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Record W2920921538 · doi:10.1177/0008417419826108

The “What Now?” Workbook: Its potential utility following life-changing events

2019· article· en· W2920921538 on OpenAlexvenueno aff
Jackie Taylor, Vivienne Jones, Carole Farrell

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2019
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsWorkbookThematic analysisIntervention (counseling)Meaning (existential)PsychologyQualitative researchOccupational therapyApplied psychologyService (business)Medical educationMedicinePsychotherapistSociologySocial scienceBusinessPsychiatryMarketing

Abstract

fetched live from OpenAlex

BACKGROUND.: Following a life-changing event, such as a serious illness, people can experience a disruption of meaning and identity, making it difficult to move forward. The "What Now?" Workbook was developed to enable exploration of the personal meanings of specific occupations to facilitate future planning. PURPOSE.: The aim of this study was to investigate the utility-usability and usefulness-of the workbook in practice. METHOD.: Five occupational therapists trialled the workbook at a specialist cancer centre in England. Qualitative data were gathered via a focus group, an interview, and questionnaires. The data were subject to a realist thematic analysis. FINDINGS.: The findings showed the workbook to have actual and potential utility for service users in this setting, as perceived by their occupational therapists, by helping them to explore occupations, their loss, meanings, and future possibilities as part of an occupational therapy intervention. IMPLICATIONS.: The workbook appears to offer a structured yet flexible way to explore personal meanings of occupations, enabling service users to gain insights and move forward following a life-changing illness.

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)0.009
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.032
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0020.002
Scholarly communication0.0040.005
Open science0.0020.005
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.234
GPT teacher head0.484
Teacher spread0.251 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2019
Admission routes1
Has abstractyes

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