., Robert, G., Bate, P., Macfarlane, F., Bate, P., & Kyriakidou, O. (2005). Diffusion of innovations in service organisations: Systematic review and recommendations. Milbank Quarterly, 82, 581629. https://doi.org/10.1111/j.0887-378X.2004.00325.xGoogle Scholar
Hagger, M. S., & Weed, M. E. (2019). DEBATE: Do behavioral interventions work in the real world? International Journal of Behavioral Nutrition and Physical Activity, 16, 36. http://dx.doi.org/10.1186/s12966-019-0795-4Google Scholar
Horodyska, K., Luszczynska, A., Hayes, C. B. et al. (2015). Implementation conditions for diet and physical activity interventions and policies: An umbrella review. BMC Public Health, 15, 1250. https://doi.org/10.1186/s12889-015-2585-5Google Scholar
Horodyska, K., Luszczynska, A., van den Berg, M. et al. (2015). Good practice characteristics of diet and physical activity interventions and policies: An umbrella review. BMC Public Health, 15, 19. https://doi.org/10.1186/s12889-015-1354-9Google Scholar
Leeman, J., Birken, S. A., Powell, B. J., Rohweder, C., & Shea, C. M. (2017). Beyond “implementation strategies”: Classifying the full range of strategies used in implementation science and practice. Implementation Science, 12, 125. https://doi.org/10.1186/s13012-017-0657-xGoogle Scholar
Lewis, C. C., Fischer, S., Weiner, B. J., Stanick, C., Kim, M., & Martinez, R. G. (2015). Outcomes for implementation science: An enhanced systematic review of instruments using evidence-based rating criteria. Implementation Science, 10, 155. https://doi.org/10.1186/s13012-015-0342-xGoogle Scholar
Logan, J., & Graham, I. D. (2010). The Ottawa model of research use. In Bucknall, J. R. M. (Ed.), Models and Frameworks for Implementing Evidence-Based Practice: Evidence to Action (pp. 83108). Oxford: Wiley-Blackwell.Google Scholar
Luebbers, E. L., Dolansky, M. A., Vehovec, A., & Petty, G. (2017). Implementation and evaluation of community-based interprofessional learning activity. Journal of Interprofessional Care, 31, 9197, https://doi.org/10.1080/13561820.2016.1237936Google Scholar
Luszczynska, A., Horodyska, K., Zarychta, K., Liszewska, N., Knoll, N., & Scholz, U. (2016). Planning and self-efficacy interventions encouraging replacing energy-dense foods intake with fruit and vegetable: A longitudinal experimental study. Psychology and Health, 31, 4064. https://doi.org/10.1080/08870446.2015.1070156Google Scholar
Michie, S., Johnston, M., Abraham, C., Lawton, R., Parker, D., & Walker, A. (2005). Making psychological theory useful for implementing evidence based practice: A consensus approach. Quality and Safety in Health Care, 14, 2633. https://doi.org/10.1136/qshc.2004.011155Google Scholar
Muellmann, S., Steenbock., B., De Cocker, K. et al. (2017). Views of policy makers and health promotion professionals on factors facilitating implementation and maintenance of interventions and policies promoting physical activity and healthy eating: results of the DEDIPAC project. BMC Public Health, 17, 932. https://doi.org/10.1186/s12889-017-4929-9Google Scholar
Nathan, N., Yoong, S. L., Sutherland, R. et al. (2016). Effectiveness of a multicomponent intervention to enhance implementation of a healthy canteen policy in Australian primary schools: A randomised controlled trial. International Journal of Behavioral Nutrition and Physical Activity, 13, 106. https://doi.org/10.1186/s12966-016-0431-5Google Scholar
Nilsen, P. (2015). Making sense of implementation theories, models and frameworks. Implementation Science, 10, 53. https://doi.org/10.1186/s13012-015-0242-0Google Scholar
Ory, M. G., Jordan, P. J., & Bazzarre, T. (2002). The behavior change consortium: Setting the stage for a new century of health behavior-change research. Health Education Research, 17, 500511. https://doi.org/10.1093/her/17.5.500Google Scholar
Peters, G. -J. Y., de Bruin, M., & Crutzen, R. (2015). Everything should be as simple as possible, but no simpler: Towards a protocol for accumulating evidence regarding the active content of health behaviour change interventions. Health Psychology Review, 9, 114. https://doi.org/10.1080/17437199.2013.848409Google Scholar
Pfadenhauer, L. M., Gerhardus, A., Mozygemba, K. et al. (2017). Making sense of complexity in context and implementation: The Context and Implementation of Complex Interventions (CICI) framework. Implementation Science, 12, 21. https://doi.org/10.1186/s13012-017-0552-5Google Scholar
Proctor, E. K., Landsverk, J., Aarons, G., Chambers, D., Gilsson, C., & Mittman, B. (2009). Implementation research in mental health services: An emerging science with conceptual, methodological, and training challenges. Administration and Policy in Mental Health, 36, 2234. https://doi.org/10.1007/s10488-008-0197-4Google Scholar
Proctor, E., Silmere, H., Raghavan, R. et al. (2011). Outcomes for implementation research: Conceptual distinctions, measurement challenges, and research agenda. Administration and Policy in Mental Health, 38, 6576. https://doi.org/10.1007/s10488-010-0319-7Google Scholar
Rabin, B. A., & Brownson, R. C. (2012). Developing the terminology for dissemination and implementation research. In Brownson, R., C, Colditz, G. A., & Proctor, E. K, (Eds.), Dissemination and Implementation Research in Health (pp. 2351). New York: Oxford University Press.Google Scholar
Reilly, K., Nathan, N., Grady, A. et al. (2019). Barriers to implementation of a healthy canteen policy: A survey using the theoretical domains framework. Health Promotion Journal of Australia. https://doi.org/10.1002/hpja.218Google Scholar
Rubio, D. M., Schoenbaum, E. E., Lee, L. S. et al. (2010). Defining translational research: Implications for training. Academic Medicine, 85, 470475. https://doi.org/10.1097/ACM.0b013e3181ccd618.Google Scholar
Rutter, H., Savona, N., Glonti, K. et al. (2017). The need for a complex systems model of evidence for public health. Lancet, 390, 26022604. https://doi.org/10.1016/S0140-6736(17)31267-9Google Scholar
SIRC (Society for Implementation Research Collaboration). (2018). The SIRC Instrument Review Project (IRP): A Systematic Review and Synthesis of Implementation Science Instruments. www.societyforimplementationresearchcollaboration.org/sirc-projects/sirc-instrument-projectGoogle Scholar
Steckler, A., Goodman, R. M., McLeroy, K. R., Davis, S., & Koch, G. (1992). Measuring the diffusion of innovative health promotion programs. American Journal of Health Promotion, 6, 214224. https://doi.org/10.4278/0890-1171-6.3.214Google Scholar
Tabak, R. G., Khoong, E. C., Chambers, D. A., & Brownson, R. C. (2012). Bridging research and practice: Models for dissemination and implementation research. American Journal of Preventive Medicine, 43, 337350.Google Scholar

