Behavior change interventions: the potential of ontologies for advancing science and practice

An ontology of mechanisms of action in behaviour change interventions

Background

Behaviour change interventions influence behaviour through causal processes called "mechanisms of action" (MoAs). Reports of such interventions and their evaluations often use inconsistent or ambiguous terminology, creating problems for searching, evidence synthesis and theory development. This inconsistency includes the reporting of MoAs. An ontology can help address these challenges by serving as a classification system that labels and defines MoAs and their relationships. The aim of this study was to develop an ontology of MoAs of behaviour change interventions.

Methods

To develop the MoA Ontology, we (1) defined the ontology's scope; (2) identified, labelled and defined the ontology's entities; (3) refined the ontology by annotating (i.e., coding) MoAs in intervention reports; (4) refined the ontology via stakeholder review of the ontology's comprehensiveness and clarity; (5) tested whether researchers could reliably apply the ontology to annotate MoAs in intervention evaluation reports; (6) refined the relationships between entities; (7) reviewed the alignment of the MoA Ontology with other relevant ontologies, (8) reviewed the ontology's alignment with the Theories and Techniques Tool; and (9) published a machine-readable version of the ontology.

Results

An MoA was defined as "a process that is causally active in the relationship between a behaviour change intervention scenario and its outcome behaviour". We created an initial MoA Ontology with 261 entities through Steps 2-5. Inter-rater reliability for annotating study reports using these entities was α=0.68 ("acceptable") for researchers familiar with the ontology and α=0.47 for researchers unfamiliar with it. As a result of additional revisions (Steps 6-8), 23 further entities were added to the ontology resulting in 284 entities organised in seven hierarchical levels.

Conclusions

The MoA Ontology extensively captures MoAs of behaviour change interventions. The ontology can serve as a controlled vocabulary for MoAs to consistently describe and synthesise evidence about MoAs across diverse sources.

The Digital Therapeutics Real-World Evidence Framework: An Approach for Guiding Evidence-Based Digital Therapeutics Design, Development, Testing, and Monitoring

Digital therapeutics (DTx) are a promising way to provide safe, effective, accessible, sustainable, scalable, and equitable approaches to advance individual and population health. However, developing and deploying DTx is inherently complex in that DTx includes multiple interacting components, such as tools to support activities like medication adherence, health behavior goal-setting or self-monitoring, and algorithms that adapt the provision of these according to individual needs that may change over time. While myriad frameworks exist for different phases of DTx development, no single framework exists to guide evidence production for DTx across its full life cycle, from initial DTx development to long-term use. To fill this gap, we propose the DTx real-world evidence (RWE) framework as a pragmatic, iterative, milestone-driven approach for developing DTx. The DTx RWE framework is derived from the 4-phase development model used for behavioral interventions, but it includes key adaptations that are specific to the unique characteristics of DTx. To ensure the highest level of fidelity to the needs of users, the framework also incorporates real-world data (RWD) across the entire life cycle of DTx development and use. The DTx RWE framework is intended for any group interested in developing and deploying DTx in real-world contexts, including those in industry, health care, public health, and academia. Moreover, entities that fund research that supports the development of DTx and agencies that regulate DTx might find the DTx RWE framework useful as they endeavor to improve how DTxcan advance individual and population health.

Getting More Out of Clinical Documentation: Can Clinical Dashboards Yield Clinically Useful Information?

This study investigated coded data retrieved from clinical dashboards, which are decision-support tools that include a graphical display of clinical progress and clinical activities. Data were extracted from clinical dashboards representing 256 youth (M age = 11.9) from 128 practitioners who were trained in the Managing and Adapting Practice (MAP) system (Chorpita & Daleiden in BF Chorpita EL Daleiden 2014 Structuring the collaboration of science and service in pursuit of a shared vision. 43(2):323 338. 2014, Chorpita & Daleiden in BF Chorpita EL Daleiden 2018 Coordinated strategic action: Aspiring to wisdom in mental health service systems. 25(4):e12264. 2018) in 55 agencies across 5 regional mental health systems. Practitioners labeled up to 35 fields (i.e., descriptions of clinical activities), with the options of drawing from a controlled vocabulary or writing in a client-specific activity. Practitioners then noted when certain activities occurred during the episode of care. Fields from the extracted data were coded and reliability was assessed for Field Type, Practice Element Type, Target Area, and Audience (e.g., Caregiver Psychoeducation: Anxiety would be coded as Field Type = Practice Element; Practice Element Type = Psychoeducation; Target Area = Anxiety; Audience = Caregiver). Coders demonstrated moderate to almost perfect interrater reliability. On average, practitioners recorded two activities per session, and clients had 10 unique activities across all their sessions. Results from multilevel models showed that clinical activity characteristics and sessions accounted for the most variance in the occurrence, recurrence, and co-occurrence of clinical activities, with relatively less variance accounted for by practitioners, clients, and regional systems. Findings are consistent with patterns of practice reported in other studies and suggest that clinical dashboards may be a useful source of clinical information. More generally, the use of a controlled vocabulary for clinical activities appears to increase the retrievability and actionability of healthcare information and thus sets the stage for advancing the utility of clinical documentation.

Toward Efficient, Sustainable, and Scalable Methods of Treatment Characterization: An Investigation of Coding Clinical Practice from Chart Notes

PURPOSE

Chart notes provide a low-cost data source that could help characterize what occurs in treatment with sufficient precision to improve management of care. This study assessed the interrater reliability of treatment content coded from chart notes and evaluated its concordance with content coded from transcribed treatment sessions.

METHOD

Fifty randomly selected and digitally recorded treatment events were transcribed and coded for practice content. Independent coders then applied the same code system to chart notes for these same treatment events.

ANALYSIS

We measured reliability and concordance of practice occurrence and extensiveness at two levels of specificity: practices (full procedures) and steps (subcomponents of those procedures).

RESULTS

For chart notes, practices had moderate interrater reliability (M k = 0.50, M ICC = 0.56) and steps had moderate (M ICC = 0.74) to substantial interrater reliability (M k = 0.78). On average, 2.54 practices and 5.64 steps were coded per chart note and 4.53 practices and 13.10 steps per transcript. Across sources, ratings for 64% of practices and 41% of steps correlated significantly, with those with significant correlations generally demonstrating moderate concordance (practice M r = 0.48; step M r = 0.47). Forty one percent of practices and 34% of steps from transcripts were also identified in the corresponding chart notes.

CONCLUSION

Chart notes provide an accessible data source for evaluating treatment content, with different levels of specificity posing tradeoffs for validity and reliability, which in turn may have implications for chart note interfaces, training, and new metrics to support accurate, reliable, and efficient measurement of clinical practice.

Specifying how intervention content is communicated: Development of a Style of Delivery Ontology

Background: Investigating and enhancing the effectiveness of behaviour change interventions requires detailed and consistent specification of all aspects of interventions. We need to understand not only their content, that is the specific techniques, but also the source, mode, schedule, and style in which this content is delivered. Delivery style refers to the manner by which content is communicated to intervention participants. This paper reports the development of an ontology for specifying the style of delivery of interventions that depend on communication. This forms part of the Behaviour Change Intervention Ontology, which aims to cover all aspects of behaviour change intervention scenarios. Methods: The Style of Delivery Ontology was developed following methods for ontology development used in the Human Behaviour-Change Project, with seven key steps: 1) defining the scope of the ontology, 2) identifying key entities and developing their preliminary definitions by reviewing 100 behaviour change intervention evaluation reports and existing classification systems, 3) refining the ontology by piloting the ontology through annotations of 100 reports, 4) stakeholder review by eight behavioural science and public health experts, 5) inter-rater reliability testing through annotating 100 reports using the ontology, 6) specifying ontological relationships between entities, and 7) disseminating and maintaining the ontology. Results: The resulting ontology is a five-level hierarchical structure comprising 145 unique entities relevant to style of delivery. Key areas include communication processes, communication styles, and attributes of objects used in communication processes. Inter-rater reliability for annotating intervention evaluation reports was α=0.77 (good) for those familiar with the ontology and α=0.62 (acceptable) for those unfamiliar with it. Conclusions: The Style of Delivery Ontology can be used for both annotating and describing behaviour change interventions in a consistent and coherent manner, thereby improving evidence comparison, synthesis, replication, and implementation of effective interventions.

