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Record W2137825237 · doi:10.1017/s1041610210000128

Screening for mental disorders in residential aged care facilities

2010· article· en· W2137825237 on OpenAlexaff
Nancy A. Pachana, Edward Helmes, Gerard J. Byrne, Barry A. Edelstein, Candace Konnert, Anne Margriet Pot

Bibliographic record

VenueInternational Psychogeriatrics · 2010
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsContext (archaeology)Extant taxonMedicineMental healthPsychologyCognitionGerontologyNursingPsychiatry

Abstract

fetched live from OpenAlex

INTRODUCTION: The International Psychogeriatric Association Task Force on Mental Health Services in Long-Term Care Facilities seeks to improve care of persons in residential aged care facilities (RACFs). As part of that effort the current authors have contributed an overview and discussion of the uses of brief screening instruments in RACFs. METHODS: While no current guidelines on the use of screening instruments in nursing homes were found, relevant extant guidelines were consulted. The literature on measurement development, testing standards, psychometric considerations and the nursing home environment were consulted. RESULTS: Cognitive, psychiatric, behavioral, functional and omnibus screening instruments are described at a category level, along with specifics about their use in a RACF environment. Issues surrounding the selection, administration, interpretation and uses of screening instruments in RACFs are discussed. Issues of international interest (such as translation of measures) or clinical concern (e.g. impact of severe cognitive decline on assessment) are addressed. Practical points surrounding who can administer, score and interpret such screens, as well as their psychometric and clinical strengths more broadly, are articulated. CONCLUSIONS: Guidelines for use of screening instruments in the RACF environment are offered, together with broad recommendations concerning the appropriate use of brief screening instruments in RACFs. Directions for future research and policy directions are outlined, with particular reference to the international context.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score0.705

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.029
GPT teacher head0.406
Teacher spread0.376 · 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 designNot applicable
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

Citations29
Published2010
Admission routes1
Has abstractyes

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