References

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179211. https://doi.org/10.1016/0749-5978(91)90020-TGoogle Scholar
Bogalo, L., & Moss-Morris, R. (2006). The effectiveness of homework tasks in an irritable bowel syndrome self-management programme. New Zealand Journal of Psychology, 35, 120125. https://psycnet.apa.org/record/2007-01035-003Google Scholar
Brito, C., Portela, M. C., & Vasconcellos, M. T. L. d. (2014). Factors associated to persistence with hormonal therapy in women with breast cancer. Revista de saude publica, 48, 284295. https://doi.org/10.1590/S0034-8910.2014048004799Google Scholar
Chilcot, J., & Moss-Morris, R. (2013). Changes in illness-related cognitions rather than distress mediate improvements in irritable bowel syndrome (IBS) symptoms and disability following a brief cognitive behavioural therapy intervention. Behaviour Research and Therapy, 51, 690695. https://doi.org/10.1016/j.brat.2013.07.007Google Scholar
Craig, P., Dieppe, P., Macintyre, S., Michie, S., Nazareth, I., & Petticrew, M. (2008). Developing and evaluating complex interventions: The new Medical Research Council guidance. British Medical Journal, 337, a1655. https://doi.org/10.1136/bmj.a1655Google Scholar
Duncan, M., Moschopoulou, E., Herrington, E. et al. (2017). Review of systematic reviews of non-pharmacological interventions to improve quality of life in cancer survivors. BMJ open, 7, e015860–e015860. https://doi.org/10.1136/bmjopen-2017-015860Google Scholar
EBCTCG (Early Breast Cancer Trialists’ Collaborative Group). (1998). Tamoxifen for early breast cancer: An overview of the randomised trials. The Lancet, 351, 14511467. https://doi.org/10.1016/S0140-6736 (97)11423-4Google Scholar
EBCTCG (Early Breast Cancer Trialists’ Collaborative Group). (2011). Relevance of breast cancer hormone receptors and other factors to the efficacy of adjuvant tamoxifen: Patient-level meta-analysis of randomised trials. The Lancet, 378, 771784. https://doi.org/10.1016/S0140-6736(11)60993-8Google Scholar
Eccles, M. P., & Mittman, B. S. (2006). Welcome to Implementation Science. Implementation Science, 1, 1. https://doi.org/10.1186/1748-5908-1-1Google Scholar
Everitt, H. A., Landau, S., O’Reilly, G. et al. (2019). Assessing telephone-delivered cognitive–behavioural therapy (CBT) and web-delivered CBT versus treatment as usual in irritable bowel syndrome (ACTIB): A multicentre randomised trial. Gut, 68, 16131623. https://doi.org/10.1136/gutjnl-2018-317805Google Scholar
Everitt, H. A., Moss-Morris, R. E., Sibelli, A. et al. (2010). Management of irritable bowel syndrome in primary care: Feasibility randomised controlled trial of mebeverine, methylcellulose, placebo and a patient self-management cognitive behavioural therapy website. (MIBS trial). BMC Gastroenterology, 10, 136145. https://doi.org/10.1186/1471-230X-10-136Google Scholar
Finch, T. (2008). Teledermatology for chronic disease management: Coherence and normalization. Chronic Illness, 4, 127134. https://doi.org/10.1177/1742395308092483Google Scholar
Horne, R., Weinman, J., & Hankins, M. (1999). The beliefs about medicines questionnaire: The development and evaluation of a new method for assessing the cognitive representation of medication. Psychology and Health, 14, 124. https://doi.org/10.1080/08870449908407311Google Scholar
Hudson, J. L., Moss-Morris, R., Game, D., Carroll, A., & Chilcot, J. (2016). Improving Distress in Dialysis (iDiD): A tailored CBT self-management treatment for patients undergoing dialysis. Journal of Renal Care, 42, 223238. https://doi.org/10.1111/jorc.12168Google Scholar
Hudson, J. L., Moss-Morris, R., Game, D., Carroll, A., McCrone, P. et al. (2016). Improving distress in dialysis (iDiD): A feasibility two-arm parallel randomised controlled trial of an online cognitive behavioural therapy intervention with and without therapist-led telephone support for psychological distress in patients undergoing haemodialysis. BMJ Open, 6. https://doi.org/10.1136/bmjopen-2016-011286Google Scholar
Hudson, J. L., Moss-Morris, R., Norton, S. et al. (2017). Tailored online cognitive behavioural therapy with or without therapist support calls to target psychological distress in adults receiving haemodialysis: A feasibility randomised controlled trial. Journal of Psychosomatic Research, 102, 6170. https://doi.org/10.1016/j.jpsychores.2017.09.009Google Scholar
Kennedy, T., Jones, R., Darnley, S., Seed, P., Wessely, S., & Chalder, T. (2005). Cognitive behaviour therapy in addition to antispasmodic treatment for irritable bowel syndrome in primary care: Randomised controlled trial. British Medical Journal, 331, 435. https://doi.org/10.1136/bmj.38545.505764.06Google Scholar
Leventhal, H., Bodnar-Deren, S., Breland, J. Y. et al. (2012). Modeling Health and Illness Behaviour: The approach of the Commonsense Model. In Baum, A. B., Revenson, T. A., & Singer, J. (Eds.), Handbook of Health Psychology (pp. 336). New York: Psychology Press.Google Scholar
Lovell, R. M., & Ford, A. C. (2012). Global prevalence of and risk factors for irritable bowel syndrome: A meta-analysis. Clinical Gastroenterology and Hepatology, 10, 712721, e714. https://doi.org/10.1016/j.cgh.2012.02.029Google Scholar
Mair, F. S., May, C., O’Donnell, C., Finch, T., Sullivan, F., & Murray, E. (2012). Factors that promote or inhibit the implementation of e-health systems: An explanatory systematic review. Bulletin of the World Health Organization, 90, 357364. https://doi.org/10.2471/BLT.11.099424Google Scholar
May, C. (2013). Towards a general theory of implementation. Implementation Science, 8, 18. https://doi.org/10.1186/1748-5908-8-18Google Scholar
May, C., Finch, T., Mair, F. et al. (2007). Understanding the implementation of complex interventions in health care: The normalization process model. BMC Health Services Research, 7, 148. https://doi.org/10.1186/1472-6963-7-148Google Scholar
May, C., Rapley, T., Mair, F. et al. (2015). Normalization process theory on-line users’ manual, toolkit and NoMAD instrument. Normalization Process Theory. Website. www.normalizationprocess.orgGoogle Scholar
May, C. R., Mair, F., Finch, T. et al. (2009). Development of a theory of implementation and integration: Normalization process theory. Implementation Science, 4, 29. https://doi.org/10.1186/1748-5908-4-29Google Scholar
Moon, Z., Moss-Morris, R., Hunter, M. S., & Hughes, L. D. (2017). Understanding tamoxifen adherence in women with breast cancer: A qualitative study. British Journal of Health Psychology, 22, 978997. https://doi.org/10.1111/bjhp.12266Google Scholar
Moon, Z., Moss-Morris, R., Hunter, M. S., & Hughes, L. D. (2019). Development of a self-management intervention to improve tamoxifen adherence in breast cancer survivors using an intervention mapping approach. Unpublished manuscript, King’s College London.Google Scholar
Moon, Z. E., Moss-Morris, R., Hunter, M. S., Goodliffe, S., & Hughes, L. D. (2019). Acceptability and feasibility of a self-management intervention for women prescribed tamoxifen. Health Education Journal. https://doi.org/10.1177/0017896919853856Google Scholar
Moon, Z. E., Moss-Morris, R., Hunter, M. S., Norton, S., & Hughes, L. D. (2019). Non-adherence to tamoxifen in breast cancer survivors: A 12 month longitudinal analysis. Health Psychology, 38, 888899. https://doi.org/10.1037/hea0000785Google Scholar
Moore, G. F., Audrey, S., Barker, M. et al. (2015). Process evaluation of complex interventions: Medical Research Council guidance. BMJ: British Medical Journal, 350, h1258. https://doi.org/10.1136/bmj.h1258Google Scholar
Moss-Morris, R., McAlpine, L., Didsbury, L. P., & Spence, M. J. (2009). A randomized controlled trial of a cognitive behavioural therapy-based self-management intervention for irritable bowel syndrome in primary care. Psychological Medicine, 40, 8594. https://doi.org/10.1017/S0033291709990195Google Scholar
Murray, E., Treweek, S., Pope, C. et al. (2010). Normalisation process theory: A framework for developing, evaluating and implementing complex interventions. BMC Medicine, 8, 63. https://doi.org/10.1186/1741-7015-8-63Google Scholar
NIHR (National Institute for Health Research). (2019). Patient and Public Involvement in Health and Social Care Research: A handbook for researchers. www.nihr.ac.uk/about-us/CCF/funding/how-we-can-help-you/RDS-PPI-Handbook-2014-v8-FINAL.pdfGoogle Scholar
NHS (National Health Service). (2019). The NHS Long-Term Plan. www.longtermplan.nhs.uk/publication/nhs-long-term-plan/Google Scholar
