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Record W2037134136 · doi:10.1097/dbp.0000000000000122

Acceptability by Parents and Children of Deception in Pediatric Research

2015· article· en· W2037134136 on OpenAlexafffund
Mélanie Noël, Katelynn E. Boerner, Kathryn A. Birnie, Line Caes, Jennifer A. Parker, Christine T. Chambers, Conrad V. Fernandez, Kang Lee

Bibliographic record

VenueJournal of Developmental & Behavioral Pediatrics · 2015
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsUniversity of TorontoDalhousie University
FundersCanadian Institutes of Health Research
KeywordsDeceptionDebriefingPsychologyPerceptionClinical psychologyMedicineDevelopmental psychologySocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: Deception has been used to investigate the role of developmental and behavioral factors in child health; however, its acceptability for use in pediatric research has received little empirical attention. This study examined the acceptability of deception in a pediatric pain research study as assessed through participating children's and parents' long-term perceptions of its use. METHOD: Ninety-four children (52 boys; mean age = 12.77 yr) and their parents (86 mothers, 8 fathers) completed a structured interview that assessed perceptions of various aspects of deception in a pediatric pain study, 2.5 years after participating. RESULTS: A minority of parents (25.5%) and children (13.8%) spontaneously recalled that deception was used. Overall, parents and children reported positive experiences with research participation, felt comfortable with the debriefing process, and deemed the research to be of societal importance. Opinions about researchers and psychologists were not negatively impacted, and most reported willingness to participate in research involving deception again. CONCLUSION: When thoughtfully planned and disclosed, deception in pediatric research seems to be acceptable to parents and children. Future research should further examine the acceptability of deception and alternatives (e.g., authorized deception) among pediatric samples.

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)0.010
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.465
GPT teacher head0.573
Teacher spread0.109 · 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 teacher head, not a consensus.

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

Citations7
Published2015
Admission routes2
Has abstractyes

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