Effects of Behavioral Weight Loss and Weight Loss Goal Setting in Cardiac Rehabilitation.
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ABSTRACT: Purpose
Obesity is prevalent among participants in cardiac rehabilitation (CR). Establishing a weight loss goal is an important strategy for promoting weight loss. We evaluate the association between a pre-program weight loss goal and change in weight during CR.Methods
Body weight was measured at CR entry and at exit from CR. Overweight/obese participants were categorized as having: (1) established a weight loss goal and attended behavioral weight loss sessions (G + BWL); (2) set a weight loss goal but did not attend BWL (G); (3) and neither set a weight loss goal nor attended BWL (NoG).Results
The cohort consisted of 317 overweight/obese participants; 52 of whom set a weight loss goal and attended BWL, 227 patients set a goal but did not attend BWL, and 38 did neither. The G + BWL group lost more weight than the G group (-6.8 + 4.3 vs -1.1 + 3.5) (P < .0001). Both groups that established a weight loss goal lost more weight than the NoG group.Conclusions
For overweight/obese individuals in CR, participating in BWL classes and setting a weight loss goal leads to more weight loss than G alone. Setting a weight loss goal alone leads to greater weight loss than not setting a weight loss goal.
SUBMITTER: Barrett KV
PROVIDER: S-EPMC7647951 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundGoal setting aids health-related behavior changes; however, the influence of different types of goals on weight loss remains unclear.ObjectiveWe aimed to investigate the association of 3 aspects of goal setting with weight and program dropout over a 24-week period.MethodsThis study was a prospective longitudinal analysis of participants in a 12-week digital behavioral weight loss program. Weight and engagement data for eligible participants (N=36,794) were extracted from the database. Eligible participants were adults in the United Kingdom who had enrolled in the program, had a BMI ≥25 kg/m2, and a weight reading recorded at baseline. Three aspects of goal setting were self-reported at enrollment: weight loss motivation (appearance, health, fitness, or self-efficacy), overall goal preference (low, medium, or high), and percentage weight loss goal (<5%, 5%-10%, or >10%). Weight was measured at 4, 12, and 24 weeks. Mixed models for repeated measures were used to explore the association between goals and weight across the 24-week period. To measure sustained weight change, the primary outcome was weight at 24 weeks. We explored dropout rates over the 24-week period by goal and whether engagement mediated the association between goals and weight loss.ResultsOf the 36,794 participants (mean 46.7, SD 11.1 years; 33,902/36,794, 92.14% female) included in the cohort, 13.09% (n=4818) reported weight at 24 weeks. Most participants set goals of 5%-10% weight loss (23,629/36,794, 64.22%), but setting goals for >10% was associated with greater weight loss (mean difference 5.21 kg, 95% CI 5.01-5.41; P<.001). There was no difference between goals of 5%-10% and <5% (mean difference 0.59 kg, 95% CI 0.00-1.18; P=.05). Appearance was the most prevalent motivational factor (14,736/36,794, 40.05%), but health and fitness were associated with greater weight losses (mean difference health vs appearance 1.40 kg, 95% CI 1.15-1.65; P<.001 and mean difference fitness vs appearance 0.38 kg, 95% CI 0.05-0.70; P=.03). Goal preference had no association with weight. Engagement was an independent predictor of weight loss but not a mediator of the effect of goal setting. At 24 weeks, those who set goals of >10% were less likely to drop out compared with 5%-10% goals (odds ratio [OR] 0.40, 95% CI 0.38-0.42; P<.001); those who liked to set overall high goals were more likely to drop out compared with medium goals (OR 1.20, 95% CI 1.11-1.29; P<.001); and those motivated by fitness or health were less likely to drop out compared with appearance (OR 0.92, 95% CI 0.85-0.995; P=.04 and OR 0.84, 95% CI 0.78-0.89; P<.001, respectively).ConclusionsSetting higher weight loss goals and being motivated by health or fitness were associated with greater weight loss and lower likelihood of dropout. Randomized trials for setting these types of goals are required to confirm causality.
