An online lifestyle diary with a persuasive computer assistant providing feedback on self-management
Abstract
In accordance with the global trend, in The Netherlands approximately 45% of the population is overweight. Existing studies show that patient self-management can reduce these figures, but medical non-adherence is a persistent problem. eHealth can potentially increase adherence to self-management. Consequently, we designed a persuasive computer assistant and evaluated its influence on self-management, i.e., the use of an online lifestyle diary called DieetInzicht.nl. The assistant is represented by an animated iCat, which shows different facial expressions and provides cooperative feedback following principles from the motivational interviewing method. We conducted a randomized controlled trial with 118 overweight people over a period of four weeks and studied the difference between diary use with and without computer assistant feedback. Results show that the computer assistant contributed to filling in the diary more frequently, reduced the decline in motivation to perform self-management, lowered the (reported) BMI, and improved the ease of use. Furthermore, diary use increased knowledge of maintaining a healthy lifestyle. Finally, personal characteristics, i.e., locus of control, vocabulary, computer experience, age, gender, education level and initial BMI, explained the variance in the diary use and its outcome. Of the 118 participants 35 filled in the closing survey, covering motivation, BMI, lifestyle knowledge and ease of use, which implies that the findings based on these results are mainly representative for motivated participants. In general, this study shows that the Dieetinzicht eHealth service, including a personal computer assistant, is likely to support motivated overweight people and lifestyle related diseases to get a better insight in and adhere to their self-management.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
ECA interventions have been found to be easier to use and used more frequently than interventions without an ECA.
“Results are promising, as ECA interventions have been found to be easier to use [5] and used more frequently [5,11-13] than interventions without an ECA.”
The findings add to the mixed evidence base on nutritional ECAs.
“Our findings might, on first sight, contradict our hypotheses, and add to the mixed evidence base on nutritional ECAs [5,6,44].”
The citation lists haven’t been fetched yet
References 33 · Cited by 96
- Authors
- Blanson Henkemans, O. A., van der Boog, P. J. M., Lindenberg, J., van der Mast, C. A. P. G., Neerincx, M. A., & Zwetsloot-Schonk, B. J. H. M.
- Affiliations
- Delft University of Technology, Delft, The Netherlands
- Leiden University Medical Center, Leiden, The Netherlands
- Netherlands Organisation for Applied Scientific Research (NL)
- Leiden University Medical Center (NL)
- ORCID
- Neerincx, Mark A.
- Venue
- Technology and Health Care
- Publisher
- SAGE Publications
- Published
- 2009-07-23
- Volume
- 17
- Issue
- 3
- Pages
- 253-267
- ISSN
- 0928-7329 (ISSN-L)
- 1878-7401
- OpenAlex
- W1741156858
- Cited by
- 96
- References
- 33
- Citations by year
- 2026: 1 · 2024: 4 · 2023: 2 · 2022: 6 · 2021: 5 · 2020: 3 · 2019: 7 · 2018: 3 · 2017: 6 · 2016: 7 · 2015: 6 · 2014: 8 · 2013: 10 · 2012: 11
- FWCI
- 16.95
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Technology and Health Care (publishedVersion)
- PubMed (publishedVersion)
- TNO Repository (submittedVersion)
- Repository hosted by TU Delft Library (TU Delft) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- Leids Universitair Medisch Centrum
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- persuasive technology, self-management, overweight, motivational interviewing, e-health, medication adherence, body mass index, motivation, locus of control, computer experience, ease of use
- MeSH terms
- Analysis of Variance, Diet, Feedback, Health Promotion, Humans, Life Style, Medical Records, Motivation, Patient Compliance, Regression Analysis, Self Care, Weight Loss, Exercise, Body Mass Index, Patient Satisfaction, Internet, Risk Reduction Behavior, Overweight
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review