Validity and Reliability of a Parental Self-Efficacy Instrument in the Healthy School Start Prevention Trial of Childhood Obesity

Abstract

Introduction. Measures of parental self-efficacy (PSE) for healthy dietary or physical activity (PA) behaviors in children have been used in several studies; however, further psychometric validation of PSE for these behaviors is needed. The purpose of the present study was to evaluate the psychometric properties of a new PSE instrument. Methods. Mothers (n = 162) of 6-year-old children in the Healthy School Start prevention trial of childhood obesity responded to the instrument and a parent-report questionnaire on diet and PA in children. In addition, PA was objectively assessed by accelerometry. Results. Exploratory factor analysis yielded a structure composed of three factors of PSE for dietary and PA behaviors in children, and PSE was associated with parent-report of these behaviors. Internal consistency was good. Discussion. Preliminary support of the validity and reliability of the PSE instrument was provided. The measure may be useful in prevention and treatment trials of childhood obesity.

Keywords

child health obesity parenting social cognitive theory

Perceived self-efficacy (SE) is the central construct in social cognitive theory and refers to “beliefs in one’s capabilities to organize and execute the courses of action required to produce given attainments” (Bandura, 1997, p. 3). According to the theory, efficacy beliefs are a prerequisite for behavior initiation and endurance and thus constitute the foundation of human motivation and action (Bandura, 1989). A large body of research suggests that SE is a causal determinant of human behavior (Bandura, 1997, 2012).

Several studies have employed measures of parental self-efficacy (PSE) and examined associations between the construct and dietary and/or physical activity (PA) behaviors in children, including Adkins, Sherwood, Story, and Davis (2004); Campbell, Hesketh, Silverii, and Abbott (2010); Smith et al. (2010); Taveras, Mitchell, and Gortmaker (2009); and Weber Cullen et al. (2000). Of these studies, two included assessment of PSE both for dietary and PA behaviors, which are the primary target behaviors in childhood obesity prevention and treatment. However, PSE for PA behaviors was measured by only two (Campbell et al., 2010) or three items (Taveras et al., 2009), and none of the studies used factor analysis to assess construct validity. The study by Adkins et al. (2004) is the only one we know that associated PSE for PA behaviors with objectively assessed PA using accelerometry. Thus, further psychometric validation of PSE for dietary and PA behaviors in children is needed.

The purpose of the present study was to evaluate the psychometric properties of a PSE instrument measuring both dietary and PA behaviors used in a recent prevention trial of childhood obesity. Construct validity was assessed using factor analysis, and the instrument was associated with measures of parent-reported dietary and PA behaviors, as well as objectively assessed PA using accelerometry.

Method

A Healthy School Start

A Healthy School Start was a cluster-randomized controlled prevention trial of childhood obesity conducted in 2011 in Stockholm, Sweden, in an area with families of low to moderate socioeconomic status. The study design and protocol have been detailed elsewhere (Nyberg, Sundblom, Norman, & Elinder, 2011). The trial concerned 6-year-old children in preschool class and their families, continued over a 6-month period, and comprised three components focusing on healthy diet and PA: an informational brochure to parents, two sessions of motivational interviewing to parents, and classroom activities to children.

Participants

Participants were mothers (n = 162) taking part in the intervention or control group of the Healthy School Start trial who responded to a set of questionnaires at baseline, including the PSE instrument. Of the participants, 53.1% had studied at a higher education institution (i.e., university/college), 21% at upper secondary school, 17.9% at primary or secondary school, and 8% had “other” education. Of the participants, 75.9% were born in Sweden or some other Nordic country, 8.1% in some other European country, and 16% in a country outside of Europe.

Assessment

As part of the Healthy School Start trial, an instrument was developed to assess the effects of the intervention on PSE in participating parents. The measure was composed of 17 items covering PSE for dietary and PA behaviors (including sedentary behaviors) and sleep in children. Responses were made on an 11-point Likert-type scale from 0 to 10, with the following anchors: 0 = not at all, 2 = to a very low degree, 4 = to some degree, 6 = to quite a degree, 8 = to a high degree, 10 = to a very high degree. A high total score indicated high PSE. Items were developed by the authors in accordance to guidelines for SE item wording and scale construction (Bandura, 2006) and by reviewing previous PSE measures, particularly the Tool to Measure Parenting Self-Efficacy (Kendall & Bloomfield, 2005), and contacting other research groups. The measure was piloted in 15 mothers, and some minor adjustments to items were made. The instrument is shown in Table 1.

Table 1.

Communalities, Factor Loadings, and Eigenvalues for Exploratory Factor Analysis on the Parental Self-Efficacy Items.

