It's LiFe! Mobile and Web-Based Monitoring and Feedback Tool Embedded in Primary Care Increases Physical Activity: A Cluster Randomized Controlled Trial
Open accessAbstract
BACKGROUND: Physical inactivity is a major public health problem. The It's LiFe! monitoring and feedback tool embedded in the Self-Management Support Program (SSP) is an attempt to stimulate physical activity in people with chronic obstructive pulmonary disease or type 2 diabetes treated in primary care. OBJECTIVE: Our aim was to evaluate whether the SSP combined with the use of the monitoring and feedback tool leads to more physical activity compared to usual care and to evaluate the additional effect of using this tool on top of the SSP. METHODS: This was a three-armed cluster randomised controlled trial. Twenty four family practices were randomly assigned to one of three groups in which participants received the tool + SSP (group 1), the SSP (group 2), or care as usual (group 3). The primary outcome measure was minutes of physical activity per day. The secondary outcomes were general and exercise self-efficacy and quality of life. Outcomes were measured at baseline after the intervention (4-6 months), and 3 months thereafter. RESULTS: The group that received the entire intervention (tool + SSP) showed more physical activity directly after the intervention than Group 3 (mean difference 11.73, 95% CI 6.21-17.25; P<.001), and Group 2 (mean difference 7.86, 95% CI 2.18-13.54; P=.003). Three months after the intervention, this effect was still present and significant (compared to Group 3: mean difference 10.59, 95% CI 4.94-16.25; P<.001; compared to Group 2: mean difference 9.41, 95% CI 3.70-15.11; P<.001). There was no significant difference in effect between Groups 2 and 3 on both time points. There was no interaction effect for disease type. CONCLUSIONS: The combination of counseling with the tool proved an effective way to stimulate physical activity. Counseling without the tool was not effective. Future research about the cost-effectiveness and application under more tailored conditions and in other target groups is recommended. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01867970, https://clinicaltrials.gov/ct2/show/NCT01867970 (archived by WebCite at http://www.webcitation.org/6a2qR5BSr).
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Two of the included studies reported a significant increase in daily steps, four reported a significant increase in MVPA, and two reported a significant increase in energy expenditure for the intervention group compared with control.
“Two of the included studies [34,44] reported a significant increase in daily steps, 4 studies [30,34,36,53] reported a significant increase in MVPA, and 2 studies [45,47] reported a significant increase in energy expenditure for the intervention group compared with control.”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [53]
The Results (Primary Outcome, page not provided) report a significant increase in daily moderate-to-vigorous physical activity for the tool-plus-support group compared with usual care, supporting the MVPA finding attributed to this study. The Methods (Outcome Measures, page not provided) identify minutes of activity, not daily steps, as the measured outcome; the copy does not report a significant increase in steps. The energy-expenditure finding is cited to other studies, not this one. (LLM, conf=0.88)
Experimental — accuracy not yet measuredOne study [53] was assessed as high risk of selection bias because of randomization of practices rather than individuals.
“One study [53] was assessed as high risk of selection bias because of the randomization of practices rather than individuals.”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [53]
8 studies included more than 1 intervention group.
“Overall, 8 studies included more than 1 intervention group [34,43,45-47,52-54].”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [53]
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References 39 · Cited by 154
Research works printed but not linked: 1
- [2]Blair SN Physical inactivity: the biggest public health problem of the 21st century Br J Sports Med 2009 01 43 1 1 2 19136507 43/1/1 19136507
- Authors
- van der Weegen, S., Verwey, R., Spreeuwenberg, M., Tange, H., van der Weijden, T., & de Witte, L.
- Affiliations
- Zuyd University of Applied Sciences (NL)
- Maastricht University (NL)
- ORCID
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2015-07-24
- Volume
- 17
- Issue
- 7
- Pages
- e184
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC4529491
- OpenAlex
- W1902239516
- Cited by
- 154
- References
- 39
- Citations by year
- 2026: 7 · 2025: 6 · 2024: 28 · 2023: 16 · 2022: 21 · 2021: 15 · 2020: 19 · 2019: 13 · 2018: 11 · 2017: 12 · 2016: 3 · 2015: 1 · 2013: 2
- FWCI
- 6.63
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, cc-by)
- Radboud Repository (Radboud University) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Funders
- ZonMw
- Topics
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- physical activity, physical activity monitoring, feedback tools, mobile health, online intervention, self-management support, chronic obstructive pulmonary disease, type 2 diabetes, primary care, exercise self-efficacy, quality of life, physical inactivity, health counseling, general practice, long-term effects, cost-effectiveness, personalized interventions, health behavior change
- MeSH terms
- Formative Feedback, Adult, Aged, Behavior Therapy, Diabetes Mellitus, Type 2, Female, Humans, Male, Middle Aged, Motor Activity, Primary Health Care, Quality of Life, Cluster Analysis, Telemedicine, Self Efficacy, Internet, Mobile Applications
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