Can We Identify Who Will Adhere to Long-Term Physical Activity? Signal Detection Methodology as a Potential Aid to Clinical Decision Making

Department of Health Research and Policy, Stanford University, Stanford, California, United States
Health Psychology (Impact Factor: 3.59). 08/1997; 16(4):380-9. DOI: 10.1037//0278-6133.16.4.380
Source: PubMed


Signal detection methodology was used to identify the best combination of predictors of long-term exercise adherence in 269 healthy, initially sedentary adults ages 50-65 years. Less educated individuals who were assigned to supervised home-based exercise of either higher or lower intensity and who were less stressed and less fit at baseline than other individuals had the greatest probability of successful adherence by the 2nd year. Overweight individuals assigned to a group-based exercise program were the least likely to be successful 2 years later. Predictors of short-term (1-year) adherence were generally similar to predictors of 2-year adherence. Signal detection analysis may be useful for identifying subgroups of people at risk for underadherence who subsequently might be targeted for intervention.

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    • "As is typically performed with this type of recursive partitioning method[42,43,46], further descriptive analysis was conducted on the distinct subgroups identified through the age-stratified recursive partitioning analyses in order to better understand subgroup membership. All variables entered into the recursive partitioning analyses were evaluated, in addition to the initial screening variables for self-reported physical activity (CHAMPS questionnaire measuring total physical activity, total walking , and walking for errands variables[36]—the latter two variables being most typically associated with built environment features47484950), and lower-extremity function measured via the Short Physical Performance Battery (SPPB)[37]. "
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    ABSTRACT: Background: Obesity is an increasingly prevalent condition among older adults, yet relatively little is known about how built environment variables may be associated with obesity in older age groups. This is particularly the case for more vulnerable older adults already showing functional limitations associated with subsequent disability. Methods: The Lifestyle Interventions and Independence for Elders (LIFE) trial dataset (n = 1600) was used to explore the associations between perceived built environment variables and baseline obesity levels. Age-stratified recursive partitioning methods were applied to identify distinct subgroups with varying obesity prevalence. Results: Among participants aged 70-78 years, four distinct subgroups, defined by combinations of perceived environment and race-ethnicity variables, were identified. The subgroups with the lowest obesity prevalence (45.5-59.4 %) consisted of participants who reported living in neighborhoods with higher residential density. Among participants aged 79-89 years, the subgroup (of three distinct subgroups identified) with the lowest obesity prevalence (19.4 %) consisted of non-African American/Black participants who reported living in neighborhoods with friends or acquaintances similar in demographic characteristics to themselves. Overall support for the partitioned subgroupings was obtained using mixed model regression analysis. Conclusions: The results suggest that, in combination with race/ethnicity, features of the perceived neighborhood built and social environments differentiated distinct groups of vulnerable older adults from different age strata that differed in obesity prevalence. Pending further verification, the results may help to inform subsequent targeting of such subgroups for further investigation. Trial registration: Identifier = NCT01072500.
    Full-text · Article · Dec 2015 · International Journal of Behavioral Nutrition and Physical Activity
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    • "This implies that fitter individuals were more likely to be intrinsically motivated to participate in the exercise program, and this ensuing motivation predicted adherence and physiological outcomes. This result aligns with previous findings showing that less fit individuals may be less likely to adhere to exercise programs (e.g., King et al., 1997). Nonetheless, the prediction was far from perfect, which means that even unfit adults can adhere to and gain positive health benefits from HIT and MICT training if intrinsic motivation can be fostered. "
