Feasibility of a smartphone application to identify young children at risk for Autism Spectrum Disorder in a low-income community setting in South Africa
| dc.contributor.advisor | de Vries, Petrus J | |
| dc.contributor.author | Kümm, Aubrey Jonathan | |
| dc.date.accessioned | 2019-02-06T09:51:15Z | |
| dc.date.available | 2019-02-06T09:51:15Z | |
| dc.date.issued | 2018 | |
| dc.date.updated | 2019-02-06T06:33:30Z | |
| dc.description.abstract | Introduction and aims More than 90% of children with Autism Spectrum Disorder (ASD) live in low- and middle-income countries (LMIC) where there is a great need for culturally appropriate, scalable and effective early identification and intervention tools. Smartphone technology and application (‘apps’) may potentially play an important role in this regard. The Autism&Beyond iPhone App was designed as a potential screening tool for ASD risk in children aged 12-72 months. Here we investigated the technical feasibility and cultural acceptability of a smartphone app to determine risk for ASD in children aged 12-72 months in a naturalistic, low-income South African community setting. Methodology 37 typically-developing African children and their parents/carers were recruited from community centres in Khayelitsha Township, Cape Town, South Africa. We implemented a mixed-methods design, collecting both quantitative and qualitative data from participants in 2 stages. In stage 1, we collected quantitative data. With appropriate ethics and consent, parents completed a short technology questionnaire about their familiarity with and access to smartphones, internet and apps, followed by electronic iPhone-based demographic and ASD-related questionnaires. Next, children were shown 3 short videos of 30s each and a mirror stimulus on a study smartphone. The smartphone front facing (“selfie”) camera recorded video of the child’s facial expressions and head movement. Automated computer algorithms quantified positive emotions and time attending to stimuli. We validated the automatic coding by a) comparing the computer-generated analysis to human coding of facial expressions in a random sample (N=9), and b) comparing automated analysis of the South African data (N=33) with a matched American sample (N=33). In stage 2, a subset of families were invited to participate in focus group discussions to provide qualitative data on accessibility, acceptability, and cultural appropriateness of the app in their local community. Results Most parents (64%) owned a smartphone of which all (100%) were Android based, and many used Apps (45%). Human-automated coding showed excellent correlation for positive emotion (ICC= 0.95, 95% CI 0.81-0.99) and no statistically significant differences were observed between the South African and American sample in % time attending to the video stimuli. South African children, however, smiled less at the Toys&Rhymes (SA mean (SD) = 14% (24); USA mean (SD) = 31% (34); p=0.05) and Bunny video (SA mean (SD) = 12% (17); USA mean (SD) = 30% (0.27); p=0.006). Analysis of focus group data indicated that parents/carers found the App relatively easy to use, and would recommend it to others in their community provided the App and data transfer were free. Conclusion The results from this pilot study suggested the App to be technically accurate, accessible and culturally acceptable to families from a low-resource environment in South Africa. Given the differences in positive emotional response between the groups, careful consideration should be given to identify suitable stimuli if % time smiling is to be used as a global marker for autism risk across cultures and environments. | |
| dc.identifier.apacitation | Kümm, A. J. (2018). <i>Feasibility of a smartphone application to identify young children at risk for Autism Spectrum Disorder in a low-income community setting in South Africa</i>. (). University of Cape Town ,Faculty of Health Sciences ,Division of Child & Adolescent Psychiatry. Retrieved from http://hdl.handle.net/11427/29355 | en_ZA |
| dc.identifier.chicagocitation | Kümm, Aubrey Jonathan. <i>"Feasibility of a smartphone application to identify young children at risk for Autism Spectrum Disorder in a low-income community setting in South Africa."</i> ., University of Cape Town ,Faculty of Health Sciences ,Division of Child & Adolescent Psychiatry, 2018. http://hdl.handle.net/11427/29355 | en_ZA |
| dc.identifier.citation | Kümm, A. 2018. Feasibility of a smartphone application to identify young children at risk for Autism Spectrum Disorder in a low-income community setting in South Africa. University of Cape Town. | en_ZA |
