Cost-effectiveness and cost-utility of Internet-based computer tailoring for smoking cessation

The Treatment Outcome of Smart Device-Based Tinnitus Retraining Therapy: Prospective Cohort Study

BACKGROUND

Tinnitus retraining therapy (TRT) is a standard treatment for tinnitus that consists of directive counseling and sound therapy. However, it is based on face-to-face education and a time-consuming protocol. Smart device-based TRT (smart-TRT) seems to have many advantages, but the efficacy of this new treatment has been questioned.

OBJECTIVE

The aim of this study was to compare the efficacy between smart-TRT and conventional TRT (conv-TRT).

METHODS

We recruited 84 patients with tinnitus. Results were compared between 42 patients who received smart-TRT and 42 control participants who received conv-TRT. An interactive smart pad application was used for directive counseling in the smart-TRT group. The smart pad application included detailed education on ear anatomy, the neurophysiological model of tinnitus, concept of habituation, and sound therapy. The smart-TRT was bidirectional: There were 17 multiple choice questions between each lesson as an interim check. The conv-TRT group underwent traditional person-to-person counseling. The primary outcome measure was the Tinnitus Handicap Inventory (THI), and the secondary outcome measure was assessed using a visual analogue scale (VAS).

RESULTS

Both treatments had a significant treatment effect, which comparably improved during the first 2 months. The best improvements in THI were -23.3 (95% CI -33.1 to -13.4) points at 3 months and -16.8 (95% CI -30.8 to -2.8) points at 2 months in the smart-TRT group and conv-TRT group, respectively. The improvements on the VAS were also comparable: smart-TRT group: -1.2 to -3.3; conv-TRT: -0.7 to -1.7.

CONCLUSIONS

TRT based on smart devices can be an effective alternative for tinnitus patients. Considering the amount of time needed for person-to-person counseling, smart-TRT can be a cost-effective solution with similar treatment outcomes as conv-TRT.

An economic evaluation of an online computer-tailored smoking cessation intervention that includes message frame-tailoring: A randomized controlled trial

Evidence of economic evaluations of behaviour change interventions is scarce, but needed to guide policy makers' decision-making. This study economically evaluated 4 versions of an innovative online computer-tailored smoking cessation intervention. The economic evaluation from a societal perspective was embedded in a randomized controlled trial among 532 smokers using a 2 (message frame-tailoring, i.e. how messages are presented: autonomy-supportive vs controlling) x 2 (content-tailoring, i.e. what content is presented: tailored vs. generic) design. Both kinds of tailoring, content-tailoring and message frame-tailoring, were based on a set of questions asked at baseline. Self-reported costs, prolonged smoking abstinence (cost-effectiveness) and quality of life (cost-utility) were assessed during a 6-month-follow-up. For cost-effectiveness analysis, costs per abstinent smoker were calculated. For cost-utility analysis, costs per QALY (i.e. quality-adjusted life year) gained were calculated. A willingness-to-pay (WTP) threshold of €20.000 was used. Bootstrapping and sensitivity analysis were conducted. Cost-effectiveness analysis showed that up to a WTP of €2.000, the combination of message frame- and content-tailoring dominated all study groups. From a WTP of €2.005, the content-tailored group dominated all study groups. Cost-utility analysis revealed that the combination of message frame-tailoring and content-tailoring had the highest probability of being the most efficient study group at all levels of the WTP. The combination of message frame-tailoring and content-tailoring in online smoking cessation programmes seemed to have high potential for cost-effectiveness (smoking abstinence) and cost-utility (quality of life), thus providing good value for money. Yet, when the WTP for each abstinent smoker is high (i.e., €2.005 or higher), the addition of message frame-tailoring might not be worth the effort and content-tailoring only is preferred.

Applying Collective Intelligence in Health Recommender Systems for Smoking Cessation: A Comparison Trial

Background: Health recommender systems (HRSs) are intelligent systems that can be used to tailor digital health interventions. We compared two HRSs to assess their impact providing smoking cessation support messages. Methods: Smokers who downloaded a mobile app to support smoking abstinence were randomly assigned to two interventions. They received personalized, ratable motivational messages on the app. The first intervention had a knowledge-based HRS (n = 181): it selected random messages from a subset matching the users’ demographics and smoking habits. The second intervention had a hybrid HRS using collective intelligence (n = 190): it selected messages applying the knowledge-based filter first, and then chose the ones with higher ratings provided by other similar users in the system. Both interventions were compared on: (a) message appreciation, (b) engagement with the system, and (c) one’s own self-reported smoking cessation status, as indicated by the last seven-day point prevalence report in different time intervals during a period of six months. Results: Both interventions had similar message appreciation, number of rated messages, and abstinence results. The knowledge-based HRS achieved a significantly higher number of active days, number of abstinence reports, and better abstinence results. The hybrid algorithm led to more quitting attempts in participants who completed their user profiles.

Efficacy of an acceptance and commitment therapy-based smartphone application for helping rural populations quit smoking: Results from the iCanQuit randomized trial

Limited access to evidence-based smoking cessation interventions among rural populations contributes to high rates of cigarette smoking and poor cessation outcomes. Yet, accessible digital interventions for cessation focusing on rural populations are lacking. In a secondary analysis, we determined the acceptability and efficacy of an Acceptance and Commitment Therapy (ACT)-based smartphone application (iCanQuit) relative to a U.S. Clinical Practice Guidelines (USCPG)-based smartphone application (QuitGuide) for smoking cessation among rural participants enrolled in the two-arm randomized iCanQuit trial. Participants were enrolled between May 2017 and September 2018 and randomized to either receive iCanQuit or QuitGuide for 12-months. Rural residence was determined by sub-county level Rural-Urban Commuting Area codes. A total of 550 rural participants were recruited from 43 U.S. states. Self-reported complete-case 30-day point-prevalence abstinence was 15% (33/226) for iCanQuit vs. 9% (22/253) for QuitGuide at 3-months (OR = 1.83; 95% CI: 1.03, 3.25) and 29% (66/231) for iCanQuit vs. 25% (64/288) for QuitGuide at 12-months (OR = 1.19 95% CI: 0.80, 1.79). Retention rate was 89% at 12-months and did not differ by arm. iCanQuit vs. QuitGuide participants were significantly more engaged and satisfied with the iCanQuit application. Increased acceptance of internal cues to smoke mediated the effect of treatment on cessation. Findings suggest that iCanQuit had significantly higher short-term quit rates, descriptively higher long-term quit rates, and operated through its hypothesized mechanisms of action relative to QuitGuide. Future larger studies are needed to further evaluate the efficacy of and methods for disseminating the iCanQuit application for smoking cessation among U.S. rural adults nationwide. Trial registrationClinicalTrials.gov Identifier: NCT02724462.

Economic Evaluation of Digital Health Interventions: Methodological Issues and Recommendations for Practice

Health care interventions are increasingly being delivered through digital technologies, offering major opportunities for delivering more health gains from scarce health care resources. Digital health interventions (DHIs) raise distinct challenges for economic evaluations compared with drugs and medical devices, not least due to their interacting, evolving features. The implications of the distinctive nature of DHIs for the methodological choices underpinning their economic evaluation is not well understood. This paper provides an in-depth discussion of distinct features of DHIs and how they might impact the design, measurement, analysis and reporting of cost-effectiveness analysis conducted alongside both randomised and non-randomised studies. These include aspects related to choice of comparator, costs and benefits assessment, study perspective and type of economic analysis. We argue that typical methodological standpoints, such as taking a health service perspective, focusing on health-related benefits and adopting cost-utility analyses, as typically adopted in the economic evaluation of non-digital technologies (pharmaceutical drugs and medical devices), are unlikely to be appropriate for DHIs. We illustrate how these methodological aspects can be appropriately addressed in an evaluation of a digitally supported, remote rehabilitation programme for patients with Long Covid in England. We highlight several methodological considerations for improving practice and areas where further methodological work is required.

Digital interventions in mental health: evidence syntheses and economic modelling

BACKGROUND

Economic evaluations provide evidence on whether or not digital interventions offer value for money, based on their costs and outcomes relative to the costs and outcomes of alternatives.

OBJECTIVES

(1) Evaluate and summarise published economic studies about digital interventions across different technologies, therapies, comparators and mental health conditions; (2) synthesise clinical evidence about digital interventions for an exemplar mental health condition; (3) construct an economic model for the same exemplar mental health condition using the previously synthesised clinical evidence; and (4) consult with stakeholders about how they understand and assess the value of digital interventions.

METHODS

We completed four work packages: (1) a systematic review and quality assessment of economic studies about digital interventions; (2) a systematic review and network meta-analysis of randomised controlled trials on digital interventions for generalised anxiety disorder; (3) an economic model and value-of-information analysis on digital interventions for generalised anxiety disorder; and (4) a series of knowledge exchange face-to-face and digital seminars with stakeholders.

RESULTS

In work package 1, we reviewed 76 economic evaluations: 11 economic models and 65 within-trial analyses. Although the results of the studies are not directly comparable because they used different methods, the overall picture suggests that digital interventions are likely to be cost-effective, compared with no intervention and non-therapeutic controls, whereas the value of digital interventions compared with face-to-face therapy or printed manuals is unclear. In work package 2, we carried out two network meta-analyses of 20 randomised controlled trials of digital interventions for generalised anxiety disorder with a total of 2350 participants. The results were used to inform our economic model, but when considered on their own they were inconclusive because of the very wide confidence intervals. In work package 3, our decision-analytic model found that digital interventions for generalised anxiety disorder were associated with lower net monetary benefit than medication and face-to-face therapy, but greater net monetary benefit than non-therapeutic controls and no intervention. Value for money was driven by clinical outcomes rather than by intervention costs, and a value-of-information analysis suggested that uncertainty in the treatment effect had the greatest value (£12.9B). In work package 4, stakeholders identified several areas of benefits and costs of digital interventions that are important to them, including safety, sustainability and reducing waiting times. Four factors may influence their decisions to use digital interventions, other than costs and outcomes: increasing patient choice, reaching underserved populations, enabling continuous care and accepting the 'inevitability of going digital'.

LIMITATIONS

There was substantial uncertainty around effect estimates of digital interventions compared with alternatives. This uncertainty was driven by the small number of studies informing most comparisons, the small samples in some of these studies and the studies' high risk of bias.

CONCLUSIONS

Digital interventions may offer good value for money as an alternative to 'doing nothing' or 'doing something non-therapeutic' (e.g. monitoring or having a general discussion), but their added value compared with medication, face-to-face therapy and printed manuals is uncertain. Clinical outcomes rather than intervention costs drive 'value for money'.

FUTURE WORK

There is a need to develop digital interventions that are more effective, rather than just cheaper, than their alternatives.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42018105837.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 1. See the NIHR Journals Library website for further project information.

The Usability of an Online Tool to Promote the Use of Evidence-Based Smoking Cessation Interventions

To increase usage of evidence-based smoking cessation interventions (EBSCIs) among smokers, an online decision aid (DA) was developed. The aims of this study were (1) to conduct a usability evaluation; (2) to conduct a program evaluation and evaluate decisional conflict after using the DA and (3) to determine the possible change in the intention to use EBSCIs before and directly after reviewing the DA. A cross-sectional study was carried out in September 2020 by recruiting smokers via the Internet (n = 497). Chi-squared tests and t-tests were conducted to test the differences between smokers who differed in the perceived usability of the DA on the program evaluation and in decisional conflict. The possible changes in intention to use EBSCIs during a cessation attempt before and after reviewing the DA were tested using t-tests, McNemar's test and χ2 analysis. The participants evaluated the usability of the DA as moderate (MU; n = 393, 79.1%) or good (GU; n = 104, 20.9%). GU smokers rated higher on all the elements of the program evaluation and experienced less decisional conflict, but also displayed a higher intention to quit. After reviewing the DA, the participants on average had a significantly higher intention to use more EBSCIs, in particular in the form of eHealth. Recommendations to make the DA more usable could include tailoring, using video-based information and including value clarification methods. Furthermore, a hybrid variant in which smokers can use the DA independently and with the guidance of a primary care professional could aid both groups in choosing a fitting EBSCI option.