Effectiveness of behavior change interventions for smoking cessation among expectant and new fathers: findings from a systematic review

BACKGROUND

Smoking cessation during pregnancy and the postpartum period by both women and their partners offers multiple health benefits. However, compared to pregnant/postpartum women, their partners are less likely to actively seek smoking cessation services. There is an increased recognition about the importance of tailored approaches to smoking cessation for expectant and new fathers. While Behavior Change Interventions (BCIs) are a promising approach for smoking cessation interventions, evidence on effectiveness exclusively among expectant and new fathers are fragmented and does not allow for many firm conclusions to be drawn.

METHODS

We conducted a systematic review on effectiveness of BCIs on smoking cessation outcomes of expectant and new fathers both through individual and/or couple-based interventions. Peer reviewed articles were identified from eight databases without any date or language restriction.Two independent reviewers screened studies for relevance, assessed methodological quality of relevant studies, and extracted data from studies using a predeveloped data extraction sheet.

RESULTS

We retrieved 1222 studies, of which 39 were considered for full text screening after reviewing the titles and abstracts. An additional eight studies were identified from reviewing the reference list of review articles picked up by the databases search. A total of nine Randomised Control Trials were included in the study. Six studies targeted expectant/new fathers, two targeted couples and one primarily targeted women with an intervention component to men. While the follow-up measurements for men varied across studies, the majority reported biochemically verified quit rates at 6 months. Most of the interventions showed positive effects on cessation outcomes. BCI were heterogenous across studies. Findings are suggestive of gender targeted interventions being more likely to have positive cessation outcomes.

CONCLUSIONS

This systematic review found limited evidence supporting the effectiveness of BCI among expectant and new fathers, although the majority of studies show positive effects of these interventions on smoking cessation outcomes. There remains a need for more research targeted at expectant and new fathers. Further, there is a need to identify how smoking cessation service delivery can better address the needs of (all) gender(s) during pregnancy.

Moving toward precision in prenatal evidence-based home visiting to achieve good birth outcomes: assessing the alignment of local programs with their national models

BACKGROUND

Low birthweight and preterm birth rates are higher in the United States than in other developed countries and exhibit pronounced racial inequities. Home visiting is a strategy to promote equity in birth outcomes. Research points to precision home visiting as the path to equity. The purpose of this study is to describe local programs' risk reduction priorities, intended behavioral pathways, and expectations of home visitors; compare these local program features with those of their national model; and assess the strength of implementation systems to support staff in meeting job expectations.

METHODS

We surveyed local programs implementing one of four evidence-based home visiting models that aim to promote good birth outcomes: Family Spirit, Healthy Families America, Nurse-Family Partnership, and Parents as Teachers.

RESULTS

Representatives from 169 local programs completed the survey. Overall, 59% endorsed all their model's high priority risks, 16% endorsed all its required behavioral pathways, and 11% endorsed all its required techniques. Local programs went beyond their national model's explicit intentions. Overall, 91% of local programs prioritized risks beyond those of their model, 85% endorsed behavioral pathways beyond those of their model, 95% endorsed visitors' use of techniques not explicitly endorsed by their model but compatible with it, and 19% endorsed use of techniques judged incompatible by their model. Implementation system strength was positively associated with local program and model expectations.

CONCLUSIONS

Precision home visiting to achieve health equity requires shared learning of what works best for whom. This observational study showed the Precision Paradigm's usefulness for cross-model research to advance precision.

Theoretical components of smoking cessation interventions for persons with physical disabilities: A scoping review

Rationale Persons with physical disabilities report higher cigarette smoking rates and a lower likelihood of accessing health services (e.g., smoking cessation services). Explicit and systematic application of behaviour change theory may be a promising approach to addressing these inequities and developing impactful smoking cessation interventions for persons with physical disabilities.

OBJECTIVE

This scoping review aimed to explore how behaviour change theory and intervention components have been used to design smoking cessation interventions for persons with physical disabilities.

METHODS

Electronic databases (Medline, Embase, PsycINFO, CINAHL, Web of Science) were systematically searched. Smoking cessation interventions for persons with physical disabilities were identified. Behaviour change theory and intervention components, including behaviour change techniques, intervention functions, mode of delivery, intervention source, and setting, were extracted from the included articles.

RESULTS

Among the eleven included articles, there were nine unique smoking cessation interventions for persons with physical disabilities. Three interventions mentioned theory, but none of these articles explicitly applied or tested the theory. Intervention components were consistently combined to deliver pharmacotherapy and behavioural counselling-based interventions.

CONCLUSION

The results of this review highlight the scarcity of theory-based smoking cessation interventions for persons with physical disabilities. While the interventions were not theory-based, they were evidence-based and aligned with recommendations for smoking cessation treatment (i.e., behavioural counselling plus pharmacotherapy). Future research should take a theory-based approach to intervention development to enhance the likelihood that smoking cessation interventions for persons with physical disabilities are effective, replicable, and equitable.

Measuring Children's Stress via Saliva in Surgical and Endoscopic Procedures and Its Measurement Intention in the Community: Reality-Future Prospects

(1) Background: Children who undergo surgical or endoscopic procedures display high levels of stress, and various means are applied to reduce their anxiety. Salivary cortisol (S Cortisol) and salivary alpha-amylase (SAA) are often used as a valid biomarker of stress. The primary purpose of the study was the investigation of stress levels through S Cortisol and S amylase after intervention in surgical or endoscopic procedures (gastroscopy-colonoscopy). The secondary outcomes were the investigation of the intention to adopt new methods of saliva sampling. We collected saliva samples from children subjected to invasive medical procedures, with the aim of applying the Theory of Planned Behavior (TPB) as an intervention means to provide information and education to both parents and children undergoing stressful situations, and assess its efficacy in reducing stress levels. We also aimed at acquiring a better understanding of the acceptability of noninvasive biomarker collection in community settings. (2) Methods: The sample of this prospective study comprised 81 children who underwent surgical or endoscopic procedures at the Attikon General University Hospital, Athens, Greece and 90 parents. The sample was divided into two groups. The first, 'Group Unexplained', was not provided any information or education about the procedures, while the second, 'Group Explained', was informed and educated based on TPB. Thereafter, 8-10 weeks after intervention, the Theory of Planned Behavior questions were re-completed by the 'Group Explained'. (3) Results: Significant differences were detected in cortisol and amylase values between the two groups postoperatively after applying the TPB intervention. Saliva cortisol was reduced by 8.09 ng/mL in the 'Group Explained' while in the 'Group Unexplained' it was reduced by 4.45 ng/mL (p < 0.001). Salivary amylase values decreased by 9.69 ng/mL in the 'Group Explained' after the intervention phase of the study, while in the 'Group Unexplained' they increased by 35.04 ng/mL (p < 0.001). The regression explains 40.3% (baseline) and 28.5% (follow-up) of parental intention. The predictive factor of parental intention (baseline) is attitude (p < 0.001) and follow-up is behavioral control (p < 0.028) and attitude (p < 0.001). (4) Conclusions: Providing proper education and information for parents has a positive effect on reducing children's stress levels. Changing parental attitudes towards saliva collection plays the most important role, since a positive attitude can influence intention and ultimately participation in these procedures.

Toward an ontology of identity-related constructs in addiction, with examples from nicotine and tobacco research

BACKGROUND AND AIMS

We aimed to create a basic set of definitions and relationships for identity-related constructs, as part of the Addiction Ontology and E-Cigarette Ontology projects, that could be used by researchers with diverse theoretical positions and so facilitate evidence synthesis and interoperability.

METHODS

We reviewed the use of identity-related constructs in psychological and social sciences and how these have been applied to addiction with a focus on nicotine and tobacco research. We, then, used an iterative process of adaptation and review to arrive at a basic set of identity-related classes with labels, definitions and relationships that could provide a common framework for research.

