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

BACKGROUND: Tobacco consumption is a leading cause of death and disease, killing >8 million people each year. Smoking cessation significantly reduces the risk of developing smoking-related diseases. Although combined treatment for addiction is promising, evidence of its effectiveness is still emerging. Currently, there is no published research comparing the effectiveness of blended smoking cessation treatments (BSCTs) with face-to-face (F2F) treatments, where web-based components replace 50% of the F2F components in blended treatment. OBJECTIVE: The primary objective of this 2-arm noninferiority randomized controlled trial was to determine whether a BSCT is noninferior to an F2F treatment with identical ingredients in achieving abstinence rates. METHODS: This study included 344 individuals who smoke (at least 1 cigarette per day) attending an outpatient smoking cessation clinic in the Netherlands. The participants received either a blended 50% F2F and 50% web-based BSCT or only F2F treatment with similar content and intensity. The primary outcome measure was cotinine-validated abstinence rates from all smoking products at 3 and 15 months after treatment initiation. Additional measures included carbon monoxide-validated point prevalence abstinence; self-reported point prevalence abstinence; and self-reported continuous abstinence rates at 3, 6, 9, and 15 months after treatment initiation. RESULTS: None of the 13 outcomes showed statistically confirmed noninferiority of the BSCT, whereas 4 outcomes showed significantly (P<.001) inferior abstinence rates of the BSCT: cotinine-validated point prevalence abstinence rate at 3 months (difference 12.7, 95% CI 6.2-19.4), self-reported point prevalence abstinence rate at 6 months (difference 19.3, 95% CI 11.5-27.0) and at 15 months (difference 11.7, 95% CI 5.8-17.9), and self-reported continuous abstinence rate at 6 months (difference 13.8, 95% CI 6.8-20.8). The remaining 9 outcomes, including the cotinine-validated point prevalence abstinence rate at 15 months, were inconclusive. CONCLUSIONS: In this high-intensity outpatient smoking cessation trial, the blended mode was predominantly less effective than the traditional F2F mode. The results contradict the widely assumed potential benefits of blended treatment and suggest that further research is needed to identify the critical factors in the design of blended interventions. TRIAL REGISTRATION: Netherlands Trial Register 27150; https://onderzoekmetmensen.nl/nl/trial/27150. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-doi.org/10.1186/s12889-016-3851-x.

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

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

A standardized validity assessment protocol for physiological signals from wearable technology: Methodological underpinnings and an application to the E4 biosensor.

Wearable physiological measurement devices for ambulatory research with novel sensing technology are introduced with ever increasing frequency, requiring fast, standardized, and rigorous validation of the physiological signals measured by these devices and their derived parameters. At present, there is a lack of consensus on a standardized protocol or framework with which to test the validity of this new technology, leading to the use of various (often unfit) methods. This study introduces a comprehensive validity assessment protocol for physiological signals (electrodermal activity and cardiovascular activity) and investigates the validity of the E4 wearable (an example of such a new device) on the three levels proposed by the protocol: (1) the signal level, with a cross-correlation; (2) the parameter level, with Bland-Altman plots; and (3) the event level, with the detection of physiological changes due to external stressor levels via event difference plots. The results of the protocol show that the E4 wearable is valid for heart rate, RMSSD, and SD at the parameter and event levels, and for the total amplitude of skin conductance responses at the event level when studying strong sustained stressors. These findings are in line with the prior literature and demonstrate the applicability of the protocol. The validity assessment protocol proposed in this study provides a comprehensive, standardized, and feasible method for assessment of the quality of physiological data coming from new wearable (sensor) technology aimed at ambulatory research.

Towards sustainable mental health promotion: trial-based health-economic evaluation of a positive psychology intervention versus usual care.

