The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Health Beliefs, Disease Severity, and Patient Adherence: A Meta-Analysis
Abstract
BACKGROUND: A large body of empirical data exists on the prediction of patient adherence from subjective and objective assessments of health status and disease severity. This work can be summarized with meta-analysis. OBJECTIVES: Retrieval and summary analysis of r effect sizes and moderators of the relationship between patient adherence and patients': (1) beliefs in disease threat; (2) rated health status (by physician, self, or parent); and (3) objective disease severity. METHODS: Comprehensive search of published literature (1948-2005) yielding 116 articles, with 143 separate effect sizes. Calculation of robust, generalizable random effects model statistics, and detailed examination of study diversity with moderator analyses. RESULTS: Adherence is significantly positively correlated with patients' beliefs in the severity of the disease to be prevented or treated ("disease threat"). Better patient adherence is associated with objectively poorer health only for patients experiencing disease conditions lower in seriousness (according to the Seriousness of Illness Rating Scale). Among conditions higher in seriousness, worse adherence is associated with objectively poorer health. Similar patterns exist when health status is rated by patients themselves, and by parents in pediatric samples. CONCLUSIONS: Results suggest that the objective severity of patients' disease conditions, and their awareness of this severity, can predict their adherence. Patients who are most severely ill with serious diseases may be at greatest risk for nonadherence to treatment. Findings can contribute to greater provider awareness of the potential for patient nonadherence, and to better targeting of health messages and treatment advice by providers.
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“the type of disease condition may influence perceived disease threat and health risk,20 which in turn impacts adherence behavior.21”
From An Adaptable Framework for Factors Contributing to Medication Adherence: Results from a Systematic Review of 102 Conceptual Frameworks (2021) · cites this paper as [21]
In the citing paper
“It should be borne in mind, however, that the participants in the present study were IBS non-patients, who may have been less motivated to engage in treatment than patients (DiMatteo, Haskard, & Williams, 2007).”
From Effectiveness of acceptance and commitment therapy for irritable bowel syndrome non-patients: A pilot randomized waiting list controlled trial (2020) · cites this paper as DiMatteo et al., 2007
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Metadata
- Authors
- DiMatteo, M. R., Haskard, K. B., & Williams, S. L.
- Affiliations
- University of California, Riverside (US)
- ORCID
- Williams, Summer L.
- Venue
- Medical Care
- Published
- 2007-06
- Volume
- 45
- Issue
- 6
- Pages
- 521-528
- ISSN
- 0025-7079 (ISSN-L)
- OpenAlex
- W2038481253
- Cited by
- 482
- References
- 52
- Citations by year
- 2026: 7 · 2025: 19 · 2024: 15 · 2023: 13 · 2022: 15 · 2021: 26 · 2020: 30 · 2019: 26 · 2018: 20 · 2017: 38 · 2016: 43 · 2015: 43 · 2014: 35 · 2013: 42 · 2012: 37
- FWCI
- 2.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Medical Care (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute on Aging (5R03AG27552-02, R03AG027552)
- Topics
- Health Sciences › Medicine › Family Practice › Medication Adherence and Compliance
- Health Sciences › Health Professions › General Health Professions › Patient-Provider Communication in Healthcare
- Social Sciences › Communication › Media Influence and Health
- Keywords
- medication adherence, treatment non-adherence, health beliefs, disease threat, perceived illness severity, health status, self-rated health, pediatric patients, predictors of adherence
- MeSH terms
- Attitude to Health, Health Status, Humans, Patient Compliance, Physician-Patient Relations, Severity of Illness Index
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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