Journal of Pediatric Psychology, Vol. 28, No. 5, 2003, pp. 335-345
© 2003 Society of Pediatric Psychology
Social Support, Knowledge, and Self-Efficacy as Correlates of Osteoporosis Preventive Behaviors Among Preadolescent Females
1 Case Western Reserve University School of Medicine, 2 Rainbow Babies & Children's Hospital, 3 University of Pittsburgh
All correspondence should be sent to Carolyn E. Ievers-Landis, Division of Behavioral Pediatrics and Psychology, Rainbow Babies and Children's Hospital, 11100 Euclid Avenue, Cleveland, Ohio 44106–6038. E-mail: cievers{at}aol.com.
 |
Abstract |
|---|
 Top Abstract IntroductionMethodResultsDiscussionReferences |
|---|
Objective To develop and test a model based on Bandura's social cognitive theory to predict healthy lifestyle behaviors for the prevention of osteoporosis. Methods Participants were 354 girls, ages 8–11 years, recruited from area Girl Scout troops. Baseline data from a randomized trial of behavioral interventions are presented. Measures of social support, knowledge, self-efficacy, dietary calcium intake, and weight-bearing physical activity (WBPA) were obtained via interviews and self-administered questionnaires. Results A structural equation model was tested and fit the data well. Family social support, perceived self-efficacy for eating a calcium-rich diet, and knowledge of WBPA significantly predicted calcium intake. Friend and family support for exercise predicted WBPA. Self-efficacy partially mediated the relationship between family support and calcium intake, as confirmed by Holmbeck's post-hoc probing strategy (2002
). Conclusions
Suggestions are made for primary prevention interventions such as parent and
peer involvement, health education, and problem-solving training. Key words: osteoporosis; calcium intake; weight-bearing physical activity; social support; knowledge; self-efficacy.
|
Introduction |
|---|
|
TopAbstractIntroductionMethodResultsDiscussionReferences |
|---|
Primary prevention of problematic health outcomes in children has been touted as a vital goal for researchers in pediatric psychology (Roberts, 1992
;
Roberts & Browne, 2000).
Even so, relatively little published research identifies variables that would
directly inform prevention intervention efforts or evaluates the efficacy of
existing prevention programs (Roberts
& Browne, 2000). To our knowledge, this is one of the first
studies within the pediatric research literature to focus on health promotion
and to employ a prevention paradigm.
Osteoporosis may serve as a model problem for developing and testing a
framework of psychosocial variables associated with preventive healthy
lifestyle behaviors. Osteoporosis is an important public health issue due to
its high prevalence, affecting over 25 million people in the United States,
and its associated marked morbidity and mortality. More than 1.5 million
fractures occur annually and are often responsible for increased disability,
decreased quality of life, and premature death, costing the country's health
system an estimated 10 billion dollars
(French, Fulkerson, & Story,
2000). Though commonly associated with postmenopausal women and
the elderly, osteoporosis has been linked to bone development during childhood
and adolescence (Cummings, Kelsey, Nevitt,
& O'Dowd, 1985). The level of bone mass achieved at skeletal
maturity influences the risk of development of osteoporosis
(Heaney, 1986); thus, a window
of opportunity exists to add to bone density during late childhood and early
adolescence, as 40% of the skeletal structure is built and enlarged during
this developmental stage (National
Institute of Child Health and Development, 1999).
The level of an adolescent's calcium (Ca) intake and physical activity are
believed to interact as modifiable risk factors in the determination of bone
mass (French et al., 2000).
The recommended daily allowance (RDA) for children ages 6 to 19 years is 1,300
mg (National Institute of Child Health and
Development, 1999). Unfortunately, 85% of girls between the ages
of 12 and 19 do not meet the RDA of Ca necessary for developing the structure
of strong bones, with a range of approximately 700 to 950 mg per day. Even
more alarmingly, studies have found that more than half of young adolescent
girls consume less than 500 mg of Ca per day
(Eck & Hackett-Renner,
1992; Fleming & Heimbach,
1994; Miller, Kimes, Hui,
Andon, & Johnston, 1991;
Weaver, 1994). This deficiency
in daily dietary intake has been identified as an important public health
concern.
Moreover, girls in this age range participate less frequently in
weight-bearing physical activity (WBPA) than do their male counterparts,
putting them at greater risk for the later development of osteoporosis
(Centers for Disease Control and
Prevention, 1998; McKenzie et
al., 1995). The recommended amount of WBPA for the prevention of
osteoporosis has not yet been specified. However, as a general guideline, the
recommended amount of physical activity for adults is 20 to 30 minutes per day
based on the Surgeon General's Report on Physical Activity and Health
(U.S. Department of Health and Human
Services, 1996). Though the level of WBPA in children is not known
specifically, recent studies have found that only 24% of girls ages
12–21 years reported engaging in regular physical activity
(U.S. Department of Health and Human
Services, 1996). A low level of moderate to vigorous physical
activity also has been reported for third and fourth grade girls (9- and
10-year-olds) (Sallis,
1993).
