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Record W2163006738

Integrated model for mental health care. Are health care providers satisfied with it?

2001· article· en· W2163006738 on OpenAlexaff
Sheryl Farrar, Nick Kates, Anne Marie Crustolo, R. N. Lambrina Nikolaou

Bibliographic record

VenuePubMed · 2001
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsHamilton Health Sciences
Fundersnot available
KeywordsMental healthFamily medicinePrimary careMedicineMental health careNursingLikert scalePrimary health careHealth carePsychologyPsychiatryPopulation
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine whether health care providers are satisfied with an integrated program of mental health care. DESIGN: Surveys using a mailed questionnaire. Surveys were developed for each of the three disciplines; each survey had 30 questions. SETTING: Thirty-six primary care practices in Hamilton, Ont, participating in the Hamilton-Wentworth Health Service Organization's Mental Health Program. PARTICIPANTS: Family physicians, psychiatrists, and mental health counselors providing mental health care in primary care settings. MAIN OUTCOME MEASURE: Satisfaction as shown on 5-point Likert scales. RESULTS: High levels of satisfaction with the model were recorded. Family physicians increased their skills, felt more comfortable with handling mental health problems, and were satisfied with the benefit to their patients. Psychiatrists and counselors were gratified that they were accepted by other members of the primary care team. Areas for improvement included finding space in primary care settings and better scheduling to allow for optimal communication. CONCLUSION: Family physicians, counselors, and psychiatrists expressed great satisfaction with a shared mental health care program based in primary care.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.061
GPT teacher head0.355
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), 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

Citations44
Published2001
Admission routes1
Has abstractyes

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