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Rethinking early intervention rehabilitation services for children with motor difficulties: engaging stakeholders in the conceptualization of telerehabilitation primary care

2021· dataset· en· W6958390016 on OpenAlexaff

Bibliographic record

VenueFigshare · 2021
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
Fundersnot available
KeywordsTelerehabilitationFocus groupTelehealthStakeholderConceptualizationKnowledge translationThematic analysisService delivery frameworkPsychological interventionService (business)

Abstract

fetched live from OpenAlex

Rehabilitation services for children with mild motor difficulties are limited. Telehealth could be a novel avenue through which to provide these services. With the input of various stakeholder groups, this study aimed to develop a logic model for a new primary care telerehabilitation intervention and to identify influencing implementation factors. A participatory research design was used. A logic model, developed in consultation with five healthcare managers, was discussed with four stakeholder groups. Focus groups were conducted with clinicians (n = 9), pediatric healthcare managers (n = 5), and technology information consultants (n = 2), while parents (n = 4) were interviewed to explore their perceptions of the proposed intervention, and factors influencing implementation. Transcribed discussions were analyzed using reflexive thematic analysis. Stakeholders supported the delivery of telerehabilitation services for children with mild motor difficulties. Although agreement was generated for each logic model component, important recommendations were voiced related to service relevance and sustainability, parent and community capacity building, and platform dependability, security, and support. Identified factors influencing the implementation encompassed consumer, provider, technological, systemic and contextual barriers and facilitators. Strategies to address them were also suggested. This study demonstrates the value of, and a process to engage stakeholders in the designing of pediatric telerehabilitation services and its implementation.IMPLICATIONS FOR PRACTICEPediatric telerehabilitation service are complex interventions which operate in complicate systems.Designing telerehabilitation services with stakeholders is recommended, yet how to do so often not clear.This study demonstrated that the development of a logic model can provide a systematic framework to helps guide the co-design process with stakeholders.Resulting recommendation underscored a broader vision for the intervention and identified crucial factors and strategies required for its successful implementation and sustainability. Pediatric telerehabilitation service are complex interventions which operate in complicate systems. Designing telerehabilitation services with stakeholders is recommended, yet how to do so often not clear. This study demonstrated that the development of a logic model can provide a systematic framework to helps guide the co-design process with stakeholders. Resulting recommendation underscored a broader vision for the intervention and identified crucial factors and strategies required for its successful implementation and 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)0.022
metaresearch head score (Gemma)0.021
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: Dataset · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0060.011
Scholarly communication0.0070.008
Open science0.0020.006
Research integrity0.0030.005
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 head0.037
GPT teacher head0.238
Teacher spread0.201 · 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
GenreDataset

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
Published2021
Admission routes1
Has abstractyes

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