Differentiation of Family System Inventory (DoFSI): Development and content validation of a new qualitative family intervention and evaluation tool

Abstract

AbstractEver since family systems therapy became a field of study in the mid‐20th century, family functioning has defied numeric data, making families about as easy to measure as the quantum world, with all their complexity and variability – and messiness. Over the years, numerous quantitative measures have attempted to master this feat, with varying success. However, quantitative, postpositivist measures do not collect rich, meaningful data about the lived experiences of real people in unique family situations. The qualitative instrument developed and validated in this study, however, utilised participant data for its final version to increase its relevance and practicality. By soliciting the input of participants in the process of psychosocial research and intervention development, this applied study aims to improve both adherence to and effectiveness of the treatment tool, bridging the gap between research and real life. This descriptive phenomenological qualitative study gathered data from nine participants on the feasibility, acceptability, usability and relevance of a new family systems intervention tool, the Differentiation of Family System Inventory (DoFSI), founded on Bowen Family Systems theory (BFST) and Papero's five‐dimensional BFST‐derived framework which follows the Research Domain Criteria (RDoC) established by the National Institute of Mental Health in 2009. According to the preponderance of the data, the DoFSI is user‐friendly, practical, relevant, and useful as a tool for ongoing reflection and growth and is appropriate for both personal and professional use. The data affirmed the practicality, content validity and usable format of the inventory, while implicating and prompting a return to Bowen's seminal work, Family Therapy in Clinical Practice, to ensure the content validity of the final version of the instrument, a derivative of the study data.