Examining the quality of smoking cessation interventions available through the internet
Bibliographic record
Abstract
Background: The Internet promises to be an effective vehicle for widespread delivery of Web-assisted tobacco use cessation interventions. Little is known regarding the quality of information available or the usefulness of search tools, such as gateways, in enabling consumers access to accurate and credible cessation information. The purpose of the study was to describe the quality of online tobacco use cessation information available through the World Wide Web (WWW), to compare content of websites retrieved through different search tools, and determine the relationship between standard criteria and evidence-based criteria for smoking cessation interventions available through the Internet. Methods: Web sites purporting to provide self-help smoking cessation information were identified using three search tools; 1) search engine (google.com), 2) private gateway (allhealthnet.com), and 3) public gateway (canadian-health-network.ca, healthfinder.gov). Two independent reviewers rated sites using a 34-item checklist, designed to measure the presence of standard criteria for health information and evidence-based information for treating tobacco use; web site scores were calculated to judge quality of information and conduct analyses. A l l sites were selected and reviewed between February and April, 2004. Results: 120 sites were evaluated; the mean total quality score was 0.57 (range = 0.09 to 0.92). Mean total scores differed significantly between search tools (p = 0.02); post-hoc comparisons (Bonferonni correction) did not detect a difference in total quality scores between the three search tools. Linear regression analysis demonstrated that evidence-based score was a significant (p < 0.1) predictor of standard score, with a coefficient of determination of 0.26. Discussion: The type and content of tobacco use cessation information available is extremely variable, and is not dependent on the search tool used to access the web site. Findings question the utility and effectiveness of standard criteria to measure informational content, and highlight the importance of research into the effectiveness of Web-assisted tobacco use cessation interventions, and developing policies to guide consumers to useful information.
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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 | 0.038 | 0.185 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".