The Effect of Web-Based Support as an Adjunct to a Self-Help Smoking Cessation Program
Bibliographic record
Abstract
For the past quarter century, the public has been educated and warned about the dangers of smoking, and both smokers and health researchers have been in search of cost-effective, smoking cessation programs that will lead to long-term cessation. This study used a randomized experimental design to investigate the effectiveness of adding Web-based support materials to a nationally sponsored self-help smoking intervention. There was no significant increase in abstinence rates nor progression through the stages of change by those participants who had access to the Web site. However, there were some overall significant trends that suggested these self-help interventions were successful at decreasing daily rates of smoking and nicotine dependency, as well as tended to encourage repeated quit attempts. Although Web-based supports did not appear to increase the effectiveness of the nationally sponsored self-help intervention, this study demonstrated overall 12 week follow-up abstinence rates of 30-32%--greater than what might be expected, given average success rates of other self-help interventions. This study also supports the notion that women may face additional barriers to smoking cessation. Limitations and implications for future research are discussed.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".