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Record W4403375244 · doi:10.1177/21582440241288759

Role of Occupational Therapy Assessment and Office Ergonomics to Support Students with Accommodations in Higher Learning: A Narrative Review

2024· review· en· W4403375244 on OpenAlexaff
Behdin Nowrouzi‐Kia, Christi Tam, Raabia Khan, Bushra Binte Alam, Sujatha Alla, Vijay Kumar Chattu

Bibliographic record

VenueSAGE Open · 2024
Typereview
Languageen
FieldEngineering
TopicErgonomics and Human Factors
Canadian institutionsLaurentian UniversityUniversity of TorontoCentre for Addiction and Mental HealthUniversity Health Network
Fundersnot available
KeywordsOccupational therapyNarrativePsychologyHuman factors and ergonomicsWorkplace learningNarrative reviewMedical educationApplied psychologyPedagogyMedicineEngineeringPoison controlPsychotherapistWork (physics)Environmental health

Abstract

fetched live from OpenAlex

Postsecondary students with disabilities (SWDs) face significant challenges to their academic and personal well-being. There is a demand for more supportive strategies to facilitate fulfilling and equitable academic experiences for SWDs. This review aimed to (1) determine the effectiveness of various interventions, programs, and accommodations for enhancing the overall well-being of postsecondary SWDs and (2) evaluate the implications of these support strategies for disability service providers at postsecondary institutions. A narrative review was conducted, examining 13 studies aimed at enhancing the well-being of postsecondary SWDs. Studies were classified using the International Classification of Functioning, Disability and Health (ICF) Model. Ergonomics, assistive technology, and counselling programs had positive improvements on the academic success of SWDs. In SWDs, health status was associated with higher community participation, and physical interventions were beneficial to reducing pain over time. Coaching and mentoring opportunities were beneficial for successful goal fulfilment. However, there remains a risk of digital eye strain when using technology to support postsecondary SWDs. The findings indicate that a range of support strategies can benefit several different components of SWDs experiences. This review identifies research gaps and opportunities to examine support strategies to improve the physical and mental well-being of SWDs.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

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

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 head0.102
GPT teacher head0.420
Teacher spread0.317 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2024
Admission routes1
Has abstractyes

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