PDF herunterladen
Open Access
CC BY 4.0 · Yearb Med Inform 2024; 33(01): 052-057
DOI: 10.1055/s-0044-1800718
Special Section: Digital Health for Precision in Prevention
Working Group Contributions

Precision Prevention through Social Media: Report of Four Cases

Authors

  • Elia Gabarron

    1   Department of Education, ICT and Learning, Østfold University College, Halden, Norway
    2   Norwegian Centre for E-health Research, University Hospital of North Norway, Tromsø, Norway

  • Guillermo Lopez-Campos

    3   Queen's University Belfast, Belfast, United Kingdom

  • Shauna Davies

    4   Faculty of Nursing, University of Regina, Canada

  • Taridzo Chomutare

    2   Norwegian Centre for E-health Research, University Hospital of North Norway, Tromsø, Norway
    5   Department of Computer Science, Faculty of Science and Technology, UiT The Arctic University of Norway, Tromsø, Norway

  • Iris Thiele Isip Tan

    6   Medical Informatics Unit, College of Medicine, University of the Philippines Manila, Philippines

  • Carolyn Petersen

    7   Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, Minnesota, United States
Weitere Informationen
Auch verfügbar auf
  Lizenzen und Reprints
Preview

Summary

Background: Precision prevention involves using biological, behavioral, socioeconomic, and epidemiological data to improve health for a particular individual or group. With almost 63% of the global population using social media, these platforms show promise to deliver tailored messaging and personalized interventions to individuals.

Objectives: To describe the personalization elements and behavior components used in a sample of precision prevention interventions delivered through social media.

Methods: To identify examples of cases, a search was done on clinicaltrials.gov, searching for ‘other terms: prevention’ + ‘Intervention/Treatment: social media intervention’ + ‘study results: With results. The selected cases were described, personalization elements reported, and their adopted intervention components were coded according to the Behavior Change Wheel (BCW) framework.

Results: A total of four cases employing personalization in their interventions were identified. Three of these cases targeted women's health. The intervention period varied from two to eight months, with participant commitment ranging from active involvement on five out of seven days to monthly participation. The BCW interventions of persuasion and incentivization, were most frequently utilized, while education and coercion were used sparingly in the selected cases. Notably, none of the four cases reported the use of training, restrictions, or modeling.

Conclusions: Social media has the potential to serve as a tool for digital phenotyping and contribute to the advancement of precision prevention. Challenges include the social media platform set-up and ensuring all ethical considerations are met.

