NIDA-Drug Addiction Treatment Outcome Study (DATOS) Relapse as a Function of Spirituality/Religiosity
Bibliographic record
Abstract
BACKGROUND: The connection between religion/spirituality and deviance, like substance abuse, was first made by Durkheim who defined socially expected behaviors as norms. He explained that deviance is due in large part to their absence (called anomie), and concluded that spirituality lowers deviance by preserving norms and social bonds. Impairments in brain reward circuitry, as observed in Reward Deficiency Syndrome (RDS), may also result in deviance and as such we wondered if stronger belief in spirituality practice and religious belief could lower relapse from drugs of abuse. METHODS: The NIDA Drug Addiction Treatment Outcome Study data set was used to examine post hoc relapse rates among 2,947 clients who were interviewed at 12 months after intake broken down by five spirituality measures. RESULTS: = 11.33, p = 0.045; logistic regression = 9.650, p = 0.002). Across the five measures of spirituality, the spiritual participants reported between 7% and 21% less alcohol, cocaine, heroin, and marijuana use than the non-spiritual subjects. However, the crack users who reported that religion was not important reported significantly less crack use than the spiritual participants. The strongest association between remission and spirituality involves attending religious services weekly, the one marker of the five that involves the highest social interaction/social bonding consistent with Durkheim's social bond theory. CONCLUSIONS: Stronger spiritual/religious beliefs and practices are directly associated with remission from abused drugs except crack. Much like the value of having a sponsor, for clients who abuse drugs, regular spiritual practice, particularly weekly attendance at the religious services of their choice is associated with significantly higher remission. These results demonstrate the clinically significant role of spirituality and the social bonds it creates in drug treatment programs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".