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Record W4301400881 · doi:10.3389/fpsyt.2022.938482

Development and reliability of the coding system evaluating maternal sensitivity to social interactions with 34- to 36-week postmenstrual age preterm infants

2022· article· en· W4301400881 on OpenAlexaff
Laure Boissel, Emeric Pinchaux, Marine Guilé, Pascal Corde, Cécile Crovetto, Momar Diouf, Charlotte Mariana, Jonathan Meynier, Carl Picard, Daphné Scoury, David Cohen, Xavier Benarous, Sylvie Viaux‐Savelon, Jean-Marc Guilé

Bibliographic record

VenueFrontiers in Psychiatry · 2022
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsMcGill University
FundersInstitut National de la Santé et de la Recherche Médicale
KeywordsInter-rater reliabilitySSS*PsychologyNeonatal intensive care unitGestational ageMaternal sensitivityPediatricsBayley Scales of Infant DevelopmentDevelopmental psychologyInfant developmentMedicinePregnancyPsychiatryPsychomotor learningCognitionRating scale

Abstract

fetched live from OpenAlex

Maternal sensitivity (MS), the ability to perceive and synchronously respond to the social signals (SSs), is affected by prematurity. The development of early supportive psychotherapy to foster MS, before discharge of the infant from the neonatal intensive care unit (NICU) is a major challenge in the prevention of subsequent developmental and mental disorders in the child. There are currently no reliable methods for evaluating MS to social interactions with very to moderate preterm infants. We investigated the reliability of a newly developed procedure for assessing MS in interactions between the mother and her 34- to 36-week postmenstrual age (PMA) preterm infant: the Preterm Infant Coding System for Maternal Sensitivity (PRICOSMAS). Method: This study encompassed three steps: testing of the capacity to videorecord SSs in very to moderate preterm infants, selection, by an expert committee, of the recordable and relevant SSs, and investigation of the internal consistency and interrater reliability. The synchronicity between infant and mother's SSs was determined on a 1 s period basis, using ELAN software. Preterm infants born after 25-weeks gestational age (GA) were included while being between 34- and 36-weeks PMA. A perinatal risk inventory score > 10 for the infant precluded from inclusion. Interrater reliabilities were assessed independently by two raters blind to the clinical situation of the mother and infant. Results: The resulting PRICOSMAS encompassed two four-item SS sections, one covering the preterm infant's SSs and the other, the mother's SSs. Reliability was assessed on a sample of 26 videorecorded observations for 13 mother-preterm infant dyads. Infants' mean age at birth was 30.4 ± 3.1-weeks GA (range: 26.4-35) and PMA at the time of the test was 34.7-weeks (±0.8). Internal consistency ranged from 0.81 to 0.89. Interrater reliability ranged from substantial to almost perfect (0.73-0.88). Conclusion: This study shows that the infants' SSs and MS can be reliably scored in preterm infants as young as 34- to 36-weeks PMA. Our findings suggest that the PRICOSMAS is sufficiently reliable for use, including in NICU, by healthcare professionals or researchers for coding early parent-infant interactions with 34- to 36-week PMA preterm infants.

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)0.028
metaresearch head score (Gemma)0.060
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.060
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.300
Teacher spread0.282 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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