scholarly journals Describing Transitions in Adherence to Physical Activity Self-monitoring and Goal Attainment in an Online Behavioral Weight Loss Program: Secondary Analysis of a Randomized Controlled Trial (Preprint)

2021 ◽  
Author(s):  
Melissa Lee Stansbury ◽  
Jean R Harvey ◽  
Rebecca A Krukowski ◽  
Christine A Pellegrini ◽  
Xuewen Wang ◽  
...  
Keyword(s):  
Physical Activity ◽  
Weight Loss ◽  
Goal Attainment ◽  
Vigorous Physical Activity ◽  
Secondary Analysis ◽  
Individual Characteristics ◽  
Behavioral Weight Loss ◽  
Self Monitoring ◽  
Program Goal ◽  
Monitoring Behavior

BACKGROUND Standard behavioral weight loss interventions often set uniform physical activity (PA) goals and promote PA self-monitoring; however, adherence remains a challenge and recommendations may not accommodate all individuals. Identifying patterns of PA goal attainment and self-monitoring behavior will offer a deeper understanding of how individuals adhere to different types of commonly prescribed PA recommendations (ie., minutes of moderate-to-vigorous physical activity [MVPA] and daily steps) and guide future recommendations for improved intervention effectiveness. OBJECTIVE This study examined weekly patterns of adherence to steps-based and minutes-based PA goals and self-monitoring behavior during a 6-month online behavioral weight loss intervention. METHODS Participants were prescribed weekly PA goals for steps (7,000 to 10,000 steps/day) and minutes of MVPA (50 to 200 minutes/week) as part of a lifestyle program. Goals gradually increased during the initial 2 months, followed by 4 months of fixed goals. PA was self-reported daily on the study website. For each week, participants were categorized as “adherent” if they self-monitored their PA and met the program PA goal, “suboptimally adherent” if they self-monitored but did not meet the program goal, or “nonadherent” if they did not self-monitor. The probability of transitioning into a less adherent status was examined using multinomial logistic regression. RESULTS Individuals (N=212) were predominantly middle-aged females with obesity, and 31.6% self-identified as a racial/ethnic minority. Initially, 34.4% were categorized as “adherent” to steps-based goals (51.9% “suboptimally adherent” and 13.7% “nonadherent”), and there was a high probability of either remaining “suboptimally adherent” from week-to-week or transitioning to a “nonadherent” status. On the other hand, 70.3% of individuals started out “adherent” to minutes-based goals (16.0% “suboptimally adherent” and 13.7% “nonadherent”), with “suboptimally adherent” seen as the most variable status. During the graded goal phase, individuals were more likely to transition to a less adherent status for minutes-based goals (OR 1.39, 95% CI 1.31-1.48) compared to steps-based goals (OR 1.24, 95% CI 1.17-1.30); however, no differences were seen during the fixed goal phase (minutes-based goals: OR 1.06, 95% CI 1.05, 1.08 versus steps-based goals: OR 1.07, 95% CI 1.05, 1.08). CONCLUSIONS States of vulnerability to poor PA adherence can emerge rapidly and early in obesity treatment. There is a window of opportunity within the initial two months to bring more people towards “adherent” behavior, especially those who fail to meet the prescribed goals but engage in self-monitoring. While this study describes the probability of adhering to steps-based and minutes-based targets, it will be prudent to determine how individual characteristics and contextual states relate to these behavioral patterns, which can inform how best to adapt interventions. CLINICALTRIAL This study was a secondary analysis of a pre-registered randomized trial (Trial Registration: ClinicalTrials.gov NCT02688621).

scholarly journals Characterizing Self-Monitoring Behavior and Its Association With Physical Activity and Weight Loss Maintenance

