The Effects of Mothers’ Self-Efficacy on Children’s Physical Activity

The Effects of Mothers’ Self-Efficacy on Children’s Physical Activity


1 Health Education Department, Faculty of Medicine, Tarbiat Modares University, Tehran, IR Iran
*Corresponding author: Shamsaddin Niknami, Health Education Department, Faculty of Medicine, Tarbiat Modares University, Tehran, IR Iran. Tel: +98-2182883549, E-mail: [email protected].
Biotechnology and Health Sciences. 2015 February; 2(1): e25731 , DOI: 10.17795/bhs-25731
Article Type: Research Article; Received: Nov 30, 2014; Revised: Dec 14, 2014; Accepted: Dec 24, 2014; epub: Jan 31, 2015; ppub: Feb 2015

Abstract

 

Background: Physical activity has many health benefits, and numerous studies have shown the association between regular physical activity and prevention of about 25 chronic diseases. The guidelines recommend that everyone should try to make physical activity a part of their daily life in order to prevent the unhealthy consequences of sedentary behaviors.

Objectives: The aim of this study was to assess the effect of maternal self-efficacy on children’s physical activity.

Patients and Methods: Inclusion criteria for schoolchildren were: studying at the 5thor 6th grade, relative body mass index of over 85 BMI, and having no restriction or prohibition for regular physical activity. Thus, a total of 300 schoolchildren with their mothers (600 participants) were recruited. To assess children’s physical activity (CPA) and maternal physical activity (MPA) we applied the previous day physical activity recall (PDPAR) tool and the international physical activity questionnaire (IPAQ), respectively. Mother’s self-efficacy (MSE) was measured using an eight-item standard questionnaire. Pearson’s correlation test was applied to assess the relationship between MSE, MPA and CPA. To assess the predictor effect of MSE on CPA, the linear regression model was used.

Results: Means and standard deviations of age of children and their mothers were 11.2 ± 1.1 and 31.2 ± 3.4 years, respectively. Nearly half (46.5%) of the mothers had no formal education and most of them (58.5%) were housewife. There was a significant positive relationship between these three variables (r (CPA × MPA) = 0.748, r (MPA × MSE) = 0.347, r (CPA × MSE) = 0.433, P ≤ 0.05)). The maternal physical activity explained approximately 56% (R2 = 0.559) of physical activity performance in children (CPA).

Conclusions: Maternal physical activity affects children’s physical activity, and is affected by mother’s self-efficacy. Yet based on the findings of this study, regarding the role model effects of mothers in children aged 10-12 years, researchers proposed that interventions related to physical activity in children would work better if they are set to increase self-efficacy in mothers, which in turn lead to increased physical activity in children.

Keywords: Physical Activity; Parent; Children; Self Efficacy

1. Background

 

Physical activity has many health benefits, and numerous studies have shown the association between regular physical activity and prevention of about 25 chronic diseases (16). Thus, national and international health agencies and organizations have introduced some guidelines to increase community and public physical activity. The guidelines recommend that everyone should try to make physical activity a part of their daily life in order to prevent the unhealthy consequences of sedentary behaviors. However, studies have shown that many people do not meet the recommended levels of physical activity. For example, recent studies from the US have shown that over 63% of adolescents do not meet the daily physical activity guidelines of 60 minutes of moderate to vigorous physical activity (MVPA) (710).

 

Figures show that most children in many countries, developed or developing, do not meet the recommended levels of physical activity (1115). Obesity and being overweight in children are two growing public health problems in many countries (1519). Guthold, in a study on physical activity and sedentary behavior in schoolchildren at five World Health Organization (WHO) zones in 34 countries concluded that the majority of students did not meet physical activity recommendations (20).

 

In Iran nearly one out of three Iranian children is either obese or overweight with no significant variation with sex and age (21, 22). There are many factors contributing to childhood obesity and being overweight, yet sedentary behaviors are one of the major factors (6, 15, 23, 24). Sedentary behaviors including watching television and using computers and any activity with no or low amounts of movement that lead to low energy consumption (25, 26).