		Factor Loadings
Parental Self-Efficacy Items	Communalities	Factor 1^a	Factor 2^b	Factor 3^c
Questions on how you perceive your ability to manage situations concerning dietary behaviors
1. I can make sure that my child has healthy dietary habits.	.42	.37	.29	.10
2. I can have pleasant meals with my child.	.47	.06	.07	.61
3. I can arrange regular meals at home.	.37	−.03	−.05	.65
4. I can make sure that we have meals together.	.54	−.07	−.03	.79
5. I can offer my child meals which include fruit and vegetables.	.39	.09	.32	.32
6. I can restrict the number of times we eat at a fast-food restaurant to once every two weeks.	.39	.62	−.07	.08
7. I can remain calm even when confronted with difficulties at meals.	.43	.59	.14	−.05
8. I can restrict my child’s intake of candy, ice cream, cookies, chips, and other similar products.	.73	1.00	−.15	−.18
9. I can stick to the rules I have set for my child.	.65	.78	−.06	.10
Questions on how you perceive your ability to manage situations concerning physical activity behaviors
10. I can make sure that my child is physically active enough.	.52	.34	.51	−.05
11. I can have fun with my child outdoors.	.61	−.18	.89	−.05
12. I can make sure that my child is performing outdoor activities (for example, playing, cycling, or doing sports).	.66	−.11	.83	.07
13. I can plan activities which my child appreciates.	.57	−.03	.74	.07
14. I understand what my child needs concerning physical activity.	.51	.25	.62	−.13
15. I can set limits concerning my child’s TV viewing.	.37	.44	.29	−.08
17. I can stick to the rules I have set for my child.	.61	.57	−.04	.34
Eigenvalues		6.48	1.67	1.47

Note. PSE = parental self-efficacy; PA = physical activity. Items 1 and 5 did not load on any factor. Item 16, “I can influence at what time my child is going to bed at night and how much it sleeps,” was excluded from analysis. As rotation is oblique, factor loadings are regression coefficients. Values in boldface represent factor loadings of .40 and above.

Factor 1 = PSE for controlling unhealthy dietary and PA behaviors in children. ^bFactor 2 = PSE for engaging children in healthy PA behaviors. ^cFactor 3 = PSE for arranging a positive meal pattern in children.

Parent-reported frequency data on previous day intake of obesity-related key foods and beverages (i.e., juice, soft/fruit drink, milk, chocolate drink, vegetables, chips/cheese flavored snacks, fruit, candy/chocolate, cookies/buns, ice cream, hamburger/Doner kebab/pizza/taco), average daily intake of vegetables, and child PA (i.e., outdoor PA, screen-based activities, leisure time activities, organized sports) were collected using the Eating and Physical Activity Questionnaire, in which dietary items have been validated against interview-administered 24-hour recall (Bennett, de Silva-Sanigorski, Nichols, Bell, & Swinburn, 2009). Average daily PA in children (i.e., total PA, moderate to vigorous PA, number of steps, sedentary behaviors) was also assessed objectively by accelerometry (GT3X, Actigraph LCC, Pensacola, FL). In addition, measurements of height, weight, and waist circumference in children were collected, as was information on hours of sleep and sociodemographic variables. For more information on assessment, see Nyberg et al. (2011).

Data Analysis

Data were analyzed using the SPSS (Version 21, SPSS Inc., Chicago, IL). To assess construct validity of the PSE instrument, exploratory factor analysis (EFA) was used. Based on the concept of domain-specificity in SE theory (Bandura, 1997), it was expected that some specific items would load on one factor and some other specific items on other factors; thus, EFA was chosen over principal component analysis. Because the aim of the analysis was to identify, not to test, the factor structure of this newly developed and until now untested instrument, EFA was chosen over confirmatory factor analysis. Items with factor loadings of .40 and above were interpreted in the factor solution. Associations between PSE and dietary and PA behaviors in children were calculated using Spearman correlation coefficient r_s. Due to multiple comparisons, significance was corrected to p < .01 using the Bonferroni procedure. Internal consistency reliability was assessed using Cronbach’s α. Item 16 was excluded from analysis because PSE for sleep in children was assessed by this single item, and the item was phrased as a double-barreled question.

Results

Item Descriptives

Analysis of descriptive indicators showed the items to be approximately normally distributed, with skewness (ranging from −0.45 to −2.17) and kurtosis (ranging from −0.26 to 4.39) within acceptable limits, and a maximum endorsement frequency (i.e., highest frequency of any response on the 0-10 scale on any item) of 65.4%. Means ranged from 7.61 to 8.96 (SDs from 1.32 to 1.98) across items.

