Low Goal Ownership Predicts Drop-out from a Weight Intervention Study in Overweight Patients with Type 2 Diabetes
Open accessAbstract
BACKGROUND: Drop-out is a major problem in weight loss studies. Although previous attrition research has examined some predictors of drop-out, theoretically grounded research on psychological predictors of drop-out from weight interventions has been lacking. PURPOSE: To examine psychological predictors of drop-out from a weight reduction study in diabetes type 2 patients. METHOD: A clinical trial was conducted with 101 overweight/obese (body mass index >27) diabetes type 2 patients. Patients were randomly assigned to a self-regulation intervention, an active control group, and a passive control group. Psychological, somatic, socio-demographic, and lifestyle variables were examined as predictors of drop-out from baseline to 6 months follow-up. RESULTS: Multiple logistic regression analysis indicated that low autonomous regulation or low 'goal ownership' was the best predictor of drop-out. CONCLUSION: It is suggested that the assessment of 'goal ownership' prior to a weight reduction intervention could identify patients who are sufficiently motivated to participate. Patients who score low on 'goal ownership' may be offered pretreatment interventions to increase their motivation.
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The rate of dropping out of treatment in psychiatric outpatients is highly variable and depends on the definition and time of drop out as well as the characteristics of the population sample and study design.
“The rate of dropping out of treatment in psychiatric outpatients is highly variable and depends on the definition and time of drop out as well as the characteristics of the population sample and study design [1, 2].”
From Determinants of dropout in a community-based mental health crisis centre (2016) · cites this paper as [2]
The Introduction reports substantially different drop-out estimates for weight-loss programs—about one-third versus as high as 80%—and the Methods specify how this study defined drop-out. But the paper concerns overweight patients with type 2 diabetes and excluded people under psychiatric treatment; it does not establish rates for psychiatric outpatients or show that variation depends on the timing of drop-out, sample characteristics, and study design. (LLM, conf=0.85)
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- Authors
- Huisman, S., Maes, S., De Gucht, V. J., Chatrou, M., & Haak, H. R.
- Affiliations
- Leiden University (NL)
- Máxima Medisch Centrum (NL)
- Corresponding author
- Huisman, Sasja
- Venue
- International Journal of Behavioral Medicine
- Published
- 2009-12-22
- Volume
- 17
- Issue
- 3
- Pages
- 176-181
- ISSN
- 1070-5503 (ISSN-L)
- 1532-7558
- PMC
- PMC2910303
- OpenAlex
- W1992660372
- Cited by
- 60
- References
- 27
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 7 · 2023: 4 · 2022: 2 · 2021: 2 · 2020: 7 · 2019: 5 · 2018: 2 · 2017: 5 · 2016: 5 · 2015: 5 · 2014: 2 · 2012: 6
- FWCI
- 4.71
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- International Journal of Behavioral Medicine (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
- Social Sciences › Psychology › Social Psychology › Motivation and Self-Concept in Sports
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Keywords
- attrition, dropout, type 2 diabetes, overweight, obesity, weight loss interventions, autonomous regulation, self-regulation, motivation, predictors of dropout
- MeSH terms
- Analysis of Variance, Diabetes Mellitus, Type 2, Employment, Female, Goals, Humans, Life Style, Male, Middle Aged, Obesity, Patient Dropouts, Psychology, Logistic Models, Self Efficacy
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 ›
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