A Pilot Exploratory Study to Form Subgroups Using Cluster Analysis of Family Needs Survey Scores for Providing Tailored Support to Parents Caring for a Population-Based Sample of 5-Year-Old Children with Developmental Concerns.

In a population-based developmental screening program, healthcare providers face a practical problem with respect to the formation of groups to efficiently address the needs of the parents whose children are screened positive. This small-scale pilot study explored the usefulness of cluster analysis to form type-specific support groups based on the Family Needs Survey (FNS) scores. All parents (N = 68), who accompanied their 5-year-old children to appointments for formal assessment and diagnostic interviews in the second phase of screening, completed the FNS as part of a developmental questionnaire package. The FNS scores of a full dataset (N = 55) without missing values were subjected to hierarchical and K-means cluster analyses. As the final solution, hierarchical clustering with a three-cluster solution was selected over K-means clustering because the hierarchical clustering solution produced three clusters that were similar in size and meaningful in each profile pattern: Cluster 1-high need for information and professional support (N = 20); Cluster 2-moderate need for information support (N = 16); Cluster 3-high need for information and moderate need for other support (N = 19). The range of cluster sizes was appropriate for managing and providing tailored services and support for each group. Thus, this pilot study demonstrated the utility of cluster analysis to classify parents into support groups, according to their needs.