Abstract
User experiences are essential to the adoption of an intervention and can be integral to intervention design. We applied two concepts from the technology acceptance model (i.e., perceived ease of use, perceived utility) to understand how mental health professionals experienced a novel system of resources (i.e., engagement system) designed to improve problem identification, coordination, and treatment planning decisions related to addressing problems of low treatment engagement in school mental health services. We conducted a 1-hour focus group with 10 mental health professionals (provider n = 8, supervisor n = 2) using prompts to elicit their perspectives about the effort involved in using the engagement system and about the usefulness of the system in their work. The focus group was transcribed and segmented into 70 excerpts by trained coders. We analyzed the transcript using a consensual qualitative research approach. Ease of use was coded in 15 (39%) excerpts and utility was coded in 24 (61%) excerpts. The valences of excerpts were neutral (n = 18; 46%), positive (n = 10; 26%), and negative (n = 11; 28%). Thirty-nine (56%) excerpts discussed the engagement system. Excerpts pertained to problem identification (n = 18; 46%), coordination (n = 18; 46%), and treatment planning (n = 3; 8%). Findings revealed that resources and procedures were rated differently on their perceived ease of use and utility. Participants reported that the coordination resource had high utility and positively impacted their clinical practice and supervision, while the problem identification resources had low ease of use and were burdensome or difficult to use. Some lessons learned include the value of designing resources that provide structure to clinical decision processes yet allow for some flexibility, the need for simpler and automated procedures to reduce provider burden, and the importance of clear guidelines on how resources should and should not be used. We used this feedback to inform changes to the engagement system prior to testing in a randomized trial. This brief report highlights how applying the technology acceptance model to evaluate interventions can aid in the successful implementation of novel clinical interventions.
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