Body Image and Depressive Symptoms as Correlates of Self-reported Versus Clinician-reported Physiologic Function
Bibliographic record
Abstract
PURPOSE: This study examined the relationships between physiologic function, depressive symptoms, and body image among maintenance cardiac rehabilitation participants. Physiologic function was operationalized as both functional status and functional capacity. METHODS: Participants were 72 men (mean age = 67.3 years) all of whom had experienced a traumatic cardiac event (ie, myocardial infarction, valve replacement surgery, coronary artery bypass graft surgery, percutaneous transluminal coronary angioplasty), and had completed some type of physician-supervised acute cardiac rehabilitation (ie, phase I and phase II). Measures of body image (social physique anxiety and body appearance satisfaction), self-reported functional status, clinician-reported functional capacity (ie, V0(2) and peak power), and depressive symptoms were collected. RESULTS: Hierarchic multiple regression analyses revealed that both functional capacity and functional status explained significant variance in social physique anxiety (R(2) = 0.11, P<.05 and R(2) = 0.18, P<.05, respectively), whereas only functional status was a significant predictor of body appearance satisfaction (R(2) = 0.37, P<.01). Contrary to our hypotheses, depressive symptoms were not significantly related to either psychosocial or physiologic indices of functional well-being. CONCLUSIONS: Both patient perceptions of functional status and clinical measures of functional capacity are important aspects of psychosocial well-being among cardiac patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".