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Physiotherapists' lived experiences of decision making in therapeutic encounters with persons suffering from whiplash-associated disorder: A hermeneutic phenomenological study.

Elles HartholtPirjo VuoskoskiClair Hebron
Published in: Musculoskeletal care (2020)
Conceptual discussions related to clinical reasoning and decision making have evolved over the years from biomedical to incorporating more holistic approach to reasoning. Empirical studies exploring clinical reasoning and decision making in physiotherapy practice have mostly focused on aspects of managing persons with low back pain, such as exercise prescription, education and communicating diagnosis. There is a paucity of studies exploring decision making in whiplash-associated disorder (WAD); thus, the aim of this study was to explore the physiotherapists' lived experiences of decision making related to treating persons with WAD. A qualitative research design based on hermeneutic phenomenological methodology was used in this study. Five participants (physiotherapists) were purposefully recruited, and data are collected via semistructured interviews, which were recorded and transcribed verbatim. Interpretative phenomenological analysis (IPA) was used as a method for analysing the data. Emergent, superordinate and master themes emerged from the data to illuminate the lived experiences under exploration. Three master themes were identified: (1) sense of collaboration; (2) sense of being out of control; and (3) sense of emotional engagement (subthemes: feeling of satisfaction and feelings of distress and uncertainty). A sense of collaboration revealed varied meaning related to the role of persons receiving care, suggesting a lack of conceptual clarity related to shared-decision making. A perceived loss of a sense of being in control was related to experienced emotions, such as feelings of distress and uncertainty. The findings of this study highlight the importance of providing space for reflection and mentoring in the workplace.
Keyphrases
  • healthcare
  • mental health
  • decision making
  • electronic health record
  • primary care
  • palliative care
  • big data
  • quality improvement
  • social media
  • machine learning
  • advance care planning