Cue Use in Distal Autism Spectrum Assessment: A Lens Model Analysis of the Efficacy of Telehealth Technologies

摘要

Recent developments in the field of telehealth suggest that novel technologies may ameliorate patients’limited access to clinicians capable of conducting ASD assessments (Koch, 2006). Specifically, studieshave shown that parents can capture informative behaviors that aid in autism assessment by using phonebasedapplications, and use of these videos result in diagnoses that are consistent with those of clinicianswho interact with the same child in person (Nazneen et al., 2015; Smith et al., In press). It is yet unknownhow clinicians make use of the information gleaned from videos uploaded to a store-and-forward system.Given that clinicians and physicians often exhibit bias in their use of available information, we sought tounderstand how cues were utilized when direct contact or observation of the patient is not possible. Weused lens model analyses to evaluate one store-and-forward approach: the Naturalistic ObservationDiagnostic Assessment (NODA; Smith et al., 2009). Brunswik’s (1952, 1955) lens model provides acomputational approach to evaluating use of information while formulating decisions (Karelaia & Hogarth,2008), such as in the assessment and diagnosis of ASD in children. The parents of 51 children used theNODA procedure to upload four 10-minute long videos depicting the child’s behavior in familiar in-homescenarios. Eleven children were typically developing, and the remaining 40 were seeking an Autismevaluation. Each child was observed twice: One clinician performed a standard in-person assessment(IPA), while the other performed an assessment via videos uploaded to the NODA tool. Observations for65 classes of behavior (e.g., limited conversation, speaking volume too loud, lack of peer play, echolalia,lining up toys, preoccupation with activity) were clustered into eight nominal variables representing theseven sub-criteria associated with ASD (American Psychiatric Association, 2013) and an additionalcriterion for behavior labeled as typical. We computed a count for each ASD variable that represented thefrequency with which the NODA clinician used the label when tagging the videos. Three pairs of linearregressions were run to estimate the weight clinicians placed on observations associated with each subcriterionfor ASD. Each pair of regressions consisted of one analysis where NODA tag counts wereregressed onto the decision made by the IPA clinician and another that regressed NODA tag counts ontothe NODA clinician’s decision. The three sets of regressions modeled the clinicians’ use of cues as anequal weight strategy, a conjunctive strategy, and a disjunctive strategy respectively. Our results suggestthat clinicians consistently derive their decisions from a limited number of the cues available to them, as noanalysis found more than two classes of observation to be predictive of diagnosis. Specifically, we foundthat IPA and NODA clinicians appeared to adopt a conjunctive rule, and relied most heavily on the numberof typical behaviors observed. We also found a high level of agreement between the IPA and NODAclinicians with respect to use of information and diagnosis. These findings suggests that there is no dearthof information available to clinicians for distal ASD assessment when observations are made through prerecordedvideo provided by parents via the NODA system as compared to IPA. The results of the reportedstudy illustrate the promise of telehealth technology adoption for distal patient assessment and diagnosis.