Effectiveness of a Web-based Intervention Aimed at Healthy Dietary and Physical Activity Behavior: A Randomized Controlled Trial About Users and Usage
Open accessAbstract
BACKGROUND: Recent studies have shown the potential of Web-based interventions for changing dietary and physical activity (PA) behavior. However, the pathways of these changes are not clear. In addition, nonusage poses a threat to these interventions. Little is known of characteristics of participants that predict usage. OBJECTIVE: In this study we investigated the users and effect of the Healthy Weight Assistant (HWA), a Web-based intervention aimed at healthy dietary and PA behavior. We investigated the value of a proposed framework (including social and economic factors, condition-related factors, patient-related factors, reasons for use, and satisfaction) to predict which participants are users and which participants are nonusers. Additionally, we investigated the effectiveness of the HWA on the primary outcomes, self-reported dietary and physical activity behavior. METHODS: Our design was a two-armed randomized controlled trial that compared the HWA with a waiting list control condition. A total of 150 participants were allocated to the waiting list group, and 147 participants were allocated to the intervention group. Online questionnaires were filled out before the intervention period started and after the intervention period of 12 weeks. After the intervention period, respondents in the waiting list group could use the intervention. Objective usage data was obtained from the application itself. RESULTS: In the intervention group, 64% (81/147) of respondents used the HWA at least once and were categorized as "users." Of these, 49% (40/81) used the application only once. Increased age and not having a chronic condition increased the odds of having used the HWA (age: beta = 0.04, P = .02; chronic condition: beta = 2.24, P = .003). Within the intervention group, users scored better on dietary behavior and on knowledge about healthy behavior than nonusers (self-reported diet: χ²₂ = 8.4, P = .02; knowledge: F₁,₁₂₅ = 4.194, P = .04). Furthermore, users underestimated their behavior more often than nonusers, and nonusers overestimated their behavior more often than users (insight into dietary behavior: χ²₂ = 8.2, P = .02). Intention-to-treat analyses showed no meaningful significant effects of the intervention. Exploratory analyses of differences between pretest and posttest scores of users, nonusers, and the control group showed that on dietary behavior only the nonusers significantly improved (effect size r = -.23, P = .03), while on physical activity behavior only the users significantly improved (effect size r = -.17, P = .03). CONCLUSIONS: Respondents did not use the application as intended. From the proposed framework, a social and economic factor (age) and a condition-related factor (chronic condition) predicted usage. Moreover, users were healthier and more knowledgeable about healthy behavior than nonusers. We found no apparent effects of the intervention, although exploratory analyses showed that choosing to use or not to use the intervention led to different outcomes. Combined with the differences between groups at baseline, this seems to imply that these groups are truly different and should be treated as separate entities. TRIAL REGISTRATION: Trial ID number: ISRCTN42687923; http://www.controlled-trials.com/ISRCTN42687923/ (Archived by WebCite at http://www.webcitation.org/5xnGmvQ9Y).
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Adherence to the Healthy Weight Assistant was as low as 3%.
“Moreover, adherence to this intervention was as low as 3%”
From How to increase reach and adherence of web-based interventions: a design research viewpoint (2015) · cites this paper as [15]
Current Web-based interventions often reach higher-educated women.
“However, several researchers have shown that current Web-based interventions often reach higher-educated women, as seen in several studies [13-17]”
From How to increase reach and adherence of web-based interventions: a design research viewpoint (2015) · cites this paper as [15]
In the Healthy Weight Assistant, users were mainly female and highly educated.
“However, users were mainly female and highly educated [15].”
From How to increase reach and adherence of web-based interventions: a design research viewpoint (2015) · cites this paper as [15]
Most Web-based interventions reach a limited group only, while aiming for a broad audience.
“On top of this, most interventions reach a limited group only, while aiming for a broad audience.”
From How to increase reach and adherence of web-based interventions: a design research viewpoint (2015) · cites this paper as [15]
The low adherence to the Healthy Weight Assistant is attributed to a mismatch between the goals of the intervention (long-term weight management) and the goals of the users (gain insight into their behaviors).
