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

The influence of sociodemographic, tobacco use, and mental health characteristics on treatment adherence among adults enrolled in a community-based tobacco cessation program

Background

While counseling and pharmacological interventions are known to facilitate smoking cessation, poor adherence can impact their effectiveness. Therefore, this study aimed to identify personal and clinical factors that influenced adherence to smoking cessation treatment among socioeconomically disadvantaged adult Oklahomans enrolled in a publicly available tobacco treatment program and observational research study.

Methods

Adult participants (N = 442) were enrolled in a community-based tobacco treatment program. Logistic regression models identified sociodemographic, mental health, and substance use characteristics associated with treatment adherence. Adherence was measured by counseling session attendance and weeks of moderate/high medication adherence assessed via the Medication Adherence Questionnaire. Analyses were conducted using SAS 9.4 with p < 0.05.

Results

Participants (mean age of 53, 55 % female, and 42.3 % racially minoritized), smoked 16 (SD = 10) cigarettes/day for 30 years on average (SD = 15), and 44.8 % reported depression (Center for Epidemiological Studies Depression Scale [CESD] score ≥ 10). Self-efficacy, White race, increasing age, and years of smoking were positively associated with counseling adherence, while menthol use, being uninsured, and depression predicted lower counseling adherence. Medication adherence was lower among individuals who used menthol cigarettes, lived with someone who smoked, and had higher levels of expired carbon monoxide.

Conclusions

This study highlights key factors that influenced adherence to smoking cessation treatment in a socioeconomically disadvantaged population. Tailored interventions are needed to address social, behavioral, and environmental factors, such as living situations and mental health, in smoking cessation interventions to enhance treatment outcomes for underserved populations. Future tobacco cessation programs should consider these factors to improve adherence and, ultimately, success rates.

Digital Smoking Cessation Intervention for Cancer Survivors: Analysis of Predictors and Moderators of Engagement and Outcome Alongside a Randomized Controlled Trial

BACKGROUND

Recent studies have shown positive, though small, clinical effects of digital smoking cessation (SC) interventions for cancer survivors. However, research on associations among participant characteristics, intervention engagement, and outcomes is limited.

OBJECTIVE

This study aimed to explore the predictors and moderators of engagement and outcome of MyCourse-Quit Smoking (in Dutch: "MijnKoers-Stoppen met Roken"), a digital minimally guided intervention for cancer survivors.

METHODS

A secondary analysis of data from the randomized controlled trial was performed. The number of cigarettes smoked in the past 7 days at 6-month follow-up was the primary outcome measure. We analyzed interactions among participant characteristics (11 variables), intervention engagement (3 variables), and outcome using robust linear (mixed) modeling.

RESULTS

In total, 165 participants were included in this study. Female participants accessed the intervention less often than male participants (B=-11.12; P=.004). A higher Alcohol Use Disorders Identification Test score at baseline was associated with a significantly higher number of logins (B=1.10; P<.001) and diary registrations (B=1.29; P<.001). A higher Fagerström Test for Nicotine Dependence score at baseline in the intervention group was associated with a significantly larger reduction in tobacco use after 6 months (B=-9.86; P=.002). No other associations and no moderating effects were found.

CONCLUSIONS

Overall, a limited number of associations was found between participant characteristics, engagement, and outcome, except for gender, problematic alcohol use, and nicotine dependence. Future studies are needed to shed light on how this knowledge can be used to improve the effects of digital SC programs for cancer survivors.

TRIAL REGISTRATION

Netherlands Trial register NTR6011/NL5434; https://onderzoekmetmensen.nl/nl/trial/22832.

Comparing the Effectiveness of the Blended Delivery Mode With the Face-to-Face Delivery Mode of Smoking Cessation Treatment: Noninferiority Randomized Controlled Trial

BACKGROUND

Tobacco consumption is a leading cause of death and disease, killing >8 million people each year. Smoking cessation significantly reduces the risk of developing smoking-related diseases. Although combined treatment for addiction is promising, evidence of its effectiveness is still emerging. Currently, there is no published research comparing the effectiveness of blended smoking cessation treatments (BSCTs) with face-to-face (F2F) treatments, where web-based components replace 50% of the F2F components in blended treatment.

