632 resultados para Activity Recall
Resumo:
BACKGROUND Sedentary behavior is continuing to emerge as an important target for health promotion. The purpose of this study was to determine the validity of a self-report use of time recall tool, the Multimedia Activity Recall for Children and Adults (MARCA) in estimating time spent sitting/lying, compared with a device-based measure. METHODS Fifty-eight participants (48% female, [mean±standard deviation] 28±7.4 years of age, 23.9±3.05 kg/m2) wore an activPAL device for 24-h and the following day completed the MARCA. Pearson correlation coefficients (r) were used to analyse convergent validity of the adult MARCA compared with activPAL estimates of total sitting/lying time. Agreement was examined using Bland-Altman plots. RESULTS According to activPAL estimates, participants spent 10.4 hr/day [standard deviation (SD)=2.06] sitting or lying down while awake. The correlation between MARCA and activPAL estimates of total sit/lie time was r=0.77 (95% confidence interval = 0.64-0.86; p<0.001). Bland-Altman analyses revealed a mean bias of +0.59 hr/day with moderately wide limits of agreement (-2.35 hours to +3.53 hr/day). CONCLUSIONS This study found a moderate to strong agreement between the adult MARCA and the activPAL, suggesting that the MARCA is an appropriate tool for the measurement of time spent sitting or lying down in an adult population.
Resumo:
The purposes of this study were to describe and compare the specific physical activity choices and sedentary pursuits of African American and Caucasian American girls. Participants were 1,124 African American and 1,068 Caucasian American eighth grade students from 31 middle schools. The 3-Day Physical Activity Recall (3DPAR) was used to measure participation in physical activities and sedentary pursuits. The most frequently reported physical activities were walking, basketball, jogging or running, bicycling, and social dancing. Differences between groups were found in 11 physical activities and 3 sedentary pursuits. Participation rates were higher in African American girls (p<.001)for social dancing, basketball, watching television, and church attendance but lower in calisthenics, ballet and other dance, jogging or running, rollerblading, soccer, softball or baseball, using an exercise machine, swimming, and homework. Cultural differences of groups should be considered when planning interventions to promote physical activity.
Resumo:
Accurate process model elicitation continues to be a time consuming task, requiring skill on the part of the interviewer to extract explicit and tacit process information from the interviewee. Many errors occur in this elicitation stage that would be avoided by better activity recall, more consistent specification methods and greater engagement in the elicitation process by interviewees. Theories of situated cognition indicate that interactive 3D representations of real work environments engage and prime the cognitive state of the viewer. In this paper, our major contribution is to augment a previous process elicitation methodology with virtual world context metadata, drawn from a 3D simulation of the workplace. We present a conceptual and formal approach for representing this contextual metadata, integrated into a process similarity measure that provides hints for the business analyst to use in later modelling steps. Finally, we conclude with examples from two use cases to illustrate the potential abilities of this approach.
Resumo:
Accurate process model elicitation continues to be a time consuming task, requiring skill on the part of the interviewer to extract explicit and tacit process information from the interviewee. Many errors occur in this elicitation stage that would be avoided by better activity recall, more consistent specification methods and greater engagement in the elicitation process by interviewees. Metasonic GmbH has developed a process elicitation tool for their process suite. As part of a research engagement with Metasonic, staff from QUT, Australia have developed a 3D virtual world approach to the same problem, viz. eliciting process models from stakeholders in an intuitive manner. This book chapter tells the story of how QUT staff developed a 3D Virtual World tool for process elicitation, took the outcomes of their research project to Metasonic for evaluation, and finally, Metasonic’s response to the initial proof of concept.
Resumo:
With measurement of physical activity becoming more common in clinical practice, it is imperative that healthcare professionals become more knowledgeable about the different methods available to objectively measure physical activity behaviour. Objective measures do not rely on information provided by the patient, but instead measure and record the biomechanical or physiological consequences of performing physical activity, often in real time. As such, objective measures are not subject to the reporting bias or recall problems associated with self-report methods. The purpose of this article was to provide an overview of the different methods used to objectively measure physical activity in clinical practice. The review was delimited to heart rate monitoring, accelerometers and pedometers since their small size, low participant burden and relatively low cost make these objective measures appropriate for use in clinical practice settings. For each measure, strengths and weakness were discussed; and whenever possible, literature-based examples of implementation were provided.
