Actionable companion · Motivation & engagement

Learning with agency: Fostering Digital Resilience Among Youth Who Experienced Cyberbullying: Design Thinking Approach

AI-assisted editorial implementation guide, separate from the original research. Proposed actions are not claims or recommendations attributed to the source authors. No independent peer review of this guide is asserted.

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Evidence and context

Title and abstract screening; stage labels describe reported settings, not verified numerical ages. Design labels require full-text appraisal. Reported stage(s): Secondary school. Verify the participant population and task before transferring the findings.

Original authors’ abstract, reproduced under the linked source license:

Abstract Background Cyberbullying affects approximately one-third of Thai secondary school students and has been linked to adverse emotional outcomes and mental health vulnerabilities. Strengthening digital resilience, along with critical thinking, empathy, and help-seeking skills, is essential to empower youth to cope with online risks and promote safer digital behavior. Despite growing recognition of cyberbullying as a critical youth mental health issue, few studies have explored how digital resilience interventions can be co-designed with youth and relevant stakeholders to address the contextual and emotional challenges experienced by affected adolescents. Objective This study aimed to develop a youth-centered, theory-informed intervention using a design thinking framework to support digital resilience in addressing cyberbullying. The research repositioned youth with lived cyberbullying experiences from passive persons who experienced abuse to active co-creators of the intervention. Grounded in empowerment principles, nudge theory, and the concept of digital resilience, this approach reimagined cyberbullying prevention through empathy-driven innovation and participatory engagement, generating a contextually grounded model for designing cyberbullying interventions in a Global South context. Methods We applied a 5-phase design thinking framework: empathize, define, ideate, prototype, and test. Twelve participants were purposively selected as extreme and lead users and key stakeholders. This group engaged in participatory design workshops and included a psychologist, experts, teacher counselors, and LGBTQI+ (lesbian, gay, bisexual, transgender, queer, and intersex) students aged 15 to 17 years with lived experience of cyberbullying. Youth participants were recruited in collaboration with school counselors to ensure diversity of experiences and perspectives. Qualitative data from the workshops were analyzed using reflexive thematic analysis to identify user needs, guide problem framing, and inform prototype development. A low-fidelity mobile-based prototype in the form of screen mockups was iteratively refined through user testing and expert consultation to ensure theoretical alignment and contextual relevance. Results The co-creation process identified key challenges, including emotional distress, lack of support, and the rapid spread of harmful content. Youth participants collaboratively designed a virtual community platform featuring peer support spaces, confidential expert consultation, skill-building workshops, a knowledge hub, gamified engagement tools, and artificial intelligence–assisted support. The intervention design was informed by the study’s theoretical framework, which guided the development of engagement strategies, supportive communication features, and youth-centered interaction pathways. Iterative refinement contributed to improvements in perceived usability, personalization, and theoretical coherence. Importantly, the process supported youth agency by positioning participants as active co-designers who shaped solutions grounded in their lived experiences. Conclusions This study illustrates how a theory-driven, participatory design thinking approach can be used to develop digital prevention and intervention for cyberbullying. By integrating behavioral theory with youth co-creation, the findings provide insights into how youth-centered co-design can inform the development of interventions addressing cyberbullying, highlighting the role of empowerment-oriented and theoretically grounded design processes in engaging youth as active contributors to solution development.

What kind of evidence is this?

Supporting AI learning science · Qualitative / mixed methods

Stage: Secondary school. Screening labels describe reported context and study-design language. They are not a risk-of-bias rating or proof of effectiveness for an age band.

Participant ages · source passage

This group engaged in participatory design workshops and included a psychologist, experts, teacher counselors, and LGBTQI+ (lesbian, gay, bisexual, transgender, queer, and intersex) students aged 15 to 17 years with lived experience of cyberbullying.

Study methods · source passage

This study used a participatory design thinking approach to guide the development of a theory-informed intervention addressing cyberbullying and digital resilience among youth. The following sections describe the study design, data collection procedures, participant recruitment, analytic approach, and strategies used to support research rigor and ethical conduct.

Limitations and uncertainty · source passage

This study has several limitations. The design thinking process in this study was conducted across 3 sessions totaling 9 hours, which limited the depth of participant engagement and reduced opportunities for iterative refinement. In addition, the relatively small sample size and purposive selection of participants may limit the diversity of perspectives captured. However, consistent with design thinking approaches, the study prioritizes depth of engagement with extreme and lead users over representativeness.

Design the system before the pilot

Use this study to inform a learning mechanism or implementation question. It is not direct evidence that autonomous agents improve learning. Keep the proposed agent behavior separate from what the source actually tested.

Measure engagement separately from achievement. Check whether novelty-driven participation persists and whether it translates to independent performance.
Use common rubrics, blind scoring where feasible and a fresh unaided reasoning task. Document permissible assistance and avoid treating AI-detector scores as proof of misconduct.

A 90-day district pilot

Days 1–15 · Appraise. Have the curriculum lead and a teacher read the methods and limitations. Record the study design, sample, comparator, outcomes and evidence gaps. Define a local question that the study can help inform.
Days 16–30 · Design. Ask learners to attempt a problem unaided, compare an agent hint, explain a revision and verify the final reasoning against a trusted source. Make the permitted use explicit for each assignment. Name an accountable owner and set the baseline, success threshold and budget before implementation.
Days 31–60 · Test. Start with a small voluntary cohort, preserve an accessible non-AI route and require teacher review. Use synthetic or de-identified examples; approve data handling and tool terms through district processes.
Days 61–90 · Decide. Measure unaided transfer and delayed retention, calibration of confidence and the ability to identify an incorrect AI explanation. Record whether help-seeking becomes answer copying. Compare with baseline, document uncertainty and stop or revise if learning worsens, access is unequal or critical errors persist.

The board decision brief

Report the learning problem, evidence quality, participating population, total cost including review time, measured benefit, errors, access differences and remaining uncertainties. Make a dated recommendation to stop, revise or expand. A positive perception survey alone does not establish learning improvement.

Attribution and reuse

Nattharat Samoh; Thomas E Guadamuz; Jintavee Khlaisang; Songphan Choemprayong. Fostering Digital Resilience Among Youth Who Experienced Cyberbullying: Design Thinking Approach. Journal of Medical Internet Research (2026-07-09). https://doi.org/10.2196/93891

Companion prepared 2026-10-30. Original authorship and DOI are preserved. The abstract is an attributed source extract; the implementation plan is new AI-assisted editorial material, offered under the same CC BY 4.0 license. This guide has not undergone independent peer review.