Despite growing knowledge of the importance of diet and exercise in the
prevention of osteoporosis, very few studies have described the
characteristics of children who engage in the behaviors necessary to prevent
this condition, particularly for Ca intake. As an example, ninth graders who
were aware of the protective benefits of a diet high in Ca had a significantly
higher intake than those who were unaware of this information
(Harel, Riggs, Vaz, White, & Menzies,
1998). Additional research with children has found social support
to be an important family determinant of physical activity
(Melnick, Dunkelman, & Mashiach,
1981), parents who are more physically active have more physically
active children (Moore et al.,
1991). Michela and Contento
(1986) found the primary
determinant of whether children ate a food was whether the parent served it,
providing evidence for the importance of family support for eating behavior.
Self-efficacy is related to physical activity
(Reynolds et al., 1990), but
the relationship between self-efficacy and WBPA has not been studied.
Self-efficacy for diet was significantly associated with children's usual food
choices in a large sample of third- and fourth-grade students
(Parcel et al., 1995).
This investigation examined a model to predict healthy lifestyle behaviors
for the prevention of later development of osteoporosis among preadolescent
girls. The relationships between social influences, self-efficacy, knowledge,
and healthy lifestyle behaviors were examined with analyses based on Bandura's
social cognitive theory's predictions
(1991) and findings with
children and adults (Duncan & McAuley,
1993; Shannon, Bagby, Wang,
& Trenkner, 1990; Slater,
1989). According to Bandura
(1982), self-efficacy is the
perceived capability to exercise control over one's behavior; this concept has
been hypothesized to relate both directly and indirectly to engagement in the
target behavior. Additionally, social influences purportedly predict
perceptions of self-efficacy as well as behavior.
In adult populations, converging evidence suggests that self-efficacy may
function as a mediator between social influences and healthy eating habits,
for example, to "choose appropriately" and "avoid
overeating" (Duncan & McAuley,
1993; Shannon et al.,
1990; Slater,
1989). Self-efficacy mediates between friend (but not family)
support and eating behavior (Shannon et
al., 1990). Additionally, knowledge mediates between social
influences and self-efficacy in the prediction of health-related behaviors
such as eating habits (Slater,
1989). As both perceived self-efficacy and knowledge function as
mediators in studies of the healthy lifestyle behaviors of adults, one of our
goals was to determine if these relationships also pertain among children.
Similar relationships were predicted, although family social influences were
expected to be greater for children than for adults, based on children's
dependence on parents for access to food and support of exercise-related
activities (see Baranowski,
1997). Successful preventive interventions for conditions such as
osteoporosis depend on identification of critical processes that affect key
health outcomes. We intended this study to inform the design of targeted
intervention strategies. We tested the following hypotheses using correlations
before developing our initial model. First, we hypothesized that social
support from friends and family was associated with preventive behaviors and
self-efficacy beliefs (Melnick et al.,
1981). Self-efficacy was expected to mediate between social
support and preventive behaviors (Duncan
& McAuley, 1993; Shannon
et al., 1990; Slater,
1989). Second, we expected greater social support from friends and
family to relate to higher perceived self-efficacy and greater knowledge of
dietary Ca and WBPA. We expected knowledge to mediate between social support
and self-efficacy beliefs (Slater,
1989). Significant hypotheses will be further tested in a
structural equation model.
|
Method |
|---|
|
TopAbstractIntroductionMethodResultsDiscussionReferences |
|---|
Participants
Participants were 354 preadolescent girls. They were enrolled in the initial phase of a randomized, controlled intervention trial designed to prevent the later development of osteoporosis. The investigators' institutional review board approved the intervention study. Preadolescent girls between the ages of 8 and 11 years who had not yet undergone menarche were recruited for participation from the Girl Scouts of Lake Erie Council. The mean age of the girls was 9.37 (11 8-year-olds, 209 9-year-olds, 113 10-year-olds, 14 11-year-olds). The racial background of the sample was 84.2% Caucasian (n = 298); 10.2% African American (n = 36); 0.3% Hispanic (n = 1); 1.4% Caucasian/African American (n = 5); 0.8% Caucasian/Asian (n = 3); 1.4% other multiracial (n = 5); 0.6% Caucasian/other (n = 2); 0.6% Caucasian/African American/other (n = 2); 0.3% Caucasian/Hispanic (n = 1); and 0.3% Caucasian/Hispanic/other (n = 1).
To avoid potential confounding factors that might affect the outcomes for the interventions, we excluded girls who had medical conditions or were taking medications that could be associated with low bone mass from participation in the data collection portion of the study. The exclusionary criteria based on the past or present condition of the girls were as follows: (1) a history of cancer, (2) the presence of severe asthma requiring steroid treatment, (3) another medical condition that may have influenced bone development (e.g., Type 1 diabetes, juvenile rheumatoid arthritis), and (4) a known disorder of dietary behavior (e.g., anorexia, bulimia). Exclusionary status was based on the girl's reports on a health history questionnaire. If siblings were in the same Girl Scout troop, only the older girls' data were included in the analyses. For twins, one girl was randomly selected. To mitigate any potential discomfort girls might experience due to being excluded, we allowed girls who did not meet the enrollment criteria to participate in the intervention programs and complete the assessments with their peers, although their information was not included in the analyses. Of the original sample of 436 girls, 42 were not eligible for participation based on the criteria for exclusion. An additional 40 girls were dropped from the data analyses due to missing data, as missing data were handled using listwise deletion to run the structural equation model. The excluded girls did not significantly differ from the study sample in race or age.