Rayner, L., Matcham, F., Hutton, J. et al. (2014). Embedding integrated mental health assessment and management in general hospital settings: Feasibility, acceptability and the prevalence of common mental disorder. General Hospital Psychiatry, 36, 318324. https://doi.org/10.1016/j.genhosppsych.2013.12.004Google Scholar
Skivington, K., Matthews, L., Craig, P., Simpson, S., & Moore, L. (2018). Developing and evaluating complex interventions: Updating Medical Research Council guidance to take account of new methodological and theoretical approaches. The Lancet, 392, S2. Meeting abstract: Public Health Science 2018, Belfast, Northern Ireland, November 23, 2018. http://dx.doi.org/10.1016/s0140-6736(18)32865-4Google Scholar
Tonkin-Crine, S., Bishop, F. L., Ellis, M., Moss-Morris, R., & Everitt, H. (2013). Exploring patients’ views of a cognitive behavioral therapy-based website for the self-management of irritable bowel syndrome symptoms. Journal of Medical Internet Research, 15, e190–e190. https://doi.org/10.2196/jmir.2672Google Scholar
Yardley, L., Morrison, L., Bradbury, K., & Muller, I. (2015). The person-based approach to intervention development: Application to digital health-related behavior change interventions. Journal of Medical Internet Research, 17, e30–e30.Google Scholar

References

Abrahamse, W., & Steg, L. (2013). Social influence approaches to encourage resource conservation: A meta-analysis. Global Environmental Change, 23, 17731785. https://doi.org/https://doi.org/10.1016/j.gloenvcha.2013.07.029Google Scholar
Abrahamse, W., Steg, L., Vlek, C., & Rothengatter, T. (2007). The effect of tailored information, goal setting, and tailored feedback on household energy use, energy-related behaviors, and behavioral antecedents. Journal of Environmental Psychology, 27, 265276. https://doi.org/10.1016/j.jenvp.2007.08.002Google Scholar
Bauer, C., & Strauss, . (2016). Location-based advertising on mobile devices. Management Review Quarterly, 66, 159194. https://doi.org/10.1007/s11301-015-0118-zGoogle Scholar
Baumeister, H., Reichler, L., Munzinger, M., & Lin, J. (2014). The impact of guidance on Internet-based mental health interventions: A systematic review. Internet Interventions, 1, 205215. https://doi.org/10.1016/j.invent.2014.08.003Google Scholar
Bradbury, K., Morton, K., Band, R. et al. (2018). Using the Person-Based Approach to optimise a digital intervention for the management of hypertension. PloS ONE, 13, e0196868. https://doi.org/10.1371/journal.pone.0196868Google Scholar
Christakis, N. A., & Fowler, J. H. (2009). Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives. New York: Little, Brown.Google Scholar
Collins, L. M., Murphy, S. A., & Strecher, V. (2007). The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): New methods for more potent eHealth interventions. American Journal of Preventive Medicine, 32, S112S118. https://doi.org/10.1016/j.amepre.2007.01.022.Google Scholar
Corbett, T., Cheetham, T., Müller, A. M. et al. (2018). Exploring cancer survivors’ views of health behaviour change: “Where do you start, where do you stop with everything?Psycho‐Oncology, 27, 18161824. https://doi.org/10.1002/pon.4732Google Scholar
Cotton, D., & Gresty, K. (2006). Reflecting on the think‐aloud method for evaluating e‐learning. British Journal of Educational Technology, 37, 4554. https://doi.org/10.1111/j.1467-8535.2005.00521Google Scholar
Friedman, C. P., Allee, N. J., Delaney, B. C. et al. (2017). The science of learning health systems: Foundations for a new journal. Learning Health Systems, 1, e10020. https://doi.org/10.1002/lrh2.10020Google Scholar
Harris, P. R., Sillence, E., & Briggs, P. (2011). Perceived threat and corroboration: Key factors that improve a predictive model of trust in internet-based health information and advice. Journal of Medical Internet Research, 13, e51. https://doi.org/10.2196/jmir.1821Google Scholar
Kreuter, M. W., Bull, F. C., Clark, E. M., & Oswald, D. L. (1999). Understanding how people process health information: A comparison of tailored and nontailored weight-loss materials. Health Psychology, 18, 487. https://doi.org/10.1037/0278-6133.18.5.487Google Scholar
Krug, S. (2006). Don’t Make Me Think! A Common Sense Approach to Web Usability. (2nd ed.). New York: New Riders.Google Scholar
Little, P., Stuart, B., Hobbs, F. R. et al. (2016). An internet-based intervention with brief nurse support to manage obesity in primary care (POWeR+): A pragmatic, parallel-group, randomised controlled trial. The Lancet Diabetes and Endocrinology, 4, 821828. https://doi.org/10.1016/S2213-8587(16)30099-7Google Scholar
Lorig, K. R., & Holman, H. R. (2003). Self-management education: History, definition, outcomes, and mechanisms. Annals of Behavioral Medicine, 26, 17. https://doi.org/10.1207/S15324796ABM2601_01Google Scholar
Maher, T. (2014). Plain English Campaign. Website. www.plainenglish.co.uk.Google Scholar
Mayer, R. E. (2002). Multimedia learning. Psychology of Learning and Motivation, 41, 85139. https://doi.org/10.1016/S0079-7421(02)80005-6Google Scholar
Mohr, D. C., Lyon, A. R., Lattie, E. G., Reddy, M., & Schueller, S. M. (2017). Accelerating digital mental health research from early design and creation to successful implementation and sustainment. Journal of Medical Internet Research, 19, e153. https://doi.org/10.2196/jmir.7725Google Scholar
Morrison, L., Moss‐Morris, R., Michie, S., & Yardley, L. (2014). Optimizing engagement with Internet‐based health behaviour change interventions: Comparison of self‐assessment with and without tailored feedback using a mixed methods approach. British Journal of Health Psychology, 19, 839855. https://doi.org/10.1111/bjhp.12083Google Scholar
Nahum-Shani, I., Hekler, E. B., & Spruijt-Metz, D. (2015). Building health behavior models to guide the development of just-in-time adaptive interventions: A pragmatic framework. Health Psychology, 34, 1209. https://doi.org/10.1037/hea0000306Google Scholar
Naughton, F., Hopewell, S., Lathia, N. et al. (2016). A context-sensing mobile phone app (Q sense) for smoking cessation: A mixed-methods study. JMIR mHealth and uHealth, 4, e106. https://doi.org/10.2196/mhealth.5787Google Scholar
Rowsell, A., Muller, I., Murray, E. et al. (2015). Views of people with high and low levels of health literacy about a digital intervention to promote physical activity for diabetes: A qualitative study in five countries. Journal of Medical Internet Research, 17, e230. https://doi.org/10.2196/jmir.4999Google Scholar
Sbaffi, L., & Rowley, J. (2017). Trust and credibility in web-based health information: A review and agenda for future research. Journal of Medical Internet Research, 19, e218. https://doi.org/10.2196/jmir.7579Google Scholar
Singal, A. G., Higgins, P. D., & Waljee, A. K. (2014). A primer on effectiveness and efficacy trials. Clinical and Translational Gastroenterology, 5, e45. https://doi.org/10.1038/ctg.2013.13Google Scholar
Smith, G. L., Banting, L., Eime, R., O’Sullivan, G., & van Uffelen, J. G. (2017). The association between social support and physical activity in older adults: A systematic review. International Journal of Behavioral Nutrition and Physical Activity, 14, 56. https://doi.org/10.1186/s12966-017-0509-8.Google Scholar
van Beurden, S. B., Greaves, C. J., Smith, J. R., & Abraham, C. (2016). Techniques for modifying impulsive processes associated with unhealthy eating: A systematic review. Health Psychology, 35, 793. https://doi.org/10.1037/hea0000337.Google Scholar
Van den Haak, M. J., De Jong, M. D., & Schellens, P. J. (2007). Evaluation of an informational web site: Three variants of the think-aloud method compared. Technical Communication, 54, 5871.Google Scholar
Van Velsen, L., Wentzel, J., & Van Gemert-Pijnen, J. E. (2013). Designing eHealth that matters via a multidisciplinary requirements development approach. JMIR Research Protocols, 2, e21. https://doi.org/10.2196/resprot.2547Google Scholar
Yardley, L., Morrison, L., Bradbury, K., & Muller, I. (2015). The Person-Based Approach to intervention development: Application to digital health-related behavior change interventions. Journal of Medical Internet Research, 17, e30. https://doi.org/10.2196/jmir.4055Google Scholar
Yardley, L., Spring, B. J., Riper, H. et al. (2016). Understanding and promoting effective engagement with digital behavior change interventions. American Journal of Preventive Medicine, 51, 833842.Google Scholar

