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Record W3045823183 · doi:10.1177/1744629520942015

Patient-oriented research: A qualitative study of research involvement of parents of children with neurodevelopmental disabilities

2020· article· en· W3045823183 on OpenAlexafffundabout
Emma Vanderlee, Megan Aston, Karen Turner, Patrick J. McGrath, Lucyna Lach

Bibliographic record

VenueJournal of Intellectual Disabilities · 2020
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
FundersCanadian Institutes of Health Research
KeywordsNova scotiaNegotiationQualitative researchAdvisory committeePsychologyDevelopmental psychologyMedical educationMedicinePolitical scienceSociology

Abstract

fetched live from OpenAlex

Patient-oriented research engages patients and caregivers as partners contributing to all phases of the research process. This was the goal of the Strongest Families Institute Neurodevelopmental research, in Halifax, Nova Scotia, when they included a parent advisory committee, made up of parents and caregivers of children and adolescents with a neurodevelopmental condition, to complete their research project. The purpose of this qualitative research was to examine the experiences of researchers and parents of children with a neurodevelopmental condition who participated on a research study advisory committee for the Strongest Families Neurodevelopment research project. From interviews with both parents/caregivers and researchers that played a role on the advisory committee, four major themes emerged on how to negotiate and navigate their time on the committee and what worked well and what did not. This led to recommendations for future researchers and patients who may create or be a part of an advisory committee.

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)0.047
metaresearch head score (Gemma)0.066
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.250

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0470.066
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0160.017
Scholarly communication0.0060.009
Open science0.0030.007
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.270
GPT teacher head0.462
Teacher spread0.192 · 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
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

Citations2
Published2020
Admission routes3
Has abstractyes

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