RESULTS

We propose that 'identity' be used to refer to 'a cognitive representation by a person or group of themselves', with 'self-identity' referring to an individual's identity and 'group identity' referring to an identity held by a social group. Identities can then be classified at any level of granularity based on the content of the representations (e.g. 'tobacco smoker identity', 'cigarette smoker identity' and 'vaper identity'). We propose distinguishing identity from 'self-appraisal' to capture the distinction between the representation of oneself (e.g. as an 'ex-smoker') and (i) the importance and (ii) the positive or negative evaluation that we attach to what is represented. We label an identity that is appraised as enduring as a 'core identity', related to 'strong identity' because of the appraisal as important. Identities that are appraised positively or negatively involve 'positive self-appraisal' and 'negative self-appraisal' respectively. This allows us to create 'logically defined classes' of identity by combining them (e.g. 'positive core cigarette smoker identity' to refer to a cigarette smoker self-identity that is both positive and important). We refer to the totality of self-identities of a person as a 'composite self-identity'.

CONCLUSIONS

An ontology of identity constructs may assist in improving clarity when discussing theories and evidence relating to this construct in addiction research.

Future Directions in Youth and Family Treatment Engagement: Finishing the Bridge Between Science and Service

The field has spent more than 50 years investing in the quality of youth mental healthcare, with intervention science yielding roughly 1,300 efficacious treatments. In the latter half of this period, concurrent efforts in implementation science have developed effective methods for supporting front-line service organizations and therapists to begin to bridge the science to service gap. However, many youths and families still do not benefit fully from these strategic investments due to low treatment engagement: nearly half of youths in need of services pursue them, and among those who do, roughly another half terminate prematurely. The negative impact of low engagement is substantial, and is disproportionally and inequitably so for many. We contend that to build a robust and "finished" bridge connecting science and service, the field must go beyond its two historical foci of designing interventions and preparing therapists to deliver them, to include an intentional focus on the youths and families who participate in these interventions and who work with those therapists. In this paper, we highlight the significance of treatment engagement in youth mental healthcare and discuss the current state of the literature related to four priorities: conceptualization, theory, measurement, and interventions. Next, we offer an example from our own program of research as one illustration for advancing these priorities. Finally, we propose recommendations to act on these priorities.

Use of behavioural change taxonomies in systematic reviews and meta-analyses regarding obesity management

We investigated the prevalence of behavioural change taxonomies in systematic reviews and meta-analyses related to obesity management. In addition, we analysed the funding sources, author conflicts of interest statements, risk of bias, and favorability of the results in such studies to determine if there was a relationship between methodological quality and taxonomy use. We searched several databases including MEDLINE, Epistemonikos, Cochrane EDSR, Pubmed and Embase for systematic reviews and meta-analyses regarding the behavioural treatment of obesity. Screening and data extraction was performed in a masked, duplicate fashion. We performed statistical analyses to determine any significant association between use of taxonomy and study characteristics. Fifteen (of 186; 8.06%) systematic reviews used a taxonomy-nine used the BCTTv1, three used OXFAB, two used the CALO-RE and one used "Taxonomy of choice architecture techniques." Most interventions that referenced a taxonomy were self-mediated (6/60, 10%). Behavioural change taxonomies were mentioned in 10 (of 87, 11.49%) studies with a public funding source. Of the studies with favourable results, 14 studies (of 181, 7.73%) referred to a taxonomy. We found no statistically significant relationships between use of taxonomy and study characteristics. We found that systematic reviews regarding the management of obesity rarely mention a behavioural change taxonomy. Given the global burden of obesity, it is crucial that behavioural change techniques are reproducible and translatable. We recommend that researchers look further into how taxonomies affect the quality and reproducibility of behavioural interventions in an effort to improve patient outcomes.

Towards a dispositionalist (and unifying) account of addiction

Addiction theorists have often utilized the metaphor of the blind men and the elephant to illustrate the complex nature of addiction and the varied methodological approaches to studying it. A common purported upshot is skeptical in nature: due to these complexities, it is not possible to offer a unifying account of addiction. I think that this is a mistake. The elephant is real-there is a there there. Here, I defend a dispositionalist account of addiction as the systematic disposition to fail to control one's desires to engage in certain types of behaviors. I explain this position, defend the inclusion of desires and impaired control, and flesh out the notion of systematicity central to my account. I then illustrate how my dispositionalist framework can unify the disparate and seemingly incompatible accounts of addiction (and their respective methodological approaches). I close with a brief plan to extend and implement my account.

Towards more personalized digital health interventions: a clustering method of action and coping plans to promote physical activity

BACKGROUND

Despite effectiveness of action and coping planning in digital health interventions to promote physical activity (PA), attrition rates remain high. Indeed, support to make plans is often abstract and similar for each individual. Nevertheless, people are different, and context varies. Tailored support at the content level, involving suggestions of specific plans that are personalized to the individual, may reduce attrition and improve outcomes in digital health interventions. The aim of this study was to investigate whether user information relates toward specific action and coping plans using a clustering method. In doing so, we demonstrate how knowledge can be acquired in order to develop a knowledge-base, which might provide personalized suggestions in a later phase.

METHODS

To establish proof-of-concept for this approach, data of 65 healthy adults, including 222 action plans and 204 coping plans, were used and were collected as part of the digital health intervention MyPlan 2.0 to promote PA. As a first step, clusters of action plans, clusters of coping plans and clusters of combinations of action plans and barriers of coping plans were identified using hierarchical clustering. As a second step, relations with user information (i.e. gender, motivational stage, ...) were examined using anova's and chi²-tests.

RESULTS

First, three clusters of action plans, eight clusters of coping plans and eight clusters of the combination of action and coping plans were identified. Second, relating these clusters to user information was possible for action plans: 1) Users with a higher BMI related more to outdoor leisure activities (F = 13.40, P < .001), 2) Women, users that didn't perform PA regularly yet, or users with a job related more to household activities (X² = 16.92, P < .001; X² = 20.34, P < .001; X² = 10.79, P = .004; respectively), 3) Younger users related more to active transport and different sports activities (F = 14.40, P < .001). However, relating clusters to user information proved difficult for the coping plans and combination of action and coping plans.

CONCLUSIONS

The approach used in this study might be a feasible approach to acquire input for a knowledge-base, however more data (i.e. contextual and dynamic user information) from possible end users should be acquired in future research. This might result in a first type of context-aware personalized suggestions on the content level.

TRIAL REGISTRATION

The digital health intervention MyPlan 2.0 was preregistered as a clinical trial (ID:NCT03274271). Release date: 6-September-2017.

Informing the development of an outcome set and banks of items to measure mobility among individuals with acquired brain injury using natural language processing

BACKGROUND

The sheer number of measures evaluating mobility and inconsistencies in terminology make it challenging to extract potential core domains and items. Automating a portion of the data synthesis would allow us to cover a much larger volume of studies and databases in a smaller fraction of the time compared to the usual process. Thus, the objective of this study was to identify a comprehensive outcome set and develop preliminary banks of items of mobility among individuals with acquired brain injury (ABI) using Natural Language Processing (NLP).

METHODS

An umbrella review of 47 reviews evaluating the content of mobility measures among individuals with ABI was conducted. A search was performed on 5 databases between 2000 and 2020. Two independent reviewers retrieved copies of the measures and extracted mobility domains and items. A pre-trained BERT model (state-of-the-art model for NLP) provided vector representations for each sentence. Using the International Classification of Functioning, Disability, and Health Framework (ICF) ontology as a guide for clustering, a k-means algorithm was used to retrieve clusters of similar sentences from their embeddings. The resulting embedding clusters were evaluated using the Silhouette score and fine-tuned according to expert input.

RESULTS

The study identified 246 mobility measures, including 474 domains and 2109 items. Encoding the clusters using the ICF ontology and expert knowledge helped in regrouping the items in a way that is more closely related to mobility terminology. Our best results identified banks of items that were used to create a 24 comprehensive outcome sets of mobility, including Upper Extremity Mobility, Emotional Function, Balance, Motor Control, Self-care, Social Life and Relationships, Cognition, Walking, Postural Transition, Recreation, and Leisure Activities, Activities of Daily Living, Physical Functioning, Communication, Work/Study, Climbing, Sensory Functions, General Health, Fatigue, Functional Independence, Pain, Alcohol and Drugs Use, Transportation, Sleeping, and Finances.

CONCLUSION

The banks of items of mobility domains represent a first step toward establishing a comprehensive outcome set and a common language of mobility to develop the ontology. It enables researchers and healthcare professionals to begin exposing the content of mobility measures as a way to assess mobility comprehensively.

