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Table 3 Relationship between perceived importance and perceived availability

From: Understanding perceived availability and importance of tobacco control interventions to inform European adoption of a UK economic model: a cross-sectional study

  Descriptive analysis Ordered logistic regression analysis
Interventions Available Not available Predicted probability of saying important [95% CI]a
  Number saying important (%) Number saying somewhat important (%) Number saying not important (%) Number saying important (%) Number saying somewhat important (%) Number saying not important (%)
Community pharmacy-based services (N = 78) 30 (50.0) 19 (31.67) 11 (18.33) 6 (33.33) 4 (22.22) 8 (44.44) 54.28%* [38.64–69.93%]
Computer tailored programs (N = 75) 25 (41.67) 27 (45.00) 8 (13.33) 3 (20.00) 7 (46.67) 5 (33.33) 44.71%* [30.35–59.08%]
Internet-based interventions (N = 77) 35 (53.03) 23 (34.85) 8 (12.12) 1 (9.09) 7 (63.64) 3 (27.27) 53.41%* [39.54–67.29%]
Stage-based interventions (N = 70) 34 (59.65) 16 (28.07) 7 (12.28) 5 (38.46) 3 (23.08) 5 (38.46) 72.90%* [57.89–87.91%]
Brief advice by a general practitioner and medication (N = 91) 49 (59.76) 27 (32.93) 6 (7.32) 2 (22.22) 2 (22.22) 5 (55.56) 62.53%* [51.24–73.82%]
  1. aPredicted probability of saying ‘important’ if the intervention is available, when holding other variables at means. It was estimated by ordered logistic regression model evaluating the effect of availability (yes or no) on importance (not important, somewhat important, or important) controlling for countries, stakeholder roles, and gender
  2. *The regression models were significant with p-values < 0.05. Availability was a significant variable associated with importance for these interventions in the models with the p-values of 0.03, 0.004, 0.01, 0.002, and < 0.001, respectively