Measuring Physical Activity of Elementary School ...

Journal of Nursing Measurement, Volume 23, Number 2, 2015

Measuring Physical Activity of Elementary School Children With Unsealed Pedometers: Compliance, Reliability, and Reactivity Jiying Ling, PhD, MS, RN College of Nursing, Michigan State University, East Lansing, Michigan

Kristi M. King, PhD, CHES Department of Health and Sport Sciences, University of Louisville, Kentucky Background and Purpose: Evidence of compliance, reliability, and reactivity of using pedometers in children remains inconsistent. This study aimed to examine these aspects of unsealed pedometers. Methods: There were 133 children who wore pedometers for 7 days. A subsample of 50 children completed surveys measuring self-efficacy, enjoyment, parental influence, and environment on Day 1 and 8. Investigator presence and incentives were used to increase compliance. Results: About 87% of children returned pedometers, with 62% wearing pedometers for 4 days or longer. The intraclass correlation coefficients ranged from .70 to .87, with ICC for 4-day pedometer steps exceeding .80. Wearing pedometers did not change pedometer steps nor alter children’s perceptions of self-efficacy, enjoyment, parental influence, and environment significantly. Conclusions: Children were compliant wearing pedometers, and there was no reactivity from wearing them. Keywords: measurement; physical activity; pedometer; child; psychometrics

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ack of consistent physical activity is a significant contributor to the current childhood obesity epidemic in the United States (Hills, Andersen, & Byrne, 2011). Obesity rates are disproportionately higher among children aged 6–11 years old compared to preschoolers aged 2–5 years old or adolescents aged 12–18 years old (Ogden & Carroll, 2010). For children who participate in afterschool programs, their prevalence (39%) of overweight or obesity is higher than the national average of 32% (Trost, Rosenkranz, & Dzewaltowski, 2008) and their physical activity levels decreased from 2004 to 2008 (Arundell et al., 2013). Considering the key role of physical activity in preventing and controlling childhood obesity, accurate measurement of physical activity is paramount for both observational and interventional studies. Various instruments have been developed to assess physical activity among children. Pedometers are the most widely used devices because they are relatively inexpensive ($10–$50; McClain & Tudor-Locke, 2009), user-friendly (Clemes & Biddle, 2013), objective (Clemes & Biddle, 2013), reliable (Rowe, Mahar, Raedeke, & Lore, 2004), and valid (McNamara, Hudson, & Taylor, 2010). © 2015 Springer Publishing Company 271 http://dx.doi.org/10.1891/1061-3749.23.2.271

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Although significant strides and accomplishments in rigorous research have been made to address the psychometric properties and feasibility of using pedometers, other issues such as compliance of wearing and returning pedometers, the number of weekday and/ or weekend days of data needed, and behavioral and psychosocial reactivity of wearing pedometers still exist and need further clarification, especially in children. Previous research with U.S. children reported the compliance of wearing pedometers ranging from 46% to 98%, with most studies reporting a compliance of 60% (Drenowatz et al., 2010; Eisenmann, Laurson, Wickel, Gentile, & Walsh, 2007; Strycker, Duncan, Chaumeton, Duncan, & Toobert, 2007). However, no study has been identified to investigate the strategies to increase children’s compliance of wearing and returning pedometers. Because children’s physical activity habits may vary from day to day because of weather, school attendance, and participation in sports or physical education, there is no consistent evidence on how many days and which days (weekday vs. weekend) are needed to reliably and adequately estimate children’s physical activity without producing avoidable participation burden (Clemes & Biddle, 2013). Few studies have investigated the number of days needed to obtain a reliable estimate of children’s physical activity. One study of 11,669 children aged 5–19 years old suggests that 2 days is sufficient to determine average daily steps of children (Craig, Tudor-Locke, Cragg, & Cameron, 2010). Some researchers, however, suggest using 7 consecutive days or at least 1 weekday and 1 weekend day (Clemes & Biddle, 2013), whereas others recommend 4 full days with at least 1 weekend day (Dollman et al., 2009; Ling, King, Speck, Kim, & Wu, 2014). Another reliability concern is the reactivity of wearing pedometers among children. Reactivity occurs when the study procedure influences individuals’ behaviors or perceptions (Rowe et al., 2004). Using pedometers to assess children’s physical activity may increase the number of steps they normally take simply because they are being monitored. No consistent evidence of reactivity is evident in studies using pedometers to assess children’s physical activity (Craig et al., 2010; Rowe et al., 2004). When using unsealed or sealed pedometers, several studies reported no indication of reactivity of children wearing pedometers (Ozdoba, Corbin, & Le Masurier, 2004; Prewitt, Hannon, & Brusseau, 2013; Vincent & Pangrazi, 2002). Craig and colleagues (2010) did find significant differences among 7-day pedometer steps when using unsealed pedometers, although no significant differences occurred between 2 consecutive days. Similarly, another study of 1,115 New Zealand children found that children took more steps on weekdays compared to weekend days when using sealed pedometers (Duncan, Schofield, & Duncan, 2006). No systematic bias was found for the day of the week to start recoding pedometer steps (Craig et al., 2010). Considering the earlier mentioned measurement concerns of using pedometers in children, the purpose of this study was to examine the compliance, reliability, and reactivity of using unsealed pedometers to assess physical activity of elementary school children attending nonphysical activity–focused, afterschool programs. Results of this study may provide valuable information for future researchers and practitioners to increase compliance and reliability of using pedometers to assess children’s physical activity.

