Purpose: Describe practice interests and priorities in addressing healthy lifestyle-related care (i.e., nutrition, physical activity, balanced screen use, and sleep) among children with autism spectrum disorder (ASD) among medical professionals and parents.

Methods: This qualitative study utilized in-depth interviews to compare, contrast, and describe the perspectives of interdisciplinary medical professionals and parents of autistic children regarding healthy lifestyle-related care for children with ASD. Using an open-ended semi-structured interview guide, participants were asked to identify priorities for healthy lifestyle care, barriers/facilitators to care, and desired resources for education and support. Interviews were audio-recorded, transcribed, verified by researchers, and double coded using the constant comparative method. All study participants resided in California in the United States.

Results: A variety of medical professionals (n=21) participated in the study and included developmental pediatricians, occupational therapists, speech-language pathologists, board certified behavior analysts, and registered dietitian nutritionists. Parents also participated (n=25) and described their children with ASD whose ages ranged between 3-15 years (mean=6.8 years). About half of parents identified as Latinx/Hispanic. Several key themes emerged during the study. Medical professionals specifically attributed a lack of knowledge, insufficient training, time-constraints, and parental limitations as barriers to offering care, particularly related to nutrition. Parents expressed distress about some providers’ understanding of day-to-day behavioral challenges associated with autism, and thus being unable to give realistic advice. Most parents identified an urgent need to address sleep and child feeding as priorities for care, while providers indicated that poor growth or major behavioral/mental health challenges would likely be the only reason to initiate care. Both groups described a lack of awareness of qualified professionals or accessible referral networks and an inability to identify evidence-based resources to address healthy lifestyle care for this population.

Conclusions:Future research should continue to explore how to adapt and enhance clinical practice to address the unique needs of all children with neurodevelopmental disabilities, including autism. Interdisciplinary medical providers may benefit from training to better understand the needs of families and to help them problem-solve and prioritize areas for care, especially for issues that impact quality of life, such as selective eating and sleep.

Purpose: Describe the process of adapting telehealth coaching in an evidence-based intervention to improve physical activity engagement, nutrition and sleep habits among youth with psychiatric and neurodevelopmental diagnoses (PND), as well as lessons learned for future research and practice.

Methods: Using an inclusion team science framework, telehealth coaches were trained using an interactive workshop and scripts to implement a pilot study among youth with heterogeneous PND including autism; the telehealth intervention was previously developed and tested in typically developing (TD) children with overweight/obesity.  Coaches were interviewed using an open-ended semi-structured interview guide after the pilot intervention was completed to evaluate their experiences and identify areas for improvement. Interviews were audio-recorded and transcribed, and emergent themes were identified by the research team.

Results: All coaches implementing the intervention participated in interviews (n=4, all male).  One reported previous experience working with children with developmental disabilities; none had worked with youth with other psychiatric diagnoses. All coaches reported that training they received prior to working with study participants (n=11, ages 10-17) prepared them well; they were able to engage participants with PND in sessions as well as TD participants.   Several coaches reported concerns about working with children with PND prior to intervention but quickly built rapport with participants and enjoying the coaching experience. Two reported the most important adaptation was increased use of positive behavioral reinforcement with the PND population. All coaches found that parent engagement and child age were important predictors of health habit change over the course of the intervention. Three coaches mentioned needing more flexibility from the coaching scripts to better engage participants with PND. Finally, all coaches reported that use of the technologies in the intervention (Xbox-based exergames, Skype, and Fitbits) was more challenging for participants with PND when compared to implementation among TD participants. 

Conclusions:  Telehealth coaching to improve health habits among youth with heterogeneous PND is feasible with specific adaptations and targeted coach training. Creating models for adaptive telehealth coaching using an inclusion team science framework may be useful for integrating physical activity, nutrition and sleep intervention into clinical treatment plans for youth with PND.

Purpose: Children with Autism Spectrum Disorders (ASD) tend to have sensory disturbances and behavioral rigidity which may predispose them to be selective in their food intake, potentially compromising their nutritional status. While ASD diagnoses capture severe levels of impairment, autistic traits vary on a continuum throughout the general population. Yet, little is known about how subclinical autistic traits relate to dietary intake. This study, therefore, examines how autistic traits throughout early childhood are associated with diet quality (DQ) in mid-childhood, and explores the mediating role of food selectivity.

Methods: Participants were children (n=4061) from the population-based birth cohort, the Generation R Study (the Netherlands). Parents completed assessments on their child’s autistic traits at 1.5, 3 and 6 years, food selectivity at 4 years and food intake at 8 years (via a Food Frequency Questionnaire), from which a DQ score (comprising 10 food groups, scale 0 to 10) was derived based on adherence to age-specific dietary guidelines. Multiple linear regression models examined the association between autistic trait SD score at each assessment wave and DQ. A mediation analysis was performed using structural equation modeling to examine the indirect effect of autistic traits at 3 years and DQ at 8 years through food selectivity at 4 years. Models adjusted for child sex, age, energy intake, ethnicity, birth weight, BMIz score, and maternal age and education.

Results: Autistic trait SD score at each wave was inversely associated with DQ (e.g. 3 years: β= -0.06; 95% CI: -0.10, -0.03). Post-hoc analyses showed that associations between autistic traits and DQ were consistently driven by lower scores on fruit, vegetable and whole grain food groups at each wave. The indirect effect of food selectivity (β = -0.03, 95% CI: -0.03, -0.02) explained 60% of the total association between autistic traits and DQ.

Conclusions: Expression of autistic traits across childhood is associated with poorer DQ in mid-childhood, and food selectivity may be one key behavioral mechanism explaining this association. Dietary interventions intended to optimize nutrition in children with elevated autistic traits may integrate behavioral strategies to support parents’ appropriately responding to and managing food selectivity.