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Relationships of Equipment Use and Play Positions to Motor Development at Eight Months Corrected Age of Infants Born Preterm

2003· article· en· W1973153840 on OpenAlexaffabout
Doreen J. Bartlett, Jamie E. Kneale Fanning

Bibliographic record

VenuePediatric Physical Therapy · 2003
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsWestern UniversitySt Joseph's Health Centre
Fundersnot available
KeywordsSittingSupine positionMotor skillMedicinePediatricsDevelopmental psychologyPsychologyAnesthesia

Abstract

fetched live from OpenAlex

In Brief Purpose The purpose of this study was to determine the relationship between both use of infant equipment and play positions and motor development of infants born preterm who were classified as high risk. Subjects were 60 parent-infant dyads attending a developmental follow-up clinic. Methods Parents reported the duration of infant equipment use and the predominant positions in which their infants played in the previous month. Infants were assessed using the Alberta Infant Motor Scale (AIMS). Results Equipment use was not related to motor development; however, the duration of carrying was negatively related to the sit subscale of the AIMS (r = −0.31, p < 0.05). As a group, the infants in this sample spent more time in the relatively less active play positions of sitting and supine than in the positions of prone and standing. Conclusions Therapists should consider the use of equipment and specific play positions to enhance motor development of infants born preterm and work with parents to promote an understanding of the importance of providing their infants with opportunities to develop early motor competencies. Infants in this study spent more time in the less active play positions of sitting and supine than in prone and standing. Therapists should encourage parents to use equipment and specific play positions to enhance motor development of infants born born preterm.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.066
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.034
GPT teacher head0.268
Teacher spread0.235 · 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

Citations62
Published2003
Admission routes2
Has abstractyes

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