Evaluation Of Behaviour Change Interventions Research Articles

Translating the Behaviour Change Technique Taxonomy v.1 to other languages: the approach used in European Portuguese (BCTTv1-PT).

The Behaviour Change Techniques Taxonomy v1 (BCTTv1) is the most widely used classification of behaviour change techniques (BCTs), contributing to the accurate report and evaluation of behaviour change interventions and accumulation of evidence. This study reports a structured approach to adapt the BCTTv1 into European Portuguese (BCTTv1-PT). A collaborative and iterative approach was used. The translation process encompassed four phases: (1) independent forward translation by two native Portuguese speakers proficient in English, (2) forward translation reconciliation, (3) expert consultation by involving seven experts in behaviour change to collect feedback on the draft version of the taxonomy through a structured online form; and (4) feedback analysis and improvement of the BCTTv1-PT. Independent forward translations and a reconciled version of the BCTTv1-PT were produced. All experts agreed with the groupings designation (100%). Recommendations were made to improve BCTs labels, definitions and/or examples in all groupings, except for Feedback and monitoring. Experts disagreed with the translated definitions in 40.9% of the BCTs (38/93), with examples in 21.5% (20/93) and with labels in 11.8% (11/93). Recommendations were made for all instances where there was disagreement (n = 69) and were enacted entirety, yielding the final version (BCTTv1-PT). Researchers, educators, students and health and other professionals will be able to standardise terminology and have a common language, contributing to the impact of the BCTTv1-PT. This study presents a systematic and rigorous approach for the adaptation of the BCTTv1 and similar taxonomies, which may guide others.

SATO (IDEAS expAnded wiTh BCIO): Workflow for designers of patient-centered mobile health behaviour change intervention applications

Designing effective theory-driven digital behaviour change interventions (DBCI) is a challenging task. To ease the design process, and assist with knowledge sharing and evaluation of the DBCI, we propose the SATO (IDEAS expAnded wiTh BCIO) design workflow based on the IDEAS (Integrate, Design, Assess, and Share) framework and aligned with the Behaviour Change Intervention Ontology (BCIO). BCIO is a structural representation of the knowledge in behaviour change domain supporting evaluation of behaviour change interventions (BCIs) but it is not straightforward to utilise it during DBCI design. IDEAS (Integrate, Design, Assess, and Share) framework guides multi-disciplinary teams through the mobile health (mHealth) application development life-cycle but it is not aligned with BCIO entities. SATO couples BCIO entities with workflow steps and extends IDEAS Integrate stage with consideration of customisation and personalisation. We provide a checklist of the activities that should be performed during intervention planning with concrete examples and a tutorial accompanied with case studies from the Cancer Better Life Experience (CAPABLE) European project. In the process of creating this workflow, we found the necessity to extend the BCIO to support the scenarios of multiple clinical goals in the same application. To ensure the SATO steps are easy to follow for the incomers to the field, we performed a preliminary evaluation of the workflow with two knowledge engineers, working on novel mHealth app design tasks.

Are commonly used lab-based measures of food value and choice predictive of self-reported real-world snacking? An ecological momentary assessment study.

While the assessment of actual food intake is essential in the evaluation of behaviour change interventions for weight-loss, it may not always be feasible to collect this information within traditional experimental paradigms. For this reason, measures of food preference (such as measures of food value and choice) are often used as more accessible alternatives. However, the predictive validity of these measures (in relation to subsequent food consumption) has not yet been studied. Our aim was to investigate the extent to which three commonly used measures of preference for snack foods (explicit food value, unhealthy food choice and implicit preference) predicted self-reported real-world snacking occasions. Ecological Momentary Assessment (EMA) design. Over a seven-day study period, participants (N= 49) completed three daily assessments where they reported their healthy and unhealthy snack food consumption and completed the three measures of preference (explicit food value, unhealthy food choice and implicit preference). Our findings demonstrated some weak evidence that unhealthy Visual Analogue Scale scores predicted between-subject increases in unhealthy snacking frequency (OR=1.018 [1.006, 1.030], p= .002). No other preference measures significantly predicted self-reported healthy or unhealthy snacking occasions (ps > .05). These findings raise questions in relation to the association between measures of preference and self-reported real-world snack food consumption. Future research should further evaluate the predictive and construct validity of these measures in relation to food behaviours and explore the development of alternative assessment methods within eating behaviour research.

