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Parental influences on 7–9 year olds’ physical activity: A conceptual model
Abstract
Objective
Models characterizing parental influence on child and adolescent physical activity (PA) over time are limited. Preschool and Adolescent Models (PM and AM) of PA are available leaving the need to focus on elementary-aged children. We tested current models (PM and AM) with a sample of 7–9 year-olds, and then developed a model appropriate to this specific target population.
Methods
Parent–child dyads completed questionnaires in 2010–2011. All models were assessed using path analysis and model fit indices.
Results
For adequate power, 90 families were needed, with 174 dyads participating. PM and AM exhibited poor fit when applied to the study population. A gender-specific model was developed and demonstrated acceptable fit. To develop an acceptable model for this population, constructs from both the PM (i.e. parental perception of child competency) and AM (i.e., child-reported self-efficacy) were used. For boys, self-efficacy was a strong predictor of PA, which was influenced by various parental variables. For girls, parental PA demonstrated the greatest strength of association with child PA.
Conclusion
This new model can be used to promote PA and guide future research/interventions. Future studies, particularly longitudinal designs, are needed to confirm the utility of this model as a bridge between currently available models.
Introduction
Parents’ physical activity (PA) related perceptions influence their children’s PA (Corder et al., 2010; Rhee et al., 2005). There is a need to better understand how parental influences relate to each other and to child PA (C-PA), while also considering various child age groups (Katzmarzyk et al., 2008).
Researchers consistently call for theoretically-sound frameworks to guide PA promotion (Katzmarzyk et al., 2008; O’Connor et al., 2009; Salmon et al., 2009) focusing on a population’s most influential characteristics (Brown et al., 2009). Current models describe parental influences on preschooler PA (Loprinzi and Trost, 2010) and adolescent PA (Trost et al., 2003). These models are guided by Eccle’s Expectancy Value Theory (Eccles et al., 1983) which explains that an individual’s behavior is regulated by outcome expectations and the values placed on the outcomes. The expectations and values parents place on C-PA regulate their influences on C-PA. We lack a theoretically-based model explaining parental influences on young, elementary-aged children’s PA.
Our goal was to provide an age-appropriate model depicting parental influences on PA of 7–9 year olds. Our central hypothesis was that existing models’ constructs would appropriately explain parental influences of C-PA. The second hypothesis was that these constructs would indicate different levels of parental influence on C-PA compared to existing models. Our findings along with the PM and AM, would offer insight into the types and levels of parental influence at various ages of children.
Methods
Kindergarten (2007–2008) or second-grade (2009–2010 & 2010–2011) parent–child dyads from a larger school-based screening program were recruited during the 2010–2011 school year. For reliability analyses, a subsample of participants completed a second survey approximately one week after returning the initial survey.
Table 1 details the study constructs and data collection tools. When possible, we used the same data collection tools as the PM and AM studies. Because the child-report measures had not previously been used in our population, we conducted cognitive testing (Leary et al., 2012) to ensure appropriateness for this age-group. Self-reported C-PA was validated with a subsample of participants using Omron-HJ-112 pedometers, which have been used in C-PA research (Nakae et al., 2008). The pedometers were included in the second survey data collection.
Table 1
Constructs used to assess parental influences on child physical activity.
