Examining sustainability in a hospital setting: Case of smoking cessation
Bibliographic record
Abstract
BACKGROUND: The Ottawa Model of Smoking Cessation (OMSC) is a hospital-based smoking cessation program that is expanding across Canada. While the short-term effectiveness of hospital cessation programs has been documented, less is known about long-term sustainability. The purpose of this exploratory study was to understand how hospitals using the OMSC were addressing sustainability and determine if there were critical factors or issues that should be addressed as the program expanded. METHODS: Six hospitals that differed on OMSC program activities (identify and document smokers, advise quitting, provide medication, and offer follow-up) were intentionally selected, and two key informants per hospital were interviewed using a semi-structured interview guide. Key informants were asked to reflect on the initial decision to implement the OMSC, the current implementation process, and perceived sustainability of the program. Qualitative analysis of the interview transcripts was conducted and themes related to problem definition, stakeholder influence, and program features emerged. RESULTS: Sustainability was operationalized as higher performance of OMSC activities than at baseline. Factors identified in the literature as important for sustainability, such as program design, differences in implementation, organizational characteristics, and the community environment did not explain differences in program sustainability. Instead, key informants identified factors that reflected the interaction between how the health problem was defined by stakeholders, how priorities and concerns were addressed, features of the program itself, and fit within the hospital context and resources as being influential to the sustainability of the program. CONCLUSIONS: Applying a sustainability model to a hospital smoking cessation program allowed for an examination of how decisions made during implementation may impact sustainability. Examining these factors during implementation may provide insight into issues affecting program sustainability, and foster development of a sustainability plan. Based on this study, we suggest that sustainability plans should focus on enhancing interactions between the health problem, program features, and stakeholder influence.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".