Exploring determinants of antimicrobial prescribing behaviour: a qualitative study using the Theoretical Domains Framework

IntroductionFew qualitative studies have explored determinants of antimicrobial prescribing behaviour in hospitals, and none has made reference to behavioural theories. An understanding of these determinants is required for the successful development and implementation of behaviour change interventions (BCIs) in this area.AimTo explore the determinants of clinicians’ antimicrobial prescribing behaviour, using the Theoretical Domains Framework (TDF; a framework of behavioural theories).MethodsThis work was part of a multi-phase explanatory, sequential mixed methods PhD programme of research. This qualitative part involved semi-structured, online (video) interviews via a videoconferencing software programme (Zoom) with clinicians (doctors and pharmacists) based in 12 Hamad Medical Corporation hospitals in Qatar. Clinicians were sampled purposively in strata of gender, profession, years of experience and area of practice. The interview schedule was developed based on a review of published literature (1), previous findings of quantitative research (2) and the TDF to ensure comprehensive coverage of key determinants (including barriers and facilitators) related to clinicians’ antimicrobial prescribing behaviour. Interviews were conducted from December 2020 to February 2021, audio-recorded, transcribed and independently analysed by two research team members using the TDF as an initial coding framework.ResultsData saturation was achieved after interviewing eight doctors and eight pharmacists from a range of areas of practices and with a variety of experiences. A number of themes, linked to ten TDF domains, were identified as determinants of antimicrobial prescribing behaviour and these determinants were interrelated. In-depth analysis identified several barriers and facilitators that may contribute to inappropriate or appropriate antimicrobial prescribing. Main barriers identified were around hospital guidelines and electronic system deficiencies (environmental context and resources), gaps in the knowledge in relation to guidelines and appropriate prescribing (knowledge), restricted roles/responsibilities of microbiologists and pharmacists (professional role and identity), uncomfortable antimicrobial prescribing decisions (memory, attention and decision processes), as well as professional hierarchies and poor multidisciplinary teamworking/relationships (social influences). “Sometimes, the barrier would be the ego of senior doctors who refuse our evidence-based recommendation and depend on their clinical judgement or experience” (Pharmacist 470, Cardiology). Key facilitators highlighted included guidelines compliance goals and intentions, and the beliefs of consequences of appropriate or inappropriate prescribing. Further education and training sessions, and some changes to guidelines, including accessibility were also considered essential. “We need to seriously consider getting an antibiotic guidelines app which is downloaded to clinicians’ mobile phones. The mobile app is handy, you can access it anytime even at the patient’s bedside” (Doctor 514, Microbiology).ConclusionThis qualitative study, using a theoretically based approach, has identified that antimicrobial prescribing in hospitals is a complex process influenced by a broad range of behavioural determinants that described specific barriers and facilitators. The in-depth understanding of this complexity provided by this phase of the research may contribute to the design and development of theoretically based BCIs to improve clinicians’ antimicrobial prescribing. Limitations include data collected with online interviews due to the Covid-19 restrictions. This may have excluded some clinicians who did not feel comfortable with or have access to the technology required.References(1) Talkhan H, Stewart D, Mcintosh T, Ziglam H, Abdulrouf P, Al-Hail M et al. The use of theory in the development and evaluation of behaviour change interventions to improve antimicrobial prescribing: a systematic review. Journal of Antimicrobial Chemotherapy. 2020;75(9):2394-2410.(2) Talkhan H, Stewart D, McIntosh T, Ziglam H, Abdulrouf P, Al-Hail M et al. Using the Theoretical Domains Framework to investigate clinicians’ behavioural determinants of antimicrobial prescribing in Qatar. International Journal of Pharmacy Practice. 2021;29(1):i20-i22.