2018 ◽  
pp. 155982761879055 ◽  
Author(s):  
Kara L. Gavin ◽  
Nancy E. Sherwood ◽  
Julian Wolfson ◽  
Mark A. Pereira ◽  
Jennifer A. Linde
Keyword(s):  
Physical Activity ◽  
Weight Loss ◽  
Weight Loss Maintenance ◽  
Self Monitoring ◽  
Monitoring Behavior

scholarly journals Weight-Related Information Avoidance Prospectively Predicts Poorer Self-Monitoring and Engagement in a Behavioral Weight Loss Intervention

2020 ◽  
Author(s):  
Leah M Schumacher ◽  
Mary K Martinelli ◽  
Alexandra D Convertino ◽  
Evan M Forman ◽  
Meghan L Butryn
Keyword(s):  
Physical Activity ◽  
Weight Loss ◽  
Body Weight ◽  
Treatment Engagement ◽  
Treatment Discontinuation ◽  
Behavioral Weight Loss ◽  
Self Monitoring ◽  
Information Avoidance ◽  
Related Information ◽  
Session Attendance

Abstract Background Self-monitoring is a key component of behavioral weight loss (BWL) interventions. Past research suggests that individuals may avoid self-monitoring in certain contexts (e.g., skipping self-weighing after higher-than-usual calorie intake). However, no studies have attempted to quantify individuals’ inclination to avoid information about their weight control (“weight-related information avoidance”; WIA) or prospectively examined its implications for treatment engagement and outcomes in BWL programs. Purpose Characterize WIA using a validated questionnaire among adults enrolled in BWL treatment and examine whether WIA prospectively predicts self-monitoring adherence, session attendance, treatment discontinuation, or weight loss. Methods Participants (N = 87; MBMI = 34.9 kg/m2, 83% female) completed a measure of WIA prior to starting a 12 week, group-based BWL intervention. Participants were given digital self-monitoring tools and instructed to self-monitor their food intake daily, physical activity daily, and body weight weekly (Weeks 1–10) and then daily (Weeks 11–12). Session attendance and treatment discontinuation were recorded. Weight was measured in-clinic pretreatment and posttreatment. Results While mean WIA was low (M = 2.23, standard deviation [SD] = 0.95; potential scale range: 1–7), greater WIA predicted poorer attendance (r = −.23; p = .03) and poorer self-monitoring of physical activity (r = −.28; p = .009) and body weight (r = −.32; p = .003). WIA did not predict food monitoring (p = .08), treatment discontinuation (p = .09), or 12 week weight loss (p = .91). Conclusions Greater WIA, as assessed via a brief questionnaire, may place individuals at risk for poorer self-monitoring and treatment engagement during BWL. Further research on the implications of WIA in the context of weight management is warranted, including evaluation of correlates, moderators, and mechanisms of action of WIA. Clinical Trial Registration NCT03337139.

scholarly journals Examination of Nutrition Literacy and Quality of Self-monitoring in Behavioral Weight Loss

2018 ◽  
Vol 52 (9) ◽  
pp. 809-816 ◽  
Author(s):  
Diane L Rosenbaum ◽  
Margaret H Clark ◽  
Alexandra D Convertino ◽  
Christine C Call ◽  
Evan M Forman ◽  
...  
Keyword(s):  
Weight Loss ◽  
Caloric Intake ◽  
Secondary Analysis ◽  
Behavioral Weight Loss ◽  
Food Record ◽  
Obese Adults ◽  
Baseline Measure ◽  
Self Monitoring ◽  
Session Attendance