| S-EPMC10357317 | biostudies-literature
Project description:BackgroundThe management of prediabetes in the community setting is a global priority. We evaluated the feasibility of a 6-month multilevel practice nurse-led prediabetes dietary intervention which involved goal setting. The aim of this paper is to explore the weight loss goals and strategies reported by participants to achieve their weight loss goals as recorded by practice nurses, and report on factors that influenced dietary behaviours.MethodsThis study used a convergent mixed-methods design. A six-month pragmatic non-randomised pilot study with a qualitative process evaluation was conducted in two neighbouring provincial cities in New Zealand. A structured dietary intervention delivered by practice nurses was implemented in four practices in 2014-2016. Content analysis of the text and descriptive statistics were used to analyse the data.ResultsOne hundred and fifty seven people with prediabetes were enrolled (85 intervention, 72 control). The intervention group lost a mean 1.3 kg more than the control group (p < .0.001). The majority of the intervention group indicated either a high level of readiness (n = 42, 53%) or some readiness (n = 31, 39%) to make food changes. The majority of weight loss goals aligned with clinical guidelines (between 5 and 10% of body weight). While just over half (n = 47, 55%) demonstrated weight loss at the end of the six month period, the majority of participants did not achieve their predetermined weight loss goal (n = 78, 83%). Gender, ethnicity and budget were not related to weight loss at six months. Readiness to change and reported challenges to making dietary changes were related to weight loss at six months. Negative factors or set-backs included sporadic adherence to diet due to other health problems, change in context or environment and coping with ill health, most notably stress and low mood.ConclusionsThe data relating to weight loss and dietary goals provided insight into the challenges that people faced in making dietary changes for weight loss across a six month period. Simplifying goal setting to those goals with the greatest potential clinical impact or the greatest significance to the person, in a socially supportive environment, may increase the success of goal achievement.Trial registrationANZCTR ACTRN1261500080656. Registered 3 August 2015 (Retrospectively registered). https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366560&isReview=true.
| S-EPMC7362527 | biostudies-literature
Project description:Objective:To explore the effect of goal-setting on physical functioning, quality of life and duration of rehabilitation in geriatric rehabilitation compared to care as usual.Data sources:Medline, Embase, CINAHL, PsycINFO and the Cochrane Library were searched from initiation to October 2018.Methods:We included randomized controlled trials (RCTs), controlled before-after studies and studies using historic controls of older patients (mean age ⩾55 years) receiving rehabilitation for acquired disabilities. Our primary outcome was physical functioning; secondary outcomes were quality of life and rehabilitation duration. Cochrane guidelines were used to assess the risk of bias of the studies and extract data. Only RCT data were pooled using standardized mean difference (SMD).Results:We included 14 studies consisting of a total of 1915 participants with a mean age ranging from 55 to 83 years. Ten out of the 14 studies had a randomized controlled design, 7 of which could be pooled for the primary outcome. The risk of bias was judged high in several domains in all included studies. The meta-analysis showed no statistically significant differences between goal-setting and care as usual for physical functioning (SMD -0.11 (-0.32 to 0.10)), quality of life (SMD 0.09 (-0.56 to 0.75)) and rehabilitation duration (MD 13.46 days (-2.46 to 29.38)).Conclusion:We found low-quality evidence that goal-setting does not result in better physical functioning compared to care as usual in geriatric rehabilitation. For quality of life and duration of rehabilitation, we could not exclude a clinically relevant effect.
| S-EPMC6416788 | biostudies-literature
Project description:ObjectivesThis scoping review aims to map the literature on goal-setting tools in adult rehabilitation, exploring their characteristics, target users and supporting evidence to inform practice and future research in this area.MethodsWe completed a comprehensive search of four databases to identify relevant articles on tools for goal setting in rehabilitation. We followed Arkey and O'Malley's scoping review process to guide article selection, data extraction and data analysis.ResultsWe identified a total of 165 studies that reported on 55 different goal-setting tools, including tools for goal selection and goal documentation (n = 31), goal setting and intervention planning (n = 15), and for measuring the quality of the goal-setting process (n = 9). Over half of the tools were primarily designed for use in rehabilitation of physical disabilities (n = 32). Some tools fell under multiple sub-categories based on their characteristics as follows: 22 framework tools, 12 interview tools, 9 outcome measurement tools for goal achievement, 6 outcome measurement tools for goal quality and 25 documentation tools. The majority of goal-setting instruments targeted goals at the level of activity and participation (n = 51) and aimed to facilitate a client-centred or shared decision-making approach to rehabilitation planning (n = 46).ConclusionsThis study provides a comprehensive overview of existing goal-setting tools, highlighting their characteristics, target users and identified needs. These findings can enhance practitioners' awareness of the range of goal-setting tools available and can enable more effective utilization of these tools in clinical practice. Further research should investigate how clinicians can combine multiple tools to deliver goal setting.
