Using latent class analysis to identify treatment-use subgroups among parents of children with autism spectrum disorder.
Parents of autistic kids sort into six income-tied service groups—know the group before you prescribe.
01Research in Context
What this study did
The team looked at 2,582 families of kids with autism. They used a stats tool called latent class analysis. The goal was to see if parents fall into clear groups based on how many treatments they chase.
They also checked family income, child regression history, and daily-living scores.
What they found
Six parent groups popped out. Income shaped every group. The highest-intensity users had kids who lost skills early and scored low on daily tasks.
Low-income families were rare in the high-intensity group even when kids had high needs.
How this fits with other research
Day et al. (2021) extends this picture. They show race, income, and schooling shape how parents view autism itself, not just service use. Put together, the two papers say: check money and background first, then tailor advice.
Bora et al. (2017) used the same latent-class trick on Autism Quotient scores. They found two parent types based on social-communication traits. Bergmann et al. (2019) adds a new layer: parent action, not just parent traits, sorts families into six boxes.
Georgiades et al. (2014) also used latent classes, but on child symptoms. They found a small group whose traits fade by age six. Bergmann et al. (2019) flips the lens to parents and finds stable, income-glued service patterns. Same method, different direction.
Why it matters
Before you list ten therapy options, ask two quick questions: What does the family earn, and which of the six parent profiles fits them? High earners with kids who lost skills will chase every service. Low earners in the same boat may need funding links, not more brochures. Match your plan to the profile and you save everyone time.
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02At a glance
03Original abstract
Among parents of 2,582 children (ages 4-17 years old) with autism spectrum disorder (ASD), we used latent class analysis to identify subgroups and profiles of treatment users and included annual household income in the specification of the models, then described characteristics of each subgroup. Based on three indicators of fit (Akaike's Information Criterion, Bayesian Information Criterion, and Lo-Mendell-Rubin), six latent classes of treatment users emerged. Subgroups included users of: (a) mostly private and school speech and occupational therapies; (b) nearly all treatment types; (c) mostly speech and occupational therapies, plus intensive behavioral and "other" treatments, but little medication use; (d) private therapies almost exclusively; (e) primarily psychotropic medications; and (f) mostly school-based therapies. Income significantly predicted class differences for all but one latent class. Probabilities of families' lifetime use of nine treatment types varied depending on latent classification. Proportions of families reporting having observed children's developmental regression were largest in those with the highest overall treatment use, and these children also had the lowest cognitive and adaptive-functioning scores and the highest ASD symptom scores. Understanding patterns of treatment use among families of children with ASD is an important first step in enhancing treatment-related selection and implementation. Autism Research 2019, 12: 843-854. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: We identified six different groups of treatment users to help explain patterns in treatment implementation among parents of children and adolescents with autism. These included families who used: (a) mostly used private and school speech and occupational therapies; (b) nearly all treatment types (private and school therapies, intensive behavioral, biomedical, psychotropic medications, and other treatments); (c) mostly speech and occupational therapies, plus intensive behavioral and "other" treatments, but little medication use; (d) private therapies almost exclusively; (e) primarily psychotropic medications; and (f) mostly school-based therapies.
Autism research : official journal of the International Society for Autism Research, 2019 · doi:10.1002/aur.2107