CONCEPTUAL FRAMEWORK The youth physical activity promotion model developed by Welk (1999) was used to select the psychosocial and environmental determinants of physical activity to examine if wearing pedometers can influence children’s perceptions of physical activity self-efficacy,

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enjoyment, parental influence, and environment. This model adopts a social-ecological perspective to highlight the influence of personal, social, and environmental factors on physical activity. The selection of the determinants was based on literature (Craggs, Corder, van Sluijs, & Griffin, 2011; Sallis, Prochaska, & Taylor, 2000) supporting that physical activity self-efficacy, enjoyment, parental influence, and environment are the most significant determinants of physical activity for children.

METHODS Design All participating children were asked to wear an unsealed pedometer for 7 consecutive days. A test–retest design was used to examine the influence of wearing pedometers on children’s perceptions of physical activity self-efficacy, enjoyment, parental influence, and environment in a randomly selected subsample of 50 children. Approval from university institutional review board (IRB), parental consent, and child assent were received before any data collection.

Participants Cluster sampling was used to recruit children from 10 elementary schools with afterschool programs in a midwestern school district in the United States from August 2013 through October 2013. There were 133 children, 59 girls and 74 boys, who participated. Their mean age was 9.25 (SD 5 .93) years. Most children were White, about 20% were Hispanic, and 26% were African American. This distribution was relatively representative of the ethnic/racial characteristics of American children attending afterschool programs (Afterschool Alliance & JCPenney Afterschool, 2009). Nearly half of the children were overweight or obese, with 18.8% (n 5 25) being overweight and 30.1% (n 5 40) being obese. More than half of the children’s parents were married, and their household had an average of three children. Approximately 43% of the families had an annual family income less than $30,000, which is within the poverty level for households with five persons (U.S. Department of Health and Human Services, 2013). About 18% of the fathers and 15% of the mothers were unemployed; 50% of the fathers and 43% of the mothers received a high school diploma or less. Table 1 describes the demographic characteristics of all participants (N 5 133) and the subsample of children who participated in the test–retest study (n 5 50). No significant demographic differences were found between the two groups of children, indicating that the subsample was representative of the total sample.

Measures Body Mass Index. Children’s body mass index (BMI) was calculated with height and weight (weight kg/height m2; Centers for Disease Control and Prevention, 2011). Height was measured to the nearest 10th of a centimeter using a Seca 213 portable stadiometer, whereas weight was assessed to the nearest 10th of a kilogram using the Tanita HD-351 Scale. The age- and gender-specific percentile for BMI was used to assess children’s obesity status. Physical Activity. The Yamax SW-200 is the most commonly used pedometer to assess physical activity among children and has demonstrated moderate to strong evidence of validity with Pearson correlation coefficients ranging from .39 to .99 with heart rate and

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TABLE 1. Demographic Characteristics of Participants (N 5 133)

Variable Age Gender (female) Ethnicity (Hispanic) Race White or Caucasian Black or African Asian/Pacific Island Mixed race Other Number of children Parents’ marital status Married/partnered Separated/widowed Single Annual family income $19,999 $20,000–$29,999 $30,000–$49,999 $50,000 Father employment status Full time Part time No Mother employment status Full time Part time No Father education level ,High school graduate High school graduate Some college Community college Bachelor’s degree Graduate degree Mother education level ,High school graduate High school graduate Some college Community college Bachelor’s degree Graduate degree

Participants (N 5 133) N (%) or M (SD)

Subsample (n 5 50) N (%) or M (SD)

9.26 (0.93) 59 (44.4%) 27 (20.3%)

9.28 (0.90) 21 (42.0%) 11 (22.0%)

68 (51.1%) 34 (25.6%) 2 (1.5%) 11 (8.3%) 10 (7.5%) 2.71 (1.42)

26 (52.0%) 8 (16.0%) 0 7 (14.0%) 4 (8.0%) 2.32 (1.00)