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Project description:The Weight Loss Maintenance Trial tested strategies for maintenance of weight loss. Personal contact was superior to interactive technology and self-directed conditions.We aimed to identify behavioral mediators of the superior effect of personal contact vs. interactive technology and of personal contact vs. self-directed arms.Overweight/obese adults at risk for cardiovascular disease (n?=?1,032) who lost at least 4 kg were randomized to personal contact, interactive technology, or self-directed. After 30 months, 880 participants had data on weight and behavioral strategies.Reported increase of intake of fruits and vegetables and physical activity and more frequent self-weighing met criteria as mediators of the better outcome of personal contact vs. interactive technology. Increased intake of fruits and vegetables, more frequent self-weighing, and decreased dessert consumption were mediators of the difference between personal contact vs. self-directed.Inducing changes in the identified behaviors might yield better outcomes in future weight loss maintenance trials.
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Project description:ObjectiveIdentify, map, and synthesize existing reviews, to extract and analyse the most prominent barriers and facilitators to applying patient-centred goal-setting practice in rehabilitation using the Capability, Opportunity Motivation Behaviour (COM-B) model.DesignScoping review.Data sourceA primary search was conducted in MEDLINE, CINAHL, EMBASE, PsychInfo, and Cochrane. Citation chaining was employed.Review methodsAll types of review (systematic, scoping, and narrative) studies published up to June 14, 2022 that included physical and neurological rehabilitation, patient-centeredness, and goal-setting were reviewed. Studies were scrutinized for relevance, quality was not assessed. The most prominent barriers and facilitators were synthesized using thematic content analysis and mapped onto the COM-B model.ResultsTwenty-six review studies covering a range of conditions and settings, acute to community were included. Barrier and facilitators were identified at patient, provider, and organizational level. Barrier themes include provider's existing beliefs about goal-setting, lack of skills, and integration into clinical routines. Patient barriers related to capacity and opportunity to participate. Organizational barriers include lack of clinical guidelines, patient preparation, insufficient provider time, and high productivity expectations. Facilitators included goal-setting guidelines, training and education of providers and patients, revised clinical routines, performance monitoring, adequate time, and resources.ConclusionHealthcare providers should be the primary target of intervention. A provider's motivation to change current practice is the most prominent barrier, followed closely by capacity and opportunity. Patients require information, training, and structured engagement opportunities. Organizations play a key role in creating the optimal environmental conditions to enable patient-centred goal-setting.
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Project description:Designing systems with human agents is difficult because it often requires models that characterize agents' responses to changes in the system's states and inputs. An example of this scenario occurs when designing treatments for obesity. While weight loss interventions through increasing physical activity and modifying diet have found success in reducing individuals' weight, such programs are difficult to maintain over long periods of time due to lack of patient adherence. A promising approach to increase adherence is through the personalization of treatments to each patient. In this paper, we make a contribution towards treatment personalization by developing a framework for predictive modeling using utility functions that depend upon both time-varying system states and motivational states evolving according to some modeled process corresponding to qualitative social science models of behavior change. Computing the predictive model requires solving a bilevel program, which we reformulate as a mixed-integer linear program (MILP). This reformulation provides the first (to our knowledge) formulation for Bayesian inference that uses empirical histograms as prior distributions. We study the predictive ability of our framework using a data set from a weight loss intervention, and our predictive model is validated by comparison to standard machine learning approaches. We conclude by describing how our predictive model could be used for optimization, unlike standard machine learning approaches which cannot.
