JOURNAL ARTICLE

A Mixed Methods Exploration of Participants' Perspectives: A Wilderness-Based Adventure Therapy Program for Youth Who Have Experienced Cancer.

  • Published In: Journal of Experiential Education, 2025, v. 48, n. 3. P. 485 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Cavanaugh, Daniel L.; Tucker, Anita Reithoff; Pertl, Kellie; Norton, Christine Lynn; Mathes, Kristin; Otto, Heather Rose 3 of 3

Abstract

This article examines how adolescents with lived experiences of cancer perceive and experience participation in the See You at the Summit (SYATS) wilderness-based adventure therapy program. Using a mixed methods design with 17 participants aged 13–17, the study identified five qualitative themes—social support and connection, choice and autonomy, psychological growth, overcoming challenges, and time in nature—that align with quantitative findings from the Adventure Therapy Experience Scale (ATES). Participants reported the greatest impact in interpersonal connections and engagement with nature, with older adolescents showing higher nature engagement and younger adolescents reporting greater focus on treatment goals. The findings suggest that adventure therapy programs like SYATS may promote resilience by fostering social support, autonomy, emotional development, and restorative experiences in nature for youth affected by cancer, highlighting the importance of incorporating choice and trauma-informed care principles in psychosocial interventions.

Additional Information

  • Source:Journal of Experiential Education. 2025/09, Vol. 48, Issue 3, p485
  • Document Type:Article
  • Subject Area:Education
  • Publication Date:2025
  • ISSN:1053-8259
  • DOI:10.1177/10538259241300118
  • Accession Number:187071362
  • Copyright Statement:Copyright of Journal of Experiential Education is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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