Procedure
Recruitment. Information about the project was distributed to
leaders of troops in the Girl Scouts of Lake Erie Council area through their
service unit directors and the council newspaper. Eligibility criteria
included at least six girls between the ages of 8 and 11 enrolled in the
troop. Service unit directors received information packets about the project
to distribute to their area troop leaders. Thirty-eight interested troops
contacted the council or the project coordinators, and 33 eligible troops were
randomly assigned to one of three groups. This article reflects the baseline
data from all three groups.
Parents were invited to a meeting to learn about the project. Upon visiting each troop, parents received packets containing a letter from the principal investigator, an information sheet describing the project, a letter of support from the chief executive officer of Girl Scouts of Lake Erie Council, a timeline of the project, and a consent form. The research assistant described the project briefly, and all questions were answered. The parents and girls were then invited to complete the assessment at the next Girl Scout meeting.
Data Collection. After we obtained informed assent from the girls and written consent from their parents or legal guardians, research assistants and dietitians from the County Board of Health administered a baseline assessment battery. This study examines a subset of the variables measured at baseline.
Measures of Dependent Variables
Dietary Assessment of Ca. The average daily dietary intake of Ca
(mg) was assessed with an interviewer-administered food frequency
questionnaire (FFQ) previously developed by Musgrave, Giambalvo, Leclerc,
Cook, and Rosen (1989). This
questionnaire covers 23 foods from the Healthy Diet Pyramid that are rich in
Ca or vitamin D. The Ca level from the FFQ correlated between r = .73
and r = .84 with 4-day food intake records in a sample of adult women
(Musgrave et al., 1989). Ca
scores were not skewed, so this variable was not transformed.
WBPA Assessment. The hours of physical activity engaged in per
week were assessed using an interviewer-administered questionnaire for
children (Fontvieille, Kriska, &
Ravussin, 1993; Kriska et.
al., 1990). The interview format of the questionnaire allowed the
girls to report an unspecified number of WBPAs and non-WBPAs performed on a
regular basis and adjusts for seasonal activities. For the purposes of this
investigation, only total hours per week of WBPA were included in the
analysis. The original data were highly skewed and kurtotic; collapsing the
data into the following clinically relevant continuous categories remedied
this problem: no WBPA, a half hour or less, a half hour to 1 hour, 1 hour to 2
hours, 2 hours to 4 hours, and more than 4 hours of WBPA per week.
Measures of Independent Variables
Knowledge of Osteoporosis Prevention. We used two subscales from a
27-item questionnaire designed for this study to determine knowledge of risk
preventive factors for osteoporosis and to assess knowledge of calcium-rich
foods and WBPA. This self-administered questionnaire was based on previous
versions with children (e.g., Parcel,
Simons-Morton, O'Hara, Baranowski, & Wilson, 1989;
Green, McIntosh, & Wilson,
1991). The knowledge of Ca subscale consists of 10 items on
high-Ca food choices (From each of the following pairs of foods, circle the
food that helps build strong bones: e.g., turkey sandwich or cheese sandwich,
carrots or broccoli, pretzels or yogurt). The knowledge of WBPA also consists
of 10 items (Do these activities help build strong bones? e.g., swimming,
soccer, watching television). The Cronbach's alphas for the knowledge
subscales were r = .54 for calcium-rich foods and r = .53
for WBPA.
Self-Efficacy for Diet. A modified version of an existing
self-efficacy diet questionnaire for children
(Parcel et al., 1995;
Sallis, Pinski, & Grossman
1988) was developed to measure children's perceived capability to
make dietary changes related to Ca intake (e.g., How sure are you that you
can: ask your parents to buy calcium-fortified orange juice? drink milk
instead of soda pop? add cheese to a sandwich to get more Ca in your diet?).
Our goal was to measure children's perceptions of their ability to choose
foods high in Ca or to get their parents to choose or purchase foods high in
calcium. Self-efficacy items were written to represent common food choices and
behaviors that could potentially increase Ca intake in this age group, and the
phrasing of the items corresponds to other measures of self-efficacy. The
interviewer-administered questionnaire consists of nine items scored on a
5-point Likert-type scale (0 = not at all true to 4 = very true). Cronbach's
alpha was moderate at r = .66. A scree plot indicated a single
factor, and an item analysis yielded factor loadings from .11 to .74. Dropping
the two items with loadings less than .3 only increased reliability to .68, so
we chose to retain all of the items.
Self-Efficacy for WBPA. The Children's Self-Efficacy Survey
(Garcia et al., 1995) was used
to measure children's perceived capability to engage in exercise. Items were
reworded to assess self-efficacy specifically for WBPA. This self-administered
survey consists of seven items (e.g., How sure are you that you can: e.g., do
a weight-bearing exercise? do some weight-bearing activity at least three
times a week? put forth the effort required to do a weight-bearing exercise?)
rated on a 5-point Likert-type scale (0 = not at all true to 4 = very true).