Message Frame-Tailoring in Digital Health Communication: Intervention Redesign and Usability Testing (Preprint)

Background

Message frame–tailoring based on the need for autonomy is a promising strategy to improve the effectiveness of digital health communication interventions. An example of a digital health communication intervention is Personal Advice in Stopping smoking (PAS), a web-based content-tailored smoking cessation program. PAS was effective in improving cessation success rates, but its effect sizes were small and disappeared after 6 months. Therefore, investigating whether message frame–tailoring based on the individual’s need for autonomy might improve effect rates is worthwhile. However, to our knowledge, this has not been studied previously.

Objective

To investigate whether adding message frame–tailoring based on the need for autonomy increases the effectiveness of content-tailored interventions, the PAS program was redesigned to incorporate message frame–tailoring also. This paper described the process of redesigning the PAS program to include message frame–tailoring, providing smokers with autonomy-supportive or controlling message frames—depending on their individual need for autonomy. Therefore, we aimed to extend framing theory, tailoring theory, and self-determination theory.

Methods

Extension of the framing theory, tailoring theory, and self-determination theory by redesigning the PAS program to include message frame–tailoring was conducted in close collaboration with scientific and nonscientific smoking cessation experts (n=10), smokers (n=816), and communication science students (n=19). Various methods were used to redesign the PAS program to include message frame–tailoring with optimal usability: usability testing, think-aloud methodology, heuristic evaluations, and a web-based experiment.

Results

The most autonomy-supportive and controlling message frames were identified, the cutoff point for the need for autonomy to distinguish between people with high and those with low need for autonomy was determined, and the usability was optimized.

Conclusions

This resulted in a redesigned digital health communication intervention that included message frame–tailoring and had optimal usability. A detailed description of the redesigning process of the PAS program is provided.

Trial Registration

Netherlands Trial Register NL6512 (NRT6700); https://www.trialregister.nl/trial/6512

A systematic review of trial-based economic evaluations of internet- and mobile-based interventions for substance use disorders

BACKGROUND

Substance use disorders (SUDs) contribute significantly to global rates of morbidity and mortality. Internet- and mobile-based interventions (IMIs) have been suggested as an adjunct to face-to-face health services. However, the evidence for the cost-effectiveness of IMIs for SUDs is scant.

METHODS

A comprehensive literature search in PubMed, PsycINFO, the Cochrane Central Register of Controlled Trials, NHS Economic Evaluations Database, NHS Health Technology Assessment Database, Office of Health Economics Evaluations Database and EconLit was conducted. We included economic evaluations alongside randomized controlled trials of IMIs for SUDs compared with a control group.

RESULTS

Of 1687 abstracts identified, 11 studies met the inclusion criteria. Targeted conditions were alcohol use disorder (four studies) and tobacco smoking (five studies) whereas two studies included any SUD. Cost-effectiveness results demonstrated that IMIs had a firm probability of being more cost-effective than TAU (e.g. less costs per additional abstinent person). Compared with (online) psycho-education, evidence towards an additional benefit of IMIs was less clear. Regarding cost-utility (e.g. costs per quality-adjusted life year gained), except for one study, results suggested that TAU and online psycho-education would probably be more preferable than IMIs. Quality of study reporting was at least adequate.

CONCLUSIONS

The likelihood of IMIs being more cost-effective than TAU looks promising but more economic evaluations are needed in order to determine the economic merit of IMIs. With an increasing pressure on health care budgets, strategies to disseminate effective interventions at affordable costs are required. This review suggests that IMIs might carry that promise and have potential as a cost-effective strategy to scale-up existing evidence-based treatments for SUDs.

SYSTEMATIC REVIEW REGISTRATION

The systematic review has been registered in the PROSPERO database (no. CRD42018099486).

Evaluation of an integrated treatment to address smoking cessation and anxiety/depressive symptoms among people living with HIV: Study protocol for a randomized controlled trial

BACKGROUND

Interventions that target anxiety/depressive symptoms in the context of smoking treatment have shown promise irrespective of psychiatric diagnosis. Yet, these tailored treatments are largely absent for persons who smoke and are living with HIV (SLWH).

OBJECTIVE

To evaluate a novel, smoking cessation intervention that addresses anxiety/depression and HIV-related health (QUIT) against a time-matched control (TMC) and a standard of care (SOC) condition.

METHODS

SLWH (N = 180) will be recruited and enrolled from 3 medical clinics in Boston, MA, and Houston, TX. The trial will consist of a baseline assessment, a 10-week intervention/assessment period, and follow-up assessments, accounting for a total study duration of approximately 8 months. All participants will complete a baseline visit and a pre-randomization standardized psychoeducation visit, and will then be randomized to one of three conditions: QUIT, TMC, or SOC. QUIT and TMC will consist of nine 60-min, cognitive behavioral therapy-based, individual weekly counseling sessions using standard smoking cessation counseling; additionally, QUIT will target anxiety and depressive symptoms by addressing underlying mechanisms related to mood and quit difficulty. SOC participants will complete weekly self-report surveys for nine weeks. All participants will be encouraged to quit at Session 7 and will be offered nicotine replacement therapy to help.

CONCLUSIONS

QUIT is designed to improve smoking cessation in SLWH by addressing anxiety and depression and HIV-related health issues. If successful, the QUIT intervention would be ready for implementation and dissemination into "real-world" behavioral health and social service settings consistent with the four objectives outlined in NIDA's Strategic Plan.

A Web-Based Computer-Tailored Program to Improve Treatment Adherence in Patients With Type 2 Diabetes: Randomized Controlled Trial

Background

Adherence to core type 2 diabetes mellitus (T2DM) treatment behaviors is suboptimal, and nonadherence is generally not limited to one treatment behavior. The internet holds promise for programs that aim to improve adherence. We developed a computer-tailored eHealth program for patients with T2DM to improve their treatment adherence, that is, adherence to both a healthy lifestyle and medical behaviors.

Objective

The objective of this study is to examine the effectiveness of the eHealth program in a randomized controlled trial.

Methods

Patients with T2DM were recruited by their health professionals and randomized into either the intervention group, that is, access to the eHealth program for 6 months, or a waiting-list control group. In total, 478 participants completed the baseline questionnaire, of which 234 gained access to the eHealth program. Of the 478 participants, 323 were male and 155 were female, the mean age was 60 years, and the participants had unfavorable BMI and HbA_1c levels on average. Outcome data were collected through web-based assessments on physical activity (PA) levels, caloric intake from unhealthy snacks, and adherence to oral hypoglycemic agents (OHAs) and insulin therapy. Changes to separate behaviors were standardized and summed into a composite change score representing changes in the overall treatment adherence. Further standardization of this composite change score yielded the primary outcome, which can be interpreted as Cohen d (effect size). Standardized change scores observed in separate behaviors acted as secondary outcomes. Mixed linear regression analyses were conducted to examine the effectiveness of the intervention on overall and separate treatment behavior adherence, accommodating relevant covariates and patient nesting.

Results

After the 6-month follow-up assessment, 47.4% (111/234) of participants in the intervention group and 72.5% (177/244) of participants in the control group were retained. The overall treatment adherence improved significantly in the intervention group compared with the control group, reflected by a small effect size (d=0.27; 95% CI 0.032 to 0.509; P=.03). When considering changes in separate treatment behaviors, a significant decrease was observed only in caloric intake from unhealthy snacks in comparison with the control group (d=0.36; 95% CI 0.136 to 0.584; P=.002). For adherence to PA (d=−0.14; 95% CI −0.388 to 0.109; P=.27), OHAs (d=0.27; 95% CI −0.027 to 0.457; P=.08), and insulin therapy (d=0.35; 95% CI −0.066 to 0.773; P=.10), no significant changes were observed. These results from the unadjusted analyses were comparable with the results of the adjusted analyses, the per-protocol analyses, and the sensitivity analyses.

Conclusions

Our multibehavior program significantly improved the overall treatment adherence compared with the control group. To further enhance the impact of the intervention in the personal, societal, and economic areas, a wide-scale implementation of our eHealth intervention is suggested.

Trial Registration

Netherlands Trial Register NL664; https://www.trialregister.nl/trial/6664

Behavioural interventions for smoking cessation: an overview and network meta-analysis

BACKGROUND

Smoking is a leading cause of disease and death worldwide. In people who smoke, quitting smoking can reverse much of the damage. Many people use behavioural interventions to help them quit smoking; these interventions can vary substantially in their content and effectiveness.

OBJECTIVES

To summarise the evidence from Cochrane Reviews that assessed the effect of behavioural interventions designed to support smoking cessation attempts and to conduct a network meta-analysis to determine how modes of delivery; person delivering the intervention; and the nature, focus, and intensity of behavioural interventions for smoking cessation influence the likelihood of achieving abstinence six months after attempting to stop smoking; and whether the effects of behavioural interventions depend upon other characteristics, including population, setting, and the provision of pharmacotherapy. To summarise the availability and principal findings of economic evaluations of behavioural interventions for smoking cessation, in terms of comparative costs and cost-effectiveness, in the form of a brief economic commentary.

METHODS

This work comprises two main elements. 1. We conducted a Cochrane Overview of reviews following standard Cochrane methods. We identified Cochrane Reviews of behavioural interventions (including all non-pharmacological interventions, e.g. counselling, exercise, hypnotherapy, self-help materials) for smoking cessation by searching the Cochrane Library in July 2020. We evaluated the methodological quality of reviews using AMSTAR 2 and synthesised data from the reviews narratively. 2. We used the included reviews to identify randomised controlled trials of behavioural interventions for smoking cessation compared with other behavioural interventions or no intervention for smoking cessation. To be included, studies had to include adult smokers and measure smoking abstinence at six months or longer. Screening, data extraction, and risk of bias assessment followed standard Cochrane methods. We synthesised data using Bayesian component network meta-analysis (CNMA), examining the effects of 38 different components compared to minimal intervention. Components included behavioural and motivational elements, intervention providers, delivery modes, nature, focus, and intensity of the behavioural intervention. We used component network meta-regression (CNMR) to evaluate the influence of population characteristics, provision of pharmacotherapy, and intervention intensity on the component effects. We evaluated certainty of the evidence using GRADE domains. We assumed an additive effect for individual components.

MAIN RESULTS

We included 33 Cochrane Reviews, from which 312 randomised controlled trials, representing 250,563 participants and 845 distinct study arms, met the criteria for inclusion in our component network meta-analysis. This represented 437 different combinations of components. Of the 33 reviews, confidence in review findings was high in four reviews and moderate in nine reviews, as measured by the AMSTAR 2 critical appraisal tool. The remaining 20 reviews were low or critically low due to one or more critical weaknesses, most commonly inadequate investigation or discussion (or both) of the impact of publication bias. Of note, the critical weaknesses identified did not affect the searching, screening, or data extraction elements of the review process, which have direct bearing on our CNMA. Of the included studies, 125/312 were at low risk of bias overall, 50 were at high risk of bias, and the remainder were at unclear risk. Analyses from the contributing reviews and from our CNMA showed behavioural interventions for smoking cessation can increase quit rates, but effectiveness varies on characteristics of the support provided. There was high-certainty evidence of benefit for the provision of counselling (odds ratio (OR) 1.44, 95% credibility interval (CrI) 1.22 to 1.70, 194 studies, n = 72,273) and guaranteed financial incentives (OR 1.46, 95% CrI 1.15 to 1.85, 19 studies, n = 8877). Evidence of benefit remained when removing studies at high risk of bias. These findings were consistent with pair-wise meta-analyses from contributing reviews. There was moderate-certainty evidence of benefit for interventions delivered via text message (downgraded due to unexplained statistical heterogeneity in pair-wise comparison), and for the following components where point estimates suggested benefit but CrIs incorporated no clinically significant difference: individual tailoring; intervention content including motivational components; intervention content focused on how to quit. The remaining intervention components had low-to very low-certainty evidence, with the main issues being imprecision and risk of bias. There was no evidence to suggest an increase in harms in groups receiving behavioural support for smoking cessation. Intervention effects were not changed by adjusting for population characteristics, but data were limited. Increasing intensity of behavioural support, as measured through the number of contacts, duration of each contact, and programme length, had point estimates associated with modestly increased chances of quitting, but CrIs included no difference. The effect of behavioural support for smoking cessation appeared slightly less pronounced when people were already receiving smoking cessation pharmacotherapies.