BACKGROUND: Mental well-being could be promoted and protected by positive psychology (PP) based interventions. Such interventions may be appealing for people at risk of anxiety and depressive disorders, but health-economic evaluations are scarce. The aim was to examine the cost-effectiveness of a PP intervention. METHODS: Participants with suboptimal levels of mental well-being were randomly assigned to an email guided PP-intervention (n = 137) or a wait-list control group (n = 138) with access to usual care (UC). At baseline and 6 months follow-up, data were collected on health care costs. Outcomes of interest were flourishing mental health and treatment response on anxiety and depressive symptoms. RESULTS: Bootstrapped mean incremental cost-effectiveness ratios were €2359 ($2899) for flourishing, €2959 ($3637) for anxiety and €2578 ($3168) for depression, suggesting appreciable health gains for low additional costs. At a willingness to pay ceiling of €10,000 ($12,290) for a treatment response, the probability that the intervention is deemed cost-effective ranged between 90 and 93%. CONCLUSIONS: The guided PP intervention appears to be a promising strategy as seen from both a public health and a health-economic perspective, especially when there is some willingness to pay. When the PP-intervention is scaled up, then outcome monitoring is recommended to better guarantee the longer term cost-effectiveness of the intervention. TRIAL REGISTRATION: The Netherlands National Trial Register NTR4297. Registered on 29 November 2013. The NTR is part of the WHO Primary Registries.

Identification of Users for a Smoking Cessation Mobile App: Quantitative Study.

BACKGROUND: The number of mobile apps that support smoking cessation is growing, indicating the potential of the mobile phone as a means to support cessation. Knowledge about the potential end users for cessation apps results in suggestions to target potential user groups in a dissemination strategy, leading to a possible increase in the satisfaction and adherence of cessation apps. OBJECTIVE: This study aimed to characterize potential end users for a specific mobile health (mHealth) smoking cessation app. METHODS: A quantitative study was conducted among 955 Dutch smokers and ex-smokers. The respondents were primarily recruited from addiction care facilities and hospitals through Web-based media via websites and forums. The respondents were surveyed on their demographics, smoking behavior, and personal innovativeness. The intention to use and the attitude toward a cessation app were determined on a 5-point Likert scale. To study the association between the characteristics and intention to use and attitude, univariate and multivariate ordinal logistic regression analyses were performed. RESULTS: The multivariate ordinal logistic regression showed that the number of previous quit attempts (odds ratio [OR] 4.1, 95% CI 2.4-7.0, and OR 3.5, 95% CI 2.0-5.9) and the score on the Fagerstrom Test of Nicotine Dependence (OR 0.8, 95% CI 0.8-0.9, and OR 0.8, 95% CI 0.8-0.9) positively correlates with the intention to use a cessation app and the attitude toward cessation apps, respectively. Personal innovativeness also positively correlates with the intention to use (OR 0.3, 95% CI 0.2-0.4) and the attitude towards (OR 0.2, 95% CI 0.1-0.4) a cessation app. No associations between demographics and the intention to use or the attitude toward using a cessation app were observed. CONCLUSIONS: This study is among the first to show that demographic characteristics such as age and level of education are not associated with the intention to use and the attitude toward using a cessation app when characteristics related specifically to the app, such as nicotine dependency and the number of quit attempts, are present in a multivariate regression model. This study shows that the use of mHealth apps depends on characteristics related to the content of the app rather than general user characteristics.

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

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

The impact of non-response bias due to sampling in public health studies: A comparison of voluntary versus mandatory recruitment in a Dutch national survey on adolescent health.