Abstract Background Few have examined nutrition literacy (i.e., capacity to process and make informed nutritional decisions) in behavioral weight loss. Nutrition literacy (NL) may impact necessary skills for weight loss, contributing to outcome disparities. Purpose The study sets out to identify correlates of NL; evaluate whether NL predicted weight loss, food record completion and quality, and session attendance; and investigate whether the relations of race and education to weight loss were mediated by NL and self-monitoring. Methods This is a secondary analysis of 6-month behavioral weight loss program in which overweight/obese adults (N = 320) completed a baseline measure of NL (i.e., Newest Vital Sign). Participants self-monitored caloric intake via food records. Results NL was lower for black participants (p < .001) and participants with less education (p = .002). Better NL predicted better 6-month weight loss (b = −.63, p = .04) and food record quality (r = .37, p < .001), but not food record completion or attendance (ps > 0.05). Black participants had lower NL, which was associated with poorer food record quality, which adversely affected weight loss. There was no indirect effect of education on weight loss through NL and food record quality. Conclusions Overall, results suggest that lower NL is problematic for weight loss. For black participants, NL may indirectly impact weight loss through quality of self-monitoring. This might be one explanation for poorer behavioral weight loss outcomes among black participants. Additional research should investigate whether addressing these skills through enhanced treatment improves outcomes. Clinical trial information NCT02363010.

Abstract P118: Changes in Physical Activity by Self-Weighing Trajectory Groups

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Yaguang Zheng ◽  
Susan M Sereika ◽  
Linda J Ewing ◽  
Cynthia A Danford ◽  
Bonny Rockette-Wagner ◽  
...  
Keyword(s):  
Physical Activity ◽  
Weight Loss ◽  
Lifestyle Changes ◽  
Future Research ◽  
Behavior Changes ◽  
Behavioral Weight Loss ◽  
Self Monitoring ◽  
Consistent Group ◽  
Behavioral Weight Loss Intervention ◽  
Average Activity

Introduction: Numerous studies have established a significant association between regular self-weighing and weight loss; however, few studies have examined how self-weighing patterns are associated with lifestyle changes, e.g. physical activity (PA). The aim was to examine the association between frequency of self-weighing and changes in PA levels. Hypothesis: We hypothesized that higher frequencies of self-weighing are associated with greater increases in PA levels. Methods: This was an analysis of data from a 12-mo behavioral weight loss intervention study. Each subject was given a Wi-Fi scale and instructed to weigh daily. The scale transmitted weight values to a central server. PA was objectively assessed by an accelerometer (ActiGraph GT3x) at 0 and 6 mos. Participants were instructed to wear the accelerometer for ≥ 3 weekdays, one weekend day, ≥10 hours/day. General linear model was used for data analysis. Results: The sample (N=89) was largely female (89.9%), White (82%), with a mean age (±SD) of 51.9±9.3 years, and a mean BMI of 33.6±4.5 kg/m2. Our previous analysis using group-based trajectory modeling identified 3 self-weighing patterns: high/consistent (self-weighed 5-6 days/week regularly); moderate/declined (declined from 4-5 to 2 days/week); minimal/declined (declined from 5-6 to 0 days/week). As shown in the table, compared with minimal/declined self-weighing group, the high/consistent group had a significant increase in energy expenditure, steps, light and moderate PA levels as well as average activity/day, while the moderate/declined group had a significant increase in steps and average activity/day. Conclusions: The differences in PA level changes across the trajectory groups suggest that improved adherence to self-weighing carried over to improved PA behavior changes. It is unclear if self-monitoring weight and observing the results led participants to regulate their PA behavior accordingly. Future research needs to examine the mechanisms of how daily weighing impacts the level of daily PA.

scholarly journals Defining Valid Activity Monitor Data: A Multimethod Analysis of Weight-Loss Intervention Participants’ Barriers to Wear and First 100 Days of Physical Activity

Informatics ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 39
Author(s):  
Stephanie L. Orstad ◽  
Lauren Gerchow ◽  
Nikhil R. Patel ◽  
Meghana Reddy ◽  
Christina Hernandez ◽  
...  
Keyword(s):  
Physical Activity ◽  
Weight Loss ◽  
Low Income ◽  
Activity Monitor ◽  
Accelerometer Data ◽  
Weight Loss Intervention ◽  
Behavioral Weight Loss ◽  
Self Monitoring ◽  
Behavioral Weight Loss Intervention ◽  
Monitor Data