Using Virtual Choreographies to Identify Office Users’ Behaviors to Target Behavior Change Based on Their Potential to Impact Energy Consumption

Reducing office buildings’ energy consumption can contribute significantly towards carbon reduction commitments since it represents ∼40% of total energy consumption. Major components of this are lighting, electrical equipment, heating, and central cooling systems. Solid evidence demonstrates that individual occupants’ behaviors impact these energy consumption components. In this work, we propose the methodology of using virtual choreographies to identify and prioritize behavior-change interventions for office users based on the potential impact of specific behaviors on energy consumption. We studied the energy-related office behaviors of individuals by combining three sources of data: direct observations, electricity meters, and computer logs. Data show that there are behaviors with significant consumption impact but with little potential for behavioral change, while other behaviors have substantial potential for lowering energy consumption via behavioral change.

Motivating Machines: The Potential of Modeling Motivation as MoA for Behavior Change Systems

The pathway through which behavior change techniques have an effect on the behavior of an individual is referred to as the Mechanism of Action (MoA). Digitally enabled behavior change interventions could potentially benefit from explicitly modelling the MoA to achieve more effective, adaptive, and personalized interventions. For example, if ‘motivation’ is proposed as the targeted construct in any behavior change intervention, how can a model of this construct be used to act as a mechanism of action, mediating the intervention effect using various behavior change techniques? This article discusses a computational model for motivation based on the neural reward pathway with the aim to make it act as a mediator between behavior change techniques and target behavior. This model’s formal description and parametrization are described from a neurocomputational sciences prospect and elaborated with the help of a sub-question, i.e., what parameters/processes of the model are crucial for the generation and maintenance of motivation. An intervention scenario is simulated to show how an explicit model of ‘motivation’ and its parameters can be used to achieve personalization and adaptivity. A computational representation of motivation as a mechanism of action may also further advance the design, evaluation, and effectiveness of personalized and adaptive digital behavior change interventions.

The search for scientific meaning in mindfulness research: Insights from a scoping review

There are on-going debates about what is and is not 'mindfulness'. These debates are stifling rigorous academic research as scientific precision is a precursor to shared meaning. While mindfulness is a growing field of research, these divergent and conflated meanings are limiting deeper interdisciplinary research. Interventions designed in one practice context may not be useful in other contexts because meaning is not transferred between settings. This review clarifies the various research domains that study mindfulness and the conceptual and operational definitions in each domain. This two-stage study comprises a scoping review of mindfulness classifications and a comparative content mapping of mindfulness studies from 2015 to 2021. The initial comprehensive search strategy followed the preferred reporting items for scoping reviews and meta-analysis (PRISMA) method. The comparative analysis was conducted using Leximancer. Findings illustrate a complex growing research corpus on mindfulness that is somewhat confused. The results from the scoping review show three shared domains in mindfulness classifications: short-term effects of mindfulness, long-term effects of mindfulness, and mindfulness practices. The results from the content mapping show four domains of mindfulness research: mental health, behavioural change, cognitive neuroscience, and ethical mindfulness. Operational definitions of mindfulness are not articulated clearly in these domains. Conceptual and operational definitions in the 'ethical mindfulness' domain are not yet developed. To enhance scientific progress in mindfulness research, further investigations of mindfulness classifications need to be developed. Content mapping and semantic typology is a potential candidate for future classification. More attention should be paid to developing operational definitions according to specific research domains. Scholars in the ethical mindfulness domain will need solid conceptual and operational definitions to support their research efforts.

Establishing the Medical Actionability of Genomic Variants

Actionability is an important concept in medicine that does not have a well-accepted standard definition, nor is there a general consensus on how to establish it. Medical actionability is often conflated with clinical utility, a related but distinct concept. This lack of clarity contributes to practice variation and inconsistent coverage decisions in genomic medicine, leading to the potential for systematic bias in the use of evidence-based interventions. We clarify how medical actionability and clinical utility are distinct and then discuss the spectrum of actionability, including benefits for the person, the family, and society. We also describe applications across the life course, including prediction, diagnosis, and treatment. Current challenges in assessing the medical actionability of identified genomic variants include gaps in the evidence, limited contexts with practice guidelines, and subjective aspects of medical actionability. A standardized and authoritative assessment of medical actionability is critical to implementing genomic medicine in a fashion that improves population health outcomes and reduces health disparities. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Accumulating Knowledge in the Organizational Sciences

In some fields, research findings are rigorously curated in a common language and made available to enable future use and large-scale, robust insights. Organizational researchers have begun such efforts [e.g., metaBUS ( http://metabus.org/ )] but are far from the efficient, comprehensive curation seen in areas such as cognitive neuroscience or genetics. This review provides a sample of insights from research curation efforts in organizational research, psychology, and beyond—insights not possible by even large-scale, substantive meta-analyses. Efforts are classified as either science-of-science research or large-scale, substantive research. The various methods used for information extraction (e.g., from PDF files) and classification (e.g., using consensus ontologies) is reviewed. The review concludes with a series of recommendations for developing and leveraging the available corpus of organizational research to speed scientific progress.

Iowa Implementation for Sustainability Framework

Background

An application-oriented implementation framework designed for clinicians and based on the Diffusion of Innovations theory included 81 implementation strategies with suggested timing for use within four implementation phases. The purpose of this research was to evaluate and strengthen the framework for clinician use and propose its usefulness in implementation research.

Methods

A multi-step, iterative approach guided framework revisions. Individuals requesting the use of the framework over the previous 7 years were sent an electronic questionnaire. Evaluation captured framework usability, generalizability, accuracy, and implementation phases for each strategy. Next, nurse leaders who use the framework pile sorted strategies for cultural domain analysis. Last, a panel of five EBP/implementation experts used these data and built consensus to strengthen the framework.

Results

Participants (n = 127/1578; 8% response) were predominately nurses (94%), highly educated (94% Master’s or higher), and from across healthcare (52% hospital/system, 31% academia, and 7% community) in the USA (84%). Most (96%) reported at least some experience using the framework and 88% would use the framework again. A 4-point scale (1 = not/disagree to 4 = very/agree) was used. The framework was deemed useful (92%, rating 3–4), easy to use (72%), intuitive (67%), generalizable (100%), flexible and adaptive (100%), with accurate phases (96%), and accurate targets (100%). Participants (n = 51) identified implementation strategy timing within four phases (Cochran’s Q); 54 of 81 strategies (66.7%, p < 0.05) were significantly linked to a specific phase; of these, 30 (55.6%) matched the original framework. Next, nurse leaders (n = 23) completed a pile sorting activity. Anthropac software was used to analyze the data and visualize it as a domain map and hierarchical clusters with 10 domains. Lastly, experts used these data and implementation science to refine and specify each of the 75 strategies, identifying phase, domain, actors, and function. Strategy usability, timing, and groupings were used to refine the framework.

Conclusion

The Iowa Implementation for Sustainability Framework offers a typology to guide implementation for evidence-based healthcare. This study specifies 75 implementation strategies within four phases and 10 domains and begins to validate the framework. Standard use of strategy names is foundational to compare and understand when implementation strategies are effective, in what dose, for which topics, by whom, and in what context.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13012-021-01157-5.

Emerging digital technologies in cancer treatment, prevention, and control

The very first issue of the journal of Translational Behavioral Medicine (TBM) was dedicated, in part, to the theme of Health Information Technology as a platform for evidence implementation. The topic was timely: legislation in the USA was passed with the intent of stimulating the adoption of electronic health records; mobile smartphones, tablets, and other devices were gaining traction in the consumer market, while members within the Society of Behavioral Medicine were gaining scientific understanding on how to use these tools to effect healthy behavior change. For the anniversary issue of TBM, we evaluated the progress and problems associated with deploying digital health technologies to support cancer treatment, prevention, and control over the last decade. We conducted a narrative review of published literature to identify the role that emerging digital technologies may take in achieving national and international objectives in the decade to come. We tracked our evaluation of the literature across three phases in the cancer control continuum: (a) prevention, (b) early detection/screening, and (c) treatment/survivorship. From our targeted review and analyses, we noted that significant progress had been made in the adoption of digital health technologies in the cancer space over the past decade but that significant work remains to be done to integrate these technologies effectively into the cancer control systems needed to improve outcomes equitably across populations. The challenge for the next 10 years is inherently translational.

