Use of Immersive Virtual Reality Spaces to Engage Adolescent and Young Adult Patients With Cancer in Therapist-Guided Support Groups: Protocol for a Pre-Post Study
Bibliographic record
Abstract
BACKGROUND: For adolescents and young adults, a cancer diagnoses can magnify feelings of social isolation at an inherently vulnerable developmental stage. Prior studies have highlighted the importance of peer groups during cancer treatment. Support groups help foster connection and resilience, but patients find in-person participation difficult due to a variety of factors. Additionally, physical changes brought on by cancer makes these patients hesitant to meet in person. The COVID-19 pandemic magnified these difficulties. Virtual reality (VR) allows for the creation of a therapist-curated, computer-generated social space that potentially enables support groups for this population. OBJECTIVE: This protocol describes a pilot study examining the efficacy, feasibility, and acceptability of a social VR support group intervention for adolescent and young adult patients with cancer. METHODS: We approached 20 participants aged 17-20 years, and 16 agreed to participate. Moreover, 1 participant dropped out due to hospitalization. Participants attended virtual, professionally facilitated support groups using Meta Quest VR headsets. The groups consisted of 4 participants and 1 facilitator, amounting to a total of 22 individual sessions. Each session lasted 45-60 minutes and took place weekly for 4-6 weeks. The primary aim of this study was to collect quantitative and qualitative data on the feasibility and acceptability of the intervention. Feasibility was measured through session participation rates and overall retention rates. The acceptability of the intervention was explored through brief in-person interviews with participants at the end of the final intervention session. The secondary aim of this study was to collect data on the preliminary efficacy of the intervention in decreasing symptoms of participant depression and anxiety and increasing positive affect and resiliency. RESULTS: In total, 15 patients aged 17-20 years participated in 22 sessions between November 5, 2019, and July 8, 2021. The median age was 19 (IQR 17-20) years. Overall, 10 (62%) participants identified as male, 5 (31%) as female, and 1 (6%) as transgender female. Furthermore, 5 (31%) participants identified as Hispanic, 1 (6%) identified as non-Hispanic Asian, 3 (19%) identified as non-Hispanic Black, 6 (38%) identified as non-Hispanic White, and 1 (6%) identified as other race or ethnicity. Hematologic malignancies or bone marrow failure was the most common diagnosis (8/16, 50%). The mean attendance rate was 72.8% (SD 25.7%) and retention was 86.7% (SD 0.35%). Moreover, 45% (10/22) of sessions had to be postponed by a week or more due to unexpected participant scheduling issues. CONCLUSIONS: The use of VR to deliver psychosocial support for adolescents and young adults with cancer may reduce common barriers associated with attending in-person peer support groups while improving quality-of-life measures. The data from this study will inform future studies focused on conducting VR support groups in other rare disease populations, including older adults with cancer. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48761.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.049 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".