scholarly journals Blended Smoking Cessation Treatment: Exploring Measurement, Levels, and Predictors of Adherence

2018 ◽  
Vol 20 (8) ◽  
pp. e246 ◽  
Author(s):  
Lutz Siemer ◽  
Marjolein GJ Brusse-Keizer ◽  
Marloes G Postel ◽  
Somaya Ben Allouch ◽  
Angelos Patrinopoulos Bougioukas ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Smoking Cessation Treatment ◽  
Cessation Treatment ◽  
Predictors Of Adherence

scholarly journals Adherence to Blended or Face-to-Face Smoking Cessation Treatment and Predictors of Adherence: Randomized Controlled Trial

10.2196/17207 ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. e17207
Author(s):  
Lutz Siemer ◽  
Marjolein G J Brusse-Keizer ◽  
Marloes G Postel ◽  
Somaya Ben Allouch ◽  
Robbert Sanderman ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Treatment Time ◽  
Patient Characteristics ◽  
Smoking Cessation Treatment ◽  
Face To Face ◽  
Cessation Treatment ◽  
The Face ◽  
Blended Treatment ◽  
Predictors Of Adherence ◽  
The Web

Background Blended face-to-face and web-based treatment is a promising way to deliver smoking cessation treatment. Since adherence has been shown to be an indicator of treatment acceptability and a determinant for effectiveness, we explored and compared adherence and predictors of adherence to blended and face-to-face alone smoking cessation treatments with similar content and intensity. Objective The objectives of this study were (1) to compare adherence to a blended smoking cessation treatment with adherence to a face-to-face treatment; (2) to compare adherence within the blended treatment to its face-to-face mode and web mode; and (3) to determine baseline predictors of adherence to both treatments as well as (4) the predictors to both modes of the blended treatment. Methods We calculated the total duration of treatment exposure for patients (N=292) of a Dutch outpatient smoking cessation clinic who were randomly assigned either to the blended smoking cessation treatment (n=130) or to a face-to-face treatment with identical components (n=162). For both treatments (blended and face-to-face) and for the two modes of delivery within the blended treatment (face-to-face vs web mode), adherence levels (ie, treatment time) were compared and the predictors of adherence were identified within 33 demographic, smoking-related, and health-related patient characteristics. Results We found no significant difference in adherence between the blended and the face-to-face treatments. Participants in the blended treatment group spent an average of 246 minutes in treatment (median 106.7% of intended treatment time, IQR 150%-355%) and participants in the face-to-face group spent 238 minutes (median 103.3% of intended treatment time, IQR 150%-330%). Within the blended group, adherence to the face-to-face mode was twice as high as that to the web mode. Participants in the blended group spent an average of 198 minutes (SD 120) in face-to-face mode (152% of the intended treatment time) and 75 minutes (SD 53) in web mode (75% of the intended treatment time). Higher age was the only characteristic consistently found to uniquely predict higher adherence in both the blended and face-to-face groups. For the face-to-face group, more social support for smoking cessation was also predictive of higher adherence. The variability in adherence explained by these predictors was rather low (blended R2=0.049; face-to-face R2=0.076). Within the blended group, living without children predicted higher adherence to the face-to-face mode (R2=0.034), independent of age. Higher adherence to the web mode of the blended treatment was predicted by a combination of an extrinsic motivation to quit, a less negative attitude toward quitting, and less health complaints (R2=0.164). Conclusions This study represents one of the first attempts to thoroughly compare adherence and predictors of adherence of a blended smoking cessation treatment to an equivalent face-to-face treatment. Interestingly, although the overall adherence to both treatments appeared to be high, adherence within the blended treatment was much higher for the face-to-face mode than for the web mode. This supports the idea that in blended treatment, one mode of delivery can compensate for the weaknesses of the other. Higher age was found to be a common predictor of adherence to the treatments. The low variance in adherence predicted by the characteristics examined in this study suggests that other variables such as provider-related health system factors and time-varying patient characteristics should be explored in future research. Trial Registration Netherlands Trial Register NTR5113; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5113

scholarly journals Blended Smoking Cessation Treatment: Exploring Measurement, Levels, and Predictors of Adherence (Preprint)

2018 ◽  
Author(s):  
Lutz Siemer ◽  
Marjolein GJ Brusse-Keizer ◽  
Marloes G Postel ◽  
Somaya Ben Allouch ◽  
Angelos Patrinopoulos Bougioukas ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Marital Status ◽  
Adherence Rate ◽  
Social Modeling ◽  
Web Based ◽  
Smoking Cessation Treatment ◽  
Face To Face ◽  
Cessation Treatment ◽  
Number Of Patients ◽  
Predictors Of Adherence