BACKGROUND: In public health monitoring of young people it is critical to understand the effects of selective non-response, in particular when a controversial topic is involved like substance abuse or sexual behaviour. Research that is dependent upon voluntary subject participation is particularly vulnerable to sampling bias. As respondents whose participation is hardest to elicit on a voluntary basis are also more likely to report risk behaviour, this potentially leads to underestimation of risk factor prevalence. Inviting adolescents to participate in a home-sent postal survey is a typical voluntary recruitment strategy with high non-response, as opposed to mandatory participation during school time. This study examines the extent to which prevalence estimates of adolescent health-related characteristics are biased due to different sampling methods, and whether this also biases within-subject analyses. METHODS: Cross-sectional datasets collected in 2011 in Twente and IJsselland, two similar and adjacent regions in the Netherlands, were used. In total, 9360 youngsters in a mandatory sample (Twente) and 1952 youngsters in a voluntary sample (IJsselland) participated in the study. To test whether the samples differed on health-related variables, we conducted both univariate and multivariable logistic regression analyses controlling for any demographic difference between the samples. Additional multivariable logistic regressions were conducted to examine moderating effects of sampling method on associations between health-related variables. RESULTS: As expected, females, older individuals, as well as individuals with higher education levels, were over-represented in the voluntary sample, compared to the mandatory sample. Respondents in the voluntary sample tended to smoke less, consume less alcohol (ever, lifetime, and past four weeks), have better mental health, have better subjective health status, have more positive school experiences and have less sexual intercourse than respondents in the mandatory sample. No moderating effects were found for sampling method on associations between variables. CONCLUSIONS: This is one of first studies to provide strong evidence that voluntary recruitment may lead to a strong non-response bias in health-related prevalence estimates in adolescents, as compared to mandatory recruitment. The resulting underestimation in prevalence of health behaviours and well-being measures appeared large, up to a four-fold lower proportion for self-reported alcohol consumption. Correlations between variables, though, appeared to be insensitive to sampling bias.

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.

Study protocol for a non-inferiority trial of a blended smoking cessation treatment versus face-to-face treatment (LiveSmokefree-Study).

BACKGROUND: Smoking cessation can significantly reduce the risk of developing smoking-related diseases. Several face-to-face and web-based treatments have shown to be effective. Blending of web-based and face-to-face treatment is expected to improve smoking cessation treatment. The primary objective of this study is to compare the prolonged abstinence rate of the blended smoking cessation treatment with the face-to-face treatment. Secondary objectives are to assess the benefits of blended treatment in terms of cost effectiveness and patient satisfaction, and to identify mechanisms underlying successful smoking cessation. METHODS/DESIGN: This study will be a single-center randomized controlled non-inferiority-trial with parallel group design. Patients (n = 344) will be randomly assigned to either the blended or the face-to-face group. Both treatments will consist of ten sessions with equal content held within 6 months. In the blended treatment five out of ten sessions will be delivered online. The treatments will cover the majority of behavior change techniques that are evidence-based within smoking cessation counseling. All face-to-face sessions in both treatments will take place at the outpatient smoking cessation clinic of a hospital. The primary outcome parameter will be biochemically validated prolonged abstinence at 15 months from the start of the smoking cessation treatment. DISCUSSION: This RCT will be the first study to examine the effectiveness of a blended smoking cessation treatment. It will also be the first study to explore patient satisfaction, adherence, cost-effectiveness, and the clinically relevant influencing factors of a blended smoking cessation treatment. The findings of this RCT are expected to substantially strengthen the base of evidence available to inform the development and delivery of smoking cessation treatment. TRIAL REGISTRATION: Nederlands Trialregister NTR5113 . Registered 24 March 2015.

The St George's Respiratory Questionnaire revisited: a psychometric evaluation.

