An analysis of 100 referrals for depression from primary care to an adult mental health service
Bibliographic record
Abstract
OBJECTIVES: Improving the interface between primary care and mental health services is a key target in current healthcare policy in Ireland. This study examines the content of referrals from primary care to a community mental health service for apparent depression. METHOD: We retrospectively reviewed the clinical records of 100 patients with depression who consecutively attended a specialist mental health service in Ireland's midwest region. Records were reviewed for demographic and clinical information provided by the doctor at the time of referral, subsequent service engagement, diagnosis and treatment initiated. RESULTS: There was considerable variation in the content and presentation of information contained in referral letters. Eleven per cent used structured HSE mental health referral forms. Seventy-six per cent of referrals contained clear information regarding name, address, symptoms and treatment previously initiated. Specifically, low mood, biological symptoms of depression and illness severity were documented in 43%, 34% and 27%, respectively. Suicide risk was documented in 20%. More detail was significantly associated with more severe illness. At initial specialist assessment, 71% had commenced antidepressant treatment, with 11% having received an adequate trial of a first antidepressant and 3% an adequate trial of two antidepressants. Two-thirds were diagnosed with mild/moderate depression. Initiation of antidepressant treatment was linked to subsequent diagnosis of depressive illness by mental health services (p < 0.001). CONCLUSIONS: Our findings indicate variable referral practices from general practice to mental health in our region. Most referrals were for mild to moderate depression. Poor access to psychological services locally may be a key factor in this phenomenon.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".