Some habits are more work than others:Deliberate self-regulation strategy use increases with behavioral complexity, even for established habits

Objective: We tested the hypothesis that complex behaviors are commonly supported by self-regulation strategies, even when those behaviors are supported by strong instigation habits. Background: Goal-directed and habit-mediated processes arise from separable systems that have been suggested to seldomly interact. Results: Self-regulation strategy use was lower for habitually instigated simple behaviors compared to nonhabitually instigated simple behaviors. However, participants' use of self-regulation strategies increased with the increasing complexity of behaviors, even when complex behaviors were habitually instigated. The difference in the extent of strategy use between habitually and nonhabitually instigated actions was absent when behavioral complexity was particularly high. Conclusion: These results point to a qualitative distinction—while simple behaviors may progress in a relatively automatic and unthinking manner, complex behaviors receive frequent support from self-regulation strategies, even if they are instigated habitually.</p

Some habits are more work than others:Deliberate self-regulation strategy use increases with behavioral complexity, even for established habits

Objective: We tested the hypothesis that complex behaviors are commonly supported by self-regulation strategies, even when those behaviors are supported by strong instigation habits. Background: Goal-directed and habit-mediated processes arise from separable systems that have been suggested to seldomly interact. Results: Self-regulation strategy use was lower for habitually instigated simple behaviors compared to nonhabitually instigated simple behaviors. However, participants' use of self-regulation strategies increased with the increasing complexity of behaviors, even when complex behaviors were habitually instigated. The difference in the extent of strategy use between habitually and nonhabitually instigated actions was absent when behavioral complexity was particularly high. Conclusion: These results point to a qualitative distinction—while simple behaviors may progress in a relatively automatic and unthinking manner, complex behaviors receive frequent support from self-regulation strategies, even if they are instigated habitually.</p

The utility of the integrated behavior change model as an extension of the theory of planned behavior

INTRODUCTION: There are several widely used theories of health behavior change, which mostly utilize the social cognitive approach. These theories tend to posit that intention is a direct predictor of behavior, do not include automatic influences on behavior, and propose a one-size-fits-all theory for both initiators and maintainers. However, the intention-behavior gap is a well-observed phenomenon, researchers have highlighted that both automatic and reflective factors promote behavioral engagement, and predictors of behavior have been shown to differ between initiators and maintainers—three issues that necessitate theory advancement. To that end, the present research compares the utility of the Integrated Behavior Change Model (IBCM) – a social cognitive model that includes automatic factors involved in behavioral engagement and a moderator of the intention-behavior gap – to its theoretical predecessor, the Theory of Planned Behavior (TPB). Further, the relevance of the IBCM factors for predicting exercise behavior is compared in initiators versus maintainers. METHOD: Participants were 494 US undergraduates. Participants reported on variables from the IBCM (and TPB) at baseline and reported on their exercise behavior in two surveys at seven- and 14-days post-baseline. RESULTS: Findings supported the first hypothesis that the IBCM would be more relevant for initiators in comparison with maintainers, using structural equation modeling. Specifically, only the paths between intrinsic motivation and affective attitude, affective attitude and intention, and intention and behavior were reliably found for maintainers. For initiators, the aforementioned paths were also reliably supported and the additional following paths were also supported: intrinsic motivation and perceived behavioral control, perceived behavioral control and intention, and intention and action planning. However, results did not support the second hypothesis that the IBCM would predict significantly more variance in behavior than its theoretical predecessor, the TPB. Specifically, the addition of action planning, implicit attitude, implicit motivation, and the interaction between intention and action planning only predicted an additional 0.3% (p < 0:05) of the variance in exercise behavior above and beyond intention. CONCLUSION: Results highlight the continued need for theoretical refinement in terms of delineating mechanisms of initiation and maintenance and the need for further development in terms of improving upon current predictions of behavior engagement and change

PAYING PARTICIPANTS:THE IMPACT OF COMPENSATION ON DATA QUALITY

Poor-quality data has the potential to increase error variance, reduce statistical power and effect sizes, and produce Type I or Type II errors. Paying participants is one technique researchers may use in an attempt to obtain high-quality data. Accordingly, two secondary datasets were used to examine the relationship between participant payment and data quality. The first dataset revealed that data quality did not differ between paid and unpaid undergraduates. Similarly, the second dataset showed that data quality did not differ between unpaid community participants and MTurkers. A comparison across studies showed that undergraduate students engaged in lower levels of careless responding than the community samples but the unpaid community sample outperformed the MTurk sample and both undergraduate samples. Taken together, the current findings suggest that offering financial incentives to undergraduate or community samples does not improve data quality but may improve data collection rates and increase the diversity of participants.</p

Psychometric Validation of Four-Item Exercise Identity and Healthy-Eater Identity Scales and Applications in Weight Loss Maintenance