Optimizing red blood cell transfusion practices in the intensive care unit: a multi-phased health technology reassessment

Health technology reassessment (HTR) is a process to manage existing health technologies to ensure ongoing optimal use. A model to guide HTR was developed; however, there is limited practical experience. This paper addresses this knowledge gap through the completion of a multi-phase HTR of red blood cell (RBC) transfusion practices in the intensive care unit (ICU). The HTR consisted of three phases and here we report on the final phase: the development, implementation, and evaluation of behavior change interventions aimed at addressing inappropriate RBC transfusions in an ICU. The interventions, comprised of group education and audit and feedback, were co-designed and implemented with clinical leaders. The intervention was evaluated through a controlled before-and-after pilot feasibility study. The primary outcome was the proportion of potentially inappropriate RBC transfusions (i.e., with a pre-transfusion hemoglobin of 70 g/L or more). There was marked variability in the monthly proportion of potentially inappropriate RBC transfusions. Relative to the pre-intervention phase, there was no significant difference in the proportion of potentially inappropriate RBC transfusions post-intervention. Lessons from this work include the importance of early and meaningful engagement of clinical leaders; tailoring the intervention modalities; and, efficient access to data through an electronic clinical information system. It was feasible to design, implement, and evaluate a tailored, multi-modal behavior change intervention in this small-scale pilot study. However, early evaluation of the intervention revealed no change in technology use leading to reflection on the important question of how the HTR model needs to be improved.

Modelling decay in effectiveness for evaluation of behaviour change interventions: a tutorial for public health economists

Background and purpose Recent methodological reviews of evaluations of behaviour change interventions in public health have highlighted that the decay in effectiveness over time has been mostly overlooked, potentially leading to suboptimal decision-making. While, in principle, discrete-time Markov chains—the most commonly used modelling approach—can be adapted to account for decay in effectiveness, this framework inherently lends itself to strong model simplifications. The application of formal and more appropriate modelling approaches has been supported, but limited progress has been made to date. The purpose of this paper is to encourage this shift by offering a practical guide on how to model decay in effectiveness using a continuous-time Markov chain (CTMC)-based approach.MethodsA CTMC approach is demonstrated, with a contextualized tutorial being presented to facilitate learning and uptake. A worked example based on the stylized case study in physical activity promotion is illustrated with accompanying R code.DiscussionThe proposed framework presents a relatively small incremental change from the current modelling practice. CTMC represents a technical solution which, in absence of relevant data, allows for formally testing the sensitivity of results to assumptions regarding the long-term sustainability of intervention effects and improving model transparency.Conclusions The use of CTMC should be considered in evaluations where decay in effectiveness is likely to be a key factor to consider. This would enable more robust model-based evaluations of population-level programmes to promote behaviour change and reduce the uncertainty surrounding the decision to invest in these public health interventions.

Behavior Change Interventions for Health Promotion in Physical Therapist Research and Practice: An Integrative Approach.

There is an increasing focus on health promotion in physical therapist research and practice. A clinical model (Health-Focused Physical Therapy Model) was developed for identifying major steps in the delivery of health promotion focusing on adoption of healthy lifestyle behaviors. One of the primary steps within this model is the design and delivery of behavior change interventions. Such interventions involve coordinated sets of activities that target change in a specific pattern of unhealthy behavior (eg, physical inactivity, smoking). This Perspective contends that the science and practice of behavior change interventions can be significantly advanced in the field of physical therapy (implementation science) through the integration of behavior change frameworks and techniques within the context of an experimental medicine approach for health behavior change. This perspective presents the integration of the Theoretical Domains Framework, the Behavior Change Wheel, including the Capability Opportunity Motivation-Behavior core system, and the Behavior Change Technique Taxonomy as a comprehensive approach for designing and delivering behavior change interventions in physical therapy. An experimental medicine approach is described, outlining a 4-step process in the design, delivery, and evaluation of behavior change interventions that can be applied to health promotion in physical therapist research and practice. The proposed integrative approach can advance public health and health promotion through healthy lifestyle behavior change in the field of physical therapy.

