The relationship between disease symptoms, life events, coping and treatment, and depression among older adults with osteoarthritis.
Bibliographic record
Abstract
OBJECTIVE: The intent of this cross-sectional study was to broaden the range of variables examined in relationship to depression in osteoarthritis (OA) to include comorbidity, stressful life events, and the ways people respond to their disease. We examined the relationship of coping behaviors and perceptions, and medical treatments received for OA and depressive symptoms. METHODS: In the fifth year of a prospective cohort study, 1227 individuals >or= 62 years of age with hip/knee OA provided information about sociodemographics (age, sex, living circumstances, education), arthritis severity (WOMAC pain and function; ClinHAQ fatigue), comorbidity, life events, coping behavior, coping efficacy, treatment (pain management, treatment for depression), and depressed mood (Centre for Epidemiological Studies Depression scale, CES-D). Using hierarchical linear regression, variables were entered in blocks to predict CES-D scores. In the final block, the interaction of coping behavior and coping efficacy was tested. RESULTS: The response rate was 82.4% (n = 1227/1489). The mean CES-D score was 9.4, with 21.3% of individuals scoring >or= 16 (supporting depressed mood). Higher level of depressed mood was independently and significantly associated with being female, experiencing greater pain and fatigue, experiencing stressful life events, more coping behaviors, receiving treatment for depression/mental illness, and a coping behavior by coping efficacy interaction, with 63.4% of the variance accounted for in the model. CONCLUSION: Among older adults with OA, the prevalence of depressive symptoms is high. Longitudinal studies must consider OA management strategies, including both the amount of behavioral coping and its perceived efficacy, to elucidate potential interventions designed to reduce depression in patients with OA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".