Depressive, anxiety, and distress symptoms among cancer patients who endorse appearance problems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Body image is a vital and complex issue in cancer patients, but not well recognized. In the ambulatory psychiatric-oncology clinic, we assessed what portion of cancer patients endorsed appearance problems and if they differed in terms of depression, anxiety, or distress scores when compared with those who did not endorse appearance problems. METHOD: All adult patients with active cancer diagnosis seen in the outpatient psychiatry oncology clinic (June 2014-January 2016) who provided informed consent were included (N = 1,939) in the cross-sectional study design. "Appearance problems" were assessed as a categorical, binomial variable (yes/no) using the National Comprehensive Cancer Network Distress Thermometer checklist. Other assessments included the Patient Health Questionnaire-9, Patient Health Questionnaire-2, Generalized Anxiety Disorder-7, Distress Thermometer, and Edmonton Symptom Assessment Scale.ResultThe overall prevalence rate of individuals who endorsed appearance problems was approximately 36%; they were more likely to be younger, female, Black or Hispanic, and not in a committed relationship (all results for demographic variables were statistically significant; all p < .001). Importantly, those patients who endorsed appearance problems exhibited higher scores for depression (p < .0001), anxiety (p < .0001), and distress (p < .0001), and these differences were of medium effect size (Cohen's d = 0.5-0.6).Significance of resultsThe current results underscore the need to identify patients with body image problems early given that they are likely to exhibit higher magnitude of anxiety, depression and distress symptoms while undergoing cancer care. The results highlight the importance of body image issues and the need to evaluate them in cancer patients.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it