Undetected depression in primary healthcare: Occurrence, severity and co-morbidity in a two-stage procedure of opportunistic screening
Bibliographic record
Abstract
BACKGROUND: Depression often remains undetected in primary healthcare, and a two-stage screening procedure has been recommended for future research on the recognition, management and outcome of these patients. The aim of this study was to analyse the occurrence and the severity of depression, as well as gender, age and psychiatric co-morbidity in patients with previously undetected depression using a screening questionnaire followed by a diagnostic interview for detecting depression among patients visiting primary healthcare. METHODS: All patients visiting a primary healthcare centre during a period of 10 days were asked to fill in the self-rating version of the Montgomery-Åsberg Depression Rating Scale. Patients with a score of 12 or more were invited to participate in a structured diagnostic interview based on the Primary Care Evaluation of Mental Disorders. RESULTS: Out of 221 (=N) participants, 45 (20.4%) patients showed signs of depression (scores of 12 or more). Of these 45 patients, 31 consented to the structured interview, and of those, 28 (12.7%) fulfilled the criteria for depression, 17 (7.7%) had a major depression and 11 (5.0%) had a mixed depression-anxiety condition. CONCLUSIONS: The rate of undetected depression in primary healthcare was considerable. The majority of these patients had a major depression. Psychiatric co-morbidity among depressed patients was almost universal. The two-stage procedure of opportunistic screening with the Montgomery-Åsberg Depression Rating Scale and the Primary Care Evaluation of Mental Disorders seems to be a feasible method for detecting these patients in primary healthcare.
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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 | 0.001 | 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 | 0.001 |
| 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".