PURPOSE: The St George's Respiratory Questionnaire (SGRQ) has clearly acquired the status of legacy questionnaire for measuring health-related quality of life in patients with chronic obstructive pulmonary disease (COPD). The main aim of this study was to assess the underlying dimensionality of the SGRQ and to investigate the added value of the empirical weights used to calculate total scores. METHODS: The official Dutch translation of the SGRQ was completed by 444 COPD patients participating in two clinical studies. These data were used for secondary data analysis in this study. Three complementary statistical methods were used to assess dimensionality: Mokken scale analysis (MSA), parametric multidimensional item response theory (IRT) and bifactor analysis. Additionally, the original SGRQ weighting procedure was compared to IRT-based weighting. RESULTS: The results of the MSA and multidimensional item response theory (MIRT) pointed toward a unidimensional structure. The bifactor analyses indicated that there was a strong general factor, but the group factors did have additional value. Nineteen items performed poorly in the MSA, MIRT analysis or both. Shortening the scale from 50 to 31 items did not negatively impact measurement precision. SGRQ total score and IRT-derived scores correlated strongly, 0.90 for the one-parameter model and 0.99 for the two-parameter model. CONCLUSION: The SGRQ contains some multidimensionality, but an abbreviated version can be used as a unidimensional tool in patients with COPD. Subscale scores should be used with care. SGRQ total scores correlated highly with IRT-based scores, and thus, the weighting methods may be used interchangeably to calculate total scores.

A comparison of time-varying covariates in two smoking cessation interventions for cardiac patients.

The aim of the study was to explore the time-varying contribution of social cognitive determinants of smoking cessation following an intervention on cessation. Secondary analyses were performed on data from two comparable randomized controlled trials on brief smoking cessation interventions for cardiac in- and outpatients. Cox regression with time-varying covariates was applied to examine the predictive cognitions for smoking cessation over time. Both samples showed self-efficacy and intention-to-quit to be strong time-varying indicators of smoking cessation during the full 1-year follow-up period, and during the post-treatment phase in particular. Less consistently, time-varying cons of quitting and social influence were also found to be associated with smoking cessation, depending on the sample and type of intervention. Self-efficacy and intention-to-quit were the major covariates and positively related to smoking cessation over time among cardiac patients, in line with social-cognitive theories. Interestingly, both cognitive constructs appeared to act with some delay. Apparently, smoking cessation is a lengthy process in which the interplay between self-efficacy (and intention indirectly) and quitting behavior will largely determine long-term maintenance of abstinence. The presented time-varying analyses seem a valid and feasible way to underpin trajectories of cognitions in datasets with a limited number of time intervals.

Implementation and User Evaluation of an eHealth Technology Platform Supporting Patients With Cardiovascular Disease in Managing Their Health After a Cardiac Event: Mixed Methods Study.

BACKGROUND: eHealth technology can help patients with cardiovascular disease adopt and maintain a healthy lifestyle by supporting self-management and offering guidance, coaching, and tailored information. However, to support patients over time, eHealth needs to blend in with their needs, treatment, and daily lives. Just as needs can differ between patients, needs can change within patients over time. To better adapt technology features to patients' needs, it is necessary to account for these changes in needs and contexts of use. OBJECTIVE: This study aimed to identify and monitor patients' needs for support from a web-based health management platform and how these needs change over time. It aimed to answer the following research questions: "How do novice and more advanced users experience an online health management platform?" "What user expectations support or hinder the adoption of an online health management platform, from a user perspective?" and "How does actual usage relate to user experiences and adoption?" METHODS: A mixed methods design was adopted. The first method involved 2 rounds of usability testing, followed by interviews, with 10 patients at 0 months (round 1) and 12 patients at 6 months (round 2). In the second method, log data were collected to describe the actual platform use. RESULTS: After starting cardiac rehabilitation, the platform was used frequently. The patients mentioned that they need to have an incentive, set goals, self-monitor their health data, and feel empowered by the platform. However, soon after the rehabilitation program stopped, use of the platform declined or patients even quit because of the lack of continued tailored or personalized advice. The reward system motivated them to log data, but most participants indicated that being healthy should be the main focus, not receiving gifts. A web-based platform is flexible, accessible, and does not have any obligations; however, it should be implemented as an addition to regular care. CONCLUSIONS: Although use of the platform declined in the longer term, patients quitting the technology did not directly indicate that the technology was not functioning well or that patients no longer focused on achieving their values. The key to success should not be user adherence to a platform but adherence to healthy lifestyle habits. Therefore, the implementation of eHealth should include the transition to a stage where patients might no longer need support from a technology platform to be independently and sustainably adherent to their healthy lifestyle habits. This emphasizes the importance of conducting multi-iterative evaluations to continuously monitor whether and how patients' needs and contexts of use change over time. Future research should focus on how this transition can be identified and monitored and how these insights can inform the design and implementation of the technology.

