Experiences and barriers to alcohol use disorder treatment among adults with and without self‐reported executive functioning challenges: A mixed‐methods study
Bibliographic record
Abstract
BACKGROUND: Executive functioning (EF)-the ability to plan, organize, and complete goal-directed tasks-plays a critical role in the onset and course of alcohol use disorder (AUD). Individuals with AUD often report challenges in EF domains, such as initiating, planning, and performing key tasks, including seeking, engaging in, and adhering to treatment. While AUD treatment efficacy is well-established, little is known about individuals' lived experiences with AUD treatment, especially among those with EF challenges. To date, no studies have explored how self-reported EF challenges shape treatment-seeking experiences in people with AUD using a mixed-methods approach. This study addresses that gap. METHODS: We conducted a mixed-methods study involving 30 adults seeking AUD treatment between June 2022 and June 2023. This work was part of a broader research program examining cognitive functioning in addictions within a mental health and addictions hospital in Toronto, Canada. Data collection included semistructured qualitative interviews and a standardized self-administered EF questionnaire. Data were integrated, analyzed thematically, and narratively synthesized. RESULTS: Approximately half of participants (53%) met the threshold for EF challenges. Many described multiple prior treatment attempts, a delayed recognition of problematic alcohol use, and an incongruence between treatment expectations and experiences. Those with EF challenges described distinct barriers to care and expressed a need for additional supports, including access to psychotherapy, clearer treatment pathways and timelines, and more proactive communication and follow-up from healthcare providers. CONCLUSIONS: Individuals with AUD often experience co-occurring mental health and EF challenges that may affect their motivation to seek treatment and shape treatment experiences and trajectories. Tailored treatment approaches that address EF challenges through enhanced support, structure, and provider communication may improve treatment engagement and outcomes among this population.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".