Despite the popularity of commercially available wearable activity monitors (WAMs), there is a paucity of consistent methodology for analyzing large amounts of accelerometer data from these devices. This multimethod study aimed to inform appropriate Fitbit wear thresholds for physical activity (PA) outcomes assessment in a sample of 616 low-income, majority Latina patients with obesity enrolled in a behavioral weight-loss intervention. Secondly, this study aimed to understand intervention participants’ barriers to Fitbit use. We applied a heart rate (HR) criterion (≥10 h/day) and a step count (SC) criterion (≥1000 steps/day) to 100 days of continuous activity monitor data. We examined the prevalence of valid wear and PA outcomes between analytic subgroups of participants who met the HR criterion, SC criterion, or both. We undertook qualitative analysis of research staff notes and participant interviews to explore barriers to valid Fitbit data collection. Overall, one in three participants did not meet the SC criterion for valid wear in Weeks 1 and 13; however, we found the SC criterion to be more inclusive of participants who did not use a smartphone than the HR criterion. Older age, higher body mass index (BMI), barriers to smartphone use, device storage issues, and negative emotional responses to WAM-based self-monitoring may predict higher proportions of invalid WAM data in weight-loss intervention research.

Enrolling Caregivers in Obesity Interventions to Improve Obesity-Related Outcomes in Children

2021 ◽  
pp. 019394592110370
Author(s):  
Hannah Bessette ◽  
MinKyoung Song ◽  
Karen S. Lyons ◽  
Sydnee Stoyles ◽  
Christopher S. Lee ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Weight Loss ◽  
Linear Regression ◽  
Body Mass ◽  
Sedentary Time ◽  
Vigorous Physical Activity ◽  
Weight Loss Program ◽  
Weight Loss Programs ◽  
Obesity Interventions

In this study, we assessed the influences of change in moderate-to-vigorous physical activity (MVPA)/sedentary time (ST) of caregivers participating in a commercial weight-loss program on their children’s change in MVPA/ST. Data from 29 caregivers and their children were collected over 8 weeks. We used multivariable linear regression to assess associations of changes in caregiver’s percent of time spent in MVPA/ST and changes in their child’s percent of time spent in MVPA/ST. For caregivers that decreased body mass index (BMI) over 8 weeks, changes in caregivers’ MVPA was strongly associated with the change in children’s MVPA (β = 2.61 [95% CI: 0.45, 4.77]) compared to caregivers who maintained/increased BMI (β = 0.24 [–2.16, 2.64]). Changes in caregivers’ ST was strongly associated with changes in children’s ST (β = 2.42 [1.02, 3.81]) compared to caregivers who maintained/increased BMI (β = 0.35 [–0.45, 1.14]). Findings reinforce encouraging caregivers to enroll in weight-loss programs for the benefit of their children as well as for themselves.

scholarly journals A Simple Liking Survey Captures Behaviors Associated with Weight Loss in a Worksite Program among Women at Risk of Type 2 Diabetes

Nutrients ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 1338
Author(s):  
Mastaneh Sharafi ◽  
Pouran Faghri ◽  
Tania B. Huedo-Medina ◽  
Valerie B. Duffy
Keyword(s):  
Physical Activity ◽  
Weight Loss ◽  
Latent Variable ◽  
Secondary Analysis ◽  
Diabetes Prevention Program ◽  
Analysis Of Covariance ◽  
Term Care ◽  
Variable Approach ◽  
Average Loss ◽  
Highly Correlated