76 (57.1%) 27 (20.3%) 30 (22.6%)

29 (58.0%) 7 (14.0%) 14 (28.0%)

37 (27.8%) 20 (15.0%) 29 (21.8%) 41 (30.8%)

13 (26.0%) 9 (18.0%) 11 (22.0%) 15 (30.0%)

78 (58.6%) 17 (12.8%) 24 (18.0%)

31 (62.0%) 5 (10.0%) 6 (12.0%)

87 (65.4%) 26 (19.5%) 20 (15.0%)

35 (70.0%) 11 (22.0%) 4 (8.0%)

p Value .874 .775 .801 .925

.080 .845

.999

.315

.429

.802 20 (15.0%) 47 (35.3%) 28 (21.1%) 9 (6.8%) 11 (8.3%) 4 (3.0%)

5 (10.0%) 20 (40.0%) 12 (24.0%) 1 (2.0%) 3 (6.0%) 1 (2.0%)

21 (15.8%) 36 (27.1%) 29 (21.8%) 17 (12.8%) 24 (18.0%) 6 (4.5%)

5 (10.0%) 14 (28.0%) 12 (24.0%) 7 (14.0%) 9 (18.0%) 3 (6.0%)

.485


oxygen consumption (McNamara et al., 2010; Sirard & Pate, 2001). Children were asked to wear an unsealed pedometer for 7 consecutive days and record their daily step counts in a pedometer log. The average daily steps were used to describe their physical activity. Evidence suggests that 13,000 steps/day for boys and 11,000 steps/day for girls provide a reasonable estimation of attainment of 60 min of moderate- or vigorous-intensity physical activity (Tudor-Locke et al., 2011). Thus, these cut points were used to assess the percentage of children meeting daily physical activity recommendations. Physical Activity Self-Efficacy. The Physical Activity Self-Efficacy Scale (PASES) is a self-administered 17-item measure used to assess children’s confidence in overcoming barriers to physical activity. Items are scored on a dichotomous scale (1 5 yes and 0 5 no), with a higher total score indicating greater physical activity self-efficacy (Saunders et al., 1997). Principal component factor analysis with varimax rotation suggested a threefactor structure: support seeking (7 items), barriers (4 items), and positive alternatives (6 items; Saunders et al., 1997). This scale had adequate reliability with Cronbach’s alpha coefficients ranging from .68 to .79 (Huhman et al., 2007) and test–retest reliability coefficients ranging from .75 to .82 (Thompson et al., 2008). In this study, the entire scale had a Cronbach’s alpha of .73 with alpha ranging from .61 to .64 for subscales and test–retest reliability coefficient (intraclass correlation coefficient [ICC]) of .83, which are considered appropriate for social sciences research (Nunnally & Bernstein, 1994). Physical Activity Enjoyment. The Physical Activity Enjoyment Scale (PACES) is a 16-item self-report instrument that assesses children’s positive affect associated with participation in physical activity. Items are scored on a 5-point Likert scale (1 5 disagree a lot to 5 5 agree a lot), with a higher total score indicating higher physical activity enjoyment (Moore et al., 2009). In 2009, Moore and colleagues tested the 16-item PACES in 564 third grade children. Results indicated that the scale had acceptable internal consistency with Cronbach’s alpha coefficient of .87. Moreover, physical activity enjoyment was significantly correlated with task goal orientation, perceptions of athletic competence, physical appearance, and self-reported physical activity, indicating this scale had acceptable convergent validity. This scale had a Cronbach’s alpha of .83 and test–retest reliability coefficient (ICC) of .63 in this study, which are considered appropriate for social sciences research (Nunnally & Bernstein, 1994). Parental Influence. The Parental Influence Scale (PAIS) is an 18-item scale with two components: parental support (parental involvement, parental facilitation, and parental encouragement; 12 items) and parental role modeling (6 items). The original PAIS used a 4-point structured alternative format Likert scale ([a] decide which of the two children is most like you [A or B] and [b] pick a side, decide whether this is “really true” or just “sort of true”; Welk, Wood, & Morss, 2003), with a higher total score indicating higher levels of parental influence. A study in 994 3rd- to 6th-grade children found that this scale had acceptable internal consistency with Cronbach’s alpha of .81 (Welk et al., 2003). The bipolar statements (Some kids have parents who get a lot of exercise vs. Other kids have parents who don’t get a lot of exercise) in the PAIS were found to be confusing for children in a pilot study with 24 elementary school children; thus, the bipolar statements were changed to unipolar statements following King, Ogletree, Fetro, Brown, and Partridge’s (2011) suggestion. In one study of 176 adolescents using unipolar statements, Cronbach’s alpha was .79 for the parental role modeling subscale and .89 for the parental support subscale, indicating acceptable internal consistency (King et al., 2011). In this study, the Cronbach’s alpha coefficients were .76, .68, and .82 and the test–retest reliability coefficients (ICC) were .74, .81, and .84 for the parental support subscale, parental role modeling subscale, and entire scale, respectively.