| Variable | Model a | Report method
| YC data collection
| ||
|---|---|---|---|---|---|
| Description of questions used | Reliability | Validity | |||
| Parent PA | AM PM YCM | Parent self-report | International Physical Activity Questionnaire (IPAQ)-Short Form (Craig et al., 2003) and IPAQ guidelines, (Patterson, 2011) | Test-retest (r(46)=0.45, p<0.01) | |
| Parent PA Enjoyment | AM PM YCM | Parent self-report | “How much do you enjoy PA or exercise” using a 5-point scale with 1 indicating “not enjoyable” and 5 indicating “very enjoyable” | Test-retest (r(46)=0.67, p<0.001) | (r(127)=0.78, P<0.001) Correlated with the “PA Enjoyment Scale” (Castro et al., 2007) |
| Parent PA Importance | AM PM YCM | Parent self-report | “How important is it to you that your child is good at sports and hysical activities” using a 5-point scale with 1 indicating “not at all important” and 5 indicating “every important” | Test-retest (r(46)=0.37, p<0.05) | (r(123)=0.39, p<0.001) Correlated with PA Importance Scale (Anderson et al., 2009) |
| Parent PA Support | AM PM YCM | Parent self-report | Six-item scale. How often parents support child PA through praise, transportation, watching, participation, discussing PA importance, and encouraging child to be physically active. A 5-point Likert scale with 1 indicating “never”, 5 indicating “daily”. | Cronbach’s alpha: 0.770 Test-retest (r(49)=0.72, p<0.001) | |
| Child PA Competency | PM YCM | Parent self-report | Adapted from the Child PA Competency Scale (Loprinzi and Trost, 2010). A 5-point Likert scale with 1 indicating “disagreed a lot” and 5 indicating “agreed a lot” | Cronbach’s alpha: 0.99 Test-retest (r(49)=0.83, p<0.001) | |
| Child age | AM PM YCM | Parent report | Variable not used in the current study’s final model | ||
| Child gender | AM PM YCM | Parent report | Variable used as a moderator in the current study’s final model | ||
| Child PA Self-efficacy | AM YCM | Child self-report | Adapted from other child PA self-efficacy scales (Bartholomew et al., 2006; Dzewaltowski et al., 2010; Trost et al., 2003). Children were asked “How sure are you that you can do the following activities?”. Five-point Likert scale choices ranged from “I am sure I cannot” to “I am sure I can”. | Cronbach’s alpha: 0.77 Test-retest (r(49)=0.73, p<0.001) | |
| Child PA | AM YCM PM | Child self-report Parent proxy-report | Log included 38 different activities (with space to enter additional activities). Log was adapted from Trost et al. (2003). Children entered number of days and minutes they took part in each activity. Activities were converted to METs based on the 2011 Compendium of Physical Activities (Ainsworth et al., 2011). A subsample of children wore a pedometer for 2–7 days [days of data required based on research by Schreiber et al. (2006)] to provide validity analysis data. | Test-retest (r(37)=0.46, p<0.01) | Correlation with pedometer data (r(38)=0.39, p<0.05) Correlation between parent and child report of child PA (r(170)=0.95, p<0.001) |
Descriptive statistics and tests of normality were conducted. T-tests assessed differences between respondents and non-respondents. The C-PA variable was transformed into a 1–10 scale to make variances comparable with other study variables. Power analyses indicated that 90 dyads were necessary for model testing. M-Plus was used to test model fit. Other analyses were conducted using SPSS 18.0.
Results
Surveys were returned by 174 parent–child dyads. Response rates varied from 4.1% to 27.9%, based on when families participated in the original school-based screening. Respondents and non-respondents did not significantly differ on most variables available at screening: child gender, child race, and child BMI percentile during screening. Respondents included significantly younger children than non-respondents (8.77 years, SD=0.51, 8.95 years, SD=0.01, p<0.05). Table 2 provides additional participant data.
Table 2
Descriptive statistics for study variables (percentages may not total 100% due to missing data).
| N | Minimum | Maximum | Mean | Std. Deviation | Skewness | Kurtosis | |
|---|---|---|---|---|---|---|---|
| Child gender (female) | 86 (49.4%) | ||||||
| Child age | 174 | 7.00 | 9.88 | 8.75 | 0.5 | −0.59 | 0.40 |
| Child race (white) | 144 (82.8%) | ||||||
| Parent gender (female) | 145 (83.3%) | ||||||
| Parent age | 144 | 21.00 | 62.00 | 36.70 | 6.0 | 0.58 | 1.47 |
| Parent PA | 164 | 0.00 | 2442.86 | 502.04 | 537.7 | 1.78 | 2.84 |
| P-PA Enjoyment | 168 | 1.00 | 5.00 | 3.71 | 1.1 | −0.57 | −0.39 |
| P-PA Importance | 163 | 1.00 | 5.00 | 4.21 | 0.9 | −1.14 | 1.21 |
| C-PA Competency | 171 | 1.00 | 5.00 | 4.23 | 0.7 | −1.42 | 3.27 |
| P-PA Support | 171 | 1.00 | 5.00 | 3.65 | 0.7 | −0.53 | 0.44 |
| C-PA Self-efficacy | 167 | 1.80 | 5.00 | 4.10 | 0.6 | −0.83 | 1.03 |
| Child PA | 172 | 21 | 336 | 130.85 | 63.5 | 0.70 | 0.35 |
| Child PA | 170 | 21 | 336 | 131.32 | 60.6 | 0.59 | 0.33 |
Neither the PM nor the AM adequately fit our dataset (Table 3). Despite poor fit for the currently available models using our dataset, correlations between constructs suggested influences on C-PA (Table 4), but in different ways from current models. Having no strong representation for this age-group in the literature, a new Young Child Model (YCM) was investigated using constructs from the original models.
