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Record W2784502233 · doi:10.1177/0008417417723119

The Daily Experiences of Pleasure, Productivity, and Restoration Profile: A case study

2017· article· en· W2784502233 on OpenAlexvenueno aff
Karen Atler, Lindsey Barney, Allyson Moravec, Pat L. Sample, Christine A. Fruhauf

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2017
Typearticle
Languageen
FieldPsychology
TopicChild Therapy and Development
Canadian institutionsnot available
Fundersnot available
KeywordsPleasureProductivityPsychologyActivities of daily livingOccupational therapyGerontologyMedicinePsychotherapistEconomicsEconomic growthPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Occupational therapy enables clients to self-manage their health through the use of occupation; however, additional occupation-focused assessments are needed to capture people's subjective experiences associated with everyday activities as awareness of one's experiences can help promote change. PURPOSE: This qualitative case study explored the utility of one such assessment, the Daily Experiences of Pleasure, Productivity, and Restoration Profile (PPR Profile). METHOD: Five spousal caregivers completed and discussed the PPR Profile with an occupational therapist. Interviews with the caregivers and therapist occurred during and following use. Content analysis revealed several themes. FINDINGS: Both caregivers and the occupational therapist reported that use of the PPR Profile provided benefits but not without challenges. IMPLICATIONS: The findings support preliminary utility of the PPR Profile; however, additional research is needed and occupational therapists need to be aware of the challenges when deciding to use the tool.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0100.005
Scholarly communication0.0030.003
Open science0.0020.005
Research integrity0.0020.003
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 head0.176
GPT teacher head0.417
Teacher spread0.241 · 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 designCase report
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

Citations11
Published2017
Admission routes1
Has abstractyes

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