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HOW DO WE MEASURE ADHERENCE TO A BLENDED SMOKING CESSATION TREATMENT?

L Siemer, M Brusse-Keizer, M Postel, S. Ben Allouch, P Patrinopoulos, R Sanderman , M Pieterse. HOW DO WE MEASURE ADHERENCE TO A BLENDED SMOKING CESSATION TREATMENT?. Background: Blended Treatment. promising way to deliver behavioral change interventions

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HOW DO WE MEASURE ADHERENCE TO A BLENDED SMOKING CESSATION TREATMENT?

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  1. L Siemer, M Brusse-Keizer, M Postel, S. Ben Allouch, P Patrinopoulos, R Sanderman, M Pieterse HOW DO WE MEASURE ADHERENCE TO A BLENDED SMOKING CESSATION TREATMENT?

  2. Background: Blended Treatment promising way to deliver behavioral change interventions combining the strengths of face-to-face (F2F) treatment with the unique features of Web-based care ”best of both worlds”

  3. Background: Adherence • Primary determinant of treatment effectiveness (dose-response relationship) • Definition of adherence: • extent to which a person’s behavior—taking medication, following a diet, or executing lifestyle changes—corresponds with recommendations from a health care provider (WHO) • Measurement • F2F: completed tasks and/or attended sessions • Web: log-ins, module completion, time spend online, messages/emails, print requests …

  4. Questions • How do we measure adherence to a blended treatment? • Develop and compare two measure (time vs. features) • Do they classify equally into adherent/non-adherent? • How valid are the measures? • Which advantages/disadvantages has each measure?

  5. Method: studyparticipants BSCT • Subset of an RCT on the effectiveness of BSCT versus F2F-treatment as usual • Outpatient smoking cessation clinic at the Medical Spectrum Twente hospital (Enschede/The Netherlands) • Inclusion criteria • being at least 18 years old, • currently smoking (at least one cigarette a day) • having access to email and internet • being able to read and write Dutch

  6. Method: studyintervention BSCT A combination of F2F-treatment and Web-based sessions blended into one integrated smoking cessation treatment delivered in routine care settings Consists of 5 F2F sessions at the outpatient clinic and 5 Web-based sessions (50-50 balance between F2F and Web) High-intensity treatment (6h total) derived from the Dutch Guideline Tobacco Addiction, fulfilling the requirements of the Dutch care module for smoking cessation

  7. Time-basedmeasure • Summing up time in treatment based on hospital administration, eg.: • First individual F2F session 50 min • Usual F2F session 20 min • Usual Web session 20 min • Telephone consult 20 min • ... • Adherence (60%-threshold) • At least 80/130 min. spent in F2F sessions • AND • At least 60/100 min. spent in Web sessions

  8. Features-basedmeasure • Active use of treatment features (based on patients‘ records of the outpatient clinic and the Web-platform) that ... • … refer to a relevant evidence-based behavior change technique (eg. goal setting, action plan) • … trace both F2F and Web-based behaviors of patients (eg, attending face-to-face treatment sessions as in “Think differently [F2F]” or completion of predefined Web-based tasks as in “Think differently” [Web]”) • … are objective (eg.receiving a message, unblocking a Web-based tool, filling in a minimal number of data in a Web-based tool such as eg. a smoking diary) • Adherence (60%-threshold) • Active use of at least 5/8 F2F features • AND • At least 6/10 Web features

  9. Results: How do patients adhere (60%-threshold)? Minutes-based measure: 33 (47.1%) adherent, 37 (52.9%) non-adherent Features-based measure: 14 (20%) adherent, 56 (80%) non-adherent

  10. Results: How do we measure adherence? Validity • Construct (both good) • Convergent • Minutes-based measure: correctly classified the patients in 70% of the cases • Feature-based measure: correctly classified the patients in 81.4% of the cases • Divergent: adherence was unrelated to non-adherence-related patients' baseline characteristics for both measures • Content (good) • Cohen's kappa test showed moderate agreement between the evaluation of adherence using the minutes-based and the features-based measure (κ = .438, p < .001) - agreement in the classification of 51 (72.9%) patients • Criterion • Concurrent (good): adherence assessed using the minutes-based measure was highly correlated with adherence evaluated using the features-based measure (rho(70) = .529, p < .001) • Predictive (unequal) • Minutes-based measure: adherence not associated with smoking abstinence (N=38, p = .47) • Feature-based measure: adherence associated with smoking abstinence (N=17, p = .03)

  11. Advantages and disadvantages

  12. Conclusion Both adherence measures correlate reasonably well with each other. Both adherence measures have useful content, construct and divergent validity. Predictive validity is only found for the content-based measure. Both methods seem adequate for clinical research. Measure can be chosen based on advantages and disadvantages of each measure.

  13. Literature Siemer, L., Pieterse, M. E., Brusse-Keizer, M. G., Postel, M. G., Allouch, S. B., & Sanderman, R. (2016). Study protocolfor a non-inferioritytrialof a blended smokingcessationtreatment versus face-to-face treatment (LiveSmokefree-Study). BMC publichealth, 16(1), 1187. Siemer, L., Brusse-Keizer, M. G., Postel, M. G., Allouch, S. B., Bougioukas, A. P., Sanderman, R., & Pieterse, M. E. (2018). Blended Smoking Cessation Treatment: Exploring Measurement, Levels, andPredictorsofAdherence. Journal ofmedical Internet research, 20(8). Patrinopoulos Bougioukas, A. (2017). Adherence to blended smoking cessation treatment (Master's thesis, University of Twente).

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