The First 40 Years of AIDS: Promising Programs, Limited Success

HIV-prevention program planning, implementation, and evaluation began in the United States shortly after reports of a mysterious, apparently acquired, immune deficiency syndrome appeared in summer 1981. In San Francisco, New York City, and elsewhere, members of LGBT communities responded by providing accurate information, giving support, and raising money. During the first decade of the AIDS pandemic (1981-1990), social and behavioral scientists contributed by designing theory-based and practical interventions, combining interventions into programs, and measuring impact on behavior change and HIV incidence. In the second decade (1991-2000), federal, state, and local agencies and organizations played a more prominent role in establishing policies and procedures, funding research and programs, and determining the direction of intervention efforts. In the third decade (2001-2010), biomedical interventions were prioritized over behavioral interventions and have dominated attempts in the fourth decade (2011-2020) to integrate biomedical, behavioral, and structural interventions into coherent, efficient, and cost-effective programs to end AIDS.

Using the Intervention Mapping Approach to Develop a Mental Health Intervention: A Case Study on Improving the Reporting Standards for Developing Psychological Interventions

Replicating or distilling information from psychological interventions reported in the scientific literature is hindered by inadequate reporting, despite the existence of various methodologies to guide study reporting and intervention development. This article provides an in-depth explanation of the scientific development process for a mental health intervention, and by doing so illustrates how intervention development methodologies can be used to improve development reporting standards of interventions. Intervention development was guided by the Intervention Mapping approach and the Theoretical Domains Framework. It relied on an extensive literature review, input from a multi-disciplinary group of stakeholders and the learnings from projects on similar psychological interventions. The developed programme, called the “Be Well Plan”, focuses on self-exploration to determine key motivators, resources and challenges to improve mental health outcomes. The programme contains an online assessment to build awareness about one’s mental health status. In combination with the exploration of different evidence-based mental health activities from various therapeutic backgrounds, the programme teaches individuals to create a personalised mental health and wellbeing plan. The use of best-practice intervention development frameworks and evidence-based behavioural change techniques aims to ensure optimal intervention impact, while reporting on the development process provides researchers and other stakeholders with an ability to scientifically interrogate and replicate similar psychological interventions.

IC-Behavior: An interdisciplinary taxonomy of behaviors

Academic disciplines are often organized according to the behaviors they examine. While most research on a behavior tends to exist within one discipline, some behaviors are examined by multiple disciplines. Better understanding of behaviors and their relationships should enable knowledge transfer across disciplines and theories, thereby dramatically improving the behavioral knowledge base. We propose a taxonomy built on the World Health Organization's International Classification of Functioning, Disability, and Health (ICF), but design the taxonomy as a stand-alone extension rather than an improvement to ICF. Behaviors considered important enough to serve as the dependent variable in articles accepted for publication in top journals were extracted from nine different behavioral and social disciplines. A six-step development and validation process was employed, leading to the final taxonomy. A hierarchy of behaviors under the top banner of Engaging in activities/participating, reflective of ICF's D. hierarchy was constructed with eight immediate domains addressing behaviors ranging from learning, exercising, self-care, and substance use. The resulting International Classification of Behaviors (IC-Behavior), provides a behavior taxonomy targeted towards the interdisciplinary integration of nomological networks relevant to behavioral theories. While IC-Behavior has been labeled v.1.0 to communicate that it is by no means an endpoint, it has empirically shown to provide flexibility for the addition of new behaviors and is tested in the health domain.

A scoping review of patient-facing, behavioral health interventions with voice assistant technology targeting self-management and healthy lifestyle behaviors

Engaging in positive healthy lifestyle behaviors continues to be a public health challenge, requiring innovative solutions. As the market for voice assistants (Amazon Alexa, Google Assistant, and Apple Siri) grows and people increasingly use them to assist their daily tasks, there is a pressing need to explore how voice assistant (VA) technology may be used in behavioral health interventions. A scoping review of literature was conducted to address a PICO (Population, Intervention, Comparison, and Outcome) question: across populations, how does the use of voice assistants in behavioral health research/interventions influence healthy lifestyle behaviors versus control or comparison interventions? To inform the science, a secondary aim of this review was to explore characteristics of VAs used in behavioral health research. The review was conducted following Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines with scoping review extension (PRISMA-ScR). Ten studies satisfied the inclusion criteria, representing research published through February 2019. Studies spanned pediatric to elderly populations, covering a vast array of self-management and healthy lifestyle behaviors. The majority of interventions were multicomponent, involving more than one of the following behavior change techniques grouped by cluster: shaping knowledge, self-belief, repetition and substitution, feedback and monitoring, goals and planning, antecedents, natural consequences, comparison of behavior, and identification. However, most studies were in early stages of development, with limited efficacy trials. VA technology continues to evolve and support behavioral interventions using various platforms (e.g., Interactive Voice Response [IVR] systems, smartphones, and smart speakers) which are used alone or in conjunction with other platforms. Feasibility, usability, preliminary efficacy, along with high user satisfaction of research adapted VAs, in contrast to standalone commercially available VAs, suggest a role for VAs in behavioral health intervention research.

Specifying who delivers behaviour change interventions: development of an Intervention Source Ontology

Background:  Identifying how behaviour change interventions are delivered, including by whom, is key to understanding intervention effectiveness. However, information about who delivers interventions is reported inconsistently in intervention evaluations, limiting communication and knowledge accumulation. This paper reports a method for consistent reporting: The Intervention Source Ontology. This forms one part of the Behaviour Change Intervention Ontology, which aims to cover all aspects of behaviour change interventions . Methods: The Intervention Source Ontology was developed following methods for ontology development and maintenance used in the Human Behaviour-Change Project, with seven key steps: 1) define the scope of the ontology, 2) identify key entities and develop their preliminary definitions by reviewing existing classification systems (top-down) and reviewing 100 behaviour change intervention reports (bottom-up), 3) refine the ontology by piloting the preliminary ontology on 100 reports, 4) stakeholder review by 34 behavioural science and public health experts, 5) inter-rater reliability testing of annotating intervention reports using the ontology, 6) specify ontological relationships between entities and 7) disseminate and maintain the Intervention Source Ontology. Results: The Intervention Source Ontology consists of 140 entities. Key areas of the ontology include Occupational Role of Source, Relatedness between Person Source and the Target Population, Sociodemographic attributes and Expertise. Inter-rater reliability was found to be 0.60 for those familiar with the ontology and 0.59 for those unfamiliar with it, levels of agreement considered 'acceptable'. Conclusions: Information about who delivers behaviour change interventions can be reliably specified using the Intervention Source Ontology. For human-delivered interventions, the ontology can be used to classify source characteristics in existing behaviour change reports and enable clearer specification of intervention sources in reporting.

Delivering Behaviour Change Interventions: Development of a Mode of Delivery Ontology

Background: Investigating and improving the effects of behaviour change interventions requires detailed and consistent specification of all aspects of interventions. An important feature of interventions is the way in which these are delivered, i.e. their mode of delivery. This paper describes an ontology for specifying the mode of delivery of interventions, which forms part of the Behaviour Change Intervention Ontology, currently being developed in the Wellcome Trust funded Human Behaviour-Change Project. Methods: The Mode of Delivery Ontology was developed in an iterative process of annotating behaviour change interventions evaluation reports, and consulting with expert stakeholders. It consisted of seven steps: 1) annotation of 110 intervention reports to develop a preliminary classification of modes of delivery; 2) open review from international experts (n=25); 3) second round of annotations with 55 reports to test inter-rater reliability and identify limitations; 4) second round of expert review feedback (n=16); 5) final round of testing of the refined ontology by two annotators familiar and two annotators unfamiliar with the ontology; 6) specification of ontological relationships between entities; and 7) transformation into a machine-readable format using the Web Ontology Language (OWL) and publishing online. Results: The resulting ontology is a four-level hierarchical structure comprising 65 unique modes of delivery, organised by 15 upper-level classes: Informational , Environmental change, Somatic, Somatic alteration, Individual-based/ Pair-based /Group-based, Uni-directional/Interactional, Synchronous/ Asynchronous, Push/ Pull, Gamification, Arts feature. Relationships between entities consist of is_a. Inter-rater reliability of the Mode of Delivery Ontology for annotating intervention evaluation reports was a=0.80 (very good) for those familiar with the ontology and a= 0.58 (acceptable) for those unfamiliar with it. Conclusion: The ontology can be used for both annotating and writing behaviour change intervention evaluation reports in a consistent and coherent manner, thereby improving evidence comparison, synthesis, replication, and implementation of effective interventions.

