Adaptation, Implementation Plan, and Evaluation of an Online Tobacco Cessation Training Program for Health Care Professionals in Three Spanish-Speaking Latin American Countries: Protocol of the Fruitful Study
Bibliographic record
Abstract
BACKGROUND: Tobacco cessation training programs to treat tobacco dependence have measureable effects on patients' smoking. Tobacco consumption in low- and middle-income countries (LMICs) is high and slowly decreasing, but these countries usually lack measures to face the epidemic, including tobacco cessation training programs for health professionals and organizations. Based on a previous online smoking cessation training program for hospital workers in Spain, the Fruitful Study aims to increase smoking cessation knowledge, attitudes, self-confidence, and performance interventions among health care professionals of three Spanish-speaking low- and middle-income Latin American and Caribbean (LAC) countries. OBJECTIVE: The purpose of this paper is to describe the methodology and evaluation strategy of the Fruitful Study intended to adapt, implement, and test the effectiveness of an online, evidence-based tobacco cessation training program addressed to health professionals from Bolivia, Guatemala, and Paraguay. METHODS: This study will use a mixed-methods design with a pre-post evaluation (quantitative approach) and in-depth interviews and focus groups (qualitative approach). The main outcomes will be (1) participants' attitudes, knowledge, and behaviors before and after the training; and (2) the level of implementation of tobacco control policies within the hospitals before and after the training. RESULTS: To date, adaptation of the materials, study enrollment, and training activities have been completed. During the adaptation, the main mismatches were language background and content adaptation. Several aids were developed to enable students' training enrollment, including access to computers, support from technicians, and reminders to correctly complete the course. Follow-up data collection is in progress. We have enrolled 281 hospital workers. Results are expected at the beginning of 2017 and will be reported in two follow-up papers: one about the formative evaluation and the other about the summative evaluation. CONCLUSIONS: There is a need to learn more about the cultural and content elements that should be modified when an online tobacco cessation training program is adapted to new contexts. Special attention should be given to the personal and material resources that could make the implementation possible. Results from the Fruitful Study may offer a new approach to adapting programs to LMICs in order to offer education solutions with the use of emerging and growing communication technologies. CLINICALTRIAL: Clinicaltrials.gov NCT02718872; https://clinicaltrials.gov/ct2/show/NCT02718872 (Archived by WebCite at http://www.webcitation.org/6mjihsgE2).
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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 | 0.049 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".