Obese Patients' Perceptions of Treatment Outcomes and the Factors That Influence Them
Abstract
BACKGROUND: Despite considerable professional consensus that modest weight losses of 5% to 10% are successful for reducing the comorbid conditions associated with obesity, obese patients often desire weight losses 2 to 3 times greater than this. Examining ways to reduce the disparities between treatment expectations and subsequent outcomes, this study evaluated the role of physical characteristics, treatment setting, and mood in patients' evaluations of treatment outcomes. METHODS: This study was conducted in a university outpatient weight loss clinic with a sample of 397 obese individuals seeking weight loss by a variety of modalities. Before treatment, participants' heights and weights were measured, and the Beck Depression Inventory and the Goals and Relative Weight Questionnaire were administered. RESULTS: Outcome evaluations ranged from 64.4 +/- 11.1 kg (mean +/- SD) for dream weight to 90.1 +/- 19.1 kg for disappointed weight. Initial body weight was the strongest predictor of disappointed, acceptable, and happy weights (beta =.90,.76, and.57, respectively). Sex (beta = -.37) and height (beta =.37) were the strongest determinants of dream weight. Heavier participants chose higher absolute weights, but the weight loss required to reach each of the outcomes was greater for heavier than for lighter patients. CONCLUSIONS: These data signal a therapeutic dilemma in which the amount of weight loss produced by the best behavioral and/or pharmacologic treatments is viewed as even less than disappointing. Patients with the highest pretreatment weights are likely to have the most unrealistic expectations for success.
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Twenty years ago, lifestyle-treated participants typically reported desiring to lose 25% or more of their baseline weight.
“Twenty years ago, lifestyle-treated participants typically reported desiring to lose 25% or more of their baseline weight [101], which was often followed by practitioners’ extolling the health benefits of a 5–10% reduction, the mean loss they could deliver at the time [8].”
From The Role of Lifestyle Modification with Second-Generation Anti-obesity Medications: Comparisons, Questions, and Clinical Opportunities (2023) · cites this paper as [101]
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- Authors
- Foster, G. D., Wadden, T. A., Phelan, S., Sarwer, D. B., & Sanderson, R. S.
- Affiliations
- University of Pennsylvania (US)
- Corresponding author
- Foster, Gary D.
- Venue
- Archives of Internal Medicine
- Publisher
- American Medical Association (AMA)
- Published
- 2001-09-24
- Volume
- 161
- Issue
- 17
- Pages
- 2133
- ISSN
- 0003-9926 (ISSN-L)
- OpenAlex
- W2054101269
- Cited by
- 185
- References
- 25
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 2 · 2023: 2 · 2022: 4 · 2021: 1 · 2020: 3 · 2019: 11 · 2018: 5 · 2017: 3 · 2016: 6 · 2015: 10 · 2014: 11 · 2013: 11 · 2012: 7
- FWCI
- 29.28
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Archives of Internal Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r01dk056114-05)
- National Institute of Diabetes and Digestive and Kidney Diseases (DK 56114)
- Topics
- Health Sciences › Health Professions › Pharmacy › Obesity and Health Practices
- Social Sciences › Psychology › Clinical Psychology › Eating Disorders and Behaviors
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Keywords
- obesity, weight loss expectations, treatment outcome assessment, patient perspectives, weight loss goals, initial body weight, sex differences, height, depression, weight loss clinics
- MeSH terms
- Adult, Behavior Therapy, Clinical Trials as Topic, Female, Humans, Male, Middle Aged, Obesity, Gastroplasty, Weight Loss, Patient Satisfaction, Outcome Assessment, Health Care
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.
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