Determinants of Physical Health Self-Management Behaviours in Adults With Serious Mental Illness: A Systematic Review

Behavioural interventions can support the adoption of healthier lifestyles and improve physical health outcomes, but it is unclear what factors might drive success of such interventions in people with serious mental illness (SMI). We systematically identified and reviewed evidence of the association between determinants of physical health self-management behaviours in adults with SMI. Data about American Association of Diabetes Educator's Self-Care Behaviours (AADE-7) were mapped against the novel Mechanisms of Action (MoA) framework. Twenty-eight studies were included in the review, reporting evidence on 104 determinant-behaviour links. Beliefs about capabilities and beliefs about consequences were the most important determinants of behaviour, especially for being physically active and healthy eating. There was some evidence that emotion and environmental context and resources played a role in determining reducing risks, being active, and taking medications. We found very limited evidence associated with problem solving, and no study assessed links between MoAs and healthy coping. Although the review predominantly identified evidence about associations from cross-sectional studies that lacked validated and objective measures of self-management behaviours, these findings can facilitate the identification of behaviour change techniques with hypothesised links to determinants to support self-management in people with SMI. Systematic Review Registration: PROSPERO, registration CRD42018099553.

Promoting adherence to physical activity among individuals with cardiovascular disease using behavioral counseling: A theory and research-based primer for health care professionals

Physical activity (PA) promotion remains a cornerstone of primary and secondary prevention efforts to reduce morbidity and mortality from cardiovascular disease (CVD). While frontline health care providers (HCPs; e.g., family physicians, cardiologists, registered nurses, nurse practitioners, etc.) are in an optimal position to administer PA-promoting interventions to their patients, many HCPs may feel ill-equipped to address common obstacles to implementing and maintaining complex health behavior change. Behavioral counseling refers to a collection of theory- and empirically-supported strategies and approaches to health behavior promotion that can be learned and applied by HCPs for CVD prevention and treatment. In this selective review, we discuss prominent theories of health behavior change and the empirical intervention literature regarding PA promotion in community and CVD-samples and provide practical recommendations for integrating effective behavioral counseling strategies to clinical practice for frontline HCPs. We argue that behavioral counseling interventions for PA can be effectively executed within the contextual constraints of health settings through subtle shifts in communication strategies and brief counseling approaches. The administration of behavioral counseling for PA by HCPs has enormous potential to reduce CVD incidence and progression at a population level.

Riding the Wave of Digital Transformation in Behavioral Medicine

BACKGROUND

Digital technologies provide a platform for accelerating science and broadening impact in behavioral medicine.

PURPOSE

The objective of this invited keynote presentation or paper is to offer a blueprint for navigating the rapidly changing waters of digital health.

METHODS

A strategic literature review on digital health technologies in behavioral medicine was combined with a review of relevant policy initiatives to yield insights on: (a) knowledge building, (b) collaboration, and (c) public health stewardship.

RESULTS

Digital platforms offer unprecedented leverage for accelerating science, facilitating collaboration, and advancing public health. Early successes in behavioral medicine demonstrated how digital platforms could extend the reach of theory-based behavioral therapeutics through increases in efficiency and scale. As medical investments in health information technology increased, the field of behavioral informatics emerged as the collaborative glue binding behavioral theory into a new generation of patient-facing applications, clinical decision support tools, evidence-based communication programs, and population health management strategies. As a leader within the interstitial space between medicine, psychology, and engineering, the Society of Behavioral Medicine is in a distinct position to exert influence on the ways in which our science is utilized to eliminate health disparities; improve support for patients, caregivers, and communities; to promote general health and well-being; and to offer relief when confronted with psychological pain or addiction.

CONCLUSION

Riding the wave of digital transformation has less to do with mastering the complexities of the latest technologies and more to do with adhering closely to established principles for navigating a rapidly changing information environment.

Delivering Behaviour Change Interventions: Development of a Mode of Delivery Ontology

Background: Investigating and improving the effects of behaviour change interventions requires detailed and consistent specification of all aspects of interventions. An important feature of interventions is the way in which these are delivered, i.e. their mode of delivery. This paper describes an ontology for specifying the mode of delivery of interventions, which forms part of the Behaviour Change Intervention Ontology, currently being developed in the Wellcome Trust funded Human Behaviour-Change Project. Methods: The Mode of Delivery Ontology was developed in an iterative process of annotating behaviour change interventions evaluation reports, and consulting with expert stakeholders. It consisted of seven steps: 1) annotation of 110 intervention reports to develop a preliminary classification of modes of delivery; 2) open review from international experts (n=25); 3) second round of annotations with 55 reports to test inter-rater reliability and identify limitations; 4) second round of expert review feedback (n=16); 5) final round of testing of the refined ontology by two annotators familiar and two annotators unfamiliar with the ontology; 6) specification of ontological relationships between entities; and 7) transformation into a machine-readable format using the Web Ontology Language (OWL) language and publishing online. Results: The resulting ontology is a four-level hierarchical structure comprising 65 unique modes of delivery, organised by 15 upper-level classes: Informational , Environmental change, Somatic, Somatic alteration, Individual-based/ Pair-based /Group-based, Uni-directional/Interactional, Synchronous/ Asynchronous, Push/ Pull, Gamification, Arts feature. Relationships between entities consist of is_a. Inter-rater reliability of the Mode of Delivery Ontology for annotating intervention evaluation reports was a=0.80 (very good) for those familiar with the ontology and a= 0.58 (acceptable) for those unfamiliar with it. Conclusion: The ontology can be used for both annotating and writing behaviour change intervention evaluation reports in a consistent and coherent manner, thereby improving evidence comparison, synthesis, replication, and implementation of effective interventions.

Development of an Intervention Setting Ontology for behaviour change: Specifying where interventions take place

Background: Contextual factors such as an intervention's setting are key to understanding how interventions to change behaviour have their effects and patterns of generalisation across contexts. The intervention's setting is not consistently reported in published reports of evaluations. Using ontologies to specify and classify intervention setting characteristics enables clear and reproducible reporting, thus aiding replication, implementation and evidence synthesis. This paper reports the development of a Setting Ontology for behaviour change interventions as part of a Behaviour Change Intervention Ontology, currently being developed in the Wellcome Trust funded Human Behaviour-Change Project. Methods: The Intervention Setting Ontology was developed following methods for ontology development used in the Human Behaviour-Change Project: 1) Defining the ontology's scope, 2) Identifying key entities by reviewing existing classification systems (top-down) and 100 published behaviour change intervention reports (bottom-up), 3) Refining the preliminary ontology by literature annotation of 100 reports, 4) Stakeholder reviewing by 23 behavioural science and public health experts to refine the ontology, 5) Assessing inter-rater reliability of using the ontology by two annotators familiar with the ontology and two annotators unfamiliar with it, 6) Specifying ontological relationships between setting entities and 7) Making the Intervention Setting Ontology machine-readable using Web Ontology Language (OWL) and publishing online. Re sults: The Intervention Setting Ontology consists of 72 entities structured hierarchically with two upper-level classes: Physical setting including Geographic location, Attribute of location (including Area social and economic condition, Population and resource density sub-levels) and Intervention site (including Facility, Transportation and Outdoor environment sub-levels), as well as Social setting. Inter-rater reliability was found to be 0.73 (good) for those familiar with the ontology and 0.61 (acceptable) for those unfamiliar with it. Conclusion: The Intervention Setting Ontology can be used to code information from diverse sources, annotate the setting characteristics of existing intervention evaluation reports and guide future reporting.

Applying the COM-B model to patient-reported barriers to medication adherence in pediatric acute lymphoblastic leukemia

BACKGROUND

Adherence to oral chemotherapy, including 6-mercaptopurine (6-MP), is suboptimal in pediatric acute lymphoblastic leukemia (ALL), which is associated with increased risk of relapse. Study objectives were to examine self-reported adherence to 6-MP and related barriers to adherence, mapped to the capability, opportunity, motivation, and behavior (COM-B) model for behavior change.

