Search Results

You are looking at 41 - 50 of 175 items for :

  • "physical activity assessment" x
Clear All
Restricted access

Diane K. Ehlers, Jennifer Huberty, Matthew Buman, Steven Hooker, Michael Todd and Gert-Jan de Vreede

Background:

Commercially available mobile and Internet technologies present a promising opportunity to feasibly conduct ecological momentary assessment (EMA). The purpose of this study was to describe a novel EMA protocol administered on middle-aged women’s smartphones via text messaging and mobile Internet.

Methods:

Women (N = 9; mean age = 46.2 ± 8.2 y) received 35 text message prompts to a mobile survey assessing activity, self-worth, and self-efficacy over 14 days. Prompts were scheduled and surveys were administered using commercial, Internet-based programs. Prompting was tailored to each woman’s daily wake/sleep schedule. Women concurrently wore a wrist-worn accelerometer. Feasibility was assessed via survey completion, accelerometer wear, participant feedback, and researcher notes.

Results:

Of 315 prompted surveys, 287 responses were valid (91.1%). Average completion time was 1.52 ± 1.03 minutes. One participant’s activity data were excluded due to accelerometer malfunction, resulting in complete data from 8 participants (n = 252 [80.0%] valid observations). Women reported the survey was easily and quickly read/completed. However, most thought the accelerometer was inconvenient.

Conclusions:

High completion rates and perceived usability suggest capitalizing on widely available technology and tailoring prompting schedules may optimize EMA in middle-aged women. However, researchers may need to carefully select objective monitors to maintain data validity while limiting participant burden.

Open access

Jeffer Eidi Sasaki, Cheryl A. Howe, Dinesh John, Amanda Hickey, Jeremy Steeves, Scott Conger, Kate Lyden, Sarah Kozey-Keadle, Sarah Burkart, Sofiya Alhassan, David Bassett Jr and Patty S. Freedson

Background:

Thirty-five percent of the activities assigned MET values in the Compendium of Energy Expenditures for Youth were obtained from direct measurement of energy expenditure (EE). The aim of this study was to provide directly measured EE for several different activities in youth.

Methods:

Resting metabolic rate (RMR) of 178 youths (80 females, 98 males) was first measured. Participants then performed structured activity bouts while wearing a portable metabolic system to directly measure EE. Steady-state oxygen consumption data were used to compute activity METstandard (activity VO2/3.5) and METmeasured (activity VO2/measured RMR) for the different activities.

Results:

Rates of EE were measured for 70 different activities and ranged from 1.9 to 12.0 METstandard and 1.5 to 10.0 METmeasured.

Conclusion:

This study provides directly measured energy cost values for 70 activities in children and adolescents. It contributes empirical data to support the expansion of the Compendium of Energy Expenditures for Youth.

Restricted access

Greg Welk, Youngwon Kim, Robin P. Shook, Laura Ellingson and Roberto L. Lobelo

Background:

The study evaluated the concurrent and criterion validity of a new, disposable activity monitor designed to provide objective data on physical activity and energy expenditure in clinical populations.

Methods:

A sample of healthy adults (n = 52) wore the disposable Metria IH1 along with the established Sensewear armband (SWA) monitor for a 1-week period. Concurrent validity was examined by evaluating the statistical equivalence of estimates from the Metria and the SWA. Criterion validity was examined by comparing the relative accuracy of the Metria IH1 and the SWA for assessing walking/running. The absolute validity of the 2 monitors was compared by computing correlations and mean absolute percent error (MAPE) relative to criterion data from a portable metabolic analyzer.

Results:

The output from 2 monitors was highly correlated (correlations > 0.90) and the summary measures yielded nearly identical allocations of time spent in physical activity and energy expenditure. The monitors yielded statistically equivalent estimates and had similar absolute validity relative to the criterion measure (12% to 15% error).

Conclusions:

The disposable nature of the adhesive Metria IH1 monitor offers promise for clinical evaluation of physical activity behavior in patients. Additional research is needed to test utility for counseling and behavior applications.

