Validity of the previous day physical activity recall (PDPAR) in fifth-grade children

This study evaluated the validity of the Previous Day Physical Activity Recall (PDPAR) self-report instrument in quantifying after-school physical activity behavior in fifth-grade children. Thirty-eight fifth-grade students (mean age, 10.8 +/- 0.1; 52.6% female; 26.3% African American) from two urban elementary schools completed the PDPAR after wearing a CSA WAM 7164 accelerometer for a day. The mean within-subject correlation between self-reported MET level and total counts for each 30-min block was 0.57 (95% C.I., 0.51-0.62). Self-reported mean MET level during the after-school period and the number of 30-min blocks with activity rated at greater than or equal to 6 METs were significantly correlated with the CSA outcome variables. Validity coefficients for these variables ranged from 0.35 to 0.43 (p <.05). Correlations between the number of 30-min blocks with activity rated at greater than or equal to 3 METs and the CSA variables were positive but failed to reach statistical significance (r = 0.19-0.23). The PDPAR provides moderately valid estimates of relative participation in vigorous activity and mean MET level in fifth-grade children. Caution should be exercised when using the PDPAR to quantify moderate physical activity in preadolescent children.

Factors associated with physical activity in children attending family child care homes

Objective To determine the relationship between family child care home (FCCH) practices and characteristics, and objectively measured physical activity (PA) among children attending FCCHs. Methods FCCH practices and characteristics were assessed in 45 FCCHs in Oregon (USA) in 2010-2011 using the Nutrition and Physical Activity Self-Assessment for Child Care Instrument. Within the 45 FCCHs, 136 children between ages 2 and 5. years wore an accelerometer during child care attendance over a one-week period. Time spent in light, moderate, and vigorous PA per hour was calculated using intensity-related cut-points (Pate et al., 2006). Results FCCH characteristics and practices associated with higher levels of PA (min/h; p < 0.05) included provision of sufficient outdoor active play [32.2 (1.0) vs. 28.6 (1.3)], active play using portable play equipment [31.7 (1.0) vs. 29.3 (1.4)], the presence of a variety of fixed play equipment [32.2 (1.0) vs. 28.9 (1.3)], and suitable indoor play space [32.2 (1.0) vs. 28.6 (1.3)], engaging in active play with children [32.1 (1.1) vs. 29.6 (1.2)], and receiving activity-related training [33.1 (1.2) vs. 30.3 (1.1)]. Conclusions This is the first study to identify practices and characteristics of FCCHs that influence children's PA. These data should be considered when developing programs and policies to promote PA in FCCHs.

Advances in population surveillance for physical activity and sedentary behavior : reliability and validity of time use surveys

Many countries conduct regular national time use surveys, some of which date back as far as the 1960s. Time use surveys potentially provide more detailed and accurate national estimates of the prevalence of sedentary and physical activity behavior than more traditional self-report surveillance systems. In this study, the authors determined the reliability and validity of time use surveys for assessing sedentary and physical activity behavior. In 2006 and 2007, participants (n = 134) were recruited from work sites in the Australian state of New South Wales. Participants completed a 2-day time use diary twice, 7 days apart, and wore an accelerometer. The 2 diaries were compared for test-retest reliability, and comparison with the accelerometer determined concurrent validity. Participants with similar activity patterns during the 2 diary periods showed reliability intraclass correlations of 0.74 and 0.73 for nonoccupational sedentary behavior and moderate/vigorous physical activity, respectively. Comparison of the diary with the accelerometer showed Spearman correlations of 0.57-0.59 and 0.45-0.69 for nonoccupational sedentary behavior and moderate/vigorous physical activity, respectively. Time use surveys appear to be more valid for population surveillance of nonoccupational sedentary behavior and health-enhancing physical activity than more traditional surveillance systems. National time use surveys could be used to retrospectively study nonoccupational sedentary and physical activity behavior over the past 5 decades.

State of the art reviews : measurement of physical activity in children and adolescents

To date, a wide range of methods has been used to measure physical activity in children and adolescents. These include self-report methods such as questionnaires, activity logs, and diaries as well as objective measures of physical activity such as direct observation, doubly labeled water, heart rate monitoring, accelerometers, and pedometers. The purpose of this review is to overview the methods currently being used to measure physical activity in children and adolescents. For each measurement approach, new developments and/or innovations are identified and discussed. Particular attention is given to the use of accelerometers and the calibration of accelerometer output to units of energy expenditure to developing children.

