Cost and cost-effectiveness analysis of a digital diabetes prevention program: results from the PREDICTS trial.

Although technology-assisted diabetes prevention programs (DPPs) have been shown to improve glycemic control and weight loss, information are limited regarding relevant costs and their cost-effectiveness. To describe a retrospective within-trial cost and cost-effectiveness analysis (CEA) to compare a digital-based DPP (d-DPP) with small group education (SGE), over a 1-year study period. The costs were summarized into direct medical costs, direct nonmedical costs (i.e., times that participants spent engaging with the interventions), and indirect costs (i.e., lost work productivity costs). The CEA was measured by the incremental cost-effectiveness ratio (ICER). Sensitivity analysis was performed using nonparametric bootstrap analysis. Over 1 year, the direct medical costs, direct nonmedical costs, and indirect costs per participant were $4,556, $1,595, and $6,942 in the d-DPP group versus $4,177, $1,350, and $9,204 in the SGE group. The CEA results showed cost savings from d-DPP relative to SGE based on a societal perspective. Using a private payer perspective for d-DPP, ICERs were $4,739 and $114 to obtain an additional unit reduction in HbA1c (%) and weight (kg), and were $19,955 for an additional unit gain of quality-adjusted life years (QALYs) compared to SGE, respectively. From a societal perspective, bootstrapping results indicated that d-DPP has a 39% and a 69% probability, at a willingness-to-pay of $50,000/QALY and $100,000/QALY, respectively, of being cost-effective. The d-DPP was cost-effective and offers the prospect of high scalability and sustainability due to its program features and delivery modes, which can be easily translated to other settings.

Although technology-assisted DPPs have been shown to improve glycemic control and/or weight loss, information is limited on examining relevant costs and the cost-effectiveness of DPPs with the use of remote technologies within a randomized controlled trial design. We evaluated the costs associated with a d-DPP and further examined the cost-effectiveness of the d-DPP with an enhanced usual care condition. The d-DPP was cost-effective in achieving HbA1c reduction and weight loss and offers the prospect of high scalability and sustainability due to its program features and delivery modes, which can be easily translated to other settings.

Effects of a digital diabetes prevention program on cardiovascular risk among individuals with prediabetes.

OBJECTIVE: To examine changes in cardiovascular disease (CVD) risk outcomes of overweight/obese adults with prediabetes. METHODS: Using data from a randomized control trial of digital diabetes prevention program (d-DPP) with 599 participants. We applied the atherosclerotic CVD (ASCVD) risk calculator to predict 10-year CVD risk for d-DPP and small education (comparison) groups. Between-group risk changes at 4 and 12 months were compared using a repeated measures linear mixed-effect model. We examined within-group differences in proportion of participants over time for specific CVD risk factors using generalized estimating equations. RESULTS: We found no differences between baseline 10-year ASCVD risk. Relative to the comparison group, the d-DPP group experienced greater reductions in predicted 10-year ASCVD risk at each follow-up visit and a significant group difference at 4 months (-0.96%; 95% confidence interval: -1.58%, -0.34%) (but not at 12 months). Additionally, we observed that the d-DPP group experienced a decreased proportion of individuals with hyperlipidemia (18% and 16% from baseline to 4 and 12 months), high-risk total cholesterol (8% from baseline to 12 months), and being insufficiently active (26% and 22% from baseline to 4 and 12 months at follow-up time points. CONCLUSIONS: Our findings suggest that a digitally adapted DPP may promote the prevention of cardiometabolic disease among overweight/obese individuals with prediabetes. However, given the lack of maintenance of effect on ASCVD risk at 12 months, there may also be a need for additional interventions to sustain the effect detected at 4 months.

Effects of a Digital Diabetes Prevention Program: An RCT.