 

Family attitudes toward physical activity play an important role in increasing physical activity (PA) in children. The effects of family attitudes and preparation for school entrance exams on students’ PA have been studied in some counties (2731).

 

Many studies have been conducted to assess parental determinants of children’s physical activity. Parents are the prominent role models for their children and initiate healthy behaviors. Family support, parental support and instrumental support are some main parental determinants of physical activity in children.

2. Objectives

 

The aim of this study was to assess the effect of maternal self-efficacy on children’s physical activity.

3. Patients and Methods

 

 

3.1. Study Design

This cross-sectional analytical study was done as part of a PhD thesis on health promotion intervention that aimed to increase physical activity of schoolchildren who were overweight or obese. The Human Research Ethics Committee of the Tarbiat Modares University approved the study, and written informed parental consents and children assents were obtained for all subjects, prior to their participation in the study.

 

3.2. Samples

Inclusion criteria for schoolchildren were: studying at the 5thor 6th grade, relative body mass index of over 85, and having no restriction or prohibition for regular physical activity. Thus, a total of 300 schoolchildren with their mothers (600 participants) were recruited for the study from all primary schools of Qazvin province, Iran, using the simple randomized sampling method.

 

3.3. Measurements

 

3.3.1. Demographic andRelative Body Mass Index Measures

Socio-demographic characteristics of the participants, such as age, gender, grade, literacy, employment and ethnicity, were gathered by a questionnaire. Relative body mass index of schoolchildren were collected from school health profiles. Based on this profile, students with relative body mass index (RBMI) over the 85 percentile were selected and then their RBMI were calculated again with standard methods.

 

3.3.2. Physical Activity of Children

Physical activity of children was measured using the previous day physical activity recall (PDPAR) tool. The tool is a standard instrument with 30-minute time blocks. Some general activities are listed on the form, and participants enter the main activity that they had performed during each time period. To help participants select the correct level of intensity, the instrument provides pictorial representations of the four levels of relative intensity. Prior to the application of the PDPAR tool, we educated students on how to mark each block based on their own main activities.

 

3.3.3. Physical Activity of Mothers

Physical activity of mothers was assessed using the Persian version of the international physical activity questionnaire (IPAQ). The daily energy consumption (MET) of the mothers was then calculated, using the IPAQ scoring protocol. Interviews were performed by a skilled and educated research colleague for participants who were illiterate and whose language was not Persian.

 

3.3.4. Mothers’ Self-Efficacy

Self-efficacy of mothers was assessed using the physical activity self-efficacy scale questionnaire. This tool is an eight-item questionnaire, which was developed based on the study of Yan Liang. The second item states, “I can ask my parent or other adults to do physically active with me”, however we changed it to “I can ask my husband or my brother ” This modification has been down based on the socio-cultural status of the participants. Each item used a Likert scale ranging from one (completely disagree) to five (completely agree).

 

3.4. Analysis

All of the collected data were coded and entered in the SPSS software version 17 for analysis. Using descriptive statistical methods, demographic data were analyzed. The significance level was set two-tailed with P ≤ 0.05. Differences between physical activity level of boys and girls were analyzed using the Chi-Square test. Bi-variate correlation test was performed to assess the correlation between CPA and MPA and MSE, consecutively.

 

Using the linear regression test we assessed the following model to determine the relationship between MSE, MPA and CPA. First, MPA regressed to MSE and determined the predictor level of MSE. Next, the total predictor effect of MPA and MSE on CPA was explored with the regression model.

 

Figure 1.

Conceptual model to describe the relation between M.PA, M.SE and C.PA

 

4. Results

 

Demographic characteristics of the children and their mothers are shown in Tables 1 and 2. Means and standard deviations of age in children and their mothers were 11.2 ± 1.1 and 31.2 ± 3.4 years, respectively. Nearly half (46.5%) of the mothers had no formal education and most of them (58.5%) were housewife.