Validity and reliability of the 3-day physical activity recall in Singaporean adolescents

Childhood obesity and physical inactivity are major health concerns for the Singaporean government (Ministry of Health, Singapore [MOH], 2001). Data from the 1998 Singaporean National Health Survey indicate that 10.8–14.7% of Singaporean children ages 6–16 years are either overweight or obese (MOH, 2001). Although true population estimates of youth physical activity are not available, descriptive epidemiological studies conducted in the 1990s suggest that a large percentage of school-aged children in Singapore fail to meet established guidelines for participation in physical activity...

Compliance with physical activity guidelines : prevalence in a population of children and youth

PURPOSE To use objective monitoring of physical activity to determine the percentages of children and youth in a population that met physical activity guidelines. METHODS A total of 375 students in grades 1–12 wore an accelerometer (CSA 7164) for seven consecutive days. Bouts of continuous activity and accumulation of minutes spent in physical activity at various intensities were calculated to determine how many students met three physical activity guidelines. RESULTS Over 90% of students met Healthy People 2010, Objective 22.6 and nearly 70% met the United Kingdom Expert Consensus Group guideline, both of which recommend daily accumulation of moderate physical activity. Less than 3% met Healthy People 2010, Objective 22.7, which calls for bouts of continuous vigorous physical activity. For the United Kingdom Expert Consensus Group guideline, compliance decreased markedly with age, but gender differences were not statistically significant. CONCLUSIONS Prevalence estimates for compliance with national physical activity guidelines varied markedly for the three guidelines examined. Objective monitoring of physical activity in youth appears to be feasible and may provide more accurate prevalence rates than self-report measures.

Objective measurement of physical activity in youth : current issues, future directions

Second-generation activity monitors have revolutionized the way in which we measure youth physical activity. Use of the monitors avoids the problems associated with self-report methods and allows for the estimation of physical activity patterns over time. This article examines important methodological issues related to the use of activity monitors in children and adolescents.

Encouragement of physical activity for weight loss may lead to negative psychological outcomes among girls

PURPOSE To examine correlates and consequences of parents' encouragement of girls' physical activity (PA) for weight loss (ENCLOSS). METHODS Data were collected for 181 girls, mothers and fathers when girls were 9, 11, and 13 years old. Mothers and fathers completed a self-report questionnaire of ENCLOSS (e.g., “I have talked to my daughter about how to exercise to lose weight”). Correlates of ENCLOSS that were assessed include girls' Body Mass Index (BMI) z-score and parents' modeling of and logistic support for PA. Dependent variables assessed at age 13 include girls' self-reported and objectively-measured PA, enjoyment of physical activity, and weight concerns. Associations between ENCLOSS, girls' BMI, and parent's support for PA were assessed using spearman rank correlations. To examine links between ENCLOSS and the outcome variables, scores for ENCLOSS were divided into tertiles at each age. Three groups were created including girls who were in the highest tertile at each age (high ENCLOSS), girls who were in the lowest tertile at each age (low ENCLOSS), and girls who varied in their tertile ranking (mid ENCLOSS). Group differences in the outcome variables were assessed using regression analysis (referent group: low ENCLOSS), controlling for girls' BMI and the outcome variable at age 9. RESULTS Girls' with higher BMI had mothers and fathers who reported higher ENCLOSS (r = .61-. 69, p<. 0001). Parents'reports of ENCLOSS were not associated with modeling of or logistic support for PA. Girls in the high ENCLOSS group reported significantly lower enjoyment of PA and higher weight concerns at age 13, independent of covariates. No differences in PA were noted. CONCLUSION Parents who encourage their daughters to be active for weight loss do not model PA or facilitate girls' PA. Persistent encouragement of PA for weight loss may lead to low enjoyment of PA and higher weight concerns among adolescent girls.

Are mothers of young children really inactive?