AUTHORS' CONCLUSIONS

Behavioural support for smoking cessation can increase quit rates at six months or longer, with no evidence that support increases harms. This is the case whether or not smoking cessation pharmacotherapy is also provided, but the effect is slightly more pronounced in the absence of pharmacotherapy. Evidence of benefit is strongest for the provision of any form of counselling, and guaranteed financial incentives. Evidence suggested possible benefit but the need of further studies to evaluate: individual tailoring; delivery via text message, email, and audio recording; delivery by lay health advisor; and intervention content with motivational components and a focus on how to quit. We identified 23 economic evaluations; evidence did not consistently suggest one type of behavioural intervention for smoking cessation was more cost-effective than another. Future reviews should fully consider publication bias. Tools to investigate publication bias and to evaluate certainty in CNMA are needed.

Persoonlijke gezondheidscounseling via e-health

Zowel in de huisartsenpraktijk als in de klinische setting krijgt een gezonde leefstijl en trouw medicijngebruik meer aandacht bij chronische patiënten. Naast face-to-face-counseling kan leefstijl- en medicatieadvies ook via e-health plaatsvinden. E-health-interventies zijn effectief én kosten-effectief gebleken. Wanneer onderbouwd met een gedegen theoretisch gedragsmodel, kan e-health een zinvolle en waardevolle aanvulling zijn op face-to-facecounseling.

A smoker's choice? Identifying the most autonomy-supportive message frame in an online computer-tailored smoking cessation intervention

OBJECTIVE

To test the effect of autonomy-supportive message framing on people's perceived autonomy-support while considering the individual need for autonomy as a moderator. Also, to test whether autonomy-supportive message frames - through increased perceived autonomy-support - lead to more self-determined motivation, and increased intention to quit smoking.

DESIGN

An online 2(autonomy-supportive; controlling language) × 2(choice; no choice) between-subjects design with control condition (generic advice) with adult smokers intending to quit (N = 626).

MAIN OUTCOME

Intention to quit smoking (Theory of Planned Behaviour).

MEASURES

Perceived autonomy-support (Virtual Climate Care Questionnaire), need for autonomy (Health Causality Orientations Scale), self-determined motivation (Treatment Self-Regulation Questionnaire), attitudes, social influence, self-efficacy (I-Change Model).

RESULTS

Structural equation modelling revealed no significant effect of autonomy-supportive-message frames on perceived autonomy-support or self-determined motivation, neither did the need for autonomy moderate these effects. Self-determined motivation had a positive, significant effect on intention to quit, mediated by attitudes, social influence, and self-efficacy.

CONCLUSION

Although message frames did not affect perceived autonomy-support or self-determined motivation, higher self-determined motivation increased intention to quit via attitudes, social influence, and self-efficacy. Before drawing the conclusion that message framing has no effect, we recommend to replicate this study in a real-life setting with smokers more likely to read and process the message frames more attentively.

Understanding Self-Guided Web-Based Educational Interventions for Patients With Chronic Health Conditions: Systematic Review of Intervention Features and Adherence

Background

Chronic diseases contribute to 71% of deaths worldwide every year, and an estimated 15 million people between the ages of 30 and 69 years die mainly because of cardiovascular disease, cancer, chronic respiratory diseases, or diabetes. Web-based educational interventions may facilitate disease management. These are also considered to be a flexible and low-cost method to deliver tailored information to patients. Previous studies concluded that the implementation of different features and the degree of adherence to the intervention are key factors in determining the success of the intervention. However, limited research has been conducted to understand the acceptability of specific features and user adherence to self-guided web interventions.

Objective

This systematic review aims to understand how web-based intervention features are evaluated, to investigate their acceptability, and to describe how adherence to web-based self-guided interventions is defined and measured.

Methods

Studies published on self-guided web-based educational interventions for people (≥14 years old) with chronic health conditions published between January 2005 and June 2020 were reviewed following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Statement protocol. The search was performed using the PubMed, Cochrane Library, and EMBASE (Excerpta Medica dataBASE) databases; the reference lists of the selected articles were also reviewed. The comparison of the interventions and analysis of the features were based on the published content from the selected articles.

Results

A total of 20 studies were included. Seven principal features were identified, with goal setting, self-monitoring, and feedback being the most frequently used. The acceptability of the features was measured based on the comments collected from users, their association with clinical outcomes, or device adherence. The use of quizzes was positively reported by participants. Self-monitoring, goal setting, feedback, and discussion forums yielded mixed results. The negative acceptability was related to the choice of the discussion topic, lack of face-to-face contact, and technical issues. This review shows that the evaluation of adherence to educational interventions was inconsistent among the studies, limiting comparisons. A clear definition of adherence to an intervention is lacking.

Conclusions

Although limited information was available, it appears that features related to interaction and personalization are important for improving clinical outcomes and users’ experience. When designing web-based interventions, the selection of features should be based on the targeted population’s needs, the balance between positive and negative impacts of having human involvement in the intervention, and the reduction of technical barriers. There is a lack of consensus on the method of evaluating adherence to an intervention. Both investigations of the acceptability features and adherence should be considered when designing and evaluating web-based interventions. A proof-of-concept or pilot study would be useful for establishing the required level of engagement needed to define adherence.

Cost-effectiveness and cost-utility analysis of a work-place smoking cessation intervention with and without financial incentives

AIMS

To perform an economic evaluation of a work-place smoking cessation group training programme with incentives compared with a training programme without incentives.

DESIGN

A trial-based cost-effectiveness analysis (CEA) and cost-utility analysis (CUA) from a societal perspective and an employer's perspective.

SETTING

Sixty-one companies in the Netherlands.

PARTICIPANTS

A total of 604 tobacco-smoking employees.

INTERVENTION AND COMPARATOR

A 7-week work-place smoking cessation group training programme. The intervention group earned gift vouchers of €350 for 12 months' continuous abstinence. The comparator group received no incentives.

MEASUREMENTS

Online questionnaires were administered to assess quality of life (EQ-5D-5 L) and resource use during the 14-month follow-up period (2-month training period plus 12-month abstinence period). For the CEA the primary outcome measure was carbon monoxide (CO)-validated continuous abstinence; for the CUA the primary outcome was quality-adjusted life years (QALY). Bootstrapping and sensitivity analyses were performed to account for uncertainty. Incremental cost-effectiveness ratio (ICER) tables were used to determine cost-effectiveness from a life-time perspective.

FINDINGS

Of the participants in the intervention group, 41.1% had quit smoking compared with 26.4% in the control group. From a societal perspective with a 14-month follow-up period, the ICER per quitter for an intervention with financial incentives compared with no incentives was €11 546. From an employer's perspective, the ICER was €5686. There was no significant difference in QALYs between the intervention and control group within the 14-month follow-up period. The intervention was dominated by the comparator in the primary analysis at a threshold of €20 000 per QALY. In the sensitivity analysis, these results were uncertain. A life-time perspective showed an ICER of €1249 (95% confidence interval = €850-2387) per QALY.

CONCLUSIONS

Financial incentives may be cost-effective in increasing quitting smoking, particularly from a life-time perspective.

An economic evaluation of a computer-tailored e-learning program to promote smoking cessation counseling guideline adherence among practice nurses

OBJECTIVE

To conduct an economic evaluation of a tailored e-learning program, which successfully improved practice nurses' smoking cessation guideline adherence.

METHODS

The economic evaluation was embedded in a randomized controlled trial, in which 269 practice nurses recruited 388 smoking patients. Cost-effectiveness was assessed using guideline adherence as effect measure on practice nurse level, and continued smoking abstinence on patient level. Cost-utility was assessed on patient level, using patients' Quality Adjusted Life Years (QALYs) as effect measure.

RESULTS

The e-learning program was likely to be cost-effective on practice nurse level, as adherence to an additional guideline step cost €1,586. On patient level, cost-effectiveness was slightly likely after six months (cost per additional quitter: €7,126), but not after twelve months. The cost-utility analysis revealed slight cost-effectiveness (cost per QALY gained: €18,431) on patient level.

CONCLUSION

Providing practice nurses with a tailored e-learning program is cost-effective to improve their smoking cessation counseling. Though, cost-effectiveness on patient level was not found after twelve months, potentially resulting from smoking relapse.

PRACTICE IMPLICATIONS

Widespread implementation of the e-learning program can improve the quality of smoking cessation care in general practice. Strategies to prevent patients' smoking relapse should be further explored to improve patients' long-term abstinence.

[Prevention of substance use disorders]

Prevention of substance use disorders Abstract. Introduction: Adolescence is a vulnerable period for the development of Substance Use Disorders and preventive intervention is a public health priority. In this article, we summarize the available evidence for behavioral preventive action for Substance Use Disorders and related dysregulated behaviors during adolescence in various settings. Results: Current meta-analytic evidence is available mainly for the school and family settings and increasingly also for internet-based prevention. The literature is dominated by US-studies that focus on universal school-based approaches for legal substances in middle adolescence. Only few German studies are published. Taken together the results indicate that developmentally sensitive substance use prevention is effective across different settings with consistent small-to-middle sized effects. Differential effectiveness analyses for schoolbased prevention suggest that younger adolescents benefit most from universal prevention, while for older adolescents targeted approaches are more effective. Conclusions: Across the relevant settings, effective preventive measures are available. However, the results could be improved. There is a need for translational research on effective and more individualized approaches to prevention and differential effects of intervention modules. Moreover, there is a need for research on the implementation of evidence-based programs and especially in Germany, coordinated approaches on community levels are lacking.

A web-based program to improve treatment adherence in patients with type 2 diabetes: Development and study protocol

BACKGROUND

Many patients with type 2 diabetes mellitus (T2DM) sub-optimally adhere to core treatment recommendations, such as healthy diets, sufficient physical activity and pharmacological support. This paper describes the development of the web-based computer-tailored program My Diabetes Profile (MDP), incorporating identified success factors of web-based interventions, and the protocol for testing the effectiveness of this program in a randomized multicentre trial.

METHODS

Formative research - including the input of a program committee, qualitative and quantitative studies with patients and health professionals and a literature search - yielded input for the development of the MDP program. MDP provides video and text tailored advice, based on determinants and salient beliefs derived from the I-Change Model, on decreasing unhealthy snack intake, increasing physical activity, and improving adherence to both oral blood glucose lowering drugs and self-administered insulin therapy. Patients with T2DM recruited by practice nurses and diabetes nurses across the Netherlands fill in online questionnaires at baseline and six-months follow-up. Participants are randomized on patient level to the intervention group (access to the MDP program) or control group (receiving care as usual).

DISCUSSION

The formative research using co-creation principles proved essential in the development of the MDP program and involved various disciplines in T2DM management including target group representatives. Co-creation revealed clearly that patients needed short and attractive messages. Consequently, a mix of video and short text messages were chosen for the ultimate program format. Pilot testing was useful to further shape the program to needs of patients and professionals.

TRIAL REGISTRATION

Dutch Trial Register NTR6840; Archived program website: http://www.webcitation.org/6xXz01S7X.

