https://cronfa.swan.ac.uk/Record/cronfa54196/Download/54196__17493__47815979be224dde9a7b3f9b037ce7ec.pdf

Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science.

It doesn't matter how beautiful your theory is, it doesn't matter how smart you are. If it doesn't agree with experiment, it's wrong. (Richard P. Feynman)The Theory of Planned Behaviour (TPB; Ajzen...

https://www.tandfonline.com/doi/pdf/10.1080/17437199.2013.869710

Time to retire the theory of planned behaviour

The Lancet Psychiatry Commission: a blueprint for protecting physical health in people with mental illness

The term ‘habit’ is widely used to predict and explain behaviour. This paper examines use of the term in the context of health-related behaviour, and explores how the concept might be made more useful. A narrative review is presented, drawing on a scoping review of 136 empirical studies and 8 literature reviews undertaken to document usage of the term ‘habit’, and methods to measure it. A coherent definition of ‘habit’, and proposals for improved methods for studying it, were derived from findings. Definitions of ‘habit’ have varied in ways that are often implicit and not coherently linked with an underlying theory. A definition is proposed whereby habit is a process by which a stimulus generates an impulse to act as a result of a learned stimulus-response association. Habit-generated impulses may compete or combine with impulses and inhibitions arising from other sources, including conscious decision-making, to influence responses, and need not generate behaviour. Most research on habit is based on correlational studies using self-report measures. Adopting a coherent definition of ‘habit’, and a wider range of paradigms, designs and measures to study it, may accelerate progress in habit theory and application.

https://www.tandfonline.com/doi/pdf/10.1080/17437199.2013.876238

A review and analysis of the use of 'habit' in understanding, predicting and influencing health-related behaviour.

BACKGROUND: The Internet is now an indispensable part of daily life for the majority of people in many parts of the world. It offers an additional means of effecting changes to behaviour such as smoking. OBJECTIVES: To determine the effectiveness of Internet-based interventions for smoking cessation. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group Specialized Register. There were no restrictions placed on language of publication or publication date. The most recent search was conducted in April 2013. SELECTION CRITERIA: We included randomized and quasi-randomized trials. 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. DATA COLLECTION AND ANALYSIS: Two authors independently assessed and extracted data. Methodological and study quality details were extracted using a standardized form. We extracted smoking cessation outcomes of six months follow-up or more, reporting short-term outcomes where longer-term outcomes were not available. We reported study effects as a risk ratio (RR) with a 95% confidence interval (CI). Clinical and statistical heterogeneity limited our ability to pool studies. MAIN RESULTS: This updated review includes a total of 28 studies with over 45,000 participants. Some Internet programmes were intensive and included multiple outreach contacts with participants, whilst others relied on participants to initiate and maintain use.Fifteen trials compared an Internet intervention to a non-Internet-based smoking cessation intervention or to a no-intervention control. Ten of these recruited adults, one recruited young adult university students and two recruited adolescents. Seven of the trials in adults had follow-up at six months or longer and compared an Internet intervention to usual care or printed self help. In a post hoc subgroup analysis, pooled results from three trials that compared interactive and individually tailored interventions to usual care or written self help detected a statistically significant effect in favour of the intervention (RR 1.48, 95% CI 1.11 to 2.78). However all three trials were judged to be at high risk of bias in one domain and high statistical heterogeneity was detected (I² = 53%), with no obvious clinical explanation. Pooled results from two studies of an interactive, tailored intervention involving the Internet and automated phone contacts also detected a significant effect (RR 2.05, 95% CI 1.42 to 2.97, I² = 42%). Results from a sixth study comparing an interactive but non-tailored intervention to control did not detect a significant effect, nor did the seventh study, which compared a non-interactive, non-tailored intervention to control. Three trials comparing Internet interventions to face-to-face or phone counselling also did not detect evidence of an effect, nor did two trials evaluating Internet interventions as adjuncts to other behavioural interventions. A trial in college students increased point prevalence abstinence after 30 weeks but had no effect on sustained abstinence. Two small trials in adolescents did not detect an effect on cessation compared to control.Fourteen trials, all in adult populations, compared different Internet sites or programmes. Pooled estimates from three trials that compared tailored and/or interactive Internet programmes with non-tailored, non-interactive Internet programmes did not detect evidence of an effect (RR 1.12, 95% CI 0.95 to 1.32, I² = 0%). One trial detected evidence of a benefit from a tailored email compared to a non-tailored one, whereas a second trial comparing tailored messages to a non-tailored message did not detect evidence of an effect. Trials failed to detect a benefit of including a mood management component (three trials), or an asynchronous bulletin board. AUTHORS' CONCLUSIONS: Results suggest that some Internet-based interventions can assist smoking cessation at six months or longer, particularly those which are interactive and tailored to individuals. However, the trials that compared Internet interventions with usual care or self help did not show consistent effects and were at risk of bias. Further research is needed despite 28 studies on the subject. Future studies should carefully consider optimising the interventions which promise most effect such as tailoring and interactivity.

/pdf/internet-based-interventions-for-smoking-cessation-250jt3p0u5.pdf

Internet‐based interventions for smoking cessation

Theory of Addiction: West/Theory

Nicotine without smoke: Tobacco harm reduction

Slowing down the covid-19 outbreak: changing behaviour by understanding it.

BACKGROUND: Behaviour change interventions (BCI), their contexts and evaluation methods are heterogeneous, making it difficult to synthesise evidence and make recommendations for real-world policy and practice. Ontologies provide a means for addressing this. They represent knowledge formally as entities and relationships using a common language able to cross disciplinary boundaries and topic domains. This paper reports the development of the upper level of the Behaviour Change Intervention Ontology (BCIO), which provides a systematic way to characterise BCIs, their contexts and their evaluations. METHODS: Development took place in four steps. (1) Entities and relationships were identified by behavioural and social science experts, based on their knowledge of evidence and theory, and their practical experience of behaviour change interventions and evaluations. (2) The outputs of the first step were critically examined by a wider group of experts, including the study ontology expert and those experienced in annotating relevant literature using the initial ontology entities. The outputs of the second step were tested by (3) feedback from three external international experts in ontologies and (4) application of the prototype upper-level BCIO to annotating published reports; this informed the final development of the upper-level BCIO. RESULTS: The final upper-level BCIO specifies 42 entities, including the BCI scenario, elaborated across 21 entities and 7 relationship types, and the BCI evaluation study comprising 10 entities and 9 relationship types. BCI scenario entities include the behaviour change intervention (content and delivery), outcome behaviour, mechanism of action, and its context, which includes population and setting. These entities have corresponding entities relating to the planning and reporting of interventions and their evaluations. CONCLUSIONS: The upper level of the BCIO provides a comprehensive and systematic framework for representing BCIs, their contexts and their evaluations.

Representation of behaviour change interventions and their evaluation: Development of the Upper Level of the Behaviour Change Intervention Ontology [version 1; peer review: awaiting peer review]

Robert West

Papers

Theory of Addiction: West/Theory

Nicotine without smoke: Tobacco harm reduction

Slowing down the covid-19 outbreak: changing behaviour by understanding it.

Representation of behaviour change interventions and their evaluation: Development of the Upper Level of the Behaviour Change Intervention Ontology [version 1; peer review: awaiting peer review]

Pilot randomized controlled trial of an internet-based smoking cessation intervention for pregnant smokers (‘MumsQuit’)