MétaCan
Menu
Back to cohort
Record W3015945698 · doi:10.1177/0008417420917500

Referral Prioritization in Home Care Occupational Therapy: A Matter of Perspective

2020· article· en· W3015945698 on OpenAlexfundvenueno aff
Marie‐Hélène Raymond, Debbie Ehrmann Feldman, Louise Demers

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2020
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
FundersFonds de Recherche du Québec - Santé
KeywordsReferralPrioritizationOccupational therapyMedicineNursingPerspective (graphical)Independence (probability theory)PsychologyFamily medicinePsychiatryBusiness

Abstract

fetched live from OpenAlex

BACKGROUND.: Prioritizing referrals for home care occupational therapy is somewhat subjective, and public and patient perspectives on waiting list priorities are unknown. PURPOSE.: To explore the views of home care occupational therapists (OTs), older persons (OPs) and adults with disabilities on waiting list priorities, as well as issues and challenges underlying these priorities. METHOD.: We conducted in-depth interviews with 11 OTs, 10 OPs and 9 adults with disabilities. Participants were asked to prioritize referral scenarios while explaining their choices. Directed and conventional content analysis allowed the identification of themes for each group of participants. FINDINGS.: OTs experienced conflicts of values but mainly prioritized referrals based on client safety. OPs sought to maximize client's independence, and persons with disabilities aimed to improve clients' social participation. IMPLICATIONS.: OTs should seek the perspectives of their target clientele on referral prioritization criteria and strive to adjust prioritization practices accordingly.

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)0.027
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.038
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0100.011
Scholarly communication0.0080.005
Open science0.0020.006
Research integrity0.0030.004
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 head0.505
Teacher spread0.180 · 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 designQualitative
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

Citations7
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Occupational TherapySame topicOccupational Therapy Practice and ResearchFrench-language works237,207