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Record W3110932913 · doi:10.5195/ijt.2020.6327

Telehealth and Home Health Occupational Therapy: Clients’ Perceived Satisfaction With and Perception of Occupational Performance

2020· article· en· W3110932913 on OpenAlexaboutno aff
Missi Zahoransky, Jennifer E Lape

Bibliographic record

VenueInternational Journal of Telerehabilitation · 2020
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
Fundersnot available
KeywordsTelehealthOccupational therapyPerceptionHealth careRestructuringData collectionNursingPatient satisfactionOccupational safety and healthTelerehabilitationMedicinePsychologyTelemedicineFamily medicinePhysical therapyBusiness

Abstract

fetched live from OpenAlex

Home health care agencies are restructuring service delivery models to address quality of care and client satisfaction while containing costs. New regulatory changes and the public health emergency due to the COVID-19 pandemic precipitated an immediate need for alternative care models. Telehealth has been recognized as a feasible delivery model to provide health care. This quasi-experimental pretest-posttest study examined the feasibility of performing occupational therapy telehealth visits as an adjunct to on-site visits for homebound clients (N=9). The Outcomes and Assessment Information Set (OASIS) data collection set, Canadian Occupational Performance Measure (COPM), and a survey were used to collect data. This combination of visits resulted in clinically and statistically significant improvements in client perception of performance and satisfaction with activities of daily living. Findings showed that participants favorably perceived this service delivery model met their therapy needs and they would recommend it to others. Results of this study warrant a larger study involving physical and speech therapy services.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.051
GPT teacher head0.379
Teacher spread0.327 · 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 designObservational
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

Citations25
Published2020
Admission routes1
Has abstractyes

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