In a secondary analysis, we assessed the ability of dietary and physical activity surveys to explain variability in weight loss within a worksite-adapted Diabetes Prevention Program. The program involved 58 overweight/obese female employees (average age = 46 ± 11 years SD; average body mass index = 34.7 ± 7.0 kg/m2 SD) of four long-term care facilities who survey-reported liking and frequency of dietary and physical activity behaviors. Data were analyzed using a latent variable approach, analysis of covariance, and nested regression analysis to predict percent weight change from baseline to intervention end at week 16 (average loss = 3.0%; range—6% gain to 17% loss), and follow-up at week 28 (average loss = 2.0%; range—8% gain to 16% loss). Using baseline responses, restrained eaters (reporting liking but low intakes of high fat/sweets) achieved greater weight loss at 28 weeks than those reporting high liking/high intake (average loss = 3.5 ± 0.9% versus 1.0 ± 0.8% S.E., respectively). Examining the dietary surveys separately, only improvements in liking for a healthy diet were associated significantly with weight loss (predicting 44% of total variance, p < 0.001). By contrasting liking versus intake changes, women reporting concurrent healthier diet liking and healthier intake lost the most weight (average loss = 5.4 ± 1.1% S.E.); those reporting eating healthier but not healthier diet liking (possible misreporting) gained weight (average gain = 0.3 ± 1.4% S.E.). Change in liking and frequency of physical activity were highly correlated but neither predicted weight loss independently. These pilot data support surveying dietary likes/dislikes as a useful measure to capture dietary behaviors associated with weight loss in worksite-based programs. Comparing dietary likes and intake may identify behaviors consistent (appropriate dietary restraint) or inconsistent (misreporting) with weight loss success.

Promoting physical activity compliance in a low socioeconomic Latina population with chronic neurological disorders: A Proof-of-Concept Study (Preprint)

2021 ◽  
Author(s):  
Alexander Garbin ◽  
Jesús Díaz ◽  
Vy Bui ◽  
Janina Morrison ◽  
Beth E Fisher ◽  
...  
Keyword(s):  
Physical Activity ◽  
Effect Size ◽  
Neurological Disorders ◽  
Medical Center ◽  
Vigorous Physical Activity ◽  
Community Based ◽  
Self Monitoring ◽  
Low Socioeconomic ◽  
Behavioral Coaching

BACKGROUND Physical activity is known to improve quality of life as well as reduce mortality and disease progression in individuals with chronic neurological disorders. However, Latinas are less likely to participate in recommended levels of physical activity due to common socioeconomic barriers including limited resources and access to exercise programs. Therefore, we developed a community-based intervention with activity-monitoring and behavioral coaching to target these barriers and facilitate sustained participation in an exercise program promoting physical activity. OBJECTIVE To determine the feasibility and efficacy of a community-based intervention to promote physical activity (PA) through self-monitoring via a Fitbit and behavioral coaching in Latina participants with chronic neurological disorders. METHODS We conducted a proof-of-concept study in 21 Spanish-speaking Latina participants recruited from the Los Angeles County/ University of Southern California (LAC/USC) neurology clinic and enrolled in the 16-week intervention at The Wellness Center at The Historic General Hospital. Demographic data was assessed at baseline. Feasibility was defined by participant attrition and Fitbit adherence. Physical activity promotion was determined by examining change in time spent performing moderate-vigorous physical activity (MVPA) over the 16-week period. The effect of behavioral coaching was assessed by quantifying the difference in MVPA on days coaching occurred vs. days without coaching. Change in psychometric measures (baseline vs. post-intervention) and medical center visits (16-weeks pre-intervention vs. during intervention) were also examined. RESULTS Participants were of low socioeconomic status and acculturation. 19 participants completed the study (attrition 9.5%) with high Fitbit wear adherence (90.31%). Time performing moderate-vigorous physical activity (MVPA) significantly increased throughout the study (P<0.001). Behavioral coaching enhanced intervention effectiveness as evidenced by a higher time spent in MVPA on days coaching occurred. Participants’ illness perception (Effect Size g=.30), self-rated quality-of-life (Effect Size g=.32), and medical center visit frequency (Effect Size r =.44) improved. CONCLUSIONS Self-monitoring with behavioral coaching is a feasible community-based intervention for PA promotion in low socioeconomic Latinas with chronic neurological conditions. PA is known to be important in brain health in neurological conditions but remains relatively unexplored in minority populations. CLINICALTRIAL Clinicaltrials.gov; NCT04820153

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