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Environment. The 4-item, 5-point Likert Measure of Perceived Environment was developed by Motl and colleagues (2005) and tested among 633 adolescent girls. Confirmatory factor analysis supported the two-factor structure: equipment accessibility (two items) and neighborhood safety (two items). The equipment accessibility subscale included only home and community components. For children who spend most of their time in school, school environment is an indispensable component that influences children’s physical activity (Bacardí-Gascon, Perez-Morales, & Jimenez-Cruz, 2012). Thus, Item 5, At school, there are playgrounds, gym spaces, and enough supplies (like balls, hula hoops) to use for physical activity, was added by the first author (JL) to address the school component of equipment accessibility. The total score of the five items was used to describe the perceived environment with a higher score indicating a more supportive environment for physical activity. In this study, the modified environment scale had Cronbach’s alpha coefficients ranging from .49 to .66 and test–retest reliability coefficients (ICC) ranging from .53 to .61, which are adequate considering the small number of items (Cortina, 1993). A principal component analysis with a varimax rotation was conducted and yielded a twofactor structure: equipment accessibility and neighborhood safety. Results from a further confirmatory factor analysis showed that the two-factor structure fit the data adequately, x2(4) 5 1.31, p 5 .859, Hoelter’s Critical N 5 910, standardized root mean square residual 5 .02, goodness-of-fit index 5 1.00, adjusted goodness-of-fit index 5 .98, root mean square error of approximation 5 .00 with 90% confidence interval (CI) [.00–.07], comparative fit index 5 1.00, normed fit index 5 .98, expected cross-validation index 5 .19, Aikake’s information criterion 5 23.31, indicating good construct validity. Personal Demographics. An investigator-developed demographic information questionnaire, adapted from a prior version used in the pilot study, was used to collect demographic information. This questionnaire was completed by children’s parents or their legal guardians. The demographic questionnaire included child’s age, gender, ethnicity, and race; number of children in the family; parents’ marital status; annual family income; and parents’ employment status and education level.

Data Collection After receiving IRB approval, the first author (JL) visited the selected 10 elementary schools with afterschool programs to explain the study purposes and procedures. There were 146 eligible children who received a recruitment folder containing a letter describing the voluntary nature of the research study, a demographic information questionnaire, and the informed consent document. Children were instructed to take the folder home to their parents or legal guardians to review. The telephone number and e-mail address of the first author (JL) were provided so that parents or legal guardians had an opportunity to discuss the study if desired. The recruitment folders were returned by the children to their teacher or program director and held for the research staff or given directly to the research staff in the data collection setting. Six eligible children (three girls and three boys) did not participate because of parents’ lack of consent. To increase the likelihood that children would return the consent form and demographic instrument, all children who brought back the informed consent form from parents/guardians, regardless of agreement or not, were included in a drawing of five basketballs. After obtaining parental consent, the first author (JL) explained all study procedures to children. Seven children (five girls and two boys) did not want to participate because of lack of fun, “challenge of wearing pedometers,” or did not want to complete surveys.


After obtaining both parental consent and child assent, the first author (JL) measured each child’s height and weight in a private room, distributed the pedometers and pedometer logs (with wearing instructions on the logs) to children, and reviewed detailed instructions with them. Each child was asked to attach the pedometer to the waistband of his or her clothing directly in-line with the knee in accordance to the manufacturer’s directions in the morning from Day 1 to Day 7. The children were instructed to keep the pedometer dry and leave it on until he or she went to bed. To improve compliance, every school day afternoon, the first author (JL) visited the afterschool programs to help children record the step counts in two pedometer logs (one for research and one for child), reset pedometers to zero after recording, and remind children to wear the pedometers if they had forgotten. On the weekend, children were instructed to record their step counts in their pedometer logs with the help of their parents/guardians. Seven days later, children were asked to return the pedometers and pedometer logs to the first author (JL) or school staff. For children who completed the whole study, a further incentive gift (a playground ball) was awarded. In addition to the earlier mentioned pedometer data collection procedures for all children, 50 randomly selected children participating in the test–retest study were also asked to complete a series of short surveys assessing physical activity self-efficacy, enjoyment, parental influence, and environment on the day they signed the assent but before they received pedometers (test, Day 1) and again on the day after they returned their pedometers (retest, Day 8). Children completed the surveys in a private room/place, with the first author (JL) sitting with each child reading the survey directions and each item to ensure that children understood the questions. Questionnaires were checked for missing data after children completed the surveys, and the first author (JL) asked children to provide responses for the missing data if they were willing to.