PROCEDURE

Forty-nine parents (median, 39 years old; 76% females) and 15 patients (median, 17 years old, 20% females) completed the study survey.

RESULTS

Suboptimal adherence was reported in 43% of parents and 73% of patients. Most parents and patients (80% and 90%, respectively) reported ≥1 adherence barrier. Parents reported difficulty helping their child meet others with ALL (43%), contacting community organizations (39%), and meeting other parents (37%). Patients reported difficulty finding out what their medications are (40%), finding out what 6-MP does (47%), and meeting other patients (40%). Using the COM-B, we found that parents and patients endorsed barriers in multiple components, especially physical (55%, 67%) and social opportunity (56%, 47%), highlighting that barriers to adherence may be multifaceted.

CONCLUSIONS

Our results suggest that parents and patients with ALL face various prevalent barriers to medication adherence and provide insight into the development of behavioral interventions focused on promoting adherence, which is essential to prevent relapse and optimize health outcomes in ALL.

Semi-Automated evidence synthesis in health psychology: current methods and future prospects

The evidence base in health psychology is vast and growing rapidly. These factors make it difficult (and sometimes practically impossible) to consider all available evidence when making decisions about the state of knowledge on a given phenomenon (e.g., associations of variables, effects of interventions on particular outcomes). Systematic reviews, meta-analyses, and other rigorous syntheses of the research mitigate this problem by providing concise, actionable summaries of knowledge in a given area of study. Yet, conducting these syntheses has grown increasingly laborious owing to the fast accumulation of new evidence; existing, manual methods for synthesis do not scale well. In this article, we discuss how semi-automation via machine learning and natural language processing methods may help researchers and practitioners to review evidence more efficiently. We outline concrete examples in health psychology, highlighting practical, open-source technologies available now. We indicate the potential of more advanced methods and discuss how to avoid the pitfalls of automated reviews.

Understanding Health Behavior Technology Engagement: Pathway to Measuring Digital Behavior Change Interventions

Researchers and practitioners of digital behavior change interventions (DBCI) use varying and, often, incongruent definitions of the term "engagement," thus leading to a lack of precision in DBCI measurement and evaluation. The objective of this paper is to propose discrete definitions for various types of user engagement and to explain why precision in the measurement of these engagement types is integral to ensuring the intervention is effective for health behavior modulation. Additionally, this paper presents a framework and practical steps for how engagement can be measured in practice and used to inform DBCI design and evaluation. The key purpose of a DBCI is to influence change in a target health behavior of a user, which may ultimately improve a health outcome. Using available literature and practice-based knowledge of DBCI, the framework conceptualizes two primary categories of engagement that must be measured in DBCI. The categories are health behavior engagement, referred to as "Big E," and DBCI engagement, referred to as "Little e." DBCI engagement is further bifurcated into two subclasses: (1) user interactions with features of the intervention designed to encourage frequency of use (ie, simple login, games, and social interactions) and make the user experience appealing, and (2) user interactions with behavior change intervention components (ie, behavior change techniques), which influence determinants of health behavior and subsequently influence health behavior. Achievement of Big E in an intervention delivered via digital means is contingent upon Little e. If users do not interact with DBCI features and enjoy the user experience, exposure to behavior change intervention components will be limited and less likely to influence the behavioral determinants that lead to health behavior engagement (Big E). Big E is also dependent upon the quality and relevance of the behavior change intervention components within the solution. Therefore, the combination of user interactions and behavior change intervention components creates Little e, which is, in turn, designed to improve Big E. The proposed framework includes a model to support measurement of DBCI that describes categories of engagement and details how features of Little e produce Big E. This framework can be applied to DBCI to support various health behaviors and outcomes and can be utilized to identify gaps in intervention efficacy and effectiveness.

The Behavioral Medicine Research Council: Its origins, mission, and methods

The Behavioral Medicine Research Council (BMRC) is a new, autonomous joint committee of 4 of the leading behavioral medicine research organizations, including the Academy of Behavioral Medicine Research, the American Psychosomatic Society, the Society for Health Psychology, and the Society of Behavioral Medicine. The BMRC's work has important implications for the science and practice of behavioral medicine. The distinguished senior scientists who comprise this new committee will identify a series of strategic research goals for behavioral medicine and promote systematic, interdisciplinary efforts to achieve them. This special report discusses the developments that led to the formation of the BMRC, describes the BMRC's mission, and explains the methods that its members will use. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Advancing the state-level tracking of evidence-based practices: a case study

Background

Despite a sustained focus by policymakers and researchers on improving the standard of clinical care in public mental health services, the use of evidence-based practice remains low. Among other challenges, this reflects the difficulty of translating clinical research into useable policy that can be feasibly funded and monitored by state or large healthcare systems.

Case presentation

In this paper we present a case study of Washington State’s strategy for monitoring the use of clinical elements at the session level for all Medicaid-funded children’s mental health services. The implementation of this strategy reflects policy actions to promote effective practice while also actively influencing multiple other levels of the implementation ecology. The approach is informed by the Policy Ecology Framework, the Consolidated Framework for Implementation Research, the evidence-based policymaking literature, and common ontology and clinical elements models.

Conclusions

We found the strategy developed in Washington State to be a feasible method of collecting session level information about the use of effective clinical mental health practices. In addition, the approach appears to be having influence on multiple layers of the implementation ecology that could be explored through further study.

A scoping review of ontologies related to human behaviour change

Ontologies are classification systems specifying entities, definitions and inter-relationships for a given domain, with the potential to advance knowledge about human behaviour change. A scoping review was conducted to: (1) identify what ontologies exist related to human behaviour change, (2) describe the methods used to develop these ontologies and (3) assess the quality of identified ontologies. Using a systematic search, 2,303 papers were identified. Fifteen ontologies met the eligibility criteria for inclusion, developed in areas such as cognition, mental disease and emotions. Methods used for developing the ontologies were expert consultation, data-driven techniques and reuse of terms from existing taxonomies, terminologies and ontologies. Best practices used in ontology development and maintenance were documented. The review did not identify any ontologies representing the breadth and detail of human behaviour change. This suggests that advancing behavioural science would benefit from the development of a behaviour change intervention ontology.

The history and future of digital health in the field of behavioral medicine

Since its earliest days, the field of behavioral medicine has leveraged technology to increase the reach and effectiveness of its interventions. Here, we highlight key areas of opportunity and recommend next steps to further advance intervention development, evaluation, and commercialization with a focus on three technologies: mobile applications (apps), social media, and wearable devices. Ultimately, we argue that future of digital health behavioral science research lies in finding ways to advance more robust academic-industry partnerships. These include academics consciously working towards preparing and training the work force of the twenty first century for digital health, actively working towards advancing methods that can balance the needs for efficiency in industry with the desire for rigor and reproducibility in academia, and the need to advance common practices and procedures that support more ethical practices for promoting healthy behavior.

Pokémon GO Within the Context of Family Health: Retrospective Study

BACKGROUND

Pokémon GO illuminated the potential for mobile phone gaming apps to engage users and promote health. However, much work is needed to fully understand the mechanisms through which digitally supported behavior change interventions operate, particularly for children and families.

OBJECTIVE

The aims of this study were (1) to explore the Pokémon GO user experience from a family perspective and (2) to investigate Pokémon GO within the context of family health.

METHODS

Between January and February 2017, congruent with one of the largest anticipated Pokémon GO updates Gen 2, participants were recruited from parks, word of mouth, and social media to complete a Web-based survey. Participants were surveyed about family characteristics, interest, and experiences playing Pokémon GO and healthy lifestyle beliefs. Using a revised Godin Leisure-Time Exercise Questionnaire, a retrospective pre-post design assessed changes in parent physical activity (PA) before and after playing Pokémon GO.

