Parenting stress in caregiver-mediated interventions for toddlers with autism: An application of quantile regression mixed models.
Hands-on parent training for toddlers with autism briefly raises parent-related stress—plan a check-in right after training ends.
01Research in Context
What this study did
Schlink et al. (2022) split parents of toddlers with autism into two groups. One group sat in a room and learned about autism. The other group practiced play skills with their child while a coach guided them.
The team tracked stress every few weeks for six months. They used a fancy stats tool called quantile mixed models. This let them see who got better, who got worse, and who stayed the same.
What they found
Child-related stress dropped in both groups. Parents felt less bothered by meltdowns and picky eating no matter which class they took.
Parent-related stress told a different story. The hands-on group saw a short jump in stress right after training ended. The jump faded by the next check-in.
How this fits with other research
Argumedes et al. (2018) also showed parent training lowers stress when child behaviors improve. Their study used family-centered support instead of direct coaching, but the end point matches: fix behaviors, ease stress.
Davis et al. (2008) warned that toddler autism itself is stressful. They surveyed parents without any treatment. Andrew’s work shows stress can move once you do something, not just describe it.
Fullana et al. (2007) looked at ABA hours and found more therapy linked to less maternal depression. Yet they also saw higher parent strain when moms joined sessions. Andrew’s short bump in parent-related stress echoes that same strain pattern.
Why it matters
You can warn families that hands-on coaching may feel harder for a few weeks. Schedule a booster call or stress check two weeks after training ends. That small step can keep parents engaged until the stress dip arrives.
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02At a glance
03Original abstract
Traditional longitudinal modeling approaches require normally distributed data and do not account for sample heterogeneity. Parenting stress, in particular, can be difficult to model across time without transforming the data as it is usually high for caregivers of children with ASD. This study used novel linear quantile mixed models (LQMMs) to model non-normal parent stress scores across two caregiver-mediated interventions involving toddlers with ASD. The sample included 86 caregiver-child dyads who were randomized to either a parent-only psychoeducational intervention or hands-on parent training in a naturalistic developmental intervention. Child and parent-related domains of the Parenting Stress Index (PSI) were the primary outcomes in this study. The PSI was collected at entry, 10-week exit, 3-month follow-up, and 6-month follow-up periods. Separate LQMMs were used to model five specific quantiles ( τ=0.1,0.25,0.5,0.75,and0.9) of the two PSI domains across the complete intervention timeline. These five quantiles effectively modeled the entire conditional distribution of parenting stress scores. The LQMMs indicated that child-related parenting stress decreased across all quantiles within both interventions, with no difference in the rate of parenting stress change between the intervention groups. For parent-related parenting stress, the effect of intervention depended on the group's stress level; some parents increased their perceived stress within the hands-on intervention at the 3-month follow-up. Overall, this study demonstrated that the use of LQMMs yielded additional information, beyond traditional longitudinal models, regarding the relationship between parenting stress within two caregiver-mediated intervention protocols. This study also discussed the methodological contributions and potential future applications of LQMMs. LAY SUMMARY: This study used a newer longitudinal modeling technique to examine how parenting stress changed across two caregiver-mediated interventions for toddlers with ASD. Results showed that certain parents in the JASPER condition might require additional support as they exit the study and enter into their first follow-up period. It was also determined that this new modeling technique could be a valuable tool to analyze highly variable data often present in ASD intervention studies.
Autism research : official journal of the International Society for Autism Research, 2022 · doi:10.1097/01.chi.0000205701.48324.26