Data Analysis The Statistical Analysis System (SAS) Version 9.3 for Windows was used to analyze data. Evidence suggests that pedometer step counts less than 1,000 or greater than 30,000 should be considered outliers (Rowe et al., 2004), therefore were truncated in this study. Descriptive statistics were used to describe the demographic characteristics of children. Continuous variables were described using means (Ms) and standard deviations (SDs), whereas categorical variables were described by frequencies and percentages. To examine the influence of wearing pedometers on children’s physical activity and how children’s physical activity changed according to day of the week, pedometer data were entered twice: Day 1 to Day 7 and Monday to Sunday. A mixed linear regression model (Brown & Prescott, 2006) was used to examine the change trend of children’s pedometer steps over time. The paired-samples t test was used to compare differences in means of pedometer steps between 2 consecutive days. The ICC was estimated by a two-way mixed model (people effects are random and time effects are fixed) with type consistency (systemic differences between two tests are considered irrelevant)—ICC (3, k) model (McGraw & Wong, 1996; Weir, 2005)—to assess the reliability of pedometer steps. Usually, a scale with ICC , .40 has poor reliability, a scale with .40  ICC , .75 has fair to good reliability, and a scale with ICC  .75 has excellent reliability (Zaki, Bulgiba, Nordin, & Ismail, 2013). The analysis process for assessing reliability of pedometer steps recommended by Rowe and colleagues (2004) was used. The paired-samples t test was used to examine the differences of physical activity self-efficacy,

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enjoyment, parental influence, and environment scores between test and retest among the randomly selected subsample of 50 children.

RESULTS Physical Activity Children took an average of 7,868 (SD 5 3,526) pedometer steps per day. Based on the mean number of pedometer steps, 13.5% (n 5 10) of boys and 11.9% (n 5 7) of girls met physical activity recommendations, that is, 13,000 steps/day for boys and 11,000 steps/ day for girls. The daily step count cut points for boys are (a) less than 10,000 (sedentary), (b) 10,000–12,499 (low active), (c) 12,500–14,999 (somewhat active), (d) 15,000–17,499 (active), and (e) 17,500 or more (highly active) steps/day and for girls are (a) less than 7,000, (b) 7,000–9,499,(c) 9,500–11,999, (d) 12,000–14,499, and (e) 14,500 or more steps/ day (Tudor-Locke et al., 2011). Based on these cut points, approximately 59.5% (n 5 44) boys and 52.5% (n 5 31) girls were sedentary, 18.9% (n 5 14) boys and 30.5% (n 5 18) girls were low active, 9.5% (n 5 7) boys and 6.8% (n 5 4) girls were somewhat active, 4.1% (n 5 3) boys and 5.1% (n 5 3) girls were active, and only 4% (n 5 2) girls were highly active. On average, boys took more pedometer steps than girls, 8,441 6 3,685 vs. 7,197 6 3,233, t(124) 5 2.02, p 5 .046. Only one child, an 8-year-old girl, met the national recommendation by accumulating at least 11,000 steps each day.

Compliance Among the 133 children, 87.2% (n 5 116) returned their pedometers at retest and 12.8% (n 5 17) lost their pedometers. About 38.4% (n 5 51) of the children wore pedometers for 7 days, 12% (n 5 16) wore pedometers for 6 days, 9% (n 5 12) wore pedometers for 5 days, and 3% (n 5 4) wore pedometers for 4 days. There were 62.4% (n 5 83) wore pedometers for 4 or more days. Therefore, 37.6% wore their pedometers for 3 or fewer days, and only 5.3% (n 5 7) of the children did not wear pedometers at all. On average, children wore pedometers for 4.6 days (SD 5 2.41), and girls wore more days than boys, 5.51 vs. 3.93, t(117) 5 23.86, p , .001. Moreover, children from families with annual family income of $30,000 or higher wore pedometers for more days than children from families with annual family income less than $30,000, 5.17 vs. 3.98, t(113) 5 22.72, p 5 .007. Father’s employment status and education level had significant influence on the number of days children wore pedometers. Specifically, children with a full-time employed father wore more day of pedometers than children with a part-time or unemployed father, 4.94 vs. 3.89, t(65) 5 22.10, p 5 .039, and children whose father received some college education wore more days than children whose father did not receive any college education, 5.39 vs. 4.00, t(102) 5 23.17, p 5 .002.

