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Record W2102146492 · doi:10.1192/bjp.181.3.214

Prevalence of psychiatric disorder and the need for psychiatric care in Northern Ireland

2002· article· en· W2102146492 on OpenAlexfundaboutno aff
Pamela Mcconnell, Paul Bebbington, Roy Mcclelland, Kate Gillespie, Sharon Houghton

Bibliographic record

VenueThe British Journal of Psychiatry · 2002
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
FundersQueen's University
KeywordsPsychiatryEpidemiologyNeuropsychiatryAnxietyDepression (economics)General Health QuestionnaireQuarter (Canadian coin)PopulationMental healthMedicineEpidemiology of child psychiatric disorders

Abstract

fetched live from OpenAlex

BACKGROUND: This is the first report on the epidemiology of psychiatric disorders and needs for psychiatric treatment in the District of Derry, Northern Ireland. AIMS: To assess the prevalence of psychiatric disorder and the needs for treatment in the general population of Derry. METHOD: The sample was drawn at random with a two-phase design using the General Health Questionnaire (GHQ-28) during the first phase, and the Schedules for Clinical Assessment in Neuropsychiatry (SCAN) with the Needs for Care Assessment (NFCAS-C) in the second phase. RESULTS: The second phase (n=307) gave a weighted 1-month prevalence of hierarchically ordered ICD-10 psychiatric disorders of 7.5% and a 1-year prevalence of 12.2%. The equivalent prevalences for depressive disorders were 2.4% and 6.0%, respectively, and those for anxiety states were 3.5% and 3.7%. Only a quarter of needs for treatment were met, with the situation being better for depression than for anxiety. CONCLUSIONS: The rates of psychiatric disorder in Derry were even higher than those reported by a similar survey in inner London. This almost certainly reflects the very high levels of social deprivation in the District. Needs for treatment were often unmet.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.285
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations71
Published2002
Admission routes2
Has abstractyes

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