References

AIHW (Australian Institute of Health and Welfare). (2013). Health Expenditure Australia 2011–12. www.aihw.gov.au/reports/health-welfare-expenditure/hea-2011-12/report-editionsGoogle Scholar
Alayli-Goebbels, A. F., Evers, S. M., Alexeeva, D. et al. (2013). A review of economic evaluations of behavior change interventions: Setting an agenda for research methods and practice. Journal of Public Health, 36, 336344. https://doi.org/10.1093/pubmed/fdt080Google Scholar
Baker, L., Birnbaum, H., Geppert, J., Mishol, D., & Moyneur, E. (2003). The relationship between technology availability and health care spending: Attempts to address technology availability and rising costs could end up badly misguided if implications for quality are not considered. Health Affairs, 22, W3537. https://doi.org/10.1377/hlthaff.w3.537Google Scholar
Battista, W., Romero-Canyas, R., Smith, S. L. et al. (2018). Behavior change interventions to reduce illegal fishing. Frontiers in Marine Science, 5, 403. https://doi.org/10.3389/fmars.2018.00403Google Scholar
Bhattacharya, J., Hyde, T., & Tu, P. (2013). Health Economics. New York: Palgrave Macmillan.Google Scholar
Binger, B. R., & Hoffman, E. (1988). Microeconomics with Calculus. Glenview, IL: Scott Foresman.Google Scholar
Bodenheimer, T. (2005). High and rising health care costs. Part 2: Technologic innovation. Annals of Internal Medicine, 142, 932937. https://doi.org/10.7326/0003-4819-142-11-200506070-00012Google Scholar
Brennan, A., Chick, S. E., & Davies, R. (2006). A taxonomy of model structures for economic evaluation of health technologies. Health Economics, 15, 12951310. https://doi.org/10.1002/hec.1148Google Scholar
Briggs, A., Sculpher, M., & Claxton, K. (2006). Decision Modelling for Health Economic Evaluation. New York: Oxford University Press.Google Scholar
Cutler, D. M. (2004). Behavioral health interventions: What works and why. In Anderson, N. B., Bulatao, R. A., & Cohen, B. (Eds.), Critical Perspectives on Racial and Ethnic Differences in Health in Late Life (pp. 643674). Washington, DC: National Academies Press. https://doi.org/10.17226/11086Google Scholar
Drummond, M. F., Sculpher, M. J., Claxton, K., Stoddart, G. L., & Torrance, G. W. (2015). Methods for the Economic Evaluation of Health Care Programmes (4th ed.). New York: Oxford University Press.Google Scholar
Fertig, A., Lefkowitz, J., & Fishbane, A. (2015). Using Behavioral Science to Increase Retirement Savings: A New Look at Voluntary Pension Contributions in Mexico. Ideas42 report. www.ideas42.org/wp-content/uploads/2015/11/I42_571_MexicoPensionsReport_ENG_final_digital.pdfGoogle Scholar
Folland, S., Goodman, A. C., & Stano, M. (2016). The Economics of Health and Health Care (7th ed.). Abingdon: Routledge.Google Scholar
Fox-Rushby, J., & Cairns, J. (2005). Economic Evaluation. Maidenhead: Open University Press.Google Scholar
Fragoulakis, V., Mitropoulou, C., Williams, M., & Patrinos, G. P. (2015). Economic Evaluation in Genomic Medicine. Burlington, CA: Academic Press.Google Scholar
Gray, A. M., Clarke, P. M., Wolstenholme, J. L., & Wordsworth, S. (2011). Applied Methods of Cost-Effectiveness Analysis in Healthcare. New York: Oxford University Press.Google Scholar
Hallsworth, M., Snijders, V., Burd, H. et al. (2016). Applying Behavioral Insights: Simple Ways to Improve Health Outcomes. Report of the WISH Behavioral Insights Forum 2016. www.imperial.ac.uk/media/imperial-college/institute-of-global-health-innovation/Behavioral_Insights_Report-(1).pdfGoogle Scholar
Huang, X., Lin, J., & Demner-Fushman, D. (2006). Evaluation of PICO as a knowledge representation for clinical questions. AMIA Annual Symposium Proceedings, 2006, 359363. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1839740/Google Scholar
Husereau, D., Drummond, M., Petrou, S. et al. (2013). Consolidated health economic evaluation reporting standards (CHEERS) statement. Cost Effectiveness and Resource Allocation, 11, 6. https://doi.org/10.1186/1478-7547-11-6Google Scholar
Kelly, M. P., & Barker, M. (2016). Why is changing health-related behaviour so difficult? Public Health, 136, 109116. https://doi.org/10.1016/j.puhe.2016.03.030Google Scholar
Morris, S., Devlin, N., & Parkin, D. (2007). Economic Analysis in Health Care. Chichester: Wiley.Google Scholar
Mpofu, E. (2014). Community-Oriented Health Services: Practices Across Disciplines. New York: Springer.Google Scholar
Neri, D., Leifer, J., & Barrows, A. (2016). Graduating Students into Voters. Overcoming the Psychological Barriers Faced by Student Voters: A Behavioral Science Approach. Ideas42 report. www.ideas42.org/wp-content/uploads/2017/05/Students_into_Voters.pdfGoogle Scholar
NICE (National Institute for Health and Care Excellence). (2013). Guide to the Methods of Technology Appraisal 2013. www.nice.org.uk/process/pmg9/chapter/evidenceGoogle Scholar
OECD (Organisation for Economic Co-operation and Development). (2017). Health spending (indicator). https://data.oecd.org/healthres/health-spending.htmGoogle Scholar
Perloff, J. (2015). Microeconomics (7th ed.). Boston: Pearson.Google Scholar
Perneczky, R., Wagenpfeil, S., Komossa, K., Grimmer, T., Diehl, J., & Kurz, A. (2006). Mapping scores onto stages: Mini-mental state examination and clinical dementia rating. The American Journal of Geriatric Psychiatry, 14, 139144. https://doi.org/10.1097/01.jgp.0000192478.82189.a8Google Scholar
Schardt, C., Adams, M. B., Owens, T., Keitz, S., & Fontelo, P. (2007). Utilization of the PICO framework to improve searching PubMed for clinical questions. BMC Medical Informatics and Decision Making, 7, 16. https://doi.org/10.1186/1472-6947-7-16Google Scholar
Thaler, R. H., & Sunstein, C. R. (2009). Nudge: Improving Decisions about Health, Wealth, and Happiness. New Haven, CT: Yale University Press.Google Scholar
WHO (World Health Organization). (2016). Health System Efficiency: How to Make Measurement Matter for Policy and Management. Geneva: WHO.Google Scholar