Restricted access

Ryan McGrath, Chantal A. Vella, Philip W. Scruggs, Mark D. Peterson, Christopher J. Williams and David R. Paul

Background: This investigation sought to determine how accelerometer wear (1) biased estimates of sedentary behavior (SB) and physical activity (PA), (2) affected misclassifications for meeting the Physical Activity Guidelines for Americans, and (3) impacted the results of regression models examining the association between moderate to vigorous physical activity (MVPA) and a clinically relevant health outcome. Methods: A total of 100 participants [age: 20.6 (7.9) y] wore an ActiGraph GT3X+ accelerometer for 15.9 (1.6) hours per day (reference dataset) on the hip. The BOD POD was used to determine body fat percentage. A data removal technique was applied to the reference dataset to create individual datasets with wear time ranging from 15 to 10 hours per day for SB and each intensity of PA. Results: Underestimations of SB and each intensity of PA increased as accelerometer wear time decreased by up to 167.2 minutes per day. These underestimations resulted in Physical Activity Guidelines for Americans misclassification rates of up to 42.9%. The regression models for the association between MVPA and body fat percentage demonstrated changes in the estimates for each wear-time adherence level when compared to the model using the reference MVPA data. Conclusions: Increasing accelerometer wear improves daily estimates of SB and PA, thereby also improving the precision of statistical inferences that are made from accelerometer data.

Restricted access

Karyn Tappe, Ellen Tarves, Jayme Oltarzewski and Deirdra Frum

Background:

Predictive modeling for physical activity behavior has included many different psychological components, including planning, motivation, personality, and self-efficacy. However, habit formation in exercise maintenance has not been well explored and lacks reliable measurement tools. The current study explores novel survey questions that examine behavioral components of exercise habit, including frequency, environmental cuing, and temporal constancy of behavior. We then relate these concepts to an established psychological measure of habit, the Self-Report Habit Inventory (SRHI).

Methods:

One hundred and seventy-four exercisers were surveyed at 2 private fitness clubs. A single questionnaire was administered that included the SRHI and the novel behavioral questions developed from habit formation concepts.

Results:

Habit formation was reported by many of the exercisers. Participants scoring higher on the SRHI also reported higher frequency of physical activity and a higher probability of environmental cuing. Exercise frequency did not correlate well with environmental cuing.

Conclusions:

Habit formation appears relevant to the physical activity patterns of many regular exercisers. However, wide variation in response styles was evident suggesting further development and exploration of the novel questionnaire is warranted. The ultimate goals are to include habit in predictive models of physical activity, and then to inform interventions to increase exercise adherence.

Restricted access

Stephen D. Herrmann, Tiago V. Barreira, Minsoo Kang and Barbara E. Ainsworth

Background:

There is little consensus on how many hours of accelerometer wear time is needed to reflect a usual day. This study identifies the bias in daily physical activity (PA) estimates caused by accelerometer wear time.

Methods:

124 adults (age = 41 ± 11 years; BMI = 27 ± 7 kg·m-2) contributed approximately 1,200 days accelerometer wear time. Five 40 day samples were randomly selected with 10, 11, 12, 13, and 14 h·d-1 of wear time. Four semisimulation data sets (10, 11, 12, 13 h·d-1) were created from the reference 14 h·d-1 data set to assess Absolute Percent Error (APE). Repeated-measures ANOVAs compared min·d-1 between 10, 11, 12, 13 h·d-1 and the reference 14 h·d-1 for inactivity (<100 cts·min-1), light (100−1951 cts·min-1), moderate (1952−5724 cts·min-1), and vigorous (≥5725 cts·min-1) PA.

Results:

APE ranged from 5.6%−41.6% (10 h·d-1 = 28.2%−41.6%; 11 h·d-1 = 20.3%−36.0%; 12 h·d-1 = 13.5%−14.3%; 13 h·d-1 = 5.6%−7.8%). Min·d-1 differences were observed for inactivity, light, and moderate PA between 10, 11, 12, and 13 h·d-1 and the reference (P < .05).

Conclusions:

This suggests a minimum accelerometer wear time of 13 h·d-1 is needed to provide a valid measure of daily PA when 14 h·d-1 is used as a reference.

Restricted access

Seung Ho Chang, Kyungun Kim, Jihyun Lee and Sukho Lee

Background: Children and youths from low-income families and certain ethnic minority groups show high levels of risk and vulnerability to physical inactivity. The aim of this review was to examine the effectiveness of interventions to increase physical activity (PA) in children and youths from low-income and ethnic minority (LIEM) families. Methods: Eight databases were systematically searched for PA interventions for LIEM children and youths. Twenty-six studies were included in the analyses. Effect sizes (ESs) were calculated using a random-effects model. The ESs were computed using Hedges g with 95% confidence interval. Results: There were small to medium effects of interventions on PA in LIEM children and youth (Q = 1499.193, df = 30, P < .05; I 2 = 97.999). Analyses on the moderator variables showed that ES for participants aged 9–12 years (ES = 0.542, P = .01); intervention length less than 13 weeks (ES = 0.561, P = .01); specialists as the intervention agent (ES = 0.680, P < .05); interventions without technology (ES = 0.363, P = .02); and interventions with a behavioral modification component (ES = 0.336, P = .03) were significantly different from zero. Conclusion: PA intervention can be an effective strategy to increase PA for LIEM children and youths.