Reducing Peak Energy Demand among Residents Who Are Not Billed for Their Electricity Consumption: Experimental Evaluation of Behaviour Change Interventions in a University Setting.

Behaviour change interventions aiming to reduce household energy consumption are regarded as an effective means to address disparities between demand and supply and reduce emissions. Less recognised is their success in shifting consumers’ energy consumption from peak demand periods to off-peak times of the day. This study reports two experiments that test the effect of feedback and reminder notifications on energy consumption in university halls-of-residence. A quasi-experiment and a randomised controlled experiment were conducted with residential students to evaluate behaviour change interventions aimed at reducing daily peak and critical peak demand, respectively. The results of Experiment One (n = 143) demonstrated significant reductions in the energy use of the treatment group relative to the control. On average, the treatment group’s energy use was 12.4 per cent lower than their pre-intervention baseline. In Experiment Two (n = 88), normative elements of the intervention were supplemented with a reminder notification prior to the onset of the simulated critical peak demand period. The results showed that, relative to the control condition, the 8-h notification reduced demand by 20% on average with a 12% decrease for the 24-h notification (with 2-h follow-up). These results indicate that peak energy issues can be alleviated using low-cost and easily implemented behaviour change strategies.

Changing Health-Related Behaviors 3: Lessons from Implementation Science.

Health-related behavior change refers to a body of behavior change strategies that aim to align people's behavior with advances in evidence-based knowledge and decision-making. However, human behavior is complex, and changing it often requires a combination of strategies to be effective. The challenge is in choosing the combination of strategies that will work best. Implementation science, the study of behavior change, has rapidly expanded in recent years and has pioneered work in providing more transparent and theory-based methods for choosing and evaluating behavior change strategies. There are several models and frameworks that underlie the science of implementation, the most recent and comprehensive of which include the Implementation of Change Model, the COM-B (capability, motivation, and behavior) Model, and the Theoretical Domains Framework, as well as the behavior change techniques (BCTs) taxonomy. These models and frameworks can be applied to help support the development and evaluation of behavior change interventions. In this chapter, we will review the latest advances and lessons learned from implementation science as it applies to health-related behavior change.

Challenges in the impact evaluation of behaviour change interventions: The case of sea turtle meat and eggs in São Tomé

AbstractRobust impact evaluations are needed for conservation to learn and grow as a field. Currently we lack a large body of evidence on the effects of behaviour change interventions in social‐ecological systems. By uncovering mechanistic relationships and establishing causality we can refine future programmes to enhance likelihood of effectiveness. Although a range of sophisticated methodological approaches to evaluation have been developed, conceptually linking project outcomes with conservation impacts remains difficult in complex systems.For example, sea turtles are one taxon in which unsustainable harvesting has been a particular problem. There have been a number of campaigns to reduce demand for sea turtle products, but we still have little evidence documenting their outcomes. We conducted the first formal impact evaluation of a conservation marketing campaign aimed at reducing the consumption of sea turtle meat and eggs. The campaign took place on the island of São Tomé, Central Africa, and included traditional mass media advertisements as well as community events. This is one of few demand reduction evaluations that has assessed both human behaviour and biological conservation outcomes. It benefited from an advantageous setting for evaluation, as nesting sea turtles are relatively easy to monitor and the island's small size and geographic isolation increased the detectability of potentially confounding factors. We found a decrease in self‐reported sea turtle egg consumption and a decrease in poaching of adult sea turtles.However, multiple unforeseen difficulties arose which complicated attempts at causal attribution. We were hampered by spatial spillovers, design effects from the sensitive questioning technique, concurring law enforcement and changes in biological monitoring effort. These challenges highlight the difficulties faced by practitioners seeking to apply impact evaluations in the field. We reflect on what this means for future impact evaluations of behaviour change interventions in conservation. Our recommendations include combining multiple outcome measures to triangulate hard‐to‐measure behaviours and theory‐based evaluation methods to explore causal impacts.A freePlain Language Summarycan be found within the Supporting Information of this article.