References

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179211. https://doi.org/10.1016/0749-5978(91)90020-TGoogle Scholar
Allen, L., Williams, J., Townsend, N. et al. (2017). Socioeconomic status and non-communicable disease behavioural risk factors in low-income and lower-middle-income countries: A systematic review. The Lancet Global Health, 5, e277e289. https://doi.org/10.1016/S2214-109X(17)30058-XGoogle Scholar
Attwood, S., van Sluijs, E., & Sutton, S. (2016). Exploring equity in primary-care-based physical activity interventions using PROGRESS-Plus: A systematic review and evidence synthesis. International Journal of Behavioral Nutrition and Physical Activity, 13, 60. https://doi.org/10.1186/s12966-016-0384-8Google Scholar
Bauer, G. R. (2014). Incorporating intersectionality theory into population health research methodology: Challenges and the potential to advance health equity. Social Science and Medicine, 110, S10S17. https://doi.org/10.1016/j.socscimed.2014.03.022Google Scholar
Bimbi, D. S., Nanin, J. E., Parsons, J. T., Vicioso, K. J., Missildine, W., & Frost, D. (2006). Assessing gay and bisexual men’s outcome expectancies for sexual risk under the influence of alcohol and drugs. Substance Use and Misuse, 41, 643665. https://doi.org/10.1080/10826080500411080Google Scholar
Burdette, A. M., Webb, N. S., Hill, T. D., & Jokinen-Gordon, H. (2017). Race-specific trends in HPV vaccinations and provider recommendations: Persistent disparities or social progress? Public Health, 142, 167176. https://doi.org/10.1016/j.puhe.2016.07.009Google Scholar
Doran, J. M., Pietrzak, R. H., Hoff, R., & Harpaz-Rotem, I. (2017). Psychotherapy utilization and retention in a national sample of veterans With PTSD. Journal of Clinical Psychology, 73, 12591279. https://doi.org/10.1002/jclp.22445Google Scholar
Engel, G. L. (1977). The need for a new medical model: A challenge for biomedicine. Science, 196(4286), 129136. https://doi.org/10.1126/science.847460Google Scholar
Erves, J. C., Mayo-Gamble, T. L., Malin-Fair, A. et al. (2017). Needs, priorities, and recommendations for engaging underrepresented populations in clinical research: A community perspective. Journal of Community Health, 42, 472480. https://doi.org/10.1007/s10900-016-0279-2Google Scholar
Fishbein, M., Triandis, H. C., Kanfer, F. H., Becker, M. H., Middlestadt, S. E., & Eichler, A. (2001). Factors influencing behavior and behavior change. In Baum, A., Revenson, T. A., & Singer, J. E. (Eds.), Handbook of Health Psychology (pp. 317). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Ford, J. G., Howerton, M. W., Lai, G. Y. et al. (2008). Barriers to recruiting underrepresented populations to cancer clinical trials: A systematic review. Cancer, 112, 228242. https://doi.org/10.1002/cncr.23157Google Scholar
Freedman, L. S., Simon, R., Foulkes, M. A. et al. 1995). Inclusion of women and minorities in clinical trials and the NIH Revitalization Act of 1993: The perspective of NIH clinical trialists. Controlled Clinical Trials, 16, 277285; discussion 286–279, 293309. https://doi.org/10.1016/0197-2456(95)00048-8Google Scholar
Geller, S. E., Koch, A., Pellettieri, B., & Carnes, M. (2011). Inclusion, analysis, and reporting of sex and race/ethnicity in clinical trials: Have we made progress? Journal of Women’s Health, 20, 315320. https://doi.org/10.1089/jwh.2010.2469Google Scholar
Hankonen, N., Heino, M. T. J., Kujala, E. et al. (2017). What explains the socioeconomic status gap in activity? Educational differences in determinants of physical activity and screentime. BMC Public Health, 17, 115. https://doi.org/10.1186/s12889-016-3880-5Google Scholar
Hardeman, W., Sutton, S., Griffin, S. et al. (2005). A causal modelling approach to the development of theory-based behaviour change programmes for trial evaluation. Health Education Research, 20, 676687. https://doi.org/10.1093/her/cyh022Google Scholar
Haughton, C. F., Silfee, V. J., Wang, M. L. et al. (2018). Racial/ethnic representation in lifestyle weight loss intervention studies in the United States: A systematic review. Preventive Medicine Reports, 9, 131137. https://doi.org/10.1016/j.pmedr.2018.01.012Google Scholar
Hooper, M. W., Baker, E. A., & Robinson, R. G. (2014). Efficacy of a DVD-based smoking cessation intervention for African Americans. Nicotine and Tobacco Research, 16, 13271335. https://doi.org/10.1093/ntr/ntu079Google Scholar
Hooper, M. W., Larry, R., Okuyemi, K. et al. (2013). Culturally specific versus standard group cognitive behavioral therapy for smoking cessation among African Americans: An RCT protocol. BMC Psychol, 1, 15. https://doi.org/10.1186/2050-7283-1-15Google Scholar
Jahnel, T., Ferguson, S. G., Shiffman, S., & Schüz, B. (2019). Daily stress as link between disadvantage and smoking: An ecological momentary assessment study. BMC Public Health, 19, 1284. https://doi.org/10.1186/s12889-019-7631-2Google Scholar
Kagawa Singer, M. (2012). Applying the concept of culture to reduce health disparities through health behavior research. Preventive Medicine, 55, 356361. https://doi.org/10.1016/j.ypmed.2012.02.011Google Scholar
Kashubeck-West, S., & Szymanski, D. M. (2008). Risky sexual behavior in gay and bisexual men: Internalized heterosexism, sensation seeking, and substance use. Counseling Psychologist, 36, 595614. https://doi.org/10.1177/0011000007309633Google Scholar
Kreuter, M. W., Lukwago, S. N., Bucholtz, D. C., Clark, E. M., & Sanders-Thompson, V. (2003). Achieving cultural appropriateness in health promotion programs: Targeted and tailored approaches. Health Education and Behavior, 30, 133146. https://doi.org/10.1177/1090198102251021Google Scholar
Kwiatkowski, K., Coe, K., Bailar, J. C., & Swanson, G. M. (2013). Inclusion of minorities and women in cancer clinical trials, a decade later: Have we improved? Cancer, 119, 29562963. https://doi.org/10.1002/cncr.28168Google Scholar
Laidley, T. M. (2011). The influence of social class and cultural variables on environmental behaviors: Municipal-level evidence from Massachusetts. Environment and Behavior, 45, 170197. https://doi.org/10.1177/0013916511416647Google Scholar
Lehne, G., & Bolte, G. (2017). Impact of universal interventions on social inequalities in physical activity among older adults: An equity-focused systematic review. International Journal of Behavioral Nutrition and Physical Activity, 14, 20. https://doi.org/10.1186/s12966-017-0472-4Google Scholar
Leventhal, H., Diefenbach, M., & Leventhal, E. A. (1992). Illness cognition: Using common sense to understand treatment adherence and affect cognition interactions. Cognitive Therapy and Research, 16, 143163. https://doi.org/10.1007/bf01173486Google Scholar
Lindbladh, E., Lyttkens, C. H., Hanson, B. S., Östergren, P., Isacsson, S. O., & Lindgren, B. (1996). An economic and sociological interpretation of social differences in health-related behaviour: An encounter as a guide to social epidemiology. Social Science and Medicine, 43, 18171827. https://doi.org/10.1016/S0277-9536(96)00087-1Google Scholar
Lorenc, T., Petticrew, M., Welch, V., & Tugwell, P. (2013). What types of interventions generate inequalities? Evidence from systematic reviews. Journal of Epidemiology and Community Health, 67, 190. https://doi.org/10.1136/jech-2012-201257Google Scholar
Manstead, A. S. R. (2018). The psychology of social class: How socioeconomic status impacts thought, feelings, and behaviour. British Journal of Social Psychology, 57, 267291. https://doi.org/10.1111/bjso.12251Google Scholar
Marmot, M. (2015). The Health Gap: The Challenge of an Unequal World. London: Bloomsbury.Google Scholar
Marshal, M. P., Friedman, M. S., Stall, R. et al. (2008). Sexual orientation and adolescent substance use: A meta-analysis and methodological review. Addiction, 103, 546556. https://doi.org/10.1111/j.1360-0443.2008.02149.xGoogle Scholar
McLeroy, K. R., Bibeau, D., Steckler, A., & Glanz, K. (1988). An ecological perspective on health promotion programs. Health Education and Behavior, 15, 351377. https://doi.org/10.1177/109019818801500401Google Scholar
Meader, N., King, K., Moe-Byrne, T. et al. (2016). A systematic review on the clustering and co-occurrence of multiple risk behaviours. BMC Public Health, 16. https://doi.org/10.1186/s12889-016-3373-6Google Scholar
Meyer, I. H. (2003). Prejudice, social stress, and mental health in lesbian, gay and bisexual populations: Conceptual issues and research evidence. Psychological Bulletin, 129, 674697. https://doi.org/10.1037/0033-2909.129.5.674Google Scholar
Michie, S., Richardson, M., Johnston, M. et al. (2013). The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: Building an international consensus for the reporting of behavior change interventions. Annals of Behavioral Medicine, 46, 8195. https://doi.org/10.1007/s12160-013-9486-6Google Scholar
Mickelson, R. A. (2003). When are racial disparities in education the result of racial discrimination? A social science perspective. Teachers College Record, 105, 10521086. https://doi.org/10.1111/1467-9620.00277Google Scholar
Myers, H. F. (2009). Ethnicity- and socio-economic status-related stresses in context: An integrative review and conceptual model. Journal of Behavioral Medicine, 32, 919. https://doi.org/10.1007/s10865-008-9181-4Google Scholar
O’Neill, J., Tabish, H., Welch, V. et al. (2014). Applying an equity lens to interventions: using PROGRESS ensures consideration of socially stratifying factors to illuminate inequities in health. Journal of Clinical Epidemiology, 67, 5664. https://doi.org/10.1016/j.jclinepi.2013.08.005Google Scholar
Odgers, C. L., Moffitt, T. E., Broadbent, J. M. et al. (2008). Female and male antisocial trajectories: From childhood origins to adult outcomes. Development and Psychopathology, 20, 673716. https://doi.org/10.1017/S0954579408000333Google Scholar
Otado, J., Kwagyan, J., Edwards, D., Ukaegbu, A., Rockcliffe, F., & Osafo, N. (2015). Culturally competent strategies for recruitment and retention of African American populations into clinical trials. Clinical and Translational Science, 8, 460466. https://doi.org/10.1111/cts.12285Google Scholar
Ouellette, S. C., & DiPlacido, J. (2001). Personality’s role in the protection and enhancement of health: Where the research has been, where it is stuck, how it might move. In Baum, A., Revenson, T. A., & Singer, J. E. (Eds.), Handbook of Health Psychology (pp. 175193). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Petrovic, D., de Mestral, C., Bochud, M. et al. (2018). The contribution of health behaviors to socioeconomic inequalities in health: A systematic review. Preventive Medicine, 113, 1531. https://doi.org/10.1016/j.ypmed.2018.05.003Google Scholar
Piff, P. K., Kraus, M. W., Côté, S., Cheng, B. H., & Keltner, D. (2010). Having less, giving more: The influence of social class on prosocial behavior. Journal of Personality and Social Psychology, 99, 771784. https://doi.org/10.1037/a0020092Google Scholar
Ready, D. D. (2010). Socioeconomic disadvantage, school attendance, and early cognitive development: The differential effects of school exposure. Sociology of Education, 83, 271286. https://doi.org/10.1177/0038040710383520Google Scholar
Resnicow, K., Baranowski, T., Ahluwalia, J. S., & Braithwaite, R. L. (1999). Cultural sensitivity in public health: Defined and demystified. Ethnicity and Disease, 9, 1021.Google Scholar
Rounsaville, B. J., Carroll, K. M., & Onken, L. S. (2001). A stage model of behavioral therapies research: Getting started and moving on from Stage I. Clinical Psychology: Science and Practice, 8, 133142. https://doi.org/10.1093/clipsy.8.2.133Google Scholar
Schüz, B. (2017). Socio-economic status and theories of health behaviour: Time to upgrade a control variable. British Journal of Health Psychology, 22, 17. https://doi.org/10.1111/bjhp.12205Google Scholar
Schüz, B., Brick, C., Wilding, S., & Conner, M. (2019). Socioeconomic status moderates the effects of health cognitions on health behaviors within participants: Two multibehavior studies. Annals of Behavioral Medicine. https://doi.org/10.1093/abm/kaz023Google Scholar
Schüz, B., Li, A. S. W., Hardinge, A., McEachan, R. R. C., & Conner, M. (2017). Socioeconomic status as a moderator between social cognitions and physical activity: Systematic review and meta-analysis based on the Theory of Planned Behavior. Psychology of Sport and Exercise, 30, 186195. https://doi.org/10.1016/j.psychsport.2017.03.004Google Scholar
Schüz, B., Wurm, S., Ziegelmann, J. P. et al. (2012). Contextual and individual predictors of physical activity: Interactions between environmental factors and health cognitions. Health Psychology, 31, 714723. https://doi.org/10.1037/a0027596Google Scholar
Shaw, M., Galobardes, B., Lawlor, D. A., Lynch, J., Wheeler, B., & Smith, G. D. (2007). The Handbook of Inequality and Socioeconomic Position. Bristol: Policy Press.Google Scholar
Smith, T. B., Rodríguez, M. D., & Bernal, G. (2011). Culture. Journal of Clinical Psychology, 67, 166175. https://doi.org/10.1002/jclp.20757Google Scholar
Spoont, M. R., Nelson, D. B., Murdoch, M. et al. (2015). Are there racial/ethnic disparities in VA PTSD treatment retention? Depression and Anxiety, 32, 415425. https://doi.org/10.1002/da.22295Google Scholar
Trinidad, D. R., Perez-Stable, E. J., White, M. M., Emery, S. L., & Messer, K. (2011). A nationwide analysis of US racial/ethnic disparities in smoking behaviors, smoking cessation, and cessation-related factors. American Journal of Public Health, 101, 699706. https://doi.org/ 10.2105/Ajph.2010.191668Google Scholar
U.S. Department of Health and Human Services. (2008). The Secretary’s Advisory Committee on National Health Promotion and Disease Prevention Objectives for 2020. Phase I Report: Recommendations for the Framework and Format of Healthy People 2020. Retrieved from Section IV: Advisory Committee Findings and Recommendations. www.healthypeople.gov/sites/default/files/PhaseI_0.pdfGoogle Scholar
U.S. Department of Health and Human Services. (2010). National Partnership for Action to End Health Disparities: The National Plan for Action. Atlanta, GA: U.S. Department of Health and Human Services. https://minorityhealth.hhs.gov/npa/files/plans/toolkit/npa_toolkit.pdfGoogle Scholar
Webb Hooper, M., Antoni, M. H., Okuyemi, K., Dietz, N. A., & Resnicow, K. (2017). Randomized controlled trial of group-based culturally specific cognitive behavioral therapy among African American smokers. Nicotine and Tobacco Research, 19, 333341. https://doi.org/10.1093/ntr/ntw181Google Scholar
Webb Hooper, M., Asfar, T., Unrod, M. et al. (2019). Reasons for exclusion from a smoking cessation trial: An analysis by race/ethnicity. Ethnicity and Disease, 29, 2330. https://doi.org/10.18865/ed.29.1.23Google Scholar
Webb Hooper, M., Mitchell, C., Marshall, V. et al. (2019). Understanding multilevel factors related to urban community trust in healthcare and research. Unpublished manuscript, Case Comprehensive Cancer Center, Cleveland, OH.Google Scholar
Webb Hooper, M., Payne, M., & Parkinson, K. A. (2017). Tobacco cessation pharmacotherapy use among racial/ethnic minorities in the United States: Considerations for primary care. Family Medicine and Community Health, 5, 193203. https://doi.org/10.15212/FMCH.2017.0138Google Scholar
Webb, M. S., Baker, E. A., & de Ybarra, D. R. (2010). Effects of culturally specific cessation messages on theoretical antecedents of behavior among low-income African American smokers. Psychology of Addictive Behaviors, 24, 333341. https://doi.org/10.1037/A0018700Google Scholar
Webb, M. S., Francis, J., Hines, B. C., & Guarles, F. B. (2007). Health disparities and culturally specific treatment: Perspectives and expectancies of African American smokers. Journal of Clinical Psychology, 63, 12471263. https://doi.org/10.1002/Jclp.20437Google Scholar
Wheldon, C. W., Kaufman, A. R., Kasza, K. A., & Moser, R. P. (2018). Tobacco use among adults by sexual orientation: Findings from the Population Assessment of Tobacco and Health Study. LGBT Health, 5, 3344. https://doi.org/10.1089/lgbt.2017.0175Google Scholar
Williams, D. R., Neighbors, H. W., & Jackson, J. S. (2003). Racial/ethnic discrimination and health: Findings from community studies. American Journal of Public Health, 93, 200208. https://doi.org/10.2105/ajph.93.2.200Google Scholar
Williams, W. W., Lu, P., O’Halloran, A. et al. (2017). Surveillance of vaccination coverage among adult populations – United States, 2015. Morbidity and Mortality Weekly Report, 66, 128. https://doi.org/10.15585/mmwr.ss6611a1Google Scholar
Wilson, S. M., Gilmore, A. K., Rhew, I. C., Hodge, K. A., & Kaysen, D. L. (2016). Minority stress is longitudinally associated with alcohol-related problems among sexual minority women. Addictive Behaviors, 61, 8083.Google Scholar