INTRODUCTION: In light of the need to expand the reach and access of clinically proven digital Diabetes Prevention Programs (d-DPPs) and the need for rigorous evidence of effectiveness, the purpose of this study was to determine the effectiveness of a digital Diabetes Prevention Program for improving weight, HbA1c, and cardiovascular risk factors among people with prediabetes compared to enhanced standard care plus waitlist control. STUDY DESIGN: This was a single-blind RCT among participants at risk of developing type 2 diabetes and included 12 months of follow-up. SETTING/PARTICIPANTS: A total of 599 volunteer patients with prediabetes were recruited primarily through electronic medical records and primary care practices. INTERVENTION: Participants were randomized to either a d-DPP (n=299) or a single-session small-group diabetes-prevention education class (n=300) focused on action planning for weight loss. The d-DPPs consisted of 52 weekly sessions, lifestyle coaching, virtual peer support, and behavior tracking tools. MAIN OUTCOME MEASURES: The primary outcome was a change in HbA1c from baseline to 12 months using intent-to-treat analyses. On the basis of multiple comparisons of endpoints, 95% CIs are presented and 2-sided p<0.025 was required for statistical significance. Secondary outcomes included body weight and cardiovascular disease risk factors. RESULTS: Among 599 randomized participants (mean age=55.4 years, 61.4% women), 483 (80%) completed the study. The d-DPPs produced significantly greater reductions in HbA1c (0.08%, 95% CI= -0.12, -0.03) and percentage change in body weight (-5.5% vs -2.1%, p<0.001) at 12 months. A greater proportion of the d-DPPs group achieved a clinically significant weight loss ≥5% (43% vs 21%, p<0.001), and more participants shifted from prediabetes to normal HbA1c range (58% vs 48%, p=0.04). Engagement in d-DPPs was significantly related to improved HbA1c and weight loss. CONCLUSIONS: This d-DPPs demonstrated clinical effectiveness and has significant potential for widespread dissemination and impact, particularly considering the growing demand for telemedicine in preventive healthcare services. TRIAL REGISTRATION: This study is registered at www. CLINICALTRIALS: gov (ClinicalTrials.gov Identifier: NCT03312764).

Does environmental message framing impact proportional reach and sample representativeness related to motivational characteristics?

Physical activity (PA) promotion messages are commonly used to engage target populations in PA programs. However, little is known about how recruitment messages impact program reach. Evidence suggests that framing messages to be congruent with individuals' motivational orientation can maximize effectiveness. This congruency effect has not been tested in the context of brief PA promotion messages used in a recruitment environment. It is plausible that framed messages attract certain individuals, while deterring others. The purpose of this study was to determine whether message framing influences representativeness of a sample recruited for a PA program with regards to motivational factors. Three messaging conditions (gain-framed, neutral, loss-framed) were counterbalanced across days of data collection in a primary care waiting room. Patients were asked to complete a questionnaire including surveys on personality and PA, and basic demographic questions. Respondents were offered the chance to participate in a low-burden PA program. Interested respondents were instructed to provide contact information. The proportion and representativeness, with respect to motivational orientation, of individuals volunteering for program participation was assessed using chi-squared tests, and two-way (condition × group) ANOVAs, respectively. After controlling for demographic and behavioral covariates, there was no effect of message framing on the motivational orientation of the resultant samples. Results did not support a congruency effect of a covert message-framing manipulation. More work should aim to understand how recruitment materials and strategies influence motivational characteristics of the resulting sample to maximize intervention outcomes, and target individuals who are more likely to engage in risky health behaviors.

Associations Between Change Over Time in Pandemic-Related Stress and Change in Physical Activity.

BACKGROUND: Physical activity (PA) mitigated psychological distress during the initial weeks of the COVID-19 pandemic, yet not much is known about whether PA had effects on stress in subsequent months. We examined the relationship between change over time in COVID-related stress and self-reported change in PA between March and July 2020. METHODS: Latent growth modeling was used to examine trajectories of change in pandemic-related stress and test their association with self-reported changes in PA in an international sample (n = 679). RESULTS: The participants reported a reduction in pandemic-related stress between April and July of 2020. Significant linear (factor mean = -0.22) and quadratic (factor mean = 0.02) changes (Ps < .001) were observed, indicating a deceleration in stress reduction over time. Linear change was related to change in PA such that individuals who became less active during the pandemic reported less stress reduction over time compared with those who maintained or increased their PA during the pandemic. CONCLUSIONS: Individuals who experienced the greatest reduction in stress over time during the pandemic were those who maintained their activity levels or became more active. Our study cannot establish a causal relationship between these variables, but the findings are consistent with other work showing that PA reduces stress.

