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Record W4411417844 · doi:10.1111/apa.70167

Small Wins for Small Babies: Celebrating Weekly Successes Helps Parents Cope With the <scp>NICU</scp> Hospitalisation

2025· article· en· W4411417844 on OpenAlexaff
Béatrice Boutillier, Fanny Labelle, Emilie Lancastre, Magali Rey‐Le Lorier, Christiane Lachambre, Annie Janvier

Bibliographic record

VenueActa Paediatrica · 2025
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineGratitudeOptimismFamily medicineIntervention (counseling)PediatricsPatienceNursingPsychologySocial psychology

Abstract

fetched live from OpenAlex

AIM: To describe the implementation and evaluation of an intervention to celebrate babies' weekly achievements in the neonatal unit (prolonged hospitalisations) and examine parental perspectives. METHODS: In a feasibility study, 92 parents reported the lack of optimism in the NICU, that clinicians often focused on what was going wrong; they recommended weekly celebration of accomplishments. The formats recommended were both physical (certificate given to parents) and virtual (text message). Inclusion criteria were baby > 1 week of life, likely survival, predicted hospitalisation > 1 month and parental consent. Parental perspectives were investigated using mixed methods with a questionnaire after discharge. RESULTS: The parents of 93 babies received weekly certificates (100% participation). The length of stay was on average 104 days, for a total of 1182 certificates/text messages received. 45% answered the questionnaire. The overall evaluation of parents was 9.1 of10; 88% reported it helped them cope with hospitalisation. Parental answers to open-ended questions were all positive and invoked gratitude, empowerment, patience and hope. CONCLUSION: Weekly text messages and certificates celebrating babies' accomplishments were appreciated and helped parents cope. It is possible to instil healthy optimism in the NICU.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.234
Teacher spread0.219 · 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.

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

Citations2
Published2025
Admission routes1
Has abstractyes

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