Is it cost-effective to provide internet-based interventions to complement the current provision of smoking cessation services in the Netherlands? An analysis based on the EQUIPTMOD

BACKGROUND AND AIM

The cost-effectiveness of internet-based smoking cessation interventions is difficult to determine when they are provided as a complement to current smoking cessation services. The aim of this study was to evaluate the cost-effectiveness of such an alternate package compared with existing smoking cessation services alone (current package).

METHODS

A literature search was conducted to identify internet-based smoking cessation interventions in the Netherlands. A meta-analysis was then performed to determine the pooled effectiveness of a (web-based) computer-tailored intervention. The mean cost of implementing internet based interventions was calculated using available information, while intervention reach was sourced from an English study. We used EQUIPTMOD, a Markov-based state-transition model, to calculate the incremental cost-effectiveness ratios [expressed as cost per quality-adjusted life years (QALYs) gained] for different time horizons to assess the value of providing internet-based interventions to complement the current package.). Deterministic sensitivity analyses tested the uncertainty around intervention costs per smoker, relative risks, and the intervention reach.

RESULTS

Internet-based interventions had an estimated pooled relative risk of 1.40; average costs per smoker of €2.71; and a reach of 0.41% of all smokers. The alternate package (i.e. provision of internet-based intervention to the current package) was dominant (cost-saving) compared with the current package alone (0.14 QALY gained per 1000 smokers; reduced health-care costs of €602.91 per 1000 smokers for the life-time horizon). The alternate package remained dominant in all sensitivity analyses.

CONCLUSION

Providing internet-based smoking cessation interventions to complement the current provision of smoking cessation services could be a cost-saving policy option in the Netherlands.

Tailored Versus Generic Knowledge Brokering to Integrate Mood Management Into Smoking Cessation Interventions in Primary Care Settings: Protocol for a Cluster Randomized Controlled Trial

Background

Both tobacco smoking and depression are major public health problems associated with high morbidity and mortality. In addition, individuals with depression are almost twice as likely to smoke and less likely to achieve smoking cessation. In the Smoking Treatment for Ontario Patients program, an established smoking cessation program in Ontario, Canada, 38% of smokers in primary care settings have current or past depression with 6-month quit rates that are significantly lower than those without depression (33% versus 40%, P<.001). Integrating self-help mood management (eg, relaxation exercises and mood monitoring) with smoking cessation treatment increases long-term quit rates by 12%-20%. However, integration in real-world settings has not been reported. It is unclear which knowledge translation strategy would be more effective for motivating clinicians to provide resources on mood management to eligible patients.

Objective

The objectives of this study are to investigate the following comparisons among depressed smokers enrolled in a smoking cessation program: 1) the effectiveness of generalized, exclusively email-based prompts versus a personalized knowledge broker in implementing mood management interventions; 2) the effectiveness of the two knowledge translation strategies on smoking quit rates; and 3) the incremental costs of the two knowledge translation strategies on the implementation of mood management interventions.

Methods

The study design is a cluster randomized controlled trial of Family Health Teams participating in the Smoking Treatment for Ontario Patients program. Family Health Teams will be randomly allocated 1:1 to receive either generalized messages (related to depression and smoking) exclusively via email (group A) or be assigned a knowledge broker who provides personalized support through phone- and email-based check-ins (group B). The primary outcome, measured at the site level, is the proportion of eligible baseline visits that result in the provision of the mood management intervention to eligible patients.

Results

Recruitment for the primary outcome of this study will be completed in 2018/2019. Results will be reported in 2019/2020.

Conclusions

This study will address the knowledge gap in the implementation strategies (ie, email-based prompts versus a knowledge broker) of mood management interventions for smokers with depression in primary care settings.

Trial Registration

ClinicalTrials.gov NCT03130998; https://clinicaltrials.gov/ct2/show/NCT03130998 (Archived on WebCite at www.webcitation.org/6ylyS6RTe)

Subgroups Among Smokers in Preparation: A Cluster Analysis Using the I-Change Model

BACKGROUND

Investigating potential sub-stages of change could provide important information that could be used to improve the tailoring of smoking cessation interventions to individual smokers' profiles. Smokers in the preparation stage may be most interesting, as they are most likely to participate in smoking cessation interventions.

OBJECTIVE

To examine whether Dutch adult smokers in the preparation stage of change, i.e. motivated to quit smoking within one month, can be organized into subgroups.

METHODS

Data from 753 smokers who participated in an effectiveness trial of a web-based, computer-tailored smoking cessation programme were subjected to secondary analysis. Cluster analyses were based on respondents' baseline responses to items on pros and cons of quitting and quitting self-efficacy. Chi-squared tests and ANOVA were used to compare the baseline characteristics of the resulting clusters. Logistic and multinomial regression were used for longitudinal comparisons of clusters with respect to smoking abstinence and stage transition at six-week and six-month follow-ups.

RESULTS

Four clusters were identified; Classic, Unprepared, Progressing and Disengaged Preparers. Cross-sectional and longitudinal analyses validated these clusters: they differed with respect to the clustering variables, gender, cigarette dependence and educational level. Disengaged Preparers were less likely than Progressing Preparers to report smoking abstinence at six months (OR = 0.28; p < .05).

CONCLUSIONS

These results suggest that smoking cessation interventions tailored to the preparation stage of change, i.e. the set of cognitions usually present in preparers, are only appropriate for the subgroup we defined as Classic Preparers. The other clusters might need different interventions as they display different cognition sets.

Analyzing recommender systems for health promotion using a multidisciplinary taxonomy: A scoping review

BACKGROUND

Recommender systems are information retrieval systems that provide users with relevant items (e.g., through messages). Despite their extensive use in the e-commerce and leisure domains, their application in healthcare is still in its infancy. These systems may be used to create tailored health interventions, thus reducing the cost of healthcare and fostering a healthier lifestyle in the population.

OBJECTIVE

This paper identifies, categorizes, and analyzes the existing knowledge in terms of the literature published over the past 10 years on the use of health recommender systems for patient interventions. The aim of this study is to understand the scientific evidence generated about health recommender systems, to identify any gaps in this field to achieve the United Nations Sustainable Development Goal 3 (SDG3) (namely, "Ensure healthy lives and promote well-being for all at all ages"), and to suggest possible reasons for these gaps as well as to propose some solutions.

METHODS

We conducted a scoping review, which consisted of a keyword search of the literature related to health recommender systems for patients in the following databases: ScienceDirect, PsycInfo, Association for Computing Machinery, IEEExplore, and Pubmed. Further, we limited our search to consider only English-language journal articles published in the last 10 years. The reviewing process comprised three researchers who filtered the results simultaneously. The quantitative synthesis was conducted in parallel by two researchers, who classified each paper in terms of four aspects-the domain, the methodological and procedural aspects, the health promotion theoretical factors and behavior change theories, and the technical aspects-using a new multidisciplinary taxonomy.

RESULTS

Nineteen papers met the inclusion criteria and were included in the data analysis, for which thirty-three features were assessed. The nine features associated with the health promotion theoretical factors and behavior change theories were not observed in any of the selected studies, did not use principles of tailoring, and did not assess (cost)-effectiveness.

DISCUSSION

Health recommender systems may be further improved by using relevant behavior change strategies and by implementing essential characteristics of tailored interventions. In addition, many of the features required to assess each of the domain aspects, the methodological and procedural aspects, and technical aspects were not reported in the studies.

CONCLUSIONS

The studies analyzed presented few evidence in support of the positive effects of using health recommender systems in terms of cost-effectiveness and patient health outcomes. This is why future studies should ensure that all the proposed features are covered in our multidisciplinary taxonomy, including integration with electronic health records and the incorporation of health promotion theoretical factors and behavior change theories. This will render those studies more useful for policymakers since they will cover all aspects needed to determine their impact toward meeting SDG3.

Internet-based interventions for smoking cessation

BACKGROUND

Tobacco use is estimated to kill 7 million people a year. Nicotine is highly addictive, but surveys indicate that almost 70% of US and UK smokers would like to stop smoking. Although many smokers attempt to give up on their own, advice from a health professional increases the chances of quitting. As of 2016 there were 3.5 billion Internet users worldwide, making the Internet a potential platform to help people quit smoking.

OBJECTIVES

To determine the effectiveness of Internet-based interventions for smoking cessation, whether intervention effectiveness is altered by tailoring or interactive features, and if there is a difference in effectiveness between adolescents, young adults, and adults.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register, which included searches of MEDLINE, Embase and PsycINFO (through OVID). There were no restrictions placed on language, publication status or publication date. The most recent search was conducted in August 2016.

SELECTION CRITERIA

We included randomised controlled trials (RCTs). Participants were people who smoked, with no exclusions based on age, gender, ethnicity, language or health status. Any type of Internet intervention was eligible. The comparison condition could be a no-intervention control, a different Internet intervention, or a non-Internet intervention. To be included, studies must have measured smoking cessation at four weeks or longer.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed and extracted data. We extracted and, where appropriate, pooled smoking cessation outcomes of six-month follow-up or more, reporting short-term outcomes narratively where longer-term outcomes were not available. We reported study effects as a risk ratio (RR) with a 95% confidence interval (CI).We grouped studies according to whether they (1) compared an Internet intervention with a non-active control arm (e.g. printed self-help guides), (2) compared an Internet intervention with an active control arm (e.g. face-to-face counselling), (3) evaluated the addition of behavioural support to an Internet programme, or (4) compared one Internet intervention with another. Where appropriate we grouped studies by age.

MAIN RESULTS

We identified 67 RCTs, including data from over 110,000 participants. We pooled data from 35,969 participants.There were only four RCTs conducted in adolescence or young adults that were eligible for meta-analysis.Results for trials in adults: Eight trials compared a tailored and interactive Internet intervention to a non-active control. Pooled results demonstrated an effect in favour of the intervention (RR 1.15, 95% CI 1.01 to 1.30, n = 6786). However, statistical heterogeneity was high (I2 = 58%) and was unexplained, and the overall quality of evidence was low according to GRADE. Five trials compared an Internet intervention to an active control. The pooled effect estimate favoured the control group, but crossed the null (RR 0.92, 95% CI 0.78 to 1.09, n = 3806, I2 = 0%); GRADE quality rating was moderate. Five studies evaluated an Internet programme plus behavioural support compared to a non-active control (n = 2334). Pooled, these studies indicated a positive effect of the intervention (RR 1.69, 95% CI 1.30 to 2.18). Although statistical heterogeneity was substantial (I2 = 60%) and was unexplained, the GRADE rating was moderate. Four studies evaluated the Internet plus behavioural support compared to active control. None of the studies detected a difference between trial arms (RR 1.00, 95% CI 0.84 to 1.18, n = 2769, I2 = 0%); GRADE rating was moderate. Seven studies compared an interactive or tailored Internet intervention, or both, to an Internet intervention that was not tailored/interactive. Pooled results favoured the interactive or tailored programme, but the estimate crossed the null (RR 1.10, 95% CI 0.99 to 1.22, n = 14,623, I2 = 0%); GRADE rating was moderate. Three studies compared tailored with non-tailored Internet-based messages, compared to non-tailored messages. The tailored messages produced higher cessation rates compared to control, but the estimate was not precise (RR 1.17, 95% CI 0.97 to 1.41, n = 4040), and there was evidence of unexplained substantial statistical heterogeneity (I2 = 57%); GRADE rating was low.Results should be interpreted with caution as we judged some of the included studies to be at high risk of bias.

AUTHORS' CONCLUSIONS

The evidence from trials in adults suggests that interactive and tailored Internet-based interventions with or without additional behavioural support are moderately more effective than non-active controls at six months or longer, but there was no evidence that these interventions were better than other active smoking treatments. However some of the studies were at high risk of bias, and there was evidence of substantial statistical heterogeneity. Treatment effectiveness in younger people is unknown.