Resumo:
Objective This study compared correlates of physical activity (PA) among African-American and white girls of different weight groups to guide future interventions. Research Methods and Procedures Participants were 1015 girls (mean age, 14.6 years; 45% African-American) from 12 high schools in South Carolina who served as control subjects for a school-based intervention. Post-intervention measures obtained at the end of ninth grade were used. PA was measured using the Three-Day PA Recall, and a questionnaire measured social-cognitive and environmental variables thought to mediate PA. Height and weight were measured, and BMI was calculated. Girls were stratified by race and categorized into three groups, based on BMI percentiles for girls from CDC growth charts: normal (BMI < 85th percentile), at risk (BMI, 85th to 94th percentile), and overweight (BMI ≥ 95th percentile). Girls were further divided into active and low-active groups, based on a vigorous PA standard (average of one or more 30-minute blocks per day per 3-day period). Mixed-model ANOVA was used to compare factors among groups, treating school as a random effect Results None of the social-cognitive or environmental variables differed by weight status for African-American or white girls. Perceived behavioral control and sports team participation were significantly higher in girls who were more active, regardless of weight or race group. In general, social-cognitive variables seem to be more related to activity in white girls, whereas environmental factors seem more related to activity in African-American girls. Discussion PA interventions should be tailored to the unique needs of girls based on PA levels and race, rather than on weight status alone.
Resumo:
BACKGROUND Although the prevalence of obesity in young children highlights the importance of early interventions to promote physical activity (PA), there are limited data on activity patterns in this age group. The purpose of this study is to describe activity patterns in preschool-aged children and explore differences by weight status. METHODS Analyses use baseline data from Healthy Homes/Healthy Kids- Preschool, a pilot obesity prevention trial of preschool-aged children overweight or at risk for overweight. A modified parent-reported version of the previous-day PA recall was used to summarize types of activity. Accelerometry was used to summarize daily and hourly activity patterns. RESULTS "Playing with toys" accounted for the largest proportion of a child's previous day, followed by "meals and snacks", and "chores". Accelerometry-measured daily time spent in sedentary behavior, light PA, and moderate-to-vigorous PA (MVPA) was 412, 247, and 69 minutes, respectively. Percent of hourly time spent in MVPA ranged from 3% to 13%, peaking in the late morning and evening hours. There were no statistically significant MVPA differences by weight status. CONCLUSIONS This study extends our understanding of activity types, amounts, and patterns in preschool-age children and warrants further exploration of differences in physical activity patterns by weight status.
Resumo:
Background Sedentary behaviour is associated with several deleterious health consequences. Although device-based measures of sedentary time are available, they are costly and do not provide a measure of domain specific sedentary time. High quality self-report measures are necessary to accurately capture domain specific sedentary time, and to provide an alternative to devices when cost is an issue. In this study, the Past-day Adults’ Sedentary Time (PAST) questionnaire, previously shown to have acceptable validity and reliability in a sample of breast cancer survivors, was modified for a university sample and validity of the modified questionnaire was examined compared with activPAL. Methods Participants (n = 58, age = 18–55 years, 48% female, 66% students) were recruited from the University of Queensland (students and staff). They answered the PAST questionnaire, which asked about time spent sitting or lying down for work, study, travel, television viewing, leisure-time computer use, reading, eating, socialising and other purposes, during the previous day. Time reported for these questions was summed to provide a measure of total sedentary time. Participants also wore an activPAL device for the full day prior to completing the questionnaire and recorded their wake and sleep times in an activity log. Total waking sedentary time derived from the activPAL was used as the criterion measure. Correlation (Pearson's r) and agreement (Bland–Altman plots) between PAST and activPAL sedentary time were examined. Results Participants were sedentary (activPAL-determined) for approximately 66% of waking hours. The correlation between PAST and activPAL sedentary time for the whole sample was r = 0.50 [95% confidence interval (CI) = 0.28–0.67]; and higher for non-students (r = 0.63, 95% CI = 0.26–0.84) than students (r = 0.46, 95% CI = 0.16–0.68). Bland–Altman plots revealed that the mean difference between the two measures was 19 min although limits of agreement were wide (95% limits of agreement −4.1 to 4.7 h). Discussion The PAST questionnaire provides an acceptable measure of sedentary time in this population, which included students and adults with high workplace sitting. These findings support earlier research that questionnaires employing past-day recall of sedentary time provide a viable alternative to existing sedentary behaviour questionnaires.