Australian surveys have found that only 43% of women meet the current recommendation for regular moderate physical activity, and that women who are mothers of young children are even less likely to be adequately active for health benefit. These women spend a significant proportion of their day in occupational, household and care-giving activities, which may not be ‘captured’ in conventional physical activity surveys. The purpose of this study was to compare physical activity in young mothers and age-matched controls using three different measures of physical activity. 35 women (16 mothers of young children, M) and 19 age-matched comparison women (NM) completed a survey which asked about walking to and from places, and about moderate and vigorous activity in leisure time and at work (paid and unpaid). They also kept a detailed diary of all their activities for two week-days and two week-end days, and wore a pedometer (Yamax digiwalker) on these days. Each activity in the diary was assigned an energy expenditure (EE) score based on it's intensity (Compendium of Physical Activity) and time spent in that activity. There were no differences between M and NM for pedometer steps (M: 9270 sd 2947; NM: 9768 sd 3051) or for daily energy expenditure (EE) calculated from the diaries (M: 2029 sd 189; NM: 2015 sd 169 METS.mins) or survey (M: 2079 sd 448; NM: 1495 sd 325). There was a significant correlation between pedometer steps and daily METs.mins estimated from the diaries (r = 0.35, p = 0.04); however no relationship was observed between pedometer steps and EE from the survey (r = .09, p = .56). Further analysis of the individual survey items found pedometer steps to be related to EE from walking to and from places (r = .34) and leisure time (r = .31), but not work related activity (r = -.08). There were no significant relationships between EE computed from the diaries and any of the survey questions. The three activity measures indicate that the physical activity levels of the young mothers in our sample were comparable to age-matched non-mothers. The results of the correlation analyses highlight the difficulty of assessing low-intensity work-related physical activity via self-report. Supported by Australian Commonwealth Department of Health and Aged Care.

Test-retest reliability of physical activity measures used in Australian population surveys

PURPOSE Accurate monitoring of prevalence and trends in population levels of physical activity is fundamental to the planning of health promotion and disease-prevention strategies. Test-retest reliability (repeatability) was assessed for four self-report measures of physical activity commonly used in population surveys: the Active Australia survey (AA, N=356), the short form of the International Physical Activity Questionnaire (IPAQ-S, N=104), the physical activity items in the Behavioral Risk Factor Surveillance System (BRFSS, N=127) and the physical activity items in the Australian National Health Survey (NHS, N=122). METHODS Percent agreement and Kappa statistics were used to assess the reliability of classification of activity status (where ‘active’= 150 minutes of activity per week) and sedentariness (where ‘sedentary’ = reporting no physical activity). Intraclass correlations (ICCs) were used to assess agreement on minutes of activity reported for each item of each survey and on total minutes reported in each survey. RESULTS Percent agreement scores for both activity status and sedentariness were very good on all four instruments. Overall the percent agreement between repeated surveys was between 73% (NHS) and 87% (IPAQ) for the criterion measure of achieving 150 minutes per week, and between 77% (NHS) and 89% (IPAQ) for the criterion of being sedentary. Corresponding Kappa statistics ranged from 0.46 (NHS) to 0.61 (AA) for activity status and from 0.20 (BRFSS) to 0.52 (AA) for sedentariness. For the individual items ICCs were highest for walking (0.45 to 0.56) and vigorous activity (0.22 to 0.64) and lowest for the moderate questions (0.16 to 0.44). CONCLUSION All four measures provide acceptable levels of test-retest reliability for assessing both activity status and sedentariness, and moderate reliability for assessing total minutes of activity. Supported by the Australian Commonwealth Department of Health and Ageing.

Methods for sociological inquiry on emotion in educational settings

Sociological approaches to inquiry on emotion in educational settings are growing. Despite a long tradition of research and theory in disciplines such as psychology and sociology, the methods and approaches for naturalistic investigation of emotion are in a developmental phase in educational settings. In this article, recent empirical studies on emotion in educational contexts are canvassed. The discussion focuses on the use of multiple methods within research conducted in high school and university classrooms highlighting recent methodological progress. The methods discussed include facial expression analysis, verbal and non-verbal conduct, and self-report methods. Analyses drawn from different studies, informed by perspectives from microsociology, highlight the strengths and limitations of any one method. The power and limitations of multi-method approaches is discussed.

