Autistic Innovative Assistant (AIA): an Android application for Arabic autism children

Sweidan, Saadeh Z.; Salameh, H. N. Bani; Zakarneh, Razan; Darabkh, Khalid A.

doi:10.1080/10494820.2019.1681468

Cited by 22 publications

(43 citation statements)

References 26 publications

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“…Of the 15 papers describing 15 unique studies ( Table 1 ), 4 were concerning participants with psychosis [ 13 - 16 ], 3 were concerning participants with eating disorders [ 17 - 19 ], 2 were concerning participants with depression [ 20 , 21 ], 2 were concerning participants with autism [ 22 , 23 ], 1 was concerning participants with substance abuse [ 24 ], 1 was concerning participants with suicidal behavior [ 25 ], 1 was concerning participants with self-harming behavior [ 26 ], and 1 was concerning participants with anxiety [ 27 ]. In all the included studies, participants were referred by external clinicians who had established the diagnosis or the need for treatment, and in 2 studies, the diagnoses were also validated by researchers at baseline [ 18 , 27 ].…”

Section: Resultsmentioning

confidence: 99%

“…Three studies had some participants older than 25 years but the clear majority of the participants were children, adolescents, or young adults, as demonstrated by the low mean age [ 14 , 15 , 19 ]. Four studies included only females [ 17 - 20 ], 2 did not provide information about gender [ 22 , 23 ], while the remaining studies included both genders. Of the 15 studies, 11 were published in 2017 or later [ 13 - 16 , 19 , 20 , 22 , 25 - 27 ].…”

Section: Resultsmentioning

confidence: 99%

“…Of the 15 studies, 11 were published in 2017 or later [ 13 - 16 , 19 , 20 , 22 , 25 - 27 ]. A total of 7 studies originated from the United States [ 14 , 15 , 20 - 22 , 24 , 25 ], 5 from Europe [ 13 , 17 - 19 , 26 ], 2 from Australia [ 16 , 27 ], and 1 from Jordan [ 23 ].…”

Section: Resultsmentioning

confidence: 99%

“…Of the 15 included studies, 3 were RCTs [ 13 , 19 , 25 ] investigating the effect of smartphone-based treatment interventions, 1 was a retrospective cohort study [ 18 ], 1 was an observational study [ 17 ], and the remaining were feasibility/pilot studies. The sample sizes of the included studies varied from 12 [ 16 ] to 100 [ 23 ] participants, with a mean (SD) sample size of 42.9 (26.5) participants.…”

Section: Resultsmentioning

confidence: 99%

“…One of the studies used an app that only administered treatment and did not use a monitoring system [ 23 ], 8 studies used a monitoring system and administered treatment [ 13 , 16 , 19 , 20 , 24 - 27 ], and the remaining 6 studies included monitoring only ( Table 2 ). In the 15 studies, there were 14 different smartphone apps, as 1 of them was used in 2 different studies [ 16 , 27 ].…”

Section: Resultsmentioning

confidence: 99%

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Smartphone-Based Self-Monitoring, Treatment, and Automatically Generated Data in Children, Adolescents, and Young Adults With Psychiatric Disorders: Systematic Review