BACKGROUND Blended face-to-face and Web-based treatment is a promising way to deliver cognitive behavioral therapy. Since adherence has been shown to be a measure for treatment’s acceptability and a determinant for treatment’s effectiveness, in this study, we explored adherence to a new blended smoking cessation treatment (BSCT). OBJECTIVE The objective of our study was to (1) develop an adequate method to measure adherence to BSCT; (2) define an adequate degree of adherence to be used as a threshold for being adherent; (3) estimate adherence to BSCT; and (4) explore the possible predictors of adherence to BSCT. METHODS The data of patients (N=75) were analyzed to trace adherence to BSCT delivered at an outpatient smoking cessation clinic. In total, 18 patient activities (eg, using a Web-based smoking diary tool or responding to counselors’ messages) were selected to measure adherence; the degree of adherence per patient was compared with quitting success. The minimum degree of adherence of patients who reported abstinence was examined to define a threshold for the detection of adherent patients. The number of adherent patients was calculated for each of the 18 selected activities; the degree of adherence over the course of the treatment was displayed; and the number of patients who were adherent was analyzed. The relationship between adherence and 33 person-, smoking-, and health-related characteristics was examined. RESULTS The method for measuring adherence was found to be adequate as adherence to BSCT correlated with self-reported abstinence (P=.03). Patients reporting abstinence adhered to at least 61% of BSCT. Adherence declined over the course of the treatment; the percentage of adherent patients per treatment activity ranged from 82% at the start of the treatment to 11%-19% at the final-third of BSCT; applying a 61% threshold, 18% of the patients were classified as adherent. Marital status and social modeling were the best independent predictors of adherence. Patients having a partner had 11-times higher odds of being adherent (OR [odds ratio]=11.3; CI: 1.33-98.99; P=.03). For social modeling, graded from 0 (=partner and friends are not smoking) to 8 (=both partner and nearly all friends are smoking), each unit increase was associated with 28% lower odds of being adherent (OR=0.72; CI: 0.55-0.94; P=.02). CONCLUSIONS The current study is the first to explore adherence to a blended face-to-face and Web-based treatment (BSCT) based on a substantial group of patients. It revealed a rather low adherence rate to BSCT. The method for measuring adherence to BSCT could be considered adequate because the expected dose-response relationship between adherence and quitting could be verified. Furthermore, this study revealed that marital status and social modeling were independent predictors of adherence. CLINICALTRIAL Netherlands Trial Registry NTR5113; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5113 (Archived by WebCite at http://www.webcitation.org/71BAPwER8).

scholarly journals Adherence to Blended or Face-to-Face Smoking Cessation Treatment and Predictors of Adherence: Randomized Controlled Trial (Preprint)

2019 ◽  
Author(s):  
Lutz Siemer ◽  
Marjolein G J Brusse-Keizer ◽  
Marloes G Postel ◽  
Somaya Ben Allouch ◽  
Robbert Sanderman ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Treatment Time ◽  
Patient Characteristics ◽  
Smoking Cessation Treatment ◽  
Face To Face ◽  
Cessation Treatment ◽  
The Face ◽  
Blended Treatment ◽  
Predictors Of Adherence ◽  
The Web

BACKGROUND Blended face-to-face and web-based treatment is a promising way to deliver smoking cessation treatment. Since adherence has been shown to be an indicator of treatment acceptability and a determinant for effectiveness, we explored and compared adherence and predictors of adherence to blended and face-to-face alone smoking cessation treatments with similar content and intensity. OBJECTIVE The objectives of this study were (1) to compare adherence to a blended smoking cessation treatment with adherence to a face-to-face treatment; (2) to compare adherence within the blended treatment to its face-to-face mode and web mode; and (3) to determine baseline predictors of adherence to both treatments as well as (4) the predictors to both modes of the blended treatment. METHODS We calculated the total duration of treatment exposure for patients (N=292) of a Dutch outpatient smoking cessation clinic who were randomly assigned either to the blended smoking cessation treatment (n=130) or to a face-to-face treatment with identical components (n=162). For both treatments (blended and face-to-face) and for the two modes of delivery within the blended treatment (face-to-face vs web mode), adherence levels (ie, treatment time) were compared and the predictors of adherence were identified within 33 demographic, smoking-related, and health-related patient characteristics. RESULTS We found no significant difference in adherence between the blended and the face-to-face treatments. Participants in the blended treatment group spent an average of 246 minutes in treatment (median 106.7% of intended treatment time, IQR 150%-355%) and participants in the face-to-face group spent 238 minutes (median 103.3% of intended treatment time, IQR 150%-330%). Within the blended group, adherence to the face-to-face mode was twice as high as that to the web mode. Participants in the blended group spent an average of 198 minutes (SD 120) in face-to-face mode (152% of the intended treatment time) and 75 minutes (SD 53) in web mode (75% of the intended treatment time). Higher age was the only characteristic consistently found to uniquely predict higher adherence in both the blended and face-to-face groups. For the face-to-face group, more social support for smoking cessation was also predictive of higher adherence. The variability in adherence explained by these predictors was rather low (blended R<sup>2</sup>=0.049; face-to-face R<sup>2</sup>=0.076). Within the blended group, living without children predicted higher adherence to the face-to-face mode (R<sup>2</sup>=0.034), independent of age. Higher adherence to the web mode of the blended treatment was predicted by a combination of an extrinsic motivation to quit, a less negative attitude toward quitting, and less health complaints (R<sup>2</sup>=0.164). CONCLUSIONS This study represents one of the first attempts to thoroughly compare adherence and predictors of adherence of a blended smoking cessation treatment to an equivalent face-to-face treatment. Interestingly, although the overall adherence to both treatments appeared to be high, adherence within the blended treatment was much higher for the face-to-face mode than for the web mode. This supports the idea that in blended treatment, one mode of delivery can compensate for the weaknesses of the other. Higher age was found to be a common predictor of adherence to the treatments. The low variance in adherence predicted by the characteristics examined in this study suggests that other variables such as provider-related health system factors and time-varying patient characteristics should be explored in future research. CLINICALTRIAL Netherlands Trial Register NTR5113; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5113