Restricted access

Andreas Wolff Hansen, Inger Dahl-Petersen, Jørn Wulff Helge, Søren Brage, Morten Grønbæk and Trine Flensborg-Madsen

Background:

The International Physical Activity Questionnaire (IPAQ) is commonly used in surveys, but reliability and validity has not been established in the Danish population.

Methods:

Among participants in the Danish Health Examination survey 2007–2008, 142 healthy participants (45% men) wore a unit that combined accelerometry and heart rate monitoring (Acc+HR) for 7 consecutive days and then completed the IPAQ. Background data were obtained from the survey. Physical activity energy expenditure (PAEE) and time in moderate, vigorous, and sedentary intensity levels were derived from the IPAQ and compared with estimates from Acc+HR using Spearman’s correlation coefficients and Bland-Altman plots. Repeatability of the IPAQ was also assessed.

Results:

PAEE from the 2 methods was significantly positively correlated (0.29 and 0.49; P = 0.02 and P < 0.001; for women and men, respectively). Men significantly overestimated PAEE by IPAQ (56.2 vs 45.3 kJ/kg/day, IPAQ: Acc+HR, P < .01), while the difference was nonsignificant for women (40.8 vs 44.4 kJ/kg/day). Bland-Altman plots showed that the IPAQ overestimated PAEE, moderate, and vigorous activity without systematic error. Reliability of the IPAQ was moderate to high for all domains and intensities (total PAEE intraclass correlation coefficient = 0.58).

Conclusions:

This Danish Internet-based version of the long IPAQ had modest validity and reliability when assessing PAEE at population level.

Restricted access

John Cooper, Barbara Stetson, Jason Bonner, Sean Spille, Sathya Krishnasamy and Sri Prakash Mokshagundam

Background:

This study assessed physical activity (PA) in community dwelling adults with Type 2 diabetes, using multiple instruments reflecting internationally normed PA and diabetes-specific self-care behaviors.

Methods:

Two hundred and fifty-three Black (44.8%) and White (55.2%) Americans [mean age = 57.93; 39.5% male] recruited at low-income clinic and community health settings. Participants completed validated PA self-report measures developed for international comparisons (International Physical Activity Questionnaire Short Form), characterization of diabetes self-care (Summary of Diabetes Self-Care Activities Measure; SDSCA) and exercise-related domains including provider recommendations and PA behaviors and barriers (Personal Diabetes Questionnaire; PDQ).

Results:

Self-reported PA and PA correlates differed by instrument. BMI was negatively correlated with PA level assessed by the PDQ in both genders, and assessed with SDSCA activity items in females. PA levels were low, comparable to previous research with community and diabetes samples. Pain was the most frequently reported barrier; females reported more frequent PA barriers overall.

Conclusions:

When using self-report PA measures for PA evaluation of adults with diabetes in clinical settings, it is critical to consider population and setting in selecting appropriate tools. PA barriers may be an important consideration when interpreting PA levels and developing interventions. Recommendations for incorporating these measures in clinical and research settings are discussed.

Restricted access

Pedro F. Saint-Maurice, Greg Welk, Michelle A. Ihmels and Julia Richards Krapfl

Background:

The System for Observing Play and Leisure Activities (SOPLAY) is a direct observation instrument designed to assess group physical activity and environmental contexts. The purpose of this study was to test the convergent validity of the SOPLAY using temporally matched data from an accelerometry-based activity monitor.

Methods:

Accelerometry-based physical activity data were obtained from 160 elementary school children from 9 after-school activity programs. SOPLAY coding was used to directly observe physical activity during these sessions. Analyses evaluated agreement between the monitored and observed physical activity behavior by comparing the percent of youth engaging in physical activity with the 2 assessments.

Results:

Agreement varied widely depending on the way the SOPLAY codes were interpreted. Estimates from SOPLAY were significantly higher than accelerometer PA levels when codes of walking and vigorous were used (in combination) to reflect participation in moderate to vigorous PA (MVPA). Estimates were similar when only SOPLAY codes of vigorous were used to define MVPA (Difference = 1.33 ± 22.06%).

Conclusions:

SOPLAY codes of walking corresponded well with estimates of Light intensity PA. Observations provide valid indicators of MVPA if coding is based on the percentage of youth classified as “vigorous.”