In total 20, 5–13 year-old participants with autism and their families were recruited through the Center for Autism and the Developing Brain (CADB) in White Plains, NY. Caregivers gave written consent; when possible, children 7 years and above assented. Weill Cornell Medicine’s IRB approved the study (#1405015095).

Participants and their caregivers completed an 8-week study consisting of home use of smartphones and clinic visits in weeks 1,4 and 8.3 In total 14 mothers, 3 fathers, 2 mothers & fathers, and 1 other family member completed the study. 55% had graduate degrees, 30% bachelor’s degrees, 5% some college and 10% high school diplomas.

Caregivers completed the Aberrant Behavior Checklist (ABC),4 Child Behavior Checklist (CBCL),5 Positive Affective and Negative Affective Scale (PANAS),6 Visual Analogue Scale (VAS) for anxiety and disruptive behavior during week 1 (T1) and week 8 (T2).

A designated caregiver installed the Janssen Autism Knowledge Engine (JAKE™) application during the first clinic visit.7 During weeks 1, 4 and 8, caregivers completed smartphone questions every day; during remaining weeks they answered questions at least 3 times per week. Questions addressed the child being tense/worried, irritable, and disruptive on an 8-point scale (0-very to 7-not at all) at the moment.

Data analysis

The internalizing subscale of the CBCL, the hyperactivity and irritability subscales of the ABC, the positive and negative mood scales of the PANAS and VAS for anxiety and disruptive behaviors were collected at T1 as representative of well documented standardized questionnnaires measuring roughly equivalent concepts. There were 456 responses on average per smartphone question. Mixed-effect ordinal logistic regression models assessed the consistency between caregiver report on the smartphone and questionnaires, with a subject-level random effect. A separate analysis included Day (1-up to 65), with a second analysis including Caregiver Education in the regression models. The clmm function from the ordinal package in R was used to fit the models (see Table 1 and Supplementary Table 1 for a summary of the regression models).

Total variance (TV) was computed for ordinal values for each smartphone question for each participant. TV was then calculated with only the first and last m days of data for a range of values of m. The correlation between TV and TV with data truncated at m day was computed for the range of truncation values m (Fig. 1). Pearson correlations, r, were computed between TV on the smartphone and paper questionnaires (Table 1).

Data availability

We will share the data upon reasonable request.