References

Algert, S. J., Agrawal, A., & Lewis, D. S. (2006). Disparities in access to fresh produce in low-income neighborhoods in Los Angeles. American Journal of Preventive Medicine, 30, 365370. https://doi.org/10.1016/j.amepre.2006.01.009Google Scholar
Armstrong, D. (2000). A survey of community gardens in upstate New York: Implications for health promotion and community development. Health and Place, 6, 319327. https://doi.org/10.1016/S1353-8292(00)00013-7Google Scholar
Atkins, M. S., Frazier, S. L., Leathers, S. J. et al. (2008). Teacher key opinion leaders and mental health consultation in low-income urban schools. Journal of Consulting and Clinical Psychology, 76, 905908. https://doi.org/10.1037/a0013036Google Scholar
Banyard, V. L., Plante, E. G., & Moynihan, M. M. (2004). Bystander education: Bringing a broader community perspective to sexual violence prevention. Journal of Community Psychology, 32, 6179. https://doi.org/10.1002/jcop.10078Google Scholar
Barker, R. (1968). Ecological Psychology: Concepts and Methods for Studying the Environment of Human Behavior. Stanford, CA: Stanford University Press.Google Scholar
Bazerghi, C., McKay, F. H., & Dunn, M. (2016). The role of food banks in addressing food insecurity: A systematic review. Journal of Community Health, 41, 732740. https://doi.org/10.1007/s10900-015-0147-5Google Scholar
Bencivenga, M., DeRubis, S., Leach, P., Lotito, L., Shoemaker, C., & Lengerich, E. J. (2008). Community partnerships, food pantries, and an evidence‐based intervention to increase mammography among rural women. The Journal of Rural Health, 24, 9195. https://doi.org/10.1111/j.1748-0361.2008.00142.xGoogle Scholar
Berkowitz, A. D. (2004). The social norms approach: Theory, research, and annotated bibliography. www.alanberkowitz.com/articles/social_norms.pdfGoogle Scholar
Borsari, B., & Carey, K. B. (2003). Descriptive and injunctive norms in college drinking: A meta-analytic integration. Journal of Studies on Alcohol, 64, 331341.Google Scholar
Brodsky, A. E. (2004). With All Our Strength: The Revolutionary Association of the Women of Afghanistan. New York: Routledge.Google Scholar
Bronfenbrenner, U. (1979). The Ecology of Human Development: Experiments by Nature and Design. Cambridge, MA: Harvard University Press.Google Scholar
Cacari-Stone, L., Wallerstein, N., Garcia, A. P., & Minkler, M. (2014). The promise of community-based participatory research for health equity: A conceptual model for bridging evidence with policy. American Journal of Public Health, 104, 16151623. https://doi.org/10.15288/jsa.2003.64.331Google Scholar
Campbell, C., Nair, Y., & Maimane, S. (2007). Building contexts that support effective community responses to HIV/AIDS: A South African case study. American Journal of Community Psychology, 39, 347363. https://doi.org/10.1007/s10464-007-9116-1Google Scholar
Coleman-Jensen, A., Rabbitt, M. P., Gregory, C. A., & Singh, A. (2018). Household Food Security in the United States in 2017 (Report No. ERR-256). Washington, DC: U.S. Department of Agriculture, Economic Research Service.Google Scholar
Corkery, L. (2004). Community gardens as a platform for education for sustainability. Australian Journal of Environmental Education, 20, 6975. https://doi.org/10.1017/S0814062600002317Google Scholar
Dynes, M., Stephenson, R., Rubardt, M., & Bartel, D. (2012). The influence of perceptions of community norms on current contraceptive use among men and women in Ethiopia and Kenya. Health and Place, 18, 766773. https://doi.org/10.1016/j.healthplace.2012.04.006Google Scholar
Elder, R. W., Lawrence, B., Ferguson, A. et al. (2010). The effectiveness of tax policy interventions for reducing excessive alcohol consumption and related harms. American Journal of Preventive Medicine, 38, 217229. https://doi.org/10.1016/j.amepre.2009.11.005Google Scholar
Fisher, E. B., Jr. (1995). The results of the COMMIT trial. Community Intervention Trial for Smoking Cessation. American Journal of Public Health, 85, 159160. https://doi.org/10.2105/AJPH.85.2.159Google Scholar
Fuller, C. M., Galea, S., Caceres, W. Blaney, S., Sisco, S., & Vlahov, D. (2007). Multilevel community-based intervention to increase access to sterile syringes among injection drug users through pharmacy sales in New York City. American Journal of Public Health, 97, 117124. https://doi.org/10.2105/AJPH.2005.069591Google Scholar
Glasgow, R. E., Cummings, K. M., & Hyland, A. (1997). Relationship of worksite smoking policy to changes in employee tobacco use: Findings from COMMIT. Community Intervention Trial for Smoking Cessation. Tobacco Control, 6, S44. https://doi.org/10.1136/tc.6.suppl_2.S44Google Scholar
Gong, F., Baron, S., Ayala, L., Stock, L., McDevitt, S., & Heaney, C. (2009). The role for community-based participatory research in formulating policy initiatives: Promoting safety and health for in-home care workers and their consumers. American Journal of Public Health, 99, S531S538. https://doi.org/10.2105/AJPH.2008.152405Google Scholar
Greder, K. A., Garasky, S., & Klein, S. (2007). Research to action: A campus-community partnership to address health issues of the food insecure. Journal of Extension, 45, 112. https://doi.org/hdfs_pubs/7/Google Scholar
Griffith, D. M., Mason, M., Yonas, M., Eng, E., Jeffries, V., Plihcik, S., & Parks, B. (2007). Dismantling institutional racism: Theory and action. American Journal of Community Psychology, 39, 381392. https://doi.org/10.1007/s10464-007-9117-0Google Scholar
Hamelin, A. M., Habicht, J. P., & Beaudry, M. (1999). Food insecurity: Consequences for the household and broader social implications. The Journal of Nutrition, 129, 525S528S. https://doi.org/10.1093/jn/129.2.525SGoogle Scholar
Handforth, B., Hennink, M., & Schwartz, M. B. (2013). A qualitative study of nutrition- based initiatives at selected food banks in the feeding America network. Journal of the Academy of Nutrition and Dietetics, 113, 411415. https://doi.org/10.1016/j.jand.2012.11.001Google Scholar
Hawe, P., Shiell, A., & Riley, T. (2009). Theorizing interventions as events in systems. American Journal of Community Psychology, 43, 267276. https://doi.org/10.1007/s10464-009-9229-9Google Scholar
Head, B., & Alford, J. (2015). Wicked problems: Implications for policy and management. Administration and Society, 47, 711739. https://doi.org/10.1177/0095399713481601Google Scholar
Hirsch, G., Levine, R., & Miller, R. (2007). Using systems dynamics modeling to understand the impact of social change initiatives. American Journal of Community Psychology, 39, 239253. https://doi.org/10.1007/s10464-007-9114-3Google Scholar
Jason, L. A., Olson, B. D., Ferrari, J. R., & Lo Sasso, A. T. (2006). Communal housing settings enhance substance abuse recovery. American Journal of Public Health, 96, 17271729. https://doi.org/10.2105/AJPH.2005.070839Google Scholar
Kaplan, R., & Kaplan, S. (1989). The Experience of Nature: A Psychological Perspective. New York: Cambridge University Press.Google Scholar
Kelly, J. G. (1966). Ecological constraints on mental health services. American Psychologist, 21, 535. https://doi.org/10.1037/h0023598Google Scholar
Kelly, J. G. (1970). Toward an ecological conception of preventive interventions. In Adelson, D. & Kalis, B. (Eds.), Community Psychology and Mental Health (pp. 126145). Scranton, PA: Chandler.Google Scholar
Kelly, J. G. (Ed.). (2006). Becoming Ecological: An Expedition into Community Psychology. Oxford: Oxford University Press.Google Scholar
Kelly, J. A., & Kalichman, S. C. (2002). Behavioral research in HIV/AIDS primary and secondary prevention: Recent advances and future directions. Journal of Consulting and Clinical Psychology, 70, 626. https://doi.org/10.1037/0022-006X.70.3.626Google Scholar
Kumar, S., Quinn, S. C., Kim, K. H., Musa, D., Hilyard, K. M., & Freimuth, V. S. (2012). The social ecological model as a framework for determinants of 2009 H1N1 influenza vaccine uptake in the United States. Health Education and Behavior, 39, 229243. https://doi.org/10.2105/AJPH.2011.300307Google Scholar
Lewin, K. (1951). Field Theory in Social Science: Selected Theoretical Papers (Ed. Cartwright, Dorwin). Oxford: Harpers.Google Scholar
Linos, N., Slopen, N., Subramanian, S. V., Berkman, L., & Kawachi, I. (2013). Influence of community social norms on spousal violence: A population-based multilevel study of Nigerian women. American Journal of Public Health, 103, 148155. https://doi.org/10.2105/AJPH.2012.300829Google Scholar
Lipperman-Kreda, S., Grube, J. W., & Paschall, M. J. (2010). Community norms, enforcement of minimum legal drinking age laws, personal beliefs and underage drinking: An explanatory model. Journal of Community Health, 35, 249257. https://doi.org/10.1007/s10900-010-9229-6Google Scholar
Martin, K., Shuckerow, M., O’Rourke, C., & Schmitz, A. (2012). Changing the conversation about hunger: The process of developing Freshplace. Progress in Community Health Partnerships: Research, Education, and Action, 6, 429434. https://doi.org/10.1353/cpr.2012.0056Google Scholar
Martin, K. S., Colantonio, A. G., Picho, K., & Boyle, K. E. (2016). Self-efficacy is associated with increased food security in novel food pantry program. SSM- Population Health, 2, 6267. https://doi.org/10.1016/j.ssmph.2016.01.005Google Scholar
Martin, K. S., Wu, R., Wolff, M., Colantonio, A. G., & Grady, J. (2013). A novel food pantry program: Food security, self-sufficiency, and diet-quality outcomes. American Journal of Preventive Medicine, 45, 569575. https://doi.org/10.1016/j.amepre.2013.06.012Google Scholar
Martinez, M. J. (2010). Power at the Roots: Gentrification, Community Gardens, and the Puerto Ricans of the Lower East Side. New York: Lexington Books.Google Scholar
Matson-Kaufman, D. M., Brownstein, J. N., Neiner, J. A., & Greaney, M. L. (2005). A site-specific literature review of policy and environmental interventions that promote physical activity and nutrition for cardiovascular health: What works? American Journal of Health Promotion, 19, 167193. https://doi.org/10.4278/0890-1171-19.3.167Google Scholar
McLeroy, K. R., Bibeau, D., Steckler, A., & Glanz, K. (1988). An ecological perspective on health promotion programs. Health Education and Behavior, 15, 351377. https://doi.org/10.1177/109019818801500401Google Scholar
Milligan, C., Gatrell, A., & Bingley, A. (2004). “Cultivating health”: Therapeutic landscapes and older people in northern England. Social Science and Medicine, 58, 17811793. https://doi.org/10.1016/S0277-9536(03)00397-6Google Scholar
Moos, R. H. (1974). Conceptualizations of human environments. American Psychologist, 38, 652665. https://doi.org/10.1037/h0035722Google Scholar
Okvat, H. A., & Zautra, A. J. (2011). Community gardening: A parsimonious path to individual, community, and environmental resilience. American Journal of Community Psychology, 47, 374387. https://doi.org/10.1007/s10464-010-9404-zGoogle Scholar
Park, R. (1952). Human Communities: The City and Human Ecology. Glencoe, IL: Free Press.Google Scholar
Perkins, H. W. (2002). Social norms and the prevention of alcohol misuse in collegiate contexts. Journal of Studies on Alcohol, 14, S164S172. https://doi.org/10.15288/jsas.2002.s14.164Google Scholar
Perkins, H. W., & Berkowitz, A. D. (1986). Perceiving the community norms of alcohol use among students: Some research implications for campus alcohol education programming. International Journal of the Addictions, 21, 961976. https://doi.org/10.3109/10826088609077249Google Scholar
Pierce, W. D., Trickett, E. J., & Moos, R. H. (1972). Changing ward atmosphere through staff discussion of the perceived ward environment. Archives of General Psychiatry, 26, 3541. https://doi.org/10.1001/archpsyc.1972.01750190037008Google Scholar
Quandt, S. A., Arcury, T. A., Early, J., Tapia, J., & Davis, J. D. (2004). Household food security among migrant and seasonal Latino farmworkers in North Carolina. Public Health Reports, 119, 568576. https://doi.org/10.1016/j.phr.2004.09.006Google Scholar
Remley, D. T., Kaiser, M. L., & Osso, T. (2013). A case study of promoting nutrition and long-term food security through choice pantry development. Journal of Hunger and Environmental Nutrition, 8, 324336. https://doi.org/10.1080/19320248.2013.819475Google Scholar
Sallis, J. F., Cervero, R. B., Ascher, W., Henderson, K. A., Kraft, M. K., & Kerr, J. (2006). An ecological approach to creating active living communities. Annual Review of Public Health, 27, 297322. https://doi.org/10.1146/annurev.publhealth.27.021405.102100Google Scholar
Sanford, N. (1970). Whatever happened to action research? Journal of Social Issues, 26, 323. https://doi.org/10.1111/j.1540-4560.1970.tb01740.xGoogle Scholar
Sarason, S. (1972). The Creation of Settings and the Future Societies. Boston, MA: Brookline Books.Google Scholar
Schensul, S. L., Singh, R., Schensul, J. J., Verma, R. K., Burleson, J. A., & Nastasi, B. K. (2015). Community gender norms change as a part of a multilevel approach to sexual health among married women in Mumbai, India. American Journal of Community Psychology, 56, 5768. https://doi.org/10.1007/s10464-015-9731-1Google Scholar
Schmid, T. L., Pratt, M., & Howze, E. (1995). Policy as intervention: Environmental and policy approaches to the prevention of cardiovascular disease. American Journal of Public Health, 85, 12071211. https://doi.org/10.2105/AJPH.85.9.1207Google Scholar
Seligman, H. K., Lyles, C., Marshall, M. B. et al. (2015). A pilot food bank intervention featuring diabetes-appropriate food improved glycemic control among clients in three states. Health Affairs, 34, 19561963. https://doi.org/10.1377/hlthaff.2015.0641Google Scholar
Sheeran, P., Abraham, C., & Orbell, S. (1999). Psychosocial correlates of heterosexual condom use: A meta-analysis. Psychological Bulletin, 125, 90132. https://doi.org/10.1037/0033-2909.125.1.90Google Scholar
Short, D. J. (2002). Newcomer programs: An educational alternative for secondary immigrant students. Education and Urban Society, 34, 173198. https://doi.org/10.1177/0013124502034002004Google Scholar
Simons-Morton, D. G., Simons-Morton, B. G., Parcel, G. S., & Bunker, J. F. (1988). Influencing personal and environmental conditions for community health: A multilevel intervention model. Family and Community Health: The Journal of Promotion and Maintenance, 11, 2535. https://doi.org/10.1097/00003727-198808000-00006Google Scholar
Stokols, D., Allen, J., & Bellingham, R. (1996). The social ecology of health promotion: Implications for research and practice. American Journal of Health Promotion, 10, 247251. https://doi.org/10.4278/0890-1171-10.4.247Google Scholar
Story, M., Kaphingst, K. M., Robinson-O’Brien, R., & Glanz, K. (2008). Creating healthy food and eating environments: Policy and environmental approaches. Annual Review of Public Health, 29, 253272. https://doi.org/10.1146/annurev.publihealth.29.020907.090926Google Scholar
Toro, P. A., Rappaport, J., & Seidman, E. (1987). Social climate comparison of mutual help and psychotherapy groups. Journal of Consulting and Clinical Psychology, 55, 430431. https://doi.org/10.1037/0022-006X.55.3.430Google Scholar
Trickett, E., Espino, S. R., & Hawe, P. (2011). How are community interventions conceptualized and conducted? An analysis of published accounts. Journal of Community Psychology. 39, 576591. https://doi.org/10.1002/jcop.20455Google Scholar
Trickett, E. J., Kelly, J. G., & Todd, D. M. (1972). The social environment of the high school: Guidelines for individual change and organizational development. In Golann, S. & Eisdorfer, C. (Eds.), Handbook of Community Mental Health (pp. 331406). New York: Appleton-Century-Crofts.Google Scholar
Wallerstein, N., Duran, B., Oetzel, J., & Minkler, M. (Eds.). (2018). Community-Based Participatory Research for Health. San Francisco: John Wiley & Sons.Google Scholar
Walter, P. (2013). Theorising community gardens as pedagogical sites in the food movement. Environmental Education Research, 19, 521539. https://doi.org/10.1080/13504622.2012.709824Google Scholar
WHO (World Health Organization). (2009). Changing Cultural and Social Norms that Support Violence. http://apps.who.int/iris/bitstream/handle/10665/44147/?sequence=1Google Scholar