Augmenting outpatient alcohol treatment as usual with online approach bias modification training: A double-blind randomized controlled trial.

Previous research shows that automatic tendency to approach alcohol plays a causal role in problematic alcohol use and can be retrained by Approach Bias Modification (ApBM). ApBM has been shown to be effective for patients diagnosed with alcohol use disorder (AUD) in inpatient treatment. This study aimed to investigate the effectiveness of adding an online ApBM to treatment as usual (TAU) in an outpatient setting compared to receiving TAU with an online placebo training. 139 AUD patients receiving face-to-face or online treatment as usual (TAU) participated in the study. The patients were randomized to an active or placebo version of 8 sessions of online ApBM over a 5-week period. The weekly consumed standard units of alcohol (primary outcome) was measured at pre-and post-training, 3 and 6 months follow-up. Approach tendency was measured pre-and-post ApBM training. No additional effect of ApBM was found on alcohol intake, nor other outcomes such as craving, depression, anxiety, or stress. A significant reduction of the alcohol approach bias was found. This research showed that approach bias retraining in AUD patients in an outpatient treatment setting reduces the tendency to approach alcohol, but this training effect does not translate into a significant difference in alcohol reduction between groups. Explanations for the lack of effects of ApBM on alcohol consumption are treatment goal and severity of AUD. Future ApBM research should target outpatients with an abstinence goal and offer alternative, more user-friendly modes of delivering ApBM training.

Cost-effectiveness of an intensive smoking cessation intervention for COPD outpatients.

INTRODUCTION: To determine the cost-effectiveness of a high-intensity smoking cessation program (SmokeStop Therapy; SST) versus a medium-intensity treatment (Minimal Intervention Strategy for Lung patients [LMIS]) for chronic obstructive pulmonary disease outpatients. METHODS: The cost-effectiveness analysis was based on a randomized controlled trial investigating the effectiveness of the SST compared with the LMIS with 12-month follow-up. The primary outcome measure was the cotinine-validated continuous abstinence rate based on intention to treat. A health care perspective was adopted, with outcomes assessed in terms of (incremental) additional quitters gained, exacerbations prevented, and hospital days prevented. Health care resource use, associated with smoking cessation, was collected at baseline and 12 months after the start of the interventions. Monte Carlo simulations were performed to evaluate the robustness of the results. RESULTS: The average patient receiving SST generated €581 in health care costs, including the costs of the smoking cessation program, versus €595 in the LMIS. The SST is also associated with a lower average number of exacerbations (0.38 vs. 0.60) and hospital days (0.39 vs. 1) per patient and a higher number of quitters (20 vs. 9) at lower total costs. This leads to a dominance of the SST compared with the LMIS. CONCLUSIONS: The high-intensive SST is more cost-effective than the medium-intensive LMIS after 1 year. This is associated with cost savings per additional quitter, prevented exacerbations, and hospital days at lower or equal costs.

The role of cognition in cost-effectiveness analyses of behavioral interventions.

BACKGROUND: Behavioral interventions typically focus on objective behavioral endpoints like weight loss and smoking cessation. In reality, though, achieving full behavior change is a complex process in which several steps towards success are taken. Any progress in this process may also be considered as a beneficial outcome of the intervention, assuming that this increases the likelihood to achieve successful behavior change eventually. Until recently, there has been little consideration about whether partial behavior change at follow-up should be incorporated in cost-effectiveness analyses (CEAs). The aim of this explorative review is to identify CEAs of behavioral interventions in which cognitive outcome measures of behavior change are analyzed. METHODS: Data sources were searched for publications before May 2011. RESULTS: Twelve studies were found eligible for inclusion. Two different approaches were found: three studies calculated separate incremental cost-effectiveness ratios for cognitive outcome measures, and one study modeled partial behavior change into the final outcome. Both approaches rely on the assumption, be it implicitly or explicitly, that changes in cognitive outcome measures are predictive of future behavior change and may affect CEA outcomes. CONCLUSION: Potential value of cognitive states in CEA, as a way to account for partial behavior change, is to some extent recognized but not (yet) integrated in the field. In conclusion, CEAs should consider, and where appropriate incorporate measures of partial behavior change when reporting effectiveness and hence cost-effectiveness.

