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Record W2071736673 · doi:10.1007/bf02287331

A comparison of client and mental health worker assessment of needs and unmet needs

2005· article· en· W2071736673 on OpenAlexaff
Michel Bédard, Carrie Gibbons, Gary W. Mack

Bibliographic record

VenueThe Journal of Behavioral Health Services & Research · 2005
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsSt. Joseph's Care GroupLakehead Psychiatric HospitalLakehead University
Fundersnot available
KeywordsHealth psychologyHealth informaticsMental healthPublic healthHealth administrationNeeds assessmentNursing researchNursingEnvironmental healthPsychologyMedicineApplied psychologyPsychiatrySociology

Abstract

fetched live from OpenAlex

This study was set up to examine agreement on needs identified by mental health clients and their primary mental health workers. Mental health workers assessed a convenience sample of clients who completed an interview about the services they receive. Data were collected from 78 client and staff dyads regarding 11 need domains. Mental health workers and clients did not agree on the number of needs (ICC = 0.42). Kappa coefficients indicated significant agreement between staff and clients for only 1 of the 11 need domains (vocational need kappa = 0.67; others ranged from 0 to 0.58). The data further revealed that mental health workers and clients disagreed about unmet needs (kappa ranged from -0.07 to 0.46). These findings show that clients and staff have divergent opinions regarding needs. Integrating clients' perspectives into treatment plans may help address this issue.

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)0.005
metaresearch head score (Gemma)0.022
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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.162
GPT teacher head0.604
Teacher spread0.442 · 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

Citations15
Published2005
Admission routes1
Has abstractno

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