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    ABSTRACT: Objective: To examine the motivational process through which increases in aerobic capacity and decreases in total body fat are achieved during high-intensity intermittent training (HIT) and moderate-intensity continuous training (MICT) interventions. Method: Eighty-seven physically inactive adults (65% women, age = 42 ± 12, BMI = 27.67 ± 4.99 kg/m2) took part in a 10-week randomized intervention testing group-based HIT, operationalized as repeated sprints of 15-60 s interspersed with periods of recovery cycling ≤ 25 min/session, 3 sessions/wk-1, or MICT, operationalized as cycling at constant workload of ∼65% maximum aerobic capacity (VO2max, 30-45 min/session-1, 5 sessions/wk-1. Assessments of VO2max and total body fat were made pre- and postintervention. Motivation variables were assessed midintervention and class attendance was monitored throughout. Path analysis was employed, controlling for treatment arm and baseline values of VO2max and total body fat. Results: The 2 groups differed in adherence only, favoring HIT. Baseline VO2max predicted intrinsic motivation midintervention. Intrinsic motivation predicted program adherence, which in turn predicted increases in VO2max and decreases in total body fat by the end of the study. Conclusion: Intrinsic motivation in HIT and MICT is positively linked to adherence to these programs, which can facilitate improvements in fitness and body composition. (PsycINFO Database Record
    Full-text · Article · Sep 2015 · Health Psychology
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    • "Inclusion criteria include: (1) mild-to-moderate radiographic medial tibiofemoral OA (Kellgren-Lawrence (KL) = 2 or 3); (2) knee neutral or varus aligned knee ( -2° valgus ≤ angle ≤ 10° varus); (3) BMI ≥ 20 kg.m-2 and ≤ 45 kg.m-2; and (4) no participation in formal strength training for more than 30 min.wk-1 in the past 6 months. We exclude people with BMI >45 kg.m-2 because of difficulty in using CT equipment and lower adherence to exercise [36,37] and <20 kg.m-2 because of limited thigh fat. We include only people with neutral (−2° valgus to 2° varus) or moderate varus (≤ 10° varus) alignment and medial knee OA and not predominant lateral compartment or severe patellofemoral (PF) compartment disease because (1) the medial compartment is the most common disease site, and (2) medial progression is strongly associated with moderate varus alignment [38-40], independent of BMI [41]. "
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    ABSTRACT: Muscle loss and fat gain contribute to the disability, pain, and morbidity associated with knee osteoarthritis (OA), and thigh muscle weakness is an independent and modifiable risk factor for it. However, while all published treatment guidelines recommend muscle strengthening exercise to combat loss of muscle mass and strength in knee OA patients, previous strength training studies either used intensities or loads below recommended levels for healthy adults or were generally short, lasting only 6 to 24 weeks. The efficacy of high-intensity strength training in improving OA symptoms, slowing progression, and affecting the underlying mechanisms has not been examined due to the unsubstantiated belief that it might exacerbate symptoms. We hypothesize that in addition to short-term clinical benefits, combining greater duration with high-intensity strength training will alter thigh composition sufficiently to attain long-term reductions in knee-joint forces, lower pain levels, decrease inflammatory cytokines, and slow OA progression. This is an assessor-blind, randomized controlled trial. The study population consists of 372 older (age >= 55 yrs) ambulatory, community-dwelling persons with: (1) mild-to-moderate medial tibiofemoral OA (Kellgren-Lawrence (KL) = 2-3); (2) knee neutral or varus aligned knee ( -2o valgus <= angle <= 10o varus); (3) 20 kg.m-2 >= BMI <= 45 kg.m-2; and (3) no participation in a formal strength-training program for more than 30 minutes per week within the past 6 months. Participants are randomized to one of 3 groups: high-intensity strength training (75-90% 1Repetition Maximum (1RM)); low-intensity strength training (30-40%1RM); or healthy living education. The primary clinical aim is to compare the interventions' effects on knee pain, and the primary mechanistic aim is to compare their effects on knee-joint compressive forces during walking, a mechanism that affects the OA disease pathway. Secondary aims will compare the interventions' effects on additional clinical measures of disease severity (e.g., function, mobility); disease progression measured by x-ray; thigh muscle and fat volume, measured by computed tomography (CT); components of thigh muscle function, including hip abductor strength and quadriceps strength, and power; additional measures of knee-joint loading; inflammatory and OA biomarkers; and health-related quality of life. Test-retest reliability for the thigh CT scan was: total thigh volume, intra-class correlation coefficients (ICC) = 0.99; total fat volume, ICC = 0.99, and total muscle volume, ICC = 0.99. ICC for both isokinetic concentric knee flexion and extension strength was 0.93, and for hip-abductor concentric strength was 0.99. The reliability of our 1RM testing was: leg press, ICC = 0.95; leg curl, ICC = 0.99; and leg extension, ICC = 0.98. Results of this trial will provide critically needed guidance for clinicians in a variety of health professions who prescribe and oversee treatment and prevention of OA-related complications. Given the prevalence and impact of OA and the widespread availability of this intervention, assessing the efficacy of optimal strength training has the potential for immediate and vital clinical impact.Trial registration:NCT01489462.
    Full-text · Article · Jul 2013 · BMC Musculoskeletal Disorders
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