The use of theory in the development and evaluation of behaviour change interventions to improve antimicrobial prescribing: a systematic review.

This systematic review (SR) reviews the evidence on use of theory in developing and evaluating behaviour change interventions (BCIs) to improve clinicians' antimicrobial prescribing (AP). The SR protocol was registered with PROSPERO. Eleven databases were searched from inception to October 2018 for peer-reviewed, English-language, primary literature in any healthcare setting and for any medical condition. This included research on changing behavioural intentions (e.g. in simulated scenarios) and research measuring actual AP. All study designs/methodologies were included. Excluded were: grey literature and/or those which did not state a theory. Two reviewers independently extracted and quality assessed the data. The Theory Coding Scheme (TCS) evaluated the extent of the use of theory. Searches found 4227 potentially relevant papers after removal of duplicates. Screening of titles/abstracts led to dual assessment of 38 full-text papers. Ten (five quantitative, three qualitative and two mixed-methods) met the inclusion criteria. Studies were conducted in the UK (n = 8), Canada (n = 1) and Sweden (n = 1), most in primary care settings (n = 9), targeting respiratory tract infections (n = 8), and medical doctors (n = 10). The most common theories used were Theory of Planned Behaviour (n = 7), Social Cognitive Theory (n = 5) and Operant Learning Theory (n = 5). The use of theory to inform the design and choice of intervention varied, with no optimal use as recommended in the TCS. This SR is the first to investigate theoretically based BCIs around AP. Few studies were identified; most were suboptimal in theory use. There is a need to consider how theory is used and reported and the systematic use of the TCS could help.

Theoretical approaches in the development and evaluation of behaviour change interventions that improve clinicians’ antimicrobial prescribing: a systematic review

Many countries have developed antimicrobial stewardship programmes with strategies to optimise antimicrobial prescribing. There remains a need for behaviour change interventions at clinician level to promote appropriate prescribing. Theories should be used for developing and evaluating interventions to change human behaviour. Aim / Objectives:The aim of this review was to critically appraise, synthesise and present the available evidence for theoretical approaches in the development and evaluation of behaviour change interventions designed to improve clinicians' antimicrobial prescribing. Design & Methodology: The systematic review protocol was developed and registered with the International Prospective Register of Systematic Reviews (CRD42018098586). Two review authors independently extracted data and assessed study quality. Clinical and methodological heterogeneity limited data synthesis. Results The searches resulted in 4227 relevant articles after duplicates removal. Screening of titles/abstracts led to retrieval and dual assessment of 38 full-text articles. Of those, a total of 10 studies met the inclusion criteria. The majority of studies were carried out in primary care settings (n = 9) targeting upper respiratory tract infections (n = 8). Use of theory varied considerably across studies included. Theory of Planned Behaviour, Social Cognitive Theory and Operant Learning Theory were the most common theories used to inform the design and choice of interventions. Conclusion / Discussion It is feasible to develop and evaluate theoretically based interventions to improve professional practice. The findings of this systematic review will inform understanding of the theoretical basis of behaviour change interventions which contribute to contain AMR rates and prevent the world entering a “post-antibiotic era”.

Use of the Fogg Behavior Model to Assess the Impact of a Social Marketing Campaign on Condom Use in Pakistan

The Fogg Behavior Model (FBM) is a new framework which posits that behavior happens when three factors – motivation, ability, and a prompt – occur in the same moment. The FBM categorizes people into four groups based on motivation and ability and posits that those with high motivation and high ability will adopt a behavior when prompted. Two rounds of panel survey data from 617 married men in urban Pakistan were used to test this hypothesis. Multilevel mixed-effects logistic regression was used for the analysis. The results show the relationships between ability, motivation, the prompt and condom use to be as hypothesized by the FBM. After adjustment for a range of variables including fertility desires, education, and household wealth, the odds of condom use among men with high motivation and high ability were 34 times higher than the odds of condom use among men with low motivation and low ability. Moreover, the association between the prompt and condom use operated through increased motivation and ability. The FBM has potential for use in the design and evaluation of behavior change interventions in developing countries.