OBJECTIVE

The primary objective of this 2-arm noninferiority randomized controlled trial was to determine whether a BSCT is noninferior to an F2F treatment with identical ingredients in achieving abstinence rates.

METHODS

This study included 344 individuals who smoke (at least 1 cigarette per day) attending an outpatient smoking cessation clinic in the Netherlands. The participants received either a blended 50% F2F and 50% web-based BSCT or only F2F treatment with similar content and intensity. The primary outcome measure was cotinine-validated abstinence rates from all smoking products at 3 and 15 months after treatment initiation. Additional measures included carbon monoxide-validated point prevalence abstinence; self-reported point prevalence abstinence; and self-reported continuous abstinence rates at 3, 6, 9, and 15 months after treatment initiation.

RESULTS

None of the 13 outcomes showed statistically confirmed noninferiority of the BSCT, whereas 4 outcomes showed significantly (P<.001) inferior abstinence rates of the BSCT: cotinine-validated point prevalence abstinence rate at 3 months (difference 12.7, 95% CI 6.2-19.4), self-reported point prevalence abstinence rate at 6 months (difference 19.3, 95% CI 11.5-27.0) and at 15 months (difference 11.7, 95% CI 5.8-17.9), and self-reported continuous abstinence rate at 6 months (difference 13.8, 95% CI 6.8-20.8). The remaining 9 outcomes, including the cotinine-validated point prevalence abstinence rate at 15 months, were inconclusive.

CONCLUSIONS

In this high-intensity outpatient smoking cessation trial, the blended mode was predominantly less effective than the traditional F2F mode. The results contradict the widely assumed potential benefits of blended treatment and suggest that further research is needed to identify the critical factors in the design of blended interventions.

TRIAL REGISTRATION

Netherlands Trial Register 27150; https://onderzoekmetmensen.nl/nl/trial/27150.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-doi.org/10.1186/s12889-016-3851-x.

Essential oils for agitation in dementia [rELOAD]: A pragmatic, cluster-randomized, placebo-controlled, pilot feasibility trial

BACKGROUND

Clinical guidelines recommend non-pharmacological interventions as the first line of treatment for agitation in dementia. One intervention that shows some promise as a treatment for agitation is essential oils. The objective of this study was to provide preliminary evidence of the effectiveness and feasibility of using topically-administered, individualized essential oil preparations for the alleviation of agitation in persons with dementia.

METHODS

We conducted a 10-week pragmatic, cluster-randomized, placebo-controlled, pilot feasibility trial to compare the effectiveness of topically-administered, individualized essential oil preparations to control (placebo) preparations. Outcomes included frequency and severity of agitation, quality of life, frequency of antipsychotic medication use and physical restraint, incidence of adverse events, and trial feasibility. Participants with dementia and clinically significant agitation were recruited from five residential aged-care facilities across regional South Australia.

RESULTS

Thirty-eight participants were randomized from five sites. Accounting for random effects, we found statistically significant differences between the intervention and control groups in Pittsburgh Agitation Scale (PAS) aberrant vocalization sub score, Cohen Mansfield Agitation Inventory (CMAI) verbally agitated sub score and CMAI total score at week 4, but not at weeks 8 (post-intervention) or 10 (follow-up). No significant time-group interactions were observed for other PAS/CMAI scores or sub scores, quality of life - Alzheimer's disease total score, or frequency of physical restraint or as-needed antipsychotic medication. No adverse events were reported in any group.

CONCLUSIONS

The study findings highlight some promising effects of topically-administered, individualized essential oil preparations for agitation in dementia, and indicate that a large multi-center, cluster-randomized controlled trial of this treatment is feasible.

TRIAL REGISTRATION

Australian New Zealand Clinical Trial Registry [ACTRN12617001159347].

