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Record W4417182152 · doi:10.1186/s40900-025-00815-y

A pre-post evaluation of the Family Engagement in Research Course: does it increase perceived knowledge, abilities, and confidence in family engagement in neurodevelopmental disability and child health research?

2025· article· en· W4417182152 on OpenAlexafffund
Andrea Cross, Alice Kelen Soper, Donna Thomson, Connie Putterman, Dayle McCauley, Myanca Rodrigues, Patricia Solomon, Christine T. Chambers, Jan Willem Gorter

Bibliographic record

VenueResearch Involvement and Engagement · 2025
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsDalhousie UniversityCentre for Addiction and Mental HealthMcMaster UniversityQueen's UniversityMcMaster University Medical Centre
FundersCanadian Institutes of Health ResearchKids Brain Health Network
KeywordsChild healthFamily healthHealth professionalsInclusion (mineral)Intellectual disabilityFamily member

Abstract

fetched live from OpenAlex

The Family Engagement in Research (FER) Course launched in 2018 for researchers and family members to co-learn the principles and practice of engagement in neurodevelopmental disability and child health research. The first six cohorts of the FER Course (2018–2021) were part of a pre-post evaluation to assess learners’ perceptions and satisfaction of the FER Course, and the impact on their perceived knowledge, abilities, attitudes, and self-confidence in FER. This paper reports on the findings from this pre-post study. Sixty-nine self-selected researchers and family members enrolled in the course completed pre-and post-evaluations; satisfaction was evaluated after the course only (n = 96). Data collection involved surveys with 10-point Likert Scale questions about experiences of the course, perceived knowledge, abilities, attitudes towards, and self-confidence in family engagement in research, and overall satisfaction. We conducted Wilcoxon rank sum to compare differences between researchers and family members’ responses about self-confidence to engage, with the Wilcoxon signed rank tests used to evaluate change in outcomes from before to after the course. Open-ended survey responses were analyzed descriptively. There were statistically significant increases in survey respondents’ perceived knowledge, abilities, and self-confidence to engage in research. Positive attitudes towards FER were rated highly at baseline and post-test, with no significant change. Respondents reported high levels of satisfaction with the FER Course. The FER Course meets the need for training both family members and researchers, so that they are equipped with the perceived knowledge, abilities, and confidence to collaborate in neurodevelopmental disability and child health research. The Family Engagement in Research (FER) Course is for researchers and family members. Together, they learn how to partner in neurodevelopmental disability and child health research. To make sure the course is helping learners, a study was done from 2018 to 2021. The study included 69 learners (researchers and family members) from six course deliveries. Learners filled out surveys before and after the course. In the surveys, they shared their thoughts on the course itself. They also reported their perceived knowledge, abilities, attitudes, and confidence in family engagement in research. The survey responses were analyzed using statistical tests to see if there were changes from before to after the course and differences between researchers and family members. The open-ended survey questions gave us a better understanding of satisfaction with the course. Findings showed an increase in perceived knowledge, abilities, and confidence in engaging in research. Positive attitudes toward family engagement in research were high and did not change. Learners were satisfied with the course. Overall, the FER Course helps researchers and family members learn how to meaningfully work together in neurodevelopmental disability and child health research.

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)0.186
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1860.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.005
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 head0.339
GPT teacher head0.510
Teacher spread0.172 · 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; both teacher heads agree on what is shown here.

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
Published2025
Admission routes2
Has abstractyes

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