The goal of this study is to evaluate how a Chatbot-based assistant can improve problem-solving skills and coping strategies in parents of children with Autism Spectrum Disorder (ASD).
A report by the World Health Organization reveals that Autism Spectrum Disorder (ASD), which is among the most prevalent and significant developmental disorders affecting children, is diagnosed in roughly one out of every 100 children around the world. This condition can cause a range of disabilities and changes in how a child communicates and interacts socially. Parenting a child with ASD is a continuous and demanding journey, often marked by heightened stress and mental health challenges for the caregivers. These parents must navigate an array of daily pressures, such as limited influence over their child's behaviors, concerns about the child's cognitive progress and their acquisition of adaptive skills, as well as the relentless requirements of caregiving and time management. They also grapple with worries regarding their bond with their child and the looming uncertainties about the child's long-term prospects. As children with ASD grow, their evolving needs can introduce new complexities. In comparison to parents of neurotypical children, those raising children with ASD encounter a significantly greater number of stress-inducing factors. The problem-solving ability is a key factor in helping parents cope with these stressors, improve their mental health, and have a positive impact on their child and other family members. There is a pressing need to find widely accepted interventions that can improve problem-solving skills and reduce distress in parents of children with ASD. Problem-Solving Skills Training (PSST) focuses on developing practical problem-solving abilities to enhance coping mechanisms and reduce psychological distress. Although PSST has demonstrated remarkable success in various populations, its application specifically for parents of children with ASD remains understudied. Given the unique challenges faced by ASD caregivers, there is a pressing need to investigate how PSST might be adapted and implemented to support this specific population's mental health and problem-solving capabilities. Considering the convenience, low cost and popularity of Chatbot, Chatbot-based PSST (C-PSST) will be administered in this study. A pilot study will be proposed to evaluate the effectiveness of C-PSST. A total of 20 caregivers of children will be recruited to receive the C-PSST and usual service. Through this proposed project, we shall determine (i) whether the C-PSST is acceptable and feasible for parents of children with ASD, (ii) whether it can improve problem-solving abilities and well-being, reduce depressive symptoms, and improve the quality of life in caregivers of children with ASD. The findings will provide evidence for C-PSST in Chinese caregivers, inform evidence-based practice to provide mental health support to caregivers of children with ASD, and provide essential guidance for practitioners (such as nurses and social workers), and policymakers to improve the quality of life in families of children with ASD.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Enrollment
20
The intervention incorporates eight sessions: Session 1 involves rapport building, understanding relevant personal and medical history, and introducing the Chatbot-based program and worksheet; Session 2 focuses on maintaining brightness and optimism when faced with a specific obstacle; Sessions 3-7 involve the continued application of problem-solving skills training(PSST) to identify problems and the promotion of problem-solving strategies and skills in vivo, including (a) identifying the problem, (b) determining the options, (c) evaluating and choosing the best option, (d) acting according to the best option, and (e) seeing if it works; and Session 8 involves a review of PSST principles and termination.
Hong Kong Metropolitan University
Hong Kong, Hong Kong
RECRUITINGFeasibility of the C-PSST
Feasibility will be assessed by 2 items modified from the Feasibility of Intervention Measure, and the semi-structured interview will be conducted immediately after the intervention. Barriers and facilitators to participant adherence and retention will be discussed to collect feedback. These 2 items will ask participants to evaluate that the Chatbot is implementable and easy to use via a 5-point Likert scale from completely disagree (1) to completely agree (5). The score range is 2 to 10 and higher scores indicate greater feasibility.
Time frame: After the intervention immediately
Acceptability of the C-PSST
Acceptability will be assessed through the following items: (i) the usage and repeated usage of the Chatbot by the participants in the trial indicated by logged user statistics; (ii) the number of times of login-errors and other login-problems. The higher usage and lower times of login-errors indicate greater acceptability
Time frame: After the intervention immediately
Problem-solving skills
Problem-solving skills will be measured by the Social Problem-Solving Inventory, Revised (SPSI-R)which is a widely recognized and validated scale with 52 items. A higher total score suggests a higher level of problem-solving skills.
Time frame: Baseline and after the intervention immediately
Stress
Stress will be assessed by a 10-item Perceived Stress Scale (PSS-10) with a 5-point Likert scale from never (0) to very often (4). The total score is from 0 to 40 and a higher score reflects a higher level of perceived stress.
Time frame: Baseline and after the intervention immediately
Depressive symptoms
Depressive symptoms will be measured by the Patient Health Questionnaire-9 (PHQ-9), which evaluates the frequency of occurrence of main depressive symptoms over the past 2 weeks via a 4-point Likert scale from not at all (0) to nearly every day (3). The total score is from 0 to 27 and the higher scores indicate more severe depressive symptoms.
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Time frame: Baseline and after the intervention immediately
Health Related Quality of life
Quality of life will be measured by the Chinese version of Short Form-12(SF-12), including 12 sub-scales. The sub-scale score can be represented as T-scores(mean =50, standard deviation =10) and a higher score indicating better QoL.
Time frame: Baseline and after the intervention immediately
Well-being
Well-being will be measured by the World Health Organization-5 Well-being Index to evaluate vitality (being active and waking up fresh and rested), being interested in things, and having a pleasant attitude. Each item is scored using a 6-point Likert scale from at no time (0) to all of the time (5). The total score ranges from 0 to 25, with higher scores suggesting better self-perceived well-being.
Time frame: Baseline and after the intervention immediately