Decisional Support Algorithm to Promote Youth Participation in Community Life
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Abstract
Background: Nearly 93 million children worldwide live with disabilities. Disparities in activity participation between children and youth with and without disabilities increase with age, resulting in fewer opportunities for children and youth with disabilities to prepare for healthy independent living in adulthood. Parents often manage their youth's activity participation on their own or with limited intervention support while balancing competing demands on their time. Parents need practical tools to efficiency develop, manage, and communicate their efforts to promote children's participation. The Participation and Environment Measure for Children and Youth (PEM-CY) is a valid and reliable parent-report survey that enables detailed assessment of children's participation in home, school, and community environments. Providers and parents have expressed their interest in using mobile technology to actively and feasibly develop their own plan of care using the PEM-CY. Towards this end, we need to know how the PEM-CY can be used to support collaborative goal setting and plan management within a clinical intervention or self-management context.
Objective: To characterize a decisional support algorithm that enables parents of children with disabilities and their providers to leverage their PEM-CY baseline results in order to systematically and feasibly prioritize needs, formulate goals, and develop intervention strategies to promote youth activity participation.
Methods: We employed an explanatory sequential mixed methods (quan>QUAL) design. The quantitative (quan) phase included PEM-CY completion by 23 parents of children with disabilities ages 5-17 years who were actively enrolled in community recreation services in Northern Colorado. For the qualitative (QUAL) phase, 7 service providers participated in 60-minute interviews to provide their perspectives about how PEM-CY results could be applied within an intervention planning context. Interview data were content coded by two research staff using NVivo 10.0. We used established procedures to ensure credibility (triangulation of 3 data sources, member-checking (n=3), key informants (n=40)), dependability (two coders for first 5 transcripts), and transferability (confirming study results across cases that differed by child's age and gender).
Results: A majority of respondents were mothers (90.9%) and between 40-49 years old (72.7%). Most children (mean age = 10.7 years) were Caucasian (77.3%) and male (69.8%). Based on PEM-CY results, more than two-thirds of parents were dissatisfied with their child's participation in community events (73.9%), organized and unstructured physical activities (73.9%), unstructured physical activities (73.9%), getting together with others (69.6%), and classes or lessons (73.9%). Provider perspectives of PEM-CY case results yielded a decisional process with five decision-making processes that result in three major steps: 1) a rank ordering of activities in which change is desired is developed by parent, considering the child's interests, abilities, and/or family schedule; 2) provider clarifies parent's goals for their child's participation for each ranked activity, especially if there is mismatch between the type of change desired and child's current participation; and 3) provider probes to identify those environmental supports and parent strategies that can be leveraged and environmental barriers that can be minimized to promote participation.
Conclusion: Results suggest that a core decisional process for applying PEM-CY results to generate an activity-specific action plan is possible. Confirmation of this decisional support algorithm with the end-user (i.e., parent) is needed. In addition, parent feedback on core and optional features of mobile technology to support use of the decisional support algorithm would be useful to develop functional specifications and wireframe of the mobile app.
Objective: To characterize a decisional support algorithm that enables parents of children with disabilities and their providers to leverage their PEM-CY baseline results in order to systematically and feasibly prioritize needs, formulate goals, and develop intervention strategies to promote youth activity participation.
Methods: We employed an explanatory sequential mixed methods (quan>QUAL) design. The quantitative (quan) phase included PEM-CY completion by 23 parents of children with disabilities ages 5-17 years who were actively enrolled in community recreation services in Northern Colorado. For the qualitative (QUAL) phase, 7 service providers participated in 60-minute interviews to provide their perspectives about how PEM-CY results could be applied within an intervention planning context. Interview data were content coded by two research staff using NVivo 10.0. We used established procedures to ensure credibility (triangulation of 3 data sources, member-checking (n=3), key informants (n=40)), dependability (two coders for first 5 transcripts), and transferability (confirming study results across cases that differed by child's age and gender).
Results: A majority of respondents were mothers (90.9%) and between 40-49 years old (72.7%). Most children (mean age = 10.7 years) were Caucasian (77.3%) and male (69.8%). Based on PEM-CY results, more than two-thirds of parents were dissatisfied with their child's participation in community events (73.9%), organized and unstructured physical activities (73.9%), unstructured physical activities (73.9%), getting together with others (69.6%), and classes or lessons (73.9%). Provider perspectives of PEM-CY case results yielded a decisional process with five decision-making processes that result in three major steps: 1) a rank ordering of activities in which change is desired is developed by parent, considering the child's interests, abilities, and/or family schedule; 2) provider clarifies parent's goals for their child's participation for each ranked activity, especially if there is mismatch between the type of change desired and child's current participation; and 3) provider probes to identify those environmental supports and parent strategies that can be leveraged and environmental barriers that can be minimized to promote participation.
Conclusion: Results suggest that a core decisional process for applying PEM-CY results to generate an activity-specific action plan is possible. Confirmation of this decisional support algorithm with the end-user (i.e., parent) is needed. In addition, parent feedback on core and optional features of mobile technology to support use of the decisional support algorithm would be useful to develop functional specifications and wireframe of the mobile app.
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