Making Sense of Negative Findings from Mobile Attention Bias Modification Interventions for Individuals with Addictive Disorders: Quantitative Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Advances in experimental psychology have led to a better understanding of unconscious, automatic processes that result in individuals relapsing into their substance-using habits. While some reviews have demonstrated the effectiveness of bias retraining of these unconscious biases, there have been other reviews that have highlighted that bias retraining is not always effective. Other studies have revealed there was no baseline biases among some participants. An examination of mobile bias retraining interventions has also revealed mixed results, with some reporting effectiveness and others null findings. A recent feasibility and acceptability study, done by the authors, revealed that 53% of participants have had no baseline biases and 21% of those with positive baseline biases did not have a positive change in magnitude following intervention. OBJECTIVE: The aim of this paper was to explore potential variables (demographic and clinical) that could account for the negative baseline biases in the prior feasibility and acceptability study, and to discuss some of the factors that could account for the absence of baseline biases. We also explored potential reasons for why there was no reduction in the magnitude of attentional biases among individuals with baseline biases. METHODS: Participants who were in the rehabilitation phase of their treatment were invited to participate. During the study they had to complete a set of baseline questionnaires, and on each day that they were on the ward they had to complete an attention bias assessment and modification task and rate their cravings using a visual analogue scale. Attention bias was deemed to be present if individuals had a positive score. RESULTS: In our study, 53% (16/30) of individuals did not present with baseline attentional biases, and among those with positive baseline biases a total of 21% (3/14) of participants did not have a reduction in the overall magnitude of attentional biases. Chi-square analyses undertaken to compare the demographic characteristics of participants with and without baseline biases did not reveal any significant findings. However, with respect to clinical characteristics, those who had positive baseline biases had experimented with more substances. CONCLUSIONS: Our study is one of the first to have explored negative findings in attention bias modification interventions for individuals with addictive disorders. We postulate that several factors could account for the absence of baseline biases and there being no changes following bias retraining. Future research ought to take into consideration these factors.
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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 | 0.068 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".