Psychometric assessment of the Brief Weight-Loss-Related Behavior Self-Efficacy Survey in adults with prediabetes.

Self-efficacy is a commonly examined cognitive determinant of behavior change in weight-loss trials, but there has been little uniformity in its measurement. To address this, a recently developed survey captures self-efficacy as it relates to three behavioral domains of interest to weight-loss interventionists: physical activity (PA), healthful eating, and weight loss. The purpose of this study was to test the psychometric properties of the Brief Weight-Loss-Related Behavior Self-Efficacy Scales in a large sample (n = 599) of adults with prediabetes. Participants completed the self-efficacy survey, as well as measures of PA, dietary intake, weight, and height. The factor structure was scrutinized using exploratory and confirmatory factor analysis, which supported a factor structure with three correlated first-order latent self-efficacy factors, specific to PA, healthful eating, and weight loss. This model is statistically equivalent to a hierarchical model including a second-order factor for overall behavioral weight-management self-efficacy. Measurement equivalence/invariance between relevant demographic groups was also supported by tests for equivalence of covariance matrices. Bivariate correlations between self-efficacy factors and measures of PA, dietary intake, and weight support the concurrent validity of score interpretations. Overall, these psychometric analyses support the validity of these scales' scores as independently reflective of self-efficacy for PA, healthful eating, and weight loss. This instrument is useful in clinical research to identify the cognitive drivers of weight loss and weight loss-inducing behavior. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

An observation of the impact of tailored messages on participant non-compliance during Desire2Move.

We assessed the impact of tailored versus targeted messages on program non-compliance during Desire2Move (D2M), an 8-week eHealth program that promotes physical activity (PA). Participants recorded minutes of PA using MapMyFitness, which counted toward their departments' PA total. Departments were randomized into the targeted messaging (TM) or tailored messaging (TM+) group based on participant-reported goals. Participants who did not provide a goal were assigned to the control group (CG). Eligible participants were employees from invited departments who were non-compliant for at least 1 week of D2M. Upon initial non-compliance, participants across groups received a targeted email message prompting program resumption. For subsequent non-compliance, the TM group continued to receive the same targeted message. The TM+ group received a message tailored to the participant's program goal. The CG group did not receive additional messages. Participants (n = 149) were mostly female (68.5%), staff (44.3%), with an average age of 43.7 (SD = 11.1). Analyses revealed significant group differences in non-compliance between TM+ (M = 2.6, SD = 1.9) and TM (M = 4.0, SD = 2.1), F(16,88) = 3.4, p < .01; d = .64, and between TM+ (M = 2.6, SD = 1.9) and CG (M = 3.8, SD = 2.1), F(1,74) = 13.3, p < .01; d = .56. There was no significant group difference between TM and CG, F(1,80) = 0.1, p = .75; d = .02. Tailored messages improved individual program compliance. More research is needed to assess the relationship between program compliance and PA behavior change.

We compared the influence of tailored messages and targeted messages on participant non-compliance (defined as not logging any activity during a program week) during an 8-week eHealth program that encourages university employees to engage in physical activity (PA). Participants received targeted or tailored email message to encourage participants to begin logging PA again. Tailored messages improved individual program non-compliance.

Using a population health management approach to enroll participants in a diabetes prevention trial: reach outcomes from the PREDICTS randomized clinical trial.

