Research landscape analysis on dual diagnosis of substance use and mental health disorders: key contributors, research hotspots, and emerging research topics
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: Substance use disorders (SUDs) and mental health disorders (MHDs) are significant public health challenges with far-reaching consequences on individuals and society. Dual diagnosis, the coexistence of SUDs and MHDs, poses unique complexities and impacts treatment outcomes. A research landscape analysis was conducted to explore the growth, active countries, and active journals in this field, identify research hotspots, and emerging research topics. METHOD: A systematic research landscape analysis was conducted using Scopus to retrieve articles on dual diagnosis of SUDs and MHDs. Inclusion and exclusion criteria were applied to focus on research articles published in English up to December 2022. Data were processed and mapped using VOSviewer to visualize research trends. RESULTS: A total of 935 research articles were found. The number of research articles on has been increasing steadily since the mid-1990s, with a peak of publications between 2003 and 2012, followed by a fluctuating steady state from 2013 to 2022. The United States contributed the most articles (62.5%), followed by Canada (9.4%). The Journal of Dual Diagnosis, Journal of Substance Abuse Treatment, and Mental Health and Substance Use Dual Diagnosis were the top active journals in the field. Key research hotspots include the comorbidity of SUDs and MHDs, treatment interventions, quality of life and functioning, epidemiology, and the implications of comorbidity. Emerging research topics include neurobiological and psychosocial aspects, environmental and sociocultural factors, innovative interventions, special populations, and public health implications. CONCLUSIONS: The research landscape analysis provides valuable insights into dual diagnosis research trends, active countries, journals, and emerging topics. Integrated approaches, evidence-based interventions, and targeted policies are crucial for addressing the complex interplay between substance use and mental health disorders and improving patient outcomes.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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