Adolescents’ Perspectives on Using Technology for Health: Qualitative Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Adolescents' wide use of technology opens up opportunities to integrate technology into health visits and health care. In particular, technology has the potential to influence adolescent behavior change by offering new avenues for provider communication and support for healthy choices through many different platforms. However, little information exists to guide the integration of technology into adolescent health care, especially adolescents' perspectives and preferences for what they find useful. Objective: This qualitative study aimed to take a broad approach to understanding adolescents' use of technology for supporting their overall health and to understand whether and how adolescents envision using technology to enhance their health and clinical care, particularly in communicating with their provider. Methods: Adolescents (13-18 years) were recruited to participate in semi-structured, in-depth individual interviews. Potential participants were approached in-person through the Seattle Children's Hospital Adolescent Medicine Clinic while they were waiting for consultation appointments, through outreach to youth who expressed interest in other local research study activities, and via flyers in waiting rooms. Interviews were recorded, transcribed, and analyzed using a thematic analysis approach. Results: Thirty-one adolescents (58% female, M= 15.2 years) were interviewed and described 3 main uses of technology: (1) to gather information, (2a) to share their own experiences and (2b) view others' experiences in order to gain social support or inspiration, and (3) to track behaviors and health goals. Perceived benefits and potential downsides were identified for technology use. Teens desired to use technology with their provider for 3 main reasons: (1) have questions answered outside of visits, (2) have greater access to providers as a way to build relationship/rapport, and (3) share data regarding behaviors in between visits. Social media was not a preferred method for communicating with providers for any of the youth due to concerns about privacy and intrusiveness. Conclusions: Although youth are avid users of technology in general, in regard to technology for health, they display specific use preferences especially in how they wish to use it to communicate with their primary care provider. Healthcare providers should offer guidance to youth with regard to how they have used and plan to use technology and how to balance potential positives and negatives of use. Technology developers should take youth preferences into account when designing new health technology and incorporate ways they can use it to communicate with their healthcare provider.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it