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Record W4321458905 · doi:10.3389/fresc.2023.1057641

Pediatric tele-coaching fidelity evaluation: Feasibility, perceived satisfaction and usefulness of a new measure

2023· article· en· W4321458905 on OpenAlexafffund
Tatiana Ogourtsova, Annette Majnemer, Amelie Brown, Helen Jillian Filliter, Kristy Wittmeier, Jessica D. Hanson, Maureen O’Donnell

Bibliographic record

VenueFrontiers in Rehabilitation Sciences · 2023
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversity of British ColumbiaProvincial Health Services AuthorityChildren's Hospital Research Institute of ManitobaDalhousie UniversityUniversity of ManitobaIzaak Walton Killam Health CentreMontreal Children's HospitalJewish Rehabilitation HospitalMcGill UniversityMcGill University Health CentreCentre for Interdisciplinary Research in Rehabilitation
FundersCanadian Institutes of Health ResearchMcGill University Health Centre
KeywordsCoachingFidelityPsychologyDescriptive statisticsApplied psychologyLikert scaleObservational studyMedical educationMedicineComputer scienceStatisticsDevelopmental psychologyPsychotherapistMathematics

Abstract

fetched live from OpenAlex

Background To promote and ensure coaches' fidelity in delivering an online health coaching program to parents of children with suspected developmental delay, we developed and implemented a novel coaching fidelity rating tool, CO-FIDEL (COaches Fidelity in Intervention DELivery). We aimed to (1) Demonstrate CO-FIDEL's feasibility in evaluating coaches' fidelity and its change over time; and (2) Explore coaches' satisfaction with and usefulness of the tool. Methods In an observational study design, coaches (n = 4) were assessed using the CO-FIDEL following each coaching session (n = 13–14 sessions/parent-participant) during the pilot phase of a large randomized clinical trial involving eleven (n = 11) parent-participants. Outcome measures included subsections' fidelity measures, overall coaching fidelity, and coaching fidelity changes over time analyzed using descriptive and non-parametric statistics. In addition, using a four-point Likert Scale and open-ended questions, coaches were surveyed on their satisfaction and preference levels, as well as facilitators, barriers, and impacts related to the use of CO-FIDEL. These were analyzed using descriptive statistics and content analysis. Results One hundred and thirty-nine (n = 139) coaching sessions were evaluated with the CO-FIDEL. On average, overall fidelity was high (88.0 ± 6.3 to 99.5 ± 0.8%). Four coaching sessions were needed to achieve and maintain a ≥ 85.0% fidelity in all four sections of the tool. Two coaches showed significant improvements in their coaching skills over time in some of the CO-FIDEL sections (Coach B/Section 1/between parent-participant B1 and B3: 89.9 ± 4.6 vs. 98.5 ± 2.6, Z = −2.74, p = 0.00596; Coach C/Section 4/between parent-participant C1 and C2: 82.4 ± 7.5 vs. 89.1 ± 4.1, Z = −2.66; p = 0.00758), and in overall fidelity (Coach C, between parent-participant C1 and C2: 88.67 ± 6.32 vs. 94.53 ± 1.23, Z = −2.66; p = 0. 00758). Coaches mainly reported moderate-high satisfaction with and usefulness of the tool, and pointed out areas of improvement (e.g., ceiling effect, missing elements). Conclusions A new tool ascertaining coaches' fidelity was developed, applied, and shown to be feasible. Future research should address the identified challenges and examine the psychometric properties of the CO-FIDEL.

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)0.012
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.154
GPT teacher head0.415
Teacher spread0.262 · 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 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

Citations4
Published2023
Admission routes2
Has abstractyes

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