Cronbach's alpha for general physical activity is reported to be r =
.77 (Garcia et al., 1995).
Cronbach's alpha in this investigation for WBPA was quite high at r =
.90.
Family Support for Exercise. A subscale from the Children's
Physical Activity Questionnaire (CPAQ; Sallis et al.,
1985,
1986,
1989) was employed to assess
family support for exercise. This self-administered subscale consists of four
items (e.g., Do your Mom and Dad encourage you to exercise? Do your Mom and
Dad ever offer to exercise with you? Do your Mom and Dad take you to sporting
events so that you can participate?) rated on a 6-point Likert-type scale (0 =
never to 5 = more than two times per week). Cronbach's alpha was moderate at
r = .65. Friend Support for Exercise. A subscale from the
CPAQ (Sallis et al., 1985,
1986,
1989) was employed to assess
friend support for exercise. This self-administered subscale consists of four
items (e.g., Do your friends ever exercise with you? Do your friends go with
you to sporting events? Do your friends encourage you to exercise?) rated on a
6-point Likert-type scale (0 = never to 5 = more than two times per week).
Cronbach's alpha was moderate at r = .73.
|
Results |
|---|
|
TopAbstractIntroductionMethodResultsDiscussionReferences |
|---|
Table I presents the means, standard deviations, percentiles, and ranges for all the variables in the present investigation. The average Ca score was 1,372.40 mg (SD = 667.49) with 49.6% of the sample meeting the recommended daily allowance of 1,300 mg. For WBPA, girls averaged a total of approximately 2.5 hours per week with much variability in reported activity (SD = 1.99). On average, the girls reported engaging in 24 minutes of activity per day. A correlation matrix was generated that included each of the variables in the study (see Table II). The bivariate relationships between the majority of independent and dependent variables were weak, while the relationship between Ca intake and self-efficacy for Ca intake was the strongest (r = .269, p < .01). Significant bivariate relationships were evident between Ca intake and family social support, knowledge of WBPA, and friend social support at the .05 level.
|
|
With consideration of Bandura's theory, previous empirical findings with
children and adults, and significant correlations from this investigation, we
constructed an initial model (see Figure
1). A structural equation model was developed and tested using
AMOS (Arbuckle, 1999). The
model reflects relationships between variables obtained at a common time
period, baseline data for an intervention project designed for the primary
prevention of the later development of osteoporosis among preadolescent girls.
Examination of our initial model indicated that adjustments could be made to
improve the match between the data and the model (
2 = 9.246,
df = 14, p = .815, CFI = 1.00, TLI = 1.052, RMSEA = .00). To
identify the sources of error in the original model, we eliminated paths that
were not significant one at a time to find the most parsimonious model. First,
we eliminated the path between friends' social support for exercise and
knowledge of WBPA (a hypothesized mediating variable between social support
and self-efficacy). Second, we dropped the path between friends' social
support for exercise and self-efficacy for Ca intake (a hypothesized mediating
variable between social support and behavior). Finally, we omitted the path
between knowledge of WBPA and Ca intake.
Table III contains the models'
goodness of fit indices.
|
|
Our final model fit the data well (2 = 15.467, df
= 18, p = .63; CFI = 1.00, TLI = 1.022, RMSEA = .00). Bentler and
Chou (1987) recommend CFI and
TLI scores of greater than .90 as indicators of good fitting models. Browne
and Cudeck (1993) state that an
RMSEA of .00 is indicative of a model with an exact fit and recommend that
models with an RMSEA of .08 or less and preferably .05 or less are good
fitting models. Figure 2 shows
the entire final model with the accompanying path coefficients. Overall, the
structural model contains relatively weak influences on the consumption of
dietary Ca, with path coefficients ranging from .11 to .25.
|
Hypothesis 1: The Influence of Social Support on Behavior With
Self-Efficacy as a Proposed Partial Mediator
We hypothesized that social support for a healthy lifestyle from friends
and family would be positively associated with engaging in regular WBPA and
eating a high Ca diet (i.e., engaging in healthy lifestyle behaviors). Social
support was expected to relate to self-efficacy beliefs that were then
hypothesized to relate to engagement in the target behaviors. Once
self-efficacy was added to the structural equation model, the direct
relationships between social support and the target behaviors should weaken.
Self-efficacy, therefore, was expected to function as a partial mediator
between social support and engagement in preventive behaviors.
As predicted for direct paths, family social support for engaging in healthy behaviors (i.e., exercising regularly) had a direct effect on WBPA (standardized ß weight = .13, p = .031) and on Ca intake (standardized ß weight = .13, p = .013). Additionally, friend social support was significantly associated with WBPA (standardized ß weight = .18, p = .002). No significant relationship was observed between friend support and Ca intake.
For indirect paths, social support from family significantly predicted self-efficacy for Ca intake as expected (standardized ß weight = .11, p = .026), and Ca self-efficacy significantly predicted dietary intake of Ca (standardized ß weight = .25, p < .001) but not frequency of exercise. Friend social support was not significantly related to self-efficacy; moreover, a significant relationship was not found between self-efficacy for exercise and engaging in either of the targeted healthy behaviors.