Table 3
Model characteristics when applied to the study population.
| χ2 | p-value | χ2/df | CFI | RMSEA (90% CI) | |
|---|---|---|---|---|---|
| Adolescent Model using YC dataset | 76.255 | 0.000 | 5.45 | 0.566 | 0.169 (0.133–0.208) |
| Preschool Model using YC dataset | 58.678 | 0.000 | 5.87 | 0.571 | 0.177 (0.135–0.222) |
| Young Child Model-by gender | 11.353 | 0.727 | 0.76 | 1.000 | 0.000 (0.000–0.080) |
| Chi-square contributions by gender | |||||
| Females | 5.784 | ||||
| Males | 5.569 |
Table 4
Correlation matrix for YC-female model variables.
| Child PA | Parent PA | P-PA Enjoyment | P-PA Importance | Competency | P-PA Support | |
|---|---|---|---|---|---|---|
| Females | ||||||
| Parent PA | 0.39a | |||||
| P-PA | 0.05 | 0.08 | ||||
| Enjoyment | ||||||
| P-PA | 0.06 | 0.11 | 0.10 | |||
| Importance | ||||||
| Competency | 0.09 | 0.14 | 0.25b | 0.24b | ||
| P-PA | 0.14 | 0.26b | 0.22 | 0.39a | 0.21 | |
| Support | ||||||
| C-PA | 0.18 | 0.10 | 0.12 | 0.16 | 0.30a | 0.32a |
| Self-efficacy | ||||||
| Males | ||||||
| Parent PA | 0.04 | |||||
| P-PA | 0.05 | 0.24b | ||||
| Enjoyment | ||||||
| P-PA | 0.07 | 0.04 | 0.33a | |||
| Importance | ||||||
| Competency | 0.14 | 0.22 | 0.32a | 0.46a | ||
| P-PA | 0.10 | 0.26b | 0.30a | 0.37a | 0.48a | |
| Support | ||||||
| C-PA | 0.26b | 0.15 | 0.20 | 0.28b | 0.54a | 0.40a |
| Self-efficacy | ||||||
Because of little variance in child age (variance=0.26) and the non-significant correlation between child age and C-PA (p=0.73), child age was removed from the model. Competency (PM) and self-efficacy (AM) were included in the YCM and served as a bridge between the current models. Because gender is consistently reported as a possible moderator in C-PA (Salmon and Timperio, 2007; te Velde et al., 2007), we included child gender as a moderator in the YCM.
Table 3 provides fit indices and Fig. 1 depicts the gender-specific strengths of relationships for the YCM. The YCM explained 6.7% of PA variance among boys. Parent PA, Importance, Enjoyment, and Competency accounted for 29.3% of Support variance. Competency and Support accounted for 31.9% of Self-efficacy variance. The main construct of influence on boy’s PA was Self-efficacy (β=0.26, p<0.001).
The YCM explained 17% of PA variance among girls. Parent PA, Importance, Enjoyment, and Competency accounted for 22.5% of Support variance. Parent PA, Competency and Support accounted for 15.6% of Self-efficacy variance. The main construct of influence on girl’s PA was Parent PA (β=0.15, p<0.001).
Discussion
Parental influence on preschool (Loprinzi and Trost, 2010) and adolescent (Trost et al., 2003) PA have been reported, but no studies, to date, include young, elementary-aged children. Our study found that currently available models were not appropriate for our population; subsequently, a new gender-specific model was developed depicting parental influences on young child PA. These three models illustrate distinct differences in parental influence on C-PA. Parental influences on C-PA were gender-specific in the YCM whereas Support was most influential in the AM (Trost et al., 2003) and Competency in the PM (Loprinzi and Trost, 2010).
The importance of child gender is evident in the YCM where boys and girls differed in their most influential construct. The PM & AM studies included gender in their models but not as a moderator. Reassessing these models with gender as a moderator may provide new insight into influences on preschooler and adolescent PA.
