Internet-Delivered Cognitive Behavioral Therapy for Problematic Alcohol Use in a Workplace Setting: Protocol for Quantitative and Qualitative Evaluation of Feasibility and Outcomes
Bibliographic record
Abstract
BACKGROUND: Internet-based cognitive behavioral therapy (ICBT) for mental health issues has been successfully implemented in routine health care settings, and research indicates that ICBT can also be applied to decrease problematic alcohol use in workplace settings. However, studies investigating the feasibility of implementing ICBT in a workplace setting have been lacking. OBJECTIVE: The current study aims to investigate the feasibility of delivering ICBT for problematic alcohol use within an employee assistance program (EAP). METHODS: The study has a quantitative naturalistic design, quantitively comparing ICBT and face-to-face treatment, and allowing for qualitative interviews with employees and employers. Recruitment of participants follows a five-session in-person psychological assessment at an EAP regarding an employee's presumed problematic alcohol consumption. All assessed employees referred to ICBT or face-to-face treatment will be offered participation in the study. Interviews will be held with employees and their employer representatives following ICBT to elucidate both stakeholders' experience and perception of ICBT and its context. Outcome comparisons between ICBT and face-to-face treatment will be assessed quantitatively using a Reliable Change Index and analysis of variance. Thematic analysis and Grounded Theory will be used to analyze the interview material. RESULTS: The study is set to begin in April 2020 and to end in September 2021. The aim is to recruit up to 150 participants to the quantitative part of the study and 45 participants (15 employees and 30 employer representatives) to the qualitative part of the study. CONCLUSIONS: The current study will provide knowledge that is lacking and urgently needed on how to implement ICBT for problematic alcohol use in a workplace setting. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/18693.
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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 | 0.054 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.046 | 0.009 |
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".