The influence of music on the addictive trajectory: a conceptual framework
Bibliographic record
Abstract
Music is increasingly considered to promote the health and well-being of clinical populations treated in hospital and psychiatric settings. Research shows numerous benefits of music on physical and mental health issues by responding to psychological, emotional, social and physical needs. However, while music’s benefits are largely supported among clinical populations, it appears that marginalized populations remain stigmatized through a lasting emphasis on their difficulties, including their use of music. Nevertheless, music appears as an innovative, accessible and promising tool to address such needs in individuals who experience social inequity regarding their access to health and helping services. Among those are marginalized individuals who suffer psychoactive substance abuse. Though research in this population remains scarce, we observe beneficial and harmful influences of music on psychoactive substance use and on the long-term addictive trajectory. In a more comprehensive manner, this article critically explores the relevance of the music and health conceptual framework developed by Västfjäll et al. to explain the role of music on the addictive trajectory. Accounting for music, individual and contextual factors, the model explains how music alters emotional states positively or negatively, which in turn modulates psychoactive substance use and the different periods encountered through the associated addictive trajectory. Despite some limitations, the model offers insights that can usefully guide and contribute to adapt its use in community interventions and as a harm reduction tool, conditional to the careful consideration of individuals’ needs and interpretation of their musical experiences.
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How this classification was reachedexpand
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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".