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Record W1985499026 · doi:10.1080/13548500701694219

An innovative framework for psychosocial assessment in complex mental capacity evaluations

2008· article· en· W1985499026 on OpenAlexaff
Andrea Margaret Newberry, Arlin Pachet

Bibliographic record

VenuePsychology Health & Medicine · 2008
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsAlberta Health Services
Fundersnot available
KeywordsPsychosocialPsychologyCoping (psychology)Construct (python library)ReferralApplied psychologyMedicineNursingPsychotherapistComputer science

Abstract

fetched live from OpenAlex

This study describes an innovative tool developed by the Regional Capacity Assessment Team (RCAT) to assess unique psychosocial factors related to capacity evaluations. Capacity is a socio-legal construct entailing the ability to understand choices, appreciate consequences and follow through (or direct a surrogate) with chosen options. RCAT's targeted psychosocial assessment includes medico-legal factors, social history and supports, coping skills, religious/cultural factors and risk of abuse. RCAT completes the psychosocial assessment to determine whether a full capacity assessment is required (referral disposition) and to determine the impact of an adult's social functioning on their decision-making capacity (capacity determination). RCAT's psychosocial assessment protocol was developed after a comprehensive literature review of capacity assessment and incorporates recommended practices in geriatric social work and psychology. This study will synthesise the pertinent literature, discuss cultural interviewing processes significant to capacity, caregiver assessment and describe the tool itself. Suggestions for future research and appropriate implementation of this tool are provided.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.325
GPT teacher head0.618
Teacher spread0.293 · 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.

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

Citations18
Published2008
Admission routes1
Has abstractyes

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