“which the authors attribute to a mismatch between the goals of the intervention—long-term weight management—and the goals of the users—gain insight into their behaviors.”
From How to increase reach and adherence of web-based interventions: a design research viewpoint (2015) · cites this paper as [15]
Reasons for dropout from Web-based interventions relate to dissatisfaction with the intervention, mismatch of goals of the intervention and those of the users, and low flexibility to adjust to different situations and user characteristics.
“Research on nonadherence indicates that reasons for dropout relate to dissatisfaction with the intervention, mismatch of goals of the intervention and those of the users, and low flexibility to adjust to different situations and user characteristics [15,22,23].”
From How to increase reach and adherence of web-based interventions: a design research viewpoint (2015) · cites this paper as [15]
Many evaluations of eHealth interventions report either no positive effects at all or only limited ones.
“However, many evaluations of eHealth interventions report either no positive effects at all or only limited ones [8-12].”
From Persuasive System Design Does Matter: a Systematic Review of Adherence to Web-based Interventions (2012) · cites this paper as [11]
Many studies focus on whether respondents' characteristics can explain variations in adherence.
“Many studies focus on whether and which respondents’ characteristics can explain variations in adherence [11, 13, 16, 22].”
From Persuasive System Design Does Matter: a Systematic Review of Adherence to Web-based Interventions (2012) · cites this paper as [11]
Poor adherence is a common issue in web-based interventions for promoting health and health-related behavior.
“poor adherence is a common issue that needs to be addressed”
From Persuasive System Design Does Matter: a Systematic Review of Adherence to Web-based Interventions (2012) · cites this paper as [11]
A lack of human centeredness explains the incidence of usability problems and high attrition rates.
“This lack of human centeredness explains the incidence of usability problems [7-9], or high attrition rates [10-18].”
From A Holistic Framework to Improve the Uptake and Impact of eHealth Technologies (2011) · cites this paper as [14]
Six working principles for a holistic development approach were derived from the review of current frameworks and empirical research.
“We introduce six working principles derived from the review of current frameworks, as well as from empirical research [7-9,14,21,56].”
From A Holistic Framework to Improve the Uptake and Impact of eHealth Technologies (2011) · cites this paper as [14]
eHealth technologies often do not fit with the intended users' needs.
“Also, eHealth technologies often do not fit with the intended users’ needs [7-9,14,68-70].”
From A Holistic Framework to Improve the Uptake and Impact of eHealth Technologies (2011) · cites this paper as [14]
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Smart technologies for older people
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Technology for Transparency: The Case of the Web‐Based Dutch National Health Portal
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- Authors
- Kelders, S. M., Van Gemert-Pijnen, J. E. W. C., Werkman, A., Nijland, N., & Seydel, E. R.
- Affiliations
- National Institute for Public Health and the Environment (NL)
- Netherlands Nutrition Centre (NL)
- University of Twente (NL)
- Corresponding author
- Kelders, Saskia M
- ORCID
- Kelders, Saskia M
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2011-04-14
- Volume
- 13
- Issue
- 2
- Pages
- e32
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC3221377
- OpenAlex
- W2108688172
- Cited by
- 156
- References
- 51
- Citations by year
- 2025: 5 · 2024: 7 · 2023: 6 · 2022: 5 · 2021: 11 · 2020: 12 · 2019: 5 · 2018: 12 · 2017: 12 · 2016: 13 · 2015: 19 · 2014: 17 · 2013: 15 · 2012: 13
- FWCI
- 29.14
- 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)
- University of Twente Research Information (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Rivm (National Institute for Public Health and the Environment) (submittedVersion)
- University of Twente Research Information (submittedVersion, cc-by)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
- Keywords
- online intervention, dietary behavior, physical activity behavior, non-users, user satisfaction, self-efficacy, self-monitoring, health behavior change, weight management, chronic disease
- MeSH terms
- Adult, Computer-Assisted Instruction, Diet, Female, Humans, Male, Medical Informatics, Middle Aged, Motor Activity, Surveys and Questionnaires, Waiting Lists, Health Behavior, Internet
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