Abstract

This paper highlights how learnings from exploring assumptions can be strengthened by taking an evolutionary approach to theory building and analysis. We discuss theory-driven evaluation applied to a community-based intervention implemented by Dancing With Parkinson’s in Toronto, Canada, targeting Parkinson’s disease (PD), a neurodegenerative condition affecting movement. A major gap in the literature is understanding the mechanisms by which dance might make a difference in the daily lives of people living with PD. This study was an early exploratory evaluation to better understand mechanisms and short-term outcomes. Conventional thinking generally favors “permanent” over “transitory” changes, and “long-term” over “short-term” effects. Yet, for people living with degenerative conditions (and also people experiencing chronic pain and other chronic symptoms), transitory and short-term changes may be highly valued and welcomed relief. In order to study and link multiple longitudinal events to explore key linkages in the theory of change, we piloted the use of diaries, with brief entries filled out daily by participants. The aim was to better understand the short-term experiences of participants using their daily routines as a means of learning about potential mechanisms, what matters to participants, and to see if small effects could be observed on days when participants danced versus days when they did not dance and also longitudinally over several months. Our initial theoretical stance began with a view of dance as exercise and the well-established benefits of exercise; yet, we explored through the diary data collected, as well as client interviews and literature review, potential other mechanisms of dancing (such as group interaction, touch, stimulation by the music, and esthetics including “feeling lovely”). This paper does not develop a full, comprehensive theory of dance but moves towards a more comprehensive view that locates dance within the routine activities of participants’ daily lives. We argue that given the challenges of evaluating complex interventions comprising multiple, interacting components, there is a need for an evolutionary learning process to understand heterogeneities in mechanisms -- what works for whom -- when faced with knowledge incompleteness in the theory of change.

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