Co-Design of a Depression Self-Management Tool for Adolescent and Young Adult Cancer Survivors: User-Centered Design Approach
Bibliographic record
Abstract
BACKGROUND: Adolescent and young adult (AYA) cancer survivors are more likely to experience elevated depressive symptoms than older survivors and healthy age-matched peers. Despite the elevated risk of depressive symptoms in AYA cancer survivors and the existence of evidence-based interventions to address depression, it is unclear whether AYA cancer survivors can access support services. Digital tools are a potential solution to overcoming barriers to AYA cancer survivors' unmet needs for psychosocial support, but they have not been tailored to the needs and preferences of this unique population. OBJECTIVE: This study engaged AYA cancer survivors and their providers in the concept generation and ideation step of the user-centered design process through online co-design workshops. The goal was to generate concepts and ideas for a digital depression self-management tool tailored to AYA cancer survivors. METHODS: We conducted 5 co-design workshops-4 with AYA cancer survivors and 1 with providers who serve them. Participants were asked to provide feedback on an existing digital mindfulness course using an "I like, I wish, I wonder" framework. Then, participants were asked "How might we..." questions focused on brainstorming ideas for how the digital tool might work. Participants brainstormed responses independently and then worked as a group to categorize and expand on their ideas. Co-design workshops were autotranscribed using Webex (Cisco) software. Transcripts underwent thematic analysis with additional context provided by the products created during the workshop. RESULTS: Eight AYA cancer survivors (aged 15-37 years) and 4 providers (2 oncologists and 2 social workers) participated in co-design workshops. We identified 6 themes: barriers to engagement, desired content, preferences for content delivery, preferences for interface, features, and aspects to avoid. Each theme had 2-7 subthemes that we relied upon when making design decisions for the prototype. CONCLUSIONS: Co-design workshops provided critical insights that informed the prototype development of a digital depression self-management tool tailored to AYA cancer survivors. Key takeaways that were integrated into prototype design include (1) using stories from other AYA cancer survivors to demonstrate concepts; (2) delivering content in brief lessons; and (3) using encouraging notifications, organizational tools, and reward systems to keep AYA cancer survivors engaged with the tool. Some of the themes identified in this study (eg, desired content and features) are consistent with known strategies for promoting user engagement and co-design work in other cancer survivors. However, this study extended previous research by identifying uniquely relevant strategies for tailoring to AYA cancer survivors, such as delivering content in brief sessions to overcome the time constraints AYA cancer survivors experience, providing opportunities for private expression, and maintaining an encouraging tone throughout the tool. These data were used to inform the prototype development of a digital depression self-management tool tailored to AYA cancer survivors.
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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 | 0.018 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".