In the Mindset for Change: Self-Reported Quit Attempts are a Product of Discontinuity-Induced Nostalgia and Incremental Beliefs
Bibliographic record
Abstract
Despite the low rate of behavior change among those engaged in addictive behaviors, some people can and do initiate change. We propose that attempting to self-regulate addictive behavior is a function of motivation and the belief that behavior is malleable. Specifically, feeling self-discontinuous (i.e., feeling that addiction has fundamentally changed the self) should motivate change by inducing nostalgia for the pre-addicted self. Importantly, we expected that discontinuity- induced nostalgia would only be associated with an attempted change among those who believe that behavior is malleable (i.e., incremental theorists). To test this moderated-mediation model, we recruited a community sample of disordered gamblers (N = 243) to assess self-reported change attempts over time. During the initial session, participants completed measures of self-discontinuity, nostalgia, and implicit theories of behavior. Three months later, participants (N = 120) reported whether they attempted to change their gambling behavior, as well as the method and extent to which they sustained this change. As expected, discontinuity-induced nostalgia was positively associated with an increased likelihood of self-reporting a change attempt, but only when behavior was believed to be malleable, rather than fixed. As very few disordered gamblers take action, these findings suggest novel psychological processes to promote positive behavior change.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".