“Double-edged sword” of Digital Media Use among Youth in Residential Treatment: Perspectives of Service Providers
Bibliographic record
Abstract
The social significance of digital media and technology is incontestable, particularly with youth. While digital media use can offer youth in residential treatment (RT) opportunities, it also carries risks. Although there has been a shift in RT from a model fostering isolated, self-contained settings, toward the promotion of family and community integration, there is a dearth of scholarship addressing youth digital media use in RT. To address the gaps in research on digital media use among youth in RT and the absence of system-wide policies and formal consensus on guidelines for addressing the issue, the findings of the current study offer insight into the experiences of 25 service providers from four programs. The findings highlight that regardless of location or treatment approach, RT is addressing youth digital media use. There exists a continuum of approaches ranging from risk prevention to risk resilience. As social media have made prohibiting contact between youth impossible, digital media use has been a catalyst for programs to attend to youth relationships outside of the programs. Digital media have thus both introduced new challenges to supporting youth and facilitated a more contemporary resilience-oriented and ecologically informed the approach to treatment.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".