Affective response to physical activity as an intermediate phenotype

Over the past seventy years, biomedical and epidemiological research has shown that regular physical activity (PA) is critical for physical and mental health. Despite this knowledge, physical inactivity is the fourth leading risk factor for global mortality, accounting for 9% (5.3 million) of premature deaths annually. We suggest this mismatch between knowing about the risks of PA and engaging in regular PA can be reconciled by focusing less on expected health benefits of PA and more on how people feel during PA. Specifically, in this position paper, we argue that affective response (feeling good versus bad) to PA is an intermediate phenotype that can explain significant variance in PA behavior and is, in turn, a function of genetic variability. In making this argument, we first review empirical evidence showing that affective response to PA predicts future physical activity behavior. Second, we systematically review research on single nucleotide morphisms (SNPs) that are associated with affective response to PA. Investigating affective response to PA as an intermediate phenotype will allow future researchers to move beyond asking “What SNPs are associated with PA?“, and begin asking “How do these SNPs influence PA?“, thus ultimately optimizing the translation of knowledge gained from genomic data to intervention development

Age Moderates the Effect of Self-Paced Exercise on Exercise Adherence among Overweight Adults

Objective: The present study tested the hypothesis that the effect of self-paced exercise on adherence to exercise programs is more pronounced with increasing age. Method: Fifty-nine low-active overweight adults (18-65 years) were encouraged to walk 30 to 60 min/day and randomized to either self-paced (n = 30) or prescribed moderate-intensity (n = 29) conditions. Results: The effect of study condition was moderated by age (main effect: b = 6.14, SE = 2.54, p = .02; Condition × Age: b = −11.55, SE = 3.77, p \u3c .01), such that among participants \u3e50 years, those in the self-paced condition exercised 6 more min/day than participants in the prescribed moderate-intensity condition (p = .02), whereas among participants \u3c50 \u3eyears, those in the self-paced condition exercised 5.4 fewer min/day compared with those in the moderate-intensity condition (p = .05). Affective response to physical activity did not mediate the moderating effect of age. Discussion: As age increases, adults may be more likely to adhere to self-paced versus prescribed moderate-intensity exercise

Affective response as a mediator of the association between the physical and social environment and physical activity behavior

Perceptions of the physical and social environment have been shown to be predictive of physical activity (PA) behavior. However, the mechanisms of this association have not been examined. Affective response to PA was examined as a putative mediator of the association between perceptions of the PA environment and subsequent PA behavior. As part of a PA promotion study, 59 low-active overweight or obese but otherwise healthy adults completed real-time assessments of the perceived physical and social PA environment, affective response to PA, and PA behavior over a 6-month period. As hypothesized, decreased latency to and greater duration of subsequent PA was predicted by engaging in PA with a partner (b = 17.24, SE = .45, p \u3c .01), engaging in PA outdoors versus indoors (b = 3.70, SE = 0.67, p \u3c .01), and perceived pleasantness of the physical (b = 0.59, SE = .17, p \u3c .01) and social settings (b = 0.68, SE = .16, p \u3c .01). Affective response to PA (a shift toward feeling good versus bad during PA) mediated the association between engaging in PA with a partner (a path: 0.53(.11), p \u3c .01, b path: 0.42(.12), p \u3c .01, ab path: 0.22(.08), 95% CI .09–.41) and perceived pleasantness of the physical (a path: .38(.02), p \u3c .01; b path: .65(.23), p = .01; ab path: .25(.09), 95% CI .08–.43) and social setting (apath: .35(.02), p \u3c .01; b path: .57(.23), p = .01; ab path: .20(.08), 95% CI .03–.37) and PA behavior, but not the association between engaging in PA outdoors versus indoors and PA behavior. These findings suggest that perceived environmental variables may have their effects on PA through the process of psychological hedonism

An ontology-based modelling system (OBMS) for representing behaviour change theories applied to 76 theories

Background: To efficiently search, compare, test and integrate behaviour change theories, they need to be specified in a way that is clear, consistent and computable. An ontology-based modelling system (OBMS) has previously been shown to be able to represent five commonly used theories in this way. We aimed to assess whether the OBMS could be applied more widely and to create a database of behaviour change theories, their constructs and propositions. Methods: We labelled the constructs within 71 theories and used the OBMS to represent the relationships between the constructs. Diagrams of each theory were sent to authors or experts for feedback and amendment. The 71 finalised diagrams plus the five previously generated diagrams were used to create a searchable database of 76 theories in the form of construct-relationship-construct triples. We conducted a set of illustrative analyses to characterise theories in the database. Results: All 71 theories could be satisfactorily represented using this system. In total, 35 (49%) were finalised with no or very minor amendment. The remaining 36 (51%) were finalised after changes to the constructs (seven theories), relationships between constructs (15 theories) or both (14 theories) following author/expert feedback. The mean number of constructs per theory was 20 (min. = 6, max. = 72), with the mean number of triples per theory 31 (min. = 7, max. = 89). Fourteen distinct relationship types were used, of which the most commonly used was 'influences', followed by 'part of'. Conclusions: The OBMS can represent a wide array of behavioural theories in a precise, computable format. This system should provide a basis for better integration and synthesis of theories than has hitherto been possible.info:eu-repo/semantics/publishedVersio

Do Combinations of Behavior Change Techniques That Occur Frequently in Interventions Reflect Underlying Theory?

