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Record W2801901166 · doi:10.3389/fpsyt.2018.00109

Using Play to Improve Infant Sleep: A Mixed Methods Protocol to Evaluate the Effectiveness of the Play2Sleep Intervention

2018· article· en· W2801901166 on OpenAlexafffundabout
Elizabeth Keys, Karen Benzies, Valerie G. Kirk, Linda Duffett‐Leger

Bibliographic record

VenueFrontiers in Psychiatry · 2018
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
FundersAlberta InnovatesAlberta Children's Hospital FoundationAlberta Children's Hospital Research InstituteCanadian Child Health Clinician Scientist ProgramChildren's Hospital Foundation
KeywordsThematic analysisPsychologyIntervention (counseling)Developmental psychologyQualitative researchPerceptionClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: One in four Canadian families struggle with infant sleep disturbances. The aim of this study is to evaluate Play2Sleep in families of infants with sleep disturbances. In addition to parental education on infant sleep, Play2Sleep uses examples from a video-recorded, structured play session with mothers and fathers separately to provide feedback on parent-infant interactions and their infant's sleep-related social cues. The quantitative phase will answer the research question: Does one dose of Play2Sleep delivered during a home visit with mothers and fathers of infants aged 5 months reduce night wakings at age 7 months? The qualitative phase will answer the research question: What are parental perceptions of family experiences, processes, and contexts related to Play2Sleep and infant sleep? The overarching mixed methods research question is as follows: How do parental perceptions of family experiences, processes, and contexts related to infant sleep explain the effectiveness of Play2Sleep? METHOD AND ANALYSIS: An explanatory sequential mixed methods design will be used. In the quantitative phase, a randomized controlled trial and RM-ANOVA will compare night wakings in infants whose parents receive Play2Sleep versus standard public health nursing information. Sixty English-speaking families (mothers and fathers) of full-term, healthy, singleton, 5-month-old infants who perceive that their infant has sleep disturbances will be recruited. The primary outcome measure will be change in the number of night wakings reported by parents. The qualitative component will use thematic analysis of family interviews to describe parental perceptions and experiences of infant sleep. Mixed methods integration will use qualitative findings to explain quantitative results. DISCUSSION: Play2Sleep is a novel approach that combines information about infant sleep with personalized feedback on parent-infant interactions and infant cues. Including fathers and mixed methods should capture complex family experiences of infant sleep disturbances and Play2Sleep. If effective, Play2Sleep has possible application for preventing infant sleep disturbance and tailoring for other populations. CLINICAL TRIAL REGISTRATION: www.ClinicalTrials.gov, identifier: NCT02742155. Registered on 2016 April 23.

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)0.017
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.017
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.011
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0170.001

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 head0.014
GPT teacher head0.389
Teacher spread0.374 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations3
Published2018
Admission routes3
Has abstractyes

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