Detección y prevalencia del trastorno por uso de alcohol en los centros de atención primaria de Cataluña
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
AIM: To describe the detection by general practitioners (GP) of alcohol use disorders (AUD) and alcohol dependence, and their prevalence in primary health settings. DESIGN: Cross-sectional study. SETTINGS: Twenty Catalan primary health care centres (Spain). PARTICIPANTS AND MEASUREMENTS: Twenty three randomly selected GP were surveyed about alcohol and other diseases of their patients. A total of 1,372 patient interviews were collected. Patients and GPs were asked about AUD and other mental and health conditions. The Composite International Diagnostic Interview (CIDI) as the gold standard was used, as well as other structured interviews (K10 screening and World Health Organization Disability Assessment Schedule 2.0). RESULTS: The CIDI diagnosed 9.6% of the total sample with an AUD, and 4.8% diagnosed by GPs. CIDI could detect more AUD in young adults, while GPs diagnosed more AUD and alcohol dependence in elderly people, who also had more health conditions. GPs recognised AUD in 28.8% of patients diagnosed with CIDI, but 42.4% of patients diagnosed by GPs were not detected with CIDI. Taking both into consideration, the gold standard and the GP clinical impression, 11.7% of patients had an AUD and 8.6% an AD. CONCLUSIONS: GP recognise AUD better in the elderly with worst health conditions than CIDI. AUD and alcohol dependence prevalence is high in primary health care centres.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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