Who Follows eHealth Interventions as Recommended? A Study of Participants' Personal Characteristics From the Experimental Arm of a Randomized Controlled Trial
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BACKGROUND: Computer-tailored eHealth interventions to improve health behavior have been demonstrated to be effective and cost-effective if they are used as recommended. However, different subgroups may use the Internet differently, which might also affect intervention use and effectiveness. To date, there is little research available depicting whether adherence to intervention recommendations differs according to personal characteristics. OBJECTIVE: The aim was to assess which personal characteristics are associated with using an eHealth intervention as recommended. METHODS: A randomized controlled trial was conducted among a sample of the adult Dutch population (N=1638) testing an intervention aimed at improving 5 healthy lifestyle behaviors: increasing fruit and vegetable consumption, increasing physical activity, reducing alcohol intake, and promoting smoking cessation. Participants were asked to participate in those specific online modules for which they did not meet the national guideline(s) for the respective behavior(s). Participants who started with fewer than the recommended number of modules of the intervention were defined as users who did not follow the intervention recommendation. RESULTS: The fewer modules recommended to participants, the better participants adhered to the intervention modules. Following the intervention recommendation increased when participants were older (χ(2)1=39.8, P<.001), female (χ(2)1=15.8, P<.001), unemployed (χ(2)1=7.9, P=.003), ill (χ(2)1=4.5, P=.02), or in a relationship (χ(2)1=7.8, P=.003). No significant relevant differences were found between groups with different levels of education, incomes, or quality of life. CONCLUSION: Our findings indicate that eHealth interventions were used differently by subgroups. The more frequent as-recommended intervention use by unemployed, older, and ill participants may be an indication that these eHealth interventions are attractive to people with a greater need for health care information. Further research is necessary to make intervention use more attractive for people with unhealthy lifestyle patterns.
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Women have been found to be more likely to use eHealth interventions as recommended.
“Women have been found to be more likely to use eHealth interventions as recommended,27”
The intended use or therapeutic dose can be justified using existing guidelines for healthy living and medication use or using previous research regarding other technologies.
“the intended use or the “therapeutic dose” can be justified just as well using existing guidelines for healthy living and medication use [74,77] or using previous research regarding other technologies [75,76].”
From Clarifying the Concept of Adherence to eHealth Technology: Systematic Review on When Usage Becomes Adherence (2017) · cites this paper as [74]
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“Women have been found to be more likely to use eHealth interventions as recommended, 27 which could explain an increased benefit from the intervention; however, the difference could also be a spurious finding due to multiple testing as the pre-planned treatment by sex interaction was not…”
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Learning to be Proficient? A Structural Model of User Dynamic Engagement in eHealth InterventionsPreprint
Zhou, T., Wang, Y., Yan, L., & Tan, Y. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4066017 · Cited by 1 · see citing works
Changing lifestyle behaviors with personalized feedback delivered via the Internet
Marsaux, C. F. M. (2016) · Research Publications (Maastricht University) · doi:10.26481/dis.20160420cm
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- Authors
- Reinwand, D. A., Schulz, D. N., Crutzen, R., Kremers, S. P., & de Vries, H.
- Affiliations
- Constructor University (DE)
- Maastricht University (NL)
- Corresponding author
- Reinwand, Dominique A
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2015-05-11
- Volume
- 17
- Issue
- 5
- Pages
- e115
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC4468602
- OpenAlex
- W1543120279
- Cited by
- 62
- References
- 97
- Citations by year
- 2026: 1 · 2025: 6 · 2024: 3 · 2023: 3 · 2022: 9 · 2021: 6 · 2020: 7 · 2019: 4 · 2018: 3 · 2017: 9 · 2016: 11
- FWCI
- 13.98
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Keywords
- digital health interventions, intervention adherence, computer-tailored intervention, healthy lifestyle behaviors, fruit and vegetable intake, physical activity, alcohol consumption, smoking cessation, personal characteristics, unemployed people, older adults
- MeSH terms
- Adult, Age Factors, Alcohol Drinking, Cost-Benefit Analysis, Female, Fruit, Humans, Life Style, Male, Middle Aged, Motor Activity, Patient Compliance, Prospective Studies, Quality of Life, Sex Factors, Unemployment, Vegetables, Cohort Studies, Health Behavior, Logistic Models, Randomized Controlled Trials as Topic, Smoking Cessation, Telemedicine, Marital Status, Internet, Risk Reduction Behavior
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