An ideographic study into physiology, alcohol craving and lapses during one hundred days of daily life monitoring.

Introduction: Alcohol craving is a highly challenging obstacle to achieve long-term abstinence. Making alcohol use disorder patients timely aware of high-risk craving situations may protect them against relapse by prompting them to mobilize their coping resources. Current advances in wearable and smart-phone technology provide novel opportunities for the development of detecting these situations of heightened risk of craving, by enabling continuous tracking of fluctuations in psychological and physiological parameters. The present study therefore aims to determine the association between self-reported craving and relapses, and between heightened physiological activity. Specifically, we measured cardiovascular and electrodermal activity, and self-reported craving during one hundred days in the daily life of people trying to recover from alcoholism. The secondary aim is to study whether the association between physiology and craving can be strengthened by the inclusion of context related psychological parameters. Methods: An intensive repeated and continuous measures in naturalistic settings case-study design was employed. Ten participants were monitored with wearable bio-sensors and answered multiple questions every three hours on a smartphone app about craving, lapsing and multiple evidence based contextual variables. The association between physiology, craving and lapses was explored using Matthews correlation coefficients both with a current and 3 h lagged design. The contextual variables were included in a decision tree together with the physiological parameters to explore the added effect on the correlation of these contextual variables. Results: The association between lapses and craving was highly different across individuals, varying between a weak to a strong association. The association between cardiovascular activity and heightened self-reported craving was negligible to weak, however with a high specificity, meaning that most craving events were accompanied by increase heart rate. However, the association between electrodermal activity and craving was lower than with cardiovascular activity for most participants, both prior (lagged) and during craving. For two of the participants the association between physiology and craving improved by adding contextual variables, however, precision was too low. Conclusions: People differ strongly in their bodily reactions and psychological experiences during the first months of their addiction treatment. No individual in our study had unique one-to-one mappings between on the one hand physiological or psychological precursors, and on the other hand craving and (re)lapses. Therefore, detecting high risk craving situations with both physiological activity measured with wearables and psychological precursors to alert people specifically for an imminent (re)lapse, does not seem viable on the basis of the current results. We do see an added benefit of using physiology during treatment, as physiology can help start the conversation about possible high risk craving situations during that week. This would also help the counselor to gain added insights into the fluctuating states of the clients, and help to ameliorate the recall bias of clients. The present study showed the possibility and paved the way for future intensive longitudinal designs integrating both physiological, psychological and contextual factors during the challenging and lengthy recovery from addiction.

The psychological effects of the physical healthcare environment on healthcare personnel.