RESULTS

Self-reported data from 160 parents and 31 children were included in the final analyses (representing 129 parents and 31 parent-child dyads). Gameplay most often occurred between sons aged 10 years or younger and mothers. "Spending time together" was the most cited reason for gameplay by both parents (122/160, 76.3%) and children (24/31, 77%), followed by "it helped me go outdoors" for parents (113/160, 70.1%) and "I am a Pokémon fan" by children (21/31, 68%). Interestingly, open-ended responses indicated that gameplay could trigger both positive and negative emotional parent response. The most cited reason for app disengagement was boredom; conversely, the most cited reason for app re-engagement was in-app events. For parents, there were significant increases in minutes spent in mild (mean 23.36 [SD 66.02]; t₉₇=3.50, P<.001) and moderate (mean 21.76 [SD 53.04]; t₁₃₀=4.70, P<.001) PA per week after playing Pokémon GO. However, child perceptions of parental influence on PA most significantly associated with parents who reported weekly strenuous PA both before (r_s=.514, P=.003) and after (r_s=.536, P=.003) Pokémon GO uptake.

CONCLUSIONS

Pokémon GO transcended traditional understanding of digital health and uniquely reached across generations to engage users. Findings from this study highlight that, for a period of time, Pokémon GO fostered social and physical well-being for children and families through a multifaceted approach.

Advances and Controversies in Diet and Physical Activity Measurement in Youth

Technological advancements in the past decades have improved dietary intake and physical activity measurements. This report reviews current developments in dietary intake and physical activity assessment in youth. Dietary intake assessment has relied predominantly on self-report or image-based methods to measure key aspects of dietary intake (e.g., food types, portion size, eating occasion), which are prone to notable methodologic (e.g., recall bias) and logistic (e.g., participant and researcher burden) challenges. Although there have been improvements in automatic eating detection, artificial intelligence, and sensor-based technologies, participant input is often needed to verify food categories and portions. Current physical activity assessment methods, including self-report, direct observation, and wearable devices, provide researchers with reliable estimations for energy expenditure and bodily movement. Recent developments in algorithms that incorporate signals from multiple sensors and technology-augmented self-reporting methods have shown preliminary efficacy in measuring specific types of activity patterns and relevant contextual information. However, challenges in detecting resistance (e.g., in resistance training, weight lifting), prolonged physical activity monitoring, and algorithm (non)equivalence remain to be addressed. In summary, although dietary intake assessment methods have yet to achieve the same validity and reliability as physical activity measurement, recent developments in wearable technologies in both arenas have the potential to improve current assessment methods.

THEME INFORMATION

This article is part of a theme issue entitled Innovative Tools for Assessing Diet and Physical Activity for Health Promotion, which is sponsored by the North American branch of the International Life Sciences Institute.

Dietary Behavior: An Interdisciplinary Conceptual Analysis and Taxonomy

Background: Dietary behavior encompasses many aspects, terms for which are used inconsistently across different disciplines and research traditions. This hampers communication and comparison across disciplines and impedes the development of a cumulative science. We describe the conceptual analysis of the fuzzy umbrella concept "dietary behavior" and present the development of an interdisciplinary taxonomy of dietary behavior. Methods: A four-phase multi-method approach was employed. Input was provided by 76 scholars involved in an international research project focusing on the determinants of dietary behavior. Input was collected from the scholars via an online mind mapping procedure. After structuring, condensing, and categorizing this input into a compact taxonomy, the result was presented to all scholars, discussed extensively, and adapted. A second revision round was then conducted among a core working group. Results: A total of 145 distinct entries were made in the original mind mapping procedure. The subsequent steps allowed us to reduce and condense the taxonomy into a final product consisting of 34 terms organized into three main categories: Food Choice, Eating Behavior, and Dietary Intake/Nutrition. In a live discussion session attended by 50 of the scholars involved in the development of the taxonomy, it was judged to adequately reflect their input and to be a valid and useful starting point for interdisciplinary understanding and collaboration. Conclusion: The current taxonomy can be used as a tool to facilitate understanding and cooperation between different disciplines investigating dietary behavior, which may contribute to a more successful approach to tackling the complex public health challenges faced by the field. The taxonomy need not be viewed as a final product, but can continue to grow in depth and width as additional experts provide their input.

Development and Validation of a Functional Behavioural Assessment Ontology to Support Behavioural Health Interventions

Background

In the cognitive-behavioral approach, Functional Behavioural Assessment is one of the most effective methods to identify the variables that determine a problem behavior. In this context, the use of modern technologies can encourage the collection and sharing of behavioral patterns, effective intervention strategies, and statistical evidence about antecedents and consequences of clusters of problem behaviors, encouraging the designing of function-based interventions.

Objective

The paper describes the development and validation process used to design a specific Functional Behavioural Assessment Ontology (FBA-Ontology). The FBA-Ontology is a semantic representation of the variables that intervene in a behavioral observation process, facilitating the systematic collection of behavioral data, the consequential planning of treatment strategies and, indirectly, the scientific advancement in this field of study.

Methods

The ontology has been developed deducing concepts and relationships of the ontology from a gold standard and then performing a machine-based validation and a human-based assessment to validate the Functional Behavioural Assessment Ontology. These validation and verification processes were aimed to verify how much the ontology is conceptually well founded and semantically and syntactically correct.

Results

The Pellet reasoner checked the logical consistency and the integrity of classes and properties defined in the ontology, not detecting any violation of constraints in the ontology definition. To assess whether the ontology definition is coherent with the knowledge domain, human evaluation of the ontology was performed asking 84 people to fill in a questionnaire composed by 13 questions assessing concepts, relations between concepts, and concepts’ attributes. The response rate for the survey was 29/84 (34.52%). The domain experts confirmed that the concepts, the attributes, and the relationships between concepts defined in the FBA-Ontology are valid and well represent the Functional Behavioural Assessment process.

Conclusions

The new ontology developed could be a useful tool to design new evidence-based systems in the Behavioral Interventions practices, encouraging the link with other Linked Open Data datasets and repositories to provide users with new models of eHealth focused on the management of problem behaviors. Therefore, new research is needed to develop and implement innovative strategies to improve the poor reproducibility and translatability of basic research findings in the field of behavioral assessment.

Evaluating the effectiveness of behavior change techniques in health-related behavior: a scoping review of methods used

Behavior change interventions typically contain multiple potentially active components: behavior change techniques (BCTs). Identifying which specific BCTs or BCT combinations have the potential to be effective for a given behavior in a given context presents a major challenge. The aim of this study was to review the methods that have been used to identify effective BCTs for given behaviors in given contexts and evaluate their strengths and limitations. A scoping review was conducted of studies that had sought to identify effective BCTs. Articles referring to "behavio(u)r change technique(s)" in the abstract/text were located, and ones that involved identification of effective BCTs were selected. The methods reported were coded. The methods were analyzed in general terms using "PASS" criteria: Practicability (facility to apply the method appropriately), Applicability (facility to generalize from findings to contexts and populations of interest), Sensitivity (facility to identify effective BCTs), and Specificity (facility to rule out ineffective BCTs). A sample of 10% of the studies reviewed was then evaluated using these criteria to assess how far the strengths and limitations identified in principle were borne out in practice. One hundred and thirty-five studies were identified. The methods used in those studies were experimental manipulation of BCTs, observational studies comparing outcomes in the presence or absence of BCTs, meta-analyses of BCT comparisons, meta-regressions evaluating effect sizes with and without specific BCTs, reviews of BCTs found in effective interventions, and meta-classification and regression trees. The limitations of each method meant that only weak conclusions could be drawn regarding the effectiveness of specific BCTs or BCT combinations. Methods for identifying effective BCTs linked to target behavior and context all have important inherent limitations. A strategy needs to be developed that can systematically combine the strengths of the different methods and that can link these constructs in an ontology of behavior change interventions.

Optimising the value of the evidence generated in implementation science: the use of ontologies to address the challenges

Implementing research findings into healthcare practice and policy is a complex process occurring in diverse contexts; it invariably depends on changing human behaviour in many parts of an intricate implementation system. Questions asked with the aim of improving implementation are multifarious variants of 'What works, compared with what, how well, with what exposure, with what behaviours (for how long), for whom, in what setting and why?'. Relevant evidence is being published at a high rate, but its quantity, complexity and lack of shared terminologies present challenges. The achievement of efficient, effective and timely synthesis of evidence is facilitated by using 'ontologies' to systematically structure and organise the evidence about constructs and their relationships, using a controlled, well-defined vocabulary.