Measuring the impact of an entertainment‐education intervention to reduce demand for bushmeat

AbstractThe trade and consumption of bushmeat are a major threat to biodiversity across the tropics. Conservationists have traditionally advocated for stricter regulation and enforcement as a way to control these practices, with less attention given to consumers and the management of the demand. Yet, it is clear that without adequately tackling demand, it is impossible to effectively curb the bushmeat trade. In this paper, we describe an intervention to reduce demand for bushmeat in northern Tanzania. The intervention was centered around the 1‐h radio show My Wildlife – My Community which included 15‐min episodes of the radio drama Temboni. Each episode of the radio drama was accompanied by a 45‐min interactive call‐in show featuring interviews with experts and local information about available community resources. We evaluated this intervention using a Before‐After‐Control‐Impact framework based on longitudinal data from 168 respondents. To account for the fact that respondents volunteered to be exposed to the intervention, in this case the radio show, we used a matching algorithm together with regression to ensure that we could build a credible counterfactual group. Our analysis did not uncover any differences in outcomes between the treatment and control groups, and thus no evidence of the intervention achieving its initial goals. One potential causal mechanism that could have led to this outcome is the low audience penetration rate. Fewer than 40% of respondents listened to the show and among those who did, only about 20% listened to five of more episodes. This research highlights the challenges of implementing and evaluating interventions delivered through mass media in developing countries, and the importance of reporting on interventions even when there is no evidence that they achieved their initial goals. Only through robust evaluation of behavior change interventions and the sharing of lessons learned can conservationists successfully tackle complex issues such as the bushmeat trade.

Bayesian evaluation of behavior change interventions: a brief introduction and a practical example

ABSTRACTIntroductionEvaluating effects of behavior change interventions is a central interest in health psychology and behavioral medicine. Researchers in these fields routinely use frequentist statistical methods to evaluate the extent to which these interventions impact behavior and the hypothesized mediating processes in the population. However, calls to move beyond the exclusive use of frequentist reasoning are now widespread in psychology and allied fields. We suggest adding Bayesian statistical methods to the researcher’s toolbox of statistical methods.ObjectivesWe first present the basic principles of the Bayesian approach to statistics and why they are useful for researchers in health psychology. We then provide a practical example on how to evaluate intervention effects using Bayesian methods, with a focus on Bayesian hierarchical modeling. We provide the necessary materials for introductory-level readers to follow the tutorial.Conclusion:Bayesian analytical methods are now available to researchers through easy-to-use software packages, and we recommend using them to evaluate the effectiveness of interventions for their conceptual and practical benefits.

From Theory-Inspired to Theory-Based Interventions: A Protocol for Developing and Testing a Methodology for Linking Behaviour Change Techniques to Theoretical Mechanisms of Action.

BackgroundUnderstanding links between behaviour change techniques (BCTs) and mechanisms of action (the processes through which they affect behaviour) helps inform the systematic development of behaviour change interventions.PurposeThis research aims to develop and test a methodology for linking BCTs to their mechanisms of action.MethodsStudy 1 (published explicit links): Hypothesised links between 93 BCTs (from the 93-item BCT taxonomy, BCTTv1) and mechanisms of action will be identified from published interventions and their frequency, explicitness and precision documented. Study 2 (expert-agreed explicit links): Behaviour change experts will identify links between 61 BCTs and 26 mechanisms of action in a formal consensus study. Study 3 (integrated matrix of explicit links): Agreement between studies 1 and 2 will be evaluated and a new group of experts will discuss discrepancies. An integrated matrix of BCT-mechanism of action links, annotated to indicate strength of evidence, will be generated. Study 4 (published implicit links): To determine whether groups of co-occurring BCTs can be linked to theories, we will identify groups of BCTs that are used together from the study 1 literature. A consensus exercise will be used to rate strength of links between groups of BCT and theories.ConclusionsA formal methodology for linking BCTs to their hypothesised mechanisms of action can contribute to the development and evaluation of behaviour change interventions. This research is a step towards developing a behaviour change ‘ontology’, specifying relations between BCTs, mechanisms of action, modes of delivery, populations, settings and types of behaviour.