Evaluating a Web-Based Coaching Program Using Electronic Health Records for Patients With Chronic Obstructive Pulmonary Disease in China: Randomized Controlled Trial

Background

Chronic obstructive pulmonary disease (COPD) is now the fourth leading cause of death in the world, and it continues to increase in developing countries. The World Health Organization expects COPD to be the third most common cause of death in the world by 2020. Effective and continuous postdischarge care can help patients to maintain good health. The use of electronic health records (EHRs) as an element of community health care is new technology in China.

Objective

The aim of this study was to develop and evaluate a Web-based coaching program using EHRs for physical function and health-related quality of life for patients with COPD in China.

Methods

A randomized controlled trial was conducted from 2008 to 2015 at two hospitals. The control group received routine care and the intervention group received routine care with the addition of the Web-based coaching program using EHRs. These were used to manage patients’ demographic and clinical variables, publish relevant information, and have communication between patients and health care providers. Participants were not blinded to group assignment. The effects of the intervention were evaluated by lung function, including percent of forced expiratory volume in 1 second (FEV1%), percent of forced vital capacity (FVC%), peak expiratory flow (PEF), maximum midexpiratory flow; St George’s Respiratory Questionnaire (SGRQ); Modified Medical Research Council Dyspnea Scale (MMRC); and 6-Minute Walk Test (6MWT). Data were collected before the program, and at 1, 3, 6, and 12 months after the program.

Results

Of the 130 participants, 120 (92.3%) completed the 12-month follow-up program. There were statistically significant differences in lung function (FEV1%: F1,4=5.47, P=.002; FVC%: F1,4=3.06, P=.02; PEF: F1,4=12.49, P<.001), the total score of SGRQ (F1,4=23.30, P<.001), symptoms of SGRQ (F1,4=12.38, P<.001), the activity of SGRQ (F1,4=8.35, P<.001), the impact of SGRQ (F1,4=12.26, P<.001), MMRC (F1,4=47.94, P<.001), and 6MWT (F1,4=35.54, P<.001) between the two groups with the variation of time tendency.

Conclusions

The Web-based coaching program using EHRs in China appears to be useful for patients with COPD when they are discharged from hospital into the community. It promotes the sharing of patients’ medical information by hospital and community nurses, and achieves dynamic management and follow-up analysis for patients’ disease. In addition, this program can postpone the decreasing rate of lung function, improve quality of life, decrease dyspnea, and increase physical capacity.

A Review of the Theoretical Basis, Effects, and Cost Effectiveness of Online Smoking Cessation Interventions in the Netherlands: A Mixed-Methods Approach

BACKGROUND

Tobacco smoking is a worldwide public health problem. In 2015, 26.3% of the Dutch population aged 18 years and older smoked, 74.4% of them daily. More and more people have access to the Internet worldwide; approximately 94% of the Dutch population have online access. Internet-based smoking cessation interventions (online cessation interventions) provide an opportunity to tackle the scourge of tobacco.

OBJECTIVE

The goal of this paper was to provide an overview of online cessation interventions in the Netherlands, while exploring their effectivity, cost effectiveness, and theoretical basis.

METHODS

A mixed-methods approach was used to identify Dutch online cessation interventions, using (1) a scientific literature search, (2) a grey literature search, and (3) expert input. For the scientific literature, the Cochrane review was used and updated by two independent researchers (n=651 identified studies), screening titles, abstracts, and then full-text studies between 2013 and 2016 (CENTRAL, MEDLINE, and EMBASE). For the grey literature, the researchers conducted a Google search (n=100 websites), screening for titles and first pages. Including expert input, this resulted in six interventions identified in the scientific literature and 39 interventions via the grey literature. Extracted data included effectiveness, cost effectiveness, theoretical factors, and behavior change techniques used.

RESULTS

Overall, many interventions (45 identified) were offered. Of the 45 that we identified, only six that were included in trials provided data on effectiveness. Four of these were shown to be effective and cost effective. In the scientific literature, 83% (5/6) of these interventions included changing attitudes, providing social support, increasing self-efficacy, motivating smokers to make concrete action plans to prepare their attempts to quit and to cope with challenges, supporting identity change and advising on changing routines, coping, and medication use. In all, 50% (3/6) of the interventions included a reward for abstinence. Interventions identified in the grey literature were less consistent, with inclusion of each theoretical factor ranging from 31% to 67% and of each behavior change technique ranging from 28% to 54%.

CONCLUSIONS

Although the Internet may provide the opportunity to offer various smoking cessation programs, the user is left bewildered as far as efficacy is concerned, as most of these data are not available nor offered to the smokers. Clear regulations about the effectiveness of these interventions need to be devised to avoid disappointment and failed quitting attempts. Thus, there is a need for policy regulations to regulate the proliferation of these interventions and to foster their quality in the Netherlands.

The Virtual Care Climate Questionnaire: Development and Validation of a Questionnaire Measuring Perceived Support for Autonomy in a Virtual Care Setting

BACKGROUND

Web-based health behavior change interventions may be more effective if they offer autonomy-supportive communication facilitating the internalization of motivation for health behavior change. Yet, at this moment no validated tools exist to assess user-perceived autonomy-support of such interventions.

OBJECTIVE

The aim of this study was to develop and validate the virtual climate care questionnaire (VCCQ), a measure of perceived autonomy-support in a virtual care setting.

METHODS

Items were developed based on existing questionnaires and expert consultation and were pretested among experts and target populations. The virtual climate care questionnaire was administered in relation to Web-based interventions aimed at reducing consumption of alcohol (Study 1; N=230) or cannabis (Study 2; N=228). Item properties, structural validity, and reliability were examined with item-response and classical test theory methods, and convergent and divergent validity via correlations with relevant concepts.

RESULTS

In Study 1, 20 of 23 items formed a one-dimensional scale (alpha=.97; omega=.97; H=.66; mean 4.9 [SD 1.0]; range 1-7) that met the assumptions of monotonicity and invariant item ordering. In Study 2, 16 items fitted these criteria (alpha=.92; H=.45; omega=.93; mean 4.2 [SD 1.1]; range 1-7). Only 15 items remained in the questionnaire in both studies, thus we proceeded to the analyses of the questionnaire's reliability and construct validity with a 15-item version of the virtual climate care questionnaire. Convergent validity of the resulting 15-item virtual climate care questionnaire was confirmed by positive associations with autonomous motivation (Study 1: r=.66, P<.001; Study 2: r=.37, P<.001) and perceived competence for reducing alcohol intake (Study 1: r=.52, P<.001). Divergent validity could only be confirmed by the nonsignificant association with perceived competence for learning (Study 2: r=.05, P=.48).

CONCLUSIONS

The virtual climate care questionnaire accurately assessed participants' perceived autonomy-support offered by two Web-based health behavior change interventions. Overall, the scale showed the expected properties and relationships with relevant concepts, and the studies presented suggest this first version of the virtual climate care questionnaire to be reasonably valid and reliable. As a result, the current version may cautiously be used in future research and practice to measure perceived support for autonomy within a virtual care climate. Future research efforts are required that focus on further investigating the virtual climate care questionnaire's divergent validity, on determining the virtual climate care questionnaire's validity and reliability when used in the context of Web-based interventions aimed at improving nonaddictive or other health behaviors, and on developing and validating a short form virtual climate care questionnaire.

Interactive web-based pulmonary rehabilitation programme: a randomised controlled feasibility trial

OBJECTIVES

The aim of this study was to determine if an interactive web-based pulmonary rehabilitation (PR) programme is a feasible alternative to conventional PR.

DESIGN

Randomised controlled feasibility trial.

SETTING

Participants with a diagnosis of chronic obstructive pulmonary disease were recruited from PR assessments, primary care and community rehabilitation programmes. Patients randomised to conventional rehabilitation started the programme according to the standard care at their referred site on the next available date.

PARTICIPANTS

103 patients were recruited to the study and randomised: 52 to conventional rehabilitation (mean (±SD) age 66 (±8) years, Medical Research Council (MRC) 3 (IQR2-4)); 51 to the web arm (mean (±SD) age 66 (±10) years, MRC 3 (IQR2-4)). Participants had to be willing to participate in either arm of the trial, have internet access and be web literate.

INTERVENTIONS

Patients randomised to the web-based programme worked through the website, exercising and recording their progress as well as reading educational material. Conventional PR consisted of twice weekly, 2 hourly sessions (an hour for exercise training and an hour for education).

OUTCOME MEASURES

Recruitment rates, eligibility, patient preference and dropout and completion rates for both programmes were collected. Standard outcomes for a PR assessment including measures of exercise capacity and quality of life questionnaires were also evaluated.

RESULTS

A statistically significant improvement (p≤0.01) was observed within each group in the endurance shuttle walk test (WEB: mean change 189±211.1; PR classes: mean change 184.5±247.4 s) and Chronic Respiratory disease Questionnaire-Dyspnoea (CRQ-D; WEB: mean change 0.7±1.2; PR classes: mean change 0.8±1.0). However, there were no significant differences between the groups in any outcome. Dropout rates were higher in the web-based programme (57% vs 23%).

CONCLUSIONS

An interactive web-based PR programme is feasible and acceptable when compared with conventional PR. Future trials maybe around choice-based PR programmes for select patients enabling stratification of patient care.

TRIAL REGISTRATION NUMBER

ISRCTN03142263; Results.

Improving Adherence to Smoking Cessation Treatment: Intervention Effects in a Web-Based Randomized Trial

BACKGROUND

Web-based smoking cessation interventions can deliver evidence-based treatments to a wide swath of the population, but effectiveness is often limited by insufficient adherence to proven treatment components. This study evaluated the impact of a social network (SN) intervention and free nicotine replacement therapy (NRT) on adherence to evidence-based components of smoking cessation treatment in the context of a Web-based intervention.

METHODS

A sample of adult U.S. smokers (N = 5290) was recruited via BecomeAnEX.org, a free smoking cessation Web site. Smokers were randomized to one of four arms: (1) an interactive, evidence-based smoking cessation Web site (WEB) alone; (2) WEB in conjunction with an SN intervention designed to integrate participants into the online community (WEB+SN); (3) WEB plus free NRT (WEB+NRT); and (4) the combination of all treatments (WEB+SN+NRT). Adherence outcomes assessed at 3-month follow-up were as follows: Web site utilization metrics, use of skills training components, intratreatment social support, and pharmacotherapy use.

RESULTS

WEB+SN+NRT outperformed all others on Web site utilization metrics, use of practical counseling tools, intratreatment social support, and NRT use. It was the only intervention to promote the sending of private messages and the viewing of community pages over WEB alone. Both social network arms outperformed WEB on most metrics of online community engagement. Both NRT arms showed higher medication use compared to WEB alone.

CONCLUSIONS

This study demonstrated the effectiveness of two approaches for improving adherence to evidence-based components of smoking cessation treatment. Integrated approaches to medication provision and social network engagement can enhance adherence to components known to improve cessation.

IMPLICATIONS

This study demonstrated that an integrated approach to medication provision and social network integration, when delivered through an online program, can enhance adherence across all three recommended components of an evidence-based smoking cessation program (skills training, social support, and pharmacotherapy use). Nicotine replacement therapy-when provided as part of an integrated program-increases adherence to other program elements, which in turn augment its own therapeutic effects. An explicit focus on approaches to improve treatment adherence is an important first step to identifying leverage points for optimizing intervention effectiveness.

Cost-utility of an internet-based intervention with or without therapist support in comparison with a waiting list for individuals with eating disorder symptoms: a randomized controlled trial

OBJECTIVE

To investigate the cost-utility of the internet-based intervention "Featback" provided with different levels of therapist support, in comparison to a waiting list.