BACKGROUND: Behavioral interventions typically include multiple behavior change techniques (BCTs). The theory informing the selection of BCTs for an intervention may be stated explicitly or remain unreported, thus impeding the identification of links between theory and behavior change outcomes. PURPOSE: This study aimed to identify groups of BCTs commonly occurring together in behavior change interventions and examine whether behavior change theories underlying these groups could be identified. METHODS: The study involved three phases: (a) a factor analysis to identify groups of co-occurring BCTs from 277 behavior change intervention reports; (b) examining expert consensus (n = 25) about links between BCT groups and behavioral theories; (c) a comparison of the expert-linked theories with theories explicitly mentioned by authors of the 277 intervention reports. RESULTS: Five groups of co-occurring BCTs (range: 3-13 BCTs per group) were identified through factor analysis. Experts agreed on five links (≥80% of experts), comprising three BCT groups and five behavior change theories. Four of the five BCT group-theory links agreed by experts were also stated by study authors in intervention reports using similar groups of BCTs. CONCLUSIONS: It is possible to identify groups of BCTs frequently used together in interventions. Experts made shared inferences about behavior change theory underlying these BCT groups, suggesting that it may be possible to propose a theoretical basis for interventions where authors do not explicitly put forward a theory. These results advance our understanding of theory use in multicomponent interventions and build the evidence base for further understanding theory-based intervention development and evaluation

Development of an online tool for linking behavior change techniques and mechanisms of action based on triangulation of findings from literature synthesis and expert consensus.

Researchers, practitioners, and policymakers develop interventions to change behavior based on their understanding of how behavior change techniques (BCTs) impact the determinants of behavior. A transparent, systematic, and accessible method of linking BCTs with the processes through which they change behavior (i.e., their mechanisms of action [MoAs]) would advance the understanding of intervention effects and improve theory and intervention development. The purpose of this study is to triangulate evidence for hypothesized BCT-MoA links obtained in two previous studies and present the results in an interactive, online tool. Two previous studies generated evidence on links between 56 BCTs and 26 MoAs based on their frequency in literature synthesis and on expert consensus. Concordance between the findings of the two studies was examined using multilevel modeling. Uncertainties and differences between the two studies were reconciled by 16 behavior change experts using consensus development methods. The resulting evidence was used to generate an online tool. The two studies showed concordance for 25 of the 26 MoAs and agreement for 37 links and for 460 "nonlinks." A further 55 links were resolved by consensus (total of 92 [37 + 55] hypothesized BCT-MoA links). Full data on 1,456 possible links was incorporated into the online interactive Theory and Technique Tool (https://theoryandtechniquetool.humanbehaviourchange.org/). This triangulation of two distinct sources of evidence provides guidance on how BCTs may affect the mechanisms that change behavior and is available as a resource for behavior change intervention designers, researchers and theorists, supporting intervention design, research synthesis, and collaborative research.MR

A systematic review and meta-analysis of the outcome expectancy construct in physical activity research

Cognition-based theories dominate physical activity (PA) research, and many include a construct broadly defined as ‘beliefs about the consequences of behavior’ (e.g. outcome expectancies, perceived benefits) hereafter referred to as perceived consequences. With the quantity of available research on this topic, it is important to examine whether the literature supports perceived consequences as a predictor of PA. A meta-analysis examining longitudinal associations between perceived consequences and PA in adults was conducted. Studies were eligible if (a) perceived consequences were measured at a time point prior to PA, and (b) the target behavior was a form of PA. This search yielded 6,979 articles, of these, 110 studies met the inclusion criteria. Studies were published between 1989 and 2020, with sample sizes ranging from 16 to 2,824. All studies were evaluated as moderate to high quality. A small positive bivariate association was identified (r = 0.11; 95% CI [0.09, 0.13]) between perceived consequences and PA. Significant bivariate associations were also identified for time, health, self-evaluative, psychological, and affective perceived consequences. There was no association between perceived weight-related consequences and PA. These findings suggest utility in examining perceived consequences as a predictor of PA, but constructs with more robust associations may require priority

Behaviour change techniques and their mechanisms of action: a synthesis of links described in published intervention literature

Background: Despite advances in behavioural science, there is no widely shared understanding of the ‘mechanisms of action’ (MoAs) through which individual behaviour change techniques (BCTs) have their effects. Cumulative progress in the development, evaluation and synthesis of behavioural interventions could be improved by identifying the MoAs through which BCTs are believed to bring about change. Purpose: This study aimed to identify the links between BCTs and MoAs described by authors of a corpus of published literature. Methods: Links between BCTs and MoAs were extracted by two coders from 277 behaviour change intervention articles. Binomial tests were conducted to provide an indication of the relative frequency of each link. Results: Of 77 BCTs coded, 70 were linked to at least one MoA. Of 26 MoAs, all but one were linked to at least one BCT. We identified 2636 BCT-MoA links in total (mean number of links per article = 9.56, SD = 13.80). The most frequently linked MoAs were ‘Beliefs about Capabilities’ and ‘Intention’. Binomial test results identified up to five MoAs linked to each of the BCTs (M = 1.71, range: 1-5), and up to eight BCTs for each of the MoAs (M = 3.63, range: 1-8). Conclusions: The BCT-MoA links described by intervention authors and identified in this extensive review present intervention developers and reviewers with a first level of systematically collated evidence. These findings provide a resource for the development of theory-based interventions, and for theoretical understanding of intervention evaluations. The extent to which these links are empirically supported requires systematic investigation