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24 - Engagement of Stakeholders in the Design, Evaluation, and Implementation of Complex Interventions

from 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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Summary

Research on complex behavior change interventions has largely focused on intervention development and testing their effects in feasibility trials, pilot studies, and randomized controlled trials. However, a significant gap exists in translating behavior interventions informed by theory into real-world practice. This chapter describes how engaging stakeholders can improve the likelihood that effective behavior change interventions are put into practice. The chapter begins with an overview of implementation science and normalization process theory – which outlines how effective interventions are routinely implemented. The roles of stakeholders as research partners and research participants are differentiated using research in health contexts. For example, the process of stakeholder involvement is illustrated using digital health interventions for people with long-term physical health conditions with reference to UK Medical Research Council guidelines on complex interventions. The examples illustrate (1) how stakeholder support in the co-design of complex interventions can improve their utility, usability, accessibility, and acceptability and (2) how stakeholder perspectives elicited using mixed methods during the feasibility and pilot phases of intervention development can help inform subsequent stages of intervention development. Finally, the evaluation and implementation phase is explored, using a case study to illustrate the need to engage with additional stakeholders to translate effective interventions into routine practice.

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Publisher: Cambridge University Press
Print publication year: 2020

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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/S0034-8910.2014048004799CrossRefGoogle ScholarPubMed
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.2013.07.007CrossRefGoogle ScholarPubMed
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.a1655CrossRefGoogle ScholarPubMed
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-2017-015860CrossRefGoogle ScholarPubMed
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)11423-4CrossRefGoogle 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/10.1186/1748-5908-1-1CrossRefGoogle 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.12168CrossRefGoogle ScholarPubMed
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-2016-011286CrossRefGoogle ScholarPubMed
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/10.1186/1748-5908-4-29CrossRefGoogle ScholarPubMed
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/10.1177/0017896919853856CrossRefGoogle 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/hea0000785CrossRefGoogle 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.2672CrossRefGoogle ScholarPubMed
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

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