References

Allam, A., Kostova, Z., Nakamoto, K., & Schultz, P. J. (2015). The effect of social support features and gamification on a Web-based intervention for rheumatoid arthritis patients: Randomized controlled trial. Journal of Medical Internet Research, 17, e14. https://doi.org/10.2196/jmir.3510Google Scholar
Appelbaum, L. G., & Erickson, G. (2018). Sports vision training: A review of the state-of-the-art in digital training techniques. International Review of Sport and Exercise Psychology, 11, 160189. https://doi.org/10.1080/1750984x.2016.1266376Google Scholar
Batterham, P. J., Neil, A. L., Bennett, K., Griffiths, K. M., & Christensen, H. (2008). Predictors of adherence among community users of a cognitive behavior therapy website. Patient Preference and Adherence, 2, 97105. www.dovepress.com/predictors-of-adherence-among-community-users-of-a-cognitive-behavior-peer-reviewed-article-PPAGoogle Scholar
Baumel, A., & Yom-Tov, E. (2018). Predicting user adherence to behavioral eHealth interventions in the real world: Examining which aspects of intervention design matter most. Translational Behavioral Medicine, 8, 793798. https://doi.org/10.1093/tbm/ibx037Google Scholar
Boyle, S. C., Earle, A. M., LaBrie, J. W., & Smith, D. J. (2017). PNF 2.0? Initial evidence that gamification can increase the efficacy of brief, web-based personalized normative feedback alcohol interventions. Addictive Behaviors, 67, 817. https://doi.org/10.1016/j.addbeh.2016.11.024Google Scholar
Brown, A., Rice, S. M., Rickwood, D. J., & Parker, A. G. (2016). Systematic review of barriers and facilitators to accessing and engaging with mental health care among at-risk young people. Asia-Pacific Psychiatry: Official Journal of the Pacific Rim College of Psychiatrists, 8, 322. https://doi.org/10.1111/appy.12199Google Scholar
Carlbring, P., Andersson, G., Cuijpers, P., Riper, H., & Hedman-Lagerlöf, E. (2018). Internet-based vs. face-to-face cognitive behavior therapy for psychiatric and somatic disorders: An updated systematic review and meta-analysis. Cognitive Behaviour Therapy, 47, 118. https://doi.org/10.1080/16506073.2017.1401115Google Scholar
Cho, V., Cheng, T. C. E., & Lai, W. M. (2009). The role of perceived user-interface design in continued usage intention of self-paced learning tools. Computers and Education, 53, 216227. https://doi.org/10.1016/j.comedu.2009.01.014Google Scholar
Clemenson, J., Rothman, M. J., Smoith, A. C., Caffery, L. J., & Danbjorg, D. B. (2017). Participatory design methods in telemedicine research. Journal of Telemedicine and Telecare, 23, 780785. https://doi.org/10.1177/1357633X16686747Google Scholar
Conserve, D. F., Jennings, L., Aguiar, C., Shin, G., Handler, L., & Maman, S. (2017). Systematic review of mobile health behavioral interventions to improve uptake of HIV testing for vulnerable and key populations. Journal of Telehealth and Telecare, 23, 347359. https://doi.org/10.1177/1357633X16639186Google Scholar
Council of Australian Governments. (2017). The Fifth National Mental Health and Suicide Plan. Canberra: Council of Australian Governments. www.coaghealthcouncil.gov.au/Portals/0/Fifth%20National%20Mental%20Health%20and%20Suicide%20Prevention%20Plan.pdfGoogle Scholar
Darvell, M., Kavanagh, D. J., & Connolly, J. (2015). A qualitative exploration of Internet-based treatment for comorbid depression and alcohol misuse. Internet Interventions, 2, 174182. https://doi.org/10.1016/j.invent.2015.03.003Google Scholar
Dear, B. F., Fogliati, V. J., Fogliati, R. et al. (2018). Treating anxiety and depression in young adults: A randomised controlled trial comparing clinician-guided versus self-guided Internet-delivered cognitive behavioural therapy. Australian and New Zealand Journal of Psychiatry, 52, 668679. https://doi.org/10.1177/0004867417738055Google Scholar
Deloitte. (2018). Behaviour Unlimited: Mobil Consumer Survey 2018: The Australian Cut. www2.deloitte.com/au/mobile-consumer-surveyGoogle Scholar
Domhardt, M., Geßlein, H., von Rezori, R., & Baumeister, H. (2018). Internet- and mobile-based interventions for anxiety disorders: A meta-analytic review of intervention components. Depression and Anxiety, 36, 213224. https://doi.org/10.1002/da.22860Google Scholar
Gulliver, A., Griffiths, K. M., & Christensen, H. (2010). Perceived barriers and facilitators to mental health help-seeking in young people: A systematic review. BMC Psychiatry, 10, 113. www.biomedcentral.com/1471-244X/10/113Google Scholar
Heber, E., Ebert, D. D., Lehr, D. et al. (2017). The benefit of web- and computer-based interventions for stress: A systematic review and meta-analysis. Journal of Medical Internet 19, e32. https://doi.org/10.2196/jmir.5774Google Scholar
Hennemann, S., Beutel, M. E., & Zwerenz, R. (2017). Ready for eHealth? Health professionals’ acceptance and adoption of eHealth interventions in inpatient routine care. Journal of Health Communication, 22, 274284. https://doi.org/10.1080/10810730.2017.1284286Google Scholar
Howarth, A., Quesada, J., Silva, J., Judycki, S., & Mills, P. (2018). The impact of digital health interventions on health-related outcomes in the workplace: A systematic review. Digital Health, 4, 118. https://doi.org/10.1177/2055207618770861Google Scholar
IQVIA Institute for Human Data Science. (2017). The Growing Value of Digital Health: Evidence and Impact on Human Health and the Healthcare System. www.iqvia.com/-/media/iqvia/pdfs/institute-reports/the-growing-value-of-digital-health.pdf?_=1547778440731Google Scholar
Jackson, C. B., Quetsch, L. B., Brabson, L. A., & Herschell, A. D. (2018). Web-based training methods for behavioral health providers: A systematic review. Administration and Policy in Mental Health and Mental Health Services Research, 45(4), 587610. https://doi.org/10.1007/s10488-018-0847-0Google Scholar
Kaker, T. B., Gustafson, D. H., & Shah, D. (2014). How can research keep up with eHealth? Ten strategies for increasing the timeliness and usefulness of eHealth research. Journal of Medical Internet Research, 16, e36. www.jmir.org/2014/2/e36Google Scholar
Kavanagh, D. J., Andrade, J., May, J., & Connor, J. P. (2014). Motivational interventions may have greater sustained impact if they trained imagery-based self-management. Addiction, 109, 10621063. https://doi.org/10.1111/add.12507Google Scholar
Kavanagh, D. J., Clark, D., Manicavasagar, V., Piatkowska, O. H., Rosen, A., & Tennant, C. (1993). Application of a cognitive-behavioural family intervention for schizophrenia in multi-disciplinary settings: What can the matter be? Australian Psychologist, 28, 181188. https://doi.org/10.1080/00050069308258899Google Scholar
Kavanagh, D. J., Sitharthan, T., Spilsbury, G., & Vignaendra, S. (1999). An evaluation of brief correspondence programs for problem drinkers. Behavior Therapy, 30, 641656. https://doi.org/10.1016/S0005-7894(99)80030-6Google Scholar
Kebede, M. M., Zeeb, H., Peters, M., Heise, T. L., & Pischke, C. R. (2018). Effectiveness of digital interventions for improving glycemic control in persons with poorly controlled type 2 diabetes: A systematic review, meta-analysis, and meta-regression analysis. Diabetes Technology and Therapeutics, 20, 767782. https://doi.org/10.1089/dia.2018.0216Google Scholar
Kelders, S. M., Sommers-Spijkerman, M., & Goldberg, J. (2018). Investigating the direct impact of a gamified versus nongamified well-being intervention: An exploratory experiment. Journal of Medical Internet Research, 20, e247. www.jmir.org/2018/7/e247Google Scholar
Kerridge, B. T., Mauro, P. M., Chou, S. P. et al. (2017). Predictors of treatment utilization and barriers to treatment utilization among individuals with lifetime cannabis use disorder in the United States. Drug and Alcohol Dependence, 181, 223228. https://doi.org/10.1016/j.drugalcdep.2017.09.032Google Scholar
Kiluk, B. D., Nich, C., Buck, M. B. et al. (2018). Randomized clinical trial of computerized and clinician-delivered CBT in comparison with standard outpatient treatment for substance use disorders: Primary within-treatment and follow-up outcomes. American Journal of Psychiatry, 175, 853863. https://doi.org/10.1176/appi.ajp.2018.17090978Google Scholar
Krebs, P., & Duncan, D. T. (2015). Health app use among US mobile phone owners: A national survey. JMIR mHealth and uHealth, 3, e101. https://doi.org/10.2196/mhealth.4924Google Scholar
Lintvedt, O. K., Griffiths, K. M., Eisemann, M., & Waterloo, K. (2013). Evaluating the translation process of an Internet-based self-help intervention for prevention of depression: A cost-effectiveness analysis. Journal of Medical Internet Research 15, e18. www.jmir.org/2013/1/e18Google Scholar
Marasinghe, R. B., Edirippulige, S., Kavanagh, D., Smith, A., & Jiffry, M. T. M. (2012). Effect of mobile phone-based psychotherapy in suicide prevention: A randomised controlled trial in Sri Lanka. Journal of Telemedicine and Telecare, 18, 151155. https://doi.org/10.1258/jtt.2012.SFT107Google Scholar
Neset, T. S., Opach, T., Lion, P., Lilja, A., & Johansson, J. (2016). Map-based web tools supporting climate change adaptation. Professional Geographer, 68, 103114. https://doi.org/10.1080/00330124.2015.1033670Google Scholar
Nesvåg, S., & McKay, J. R. (2018). Feasibility and effects of digital interventions to support people in recovery from substance use disorders: Systematic Review. Journal of Medical Internet Research, 20, e255. www.jmir.org/2018/8/e255Google Scholar
Parham, S., Kavanagh, D. J., Shimada, M., May, J., & Andrade, J. (2018). Qualitative analysis of feedback on Functional Imagery Training: A novel motivational intervention for type 2 diabetes. Psychology and Health, 33, 416429. https://doi.org/10.1080/08870446.2017.1360493Google Scholar
Park, E., & Kwon, M. (2018). Health-related Internet use by children and adolescents: Systematic review. Journal of Medical Internet Research, 20, e120. www.jmir.org/2018/4/e120/Google Scholar
Pew Research Center. (2018a). Internet use by age: Surveys conducted 2000–2018. www.pewinter.net.org/chart/internet-use-by-age/Google Scholar
Pew Research Center. (2018b). Mobile fact sheet: Other devices. www.pewinternet.org/fact-sheet/mobile/Google Scholar
Randall, G. E., Wakefield, P. A., & Richards, D. A. (2012). Fidelity to assertive community treatment program standards: A regional survey of adherence to standards. Community Mental Health Journal, 48, 138149. https://doi.org/10.1007/s10597-010-9353-xGoogle Scholar
Richard, C., Glaser, E., & Lussier, M. T. (2017). Communication and patient participation influencing patient recall of treatment discussions. International Journal of Public Participation in Health Care and Health Policy, 20, 760770. https://doi.org/10.1111/hex.12515Google Scholar
Robinson, N. L., Cottier, T. V., & Kavanagh, D. J. (2019). Psychosocial health interventions by social robots: Systematic review of randomized controlled trials. Journal of Medical Internet Research, 21, e13203. https://doi.org/10.2196/13203Google Scholar
SAMHSA (Substance Abuse and Mental Health Services Administration). (2018). Key Substance Use and Mental Health Indicators in the United States: Results from the 2017 National Survey on Drug Use and Health (HHS Publication No. SMA 18–5068, NSDUH Series H-53). Rockville, MD: SAMHSA. www.samhsa.gov/data/sites/default/files/cbhsq-reports/NSDUHFFR2017/NSDUHFFR2017.pdfGoogle Scholar
Sander, L., Rausch, L., & Baumeister, H. (2016). Effectiveness of internet-based interventions for the prevention of mental disorders: A systematic review and meta-analysis. JMIR Mental Health, 3, e38. www.jmir.org/2016/3/e38/Google Scholar
Schleibe, M., Reichelt, J., Bellman, M., & Kirch, W. (2015). Acceptance factors of mobile apps for diabetes by patients aged 50 or older: A qualitative study. Medicine 2.0, 4, e1. www.medicine20.com/2015/1/e1/Google Scholar
Schoeppe, S., Alley, S., Van Lippevelde, W. et al. (2016). Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour: A systematic review. The International Journal of Behavioral Nutrition and Physical Activity, 13, 127. https://doi.org/10.1186/s12966-016-0454-yGoogle Scholar
Sijbrandij, M., Kunovsk, I., & Cuijpers, P. (2016). Effectiveness of internet-delivered cognitive behavioral therapy for posttraumatic stress disorder: A systematic review and meta-analysis. Depression and Anxiety, 33, 783791. https://doi.org/10.1002/da.22533Google Scholar
Solbrig, L., Whalley, B., Kavanagh, D. J. et al. (2018). Functional imagery training versus motivational interviewing for weight loss: A randomised controlled trial of brief individual interventions for overweight and obesity. International Journal of Obesity, 43, 883894. https://doi.org/10.1038/s41366-018-0122-1Google Scholar
Stoyanov, S., Hides, L., Kavanagh, D. J., Tjondronegoro, D., Zelenko, O., & Mani, M. (2015). Mobile application rating scale (MARS). A new tool for assessing the quality of health-related mobile applications. JMIR mHealth and uHealth, 3, e27. https://mhealth.jmir.org/2015/1/e27/Google Scholar
Stoyanov, S., Hides, L., Kavanagh, D. J., & Wilson, H. (2016). Development and validation of the user version of the mobile application rating scale (uMARS). JMIR mHealth and uHealth, 4, e72. https://doi.org/10.2196/mhealth.5849Google Scholar
Sucala, M., Cuijpers, P., Muench, F. et al. (2017). Anxiety: There is an app for that. A systematic review of anxiety apps. Depression and Anxiety, 34, 518525. https://doi.org/10.1002/da.22654Google Scholar
Sztein, D., Koransky, C. E., Fegan, L., & Himelhoch, S. (2018). Efficacy of cognitive behavioural therapy delivered over the Internet for depressive symptoms: A systematic review and meta-analysis. Journal of Telemedicine and Telecare, 24, 527539. https://doi.org/10.1177/1357633X17717402Google Scholar
Titov, N., Dear, B., Nielssen, O. et al. (2018). ICBT in routine care: A descriptive analysis of successful clinics in five countries. Internet Interventions, 13, 108115. https://doi.org/10.1016/j.invent.2018.07.006Google Scholar
Titov, N., Dear, B., Staples, L. G. et al. (2017). The first 30 months of the MindSpot Clinic: Evaluation of a national e-mental health service against project objectives. Australian and New Zealand Journal of Psychiatry, 51, 12271239. https://doi.org/10.1177/0004867416671598Google Scholar
We Are Social, & Hootsuite. (2018). Digital in 2018: Global Overview. https://wearesocial.com/blog/2018/01/global-digital-report-2018Google Scholar
Whiteford, H. A., Buckingham, W. J., Harris, M. G. et al. (2014). Estimating treatment rates for mental disorders in Australia. Australian Health Review, 38, 8085. https://doi.org/10.1071/AH13142Google Scholar
Zachariae, R., Lyby, M. S., Ritterband, L. M., & O’Toole, M. S. (2016). Efficacy of internet-delivered cognitive-behavioral therapy for insomnia: A systematic review and meta-analysis of randomized controlled trials. Sleep Medicine Reviews, 30, 110. https://doi.org/10.1016/j.smrv.2015.10.004Google Scholar
Zeng, E. Y., Heffner, J. L., Copeland, W. K., Mull, K. E., & Bricker, J. B. (2016). Get with the program: Adherence to a smartphone app for smoking cessation. Addictive Behaviors, 63, 120124. https://doi.org/10.1016/j.addbeh.2016.07.007Google Scholar