Reliability Starting with 2 consecutive days (Day 1 and Day 2), reliability of successive combination of days was estimated by adding 1 day at a time (Rowe et al., 2004). The ICCs with 95% CI for daily pedometer steps are presented in Table 2. Two days’ data had an ICC exceeding .70, and 4 days’ data had an ICC exceeding .80. As expected, the reliability coefficients increased with the number of days of data increasing. All the reliability coefficients were strong even with only 2 days’ data.


TABLE 2. Pedometer Reliability Over 7 Consecutive Days (N 5 126) 95% CI Days

ICC

Lower Boundary

Upper Boundary

Day 1–2 Day 1–3 Day 1–4 Day 1–5 Day 1–6 Day 1–7 Weekdays Weekend days

.70 .79 .85 .85 .86 .87 .80 .79

.54 .70 .78 .78 .79 .81 .70 .66

.80 .86 .90 .90 .91 .92 .87 .87

Note. ICC 5 intraclass correlation coefficient; CI 5 confidence interval.

Reactivity Table 3 demonstrates the mean and standard deviation of the pedometer steps over time. The results of the mixed linear regression model indicated that pedometer steps did not change over time from Day 1 to Day 7, t(485) 5 21.33, p 5 .184, or from Monday through Sunday, t(485) 5 0.80, p 5.426. Consistently, no significant differences were found between 2 consecutive days. In addition, children’s perceptions of physical activity self-efficacy, enjoyment, parental influence, and environment did not change significantly after 1-week pedometer wearing (Table 4).

DISCUSSION This study aimed to examine the compliance, reliability, and reactivity of using unsealed pedometers to assess physical activity of elementary school children attending nonphysical Table 3. Mean and Standard Deviation of Pedometer Steps Over Time (N 5 126) Day 1–7 Variable

Day 1

Day 2

Day 3

Day 4

Day 5

Day 6

Day 7

Steps

8,303 (4,227)

8,329 (4,329)

8,229 (4,902)

7,958 (4,620)

7,424 (4,244)

8,051 (4,538)

7,944 (4,919)

Monday–Sunday Steps

Monday

Tuesday

7,859 (4,531)

7,668 (4,786)

Wednesday Thursday 7,924 (3,786)

8,348 (4,495)

Friday 8,380 (4,751)

Saturday Sunday 8,120 (4,969)

8,072 (4,477)

Note. Pedometer wearing day: Day 1–Day 7; day of the week of wearing pedometer: Monday to Sunday.

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activity–focused, afterschool programs. In this study, approximately 87% of the children returned their pedometers and 62% wore pedometers for 4 or more days. Pedometer steps did not change over time, and the day of the week selected to start recoding pedometer steps did not have significant influence on children’s physical activity. Wearing pedometers did not affect children’s perceptions of physical activity self-efficacy, enjoyment, parental influence, and environment. This section first discusses the low physical activity level in this study sample and its possible contributors. Then the compliance, reliability, and reactivity of wearing pedometers are discussed, respectively.

Physical Activity Children in this study took about 7,868 pedometer steps per day, with 8,441 steps for boys and 7,197 steps for girls. On average, U.S. boys take about 13,000 accelerometer steps per day and girls take about 12,000 accelerometer steps per day (Tudor-Locke, Johnson, & Katzmarzyk, 2010), somewhat higher than levels are reported among Canadian children: 12,037 pedometer steps for boys and 10,587 pedometer steps for girls each day (Craig, Cameron, & Tudor-Locke, 2013). In a study of 608 children from two midwestern communities in the United States, children took an average of 11,665 pedometer steps, with 12,709 steps for boys and 10,834 steps for girls (Eisenmann et al., 2007). Thus, children in this study accumulated much lower physical activity levels than children in the United States or Canada or even compared to other midwestern communities. Only 13% of the children in this study met national physical activity recommendations, but nearly half of the children were overweight or obese. Analysis of the national data found that about 70% of children reported meeting recommended levels of physical activity (Fakhouri, Hughes, Brody, Kit, & Ogden, 2013) and 42% of children met physical activity recommendations when using accelerometers to assess physical activity (Troiano et al., 2008). Worldwide, about 24% of boys and 15% of girls meet physical activity recommendations (Guthold, Cowan, Autenrieth, Kann, & Riley, 2010). TABLE 4. Effects of Wearing Pedometers on the Determinants of Physical Activity (n 5 50) Variable Self-efficacy Support seeking Barriers Positive alternatives Enjoyment Parental influence Role modeling Parental support Environment Access Safety

Pretest M 6 SD

Posttest M 6 SD

t Statistic

p Value

13.31 6 3.47 5.82 6 1.48 3.18 6 1.13 4.31 6 1.57 66.43 6 8.78 52.65 6 8.89 16.96 6 3.52 35.69 6 6.55 18.39 6 4.07 11.92 6 2.32 6.47 6 2.69