Post-hoc probing of significant mediation effects was performed as
recommended by Holmbeck (2002)
to determine if the drop in the total effect (i.e., family support for
exercise to Ca intake) is significant upon inclusion of the mediator
(self-efficacy for Ca intake) in the model. This strategy indicated that
self-efficacy did function as a mediator (z = 2.020, p <
.05). (Note that p < .05 if the absolute value of z >
1.96 [Holmbeck, 2002].) Thus,
self-efficacy for Ca intake does function as a partial mediator of the
relationship between family support for exercise and Ca intake.
Hypothesis 2: The Influence of Social Support on Self-Efficacy With
Knowledge as a Proposed Partial Mediator
Preadolescents with greater social support from friends and family were
predicted to have higher perceived self-efficacy for exercise and Ca intake.
Social support was believed to relate to greater knowledge of how to reduce
the risk for the later development of osteoporosis; knowledge was then
expected to relate to self-efficacy beliefs. Once knowledge was added to the
model, the direct relationship between social support and self-efficacy was
predicted to diminish. Therefore, knowledge was expected to function as a
partial mediator between social support and self-efficacy for engaging in
healthy behaviors.
For direct paths (as mentioned in the section on indirect paths), social support from family significantly predicted self-efficacy for Ca intake, as expected. Contrary to our hypotheses, family support was not related to self-efficacy for WBPA, and friend social support was not significantly related to perceptions of self-efficacy.
For indirect paths, family social support significantly predicted knowledge of WBPA, as expected (standardized ß weight = .16, p = .002), and this type of knowledge significantly predicted self-efficacy for Ca intake (standardized ß weight = .13, p = .014) but not for exercise. Family social support significantly predicted knowledge of calcium-rich foods (standardized ß weight = .12, p < .018), but no significant relationships were found between knowledge of calcium-rich foods and perceptions of self-efficacy for engaging in either of the targeted healthy behaviors. Additionally, friend support for exercise was not significantly related to knowledge of calcium-rich foods or WBPA.
Once again, post-hoc probing of significant mediation effects was performed
as a follow-up to the findings from the structural equation model
(Holmbeck, 2002). This
post-hoc strategy was conducted to determine if the drop in the total effect
(i.e., family support for exercise to self-efficacy for Ca intake) is
significant upon inclusion of the mediator (knowledge of WBPA) in the model.
This strategy indicated that knowledge of WBPA did not function as a mediator
(z = 1.921, p > .05). Thus, knowledge of WBPA does not
partially mediate the relationship between family support for exercise and
self-efficacy for Ca intake.
|
Discussion |
|---|
|
TopAbstractIntroductionMethodResultsDiscussionReferences |
|---|
This investigation is one of the first within pediatric research literature to concentrate on health promotion with a prevention paradigm based on osteoporosis as a model condition. Our findings from a structural equation model were in accord with Bandura's (1986
) predictions of the
relationships of social support and self-efficacy to health-related behaviors
such as eating habits and in general agreement with correlates of eating
behavior in adult populations (Duncan
& McAuley, 1993; Shannon
et al., 1990; Slater,
1989). Preadolescent girls who reported higher perceived
self-efficacy (this translates into having an easier time choosing high Ca
foods) reported healthier eating habits (i.e., eating a higher Ca diet).
In contrast to the previous studies with adults (e.g.,
Shannon et al., 1990), social
support was directly related to eating habits in our investigation.
Specifically, support from family but not from friends was associated with
eating behavior, demonstrating the continuing influence of parents on the
health-related behaviors of preadolescents. This finding has developmental
relevance for understanding family influences on critical health behaviors
such as diet and exercise and hence should inform subsequent studies of
predictors of health behaviors.
Also, as predicted based on models tested on adult populations
(Slater, 1989), greater
knowledge predicted greater self-efficacy. And, finally, social support from
family predicted perceived self-efficacy. Once again, this finding differs
from the research with adult populations, as social support from friends but
not family was related to perceived self-efficacy regarding maintaining a
healthy lifestyle. The developmental context of our findings should be
recognized; that is, the influence of parents on our sample of preadolescent
girls should arguably be greater than for older adolescents for whom peer
influence should be greater (La Greca,
1992).
Our hypothesis of the mediational effect of self-efficacy on the
relationship between social support and protective healthy lifestyle behaviors
was supported through post-hoc probing, as recommended by Holmbeck
(2002). Thus, social support
from parents for living a healthy lifestyle is related to children's beliefs
that they can more easily engage in healthy behaviors; subsequently, children
are more likely to adopt healthy habits. The mediating role of self-efficacy
has previously been illustrated in studies of adult lifestyle behaviors
(Duncan & McAuley, 1993;
Shannon et al., 1990;
Slater, 1989). This study
provided additional validity for self-efficacy as a mediator with a different
population (children rather than adults) and a specific aspect of eating
behavior (Ca intake). The mediational effect of knowledge of WBPA on the
relationship between family social support and self-efficacy for Ca intake was
not supported by the same post-hoc strategy. This illustrates the vital
importance of post-hoc testing of mediational effects in pediatric psychology
research to decrease the acceptance of false-positive conclusions.
