A Brief Outline of the Use of New Technologies for Treating Substance Use Disorders in the European Union
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: Clinicians in the field of drug addiction have started to exploit the growth of Technology-Based Interventions (TBIs). However, there is little information on how health personnel evaluate them. METHODS: Semi-structured interviews were conducted among 20 European experts. RESULTS: All of the interviewees recognised TBIs as a valuable tool to improve the management of substance-use disorders (SUDs). Most interviewees indicated that combining both traditional face-to-face therapist-patient clinic appointment with TBIs is probably the most effective method. Most interviewees agree that TBIs are valuable tools to overcome both physical and social barriers, and hence significantly facilitate the access to treatment. Poor infrastructure and lack of digital literacy are recognised as major barriers to the diffusion of these tools. CONCLUSIONS: The application of various forms of technology in SUD treatment is an interesting development for the European Union. Technical and non-technical barriers exist and impede their full exploitation.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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