“Impact of Smoking Cessation Treatment” on Lung Function and Response Rate in EGFR Mutated Patients: A Short-Term Cohort Study

2015 ◽  
Vol 10 (3) ◽  
pp. 342-351 ◽  
Author(s):  
Aldo Pezzuto ◽  
Luciano Stumbo ◽  
Marco Russano ◽  
Pierfilippo Crucitti ◽  
Simone Scarlata ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Cohort Study ◽  
Lung Function ◽  
Response Rate ◽  
Short Term ◽  
Smoking Cessation Treatment ◽  
Cessation Treatment ◽  
Egfr Mutated

scholarly journals Electronic cigarettes in standard smoking cessation treatment by tobacco counselors in Flanders: E-cigarette users show similar if not higher quit rates as those using commonly recommended smoking cessation aids

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Karolien Adriaens ◽  
Eline Belmans ◽  
Dinska Van Gucht ◽  
Frank Baeyens
Keyword(s):  
Smoking Cessation ◽  
Cohort Study ◽  
Replacement Therapy ◽  
Electronic Cigarettes ◽  
Evidence Based ◽  
Smoking Abstinence ◽  
Smoking Cessation Treatment ◽  
Cessation Treatment ◽  
Point Prevalence Abstinence

Abstract Background This interventional-cohort study tried to answer if people who smoke and choose an e-cigarette in the context of smoking cessation treatment by tobacco counselors in Flanders are achieving smoking abstinence and how they compare to clients who opt for commonly recommended (or no) aids (nicotine replacement therapy, smoking cessation medication). Methods Participants were recruited by tobacco counselors. They followed smoking cessation treatment (in group) for 2 months. At several times during treatment and 7 months after quit date, participants were asked to fill out questionnaires and to perform eCO measurements. Results One third of all participants (n = 244) achieved smoking abstinence 7 months after the quit date, with e-cigarette users having higher chances to be smoking abstinent at the final session compared to NRT users. Point prevalence abstinence rates across all follow-up measurements, however, as well as continuous and prolonged smoking abstinence, were similar in e-cigarette users and in clients having chosen a commonly recommended (or no) smoking cessation aid. No differences were obtained between smoking cessation aids with respect to product use and experiences. Conclusions People who smoke and choose e-cigarettes in the context of smoking cessation treatment by tobacco counselors show similar if not higher smoking cessation rates compared to those choosing other evidence-based (or no) smoking cessation aids.

scholarly journals Smoking cessation treatment for COPD smokers: the role of counselling

2015 ◽  
Vol 79 (1) ◽  
Author(s):  
C.A. Jiménez-Ruiz ◽  
K.O. Fagerström
Keyword(s):  
Smoking Cessation ◽  
Weight Gain ◽  
Direct Relationship ◽  
Gain Control ◽  
Self Esteem ◽  
Smoking Cessation Treatment ◽  
Quit Attempt ◽  
Previous Diagnosis ◽  
Cessation Treatment

Smoking cessation is the only therapeutic intervention that can prevent COPD smokers from the chronic progression of their disorder. The most important intervention for helping these smokers to quit is a combination of counseling plus pharmacological treatment. The characteristics of the counseling should be different depending if this intervention is offered to smokers with a previous diagnosis of COPD or if the intervention is offered to smokers who have been recently diagnoses with COPD. The counseling of patients who have been recently diagnosed should include: a) explanation of the direct relationship between smoking and COPD, b) encouraging these patients to quit and c) using of spirometry and measurements of CO as a motivational tools. The counseling of patients who have been previously diagnosed should include: a) encouragement to make a serious quit attempt, b) an intervention that increases motivation, self-efficacy and self-esteem, c) and the intervention should also control depression and be directed to weight gain control.

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