2,697 research outputs found

    Identification of behaviour change techniques and engagement strategies to design a smartphone app to reduce alcohol consumption using a formal consensus method

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    Background: Digital interventions to reduce excessive alcohol consumption have the potential to have a broader reach and be more cost-effective than traditional brief interventions. However, there is not yet a strong evidence base on their ability to engage users or on their effectiveness. Objective: This study aimed to identify the behaviour change techniques (BCTs) and engagement strategies most worthy of further study by inclusion in a smartphone application (app) to reduce alcohol consumption, using formal expert consensus methods. Methods: The first phase of the study consisted of a Delphi exercise with three rounds. It was conducted with seven international experts in the field of alcohol and/or behaviour change. In the first round, experts identified BCTs most likely to be effective at reducing alcohol consumption and strategies most likely to engage users with an app; these were rated in the second round; and those rated as effective by at least four out of seven participants were ranked in the third round. The rankings were analysed using Kendall’s W coefficient of concordance, which indicates consensus between participants. The second phase consisted of a new, independent group of experts (n=43) ranking the BCTs that were identified in the first phase. The correlation between the rankings of the two groups was assessed using Spearman’s rank correlation coefficient. Results: Twelve BCTs were identified as likely to be effective. There was moderate agreement among the experts over their ranking (W=.465, χ2(11)=35.77, P<.001) and the BCTs receiving the highest mean rankings were self-monitoring, goal-setting, action planning, and feedback in relation to goals. There was a significant correlation between the ranking of the BCTs by the group of experts who identified them and a second independent group of experts (Spearman’s rho=.690, P=.01). Seventeen responses were generated for strategies likely to engage users. There was moderate agreement among experts on the ranking of these engagement strategies (W=.563, χ2(15)=59.16, P<.001) and those with the highest mean rankings were ease of use, design – aesthetic, feedback, function, design – ability to change design to suit own preferences, tailored information, and unique smartphone features. Conclusions: The BCTs with greatest potential to include in a smartphone app to reduce alcohol consumption were judged by experts to be self-monitoring, goal-setting, action planning, and feedback in relation to goals. The strategies most likely to engage users were ease of use, design, tailoring of design and information, and unique smartphone features

    A Mobile App to Aid Smoking Cessation: Preliminary Evaluation of SmokeFree28

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    Background: Little is known about the effectiveness of mobile apps in aiding smoking cessation or their validity for automated collection of data on smoking cessation outcomes. Objective: We conducted a preliminary evaluation of SF28 (SF28 is the name of the app, short for SmokeFree28)—an app aimed at helping smokers to be smoke-free for 28 days. / Methods: Data on sociodemographic characteristics, smoking history, number of logins, and abstinence at each login were uploaded to a server from SF28 between August 2012 and August 2013. Users were included if they were aged 16 years or over, smoked cigarettes at the time of registration, had set a quit date, and used the app at least once on or after their quit date. Their characteristics were compared with data from a representative sample of smokers trying to stop smoking in England. The percentage of users recording 28 days of abstinence was compared with a value of 15% estimated for unaided quitting. Correlations were assessed between recorded abstinence for 28 days and well-established abstinence predictors. / Results: A total of 1170 users met the inclusion criteria. Compared with smokers trying to quit in England, they had higher consumption, and were younger, more likely to be female, and had a non-manual rather than manual occupation. In total, 18.9% (95% CI 16.7-21.1) were recorded as being abstinent from smoking for 28 days or longer. The mean number of logins was 8.5 (SD 9.0). The proportion recording abstinence for 28 days or longer was higher in users who were older, in a non-manual occupation, and in those using a smoking cessation medication. / Conclusions: The recorded 28-day abstinence rates from the mobile app, SF28, suggest that it may help some smokers to stop smoking. Further evaluation by means of a randomized trial appears to be warranted

    Validation of the theoretical domains framework for use in behaviour change and implementation research

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    BACKGROUND: An integrative theoretical framework, developed for cross-disciplinary implementation and other behaviour change research, has been applied across a wide range of clinical situations. This study tests the validity of this framework. METHODS: Validity was investigated by behavioural experts sorting 112 unique theoretical constructs using closed and open sort tasks. The extent of replication was tested by Discriminant Content Validation and Fuzzy Cluster Analysis. RESULTS: There was good support for a refinement of the framework comprising 14 domains of theoretical constructs (average silhouette value 0.29): 'Knowledge', 'Skills', 'Social/Professional Role and Identity', 'Beliefs about Capabilities', 'Optimism', 'Beliefs about Consequences', 'Reinforcement', 'Intentions', 'Goals', 'Memory, Attention and Decision Processes', 'Environmental Context and Resources', 'Social Influences', 'Emotions', and 'Behavioural Regulation'. CONCLUSIONS: The refined Theoretical Domains Framework has a strengthened empirical base and provides a method for theoretically assessing implementation problems, as well as professional and other health-related behaviours as a basis for intervention development

    Detection of solvents using a distributed fibre optic sensor

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    A fibre optic sensor that is capable of distributed detection of liquid solvents is presented. Sensor interrogation using optical time domain reflectometry (OTDR) provides the capability of locating solvent spills to a precision of ±2 m over a total sensor length that may extend to 20 km

