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Record W7011364915

Maternal-infant Predictors of Attendance at Neonatal Follow-up Programs

2010· dissertation· en· W7011364915 on OpenAlexfundaboutno aff

Bibliographic record

VenueTSpace · 2010
Typedissertation
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
FundersHealth Canada
KeywordsAttendancePsychosocialReferralLongitudinal studyCohortCohort study
DOInot available

Abstract

fetched live from OpenAlex

Attendance at Neonatal Follow-up (NFU) programs is crucial for parents to gain access to timely diagnostic expertise, psychosocial support, and referral to needed services for their infants. Although NFU programs are considered beneficial, up to 50% of parents do not attend these programs with their infants. Non-attending infants have poorer outcomes (e.g., higher rates of disabilities and less access to required services) as compared to attenders. \nThe purpose was to determine factors that predicted attendance at NFU. Naturally occurring attendance was monitored and maternal-infant factors including predisposing, enabling, and needs factors were investigated, guided by the Socio-Behavioral Model of Health Services Use. \nA prospective two-phase multi-site descriptive cohort study was conducted in 3 Canadian Neonatal Intensive Care Units that refer to 2 NFU programs. In Phase 1, standardized questionnaires were completed by 357 mothers (66% response rate) prior to their infant’s (N= 400 infants) NICU discharge. In Phase 2, attendance patterns at NFU were followed for 12 months.\nHigher maternal stress at the time of the infant’s NICU hospitalization was predictive of attendance at NFU. Parenting alone, more worry about maternal alcohol or drug use, and greater distance to NFU were predictive of non-attendance at NFU. Attendance at NFU decreased over time from 84% at the first appointment to 74% by 12 months. Two distinct attendance patterns emerged: no or minimal attendance (18.5%) and attendance at all or the majority of scheduled appointments (81.5%). The most frequent point of withdrawal from NFU occurred between NICU discharge and the first scheduled appointment; followed by drop-out following the first NFU appointment. \nThese results provide new insight into patterns of attendance and the maternal-infant factors that characterize attenders/non-attenders at NFU and serve as the critical first step in developing interventions targeted at improving attendance, infant outcomes, and reporting of developmental sequelae.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.166
Threshold uncertainty score0.329

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.290
Teacher spread0.279 · 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

Citations2
Published2010
Admission routes2
Has abstractyes

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