Technology Use During the COVID-19 Pandemic and the Ways in Which Technology Can Support Adolescent Well-being: Qualitative Exploratory Study
Bibliographic record
Abstract
BACKGROUND: Most adolescents in the United States engage with technology. Social isolation and disruptions in activities owing to the COVID-19 pandemic have been linked to worsening mood and overall decreased well-being in adolescents. Although studies on the direct impacts of technology on adolescent well-being and mental health are inconclusive, there are both positive and negative associations depending on various factors, such as how the technology is used and by whom under certain settings. OBJECTIVE: This study applied a strengths-based approach and focused on the potential to leverage technology to benefit adolescent well-being during a public health emergency. This study aimed to gain an initial and nuanced understanding of how adolescents have used technology to support their wellness throughout the pandemic. In addition, this study aimed to further motivate future large-scale research on how technology can be leveraged to benefit adolescent well-being. METHODS: This study used an exploratory qualitative approach and was conducted in 2 phases. Phase 1 consisted of interviewing subject matter experts who work with adolescents to inform the creation of a semistructured interview for phase 2. Subject matter experts were recruited from existing connections with the Hemera Foundation and National Mental Health Innovation Center's (NMHIC) networks. In phase 2, adolescents (aged 14-18 years) were recruited nationally through social media (eg, Facebook, Twitter, LinkedIn, and Instagram) and via email to institutions (eg, high schools, hospitals, and health technology companies). High school and early college interns at NMHIC led the interviews via Zoom (Zoom Video Communications) with an NMHIC staff member on the call in an observational role. A total of 50 adolescents completed interviews regarding their technology use and its role during the COVID-19 pandemic. RESULTS: The overarching themes identified from the data were COVID-19's impact on adolescent lives, positive role of technology, negative role of technology, and resiliency. Adolescents engaged with technology as a way to foster and maintain connection in a time of extended isolation. However, they also demonstrated an awareness of when technology was negatively affecting their well-being, prompting them to turn to other fulfilling activities that do not involve technology. CONCLUSIONS: This study highlights how adolescents have used technology for well-being throughout the COVID-19 pandemic. Guidelines based on insights from the results of this study were created for adolescents, parents, caregivers, and teachers to provide recommendations for how adolescents can use technology to bolster overall well-being. Adolescents' ability to recognize when they need to engage in nontechnology-related activities and their ability to use technology to reach a larger community indicate that technology can be facilitated in positive ways to benefit their overall well-being. Future research should focus on increasing the generalizability of recommendations and identifying additional ways to leverage mental health technologies.
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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 | 0.015 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".