Uptake of behavior change techniques - a key focus for process analysis and for intervention delivery: a comment on Hankonen et al.

“There’s many a slip twixt cup and lip.” In interventions to change health behavior, even the most carefully crafted interventions can be undermined by a lack of fidelity in intervention delivery [1], or by a lack of ‘enactment’ (the degree to which participants engage with and use the intended behavior change techniques) [2]. The article by Hankonen and colleagues in this issue [3] describes a novel method for exploring the mechanisms of change in behavioral interventions. The authors measured the level of enactment of behavior change techniques by 210 participants in the intervention arm of a lifestyle intervention for people with newly diagnosed type 2 diabetes (the ADDITION-Plus trial). They found that increased use of the targeted behavior change techniques was associated with an increase in weight loss. Although the intervention overall did not generate weight loss, individuals who reported using all 16 of the intervention’s intended behavior change techniques lost significantly more weight than those who used 10 or less. This suggests that the intervention model and selected behavior change strategies may have been valid (when the techniques were used, change occurred), but that the lack of overall weight loss may have stemmed from suboptimal promotion of the use of these strategies (participants were not inspired to use the techniques suggested). The picture is limited to some extent by the sensitivity and precision of the measures used for enactment and for dietary and physical activity behaviors. However, the analyses suggest that some specific behavior change techniques were associated with changes in diet and physical activity. A particularly interesting aspect of this type of process analysis is that it prompts us to consider the use of behavior change techniques as a behavioral target in itself. This introduces a ‘second order’ question to the field—how can we increase the uptake and use of behavior change techniques? What ‘meta behavior change techniques’ (MBCTs) or intervention-delivery techniques (IDTs) are effective in motivating, supporting, and maintaining the use of the BCTs targeted by the intervention? For instance, to prompt selfmonitoring of physical activity, is it sufficient to simply give people a pedometer and some instructions? Can we use existing techniques, such as ‘prompting practice’ or encouraging social support (e.g., asking partners to remind or encourage the participant to use the pedometer)? Or, do we need novel techniques to promote the uptake and maintenance of BCTs (e.g., explaining the process of behavior change [4]; providing evidence on the link between use of the technique and successful behavior change)? Hakonen et al.’s article demonstrates that enactment-based process evaluation can add considerable explanatory value to the evaluation of behavior change interventions. It also prompts deeper thinking about how we can best promote the uptake and sustained use of behavior change techniques. This is a major contribution to the field.

Methods of Measurement in epidemiology: Sedentary Behaviour

Research examining sedentary behaviour as a potentially independent risk factor for chronic disease morbidity and mortality has expanded rapidly in recent years. We present a narrative overview of the sedentary behaviour measurement literature. Subjective and objective methods of measuring sedentary behaviour suitable for use in population-based research with children and adults are examined. The validity and reliability of each method is considered, gaps in the literature specific to each method identified and potential future directions discussed. To date, subjective approaches to sedentary behaviour measurement, e.g. questionnaires, have focused predominantly on TV viewing or other screen-based behaviours. Typically, such measures demonstrate moderate reliability but slight to moderate validity. Accelerometry is increasingly being used for sedentary behaviour assessments; this approach overcomes some of the limitations of subjective methods, but detection of specific postures and postural changes by this method is somewhat limited. Instruments developed specifically for the assessment of body posture have demonstrated good reliability and validity in the limited research conducted to date. Miniaturization of monitoring devices, interoperability between measurement and communication technologies and advanced analytical approaches are potential avenues for future developments in this field. High-quality measurement is essential in all elements of sedentary behaviour epidemiology, from determining associations with health outcomes to the development and evaluation of behaviour change interventions. Sedentary behaviour measurement remains relatively under-developed, although new instruments, both objective and subjective, show considerable promise and warrant further testing.