| dc.identifier.ris | TY - Thesis / Dissertation AU - Kümm, Aubrey Jonathan AB - Introduction and aims More than 90% of children with Autism Spectrum Disorder (ASD) live in low- and middle-income countries (LMIC) where there is a great need for culturally appropriate, scalable and effective early identification and intervention tools. Smartphone technology and application (‘apps’) may potentially play an important role in this regard. The Autism&Beyond iPhone App was designed as a potential screening tool for ASD risk in children aged 12-72 months. Here we investigated the technical feasibility and cultural acceptability of a smartphone app to determine risk for ASD in children aged 12-72 months in a naturalistic, low-income South African community setting. Methodology 37 typically-developing African children and their parents/carers were recruited from community centres in Khayelitsha Township, Cape Town, South Africa. We implemented a mixed-methods design, collecting both quantitative and qualitative data from participants in 2 stages. In stage 1, we collected quantitative data. With appropriate ethics and consent, parents completed a short technology questionnaire about their familiarity with and access to smartphones, internet and apps, followed by electronic iPhone-based demographic and ASD-related questionnaires. Next, children were shown 3 short videos of 30s each and a mirror stimulus on a study smartphone. The smartphone front facing (“selfie”) camera recorded video of the child’s facial expressions and head movement. Automated computer algorithms quantified positive emotions and time attending to stimuli. We validated the automatic coding by a) comparing the computer-generated analysis to human coding of facial expressions in a random sample (N=9), and b) comparing automated analysis of the South African data (N=33) with a matched American sample (N=33). In stage 2, a subset of families were invited to participate in focus group discussions to provide qualitative data on accessibility, acceptability, and cultural appropriateness of the app in their local community. Results Most parents (64%) owned a smartphone of which all (100%) were Android based, and many used Apps (45%). Human-automated coding showed excellent correlation for positive emotion (ICC= 0.95, 95% CI 0.81-0.99) and no statistically significant differences were observed between the South African and American sample in % time attending to the video stimuli. South African children, however, smiled less at the Toys&Rhymes (SA mean (SD) = 14% (24); USA mean (SD) = 31% (34); p=0.05) and Bunny video (SA mean (SD) = 12% (17); USA mean (SD) = 30% (0.27); p=0.006). Analysis of focus group data indicated that parents/carers found the App relatively easy to use, and would recommend it to others in their community provided the App and data transfer were free. Conclusion The results from this pilot study suggested the App to be technically accurate, accessible and culturally acceptable to families from a low-resource environment in South Africa. Given the differences in positive emotional response between the groups, careful consideration should be given to identify suitable stimuli if % time smiling is to be used as a global marker for autism risk across cultures and environments. DA - 2018 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2018 T1 - Feasibility of a smartphone application to identify young children at risk for Autism Spectrum Disorder in a low-income community setting in South Africa TI - Feasibility of a smartphone application to identify young children at risk for Autism Spectrum Disorder in a low-income community setting in South Africa UR - http://hdl.handle.net/11427/29355 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/29355 | |
| dc.identifier.vancouvercitation | Kümm AJ. Feasibility of a smartphone application to identify young children at risk for Autism Spectrum Disorder in a low-income community setting in South Africa. []. University of Cape Town ,Faculty of Health Sciences ,Division of Child & Adolescent Psychiatry, 2018 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/29355 | en_ZA |
| dc.language.iso | eng | |
| dc.publisher.department | Division of Child and Adolescent Psychiatry | |
| dc.publisher.faculty | Faculty of Health Sciences | |
| dc.publisher.institution | University of Cape Town | |
| dc.subject.other | Neuroscience | |
| dc.title | Feasibility of a smartphone application to identify young children at risk for Autism Spectrum Disorder in a low-income community setting in South Africa | |
| dc.type | Master Thesis | |
| dc.type.qualificationlevel | Masters | |
| dc.type.qualificationname | MSc (Med) |