 

Distributions of children’s physical activity based on gender, grade and RBMI variables are shown in Table 3. Based on the findings, obese children were significantly more active than overweight children (mean ± SD; 5.1 ± 0.9 vs. 4.6 ± 1.1) (P ≤ 0.05), and boys had more physical activity than girls (5.5 ± 0.422 vs. 4.2 ± 0.9) (P ≤ 0.05). Finally, there was a significant difference between means of physical activity in the two proposed grades (P ≤ 0.05). Students in grade 6 had less physical activity than those in grade 5 (mean ± SD; 5.0 ± 0.22 vs. 4.3 ± 0.3).

 

The association between CPA, MPA and MSE was assessed using Pearson’s correlation test. Pearson’s correlation test discovered a significant positive relationship between these three variables (r (CPA × MPA) = 0.748, r (MPA × MSE) =0.347, r (CPA × MSE) = 0.433, P ≤ 0.05)). The pictorial exhibitions of these relations are shown in Figures 2, 3 and 4.

 

Children’s physical activity was regressed on MPA in step 1, and MPA and MSE in the next step. Both models were statistically significant (Model 1; F = 38, P = 0.005, R2 = 0.559 and Model 2; F = 21, P = 0.004, R2 = 0.594). In model 1, MPA explained about 56% (R2 = 0.559) of the physical activity performance of children (CPA).

 

Figure 2.

Correlation between Maternal Physical Activity and Children’s Physical Activity

 

Figure 3.

Correlation Between Maternal Physical Activity and Mothers Self-Efficacy

 

Figure 4.

Correlation Between Mothers Self-Efficacy and Children’s Physical Activity

 

Table 1.

Demographic Characteristics of Children and Their Mothers

 

Table 2.

Distribution of Children’s Physical Activity by Relative Body Mass Index, Grade and Gender

 

Table 3.

Summary of Regression Analysis for Variables Predicting C. PA

5. Discussion

 

As parents play an important role to initiate healthy behaviors in children, parental effects on children’s physical activity have been assessed by many studies (14, 18, 30, 32). Generally, parental activity pattern and self-efficacy have been considered as the two main predictors for CPA. For this reason, many health promotion interventions have focused on parental determinants of physical activity to increase children’s physical activity. Most studies have discovered differences between parental (paternal/maternal) determinants.

 

Our study revealed that obese children had more physical activity than overweight children (Table 3). This means that increasing RBMI is accompanied by increasing physical activity. Although, most studies have discovered a negative relationship between RBMI and physical activity (33, 34). still some have reported that obese children have a high tendency to exaggerate and overestimate their physical activity, especially in recall tool application (33, 35).

 

On the other hand, students at the 6th had less physical activity than those at the 5th grade (Table 3). Students at the 6th grade were going to sit hard examinations to enter outstanding schools. Thus, learning had a competitive effect on physical activity. Some studies regarded learning and other cognitive performance achievements as a barrier for physical activity (3638).

 

Our study examined the effects of maternal self efficacy on children physical activity. Based on the findings, there was a positive correlation (r = 0.75) between MPA and CPA (Figure 2). Some other studies have discovered similar associations between parental physical activity and children’s physical activity (3941). However, our study showed that for children between 10-12 years, mothers could be powerful role models to initiate physical activity; the regression model revealed that MPA by itself could predict about 56% of physical activity in children. These findings are consistent with the results of review study about maternal determinants of physical activity in children (14, 42, 43).

 

Mother’s self-efficacy by itself predicted 0.22% of variation in children’s physical activity. In summary, maternal physical activity affects children’s physical activity, and is affected by mother’s self-efficacy. Yet based on the findings of this study, regarding the role model effects of mothers in children aged 10-12 years, researchers proposed that interventions related to physical activity in children would work better if they are set to increase self-efficacy in mothers, which in turn lead to increased physical activity in children.

Acknowledgments

We would like to kindly appreciate all participants at the present study.

Footnotes

Authors’ Contributions: Kazem Hosseinzadeh: study design and measurement of variables. Prof. Shamsaddin Niknami: data entry in SPSS and analysis of data. Prof. Alireza Hidarnia: academic writing, analysis of data, regression model.
Funding/Support: All financial support of this study was provided by the Tarbiat Modares University.

