BackgroundIn 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.MethodsCross-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.ResultsAs 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.ConclusionsThis 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.

IntroductionBest–worst scaling (BWS) is becoming increasingly popular to elicit preferences in health care. However, little is known about current practice and trends in the use of BWS in health care. This study aimed to identify, review and critically appraise BWS in health care, and to identify trends over time in key aspects of BWS.MethodsA systematic review was conducted, using Medline (via Pubmed) and EMBASE to identify all English-language BWS studies published up until April 2016. Using a predefined extraction form, two reviewers independently selected articles and critically appraised the study quality, using the Purpose, Respondents, Explanation, Findings, Significance (PREFS) checklist. Trends over time periods (≤2010, 2011, 2012, 2013, 2014 and 2015) were assessed further.ResultsA total of 62 BWS studies were identified, of which 26 were BWS object case studies, 29 were BWS profile case studies and seven were BWS multi-profile case studies. About two thirds of the studies were performed in the last 2 years. Decreasing sample sizes and decreasing numbers of factors in BWS object case studies, as well as use of less complicated analytical methods, were observed in recent studies. The quality of the BWS studies was generally acceptable according to the PREFS checklist, except that most studies did not indicate whether the responders were similar to the non-responders.ConclusionUse of BWS object case and BWS profile case has drastically increased in health care, especially in the last 2 years. In contrast with previous discrete-choice experiment reviews, there is increasing use of less sophisticated analytical methods.Electronic supplementary materialThe online version of this article (doi:10.1007/s40273-016-0429-5) contains supplementary material, which is available to authorized users.

ObjectiveTailored digital health programs can promote positive health-related lifestyle changes and have been shown to be (cost) effective in trials. However, such programs are used suboptimally. New approaches are needed to optimise the use of these programs. This paper illustrates the potential of recommender systems to support and enhance computer-tailored digital health interventions. The aim is threefold, to explore: (1) how recommender systems provide health recommendations, (2) to what extent recommender systems incorporate theoretical models and (3) how the use of recommender systems may enhance the usage of computer-tailored interventions.MethodsA scoping review was conducted, using MEDLINE and ScienceDirect, to identify health recommender systems reported in studies between January 2007 and December 2017. Information was subsequently extracted to understand the potential benefits of recommender systems for computer-tailored digital health programs. Titles and abstracts of 1184 studies were screened for the full-text screening, in which two reviewers independently selected articles and systematically extracted data using a predefined extraction form.ResultsA total of 26 articles were included for data extraction. General characteristics were reported, with eight studies reporting hybrid filtering. A description of how each recommender system provides a recommendation is described; the majority of recommender systems used messages as recommendation. We identified the potential effects of recommender systems on efficiency, effectiveness, trustworthiness and enjoyment of the digital health program.ConclusionsIncorporating a collaborative method with demographic filtering as a second step to knowledge-based filtering could potentially add value to traditional tailoring with regard to enhancing the user experience. This study illustrates how recommender systems, especially hybrid programs, may have the potential to bring tailored digital health forward.

BackgroundDifferent criteria regarding outcome measures in smoking research are used, which can lead to confusion about study results. Consensus in outcome criteria may enhance the comparability of future studies. This study aims (1) to provide an overview of tobacco researchers’ considered preferences regarding outcome criteria in randomized controlled smoking cessation trials, and (2) to identify the extent to which researchers can reach consensus on the importance of these outcome criteria.MethodsA three-round online Delphi study was conducted among smoking cessation experts. In the first round, the most important smoking cessation outcome measures were collected by means of open-ended questions, which were categorized around self-reported and biochemical validation measures. Experts (n = 17) were asked to name the outcome measures (as well as their assessment method and ideal follow-up period) that they thought were important when assessing smoking-related outcomes. In the second (n = 48) and third rounds (n = 37), a list of outcome measures—identified in the first round—was presented to experts. Asking them to rate the importance of each measure on a seven-point scale.ResultsExperts reached consensus on several items. For self-reports, experts agreed that prolonged abstinence (6 or/and 12 months), point prevalence abstinence (7 days), continuous abstinence (6 months), and the number of cigarettes smoked (7 days) are important outcome measures. Experts reached consensus that biochemical validation methods should not always be used. The preferred biochemical validation methods were carbon monoxide (expired air) and cotinine (saliva). Preferred follow-ups included 6 and/or 12 months, with or without intermediate measurements.ConclusionsFindings suggest only partial compliance with the Russell standard and that more outcome measures may be important (including seven-day point-prevalence abstinence, number of cigarettes smoked, and cotinine when using biochemical validation). This study showed where there is and is not consensus, reflecting the need to develop a more comprehensive standard. For these purposes we provided suggestions for the Russell 2.0 standard.

