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Record W7120573061

Assessment of motor development in children from birth to eighteen months

2013· dissertation· pt· W7120573061 on OpenAlexaboutno aff
Larissa Paiva Silva

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2013
Typedissertation
Languagept
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
Fundersnot available
KeywordsChristian ministryChild developmentMotor skillScale (ratio)Socioeconomic statusData collectionPopulationToddler
DOInot available

Abstract

fetched live from OpenAlex

The accompaniment of infant development is considered one of the most important initiatives to reach a better quality of life. We sought to evaluate motor development in babies aged zero to 18 months. This is a descriptive, transversal and evaluative study performed in Health Family Centers (CSF) of the municipalities of Fortaleza and Sobral CE), Brazil. The sample was composed of 330 children, 165 from each studied municipality. Data collection took place between February/March 2012 through a predetermined form with child and family variables using the Alberta Infant Motor Scale (AIMS), Portuguese version and the Ministry of Health Control Protocol included in the Child Health Booklet (CSC), after approval granted by the Research Ethics Committee. According to results, in the Fortaleza municipality, most children were females born through cesarean section whereas in Sobral there was a predominance of males and natural births. In Fortaleza, 7.2% of children were premature and 6.6% had lower weight at birth while in Sobral, 8.5% were premature and 8.5% were born with low weight. As for the socioeconomic and educational profile of children’s parents/tutors, we found that in both municipalities the majority of them had 11 to 13 years of study, were aged 22 to 35 and did not have a paid occupation. With regards to their socio-demographic profile, most of them had basic sanitation, garbage collection service and ceramic floors. Child motor development was evaluated through the AIMS scale in both municipalities and it was considered normal for most children (307). This was corroborated by the second evaluation, made by the Ministry of Health Control Protocol (CSC) (302 children). The analysis of both documents showed agreement between them, however weak (k=0096; 0.077). When analyzing both results separately, we noticed more concordance among development deficit items. Different evaluation items were identified as “With deficit” or Without Deficit”, resulting in an almost perfect concordance (k=0.879; 0.910) between both instruments. There was also an important connection between the gestational age (p=0.012; 0.000) and the weight at birth (p=0.000; 0.000), considering the complete sample for both documents. We also found a relevant concordance between motor development when considering the full sample and risks factors associated to hospitalization, oxygen therapy and phototherapy. The maternal age showed a significant correlation in Fortaleza (p=0.001; 0.004). The analysis of the full sample (p=0.017; 0.016), the marital status (p=0.054; 0.049) and paid occupations in Sobral (p=0.003; 0.013), also resulted to be closely related to the scale qualifications. As for socio-demographic data, no statistically significant associations were found with regards to development levels according to the evaluation instruments. There was no difference between the children’s motor performance in the two studied municipalities. Both instruments presented high concordance levels in deficit detection and a significant correlation with infant mobility considering the following variables: gestational age, weight at birth, hospitalization, oxygen therapy, phototherapy, maternal age, marital status and mother paid occupation.

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)0.002
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.014
GPT teacher head0.257
Teacher spread0.243 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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