While we provided evidence of validity for self-reported C-PA data using pedometers, objectively-measured PA may provide a more accurate representation of the association between parental influences and C-PA. Given that self-reported methodology is prone to more random measurement error, thus attenuating associations toward the null; our findings may underestimate the effects of parental influences on child activity. Several children could not participate in the pedometer portion of this study because they could not wear the pedometer at school or while participating in organized sports. This may explain the modest correlation between the pedometers and self-report PA. This also underscores the need for data collection tools for children who cannot wear electronic devises.
While the required sample size of 90 dyads was exceeded (n=174), the overall response rate was very low (8.5%). Typically, this population has a response rate of 20–30% when surveys are completed immediately after screening program participation. Our response rate varied from 4.1% for families who participated in the screening 3 years ago to 27.9% for the current screening families. This stresses surveying participants soon after their initial interest in research participation. Nevertheless, there was little difference in available demographic characteristics of respondents and non-respondents, suggesting limited selection bias.
Participants were from predominately rural, Appalachian areas. Almost half (47.7%) of participating adults were college graduates compared with 17.3% in the state (US Census Bureau, 2013) but similar to the PM (60.9%; Loprinzi and Trost, 2010) and AM (53.0%; Trost et al., 2003) families. Most participants were white. These characteristics may limit generalizing results to other populations.
This study also has several strengths. Health professionals need accurate, age-appropriate information to assist parents with children of various ages to have a healthful impact on each child’s PA. The resulting YCM fills a gap in the literature and suggests that parental influences on 7–9 year-old PA differ from that of other populations. The YCM can be used to better understand how parent–child relationships evolve as children progress from preschool to adolescence.
Based on the present study’s findings, interventionists may want to focus on increasing child self-efficacy for overcoming PA barriers, increasing parental support of C-PA, promoting parent PA role modeling, and improving parent PA attitudes. Child self-efficacy appears to be important regardless of parental influences, demonstrated by the strong direct link between Self-efficacy and C-PA in both the YCM-Boys and AM. Competency had a significant direct link with preschooler PA and a significant indirect link in the YCM.
Parental support was an important direct influence in the PM and AM and should be considered. While there was a not direct link between parental support and C-PA in the YCM, one was found between parental support and child self-efficacy. Interventionists can promote higher child self-efficacy by assisting parents in improving PA support offered to their child, which may in turn, increase actual C-PA.
Parent PA had an indirect link through parental support in the PM and AM. In the YCM, the same indirect link was present, but for girls, there was also a direct link between girls’ PA and parent PA. The majority of parent respondents were mothers; girls may have identified with their mother more so than boys. Additional research is necessary to assess parent–child gender relationships and C-PA. Meanwhile, reminding parents that their PA may serve as a model for their children may prompt parents to be more active, thus promoting parent PA and C-PA.
PA’s effect on child health is critical. Behaviors cemented into habit during childhood are likely to continue into adulthood (Telama et al., 2005). Understanding mechanisms that promote PA is important to fostering a health promoting lifestyle. This study supports the importance of parental influences on C-PA while underscoring age-dependent differences to be considered when promoting C-PA.
Footnotes
Conflict of interest
The authors declare that there are no conflicts of interests.
