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Managing unsolicited findings in genomics: A qualitative interview study with cancer patients.

Rhodé M BijlsmaR H P WoutersH WesselsA M MayM G E M AusemsE E VoestA L Bredenoord
Published in: Psycho-oncology (2018)
The results of our study contribute to a better understanding of what cancer patients consider important and what may motivate and influence them when making decisions on the disclosure of unsolicited findings following NGS. We show how Joel Feinberg's classification of autonomy may help clinicians to better understand cancer patients' desire for autonomous decision making while also acknowledging the emotional and cognitive difficulties regarding the disclosure of unsolicited findings. These insights could be helpful for clinicians to guide patients through this complex process.
Keyphrases
  • decision making
  • palliative care
  • machine learning
  • end stage renal disease
  • ejection fraction
  • deep learning
  • patient reported outcomes