Article

Longitudinal research on gross motor percentile rank scores of
children with typical development has documented intra-individual variability of
scoring patterns. Clinically, interpreting these fluctuations presents a
challenge for therapists. The aim of this study was to determine the
utility of cluster analysis as a technique to organize the gross motor scoring
patterns of children with typical development into clinically relevant groups.
This was a descriptive, exploratory study using data from 2 longitudinal
studies. PARTICIPANTS: Sixty-six children with typical development participated
in the study. METHODS: The children were assessed on the gross motor subscale of
the Peabody Developmental Motor Scales at 9, 11, 13, 16, and 21 months of age and
on the gross motor subscale of the Peabody Developmental Motor Scales, 2nd
edition, at 4, 4.5, 5, and 5.5 years of age. Demographic and health data were
collected. Parents were interviewed when the children were 8 years of age.
Cluster analysis was conducted. Demographic and health data were compared across
clusters. RESULTS: Four distinct and clinically relevant clusters were
identified. A significant difference was found among the clusters for total
number of illnesses. LIMITATIONS: The children in these analyses were at low risk
for gross motor problems. Further research with a more high-risk sample is needed
to validate the clinical utility of the identified clusters. CONCLUSIONS: Cluster
analysis techniques may offer a mechanism to explore longitudinal data in
physical therapy research. The techniques provided a mechanism to group data
without losing the richness of information provided by the intra-individual
variability of scoring patterns. Clinically, examination of distinct scoring
patterns may lead to improved accuracy in screening for gross motor concerns
compared with the traditional use of single-assessment cutoff points.

Langue : ANGLAIS