Validity and Reliability

The Kaiser-Meyer-Olkin measure of sampling adequacy was .87, indicating factorability of the items. Factors were extracted using principal axis factoring, and oblique rotation using Promax was performed on the axis. The factor correlation matrix showed that the correlations between factors were all above r = .32 (ranging from r = .52 to r = .57); thus, oblique rotation was appropriate (Tabachnick & Fidell, 2007). The Kaiser-Guttman criterion (i.e., eigenvalues above 1) suggested the extraction of three factors. The factors were interpreted as PSE for controlling unhealthy dietary and PA behaviors in children (Factor 1: Items 6-9, 15, and 17), PSE for engaging children in healthy PA behaviors (Factor 2: Items 10-14), and PSE for arranging a positive meal pattern in children (Factor 3: Items 2-4). Using a factor loading of .40 as a threshold for consideration, no item loaded on more than one factor, and two items (Items 1 and 5) did not load on any factor. For communalities, factor loadings, and eigenvalues, see Table 1.

The total scale and the factors of a 14-item version of the PSE instrument (Items 1 and 5 were excluded since they did not load on any factor and Item 16 because it was inadequate) were positively associated with several parent-reported healthy behaviors in children and negatively associated with several unhealthy behaviors. Generally, associations between the PSE factors and behaviors were in the expected direction: Unhealthy dietary behaviors were negatively associated with Factor 1, and healthy PA behaviors were positively associated with Factor 2. Factor 3 was associated with few behaviors, which is not surprising given that the factor concerns behaviors not measured (i.e., arranging a positive meal pattern). However, associations between PSE and several other parent-reported behaviors, body mass index, waist circumference, and objectively assessed PA in children did not reach the Bonferroni corrected level of statistical significance (p < .01), although there was a trend for PSE for accelerometry-based total PA during weekdays, r_s = .20, p = .02. For significant associations between PSE and parent-reported dietary and PA behaviors in children, see Table 2.

Table 2.

Associations Between Parental Self-Efficacy and Parent-Reported Dietary and Physical Activity Behaviors in Children.

	Parental Self-Efficacy
	Total Scale	Factor 1^a	Factor 2	Factor 3
Percent fat in milk	ns	ns	ns	.24
Average daily intake of vegetables	.22	ns	.30	ns
Candy/chocolate	−.22	−.29	ns	ns
Ice cream	−.29	−.33	ns	ns
Hamburger/Doner kebab/pizza/taco	−.21	−.23	ns	ns
Afternoon screen-based activities	−.29	−.31	−.23	ns
Level of PA during leisure time	ns	ns	.25	ns
PA outside home last week	.28	ns	.30	.25
Hours of sleep	.29	.25	.21	ns

Note. All correlations are Spearman, and p < .01. ns = nonsignificant; PA = physical activity; PSE = parental self-efficacy.

Internal consistency reliability of the revised 14-item PSE instrument was α = .88, and for factors it was α = .84 for Factor 1, α = .86 for Factor 2, and α = .70 for Factor 3.

Discussion

An EFA of a 14-item version of a PSE instrument used in the Healthy School Start prevention trial of childhood obesity (Nyberg et al., 2011) yielded a structure composed of three factors of PSE for dietary and PA behaviors in children, and internal consistency reliability was good. The factor solution suggested that PSE for preventing unhealthy behaviors (i.e., Factor 1) might be separate from PSE for promoting healthy behaviors (i.e., Factors 2 and 3), a finding that is of relevance to prevention and treatment of childhood obesity and warrants further study. The factors were differentially associated with parent-reported dietary and PA behaviors in children, lending support of construct validity. However, some behaviors were associated with an unexpected factor, and others were associated with more than one factor. These findings may be explained by the interrelatedness of efficacy beliefs in proximate domains (i.e., between-domain generality; Bandura, 1997) and by the clustering of dietary and PA behaviors in children (Gubbels et al., 2012). The magnitudes of the associations were moderate, suggesting that PSE is just one of several variables explaining variance in these behaviors in children.

A limitation of the present study is the moderate communality values in the factor analysis. However, in addition to level of communality, good recovery of population factors is dependent on sample size and level of determination (MacCallum, Widaman, Zhang, & Hong, 1999), and we argue that the interaction of these aspects supports the validity of the obtained factor solution. A second limitation concerns the PSE items, which were not developed using the preferred procedure, that is, to systematically reduce the number of items from a larger pool. A third limitation pertains to the use of a parent-proxy questionnaire of child behaviors. Although not an independent measure, parent-report is required in populations of young children and is a valid and resource-saving method (Bennett et al., 2009).

To our knowledge, the present study is the first to evaluate a PSE instrument covering both dietary and PA behaviors in children using factor analysis and objective accelerometer data. Thus, the study contributes to the validation of PSE for these behaviors. The psychometric assessment provided some preliminary support of the validity and reliability of a 14-item version of the PSE instrument, which may be useful in prevention and treatment trials of childhood obesity. As previous research indicates that SE is a causal determinant of behavior (Bandura, 1997, 2012), practitioners should include the construct in such trials.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

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