Limitations
A number of potential limitations of this investigation should be
considered. First, higher Ca scores on average were obtained for our sample
than for other samples of young girls reported in the literature. For example,
in a recent study by Weaver, Peacock, and Johnson
(1999), an average of 897 mg
was found for girls 9 to 13; the older age range in their study may in part
explain this discrepancy. Also, membership in a group such as Girl Scouts may
be related to having a healthier lifestyle. An additional possibility is that
children may overreport Ca intake on food frequency questionnaires, as found
when this technique was used for fruits and vegetables
(Domel et al., 1994). Though
the impact of our sample's generally higher Ca intake on our findings is
unknown, approximately half of our sample was still below the RDA. Second, our
sample consisted of primarily Caucasian girls, which limits the
generalizability of our findings. However, our decision to study this
population makes sense, as bone mass is lower in Caucasian than in African
American children (Bell, Shary, Garza,
Gordon, & Edwards, 1991). Third, the use of single-respondent
data for these analyses should be taken into consideration. Data collected
from others such as parents and teachers would have increased the validity of
our findings. Fourth, the structural equation model, while fitting the data
well, identified only relatively weak influences on the consumption of dietary
Ca, with path coefficients ranging from .11 to .25. However, these paths were
hypothesized based on available research concerning predictors of eating
behavior in adults (Duncan & McAuley,
1993; Shannon et al.,
1990; Slater,
1989), and the fact that many of these relationships were
confirmed in another population with different outcomes suggests that our
model may be promising. A potential contributor to these weaker relationships
was the relatively low reliabilities of some of our measures, such as the
subscales of Ca and WBPA knowledge. Expanding the knowledge measure to include
other facets such as the benefits of dietary Ca or WBPA and the risk factors
associated with the increased likelihood of developing osteoporosis may
provide greater power to detect existing relationships. Fifth, our model
identified fewer significant influences on the frequency of WBPA. Further
research is warranted in this area employing different measures of level of
WBPA and psychosocial variables (e.g., access to exercise equipment, perceived
barriers to exercising). Sixth, our model identified significant direct and
indirect paths between exercise-related variables and diet-related variables.
We propose that the nonspecific effects of influences on the adoption of a
healthy lifestyle explain these relationships. Finally, the structural
equation model was based on cross-sectional data, necessitating caution in the
interpretation of causal influences. For instance, engagement in the target
behaviors may influence the psychosocial variables; for example, consumption
of dietary Ca may influence feelings of self-efficacy, rather than vice
versa.
Future Research Directions
Our findings address the important need for studies that generate
empirically sound and theoretically relevant data to identify variables likely
to be effective targets of intervention. Further research to describe
preadolescent girls who engage in the requisite behaviors to reduce the future
risk of osteoporosis should be expanded to include other psychosocial
variables related to exercise and diet habits. Among these are perceived
barriers and benefits to engaging in the target behaviors and access to the
appropriate equipment both for WBPA and Ca intake. With regard to the latter,
a modified observation procedure used with studies of obese and nonobese
families could be employed to measure storage of calcium-rich foods such as
foods openly visible in the house, as well as foods in the freezer and the
refrigerator (Terry & Beck,
1985).
Future research efforts should also include data from parents to determine the degree of influence on their girls' preventive healthy lifestyle behaviors. Parent variables to consider include parental consumption of dietary Ca and frequency of WBPA (to measure their status as healthy role models), as well as parental knowledge of preventive behaviors, perceived self-efficacy regarding their ability to engage in such behaviors, and social support for physical activity.
And, finally, results from this investigation may provide guidance for the
design of future interventions. Our findings suggest that intervention
programs to increase healthy lifestyle behaviors among preadolescent girls
should include the following components: (1) involvement of family members,
particularly parents, for increased social support for engaging in these
behaviors; (2) peer programs to enhance support from friends for being
physically active; (3) health education to improve knowledge of WBPA for the
primary prevention of osteoporosis; and (4) strategies for improving the ease
at which preadolescent girls feel they can engage in healthy behaviors, such
as problem-solving training to facilitate overcoming barriers to eating a
calcium-rich diet (e.g., not wanting to eat cheese or milk because of
avoidance of dietary fat). These strategies are being tested as part of an
ongoing intervention program based on the theoretical principles of enhancing
family social support, knowledge, and self-efficacy
(Ievers-Landis et al.,
2002).
|
Acknowledgments |
|---|
The study was supported by grant AR-20618 from the Northeast Ohio Multipurpose Arthritis Center and in part by the Elizabeth Severance Prentice Foundation awarded to Dr. C. Kent Kwoh. We also acknowledge support by grant NIH M01-RR0080 awarded to the General Clinical Research Center. We thank Grayson N. Holmbeck for his comments on an earlier draft of this manuscript.
Received April 15, 2002; revision received July 19, 2002; accepted August 28, 2002
|
References |
|---|
|
TopAbstractIntroductionMethodResultsDiscussionReferences |
|---|
Arbuckle, J. L. (1999). Amos (Version 4.0). Chicago: Smallwaters.
Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37, 122 –147.[CrossRef]
Bandura, A. (1986). Social foundations of thought and foundation. Englewood Cliffs, NJ: Prentice Hall.
Bandura, A. (1991). Social cognitive theory of self-regulation. Organizational Behavior and Human Processes, 50, 248 –287.[CrossRef]
Baranowski, T. (1997). Families and health actions. In D. S. Gochman (Ed.), Handbook of health behavior research I: Personal and social determinants. New York: Plenum Press.
Bell, N. H., Shary, J., Garza, M., Gordon, L., & Edwards, J. (1991). Demonstration that bone mass is greater in black than in white children. Journal of Bone and Mineral Research, 6(7), 719 –723.[ISI][Medline]
Bentler, P. M., & Chou, C. (1987). Practical issues in structural modeling. Sociological Methods and Research, 16, 78 –117.[CrossRef]
Browne, M. W., & Cudeck, R. (1993). Alternate ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136 –162). Newbury Park, CA: Sage.
Centers for Disease Control and Prevention. (1998). Youth risk behavior surveillance—United States. Atlanta, GA: Centers for Disease Control.
Cummings, S. R., Kelsey, J. L., Nevitt, M. C., & O'Dowd, K. J.
(1985). Epidemiology of osteoporosis and osteoporotic fractures.
Epidemiologic Reviews,
7, 178
–208.
Domel, S. B., Baranowski, T., David, H., Leonard, S. B., Riley, P., & Baranowski, J. (1994). Fruit and vegetable food frequencies by fourth and fifth grade students: Validity and reliability. Journal of the American College of Nutrition, 13(1), 33 –39.[Abstract]
Duncan, T. E., & McAuley, E. (1993). Social support and efficacy cognitions in exercise adherence: A latent growth curve analysis. Journal of Behavioral Medicine, 16(2), 199 –218.[CrossRef][ISI][Medline]
Eck, L., & Hackett-Renner, C. (1992). Calcium intake in youth: Sex, age and racial differences in NHANES II. Preventive Medicine, 21(4), 473 –482.[CrossRef][ISI][Medline]
Fleming, K., & Heimbach, J. (1994). Consumption of calcium in the U.S.: Food sources and intake levels. Journal of Nutrition, 124(suppl. 8), 1426 –1430.
Fontvieille, A. M., Kriska, A., & Ravussin, E. (1993). Decreased physical activity in Pima Indian compared with Caucasian children. International Journal of Obesity Related Metabolism Disorders, 17, 445 –452.
French, S. A., Fulkerson, J. A., & Story, M. (2000). Increasing weight-bearing physical activity and calcium intake for bone mass growth in children and adolescents: A review of intervention trials. Preventive Medicine, 31, 722 –731.[CrossRef][ISI][Medline]
Garcia, A. W., Broda, M. A. N., Frenn, M., Coviak, C., Pender, N. J., & Ronis, D. L. (1995). Gender and developmental differences in exercise beliefs among youth and prediction of their exercise behavior. Journal of School Health, 65, 213 –219.
Green, J., McIntosh, M., & Wilson, A. (1991). Changes in nutrition knowledge scores and calcium intake in female adolescents. Home Economics Research Journal, 19, 207 –214.
Harel, Z., Riggs, S., Vaz, R., White, L., & Menzies, G. (1998). Adolescents and calcium: What they do and do not know and how much they consume. Journal of Adolescent Health, 22, 225 –228.[CrossRef][ISI][Medline]
Heaney, R. P. (1986). Calcium, bone health and osteoporosis. In W. A. Peck (Ed.), Bone and mineral research (pp. 255–301). New York: Elsevier.
Holmbeck, G. N. (2002). Post-hoc probing of significant moderational and mediational effects in studies of pediatric populations. Journal of Pediatric Psychology, 29(1), 87 –96.
Ievers-Landis, C. E., Burant, C., Drotar, D., Morgan, L. I., Trapl, E. S., & Kwoh, C. K. (2002). A randomized, controlled trial of interventions for the primary prevention of osteoporosis among preadolescent females: Effectiveness of a behavioral program with Girl Scouts. Unpublished manuscript.
Kriska, A. M., Knowler, W. C., LaPorte, R. E., Drash, A. L., Wing, R. R., Blair, S. N., et al. (1990). Development of a questionnaire to examine relationship of physical activity and diabetes in Pima Indians. Diabetes Care, 13(4), 401 –407.[Abstract]
La Greca, A. M. (1992). Peer influences in pediatric
chronic illness: An update. Journal of Pediatric
Psychology, 17, 775
–784.
McKenzie, T. L., Feldman, H., Woods, S. E., Romero, K. A., Dahlstrom, V., Stone, E. J., et al. (1995). Children's activity levels and lesson context during third-grade physical education. Research Quarterly for Exercise and Sport, 66, 184 –193.[ISI][Medline]
Melnick, M. J., Dunkelman, N., & Mashiach, A. (1981). Familial factors of sports giftedness in young Israeli athletes. Journal of Sport Behavior, 4, 82 –94.