Population health management (PHM) strategies to address diabetes prevention have the potential to engage large numbers of at-risk individuals in a short duration. We examined a PHM approach to recruit participants to a diabetes prevention clinical trial in a metropolitan health system. We examined reach and representativeness and assessed differences from active and passive respondents to recruitment outreach, and participants enrolled through two clinical screening protocols. The PHM approach included an electronic health record (EHR) query, physician review of identified patients, letter invitation, and telephone follow-up. Data describe the reach and representativeness of potential participants at multiple stages during the recruitment process. Subgroup analyses examined proportional reach, participant differences based on passive versus active recruitment response, and clinical screening method used to determine diabetes risk status. The PHM approach identified 10,177 potential participants to receive a physician letter invitation, 60% were contacted by telephone, 2,796 (46%) completed telephone screening, 1,961 were eligible from telephone screen, and 599 were enrolled in 15 months. Accrual was unaffected by shifting clinical screening protocols despite the increase in participant burden. Relative to census data, study participants were more likely to be obese, female, older, and Caucasian. Relative to the patient population, enrolled participants were less likely to be Black and were older. Active respondents were more likely to have a higher income than passive responders. PHM strategies have the potential to reach a large number of participants in a relatively short period, though concerted efforts are needed to increase participant diversity.

Physical activity partially mediates associations between "Big" personality traits and incident generalized anxiety disorder: Findings from the irish longitudinal study on ageing.

BACKGROUND: This study aimed to examine associations of personality with generalized anxiety disorder (GAD) and physical activity (PA), PA with GAD, and PA mediates associations between personality and incident GAD. METHODS: Participants aged ≥50 years completed the 60-item NEO-Five Factor Inventory questionnaire to assess personality and short-form International Physical Activity Questionnaire at baseline, and the Composite International Diagnostic Interview - Short Form to clinically assess GAD at baseline and 2, 4, and 6 years later. Participants who had GAD at baseline or reported having ever been told by a doctor that they had anxiety were excluded from analyses. Binary logistic regression quantified associations of the 'Big Five' personality traits with PA and incident GAD, and associations of PA with incident GAD (i.e., GAD at any point during follow-up). The 'counterfactual approach' identified potential mediating effects of PA in the associations between personality traits and incident GAD. RESULTS: Participants (n = 4582; 53.7% female) were aged 64.38±8.88 years. Incidence of GAD was 2.95% (n = 135). Extraversion (OR=1.160, 95%CI=1.087-1.237), openness (1.113, 1.043-1.188), and conscientiousness (1.083, 1.015-1.155) were positively associated with physical activity. Neuroticism was positively (2.335, 1.945-2.803), and extraversion (0.700, 0.563-0.797), conscientiousness (0.826, 0.693-0.985), and PA (0.655, 0.451-0.952) were inversely, associated with the incident GAD. Approximately 8.7% of the effect of extraversion and 8.8% of the effect of conscientiousness on GAD was due to mediation by PA only. LIMITATIONS: PA was self-reported Conclusions: Personality screening may help to identify older adults at-risk of anxiety who would benefit from participation in physical activity interventions.

Physical Activity Promotion Message Perceptions Biased by Motivational Dispositions.

BACKGROUND: The delivery of physical activity (PA) promotion messages is an important component of any PA intervention. Gain-framed messages appear beneficial for prevention (rather than detection) behaviors such as PA, but the effects are small and inconsistent. It is possible that these effects are moderated by motivational traits, but this has not been systematically tested in the context of PA promotion messages. This study tested whether motivational traits interact with message features to influence basic subjective perceptions of a standardised set of very brief PA promotion statements. METHODS: Fifteen statements were developed across five conditions, manipulated according to frame and kernel state. Participants (n = 800) rated statement content using semantic differential scales reflecting perceived gains/losses, costs/benefits, and positive/negative outcomes. Traits and PA were measured by survey. RESULTS: Structural equation models revealed that ratings of gain-framed statements were positively related to approach motivation, and ratings of loss-framed statements were negatively related to avoidance motivation. CONCLUSIONS: Observations support the presence of a congruency effect of motivational traits and message frame on basic perceptions of message content. Future studies should test the impact of these biases on indices of persuasion (attitude and intention) as well as intervention reach and effectiveness.

