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Record W4318832994 · doi:10.1055/s-0042-1760631

Implementing an Electronic Patient-Reported Outcome and Decision Support Tool in Early Intervention

2023· article· en· W4318832994 on OpenAlexaff
Sabrin Rizk, Vera Kaelin, Julia Gabrielle C. Sim, Elizabeth Lerner Papautsky, Mary A. Khetani, Natalie Murphy, Beth M. McManus, Natalie E. Leland, Ashley Stoffel, Lesly Wilson James, Kris Barnekow

Bibliographic record

VenueApplied Clinical Informatics · 2023
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsMcMaster University
FundersNational Center for Advancing Translational SciencesAgency for Healthcare Research and Quality
KeywordsIntervention (counseling)Outcome (game theory)Computer scienceMedicineData scienceNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of the study is to identify and prioritize early intervention (EI) stakeholders' perspectives of supports and barriers to implementing the Young Children's Participation and Environment Measure (YC-PEM), an electronic patient-reported outcome (e-PRO) tool, for scaling its implementation across multiple local and state EI programs. METHODS: = 7). Semi-structured interviews and focus groups were used to share select quantitative pragmatic trial results (e.g., percentages for perceived helpfulness of implementation strategies) and elicit stakeholder perspectives to contextualize these results. Three study staff deductively coded transcripts to constructs in the Consolidated Framework for Implementation Research (CFIR). Data within CFIR constructs were inductively analyzed to generate themes that were rated by national early childhood advisors for their relevance to longer term implementation. RESULTS: All three stakeholder groups (i.e., families, service coordinators, program leadership) identified thematic supports and barriers across multiple constructs within each of four CFIR domains: (1) Six themes for "intervention characteristics," (2) Six themes for "process," (3) three themes for "inner setting," and (4) four themes for "outer setting." For example, all stakeholder groups described the value of the YC-PEM e-PRO in forging connections and eliciting meaningful information about family priorities for efficient service plan development ("intervention characteristics"). Stakeholders prioritized reaching families with diverse linguistic preferences and user navigation needs, further tailoring its interface with automated data capture and exchange processes ("process"); and fostering a positive implementation climate ("inner setting"). Service coordinators and program leadership further articulated the value of YC-PEM e-PRO results for improving EI access ("outer setting"). CONCLUSION: Results demonstrate the YC-PEM e-PRO is an evidence-based intervention that is viable for implementation. Optimizations to its interface are needed before undertaking hybrid type-2 and 3 multisite trials to test these implementation strategies across state and local EI programs with electronic data capture capabilities and diverse levels of organizational readiness and resources for implementation.

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)0.045
metaresearch head score (Gemma)0.085
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.239

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.085
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.116
GPT teacher head0.473
Teacher spread0.357 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

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