Impact of Task-Fit Misalignment and the Director of Clinical Education: A Grounded Theory Study.

Abstract

The roles and responsibilities of the director of clinical education (DCE) are of interest in the academic physical therapist (PT) community. This study explored the impact of professional and positional task characteristics of the DCE position on task-fit misalignment within PT education programs. Task-fit explores how the tasks of a particular job align with the appropriately trained person who holds the position. A recently published DCE Matrix highlights 2 extremes of misalignment and nonoptimal task-fit between the position and the person. Misalignment was investigated rather than alignment because negative connotations often have greater impact on behavior, decision making, and relationships. The impact of misalignment is unknown. Program directors and DCEs among ACAPT member PT programs were surveyed. A qualitative grounded theory design was used. Two rounds of surveys with focused questions about the impact of task-fit misalignment. Qualitative content data analysis through a constant comparative process was followed. Respondent descriptive statistics were collected. Three realms of impact were identified when misalignment of positional and professional characteristics exists. The realms include the 1) individual person holding the position; 2) academic program; or 3) physical therapy profession. There is a high level of agreement that task-fit misalignment affects each realm; variability exists about its prevalence. There seems to be an interconnectedness of impact among the person, the program, and the profession when misalignment exists between the fit of the DCE to the job or the work environment to the DCE. Findings indicate job crafting may be necessary to evolve the nature of the DCE work toward higher director-level tasks. This is the first study of its kind to explore the impact intersection of person-job fit and task-fit and the impact on a DCE's responsibilities. Nonrespondent or attrition bias may have limited sample size.