References

 

  • 1. Kaushal N, Rhodes RE. The home physical environment and its relationship with physical activity and sedentary behavior: a systematic review. Prev Med. 2014;67:221-37. [PubMed]
  • 2. Chastin SF, Mandrichenko O, Helbostadt JL, Skelton DA. Associations between objectively-measured sedentary behaviour and physical activity with bone mineral density in adults and older adults, the NHANES study. Bone. 2014;64:254-62. [PubMed]
  • 3. Guallar-Castillon P, Bayan-Bravo A, Leon-Munoz LM, Balboa-Castillo T, Lopez-Garcia E, Gutierrez-Fisac JL, et al. The association of major patterns of physical activity, sedentary behavior and sleep with health-related quality of life: a cohort study. Prev Med. 2014;67:248-54. [PubMed]
  • 4. Mansoubi M, Pearson N, Biddle SJ, Clemes S. The relationship between sedentary behaviour and physical activity in adults: A systematic review. Prev Med. 2014;69C:28-35. [PubMed]
  • 5. Marques EA, Baptista F, Santos DA, Silva AM, Mota J, Sardinha LB. Risk for losing physical independence in older adults: the role of sedentary time, light, and moderate to vigorous physical activity. Maturitas. 2014;79(1):91-5. [PubMed]
  • 6. McClain JJ, Lewin DS, Laposky AD, Kahle L, Berrigan D. Associations between physical activity, sedentary time, sleep duration and daytime sleepiness in US adults. Prev Med. 2014;66:68-73. [PubMed]
  • 7. Castelli DM, Centeio EE, Beighle AE, Carson RL, Nicksic HM. Physical literacy and Comprehensive School Physical Activity Programs. Prev Med. 2014;66:95-100. [PubMed]
  • 8. Babey SH, Wu S, Cohen D. How can schools help youth increase physical activity? An economic analysis comparing school-based programs. Prev Med. 2014;69, Supplement(1):S55-60.
  • 9. De Meester A, Aelterman N, Cardon G, De Bourdeaudhuij I, Haerens L. Extracurricular school-based sports participation and the relationship with physical activity and motivation towards sports. Sci Sport. 2014;29, Supplement:S39.
  • 10. Hills AP, Dengel DR, Lubans DR. Supporting public health priorities: recommendations for physical education and physical activity promotion in schools. Prog Cardiovasc Dis. 2015;57(4):368-74. [PubMed]
  • 11. Rasberry CN, Lee SM, Robin L, Laris BA, Russell LA, Coyle KK, et al. The association between school-based physical activity, including physical education, and academic performance: a systematic review of the literature. Prev Med. 2011;52 Suppl 1:S10-20. [PubMed]
  • 12. Wilson PM, Sabiston CM, Mack DE, Blanchard CM. On the nature and function of scoring protocols used in exercise motivation research: An empirical study of the behavioral regulation in exercise questionnaire. Psychol Sport Exerc. 2012;13(5):614-22. [DOI]
  • 13. Cardon G, De Craemer M, De Bourdeaudhuij I, Verloigne M. More physical activity and less sitting in children: Why and how? Sci Sport. 2014;29, Supplement:3-5.
  • 14. Corder K, Crespo NC, van Sluijs EM, Lopez NV, Elder JP. Parent awareness of young children’s physical activity. Prev Med. 2012;55(3):201-5. [PubMed]
  • 15. Herman KM, Sabiston CM, Mathieu ME, Tremblay A, Paradis G. Sedentary behavior in a cohort of 8- to 10-year-old children at elevated risk of obesity. Prev Med. 2014;60:115-20. [PubMed]
  • 16. Berdah C. Obésité et troubles psychopathologiques. Ann Med-Psychol Rev Psychiatrique. 2010;168(3):184-90. [DOI]
  • 17. Hallal PC, Clark VL, Assuncao MC, Araujo CL, Goncalves H, Menezes AM, et al. Socioeconomic trajectories from birth to adolescence and risk factors for noncommunicable disease: prospective analyses. J Adolesc Health. 2012;51(6 Suppl):S32-7. [PubMed]
  • 18. Jaballas E, Clark-Ott D, Clasen C, Stolfi A, Urban M. Parents’ perceptions of their children’s weight, eating habits, and physical activities at home and at school. J Pediatr Health Care. 2011;25(5):294-301. [PubMed]
  • 19. Maddah M, Solhpour A. Obesity in relation to gender, educational levels and living area in adult population in Rasht, northern Iran. Int J Cardiol. 2010;145(2):310-1. [PubMed]
  • 20. Guthold R, Cowan MJ, Autenrieth CS, Kann L, Riley LM. Physical activity and sedentary behavior among schoolchildren: a 34-country comparison. J Pediatr. 2010;157(1):43-49 e1. [PubMed]
  • 21. Kelishadi R, Haghdoost AA, Sadeghirad B, Khajehkazemi R. Trend in the prevalence of obesity and overweight among Iranian children and adolescents: a systematic review and meta-analysis. Nutrition. 2014;30(4):393-400. [PubMed]
  • 22. Kargarfard M, Kelishadi R, Ziaee V, Ardalan G, Halabchi F, Mazaheri R, et al. The impact of an after-school physical activity program on health-related fitness of mother/daughter pairs: CASPIAN study. Prev Med. 2012;54(3-4):219-23. [PubMed]