The impact of pairing a wearable movement tracker with an online community weight loss intervention.

Evidence supports the use of technology supported multicomponent interventions for promoting weight loss. Many such programs include the opportunity to synchronously pair commercially available physical activity trackers (PA-T) with a goal to enhance weight loss outcomes. However, little is known about the reach and effectiveness of allowing participants to pair a PA-T within an existing online program. PURPOSE: This matched cohort, quasi-experimental study aimed to determine 1) the proportion of participants that pair a PA-T to the existing program, 2) the representativeness of participants who pair a PA-T; 3) the relationship between pairing a PA-T, overall weight loss, and the likelihood of achieving a clinically meaningful weight loss; and 4) if pairing a PA-T with program participation is related to weight loss outcomes independently or collectively when considering other indices of program engagement. METHODS: Data collected over a four-year period included demographic self-report, objective weight data uploaded when participants weighed themselves at a self-serve program kiosk available to the community, and program engagement data (e.g., logins to program website). A range of analyses, including descriptive proportions, analyses of variance, and path analyses, were used to address the purposes of the study. RESULTS: Participants who paired a PA-T were more likely to be women (p<.001), African American (p<.001), and have a higher BMI (p<.05). Those who paired a PA-T lost on average an extra 1% body weight and were 1.4 times more likely to lose 5% body weight. Pairing a PA-T was related to other indices of online program engagement and both directly and indirectly contributed to weight loss outcomes (p<.05). CONCLUSIONS: Pairing a PA-T within an online weight loss program appeals to groups that experience disparities related to obesity and predicts improvements in weight loss. More translational studies are needed to examine the role of personal psychosocial and environmental factors that may enhance or diminish the benefit of pairing a PA-T to evidence-based, online weight loss programs.

Preventing diabetes with digital health and coaching for translation and scalability (PREDICTS): A type 1 hybrid effectiveness-implementation trial protocol.

BACKGROUND: Diabetes prevention remains a top public health priority; digital approaches are potential solutions to existing scalability and accessibility challenges. There remains a gap in our understanding of the relationship between effectiveness, costs, and potential for sustained implementation of digital diabetes prevention strategies within typical healthcare settings. PURPOSE: To describe the methods and design of a type 1 hybrid effectiveness-implementation trial of a digital diabetes prevention program (DPP) using the iPARIHS and RE-AIM frameworks. METHODS: The trial will contrast the effects of two DPP interventions: (1) small group, in-person class, and (2) a digital DPP consisting of small group support, personalized health coaching, digital tracking tools, and weekly behavior change curriculum. Each intervention includes personal action planning with a focus on key elements of the lifestyle intervention from the CDC National DPP. Adults at risk for diabetes (BMI ≥25 and 5.7% ≤ HbA1c ≤ 6.4) will be randomly assigned to either the intervention group (n = 241) or the small group (n = 241). Assessment of primary (HbA1c) and secondary (weight loss, costs, cardiovascular risk factors) outcomes will occur at baseline, 4, and 12 months. Additionally, the trial will explore the potential for future adoption, implementation, and sustainability of the digitally-based intervention within a regional healthcare system based on key informant interviews and assessments of organizational administrators and primary care physicians. CONCLUSION: This trial of a digital DPP will allow the research team to determine the relationships between reach, effectiveness, implementation, and costs.

Cost effectiveness and return on investment of a scalable community weight loss intervention.