BACKGROUND: The physical healthcare environment is capable of affecting patients. This concept of 'healing environments' refers to the psychological impact of environmental stimuli through sensory perceptions. It excludes more physiological effects such as those produced by ergonomic (i.e. fall prevention) or facilitative (i.e. hygiene-related) variables. The importance of an atmosphere in the healthcare environment that promotes the health and well-being of patients is evident, but this environment should not negatively affect healthcare personnel. The physical healthcare environment is part of the personnel's 'workscape'. This can make the environment an important determinant of subjective work-related outcomes like job satisfaction and well-being, as well as of objective outcomes like absenteeism or quality of care. In order to effectively build or renovate healthcare facilities, it is necessary to pay attention to the needs of both patients and healthcare personnel. OBJECTIVES: To assess the psychological effects of the physical healthcare environment on healthcare personnel. SEARCH STRATEGY: We searched the Cochrane EPOC Group Specialised Register; Cochrane Central Register of Controlled Trials; Database of Abstracts and Reviews of Effects; MEDLINE; EMBASE; CINAHL; Civil Engineering Database and Compendex. We also searched the reference lists of included studies. SELECTION CRITERIA: We included randomised controlled trials (RCT), controlled clinical trials (CCT), controlled before and after studies (CBA), and interrupted time series (ITS) of psychological effects of the physical healthcare environment interventions for healthcare staff. The outcomes included measures of job satisfaction, satisfaction with the physical healthcare environment, quality of life, and quality of care. DATA COLLECTION AND ANALYSIS: Two reviewers independently assessed studies for eligibility, extracted data, and assessed methodological quality. MAIN RESULTS: We identified one study, which adopted a CBA study design to investigate the simultaneous effects of multiple environmental stimuli. Staff mood improved in this study, while no effects were found on ward atmosphere or unscheduled absences. AUTHORS' CONCLUSIONS: One study was included in this review. This review therefore indicates that, at present, there is insufficient evidence to support or refute the impact of the physical healthcare environment on work-related outcomes of healthcare staff. Methodological shortcomings, particularly confounding with other variables and the lack of adequate control conditions, partially account for this lack of evidence. Given these methodological issues, the field is in need of well-conducted controlled trials.

Values of Importance to Patients With Cardiovascular Disease as a Foundation for eHealth Design and Evaluation: Mixed Methods Study.

BACKGROUND: eHealth interventions are developed to support and facilitate patients with lifestyle changes and self-care tasks after being diagnosed with a cardiovascular disease (CVD). Creating long-lasting effects on lifestyle change and health outcomes with eHealth interventions is challenging and requires good understanding of patient values. OBJECTIVE: The aim of the study was to identify values of importance to patients with CVD to aid in designing a technological lifestyle platform. METHODS: A mixed method design was applied, combining data from usability testing with an additional online survey study, to validate the outcomes of the usability tests. RESULTS: A total of 11 relevant patient values were identified, including the need for security, support, not wanting to feel anxious, tailoring of treatment, and personalized, accessible care. The validation survey shows that all values but one (value 9: To have extrinsic motivation to accomplish goals or activities [related to health/lifestyle]) were regarded as important/very important. A rating of very unimportant or unimportant was given by less than 2% of the respondents (value 1: 4/641, 0.6%; value 2: 10/641, 1.6%; value 3: 9/641, 1.4%; value 4: 5/641, 0.8%; value 5: 10/641, 1.6%; value 6: 4/641, 0.6%; value 7: 10/639, 1.6%; value 8: 4/639, 0.6%; value 10: 3/636, 0.5%; value 11: 4/636, 0.6%) to all values except but one (value 9: 56/636, 8.8%). CONCLUSIONS: There is a high consensus among patients regarding the identified values reflecting goals and themes central to their lives, while living with or managing their CVD. The identified values can serve as a foundation for future research to translate and integrate these values into the design of the eHealth technology. This may call for prioritization of values, as not all values can be met equally.

Psychologically mediated effects of the physical healthcare environment on work-related outcomes of healthcare personnel.