13.43 6 3.32 5.90 6 1.56 2.98 6 1.23 4.55 6 1.42 67.16 6 9.33 52.55 6 9.96 16.84 6 4.16 35.71 6 7.05 18.39 6 3.99 11.84 6 2.69 6.55 6 2.44

20.33 20.41 1.70 21.27 20.55 0.10 0.28 20.02 0.00 0.20 20.21

.744 .684 .096 .209 .587 .919 .783 .982 1.00 .841 .836


Factors influencing children’s physical activity are difficult to explain; however, seasonal variation may be a confounding factor influencing children’s physical activity in this study. Data were collected from August 2013 to October 2013. The mean temperature was 74.9 °F (range: 52–96 °F) in August, 69.5 °F (range: 48–96 °F) in September, and 54.6 °F (range: 26–82 °F) in October (National Weather Service Weather Forecast Office, 2013). Evidence suggests that children tend to take more steps in spring (May) compared to winter (February; Beighle, Alderman, Morgan, & Le Masurier, 2008). Future studies should consider weather as a potential confounder when assessing children’s physical activity, especially in intervention studies. Another potential factor that may have affected the low percentage of children in this study meeting physical activity recommendations may be the demographic characteristics of this vulnerable population. Children in this study participated in the afterschool programs because of parents’ busy work schedules, children’s learning difficulties and need for afterschool tutoring, or factors related to low socioeconomic status; thus, they might be more likely to have lower levels of physical activity. Afterschool programs aim to provide children academic support rather than opportunities for physical activity (Gardner, Roth, & Brooks-Gunn, 2009). Therefore, most opportunities for physical activity might have occurred during school time for this sample. Children spend only about 20% of afterschool time on physical activity (Beighle, Morgan, Le Masurier, & Pangrazi, 2006); thus, more studies should target afterschool time to improve physical activity of children.

Compliance In this study, 87% of the children returned their pedometers and about 38% wore pedometers for the full 7 days. Compared to a Canadian study in which 58% returned pedometers and data (Craig et al., 2010), the rate of pedometer return in this study was encouraging. In the Canadian study, a foldable flying disc was awarded to children who completed the study. In this study, basketballs and playground balls served as external motivation for children to return pedometers and pedometer logs. Some researchers indicated that providing monetary incentives over the course of study was more effective than gifts or prizes to recruit and retain adolescents in studies (Martinson et al., 2000). For elementary school children aged 8–11 years old, gift certificates, DVDs, tickets to concerts or sporting events, t-shirts, and movie passes have been suggested based on their developmental level (Rice & Broome, 2004). No study was found examining the effectiveness of using incentives of any sort on recruiting and retaining elementary school children. In this study, sports equipment motivated most children to participate, but it might be more effective if various types of sports equipment were available. Another factor that may affect compliance is the availability of adult participation or guidance. Evidence suggests that involving children and school staff directly in the study process could yield higher response rates in school-based surveys than involving parents and school staff or only school staff (Claudio & Stingone, 2008). In this study, the first author (JL) visited the afterschool programs each weekday to help children record pedometer steps, reset pedometers to zero, and remind them to wear pedometers if they had forgotten. As a result, about 93 (69.9%) children wore pedometers on weekdays, but this number dropped to 74 (55.6%) on weekends. Therefore, the investigator’s daily physical presence markedly improves the compliance of wearing pedometers. In the future, afterschool program staff might play the same role of helping children record pedometer steps, reset pedometers to zero, and remind them to wear pedometers.

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In addition, gender, family socioeconomic status, and fathers’ employment status and education level had significant influence on the compliance of wearing pedometers in children. One study also found that girls tended to value the opportunity of wearing pedometers and wore pedometers for longer time spans than boys (Groffik, Fromel, & Pelclova, 2008). Fathers’ employment status and education level can significantly contribute to the whole family’s socioeconomic status (Conger & Donnellan, 2007). Evidence has consistently indicated that children from low socioeconomic families participate in lower physical activity than children from high socioeconomic families (Tandon et al., 2012). In addition, some researchers indicate that parents with high socioeconomic status tend to communicate more clearly their expectations with children, which may influence children’s responsibility and compliance of participating in a research study (Sohr-Preston et al., 2013). Therefore, children’s gender and family’s socioeconomic status should be considered when trying to increase children’s compliance in a research study.