This study assessed the lifetime health and economic consequences of an efficacious scalable community weight loss program for overweight and obese adults. We applied a state-transition Markov model to project lifetime economic outcome (US dollar) and the degree of disease averted as a result of a weight loss intervention, compared with no intervention, from a payer perspective. Effect sizes of the intervention on weight loss, by sex, race and ethnicity, and body mass index (BMI) of participants, were derived from a 12-month community program. Relative risk of diseases across BMI levels and other parameters were informed by the literature. A return on investment (ROI) analysis was conducted to present the overall cost-benefit of the program. Simulation results showed that among 33,656 participants and at a cost of $2.88 million, the program was predicted to avert (with a corresponding estimated medical costs saved of) 78 cases of coronary heart disease ($28 million), 9 cases of strokes ($971,832), 92 cases of type 2 diabetes ($24 million), 1 case of colorectal cancer ($357,022), and 3 cases of breast cancer ($483,259) over the participant lifetime. The estimated medical costs saved per participant was $1403 ($1077 of African American men and $1532 of Hispanic men), and the ROI was $16.7 ($12.8 for African American men and $18.3 for Hispanic men) for every $1 invested. We concluded that a scalable efficacious community weight loss program provides a cost-effective approach with significant ROI, which will assist informed decisions for future adoption and dissemination.

A Quasi-Experiment to Assess the Impact of a Scalable, Community-Based Weight Loss Program: Combining Reach, Effectiveness, and Cost.

BACKGROUND: Primary care addresses obesity through physician oversight of intensive lifestyle interventions or referral to external programs with demonstrated efficacy. However, limited information exists on community program reach, effectiveness, and costs across different groups of participants. OBJECTIVE: To evaluate a scalable, community weight loss program using reach, effectiveness, and cost metrics. DESIGN: Longitudinal pre-post quasi-experiment without control. PARTICIPANTS: Enrolled participants in Weigh and Win (WAW), a community-based weight loss program. INTERVENTION: A 12-month program with daily social cognitive theory-based email and/or text support, online access to health coaches, objective weight assessment through 83 community-based kiosks, and modest financial incentives to increase program reach. MAIN MEASURES: Number of participants, representativeness, weight loss achievement (3%, 5% of initial weight lost), and cost of implementation. KEY RESULTS: A total of 40,308 adults (79% women; 73% white; BMI = 32.3 ± 7.44, age = 43.9 ± 13.1 years) enrolled in WAW. Women were more likely than men to enroll in the program and continue engagement beyond an initial weigh-in (57% vs. 53%). Based on census data, African Americans were over-represented in the sample. Among participants who engaged in the program beyond an initial weigh-in (n = 19,029), 47% and 34% of participants lost 3% and 5% of their initial body weight, respectively. The average duration for those who achieved 5% weight loss was 1.7 ± 1.3 years. African American participants were more likely to achieve 5% weight loss and remain enrolled in the program longer compared to non-African American participants (2.0 ± 1.3 vs. 1.6 ± 1.2 years). Implementation costs were $2,822,698. Cost per clinically meaningful weight loss for African Americans ($257.97/3% loss; $335.96/5% loss) was lower than that for Hispanics ($318.62; $431.10) and Caucasians ($313.65; $441.87), due to the higher success rate of that subgroup of participants. CONCLUSIONS: Weigh and Win is a scalable technology-supported and community-based weight loss program that reaches a large number of participants and may contribute to reducing health disparities.

Informing the development and uptake of a weight management intervention for preconception: a mixed-methods investigation of patient and provider perceptions.

BACKGROUND: It is recommended for women to have a healthy body mass index before conception. However, there is limited research on appropriate preconception interventions for weight loss. Furthermore, there is a lack of knowledge on providers' willingness to refer to particular behavioral interventions and the degree to which patients would attend those interventions. METHODS: A cross-section of 67 patients and 21 providers completed surveys related to their demographics and willingness to refer/attend a number of interventions for weight loss. A case study of three patients from the target audience was used to elicit detailed feedback on preconception weight status and weight loss intervention. RESULTS: Overall, patients were willing to attend a variety of interventions, regardless of BMI category. Focus group participants shared that weight loss prior to conception would be beneficial for them and their child, but cited barriers such as time, location, and the way providers encourage weight loss. Providers were willing to refer to a number of behavioral interventions, and were less willing to prescribe weight loss medications than other intervention options. CONCLUSIONS: A number of intervention strategies may be well received by both patients and providers in preconception care to assist with weight loss prior to conception. Future research is needed on intervention effects and sustainability.

