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A Social Marketing Intervention to Improve Treatment Adherence in Patients with Type 1 Diabetes

Author

Listed:
  • Citlali Calderon

    (Tecnologico de Monterrey, Business School, Toluca, Estado de Mexico 50110, Mexico)

  • Lorena Carrete

    (Tecnologico de Monterrey, Business School, Toluca, Estado de Mexico 50110, Mexico)

  • Jorge Vera-Martínez

    (Tecnologico de Monterrey, Business School, Tlalpan, Ciudad de Mexico 14380, Mexico)

  • María Esther Gloria-Quintero

    (Endocrinología Pediátrica HGR 251, IMSS, Metepec, Estado de Mexico 52148, Mexico)

  • María del Socorro Romero-Figueroa

    (Centro de Investigación en Ciencias de la Salud, FSC, Universidad Anáhuac Campus Norte, Naucalpan de Juárez 52786, Mexico)

Abstract

This research explores if a social marketing intervention model based on social representations theory and the health belief model can generate changes regarding treatment adherence and improve patient self-efficacy. As a pilot, a test–retest field quasi-experiment was designed to evaluate the intervention model with type 1 diabetes (T1DM) patients of families with 8- to 17-year-old children. The intervention model was designed to clarify misconceptions, increase awareness of the benefits of following doctors’ treatments and improve patients’ self-efficacy. In-depth interviews were carried out to gain a richer understanding of the intervention’s effect. The pilot intervention generated a favourable change in shared misconceptions, individual health beliefs, glycaemic control and declared treatment adherence. This paper contributes to the social marketing literature and public health by providing early support for the theoretical assumptions regarding the role of shared misconceptions in physiological and behavioural outcomes for patients with T1DM. Contrary to previous studies, instead of only focusing on individual beliefs, this study incorporates shared beliefs between patients and caregivers, generating more comprehensive behavioural change.

Suggested Citation

  • Citlali Calderon & Lorena Carrete & Jorge Vera-Martínez & María Esther Gloria-Quintero & María del Socorro Romero-Figueroa, 2021. "A Social Marketing Intervention to Improve Treatment Adherence in Patients with Type 1 Diabetes," IJERPH, MDPI, vol. 18(7), pages 1-14, March.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:7:p:3622-:d:527373
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    References listed on IDEAS

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    1. Horowitz, Carol R. & Rein, Stephanie B. & Leventhal, Howard, 2004. "A story of maladies, misconceptions and mishaps: effective management of heart failure," Social Science & Medicine, Elsevier, vol. 58(3), pages 631-643, February.
    2. Hisashi Tanizaki, 1997. "Power comparison of non-parametric tests: Small-sample properties from Monte Carlo experiments," Journal of Applied Statistics, Taylor & Francis Journals, vol. 24(5), pages 603-632.
    3. Dominic Ehrmann & Nikola Bergis-Jurgan & Thomas Haak & Bernhard Kulzer & Norbert Hermanns, 2016. "Comparison of the Efficacy of a Diabetes Education Programme for Type 1 Diabetes (PRIMAS) in a Randomised Controlled Trial Setting and the Effectiveness in a Routine Care Setting: Results of a Compara," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-12, January.
    4. Quinn McNemar, 1947. "Note on the sampling error of the difference between correlated proportions or percentages," Psychometrika, Springer;The Psychometric Society, vol. 12(2), pages 153-157, June.
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