References

Abraham, C., Kelly, M., West, R., & Michie, S. (2009). The UK National Institute for Health and Clinical Excellence public health guidance on behaviour change: A brief introduction. Psychology, Health and Medicine, 14, 18. https://doi.org/10.1080/13548500802537903Google Scholar
Acunzo, D., Escher, G., Ottersen, O. et al. (2018). Framing planetary health: Arguing for resource-centred science. The Lancet Planetary Health, 2, e101e102. https://doi.org/10.1016/S2542-5196(18)30023-8Google Scholar
Blue, S., Shove, E., Carmona, C., & Kelly, M. P. (2016). Theories of practice and public health: Understanding (un)healthy practices. Critical Public Health, 26, 3650. https://doi.org/10.1080/09581596.2014.980396Google Scholar
Bouton, M. E. (2014). Why behavior change is difficult to sustain. Preventive Medicine, 68, 2936. https://doi.org/10.1016/j.ypmed.2014.06.010Google Scholar
Bryant, A., & Charmaz, K. (Eds.). (2007). The SAGE Handbook of Grounded Theory. Thousand Oaks, CA: SAGE.Google Scholar
Carter, S. M., & Little, M. (2007). Justifying knowledge, justifying method, taking action: Epistemologies, methodologies, and methods in qualitative research. Qualitative Health Research, 17, 13161328. https://doi.org/10.1177/1049732307306927Google Scholar
Chamberlain, K. (2014). Epistemology and qualitative research. In Rohleder, P. & Lyons, A. (Eds.), Qualitative Research in Clinical and Health Psychology (pp. 928). Basingstoke: Palgrave Macmillan.Google Scholar
Chevalier, J., & Buckles, D. (2013). Participatory Action Research: Theory and Methods for Engaged Inquiry. New York: Routledge.Google Scholar
Christakis, N., & Fowler, J. (2008). The collective dynamics of smoking in a large social network. New England Journal of Medicine, 358, 22492258. https://doi.org/10.1056/NEJMsa0706154Google Scholar
Clandinin, D. (2013). Engaging in Narrative Inquiry. New York: Routledge.Google Scholar
Crossley, M. (2000). Rethinking Health Psychology. Buckingham: Open University Press.Google Scholar
Davis, R., Campbell, R., Hildon, Z., Hobbs, L., & Michie, S. (2015). Theories of behaviour and behaviour change across the social and behavioural sciences: A scoping review. Health Psychology Review, 9, 323344. https://doi.org/10.1080/17437199.2014.941722Google Scholar
Dohan, D., Garrett, S. B., Rendle, K. A., Halley, M., & Abramson, C. (2016). The importance of integrating narrative into health care decision making. Health Affairs, 35, 720725. https://doi.org/10.1377/hlthaff.2015.1373Google Scholar
Evans, D., Welch, D., & Swaffield, J. (2017). Constructing and mobilizing the “consumer”: Responsibility, consumption and the politics of sustainability. Environment and Planning A, 49, 13961412. https://doi.org/10.1177/0308518X17694030Google Scholar
French, S., Green, S., O’Connor, D. et al. (2012). Developing theory-informed behavior change interventions to implement evidence into practice: A systematic approach using the Theoretical Domains Framework. Implementation Science, 7, 38. https://doi.org/10.1186/1748-5908-7-38Google Scholar
Gergen, K. J. (2019). Qualitative psychology and the new pluralism. In Schiff, B. (Ed.), Situating Qualitative Methods in Psychological Science (pp. 6171). New York: Routledge.Google Scholar
Gergen, K. J., Josselson, R., & Freeman, M. (2015). The promises of qualitative inquiry. American Psychologist, 70, 19. https://doi.org/10.1037/a0038597Google Scholar
Giddens, A. (1984). The Constitution of Society: Outline of the Structuration Theory. Cambridge: Polity.Google Scholar
Greenhalgh, T., Annandale, E., Ashcroft, R. et al. (2016). An open letter to The BMJ editors on qualitative research. BMJ, 352, i563. https://doi.org/10.1136/bmj.i563Google Scholar
Hagger, M., & Chatzisarantis, N. (2011). Never the twain shall meet? Quantitative psychological researchers’ perspectives on qualitative research. Qualitative Research in Sport, Exercise and Health, 3, 266277. https://doi.org/10.1080/2159676X.2011.607185Google Scholar
Hargreaves, T. (2011). Practice-ing behaviour change: Applying social practice theory to pro-environmental behaviour change. Journal of Consumer Culture, 11, 7999. https://doi.org/10.1177/1469540510390500Google Scholar
Hilton, C. E., & Johnston, L. H. (2017). Health psychology: It’s not what you do, it’s the way that you do it. Health Psychology Open, 4. https://doi.org/10.1177/2055102917714910Google Scholar
Holman, D., & Borgstrom, E. (2016). Applying social theory to understand health-related behaviours. Medical Humanities, 42(2), 143145. https://doi.org/10.1136/medhum-2015-010688Google Scholar
Holman, D., Lynch, R., & Reeves, A. (2017). How do health behaviour interventions take account of social context? A literature trend and co-citation analysis. Health, 22, 389410. https://doi.org/10.1177/1363459317695630Google Scholar
Johnston, M., Johnston, D., Wood, C. E., Hardeman, W., Francis, J., & Michie, S. (2018). Communication of behaviour change interventions: Can they be recognised from written descriptions? Psychology and Health, 33, 713723. https://doi.org/10.1080/08870446.2017.1385784Google Scholar
Kaza, S., Yao, L. C., Bhada-Tata, P., & Van Woerden, F. (2018). What a Waste 2.0: A Global Snapshot of Solid Waste Management to 2050. Washington, DC: World Bank. https://openknowledge.worldbank.org/handle/10986/30317Google Scholar
Keane, H., Weier, M., Fraser, D., & Gartner, C. (2017). “Anytime, anywhere”: Vaping as social practice. Critical Public Health, 27, 465476. https://doi.org/10.1080/09581596.2016.1250867Google Scholar
Kelly, M., & Barker, M. (2016). Why is changing health-related behaviour so difficult? Public Health, 136, 109116. https://doi.org/10.1016/j.puhe.2016.03.030Google Scholar
Kidd, S. (2002). The role of qualitative research in psychological journals. Psychological Methods, 7, 126138. https://doi.org/10.1037/1082-989X.7.1.126Google Scholar
Kippax, S. (2018). A journey to HIV prevention research: From social psychology to social health via multidisciplinarity. Journal of Health Psychology, 23, 442456. https://doi.org/10.1177/1359105317707529Google Scholar
Kippax, S., & Race, K. (2003). Sustaining safe practice: Twenty years on. Social Science and Medicine, 57, 112. https://doi.org/10.1016/S0277-9536(02)00303-9Google Scholar
Kok, G., Gottlieb, N., Peters, G.-J. et al. (2016). A taxonomy of behaviour change methods: An intervention mapping approach. Health Psychology Review, 10, 297312. https://doi.org/10.1080/17437199.2015.1077155Google Scholar
Lally, P., Wardle, J., & Gardner, B. (2011). Experiences of habit formation: A qualitative study. Psychology, Health and Medicine, 16, 484489. https://doi.org/10.1080/13548506.2011.555774Google Scholar
Laurier, E., McKie, L., & Goodwin, N. (2000). Daily and lifecourse contexts of smoking. Sociology of Health and Illness, 22, 289309. https://doi.org/10.1111/1467-9566.00205Google Scholar
Levitt, H. M., Bamberg, M., Creswell, J. W., Frost, D. M., Josselson, R., & Suárez-Orozco, C. (2018). Journal article reporting standards for qualitative primary, qualitative meta-analytic, and mixed methods research in psychology: The APA Publications and Communications Board task force report. American Psychologist, 73, 26. https://doi.org/10.1037/amp0000151Google Scholar
Lyons, A. C. (2011). Advancing and extending qualitative research in health psychology. Health Psychology Review, 5, 18. https://doi.org/10.1080/17437199.2010.544638Google Scholar
Lyons, A. C., & Chamberlain, K. (2017). Critical health psychology. In Gough, B., (Ed.), Palgrave Handbook of Critical Social Psychology (pp. 533555). London: Palgrave Macmillan. https://doi.org/10.1057/978-1-137-51018-1_26Google Scholar
Madison, D. S. (2019). Critical Ethnography: Method, Ethics, and Performance. London: SAGE.Google Scholar
Majid, U., & Vanstone, M. (2018). Appraising qualitative research for evidence syntheses: A compendium of quality appraisal tools. Qualitative Health Research, 28, 21152131. https://doi.org/10.1177/1049732318785358Google Scholar
Malterud, K. (2019). The impact of evidence-based medicine on qualitative metasynthesis: Benefits to be harvested and warnings to be given. Qualitative Health Research, 29, 717. https://doi.org/10.1177/1049732318795864Google Scholar
Marini, M. G. (2015). Narrative Medicine: Bridging the Gap Between Evidence-Based Care and Medical Humanities. Cham: Springer International.Google Scholar
Marks, D. F. (2013). Health psychology: Overview. In Nezu, A., Nezu, C., & Geller, P. (Eds.), Handbook of Psychology, Vol. 9: Health Psychology (2nd ed.). Hoboken, NJ: Wiley.Google Scholar
Meier, P., Warde, A., & Holmes, J. (2018). All drinking is not equal: How a social practice theory lens could enhance public health research on alcohol and other health behaviours. Addiction, 113, 206213. https://doi.org/10.1111/add.13895Google Scholar
Michie, S., Richardson, M., Johnston, M. et al. (2013). The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: Building an international consensus for the reporting of behavior change interventions. Annals of Behavioral Medicine, 46, 8195. https://doi.org/10.1007/s12160-013-9486-6Google Scholar
Michie, S., & Wood, C. (2015). Health behaviour change techniques. In Conner, M. & Norman, P. (Eds.), Predicting and Changing Health Behaviour: Research and Practice With Social Cognition Models (pp. 358389). New York: McGraw Hill.Google Scholar
Mielewczyk, F., & Willig, C. (2007). Old clothes and an older look: The case for a radical makeover in health behaviour research. Theory and Psychology, 17, 811837. https://doi.org/10.1177/0959354307083496Google Scholar
Murray, M., & Chamberlain, K. (2014). Health psychology. In Teo, T. (Ed.), Encyclopaedia of Critical Psychology (pp. 844850). New York: Springer. https://doi.org/10.1007/978-1-4614-5583-7_132Google Scholar
Nair, C. (2018). The Sustainable State: The Future of Government, Economy, and Society. Oakland, CA: Berrett-Koehler Publishers.Google Scholar
NICE (National Institute for Health and Care Excellence). (2007). Behaviour Change: General Approaches. (Public health guideline [PH6]). London: NICE.Google Scholar
NICE (National Institute for Health and Care Excellence). (2014). Behaviour Change: Individual Approaches. (Public health guideline [PH49]). London: NICE.Google Scholar
Norris, E., Finnerty, A. N., Hastings, J., Stokes, G., & Michie, S. (2018). Identifying and evaluating ontologies related to human behaviour change interventions: A scoping review. PsyArXiv. https://doi.org/10.31234/osf.io/y7dusGoogle Scholar
Noyes, J., Booth, A., Cargo, M. et al. (2018). Cochrane Qualitative and Implementation Methods Group guidance series – paper 1: Introduction. Journal of Clinical Epidemiology, 97, 3538. https://doi.org/10.1016/j.jclinepi.2017.09.025Google Scholar
Ogden, J. (2016). Celebrating variability and a call to limit systematization: The example of the behaviour change technique taxonomy and the behaviour change wheel. Health Psychology Review, 10, 245250. https://doi.org/10.1080/17437199.2016.1190291Google Scholar
Penn, L., Moffatt, S. M., & White, M. (2008). Participants’ perspective on maintaining behaviour change: A qualitative study within the European Diabetes Prevention Study. BMC Public Health, 8, 235. https://doi.org/10.1186/1471-2458-8-235Google Scholar
Sheeran, P., Klein, W., & Rothman, A. (2017). Health behavior change: Moving from observation to intervention. Annual Review of Psychology, 68, 573600. https://doi.org/10.1146/annurev-psych-010416-044007Google Scholar
Shove, E., Pantzar, M., & Watson, M. (2012). The Dynamics of Social Practice: Everyday Life and How It Changes. London: SAGE. https://doi.org/10.4135/9781446250655.n1Google Scholar
Shove, E., & Warde, A. (2002). Inconspicuous consumption: The sociology of consumption, lifestyles and the environment. In Dunlap, R., Buttel, F., Dickens, P., & Giswijt, A. (Eds.), Sociological Theory and the Environment: Classical Foundations, Contemporary Insights (pp. 230250). London: Rowman & Littlefield.Google Scholar
Sniehotta, F., Presseau, J., & Araujo-Soares, V. (2014). Time to retire the theory of planned behaviour. Health Psychology Review, 8, 17. https://doi.org/10.1080/17437199.2013.869710Google Scholar
Stautz, K., Zupan, Z., Field, M., & Marteau, T. (2018). Does self-control modify the impact of interventions to change alcohol, tobacco, and food consumption? A systematic review. Health Psychology Review, 12, 157178. https://doi.org/10.1080/17437199.2017.1421477Google Scholar
Tombor, I., & Michie, S. (2017). Methods of health behavior change. In Braddick, O. (Ed.), Oxford Research Encyclopedia of Psychology. New York: Oxford University Press. https://doi.org/10.1093/acrefore/9780190236557.013.125Google Scholar
Twine, R. (2018). Materially constituting a sustainable food transition: The case of vegan eating practice. Sociology, 52, 166181. https://doi.org/10.1177/0038038517726647Google Scholar
Van Manen, M. (2016). Phenomenology of Practice: Meaning-Giving Methods in Phenomenological Research and Writing. New York: Routledge.Google Scholar
Wodak, R., & Meyer, M. (Eds.). (2016). Methods of Critical Discourse Studies (3rd ed.). London: SAGE.Google Scholar

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