BLEND-A: blending internet treatment into conventional face-to-face treatment for alcohol use disorder - a study protocol

BACKGROUND

A major challenge to psychological treatment for alcohol use disorder (AUD) is patient non-compliance. A promising new treatment approach that is hypothesized to increase patient compliance is blended treatment, consisting of face-to-face contact with a therapist combined with modules delivered over the internet within the same protocol. While this treatment concept has been developed and proven effective for a variety of mental disorders, it has not yet been examined for AUD.

AIMS

The study described in this protocol aims to examine and evaluate patient compliance with blended AUD treatment as well as the clinical and cost effectiveness of such treatment compared to face-to-face treatment only.

METHODS

The study design is a pragmatic, stepped-wedge cluster randomized controlled trial. The included outpatient institutions (planned number of patients: n = 1800) will be randomized in clusters to implement either blended AUD treatment or face-to-face treatment only, i.e. treatment as usual (TAU). Both treatment approaches consist of motivational interviewing and cognitive behavioral therapy. Data on sociodemographics, treatment (e.g. intensity, duration), type of treatment conclusion (compliance vs. dropout), alcohol consumption, addiction severity, consequences of drinking, and quality of life, will be collected at treatment entry, at treatment conclusion, and 6 months after treatment conclusion. The primary outcome is compliance at treatment conclusion, and the secondary outcomes include alcohol consumption and quality of life at six-months follow-up. Data will be analyzed with an Intention-to-treat approach by means of generalized linear mixed models with a random effect for cluster and fixed effect for each step. Also, analyses evaluating cost-effectiveness will be conducted.

DISCUSSION

Blended treatment may increase treatment compliance and thus improve treatment outcomes due to increased flexibility of the treatment course. Since this study is conducted within an implementation framework it can easily be scaled up, and when successful, blended treatment has the potential to become an alternative offer in many outpatient clinics nationwide and internationally.

TRIAL REGISTRATION

Clinicaltrials.gov .: NCT04535258 , retrospectively registered 01.09.20.

Development and validation of a diabetes mellitus treatment adherence scale

AIMS

The aim of this study was to develop a Diabetes Mellitus Treatment Adherence Scale (DMTAS) to fill the gap in the internationally accepted comprehensive scale.

METHODS

An initial item pool for the Diabetes Mellitus Treatment Adherence Scale (DMTAS) was generated based on a review of the literature and an open-ended interview. An expert group screened this initial item pool using an item-level content validity index. Then, pilot testing with 116 participants was conducted. After removing redundant and cross-loading items by exploratory factor analysis, 630 subjects were recruited to evaluate the reliability and validity of DMTAS. Analyses included internal consistency, test-retest reliability, split-half reliability, construct validity, convergent validity, and discriminant validity analysis.

RESULTS

The final DMTAS consisted of 19 items and six dimensions. The results of the exploratory factor analysis indicated that the variances of each factor explained were 23.07%, 12.28%, 9.50%, 8.25%, 7.85%, and 5.80%, and all six factors explained 66.75% of the variance in the 19 items. The items' factor loadings were all above 0.6. The results of the confirmatory factor analysis indicated that adequate fit indices (χ2 value to degrees of freedom = 3.62; root mean square error of approximation = 0.06; goodness-of-fit index = 0.92) were achieved. The Cronbach's alpha coefficient was 0.79, test-retest reliability was 0.73, and split-half reliability was 0.75.

CONCLUSIONS

The DMTAS showed good validity and reliability to measure the out-of-hospital treatment adherence in patients with diabetes mellitus.

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

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.

Patients' User Experience of a Blended Face-to-Face and Web-Based Smoking Cessation Treatment: Qualitative Study

Background

Blended web-based and face-to-face (F2F) treatment is a promising electronic health service because the strengths of one mode of delivery should compensate for the weaknesses of the other.

Objective

The aim of this study was to explore this compensation by examining patients’ user experience (UX) in a blended smoking cessation treatment (BSCT) in routine care.

Methods

Data on patients’ UX were collected through in-depth interviews (n=10) at an outpatient smoking cessation clinic in the Netherlands. A content analysis of the semantic domains was used to analyze patients’ UX. To describe the UX, the Hassenzahl UX model was applied, examining 4 of the 5 key elements of UX from a user’s perspective: (1) patients’ standards and expectations, (2) apparent character (pragmatic and hedonic attributes), (3) usage situation, and (4) consequences (appeal, emotions, and behavior).