METHOD

This economic evaluation was conducted from a societal perspective and was part of a randomized controlled trial in which participants (N = 354) with self-reported ED symptoms were randomized to: (1) 8 weeks of Featback, consisting of psychoeducation and a fully automated monitoring- and feedback system, (2) Featback with low-intensity (weekly) therapist support, (3) Featback with high-intensity (three times a week) therapist support, and (4) a waiting list. Participants were assessed at baseline, postintervention, and 3-month follow-up. Cost-utility acceptability curves were constructed.

RESULTS

No significant differences between the study conditions were found regarding quality-adjusted life-years (P = 0.55) and societal costs (P = 0.45), although the mean costs per participant were lowest in the Featback condition with low-intensity therapist support (€1951), followed by Featback with high-intensity therapist support (€2032), Featback without therapist support (€2102), and the waiting list (€2582). Featback seemed to be cost-effective as compared to the waiting list. No clear preference was found for Featback with or without therapist support.

DISCUSSION

A fully automated Internet-based intervention for ED symptoms with no, low-, or high-intensity therapist support represented good value for money when compared to a waiting list. This finding may have important implications for clinical practice, as both the unguided- and guided intervention could allow for more efficient care and widespread dissemination, potentially increasing the accessibility and availability of mental health care services for individuals with ED symptoms. © 2016 Wiley Periodicals, Inc. (Int J Eat Disord 2016; 49:1068-1076).

mHealth or eHealth? Efficacy, Use, and Appreciation of a Web-Based Computer-Tailored Physical Activity Intervention for Dutch Adults: A Randomized Controlled Trial

Background

Until a few years ago, Web-based computer-tailored interventions were almost exclusively delivered via computer (eHealth). However, nowadays, interventions delivered via mobile phones (mHealth) are an interesting alternative for health promotion, as they may more easily reach people 24/7.

Objective

The first aim of this study was to compare the efficacy of an mHealth and an eHealth version of a Web-based computer-tailored physical activity intervention with a control group. The second aim was to assess potential differences in use and appreciation between the 2 versions.

Methods

We collected data among 373 Dutch adults at 5 points in time (baseline, after 1 week, after 2 weeks, after 3 weeks, and after 6 months). We recruited participants from a Dutch online research panel and randomly assigned them to 1 of 3 conditions: eHealth (n=138), mHealth (n=108), or control condition (n=127). All participants were asked to complete questionnaires at the 5 points in time. Participants in the eHealth and mHealth group received fully automated tailored feedback messages about their current level of physical activity. Furthermore, they received personal feedback aimed at increasing their amount of physical activity when needed. We used analysis of variance and linear regression analyses to examine differences between the 2 study groups and the control group with regard to efficacy, use, and appreciation.

Results

Participants receiving feedback messages (eHealth and mHealth together) were significantly more physically active after 6 months than participants in the control group (B=8.48, df=2, P=.03, Cohen d=0.27). We found a small effect size favoring the eHealth condition over the control group (B=6.13, df=2, P=.09, Cohen d=0.21). The eHealth condition had lower dropout rates (117/138, 84.8%) than the mHealth condition (81/108, 75.0%) and the control group (91/127, 71.7%). Furthermore, in terms of usability and appreciation, the eHealth condition outperformed the mHealth condition with regard to participants receiving (t₁₈₂=3.07, P=.002) and reading the feedback messages (t₁₈₁=2.34, P=.02), as well as the clarity of the messages (t₁₈₁=1.99, P=.049).

Conclusions

We tested 2 Web-based computer-tailored physical activity intervention versions (mHealth and eHealth) against a control condition with regard to efficacy, use, usability, and appreciation. The overall effect was mainly caused by the more effective eHealth intervention. The mHealth app was rated inferior to the eHealth version with regard to usability and appreciation. More research is needed to assess how both methods can complement each other.

Trial Registration

Netherlands Trial Register: NTR4503; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4503 (Archived by WebCite at http://www.webcitation.org/6lEi1x40s)

Results of the PAS Study: A Randomized Controlled Trial Evaluating the Effectiveness of a Web-Based Multiple Tailored Smoking Cessation Program Combined With Tailored Counseling by Practice Nurses

This study investigated the effects of Web-based multiple computer tailoring and counseling by a practice nurse (MTC) compared with computer tailoring without counseling (MT) and usual care (UC) on smoking cessation rates, via a randomized controlled trial with 414 Dutch adult smokers, recruited by 91 practice nurses from May 2009 to June 2010. Logistic multilevel regression analyses were conducted with 24-hour point prevalence, 7-day point prevalence, and prolonged abstinence after 6 and 12 months as dependent variables and experimental condition as the independent variable. After 6 and 12 months, 38% and 56% of respondents were followed up, respectively. At both follow-ups, no main effects of the interventions could be identified when comparing them with care as usual and with each other-neither in analyses using available data nor in analyses using a negative scenario in which respondents lost to follow-up were considered to still be smoking. A Web-based multiple computer-tailored smoking cessation program combined with a single face-to-face counseling session by a practice nurse may not be more effective than this computer-tailored program alone or than usual smoking cessation care in the general practice setting. Yet before concluding that the addition of counseling to Web-based computer tailoring cannot be successful, more research needs to be conducted to identify the optimal number of counseling sessions to be combined with the Web-based program and to how to best attune the two modalities.

Extended Self-Help for Smoking Cessation: A Randomized Controlled Trial

INTRODUCTION

Far too few smokers receive recommended interventions at their healthcare visits, highlighting the importance of identifying effective, low-cost smoking interventions that can be readily delivered. Self-help interventions (e.g., written materials) would meet this need, but they have shown low efficacy. The purpose of this RCT was to determine the efficacy of a self-help intervention with increased duration and intensity.

DESIGN

Randomized parallel trial design involving enrollment between April 2010 and August 2011 with follow-up data for 24 months.

SETTING/PARTICIPANTS

U.S. national sample of daily smokers (N=1,874).

INTERVENTION

Participants were randomized to one of three arms of a parallel trial design: Traditional Self-Help (TSH, n=638), Standard Repeated Mailings (SRM, n=614), or Intensive Repeated Mailings (IRM, n=622). TSH received an existing self-help booklet for quitting smoking. SRM received eight different cessation booklets mailed over a 12-month period. IRM received monthly mailings of ten booklets and additional material designed to enhance social support over 18 months.

MAIN OUTCOME MEASURES

The primary outcome was 7-day point-prevalence abstinence collected at 6, 12, 18, and 24 months.

RESULTS

Data were analyzed between 2013 and 2015. A dose-response effect was found across all four follow-up points. For example, by 24 months, IRM produced the highest abstinence rate (30.0%), followed by SRM (24.4%) and TSH (18.9%). The difference in 24-month abstinence rates between IRM and TSH was 11.0% (95% CI=5.7%, 16.3%). Cost analyses indicated that, compared with TSH, the incremental cost per quitter who received SRM and IRM was $560 and $361, respectively.

CONCLUSIONS

Self-help interventions with increased intensity and duration resulted in significantly improved abstinence rates that extended 6 months beyond the end of the intervention. Despite the greater intensity, the interventions were highly cost effective, suggesting that widespread dissemination in healthcare settings could greatly enhance quitting.

TRIAL REGISTRATION

This study is registered at www.clinicaltrials.gov NCT01352195.

Implementation of a Substance Use Recovery Support Mobile Phone App in Community Settings: Qualitative Study of Clinician and Staff Perspectives of Facilitators and Barriers

BACKGROUND

Research supports the effectiveness of technology-based treatment approaches for substance use disorders. These approaches have the potential to broaden the reach of evidence-based care. Yet, there is limited understanding of factors associated with implementation of technology-based care approaches in different service settings.

OBJECTIVES

In this study, we explored provider and staff perceptions of facilitators and barriers to implementation of a mobile phone substance use recovery support app with clients in 4 service settings.

METHODS

Interviews were conducted with leadership and provider stakeholders (N=12) from 4 agencies in the first year of an implementation trial of the mobile phone app. We used the Consolidated Framework for Implementation Research as the conceptual foundation for identifying facilitators and barriers to implementation.

RESULTS

Implementation process facilitators included careful planning of all aspects of implementation before launch, engaging a dedicated team to implement and foster motivation, working collaboratively with the app development team to address technical barriers and adapt the app to meet client and agency needs, and consistently reviewing app usage data to inform progress. Implementation support strategies included training all staff to promote organization awareness about the recovery support app and emphasize its priority as a clinical care tool, encouraging clients to try the technology before committing to use, scaling rollout to clients, setting clear expectations with clients about use of the app, and using peer coaches and consistent client-centered messaging to promote engagement. Perceived compatibility of the mobile phone app with agency and client needs and readiness to implement emerged as salient agency-level implementation facilitators. Facilitating characteristics of the recovery support app itself included evidence of its impact for recovery support, perceived relative advantage of the app over usual care, the ability to adapt the app to improve client use, and its ease of use. The mobile phone itself was a strong motivation for clients to opt in to use the app in settings that provided phones. App access was limited in settings that did not provide phones owing to lack of mobile phone ownership or incompatibility of the app with clients' mobile phones. Individual differences in technology literacy and provider beliefs about substance use care either facilitated or challenged implementation. Awareness of patient needs and resources facilitated implementation, whereas external policies and regulations regarding technology use introduced barriers to implementation.

CONCLUSIONS

The conceptually grounded facilitators and barriers identified in this study can guide systematic targeting of strategies to improve implementation of mobile phone interventions in community treatment settings. Results also inform the design of technology-based therapeutic tools. This study highlights directions for research with regard to implementation of technology-based behavioral health care approaches.

A Web-Based Computer-Tailored Alcohol Prevention Program for Adolescents: Cost-Effectiveness and Intersectoral Costs and Benefits

Background

Preventing excessive alcohol use among adolescents is important not only to foster individual and public health, but also to reduce alcohol-related costs inside and outside the health care sector. Computer tailoring can be both effective and cost-effective for working with many lifestyle behaviors, yet the available information on the cost-effectiveness of computer tailoring for reducing alcohol use by adolescents is limited as is information on the costs and benefits pertaining to sectors outside the health care sector, also known as intersectoral costs and benefits (ICBs).

Objective

The aim was to assess the cost-effectiveness of a Web-based computer-tailored intervention for reducing alcohol use and binge drinking by adolescents from a health care perspective (excluding ICBs) and from a societal perspective (including ICBs).

Methods

Data used were from the Alcoholic Alert study, a cluster randomized controlled trial with randomization at the level of schools into two conditions. Participants either played a game with tailored feedback on alcohol awareness after the baseline assessment (intervention condition) or received care as usual (CAU), meaning that they had the opportunity to play the game subsequent to the final measurement (waiting list control condition). Data were recorded at baseline (T0=January/February 2014) and after 4 months (T1=May/June 2014) and were used to calculate incremental cost-effectiveness ratios (ICERs), both from a health care perspective and a societal perspective. Stochastic uncertainty in the data was dealt with by using nonparametric bootstraps (5000 simulated replications). Additional sensitivity analyses were conducted based on excluding cost outliers. Subgroup cost-effectiveness analyses were conducted based on several background variables, including gender, age, educational level, religion, and ethnicity.

Results

From both the health care perspective and the societal perspective for both outcome measures, the intervention was more costly and more effective in comparison with CAU. ICERs differed for both perspectives, namely €40 and €79 from the health care perspective to €62 and €144 for the societal perspective per incremental reduction of one glass of alcohol per week and one binge drinking occasion per 30 days, respectively. Subgroup analyses showed, from both perspectives and for both outcome measures, that the intervention was cost-effective for older adolescents (aged 17-19 years) and those at a lower educational level and, from a health care perspective, the male and nonreligious adolescent subgroups.

Conclusions

Computer-tailored feedback could be a cost-effective way to target alcohol use and binge drinking among adolescents. Including ICBs in the economic evaluation had an impact on the cost-effectiveness results of the analysis. It could be worthwhile to aim the intervention specifically at specific subgroups.