BACKGROUND: The physical healthcare environment is capable of affecting patients. This concept of 'healing environments' refers to the psychological impact of environmental stimuli through sensory perceptions. It excludes more physiological effects such as those produced by ergonomic (i.e. fall prevention) or facilitative (i.e. hygiene-related) variables. The importance of an atmosphere in the healthcare environment that promotes the health and well-being of patients is evident, but this environment should not negatively affect healthcare personnel. The physical healthcare environment is part of the personnel's 'workscape'. This can make the environment an important determinant of subjective work-related outcomes like job satisfaction and well-being, as well as of objective outcomes like absenteeism or quality of care. In order to effectively build or renovate healthcare facilities, it is necessary to pay attention to the needs of both patients and healthcare personnel. OBJECTIVES: To assess the psychological effects of the physical healthcare environment on healthcare personnel. SEARCH STRATEGY: We searched the Cochrane EPOC Group Specialised Register; Cochrane Central Register of Controlled Trials; Database of Abstracts and Reviews of Effects; MEDLINE; EMBASE; CINAHL; Civil Engineering Database and Compendex. We also searched the reference lists of included studies. SELECTION CRITERIA: We included randomised controlled trials (RCT), controlled clinical trials (CCT), controlled before and after studies (CBA), and interrupted time series (ITS) of psychological effects of the physical healthcare environment interventions for healthcare staff. The outcomes included measures of job satisfaction, satisfaction with the physical healthcare environment, quality of life, and quality of care. DATA COLLECTION AND ANALYSIS: Two reviewers independently assessed studies for eligibility, extracted data, and assessed methodological quality. MAIN RESULTS: We identified one study, which adopted a CBA study design to investigate the simultaneous effects of multiple environmental stimuli. Staff mood improved in this study, while no effects were found on ward atmosphere or unscheduled absences. AUTHORS' CONCLUSIONS: One study was included in this review. This review therefore indicates that, at present, there is insufficient evidence to support or refute the impact of the physical healthcare environment on work-related outcomes of healthcare staff. Methodological shortcomings, particularly confounding with other variables and the lack of adequate control conditions, partially account for this lack of evidence. Given these methodological issues, the field is in need of well-conducted controlled trials.

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

BACKGROUND: Blended web-based and face-to-face (F2F) treatment is a promising electronic health service because the strengths of one mode of delivery should compensate for the weaknesses of the other. OBJECTIVE: The aim of this study was to explore this compensation by examining patients' user experience (UX) in a blended smoking cessation treatment (BSCT) in routine care. METHODS: Data on patients' UX were collected through in-depth interviews (n=10) at an outpatient smoking cessation clinic in the Netherlands. A content analysis of the semantic domains was used to analyze patients' UX. To describe the UX, the Hassenzahl UX model was applied, examining 4 of the 5 key elements of UX from a user's perspective: (1) patients' standards and expectations, (2) apparent character (pragmatic and hedonic attributes), (3) usage situation, and (4) consequences (appeal, emotions, and behavior). RESULTS: BSCT appeared to be a mostly positively experienced service. Patients had a positive-pragmatic standard and neutral-open expectation toward BSCT at the treatment start. The pragmatic attributes of the F2F sessions were mostly perceived as positive, whereas the pragmatic attributes of the web sessions were perceived as both positive and negative. For the hedonic attributes, there seemed to be a difference between the F2F and web sessions. Specifically, the hedonic attributes of the web sessions were experienced as mostly negative, whereas those of the F2F sessions were experienced as mostly positive. For the usage situation, the physical and social contexts were experienced positively, whereas the task and technical contexts were experienced negatively. Nevertheless, the consequential appeal of BSCT was positive. However, the consequential emotions and behavior varied, ultimately resulting in diverse combinations of consequential appeal, emotions, and behavior (positive, negative, and mixed). CONCLUSIONS: This study provided insights into the UX of a blended treatment, and the results support the expectation that in a blended treatment, the strengths of one mode of delivery may compensate for the weaknesses of the other. However, in this certain setting, this is mainly achieved in only one way: F2F sessions compensated for the weaknesses of the web sessions. As a practical conclusion, this may mean that the web sessions, supported by the strengths of the F2F sessions, offer an interesting approach for further improving the blended treatment. Our theoretical findings reflect the relevance of the aspects of hedonism, such as fun, joy, or happiness in the UX, which were not mentioned in relation to the web sessions and were only scarcely mentioned in relation to the F2F sessions. Future research should further investigate the role of hedonistic aspects in a blended treatment and whether increased enjoyment of a blended treatment could increase treatment adherence and, ultimately, effectiveness.