    Statistical interaction modeling of bovine herd behaviors

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    While there has been interest in modeling the group behavior of herds or flocks, much of this work has focused on simulating their collective spatial motion patterns which have not accounted for individuality in the herd and instead assume a homogenized role for all members or sub-groups of the herd. Animal behavior experts have noted that domestic animals exhibit behaviors that are indicative of social hierarchy: leader/follower type behaviors are present as well as dominance and subordination, aggression and rank order, and specific social affiliations may also exist. Both wild and domestic cattle are social species, and group behaviors are likely to be influenced by the expression of specific social interactions. In this paper, Global Positioning System coordinate fixes gathered from a herd of beef cows tracked in open fields over several days at a time are utilized to learn a model that focuses on the interactions within the herd as well as its overall movement. Using these data in this way explores the validity of existing group behavior models against actual herding behaviors. Domain knowledge, location geography and human observations, are utilized to explain the causes of these deviations from this idealized behavior

    The Behaviour Change Wheel approach

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    The Behaviour Change Wheel (BCW) approach is a set of interrelated tools and principles intended to guide decision-making and facilitate systematic development of behavioural interventions. This chapter presents the four behavioural science tools of the BCW and demonstrates how they interlink and can be applied as a system for understanding behaviour and designing behaviour change interventions. Implementing new practices and/or changing existing practices in organizations, services and systems requires changes in individual (for example, health care professional) and collective (for example, clinical team) human behaviour. The implementation research literature contains multiple examples of how the BCW approach has been applied in different ways for different purposes. These include exploring implementation problems, designing and refining implementation interventions, conducting process evaluation of implementation interventions and synthesising implementation research. The authors report on ways in which the various tools have predominantly been used, with accompanying examples to illustrate objectives, methods and high-level outcomes

    Increasing condom use in heterosexual men: development of a theory-based interactive digital intervention

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    Increasing condom use to prevent sexually transmitted infections is a key public health goal. Interventions are more likely to be effective if they are theory- and evidence-based. The Behaviour Change Wheel (BCW) provides a framework for intervention development. To provide an example of how the BCW was used to develop an intervention to increase condom use in heterosexual men (the MenSS website), the steps of the BCW intervention development process were followed, incorporating evidence from the research literature and views of experts and the target population. Capability (e.g. knowledge) and motivation (e.g. beliefs about pleasure) were identified as important targets of the intervention. We devised ways to address each intervention target, including selecting interactive features and behaviour change techniques. The BCW provides a useful framework for integrating sources of evidence to inform intervention content and deciding which influences on behaviour to target

    Face masks to prevent community transmission of viral respiratory infections: A rapid evidence review using Bayesian analysis [Preprint, version 1]

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    Background: Face masks have been proposed as an important way of reducing transmission of viral respiratory infections, including SARS-CoV-2. / Objective: To assess the likelihood that wearing face masks in community settings reduces transmission of viral respiratory infections. / Methods: We conducted a rapid evidence review and used a Bayesian statistical approach to analysing experimental and observational studies conducted in community-dwelling children and adults that assessed the effectiveness of face mask wearing (vs. no face masks) on self-reported, laboratory-confirmed, or clinically diagnosed viral respiratory infections. / Results: Eleven RCTs and 10 observational studies met the inclusion criteria. The calculation of Bayes factors and cumulative posterior odds from the RCTs showed a moderate likelihood of a small effect of wearing surgical face masks in community settings in reducing self-reported influenza-like illness (ILI) (cumulative posterior odds = 3.61). However, the risk of reporting bias was high and evidence of reduction of clinically- or laboratory-confirmed infection was equivocal (cumulative posterior odds = 1.07 and 1.22, respectively). Observational studies yielded evidence of a negative association between face mask wearing and ILI but with high risk of confounding and reporting bias. / Conclusions: Available evidence from RCTs is equivocal as to whether or not wearing face masks in community settings results in a reduction in clinically- or laboratory-confirmed viral respiratory infections. No relevant studies concerned SARS-CoV-2 or were undertaken in community settings in the UK

    Face masks to prevent community transmission of viral respiratory infections: A rapid evidence review using Bayesian analysis [Preprint, version 1]

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    Background: Face masks have been proposed as an important way of reducing transmission of viral respiratory infections, including SARS-CoV-2. / Objective: To assess the likelihood that wearing face masks in community settings reduces transmission of viral respiratory infections. / Methods: We conducted a rapid evidence review and used a Bayesian statistical approach to analysing experimental and observational studies conducted in community-dwelling children and adults that assessed the effectiveness of face mask wearing (vs. no face masks) on self-reported, laboratory-confirmed, or clinically diagnosed viral respiratory infections. / Results: Eleven RCTs and 10 observational studies met the inclusion criteria. The calculation of Bayes factors and cumulative posterior odds from the RCTs showed a moderate likelihood of a small effect of wearing surgical face masks in community settings in reducing self-reported influenza-like illness (ILI) (cumulative posterior odds = 3.61). However, the risk of reporting bias was high and evidence of reduction of clinically- or laboratory-confirmed infection was equivocal (cumulative posterior odds = 1.07 and 1.22, respectively). Observational studies yielded evidence of a negative association between face mask wearing and ILI but with high risk of confounding and reporting bias. / Conclusions: Available evidence from RCTs is equivocal as to whether or not wearing face masks in community settings results in a reduction in clinically- or laboratory-confirmed viral respiratory infections. No relevant studies concerned SARS-CoV-2 or were undertaken in community settings in the UK
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