Trial Registration

Nederlands Trial Register: NTR4048; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4048 (Archived by Webcite at http://www.webcitation.org/6c7omN8wG)

Economic evaluation of a telephone- and face-to-face-delivered counseling intervention for smoking cessation in patients with coronary heart disease

OBJECTIVE

This study examined the cost-effectiveness and cost-utility of two smoking cessation counseling interventions differing in their modality for patients diagnosed with coronary heart disease from a societal perspective.

METHODS

In a randomized controlled trial conducted in Dutch hospital wards, cardiac patients who smoked prior to admission were allocated to usual care (n = 245), telephone counseling (n = 223) or face-to-face counseling (n = 157). The counseling interventions lasted for 3 months and were complemented by nicotine patches. Baseline histories were obtained, and interviews took place 6 months after hospitalization to assess self-reported smoking status and quality adjusted life years (QALYs). Incremental cost-effectiveness ratios per quitter and cost-utility ratios per QALY were calculated and presented in acceptability curves. Uncertainty was accounted for by sensitivity analysis.

RESULTS

Using continued abstinence as the outcome measure showed that telephone counseling had the highest probability of being cost-effective. Face-to-to-face counseling was also more cost-effective than usual care. No significant improvements and differences in QALYs between the three conditions were found. Varying costs and effect estimations revealed that the results of the primary analyses were robust.

CONCLUSIONS

Assuming a willingness-to-pay of €20,000 per abstinent patient, telephone counseling would be a highly cost-effective smoking cessation intervention assisting cardiac patients to quit. However, the lack of consensus concerning the willingness-to-pay per quitter impedes drawing firm conclusions. Moreover, studies with extended follow-up periods are needed to capture late relapses and possible differences in QALYs.

Dealing With Missing Behavioral Endpoints in Health Promotion Research by Modeling Cognitive Parameters in Cost-Effectiveness Analyses of Behavioral Interventions: A Validation Study

Cost-effectiveness analyses (CEAs) of behavioral interventions typically use physical outcome criteria. However, any progress in cognitive antecedents of behavior change may be seen as a beneficial outcome of an intervention. The aim of this study is to explore the feasibility and validity of incorporating cognitive parameters of behavior change in CEAs. The CEA from a randomized controlled trial on smoking cessation was reanalyzed. First, relevant cognitive antecedents of behavior change in this dataset were identified. Then, transition probabilities between combined states of smoking and cognitions at 6 weeks and corresponding 6 months smoking status were obtained from the dataset. These rates were extrapolated to the period from 6 to 12 months in a decision analytic model. Simulated results were compared with the 12 months' observed cost-effectiveness results. Self-efficacy was the strongest time-varying predictor of smoking cessation. Twelve months' observed CEA results for the multiple tailoring intervention versus usual care showed € 3188 had to be paid for each additional quitter versus € 10,600 in the simulated model. The simulated CEA showed largely similar but somewhat more conservative results. Using self-efficacy to enhance the estimation of the true behavioral outcome seems a feasible and valid way to estimate future cost-effectiveness.

Effectiveness of video- versus text-based computer-tailored smoking cessation interventions among smokers after one year

BACKGROUND

In western countries, smoking prevalence rates are high among smokers unmotivated to quit and those with a lower socioeconomic status (LSES). Multiple computer tailoring and the use of audio-visual aids may improve such interventions and increase cessation in LSES smokers. This study assessed the 12-month effectiveness of a video- and text-based computer-tailored intervention.

METHODS

A randomized controlled trial in the Netherlands was used in which smokers were allocated to the video-based condition (VC) (N=670), the text-based condition (TC) (N=708) or the control condition (CC) (brief generic text advice) (N=721). After 12months, self-reported prolonged abstinence was assessed and biochemically verified in respondents indicating to have quit smoking. Three analysis strategies were used to assess the effects: (1) multiple imputation (MI); (2) intention-to-treat (ITT); (3) complete case analysis (CC).

RESULTS

VC was more effective in prolonged abstinence compared to CC (odds ratio (OR)=1.90, p=.005) and the text-based condition (OR=1.71, p=.01). VC was furthermore more effective than TC. No differences were found for SES and motivational levels. Results were similar when using ITT and CC. For our secondary outcome seven-day point prevalence abstinence; however, neither VC (OR=1.17, p=.34) or TC (OR=0.91, p=.52) outperformed the CC.

CONCLUSION

The video-based computer-tailored intervention was effective in obtaining substantial long-term abstinence compared to the text-based version and a brief generic text advice.

Understanding the stakeholders' intention to use economic decision-support tools: A cross-sectional study with the tobacco return on investment tool

BACKGROUND

Despite an increased number of economic evaluations of tobacco control interventions, the uptake by stakeholders continues to be limited. Understanding the underlying mechanism in adopting such economic decision-support tools by stakeholders is therefore important. By applying the I-Change Model, this study aims to identify which factors determine potential uptake of an economic decision-support tool, i.e., the Return on Investment tool.

METHODS

Stakeholders (decision-makers, purchasers of services/pharma products, professionals/service providers, evidence generators and advocates of health promotion) were interviewed in five countries, using an I-Change based questionnaire. MANOVA's were conducted to assess differences between intenders and non-intenders regarding beliefs. A multiple regression analysis was conducted to identify the main explanatory variables of intention to use an economic decision-support tool.

FINDINGS

Ninety-three stakeholders participated. Significant differences in beliefs were found between non-intenders and intenders: risk perception, attitude, social support, and self-efficacy towards using the tool. Regression showed that demographics, pre-motivational, and motivational factors explained 69% of the variation in intention.

DISCUSSION

This study is the first to provide a theoretical framework to understand differences in beliefs between stakeholders who do or do not intend to use economic decision-support tools, and empirically corroborating the framework. This contributes to our understanding of the facilitators and barriers to the uptake of these studies.

Economic evaluations of Internet interventions for mental health: a systematic review

BACKGROUND

Internet interventions are assumed to be cost-effective. However, it is unclear how strong this evidence is, and what the quality of this evidence is.

METHOD

A comprehensive literature search (1990-2014) in Medline, EMBASE, the Cochrane Central Register of Controlled Trials, NHS Economic Evaluations Database, NHS Health Technology Assessment Database, Office of Health Economics Evaluations Database, Compendex and Inspec was conducted. We included economic evaluations alongside randomized controlled trials of Internet interventions for a range of mental health symptoms compared to a control group, consisting of a psychological or pharmaceutical intervention, treatment-as-usual (TAU), wait-list or an attention control group.

RESULTS

Of the 6587 abstracts identified, 16 papers met the inclusion criteria. Nine studies featured a societal perspective. Results demonstrated that guided Internet interventions for depression, anxiety, smoking cessation and alcohol consumption had favourable probabilities of being more cost-effective when compared to wait-list, TAU, group cognitive behaviour therapy (CBGT), attention control, telephone counselling or unguided Internet CBT. Unguided Internet interventions for suicide prevention, depression and smoking cessation demonstrated cost-effectiveness compared to TAU or attention control. In general, results from cost-utility analyses using more generic health outcomes (quality of life) were less favourable for unguided Internet interventions. Most studies adhered reasonably to economic guidelines.

CONCLUSIONS

Results of guided Internet interventions being cost-effective are promising with most studies adhering to publication standards, but more economic evaluations are needed in order to determine cost-effectiveness of Internet interventions compared to the most cost-effective treatment currently available.

Cost-effectiveness of a voucher-based intervention for smoking cessation

BACKGROUND

Contingency management (CM) has been shown to be effective in reducing smoking consumption, but has traditionally been criticized for its costs.

OBJECTIVES

This study assessed the cost-effectiveness of using a voucher-based CM protocol added to a cognitive behavioral treatment (CBT) for smoking cessation among treatment-seeking patients from the general population.

METHODS

A total of 92 patients were randomly assigned to CBT or CBT plus CM for abstinence. Incremental cost-effectiveness ratios (ICERs) were calculated by dividing the increase in costs by the increase in effects (continuous abstinence, longest duration of abstinence at 6-month follow-up and cotinine results during the treatment). An acceptability curve illustrated the statistical uncertainty surrounding the cost-effectiveness estimate. We also determined the optimum cost per participant for predicting the smoking status at 6-month follow-up.

RESULTS

The average cost per participant in the CBT condition was €138.73 (US$ 150.23) as opposed to €411.61 (US$ 445.73) in the CBT plus CM condition (p < 0.01). The incremental cost of using voucher-based CM to increase the number of participants that maintained abstinence at 6-month follow-up by one extra participant was €68.22 (US$ 73.88), and to lengthen the longest duration of abstinence by 1 week was €53.92 (US$ 58.39). The incremental cost to obtain an extra cotinine-negative result was €181.90 (US$ 196.98).

CONCLUSION

Compared with CBT alone, the voucher-based protocol required additional costs but achieved significantly better outcomes. These results will allow stakeholders to make policy decisions about CM implementation for smoking cessation in the broader community.

Comparing a Video and Text Version of a Web-Based Computer-Tailored Intervention for Obesity Prevention: A Randomized Controlled Trial

Background

Web-based computer-tailored interventions often suffer from small effect sizes and high drop-out rates, particularly among people with a low level of education. Using videos as a delivery format can possibly improve the effects and attractiveness of these interventions

Objective

The main aim of this study was to examine the effects of a video and text version of a Web-based computer-tailored obesity prevention intervention on dietary intake, physical activity, and body mass index (BMI) among Dutch adults. A second study aim was to examine differences in appreciation between the video and text version. The final study aim was to examine possible differences in intervention effects and appreciation per educational level.

Methods

A three-armed randomized controlled trial was conducted with a baseline and 6 months follow-up measurement. The intervention consisted of six sessions, lasting about 15 minutes each. In the video version, the core tailored information was provided by means of videos. In the text version, the same tailored information was provided in text format. Outcome variables were self-reported and included BMI, physical activity, energy intake, and appreciation of the intervention. Multiple imputation was used to replace missing values. The effect analyses were carried out with multiple linear regression analyses and adjusted for confounders. The process evaluation data were analyzed with independent samples t tests.

Results

The baseline questionnaire was completed by 1419 participants and the 6 months follow-up measurement by 1015 participants (71.53%). No significant interaction effects of educational level were found on any of the outcome variables. Compared to the control condition, the video version resulted in lower BMI (B=-0.25, P=.049) and lower average daily energy intake from energy-dense food products (B=-175.58, P<.001), while the text version had an effect only on energy intake (B=-163.05, P=.001). No effects on physical activity were found. Moreover, the video version was rated significantly better than the text version on feelings of relatedness (P=.041), usefulness (P=.047), and grade given to the intervention (P=.018).

Conclusions

The video version of the Web-based computer-tailored obesity prevention intervention was the most effective intervention and most appreciated. Future research needs to examine if the effects are maintained in the long term and how the intervention can be optimized.

ClinicalTrial

Netherlands Trial Register: NTR3501; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3501 (Archived by WebCite at http://www.webcitation.org/6cBKIMaW1)

Impact of Educational Level on Study Attrition and Evaluation of Web-Based Computer-Tailored Interventions: Results From Seven Randomized Controlled Trials

Background

Web-based computer-tailored interventions have shown to be effective in improving health behavior; however, high dropout attrition is a major issue in these interventions.

Objective

The aim of this study is to assess whether people with a lower educational level drop out from studies more frequently compared to people with a higher educational level and to what extent this depends on evaluation of these interventions.

Methods

Data from 7 randomized controlled trials of Web-based computer-tailored interventions were used to investigate dropout rates among participants with different educational levels. To be able to compare higher and lower educated participants, intervention evaluation was assessed by pooling data from these studies. Logistic regression analysis was used to assess whether intervention evaluation predicted dropout at follow-up measurements.