Real or imagined? A study exploring the existence of common method variance effects in road safety research

Common method variance (CMV) has received little attention within the field of road safety research despite a heavy reliance on self-report data. Two surveys were completed by 214 motorists over a two-month period, allowing associations between social desirability and key road safety variables and relationships between scales across the two survey waves to be examined. Social desirability was found to have a strong negative correlation with the Driver Behaviour Questionnaire (DBQ) sub-scales as well as age, but not with crashes and offences. Drivers who scored higher on the social desirability scale were also less likely to report aberrant driving behaviours as measured by the DBQ. Controlling for social desirability did not substantially alter the predictive relationship between the DBQ and the crash and offences variables. The strength of the correlations within and between the two waves were also compared with the results strongly suggesting that effects associated with CMV were present. Identification of CMV would be enhanced by the replication of this study with a larger sample size and comparing self-report data with official sources.

Using the Driver Behaviour Questionnaire to predict crashes and demerit point loss : does it get better with larger sample sizes?

The Driver Behaviour Questionnaire (DBQ) continues to be the most widely utilised self-report scale globally to assess crash risk and aberrant driving behaviours among motorists. However, the scale also attracts criticism regarding its perceived limited ability to accurately identify those most at risk of crash involvement. This study reports on the utilisation of the DBQ to examine the self-reported driving behaviours (and crash outcomes) of drivers in three separate Australian fleet samples (N = 443, N = 3414, & N = 4792), and whether combining the samples increases the tool’s predictive ability. Either on-line or paper versions of the questionnaire were completed by fleet employees in three organisations. Factor analytic techniques identified either three or four factor solutions (in each of the separate studies) and the combined sample produced expected factors of: (a) errors, (b) highway-code violations and (c) aggressive driving violations. Highway code violations (and mean scores) were comparable across the studies. However, across the three samples, multivariate analyses revealed that exposure to the road was the best predictor of crash involvement at work, rather than DBQ constructs. Furthermore, combining the scores to produce a sample of 8649 drivers did not improve the predictive ability of the tool for identifying crashes (e.g., 0.4% correctly identified) or for demerit point loss (0.3%). The paper outlines the major findings of this comparative sample study in regards to utilising self-report measurement tools to identify “at risk” drivers as well as the application of such data to future research endeavours.

Food insecurity and physical activity among U.S. populations

Objectives: Examine the association between food insecurity (FI) and physical activity (PA) in the U.S. population. Methods: Accelerometry (PAM) and self-report PA (PAQ) data from NHANES 2003-2006 were used. Those aged less than six years or were older than 65 years, pregnant, with physical limitations, or with family income above 350% of the poverty line were excluded. FI was measured by the USDA Household Food Security Survey Module. Crude and adjusted odd ratios were calculated from logistic regression to identify the association between FI and adherence to the PA recommendation. Crude and adjusted coefficients were calculated from linear regression to identify the association between FI and both sedentary and activity minutes. Results: In children, FI was not associated with adherence to PA recommendation measured via PAM or PAQ (p>0.05) but was significantly associated with sedentary minutes (adjusted coefficient=10.74, one-sided p<0.05). Food-insecure children did less moderate-to-vigorous PA than did food-secure children (adjusted coefficient = -5.31, p = 0.032). In adults, FI was significantly associated with PA (adjusted OR=0.722 for PAM and OR=0.839 for PAQ, one-sided p<0.05) but not associated with sedentary minutes (p>0.05) Conclusions: FI children were more sedentary and FI adults were less likely to adhere to the PA recommendation than those without FI.

Choice impulsivity: Definitions, measurement issues, and clinical implications

Background Impulsivity critically relates to many psychiatric disorders. Given the multifaceted construct that impulsivity represents, defining core aspects of impulsivity is vital for the assessment and understanding of clinical conditions. Choice impulsivity (CI), involving the preferential selection of smaller sooner rewards over larger later rewards, represents one important type of impulsivity. Method The International Society for Research on Impulsivity (InSRI) convened to discuss the definition and assessment of CI and provide recommendations regarding measurement across species. Results Commonly used preclinical and clinical CI behavioral tasks are described, and considerations for each task are provided to guide CI task selection. Differences in assessment of CI (self-report, behavioral) and calculating CI indices (e.g., area-under-the-curve, indifference point, steepness of discounting curve) are discussed along with properties of specific behavioral tasks used in preclinical and clinical settings. Conclusions The InSRI group recommends inclusion of measures of CI in human studies examining impulsivity. Animal studies examining impulsivity should also include assessments of CI and these measures should be harmonized in accordance with human studies of the disorders being modeled in the preclinical investigations. The choice of specific CI measures to be included should be based on the goals of the study and existing preclinical and clinical literature using established CI measures.