Structural Equation Modeling Supports a Moderating Role of Personality in the Relationship Between Physical Activity and Mental Health in College Women.

BACKGROUND: A positive association between physical activity and mental health is well established, particularly for lower symptoms of depression and anxiety among active adults. However, it is unclear whether the association is influenced by personality, which might moderate or otherwise explain the association. In addition, past studies have not confirmed the association using an objective measure of physical activity. OBJECTIVE: Our objective was to examine whether Extraversion and Neuroticism influence the association between mental health and physical activity measured by convergent self-reports and an accelerometer. METHODS: Structural equation modeling was used to test competing models of the relationships between personality, physical activity, and mental health in a sample of female undergraduates. RESULTS: In bivariate analysis, mental health was negatively related to Neuroticism and positively related to Extraversion, self-reported physical activity (which was related only to Extraversion, positively), and objective physical activity (which was related only to Neuroticism, negatively). In structural equation modeling, a 3-way interaction indicated that objective physical activity and mental health were unrelated in extraverts, but related positively in neurotic-introverts and negatively in stable-introverts. CONCLUSIONS: Higher levels of physical activity were associated with better mental health only in neurotic-introverts, who are at higher risk for mental health problems.

Brief self-efficacy scales for use in weight-loss trials: Preliminary evidence of validity.

Self-efficacy is a commonly included cognitive variable in weight-loss trials, but there is little uniformity in its measurement. Weight-loss trials frequently focus on physical activity (PA) and eating behavior, as well as weight loss, but no survey is available that offers reliable measurement of self-efficacy as it relates to each of these targeted outcomes. The purpose of this study was to test the psychometric properties of brief, pragmatic self-efficacy scales specific to PA, healthful eating and weight-loss (4 items each). An adult sample (n = 1,790) from 28 worksites enrolled in a worksite weight-loss program completed the self-efficacy scales, as well as measures of PA, dietary fat intake, and weight, at baseline, 6-, and 12-months. Confirmatory factor analysis supported the hypothesized factor structure indicating, 3 latent self-efficacy factors, specific to PA, healthful eating, and weight-loss. Measurement equivalence/invariance between relevant demographic groups, and over time was also supported. Parallel growth processes in self-efficacy factors and outcomes (PA, fat intake, and weight) support the predictive validity of score interpretations. Overall, this initial series of psychometric analyses supports the interpretation that scores on these scales reflect self-efficacy for PA, healthful eating, and weight-loss. The use of this instrument in large-scale weight-loss trials is encouraged. (PsycINFO Database Record

Personality Correlates of Physical Activity in College Women.

UNLABELLED: Commonly reported relationships of the broad personality traits of extraversion and neuroticism with self-reports of physical activity (PA) have not been elaborated within motivational theory that posits how functioning of the behavioral inhibition (BIS) and activation (BAS) systems can explain or modify the influence of personality on PA. Whether personality predicts physical activity when it is measured objectively has not been established. PURPOSE: The study was aimed to test direct, indirect, and interactive relations between extraversion, neuroticism, BIS and BAS, and PA measured by validated self-report and accelerometry. METHODS: Two samples of female undergraduates completed personality questionnaires. Sample 2 also completed three PA self-reports and wore an accelerometer for 7 d. Factor structure and measurement equivalence of personality measures, structural equivalence of relationships between personality factors, and multivariate prediction of self-reported and objectively measured PA by personality were tested using structural equation modeling. RESULTS: Equivalence between samples for personality models was confirmed. Behavioral activation system predicted self-reported PA. Neuroticism and BIS predicted objectively measured PA. CONCLUSIONS: The relationship between personality and PA may differ according to method used to measure PA. Behavioral inhibition system seems to protect against inactivity among young women high in neuroticism.