Classification systems in behavioural science: current systems and lessons from the natural, medical and social sciences

Background: Specifying individual behaviour change techniques (BCTs) is crucial for better development and evaluation of behaviour change interventions. Classification of BCTs will help this process and can be informed by classification systems in the natural, medical and social sciences. Method: A search of the classification literature in the natural, medical and social sciences produced a framework within which to consider a systematic search of classification systems of BCTs in the behaviour change literature. Results: Six distinct types of classification system from other scientific disciplines were identified: nomenclatures, ordered sets, hierarchical, matrices, faceted and social categorisations. Eight classification systems of BCTs were identified, none of which had a formal, hierarchical structure. Most were developed for specific behaviours, although one was general. Discussion: Developing a hierarchical structure, similar to those used in other scientific disciplines, would enable better communication and understanding of BCTs and inform the development and evaluation of interventions. Hierarchical structured classification systems contain many of the characteristics most desirable in a classification of BCTs.

Looking Back, Looking Forward

As 2012 draws to an end, we are excited by the fact that the busyness that we've seen here publishing this issue will soon be accompanied by a sense of deep joy. Not many have the privilege of knowing that the work they do can help and inspire those with similar passions, and we consider ourselves especially fortunate to contribute to a community of likeminded people. Finally, Issue 4 of Volume 18 is now officially published, ready to be read. Whether it be an academic journal or a novel, we all have different ways of approaching a text. Some start with the table of contents, while others jump straight ahead to the parts that interest them. I personally enjoy reading a text by reading the preface first. I have always felt that only when I read the preface do I get to see the big picture of the text-what the author is trying to do and how he or she is planning to go about doing it. In a journal like ours, the editorial works like the preface, so I feel obligated to give a short introduction to the articles presented here. This issue consists of eight articles-two reviews and six original research papers-that we hope will help you promote awareness of healthcare informatics as well as advance knowledge and application systems in healthcare fields. Two articles deal with clinical research support systems and what they have taught us about expert systems for diagnosis and sentence classifications. One article deals with bioinformatics, especially how to design and integrate a compact gene knowledge database. The remaining five, though touching upon a variety of topics in healthcare information systems, can be said to be articles on social factors, policies, and behavioral approaches; specifically, they concern topics such as the mobile environment, u-Health, organizational and individual barriers to information systems, user preference to monitors, and human factors in engineering. The collection of topics here is only one example of the gradual rise in interest in social factors, policy, and behavioral informatics. This trend is not only a consequence of recent focus on behavioral approaches (such as behavioral economics and behavioral politics) but is also an indicator of the growing importance of health attitude and behavior and environmental factors in one's health. Now more than ever, people across the disciplines are realizing that behavior is a key entity in problem solving. User behavior in healthcare informatics plays an important role in promoting the appropriate use of information technologies in order to improve health and healthcare. Clearly, there is a growing need for researchers who specialize in the use of technologies by patients and healthcare providers and in the design, implementation, and evaluation of behavior change interventions delivered through advanced technologies. We are glad to know that our journal is an attempt to address this need and its implications. This issue is yet another step in the right direction. It has been three years since we transformed the Journal of Korean Society of Medical Informatics (JKOSMI) into Healthcare Informatics Research (HIR), and a lot has happened since then. In its first year, 2010, it was indexed in the National Library of Medicine (NLM) Catalog; in its second year, in PubMed Central; and this year, we finished our application for SCOPUS. We're also happy to share that this year, HIR was recognized as the best academic journal in Korea by The Korean Federation of Science and Technology Societies. Now, our next goal is to apply for Science Citation Index (SCI) next year. We look back and feel pride in our growth in the last three years, and we look forward to growing even further in the next three. These achievements would not have been possible without you. As a reader and as a member of KOSMI, you are not a mere witness to this growth but a participant in it, and we hope that you feel as proud as we do in how far we've come. We also hope that you join us in our next step. To become an SCI journal, we need more high-quality articles and more diversity in our contributors. You can help by contributing your own work and helping us publicize at home and abroad. It is our hope that next year, when we look back on 2013, we can take joy not only in what we've achieved but also in how we achieved it together. May your 2013 be filled with joys for you and your family.