Results

BSCT appeared to be a mostly positively experienced service. Patients had a positive-pragmatic standard and neutral-open expectation toward BSCT at the treatment start. The pragmatic attributes of the F2F sessions were mostly perceived as positive, whereas the pragmatic attributes of the web sessions were perceived as both positive and negative. For the hedonic attributes, there seemed to be a difference between the F2F and web sessions. Specifically, the hedonic attributes of the web sessions were experienced as mostly negative, whereas those of the F2F sessions were experienced as mostly positive. For the usage situation, the physical and social contexts were experienced positively, whereas the task and technical contexts were experienced negatively. Nevertheless, the consequential appeal of BSCT was positive. However, the consequential emotions and behavior varied, ultimately resulting in diverse combinations of consequential appeal, emotions, and behavior (positive, negative, and mixed).

Conclusions

This study provided insights into the UX of a blended treatment, and the results support the expectation that in a blended treatment, the strengths of one mode of delivery may compensate for the weaknesses of the other. However, in this certain setting, this is mainly achieved in only one way: F2F sessions compensated for the weaknesses of the web sessions. As a practical conclusion, this may mean that the web sessions, supported by the strengths of the F2F sessions, offer an interesting approach for further improving the blended treatment. Our theoretical findings reflect the relevance of the aspects of hedonism, such as fun, joy, or happiness in the UX, which were not mentioned in relation to the web sessions and were only scarcely mentioned in relation to the F2F sessions. Future research should further investigate the role of hedonistic aspects in a blended treatment and whether increased enjoyment of a blended treatment could increase treatment adherence and, ultimately, effectiveness.

Predictors of Smoking Cessation in a Lifestyle-Focused Text-Message Support Programme Delivered to People with Coronary Heart Disease: An Analysis From the Tobacco Exercise and Diet Messages (TEXTME) Randomised Clinical Trial

Background:

Studies have demonstrated the effectiveness of text message-based prevention programs on smoking cessation, including our recently published TEXTME randomised controlled trial. However, little is known about the predictors of smoking cessation in this context and if other clinically important factors interact with the program to lead to quitting. Hence, the objective of this study was to first assess the predictors of smoking cessation in TEXTME and then determine if the effect of texting on quitting was modified by interactions with important clinical variables. This will allow us to better understand how text messaging works and thus help optimise future text-message based prevention programs.

Methods

This sub-analysis used data collected as part of the TEXTME trial which recruited 710 participants (377 current smokers at baseline) between September 2011 and November 2013 from a large tertiary hospital in Sydney, Australia. Smokers at baseline were analysed at 6 months and grouped into those who quit and those who did not. Univariate analyses were performed to determine associations between the main outcome and clinically important baseline factors selected a priori. A multiple binominal logistic regression analysis was conducted to develop a predictive model for the dependent variable smoking cessation. A test of interaction between the intervention group and baseline variables selected a priori with the outcome smoking cessation was performed.

Results

Univariate analysis identified receiving text-messages, age, and mean number of cigarettes smoked each day as being associated with quitting smoking. After adjusting for age, receiving the text-messaging program (OR 2.34; 95%CI 1.43-3.86; p<0.01) and mean number of cigarettes smoked per day (OR 1.02; 95%CI 1.00-1.04; p=0.03) were independent predictors for smoking cessation. LDL-C showed a significant interaction effect with the intervention (High LDL*Intervention OR 3.77 (95%CI 2.05-6.94); Low LDL*Intervention OR 1.42 (95%CI 0.77-2.60); P=0.03).

Conclusions

Smoking quantity at baseline is independently associated with smoking cessation and higher LDL-C may interact with the intervention to result in quitting smoking. Those who have a higher baseline risk maybe more motivated towards beneficial lifestyle change including quitting smoking, and thus more likely to respond to mHealth smoking cessation programs. The effect of text-messages on smoking cessation was independent of age, gender, psychosocial parameters, education, and baseline control of risk factors in a secondary prevention cohort.