et al. 2020

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Background Psychiatric disorders often have an onset at an early age, and early identification and intervention help improve prognosis. A fine-grained, unobtrusive, and effective way to monitor symptoms and level of function could help distinguish severe psychiatric health problems from normal behavior and potentially lead to a more efficient use of clinical resources in the current health care system. The use of smartphones to monitor and treat children, adolescents, and young adults with psychiatric disorders has been widely investigated. However, no systematic review concerning smartphone-based monitoring and treatment in this population has been published. Objective This systematic review aims at describing the following 4 features of the eligible studies: (1) monitoring features such as self-assessment and automatically generated data, (2) treatment delivered by the app, (3) adherence to self-monitoring, and (4) results of the individual studies. Methods We conducted a systematic literature search of the PubMed, Embase, and PsycInfo databases. We searched for studies that (1) included a smartphone app to collect self-monitoring data, a smartphone app to collect automatically generated smartphone-based data, or a smartphone-based system for treatment; (2) had participants who were diagnosed with psychiatric disorders or received treatment for a psychiatric disorder, which was verified by an external clinician; (3) had participants who were younger than 25 years; and (4) were published in a peer-reviewed journal. This systematic review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The risk of bias in each individual study was systematically assessed. Results A total of 2546 unique studies were identified through literature search; 15 of these fulfilled the criteria for inclusion. These studies covered 8 different diagnostic groups: psychosis, eating disorders, depression, autism, self-harm, anxiety, substance abuse, and suicidal behavior. Smartphone-based self-monitoring was used in all but 1 study, and 11 of them reported on the participants’ adherence to self-monitoring. Most studies were feasibility/pilot studies, and all studies on feasibility reported positive attitudes toward the use of smartphones for self-monitoring. In 2 studies, automatically generated data were collected. Three studies were randomized controlled trials investigating the effectiveness of smartphone-based monitoring and treatment, with 2 of these showing a positive treatment effect. In 2 randomized controlled trials, the researchers were blinded for randomization, but the participants were not blinded in any of the studies. All studies were determined to be at high risk of bias in several areas. Conclusions Smartphones hold great potential as a modern, widely available technology platform to help diagnose, monitor, and treat psychiatric disorders in children and adolescents. However, a higher level of homogeneity and rigor among studies regarding their methodology and reporting of adherence would facilitate future reviews and meta-analyses.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Smartphone-Based Self-Monitoring, Treatment, and Automatically Generated Data in Children, Adolescents, and Young Adults With Psychiatric Disorders: Systematic Review

et al. 2020

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SIAAA‐C: A student interactive assistant android application with chatbot during COVID‐19 pandemic

Sweidan

Laban

Alnaimat

et al. 2021

Comp Applic In Engineering

Self Cite

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Nowadays, smartphone applications (apps) are literally used in all life aspects, improving the quality of different services in addition to saving time and effort. However, the majority of currently used apps in different universities around the world are limited in their features and not very popular among students who may suffer to get useful information using traditional guiding methods. However, the importance of these apps is constantly increasing, especially in times of crises like the COVID-19 pandemic during which people were forced to work from home and the human interaction was reduced to its minimal degree. In this paper, we present a Student Interactive Assistant Android Application with Chatbot (SIAAA-C), which is basically a personal electronic guide that is used by students to get various and effective academic services.The app has a number of useful features including a campus map, multiple types of notifications, and most important, an efficient built in chatbot that responds to both Arabic and English written queries and covers a wide range of academic topics ranging from basic to complex. Even more, SIAAA-C was designed to have Arabic and English interfaces to be used in the University of Jordan (UoJ), which has one of the biggest campuses in the Arabic area with more than 40,000 local and foreign students. Moreover, SIAAA-C was practically tested in a real-life environment by a group of UoJ students who were selected from different faculties during the pandemic peak period and the feedbacks were very promising, based on the outcomes of an evaluation survey that was answered by 102 students after a 1-month test period.

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Adaptive E-learning to Improve Communicative Skills of Learners with Autism Spectrum Disorder Using Eye Tracking and Machine Learning

Lhafra,

Abdoun

2024

Lecture Notes in Networks and Systems

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Autistic Innovative Assistant (AIA): an Android application for Arabic autism children

Cited by 22 publications

References 26 publications

Smartphone-Based Self-Monitoring, Treatment, and Automatically Generated Data in Children, Adolescents, and Young Adults With Psychiatric Disorders: Systematic Review

Smartphone-Based Self-Monitoring, Treatment, and Automatically Generated Data in Children, Adolescents, and Young Adults With Psychiatric Disorders: Systematic Review

SIAAA‐C: A student interactive assistant android application with chatbot during COVID‐19 pandemic

Adaptive E-learning to Improve Communicative Skills of Learners with Autism Spectrum Disorder Using Eye Tracking and Machine Learning

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