International addiction researchers’ perspectives on the needs of persons with addictions, the use of neuroscientific research for prevention and treatment, and future foci in addictions research
Bibliographic record
Abstract
Brain-based explanations of addiction have been promoted for several decades. Their utility, however, is controversially discussed in the scientific community. While existing literature documents how stakeholders such as treatment providers, affected persons, and the public view their utility, views of the addiction research community are rarely represented. We aimed to complement existing studies by surveying researchers on their perspectives on the needs of addicted individuals, the utility of neuroscientific research for prevention and treatment, and future research priorities. 1440 international addiction researchers from many disciplines were invited to participate in a LimeSurvey. Their views on the treatment requirements of persons with addictions were assessed with a Likert scale and an open-ended question. The utility of neuroscientific research for prevention and treatment and the desired future priorities in addiction research were surveyed with open-ended questions. Quantitative items were analyzed descriptively. The qualitative content analysis of the free-text contributions followed an iterative inductive approach. Additionally, future research priorities were categorized deductively according to the underlying direction. 190 researchers from 29 countries participated (13.2%). Most considered various treatment and support options helpful and approaches tailored to the needs of individuals to be the most promising. The utility of neuroscientific research was evaluated critically by several, but benefits in terms of pharmacological treatment and the possibility to identify risk groups were acknowledged. Future areas of inquiry for addiction research mentioned were heterogenous and included neuroscientific/genetic/medications development (13%), psychosocial aspects (19%), and integrated bio-psycho-social approaches (45%). A corresponding reconsideration of treatment, support, and research seems warranted.
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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 | 0.044 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".