This pilot study tested the use of a best-worst scaling (BWS) instrument to aid caregivers of a child with mental health comorbidities in clarifying preferences for treatment outcomes. BWS methodology closely approximates real-life decision-making by requiring the selection of one “most important” and one “least important” among a group of competing attributes. 38 caregivers were recruited from support groups in Maryland from March through July of 2015. Criteria for participation were a) their child was 21 years or younger, b) was diagnosed with a developmental delay related to cognitive or emotional disability and, c) with a comorbid mental illness (i.e. ADHD, depression, anxiety, etc.). Subsequent to survey completion, the caregivers took part in one of 6 debriefing sessions to determine the ease of comprehension, relevance of the concepts, distinctiveness of the statements, and clarity of language. The dataset includes family demographics, child characteristics (diagnoses, type of treatment, etc.), session transcripts, and statistics associated with the caregiver responses to the attributes included in the BWS instrument.
This study investigated a systematic process for using qualitative data to identify attributes and levels most important to caregivers in making health care treatment decisions. Grounded theory methodology was selected for its suitability in assessing an individual’s response to a specific experience. Stakeholder advisors worked with academic researchers in all phases of the project. A total of 48 caregivers were recruited from community support groups from across Maryland. Criteria for selection were a) responsibility for a child 26 years or younger, b) who had an intellectual, emotional, or social developmental disability and, c) with a concomitant mental health condition. 6 caregivers participated in in–depth interviews while the remaining 42 were distributed among 6 focus groups. This dataset includes family demographics, child characteristics (e.g. school grade level, diagnoses, treatment, behavioral problems, etc.), interview transcripts, focus group data, and attribute descriptions and levels.