Results

In 3 studies, we found a higher study dropout attrition rate among participants with a lower educational level, whereas in 2 studies we found that middle educated participants had a higher dropout attrition rate compared to highly educated participants. In 4 studies, no such significant difference was found. Three of 7 studies showed that participants with a lower or middle educational level evaluated the interventions significantly better than highly educated participants (“Alcohol-Everything within the Limit”: F_2,376=5.97, P=.003; “My Healthy Behavior”: F_2,359=5.52, P=.004; “Master Your Breath”: F_2,317=3.17, P=.04). One study found lower intervention evaluation by lower educated participants compared to participants with a middle educational level (“Weight in Balance”: F_2,37=3.17, P=.05). Low evaluation of the interventions was not a significant predictor of dropout at a later follow-up measurement in any of the studies.

Conclusions

Dropout attrition rates were higher among participants with a lower or middle educational level compared with highly educated participants. Although lower educated participants evaluated the interventions better in approximately half of the studies, evaluation did not predict dropout attrition. Further research is needed to find other explanations for high dropout rates among lower educated participants.

Effectiveness of multicomponent interventions in primary healthcare settings to promote continuous smoking cessation in adults: a systematic review

OBJECTIVE

The objective of the present review is to evaluate multicomponent/complex primary care (PC) interventions for their effectiveness in continuous smoking abstinence by adult smokers.

DESIGN

A systematic review of randomised and non-randomised controlled trials was undertaken.

ELIGIBILITY CRITERIA FOR INCLUDED STUDIES

Selected studies met the following criteria: evaluated effects of a multicomponent/complex intervention (with 2 or more intervention components) in achieving at least 6-month abstinence in adult smokers who visited a PC, biochemical confirmation of abstinence, intention-to-treat analysis and results published in English/Spanish.

METHODS

We followed PRISMA statement to report the review. We searched the following data sources: MEDLINE, Web of Science, Scopus (from inception to February 2014), 3 key journals and a tobacco research bulletin. The Scottish Intercollegiate Guidelines Network checklists were used to evaluate methodological quality. Data selection, evaluation and extraction were done independently, using a paired review approach. Owing to the heterogeneity of interventions in the studies included, a meta-analysis was not conducted.

RESULTS

Of 1147 references identified, 9 studies were selected (10,204 participants, up to 48 months of follow-up, acceptable methodological quality). Methodologies used were mainly individual or group sessions, telephone conversations, brochures or quit-smoking kits, medications and economic incentives for doctors and no-cost medications for smokers. Complex interventions achieved long-term continuous abstinence ranging from 7% to 40%. Behavioural interventions were effective and had a dose-response effect. Both nicotine replacement and bupropion therapy were safe and effective, with no observed differences.

CONCLUSIONS

Multicomponent/complex interventions in PC are effective and safe, appearing to achieve greater long-term continuous smoking cessation than usual care and counselling alone. Selected studies were heterogeneous and some had significant losses to follow-up. Our results show that smoking interventions should include more than one component and a strong follow-up of the patient to maximise results.

Use and Effectiveness of a Video- and Text-Driven Web-Based Computer-Tailored Intervention: Randomized Controlled Trial

Background

Many Web-based computer-tailored interventions are characterized by high dropout rates, which limit their potential impact.

Objective

This study had 4 aims: (1) examining if the use of a Web-based computer-tailored obesity prevention intervention can be increased by using videos as the delivery format, (2) examining if the delivery of intervention content via participants’ preferred delivery format can increase intervention use, (3) examining if intervention effects are moderated by intervention use and matching or mismatching intervention delivery format preference, (4) and identifying which sociodemographic factors and intervention appreciation variables predict intervention use.

Methods

Data were used from a randomized controlled study into the efficacy of a video and text version of a Web-based computer-tailored obesity prevention intervention consisting of a baseline measurement and a 6-month follow-up measurement. The intervention consisted of 6 weekly sessions and could be used for 3 months. ANCOVAs were conducted to assess differences in use between the video and text version and between participants allocated to a matching and mismatching intervention delivery format. Potential moderation by intervention use and matching/mismatching delivery format on self-reported body mass index (BMI), physical activity, and energy intake was examined using regression analyses with interaction terms. Finally, regression analysis was performed to assess determinants of intervention use.

Results

In total, 1419 participants completed the baseline questionnaire (follow-up response=71.53%, 1015/1419). Intervention use declined rapidly over time; the first 2 intervention sessions were completed by approximately half of the participants and only 10.9% (104/956) of the study population completed all 6 sessions of the intervention. There were no significant differences in use between the video and text version. Intervention use was significantly higher among participants who were allocated to an intervention condition that matched their preferred intervention delivery format. There were no significant interaction terms for any of the outcome variables; a match and more intervention use did not result in better intervention effects. Participants with a high BMI and participants who felt involved and supported by the intervention were more likely to use the intervention more often.

Conclusions

Video delivery of tailored feedback does not increase the use of Web-based computer-tailored interventions. However, intervention use can potentially be increased by delivering intervention content via participants’ preferred intervention delivery format and creating feelings of relatedness. Because more intervention use was not associated with better intervention outcomes, more research is needed to examine the optimum number of intervention sessions in terms of maximizing use and effects.

Trial Registration

Nederlands Trial Register: NTR3501; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3501 (Archived by WebCite at http://www.webcitation.org/6b2tsH8Pk)

The Economic Impact of Smoking and of Reducing Smoking Prevalence: Review of Evidence

BACKGROUND

Tobacco smoking is the cause of many preventable diseases and premature deaths in the UK and around the world. It poses enormous health- and non-health-related costs to the affected individuals, employers, and the society at large. The World Health Organization (WHO) estimates that, globally, smoking causes over US$500 billion in economic damage each year.

OBJECTIVES

This paper examines global and UK evidence on the economic impact of smoking prevalence and evaluates the effectiveness and cost effectiveness of smoking cessation measures.

STUDY SELECTION

SEARCH METHODS We used two major health care/economic research databases, namely PubMed and the National Institute for Health Research (NIHR) database that contains the British National Health Service (NHS) Economic Evaluation Database; Cochrane Library of systematic reviews in health care and health policy; and other health-care-related bibliographic sources. We also performed hand searching of relevant articles, health reports, and white papers issued by government bodies, international health organizations, and health intervention campaign agencies. SELECTION CRITERIA The paper includes cost-effectiveness studies from medical journals, health reports, and white papers published between 1992 and July 2014, but included only eight relevant studies before 1992. Most of the papers reviewed reported outcomes on smoking prevalence, as well as the direct and indirect costs of smoking and the costs and benefits of smoking cessation interventions. We excluded papers that merely described the effectiveness of an intervention without including economic or cost considerations. We also excluded papers that combine smoking cessation with the reduction in the risk of other diseases. DATA COLLECTION AND ANALYSIS The included studies were assessed against criteria indicated in the Cochrane Reviewers Handbook version 5.0.0. OUTCOMES ASSESSED IN THE REVIEWPrimary outcomes of the selected studies are smoking prevalence, direct and indirect costs of smoking, and the costs and benefits of smoking cessation interventions (eg, "cost per quitter", "cost per life year saved", "cost per quality-adjusted life year gained," "present value" or "net benefits" from smoking cessation, and "cost savings" from personal health care expenditure).

MAIN RESULTS

The main findings of this study are as follows: The costs of smoking can be classified into direct, indirect, and intangible costs. About 15% of the aggregate health care expenditure in high-income countries can be attributed to smoking. In the US, the proportion of health care expenditure attributable to smoking ranges between 6% and 18% across different states. In the UK, the direct costs of smoking to the NHS have been estimated at between £2.7 billion and £5.2 billion, which is equivalent to around 5% of the total NHS budget each year. The economic burden of smoking estimated in terms of GDP reveals that smoking accounts for approximately 0.7% of China's GDP and approximately 1% of US GDP. As part of the indirect (non-health-related) costs of smoking, the total productivity losses caused by smoking each year in the US have been estimated at US$151 billion.The costs of smoking notwithstanding, it produces some potential economic benefits. The economic activities generated from the production and consumption of tobacco provides economic stimulus. It also produces huge tax revenues for most governments, especially in high-income countries, as well as employment in the tobacco industry. Income from the tobacco industry accounts for up to 7.4% of centrally collected government revenue in China. Smoking also yields cost savings in pension payments from the premature death of smokers.Smoking cessation measures could range from pharmacological treatment interventions to policy-based measures, community-based interventions, telecoms, media, and technology (TMT)-based interventions, school-based interventions, and workplace interventions.The cost per life year saved from the use of pharmacological treatment interventions ranged between US$128 and US$1,450 and up to US$4,400 per quality-adjusted life years (QALYs) saved. The use of pharmacotherapies such as varenicline, NRT, and Bupropion, when combined with GP counseling or other behavioral treatment interventions (such as proactive telephone counseling and Web-based delivery), is both clinically effective and cost effective to primary health care providers.Price-based policy measures such as increase in tobacco taxes are unarguably the most effective means of reducing the consumption of tobacco. A 10% tax-induced cigarette price increase anywhere in the world reduces smoking prevalence by between 4% and 8%. Net public benefits from tobacco tax, however, remain positive only when tax rates are between 42.9% and 91.1%. The cost effectiveness ratio of implementing non-price-based smoking cessation legislations (such as smoking restrictions in work places, public places, bans on tobacco advertisement, and raising the legal age of smokers) range from US$2 to US$112 per life year gained (LYG) while reducing smoking prevalence by up to 30%-82% in the long term (over a 50-year period).Smoking cessation classes are known to be most effective among community-based measures, as they could lead to a quit rate of up to 35%, but they usually incur higher costs than other measures such as self-help quit-smoking kits. On average, community pharmacist-based smoking cessation programs yield cost savings to the health system of between US$500 and US$614 per LYG.Advertising media, telecommunications, and other technology-based interventions (such as TV, radio, print, telephone, the Internet, PC, and other electronic media) usually have positive synergistic effects in reducing smoking prevalence especially when combined to deliver smoking cessation messages and counseling support. However, the outcomes on the cost effectiveness of TMT-based measures have been inconsistent, and this made it difficult to attribute results to specific media. The differences in reported cost effectiveness may be partly attributed to varying methodological approaches including varying parametric inputs, differences in national contexts, differences in advertising campaigns tested on different media, and disparate levels of resourcing between campaigns. Due to its universal reach and low implementation costs, online campaign appears to be substantially more cost effective than other media, though it may not be as effective in reducing smoking prevalence.School-based smoking prevalence programs tend to reduce short-term smoking prevalence by between 30% and 70%. Total intervention costs could range from US$16,400 to US$580,000 depending on the scale and scope of intervention. The cost effectiveness of school-based programs show that one could expect a saving of approximately between US$2,000 and US$20,000 per QALY saved due to averted smoking after 2-4 years of follow-up.Workplace-based interventions could represent a sound economic investment to both employers and the society at large, achieving a benefit-cost ratio of up to 8.75 and generating 12-month employer cost savings of between $150 and $540 per nonsmoking employee. Implementing smoke-free workplaces would also produce myriads of new quitters and reduce the amount of cigarette consumption, leading to cost savings in direct medical costs to primary health care providers. Workplace interventions are, however, likely to yield far greater economic benefits over the long term, as reduced prevalence will lead to a healthier and more productive workforce.

CONCLUSIONS

We conclude that the direct costs and externalities to society of smoking far outweigh any benefits that might be accruable at least when considered from the perspective of socially desirable outcomes (ie, in terms of a healthy population and a productive workforce). There are enormous differences in the application and economic measurement of smoking cessation measures across various types of interventions, methodologies, countries, economic settings, and health care systems, and these may have affected the comparability of the results of the studies reviewed. However, on the balance of probabilities, most of the cessation measures reviewed have not only proved effective but also cost effective in delivering the much desired cost savings and net gains to individuals and primary health care providers.