Reliability Wearing pedometers for 4 consecutive days resulted in a reliability coefficient greater than .80, and wearing pedometers for 2 consecutive days yielded a coefficient greater than .70. Other researchers found that the ICC exceeded .80 for 3 consecutive days and exceeded .70 for just 2 consecutive days among children aged 5–19 years old (Craig et al., 2010). One study in U.S. adolescents suggests that 6 consecutive days yield a reliability coefficient greater than .80 (Rowe et al., 2004). Currently, most studies use 7 consecutive days to assess children’s physical activity (Clemes & Biddle, 2013). Considering the compliance, cost, and participant burden of wearing pedometers for 7 consecutive days, the findings of this study suggest that 4 consecutive days of wearing pedometers is adequate to obtain an accurate estimation of children’s physical activity. To include children’s physical activity on the weekend, 3 weekdays and 1 weekend day is recommended to obtain a better estimation of elementary school children’s physical activity as is suggested by other researchers as well (Dollman et al., 2009).

Reactivity Although there is controversy about the reactivity of wearing pedometers, there was no reactivity because of wearing unsealed pedometers among children in this study, aligning with other notable studies suggesting that reactivity does not appear to be present (Ozdoba et al., 2004; Prewitt et al., 2013; Vincent & Pangrazi, 2002). In addition, the day of the week selected to start recording pedometer steps did not have a significant effect on children’s pedometer steps in this study. During data collection, the first author (JL) repeatedly emphasized that each child would receive a playground ball no matter how many steps he or she took. In addition, most children reported wearing unsealed pedometers on other occasions, and pedometers were not considered new, exciting, or innovative. Previous studies found evidence of reactivity for wearing unsealed pedometers, which may have resulted from a high percentage of missing data (Craig et al., 2010), missing data imputation (Rowe et al., 2004), or statistical methods used (e.g., repeated measures analysis of variance [ANOVA] vs. mixed linear regression model). Some researchers suggest that if children are informed that their physical activity data are being collected, thus creating a Hawthorne effect, then reactivity cannot truly be measured (Foley, Beets, & Cardinal, 2011). Recently, health care professionals use pedometers as an intervention tool to increase children’s physical activity rather than as a measurement device for physical activity (Siwik et al., 2013; Wright, Giger, Norris, & Suro, 2013). Therefore, reactivity of wearing pedometers in children may be influenced by the study’s purpose and how the investigator informs children.


Attaching the pedometers to overweight or obese children’s pants was very difficult because most children did not wear a belt. Much of the time, overweight or obese children’s pedometers turned upside down or at an angle instead of remaining vertical because of increased waist circumference. Pedometers are known to often have a higher percentage of error for overweight or obese children compared to healthy weight children (Mitre, Lanningham-Foster, Foster, & Levine, 2009). Using pedometers that can attach to children’s shoes or using pedometer belts may be more practical for overweight or obese children, but supportive evidence of the psychometric properties of attaching pedometers to shoes has not been evaluated. Compared to pedometers, some scientists suggest using accelerometers to accurately estimate overweight or obese children’s physical activity because accelerometers can respond both to vertical and horizontal acceleration of hips, but they are much more expensive than pedometers (Mitre et al., 2009).

CONCLUSIONS AND RECOMMENDATIONS Considering the low levels of physical activity and high prevalence of overweight or obesity, children attending afterschool programs are a vulnerable population in need of more attention to improve their healthy behaviors and promote overall health. Although with unavoidable recording bias because of overrecording, underrecording, wear problems, or even children shaking pedometers to register more step counts, this study’s findings suggest that using pedometers to assess elementary school children’s physical activity is feasible and reliable. External motivation (exercise equipment) and adult presence during data collection, along with verbal reminders to continue participation, can increase the compliance of children wearing and returning pedometers. Future studies are needed to further examine the effects of different incentives and reminders in motivating children to wear and return pedometers, or to participate and remain in a research study. Based on the findings in this study, 4 consecutive days, including 3 weekdays and 1 weekend day, are recommended to assess elementary school children’s physical activity in future studies. Nevertheless, more studies should be conducted to verify this recommendation to obtain the balance of accurately assessing physical activity and adequately reducing unnecessary participant burden. No evidence of reactivity for wearing unsealed pedometers was found. Further studies incorporating longer monitoring periods (2 weeks or longer) should be conducted to investigate the conflicting findings related to reactivity.

IMPLICATIONS FOR NURSING The principle of Exercise is Medicine, proposed by the American College of Sports Medicine and American Medical Association, is designed to improve human’s health and well-being through a regular physical activity treatment by health care professionals including nurses and physicians (Exercise is Medicine, 2008). Pedometers are costefficient devices used to assess physical activity in primary care and community settings (McClain & Tudor-Locke, 2009). Findings in this study provide psychometric evidence for health care professionals (e.g., pediatric nurse, school nurse, public health nurse) to apply the cost-efficient pedometer to measure children’s physical activity in primary care, school, and community settings. Furthermore, this study discusses the strategies to increase the compliance of wearing and returning pedometers in elementary school children, which can be applied to future nursing and public health studies.

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