Keywords

Social media - Prevention - Precision medicine - Internet-based intervention


Publikationsverlauf

Artikel online veröffentlicht:
08. April 2025

© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Statista. Number of social media users worldwide from 2017 to 2027 2023. Available from: https://www.statista.com/statistics/278414/number-of-worldwide-social-network-users/
    PubMed
  • 2 Chen J, Wang Y. Social Media Use for Health Purposes: Systematic Review. J Med Internet Res. 2021 May 12;23(5):e17917.
    PubMed
  • 3 Ghahramani A, de Courten M, Prokofieva M. “The potential of social media in health promotion beyond creating awareness: an integrative review”. BMC Public Health. 2022 Dec 21;22(1):2402.
    PubMed
  • 4 Syed-Abdul S, Gabarron E, Lau AYS. Participatory Health Through Social Media. 2016.
    PubMed
  • 5 Alfian R, Athiyah U, Nita Y. Social media health interventions to improve diabetes mellitus patient outcome: a systematic review. J Basic Clin Physiol Pharmacol. 2021 Jun 25;32(4):297-304.
    PubMed
  • 6 Gabarron E, Reichenpfader D, Denecke K. Exploring the evolution of social media in mental health interventions: A mapping review. Yearbook of Medical Informatics. 2023:In press.
    PubMed
  • 7 Gabarron E, Skafle I, Nordahl-Hansen A, et al. Social media interventions for autistic individuals: Systematic review. Front Psychiatry. 2023;14:1089452.
    PubMed
  • 8 Li L, Wood CE, Kostkova P. Vaccine hesitancy and behavior change theory-based social media interventions: a systematic review. Transl Behav Med. 2022 Feb 16;12(2):243-272.
    PubMed
  • 9 Petkovic J, Duench S, Trawin J, et al. Behavioural interventions delivered through interactive social media for health behaviour change, health outcomes, and health equity in the adult population. Cochrane Database Syst Rev. 2021 May 31;5(5):Cd012932.
    PubMed
  • 10 Seiler J, Libby TE, Jackson E, et al. Social Media-Based Interventions for Health Behavior Change in Low- and Middle-Income Countries: Systematic Review. J Med Internet Res. 2022 Apr 14;24(4):e31889.
    PubMed
  • 11 Shaw JM, Mitchell CA, Welch AJ, et al. Social media used as a health intervention in adolescent health: A systematic review of the literature. Digit Health. 2015 Jan-Dec;1:2055207615588395.
    PubMed
  • 12 Simeon R, Dewidar O, Trawin J, et al. Behavior Change Techniques Included in Reports of Social Media Interventions for Promoting Health Behaviors in Adults: Content Analysis Within a Systematic Review. J Med Internet Res. 2020 Jun 11;22(6):e16002.
    PubMed
  • 13 McGrath C, Palmarella G, Solomon S, et al. Precision prevention and public health 2017. Available from: https://repository.upenn.edu/entities/publication/9ce0f712-f4ca-4e5d-916d-c2e70cb0a568
    PubMed
  • 14 Bíró K, Dombrádi V, Jani A, et al. Creating a common language: defining individualized, personalized and precision prevention in public health. J Public Health (Oxf). 2018 Dec 1;40(4):e552-e559.
    PubMed
  • 15 Ramos KS, Bowers EC, Tavera-Garcia MA, et al. Precision prevention: A focused response to shifting paradigms in healthcare. Exp Biol Med (Maywood). 2019 Mar;244(3):207-212.
    PubMed
  • 16 Michie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. 2011 Apr 23;6:42.
    PubMed
  • 17 Bonar E. A Social Media Intervention for Risky Drinking 2021. Available from: https://www.clinicaltrials.gov/study/NCT04721925
    PubMed
  • 18 Boyle SC. A Gamified, Social Media Inspired Personalized Normative Feedback Alcohol Intervention for Sexual Minority Women 2019. Available from: https://clinicaltrials.gov/study/NCT03884478
    PubMed
  • 19 Chou C-C. Walking Exercise on Memory, Subjective Cognitive Complaint, and Brain-derived Neurotrophic Factor for Hypertension 2021. Available from: https://www.clinicaltrials.gov/study/NCT04930263
    PubMed
  • 20 Waring ME. The Healthy Moms Study: Comparison of a Post-Partum Weight Loss Intervention Delivered Via Facebook or In-Person Groups 2018. Available from: https://www.clinicaltrials.gov/study/NCT03700736
    PubMed
  • 21 Boyle SC, LaBrie JW. A Gamified, Social Media-Inspired, Web-Based Personalized Normative Feedback Alcohol Intervention for Lesbian, Bisexual, and Queer-Identified Women: Protocol for a Hybrid Trial. JMIR Res Protoc. 2021 Apr 16;10(4):e24647.
    PubMed
  • 22 Boyle SC, LaBrie JW, Trager BM, et al. A Gamified Personalized Normative Feedback App to Reduce Drinking Among Sexual Minority Women: Randomized Controlled Trial and Feasibility Study. J Med Internet Res. 2022 May 13;24(5):e34853.
    PubMed
  • 23 Waring ME, Libby BA, Moore Simas TA, et al. Delivering a Post-Partum Weight Loss Intervention via Facebook or In-Person Groups: Protocol for a Randomized Feasibility Pilot Trial. JMIR Res Protoc. 2019 Nov 28;8(11):e15530.
    PubMed
  • 24 Waring ME, Pagoto SL, Moore Simas TA, et al. Delivering a Postpartum Weight Loss Intervention via Facebook or In-Person Groups: Results From a Randomized Pilot Feasibility Trial. JMIR Mhealth Uhealth. 2023 Apr 27;11:e41545.
    PubMed
  • 25 Chou CC, Chien LY, Lin MF, et al. Effects of Aerobic Walking on Memory, Subjective Cognitive Complaints, and Brain-Derived Neurotrophic Factor Among Older Hypertensive Women. Biol Res Nurs. 2022 Oct;24(4):484-492.
    PubMed
  • 26 Alhasani M, Mulchandani D, Oyebode O, et al. A Systematic and Comparative Review of Behavior Change Strategies in Stress Management Apps: Opportunities for Improvement. Front Public Health. 2022;10:777567.
    PubMed
  • 27 Hare AJ, Patel MS, Volpp K, et al. The Role of Behavioral Economics in Improving Cardiovascular Health Behaviors and Outcomes. Curr Cardiol Rep. 2021 Oct 1;23(11):153.
    PubMed
  • 28 Stonerock GL, Blumenthal JA. Role of Counseling to Promote Adherence in Healthy Lifestyle Medicine: Strategies to Improve Exercise Adherence and Enhance Physical Activity. Prog Cardiovasc Dis. 2017 Mar-Apr;59(5):455-462.
    PubMed
  • 29 Tooley EM, Kolahi A. Motivating Behavioral Change. Med Clin North Am. 2022 Jul;106(4):627-639.
    PubMed
  • 30 Dunn AG, Mandl KD, Coiera E. Social media interventions for precision public health: promises and risks. NPJ Digit Med. 2018;1.
    PubMed
  • 31 Campbell CI, Chen CH, Adams SR, et al. Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder. J Med Internet Res. 2023 Jun 13;25:e45556.
    PubMed
  • 32 Montag C, Quintana DS. Digital phenotyping in molecular psychiatry-a missed opportunity? Mol Psychiatry. 2023 Jan;28(1):6-9.
    PubMed
  • 33 Tanner AR, Di Cara NH, Maggio V, et al. Epicosm-a framework for linking online social media in epidemiological cohorts. Int J Epidemiol. 2023 Jun 6;52(3):952-957.
    PubMed