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Project description:Physical activity (PA) goal adherence is consistently associated with greater weight loss during behavioral obesity treatment, and early weight loss response predicts future weight loss success. However, it remains unclear which behaviors during the initial weeks of treatment distinguish responders from nonresponders and might be effective targets for improving treatment outcomes. To characterize subgroups with distinct patterns of PA goal adherence during the initial 2 months of an online, group-based weight control program and determine associations between these patterns and 6-month weight loss. Participants received an online behavioral obesity intervention with PA goals and daily self-monitoring. Weekly adherence to step goals and moderate-to-vigorous PA (MVPA) minute goals based on self-monitoring records were examined using latent class analysis. Body weight was objectively measured at 0, 2, and 6 months. Participants (N = 212; 91.5% female, 31.6% race/ethnic minority, mean body mass index: 35.8 ± 5.9 kg/m2) clustered into three subgroups based on early goal attainment: "Both PA Goals," "MVPA Goals Only," and "Neither PA Goal." The "Both PA Goals" class had significantly greater 6-month weight loss (estimated mean weight loss [95% CI]: -9.4% [7.4 to 11.5]) compared to the "MVPA Goals Only" (-4.8% [3.4 to 6.1]) and "Neither PA Goal" classes (-2.5% [1.4 to 3.6]). Individuals meeting both PA goals early in treatment achieve greater weight losses than those meeting MVPA but not step goals, pointing to the need to explore factors associated with nonadherence to each of the PA goals to better understand these potential targets for treatment refinement and adaptive interventions.
| S-EPMC8672928 | biostudies-literature
Project description:This study examined whether community food environments altered the longer-term effects of a nationwide behavioral weight management program on body mass index (BMI). The sample was comprised of 98,871 male weight management program participants and 15,385 female participants, as well as 461,302 and 37,192 inverse propensity-score weighted matched male and female controls. We measured the community food environment by counting the number of supermarkets, convenience stores, and fast food restaurants within a 1-mile radius around each person's home address. We used difference-in-difference regression models with person and calendar time fixed effects to estimate MOVE! effects over time in sub-populations defined by community food environment attributes. Among men, after an initial decrease in BMI at 6 months, the effect of the program decreased over time, with BMI increasing incrementally at 12 months (0.098 kg/m², p < 0.001), 18 months (0.069 kg/m², p < 0.001), and 24 months (0.067 kg/m², p < 0.001). Among women, the initial effects of the program decreased over time as well. Women had an incremental BMI change of 0.099 kg/m² at 12 months (p < 0.05) with non-significant incremental changes at 18 months and 24 months. We found little evidence that these longer-term effects of the weight management program differed depending on the community food environment. Physiological adaptations may overwhelm environmental influences on adherence to behavioral regimens in affecting longer-term weight loss outcomes.
| S-EPMC5858280 | biostudies-other
Project description:ObjectiveTo map the extant literature evaluating the use of technology for goal setting in adult rehabilitation and the impact of technology for patient outcomes.DesignScoping review.MethodsMEDLINE (via Ovid), CINAHL (via EBSCO), AMED and Scopus were searched for articles describing observational or interventional studies. ProQuest Dissertations and Theses database were searched for grey literature. Two review authors independently screened all titles and abstracts for potentially relevant articles. We included articles describing studies that had evaluated the development or application of technology to facilitate goal setting in rehabilitation for adults. Articles were excluded if the technology described did not include features to facilitate goal setting or were not in English. Narrative reviews, opinion pieces and editorials were also excluded.ResultsAfter screening 1640 publications of potential interest, we identified 27 studies for inclusion. These 27 articles described studies involving a total of 16 different technologies including, seven mobile apps, three websites, two mobile apps/website hybrids, two apps and two websites connected to a pedometer. We found that most technologies described were designed to facilitate self-management with goal setting as a feature and that only five included a shared decision moment around goal setting. Only six of the 16 technologies had research providing evidence of effectiveness in terms of improved patient outcomes, with the best evidence of beneficial effects associated with technologies that linked goal setting to pedometer use.ConclusionsThe identified technologies for use in adult rehabilitation that included goal setting as a feature were largely accepted and valued by patients and health professionals. The limited data suggest that there is a need for further research; specific foci may include the impact of incorporation of a shared decision-making moment and evaluation of effectiveness on patient outcomes.
| S-EPMC7656911 | biostudies-literature