References
- Ainsworth BE, Haskell WL, Herrmann SD, et al. Compendium of physical activities: a second update of codes and MET values. Med Sci Sports Exerc. 2011;43(8):1575–1581. [PubMed] [Google Scholar]
- Anderson CB, Hughes SO, Fuemmeler BF. Parent–child attitude congruence on type and intensity of physical activity: testing multiple mediators of sedentary behavior in older children. Health Psychol. 2009;28(4):428–438. [PMC free article] [PubMed] [Google Scholar]
- Bartholomew JB, Loukas A, Jowers EM, Allua S. Validation of the Physical Activity Self-Efficacy Scale: testing measurement invariance between Hispanic and Caucasian children. J Phys Act Health. 2006;3(1):70–78. [Google Scholar]
- Brown H, Hume C, Chin AM. Validity and reliability of instruments to assess potential mediators of children’s physical activity: a systematic review. J Sci Med Sport. 2009;12:539–548. [PubMed] [Google Scholar]
- Castro CM, Sallis JF, Hickmann SA, Lee RE, Chen AH. A prospective study of psychosocial correlates of physical activity for ethnic minority women. Psychol Health. 2007;14(2):277–293. [Google Scholar]
- Corder K, van Sluijs EM, McMinn AM, Ekelund U, Cassidy A, Griffin SJ. Perception versus reality awareness of physical activity levels of British children. Am J Prev Med. 2010;38:1–8. [PMC free article] [PubMed] [Google Scholar]
- Craig CL, Marshall AL, Sjostrom M, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):1381–1395. [PubMed] [Google Scholar]
- Dzewaltowski DA, Geller KS, Rosenkranz RR, Karteroliotis K. Children’s self-efficacy and proxy efficacy for after-school physical activity. Psychol Sport Exerc. 2010;11:100–106. [Google Scholar]
- Eccles J, Adler T, Futterman R, et al. Expectancies values and academic behaviors. In: Spence JT, editor. Achievement and achievement motivation. W. H. Freeman; San Francisco, CA: 1983. pp. 75–146. [Google Scholar]
- Katzmarzyk PT, Baur LA, Blair SN, Lambert EV, Oppert JM, Riddoch C. Expert panel report from the International Conference on Physical Activity and Obesity in Children, 24–27 June 2007, Toronto, Ontario: summary statement and recommendations. Appl Physiol Nutr Metab. 2008;33:371–388. [PubMed] [Google Scholar]
- Leary JM, Ice C, Cottrell L. Adaptation and cognitive testing of physical activity measures for use with young, school-aged children and their parents. Qual Life Res. 2012;21:1815–1828. [PubMed] [Google Scholar]
- Loprinzi PD, Trost SG. Parental influences on physical activity behavior in preschool children. Prev Med. 2010;50:129–133. [PubMed] [Google Scholar]
- Nakae S, Oshima Y, Ishii K. Accuracy of spring-levered and piezo-electric pedometers in primary school Japanese children. J Physiol Anthropol. 2008;27:233–239. [PubMed] [Google Scholar]
- O’Connor TM, Jago R, Baranowski T. Engaging parents to increase youth physical activity: a systematic review. Am J Prev Med. 2009;37:141–149. [PubMed] [Google Scholar]
- Patterson E. [Accessed 5/1/2011];Guidelines for data processing and analysis of the International Physical Activity Questionnaire (IPAQ)—Short and Long Forms. 2011 https://docs.google.com/viewer?a=v&pid=sites&srcid=ZGVmYXVsdGRvbWFpbnx0aGVpcGFxfGd4OjE0NDgxMDk3NDU1YWRlZTM&pli=1.
- Rhee KE, De Lago CW, Arscott-Mills T, Mehta SD, Davis RK. Factors associated with parental readiness to make changes for overweight children. Pediatrics. 2005;116:e94–e101. [PubMed] [Google Scholar]
- Salmon J, Timperio A. Prevalence, trends and environmental influences on child and youth physical activity. Med Sport Sci. 2007;50:183–199. [PubMed] [Google Scholar]
- Salmon J, Brown H, Hume C. Effects of strategies to promote children’s physical activity on potential mediators. Int J Obes (Lond) 2009;33(Suppl 1):S66–S73. [PubMed] [Google Scholar]
- Schreiber JB, Stage FK, King J, Nora A, Barlow EA. Reporting structural equation modeling and confirmatory factor analysis results. J Educ Res. 2006;99(6):323–337. [Google Scholar]
- te Velde S, De Bourdeaudhuij I, Thorsdottir I, et al. Patterns in sedentary and exercise behaviors and associations with overweight in 9–14-year-old boys and girls—a cross-sectional study. BMC Public Health. 2007;7:16. [PMC free article] [PubMed] [Google Scholar]
- Telama R, Yang X, Viikari J, Valimaki I, Wanne O, Raitakari O. Physical activity from childhood to adulthood: a 21-year tracking study. Am J Prev Med. 2005;28:267–273. [PubMed] [Google Scholar]
- Trost SG, Sallis JF, Pate RR, Freedson PS, Taylor WC, Dowda M. Evaluating a model of parental influence on youth physical activity. Am J Prev Med. 2003;25:277–282. [PubMed] [Google Scholar]
- US Census Bureau. State & County QuickFacts: West Virginia. 2013 http://quickfacts.census.gov/qfd/states/54000.html.