Digital Media and Developing Brains: Concerns and Opportunities
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
Purpose of Review: The incorporation of digital technologies and their use in youth's everyday lives has been increasing rapidly over the past several decades with possible impacts on youth development and mental health. This narrative review aimed to consider how the use of digital technologies may be influencing brain development underlying adaptive and maladaptive screen-related behaviors. Recent Findings: To explore and provide direction for further scientific inquiry, an international group of experts considered what is known, important gaps in knowledge, and how a research agenda might be pursued regarding relationships between screen media activity and neurodevelopment from infancy through childhood and adolescence. While an understanding of brain-behavior relationships involving screen media activity has been emerging, significant gaps exist that have important implications for the health of developing youth. Summary: Specific considerations regarding brain-behavior relationships involving screen media activity exist for infancy, toddlerhood, and early childhood; middle childhood; and adolescence. Transdiagnostic frameworks may provide a foundation for guiding future research efforts. Translating knowledge gained into better interventions and policy to promote healthy development is important in a rapidly changing digital technology environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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