  • 23. He M, Piche L, Beynon C, Harris S. Screen-related sedentary behaviors: children’s and parents’ attitudes, motivations, and practices. J Nutr Educ Behav. 2010;42(1):17-25. [PubMed]
  • 24. Davison KK, Li K, Baskin ML, Cox T, Affuso O. Measuring parental support for children’s physical activity in white and African American parents: the Activity Support Scale for Multiple Groups (ACTS-MG). Prev Med. 2011;52(1):39-43. [PubMed]
  • 25. Fitzsimmons PT, Maher JP, Doerksen SE, Elavsky S, Rebar AL, Conroy DE. A Daily Process Analysis of Physical Activity, Sedentary Behavior, and Perceived Cognitive Abilities. Psychol Sport Exerc. 2014;15(5):498-504. [PubMed]
  • 26. Foti KE, Eaton DK, Lowry R, McKnight-Ely LR. Sufficient sleep, physical activity, and sedentary behaviors. Am J Prev Med. 2011;41(6):596-602. [PubMed]
  • 27. Pinar S, Yetgin MK, Bicer B, Ozbar N, Tiryaki C, Agopyan A, et al. The Effect of Family Attitudes and Preparation of High School Entrance Exam on Habitual Physical Activity in Children. Procedia Soc Behav Sci. 2014;116:2852-6. [DOI]
  • 28. Rhee KE, McEachern R, Jelalian E. Parent readiness to change differs for overweight child dietary and physical activity behaviors. J Acad Nutr Diet. 2014;114(10):1601-10. [PubMed]
  • 29. Thorn JE, DeLellis N, Chandler JP, Boyd K. Parent and child self-reports of dietary behaviors, physical activity, and screen time. J Pediatr. 2013;162(3):557-61. [PubMed]
  • 30. Wang ML, Peterson KE, Richmond TK, Spadano-Gasbarro J, Greaney ML, Mezgebu S, et al. Family physical activity and meal practices associated with disordered weight control behaviors in a multiethnic sample of middle-school youth. Acad Pediatr. 2013;13(4):379-85. [PubMed]
  • 31. Wilson DK, Lawman HG, Segal M, Chappell S. Neighborhood and parental supports for physical activity in minority adolescents. Am J Prev Med. 2011;41(4):399-406. [PubMed]
  • 32. Cantell M, Wilson A, Dewey D. The motivational state and perceived benefits and barriers to physical activity participation in parents of preschool age children. Sci Sport. 2014;29, Supplement:S42.
  • 33. Erlacher C, Erlacher D, Schredl M. The effects of exercise on self-rated sleep among adults with chronic sleep complaints. J Sport Heal Sci. 2014.
  • 34. Manley D, Cowan P, Graff C, Perlow M, Rice P, Richey P, et al. Self-efficacy, physical activity, and aerobic fitness in middle school children: examination of a pedometer intervention program. J Pediatr Nurs. 2014;29(3):228-37. [PubMed]
  • 35. Silva-Smith AL, Fleury J, Belyea M. Effects of a physical activity and healthy eating intervention to reduce stroke risk factors in older adults. Prev Med. 2013;57(5):708-11. [PubMed]
  • 36. Eronen J, von Bonsdorff MB, Tormakangas T, Rantakokko M, Portegijs E, Viljanen A, et al. Barriers to outdoor physical activity and unmet physical activity need in older adults. Prev Med. 2014;67:106-11. [PubMed]
  • 37. Gee ME, Bienek A, Campbell NR, Bancej CM, Robitaille C, Kaczorowski J, et al. Prevalence of, and barriers to, preventive lifestyle behaviors in hypertension (from a national survey of Canadians with hypertension). Am J Cardiol. 2012;109(4):570-5. [PubMed]
  • 38. Jerome GJ, McAuley E. Physical activity levels among adult computer users. Comput Hum Behav. 2011;27(3):1207-10. [DOI]
  • 39. Batey CA, Missiuna CA, Timmons BW, Hay JA, Faught BE, Cairney J. Self-efficacy toward physical activity and the physical activity behavior of children with and without Developmental Coordination Disorder. Hum Mov Sci. 2014;36:258-71. [PubMed]
  • 40. Christian H, Giles-Corti B, Knuiman M, Timperio A, Foster S. The influence of the built environment, social environment and health behaviors on body mass index. results from RESIDE. Prev Med. 2011;53(1-2):57-60. [PubMed]
  • 41. Demoulin C, Huijnen IP, Somville PR, Grosdent S, Salamun I, Crielaard JM, et al. Relationship between different measures of pain-related fear and physical capacity of the spine in patients with chronic low back pain. Spine J. 2013;13(9):1039-47. [PubMed]
  • 42. Carver A, Timperio A, Hesketh K, Crawford D. Are children and adolescents less active if parents restrict their physical activity and active transport due to perceived risk? Soc Sci Med. 2010;70(11):1799-805. [PubMed]
  • 43. Drewnowski A, Aggarwal A, Rehm CD, Cohen-Cline H, Hurvitz PM, Moudon AV. Environments perceived as obesogenic have lower residential property values. Am J Prev Med. 2014;47(3):260-74. [PubMed]