Background During the first wave of the COVID-19 pandemic, social distancing and hand hygiene have been the primary means of reducing transmission in the absence of effective treatments or vaccines, but understanding of their determinants is limited. This study aimed to investigate knowledge and socio-cognitive perceptions, and their associations with such protective behaviours, in UK university students. Methods A cross-sectional online survey of 293 students was undertaken on 13 May 2020. Survey questions addressed demographics, knowledge of the disease and effectiveness of the protective measures, risk perception, socio-cognitive perceptions (e.g. attitude, social support, and self-efficacy), habit, time factors and trust, as well as the hand hygiene and social distancing behaviours. Multiple linear regression was used to identify the strongest associations of potential determinants with behaviour. Results Participants reported high levels of social distancing with 88.9% answering “Mostly” or “Always” for every activity, but only 42.0% reporting the same for all hand hygiene activities. Knowledge of the effectiveness of each activity in preventing transmission was high, with 90.7% and 93.5% respectively identifying at least 7 of 8 hand hygiene or 9 of 10 social distancing activities correctly. Habit (β = 0.39, p = 0.001) and time factors (β = 0.28, p = 0.001) were the greatest contributors to unique variance in hand hygiene behaviour, followed by ethnicity (β = − 0.13, p = 0.014) and risk perception (β = 0.13, p = 0.016). For social distancing behaviour, the determinants were self-efficacy (β = 0.25, p < 0.001), perceived advantages (β = 0.15, p = 0.022), trust in policy (β = 0.14, p = 0.026) and gender (β = − 0.14, p = 0.016). Regression models explained 40% hand hygiene and 25% social distancing variance. Conclusions This study indicated that communications about effectiveness of hand hygiene and social distancing behaviours had been effective in terms of knowledge acquisition. However, in the light of likely second waves of COVID-19, attention to maintaining social distancing behaviour and improving hand hygiene behaviour may need to address more difficult areas of changing habits, overcoming time factors and building trust, as well as interventions to increase self-efficacy and address risk perception concerns.

Computer-tailored programs may help to prevent overweight and obesity, which are worldwide public health problems. This study investigated (1) the 12-month effectiveness of a video- and text-based computer-tailored intervention on energy intake, physical activity, and body mass index (BMI), and (2) the role of educational level in intervention effects. A randomized controlled trial in The Netherlands was conducted, in which adults were allocated to a video-based condition, text-based condition, or control condition, with baseline, 6 months, and 12 months follow-up. Outcome variables were self-reported BMI, physical activity, and energy intake. Mixed-effects modelling was used to investigate intervention effects and potential interaction effects. Compared to the control group, the video intervention group was effective regarding energy intake after 6 months (least squares means (LSM) difference = −205.40, p = 0.00) and 12 months (LSM difference = −128.14, p = 0.03). Only video intervention resulted in lower average daily energy intake after one year (d = 0.12). Educational role and BMI did not seem to interact with this effect. No intervention effects on BMI and physical activity were found. The video computer-tailored intervention was effective on energy intake after one year. This effect was not dependent on educational levels or BMI categories, suggesting that video tailoring can be effective for a broad range of risk groups and may be preferred over text tailoring.

BackgroundTobacco 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.ObjectiveThe 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.MethodsA 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.ResultsOverall, 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%.ConclusionsAlthough 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.

AimsTo identify different types of models used in economic evaluations of smoking cessation, analyse the quality of the included models examining their attributes and ascertain their transferability to a new context.MethodsA systematic review of the literature on the economic evaluation of smoking cessation interventions published between 1996 and April 2015, identified via Medline, EMBASE, National Health Service (NHS) Economic Evaluation Database (NHS EED), Health Technology Assessment (HTA). The checklist‐based quality of the included studies and transferability scores was based on the European Network of Health Economic Evaluation Databases (EURONHEED) criteria. Studies that were not in smoking cessation, not original research, not a model‐based economic evaluation, that did not consider adult population and not from a high‐income country were excluded.FindingsAmong the 64 economic evaluations included in the review, the state‐transition Markov model was the most frequently used method (n = 30/64), with quality adjusted life years (QALY) being the most frequently used outcome measure in a life‐time horizon. A small number of the included studies (13 of 64) were eligible for EURONHEED transferability checklist. The overall transferability scores ranged from 0.50 to 0.97, with an average score of 0.75. The average score per section was 0.69 (range = 0.35–0.92). The relative transferability of the studies could not be established due to a limitation present in the EURONHEED method.ConclusionAll existing economic evaluations in smoking cessation lack in one or more key study attributes necessary to be fully transferable to a new context.