Background: Identifying as someone who engages in health promoting behaviors like healthy eating and exercising may be associated with sustained engagement in those behaviors, but reliable and valid instruments are needed to improve the rigor of this research. Two studies were conducted to (1) examine the psychometric properties of a four-item exerciser identity measure (4-EI) and an adapted healthy-eater identity measure (4-HEI) and (2) examine differences in identity strengths across categories of weight loss success. Methods: Data from 1,709 community dwelling adults in the International Weight Control Registry (IWCR) were used. A random half of the sample was used to assess the proposed unidimensional factor structure of the 4-EI and 4-HEI and examine convergent and discriminant validity using Spearman rank-order correlations. One-way ANOVA was used in the other random half of the sample to compare 4-EI and 4-HEI scores (-3 to + 3) across three self-defined weight loss categories (‘Successful’, ‘Regain’, and ‘Unsuccessful’) and those maintaining ≥ 5% weight loss for &gt; 1 year vs. not. Results: Results support the unidimensional factor structure with all four items (eigenvalue scores &gt; 2.89) as well as convergent and discriminant validity for both measures. Exercise identity was strongly correlated with self-reported physical activity (r (735) = 0.52, p &lt;.001) and measures of autonomous motivation. Healthy eating identity was moderately correlated with cognitive restraint in eating (r (744) = 0.42, p &lt;.001) and other measures predictive of eating behavior. 4-EI and 4-HEI are stronger in Successful (4-EI: M = 0.90, SD = 1.77; 4-HEI: M = 1.56 SD = 1.37) vs. Regain (4-EI: M=-0.18, SD = 1.68; 4-HEI: M =.57, SD = 1.48) and Unsuccessful (4-EI:M=-0.28, SD = 1.62; 4-HEI: M = 0.51, SD = 1.33) and those maintaining ≥ 5% weight loss (4-EI:M = 0.47, SD = 1.78; 4-HEI: M = 1.13, SD = 1.49) vs. not (4-EI:M=-0.27, SD = 1.66; 4-HEI: M = 0.53, SD = 1.47), p’s &lt; 0.001. Conclusions: The 4-EI and 4-HEI have acceptable psychometric properties and can advance understanding of the role of identity in exercise and dietary behaviors and weight loss maintenance. Trial registration: The parent observational study, International Weight Control Registry (IWCR), for these sub-studies is registered in ClinicalTrials.gov (NCT04907396).</p

An Updated Review of Interventions that Include Promotion of Physical Activity for Adult Men

The marked disparity in life expectancy between men and women suggests men are a vulnerable group requiring targeted health promotion programs. As such, there is an increasing need for health promotion strategies that effectively engage men with their health and/or illness management. Programs that promote physical activity could significantly improve the health of men. Although George et al. (Sports Med 42(3):281, 30) reviewed physical activity programs involving adult males published between 1990 and 2010, developments in men’s health have prompted the emergence of new sex- and gender-specific approaches targeting men. The purpose of this review was to: (1) extend and update the review undertaken by George et al. (Sports Med 42(3):281, 30) concerning the effectiveness of physical activity programs in males, and (2) evaluate the integration of gender-specific influences in the content, design, and delivery of men’s health promotion programs. A search of MEDLINE, CINAHL, ScienceDirect, Web of Science, PsycINFO, the Cochrane Library, and the SPORTDiscus databases for articles published between January 2010 and August 2014 was conducted. In total, 35 studies, involving evaluations of 31 programs, were identified. Findings revealed that a variety of techniques and modes of delivery could effectively promote physical activity among men. Though the majority of programs were offered exclusively to men, 12 programs explicitly integrated gender-related influences in male-specific programs in ways that recognized men’s interests and preferences. Innovations in male-only programs that focus on masculine ideals and gender influences to engage men in increasing their physical activity hold potential for informing strategies to promote other areas of men’s health

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Psychometric Validation of Four-Item Exercise Identity and Healthy-Eater Identity Scales and Applications in Weight Loss Maintenance

Background: Identifying as someone who engages in health promoting behaviors like healthy eating and exercising may be associated with sustained engagement in those behaviors, but reliable and valid instruments are needed to improve the rigor of this research. Two studies were conducted to (1) examine the psychometric properties of a four-item exerciser identity measure (4-EI) and an adapted healthy-eater identity measure (4-HEI) and (2) examine differences in identity strengths across categories of weight loss success. Methods: Data from 1,709 community dwelling adults in the International Weight Control Registry (IWCR) were used. A random half of the sample was used to assess the proposed unidimensional factor structure of the 4-EI and 4-HEI and examine convergent and discriminant validity using Spearman rank-order correlations. One-way ANOVA was used in the other random half of the sample to compare 4-EI and 4-HEI scores (-3 to + 3) across three self-defined weight loss categories (‘Successful’, ‘Regain’, and ‘Unsuccessful’) and those maintaining ≥ 5% weight loss for &gt; 1 year vs. not. Results: Results support the unidimensional factor structure with all four items (eigenvalue scores &gt; 2.89) as well as convergent and discriminant validity for both measures. Exercise identity was strongly correlated with self-reported physical activity (r (735) = 0.52, p &lt;.001) and measures of autonomous motivation. Healthy eating identity was moderately correlated with cognitive restraint in eating (r (744) = 0.42, p &lt;.001) and other measures predictive of eating behavior. 4-EI and 4-HEI are stronger in Successful (4-EI: M = 0.90, SD = 1.77; 4-HEI: M = 1.56 SD = 1.37) vs. Regain (4-EI: M=-0.18, SD = 1.68; 4-HEI: M =.57, SD = 1.48) and Unsuccessful (4-EI:M=-0.28, SD = 1.62; 4-HEI: M = 0.51, SD = 1.33) and those maintaining ≥ 5% weight loss (4-EI:M = 0.47, SD = 1.78; 4-HEI: M = 1.13, SD = 1.49) vs. not (4-EI:M=-0.27, SD = 1.66; 4-HEI: M = 0.53, SD = 1.47), p’s &lt; 0.001. Conclusions: The 4-EI and 4-HEI have acceptable psychometric properties and can advance understanding of the role of identity in exercise and dietary behaviors and weight loss maintenance. Trial registration: The parent observational study, International Weight Control Registry (IWCR), for these sub-studies is registered in ClinicalTrials.gov (NCT04907396).</p