Table 1.

Demographic Characteristics of Children and Their Mothers

Variables Value Range, Yr
Children
Age , yr a 11.2 ± 1.1 10.2-12.3
Gender
Boy b 145 (48.5%)
Girl b 155 (51.5%)
School grade b
5th 152 (50.5%)
6th 148 (49.5%)
RBMI
85-95 percentile 135 (45)
≥95 percentile 6 165 (55)
Mothers
Age , yr a 31.2 ± 3.4 27-36
Education b
No formal school 140 (46.5%)
High school or diploma 80 (26.5%)
College degree 80 (26.5%)
Employment b
Full or part time 125 (41.5%)
Housewife 175 (58.5%)
Ethnicity b
Azeri 105 (35%)
Gilaks 75 (25%)
Fars 120 (40%)

a Values are presented as Mean ±SD.
b Values are presented as No.(%)

Table 2.

Distribution of Children’s Physical Activity by Relative Body Mass Index, Grade and Gender

C.PA Mean ± SD t testa
RBMI 0.000
85-95 4.6±1.1
≥95 5.1±0.9
Gender 0.000
Male 5.5±0.422
Female 4.2±0.9
Grade 0.000
5th 5.0±0.22
6th 4.3±0.3

a t test shows significant differences between PA based on RBMI, grade and gender.

Table 3.

Summary of Regression Analysis for Variables Predicting C. PA

Variables B SE B β P value
Step 1
M.PA 0.389 0.043 0.748 0.03
Step 2
M.PA 0.762 0.044 0.679 0.04
M.SE 0.221 0.044 0.198 0.01

Figure 1.

Conceptual model to describe the relation between M.PA, M.SE and C.PA

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