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Purpose <p>Peer support can provide many benefits to cancer patients. However, sustained use of one-on-one peer support requires a good match between patient and peer mentor. Using an artificial intelligence (AI) matching algorithm has the potential to improve peer matching by achieving complex, preference-based matching. Therefore, using stakeholder co-design, this study identified patient preferences for peer matching criteria and other features of OpalBuddy, a digital peer support service to be developed within the Opal patient portal.</p> Methods <p>Patients using the Opal app were recruited, and semi-structured individual interviews were carried out with eight available women cancer patients. Qualitative data analysis followed an iterative and collaborative thematic analysis approach, using computer-assisted software (NVivo).</p> Results <p>Three themes, with supporting sub-themes, that describe patient preferences for matching with an ideal peer mentor were identified:</p> <p>Theme 1. An ideal mentor can provide support at multiple levels, with sub-themes describing the levels: (A) Sharing illness experiences, (B) Practical information support, (C) Emotional support, (D) Social management coaching.</p> <p>Theme 2. The ideal mentor has similar lived experience, with sub-themes describing the type of lived experience: (A) Similar clinical situation, (B) Similar socio-demographics, (C) Interpersonal affinity.</p> <p>Theme 3. The ideal peer mentor will be supported in their role, with sub-themes describing support options: (A) Formal or informal training, (B) General guidance, (C) Supportive supervision.</p> <p>Finally, based on different support needs (practical vs emotional), it was found that patients had varying, even opposing, expectations from a mentor’s interpersonal communication style (solution focused vs good listener).</p> Conclusion <p>Patient preferences for an ideal peer mentor were identified through semi-structured interviews with a sample of eight women with a diverse set of cancers. Findings will be used to guide further work, including a similar study with men and a pilot study of a digital patient matching service for peer support in the open-source Opal patient portal.</p>

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Who is your ideal peer mentor? A qualitative study to identify cancer patient preferences for a digital peer support app

  • 期刊论文

  • 发表日期：

    2025年3月6日

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  • Loes Knaapen,
  • Andréa Maria Laizner,
  • Kelly Agnew,
  • Xiao Jian Du,
  • Douaa El Abiad,
  • Luc Galarneau,
  • Susie Judd,
  • James Manalad,
  • Ridhi Mittal,
  • Tristan Williams,
  • Brandon Woolfson,
  • Angele Wen,
  • John Kildea

摘要

Purpose

Peer support can provide many benefits to cancer patients. However, sustained use of one-on-one peer support requires a good match between patient and peer mentor. Using an artificial intelligence (AI) matching algorithm has the potential to improve peer matching by achieving complex, preference-based matching. Therefore, using stakeholder co-design, this study identified patient preferences for peer matching criteria and other features of OpalBuddy, a digital peer support service to be developed within the Opal patient portal.

Methods

Patients using the Opal app were recruited, and semi-structured individual interviews were carried out with eight available women cancer patients. Qualitative data analysis followed an iterative and collaborative thematic analysis approach, using computer-assisted software (NVivo).

Results

Three themes, with supporting sub-themes, that describe patient preferences for matching with an ideal peer mentor were identified:

Theme 1. An ideal mentor can provide support at multiple levels, with sub-themes describing the levels: (A) Sharing illness experiences, (B) Practical information support, (C) Emotional support, (D) Social management coaching.

Theme 2. The ideal mentor has similar lived experience, with sub-themes describing the type of lived experience: (A) Similar clinical situation, (B) Similar socio-demographics, (C) Interpersonal affinity.

Theme 3. The ideal peer mentor will be supported in their role, with sub-themes describing support options: (A) Formal or informal training, (B) General guidance, (C) Supportive supervision.

Finally, based on different support needs (practical vs emotional), it was found that patients had varying, even opposing, expectations from a mentor’s interpersonal communication style (solution focused vs good listener).

Conclusion

Patient preferences for an ideal peer mentor were identified through semi-structured interviews with a sample of eight women with a diverse set of cancers. Findings will be used to guide further work, including a similar study with men and a pilot study of a digital patient matching service for peer support in the open-source Opal patient portal.