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Record W2301707555 · doi:10.1177/1357633x16632950

Home tele-rehabilitation for rheumatic patients: impact and satisfaction of care analysis

2016· article· en· W2301707555 on OpenAlexaboutno aff
Danilo Pani, Matteo Piga, Giulio Barabino, Michele Crabolu, Selene Uras, Alessandro Mathieu, Luigi Raffo

Bibliographic record

VenueJournal of Telemedicine and Telecare · 2016
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialRehabilitationMedicinePhysical therapyPatient satisfactionActivities of daily livingScale (ratio)PerceptionHealth careHealth literacyPsychologyNursingPsychiatry

Abstract

fetched live from OpenAlex

Introduction In this paper, we evaluated patients' perspectives on the use of a system for home tele-rehabilitation, designed for subjects with low computer literacy suffering hand impairment due to rheumatic diseases. Methods After a clinical trial assessing device effectiveness, the Psychosocial Impact of Assistive Devices Scale (PIADS), Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST) and Individually Prioritised Problem Assessment (IPPA) questionnaires were administered to evaluate the system's impact on each patient's life, and the results were correlated with clinical indices. Patients were asked to continue self-administered rehabilitation with common objects. One year later, a semi-structured telephone interview gathered data on their experience. Results The system received a positive QUEST score (4.5 ± 0.3) and a modest PIADS score (0.84 ± 0.8) due to the small impact on adaptability and self-esteem. The IPPA (3.7 ± 3.4) revealed improvement in the ability to perform tasks considered important, which was significantly correlated ( r = 0.60; p < 0.02) with the clinical Health Assessment Questionnaire (HAQ) index improvement. The interviews revealed a positive engagement effect, enhanced by the need to develop skills to be able to use the device (technological challenge) and by the perception of more attention by the medical staff. This may explain the significant dropout rate (80%) from the post-trial rehabilitation of the patients who used the device. Discussion The system was largely accepted by the patients. The results suggest that the need for information on their rehabilitation progress and the technological challenge deserves further study to make patients more autonomous in cases of continuous rehabilitation.

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)0.001
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 score0.268
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.009
GPT teacher head0.326
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 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
Published2016
Admission routes1
Has abstractyes

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