Screening for depression in head and neck cancer
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
OBJECTIVES: The objectives of this study are to identify the prevalence of depression and the accuracy of depression screening instruments in ambulatory head and neck cancer patients who have received radiation. This population is at risk for depression because of the life-threatening nature of the illness, and treatment-induced oral morbidity. METHODS: Sixty subjects were evaluated for Major and Minor Depression according to Research Diagnostic Criteria using the Schedule for Affective Disorders and Schizophrenia (SADS). Screening instruments examined were the Beck Depression Inventory (BDI), the Hospital Anxiety and Depression Scale (HADS) and the Centre for Epidemiological Studies-Depression (CES-D) scale. Accuracy was assessed by calculating the sensitivities, specificities, positive predictive values (PPV) and areas under curve (AUC) from Receiver Operating Characteristic (ROC) curves. RESULTS: The prevalence of Major and Minor Depression was 20%. All of the screening instruments tested were found to be highly accurate. Statistically significant differences between the instruments were not observed but the HADS demonstrated the highest absolute levels of sensitivity, specificity and PPV. No cases of Major Depression were missed by any of the instruments tested. CONCLUSIONS: These results suggest that a significant minority of head and neck cancer patients are depressed in the post radiation period, and that accurate screening for clinically significant depression is possible using any of the three instruments evaluated here.
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.
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 it