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Record W4391493304 · doi:10.1177/00084174231222310

Exploring the Sustainability of Home Modifications and Adaptations in Occupational Therapy

2024· article· en· W4391493304 on OpenAlexvenueno aff
Tanya Fawkes, Caitlin S. Croft, Chloe M. Peters, W. Ben Mortenson

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2024
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityOccupational therapyQualitative researchProcess (computing)Social sustainabilityPsychologyPublic relationsNursingMedicineBusinessMedical educationSociologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Background. Many occupational therapists make home modification recommendations; however, it is unknown if sustainability considerations (i.e., economic, social, and environmental) are contemplated during this process. Purpose. To understand occupational therapists’ perceptions regarding the sustainability of home modifications. Method. This study adopted a qualitative description approach. Researchers utilized semistructured interviews as the primary means of data collection. Findings. The ten female occupational therapists interviewed had three or more years of experience working with home modifications. The analysis identified three themes: It's not easy being green: environmental sustainability, stretching a dollar: financial inequities, and barriers and benefits in the home modification process. Implications. Findings suggest OTs have a varied and a general understanding of how to implement sustainability concepts in their practice. There is also a need to make access to home modifications more equitable. Further research is needed to build a more robust understanding of how OT recommended home modifications can contribute to sustainability.

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)0.011
metaresearch head score (Gemma)0.020
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 score0.013
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.009
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0010.001
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 head0.579
GPT teacher head0.528
Teacher spread0.051 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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