Michela, J. L., & Contento, I. R. (1986). Cognitive, motivational, social, and environmental influences on children's food choices. Health Psychology, 5, 209 –230.[CrossRef][ISI][Medline]
Miller, J., Kimes, T., Hui, S., Andon, M., & Johnston, C. J.
(1991). Nutrient intake variability in a pediatric population:
Implications for study design. Journal of Nutrition,
121, 265
–274.
Moore, L. L., Lombardi, D. A., White, M. J., Campbell, J. L., Oliveria, S. A., & Ellison, R. C. (1991). Influence of parents' physical activity levels on activity levels of young children. Journal of Pediatrics, 118, 215 –219.[CrossRef][ISI][Medline]
Musgrave, K., Giambalvo, L., Leclerc, H., Cook, R., & Rosen, C. (1989). Validation of a quantitative food frequency questionnaire for rapid assessment of dietary calcium intake. Journal of the American Dietetic Association, 89, 1484 –1488.[ISI][Medline]
National Institute of Child Health and Development. (1999). Why milk matters: Questions and answers for professionals. Washington, DC: National Institutes of Health.
Parcel, G. S., Edmundson, E., Perry, C. L., Feldman, H. A., O'Hara-Tompkins, N., Nader, P. R., et al. (1995). Measurement of self-efficacy for diet-related behaviors among elementary school children. Journal of School Health, 65, 23 –27.
Parcel, G. S., Simmons-Morton, B., O'Hara, N. M., Baranowski, T., & Wilson, B. (1989). School promotion of healthful diet and physical activity: Impact on learning outcomes and self-reported behavior. Health Education Quarterly, 16, 181 –199.[ISI][Medline]
Reynolds, K. D., Killen, J. D., Bryson, S. W., Maron, D. J., Taylor, C. B., Maccoby, N., et al. (1990). Psychosocial predictors of physical activity in adolescents. Preventative Medicine, 19, 541 –551.[CrossRef][ISI][Medline]
Roberts, M. C. (1992). Vale dictum: An editor's view of the field of pediatric psychology and its journal. Journal of Pediatric Psychology, 19(6), 785 –805.
Roberts, M. C., & Brown, K. J. (2000, Fall). Overcoming obstacles in prevention in pediatric psychology. Progress Notes, 24(3), 11 –14.
Sallis, J. F. (1993). Epidemiology of physical activity and fitness in children and adolescents. Critical Review of Food Science and Nutrition, 33(4/5), 403 –408.
Sallis, J. F., Haskell, W. L., Fortmann, S. P., Vranizan, K. M., Taylor, T. L., & Solomon, D. S. (1986). Predictors and adoption and maintenance of physical activity in a community sample. Preventive Medicine, 15, 331 –341.[CrossRef][ISI][Medline]
Sallis, J. F., Haskell, W. L., Wood, P. D., Fortmann, S. P.,
Rogers, T., Blair, S. N., et al. (1985). Physical activity
assessment methodology in the Five-City Project. American Journal
of Epidemiology, 121, 91
–106.
Sallis, J. F., Hovell, M. F., Hofsetter, C. R., Faucher, P., Elder, J. P., Blanchard, J., et al. (1989). A multivariate study of determinants of vigorous exercise in a community sample. Preventative Medicine, 18, 20 –34.[CrossRef][ISI][Medline]
Sallis, J. F., Pinski, R. B., & Grossman, R. M.
(1988). The development of self-efficacy scales for
health-related diet and exercise behaviors. Health Education
Research, 3, 283
–292.
Shannon, B., Bagby, R., Wang, M. Q., & Trenkner, L. L.
(1990). Self-efficacy: A contributor to the explanation of eating
behavior. Health Education Research,
5(4), 395
–407.
Slater, M. (1989). Social influences and cognitive control as predictors of self-efficacy and eating behavior. Cognitive Therapy and Research, 13(3), 231 –245.[CrossRef]
Terry, K., & Beck, S. (1985). Eating style and food storage habits in the home: Assessment of obese and non-obese families. Behavior Modification, 9(2), 242 –261.[Abstract]
U.S. Department of Health and Human Services. (1996). Physical activity and health: A report of the Surgeon General. Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service, CDC National Center for Chronic Disease Prevention and Health Promotion.
Weaver, C. (1994). Age related calcium requirements due to changes in absorption and utilization. Journal of Nutrition, 124(suppl. 8), 1418 –1425.
Weaver, C. M., Peacock, M., & Johnson, C. C. (1999). Adolescent nutrition in the prevention of postmenopausal osteoporosis. Journal of Endocrinology & Metabolism, 84, 1839 –1843.
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  R. T. Brown Journal of Pediatric Psychology (JPP), 2003 2007: Editor's Vale Dictum J. Pediatr. Psychol., December 11, 2007; (2007) jsm111v1. [Full Text] [PDF]
|
|
|
|
|
|
C. E. Ievers-Landis, C. Burant, D. Drotar, L. Morgan, E. S. Trapl, N. Colabianchi, and C. K. Kwoh A Randomized Controlled Trial for the Primary Prevention of Osteoporosis Among Preadolescent Girl Scouts: 1-Year Outcomes of a Behavioral Program J. Pediatr. Psychol., March 1, 2005; 30(2): 155 - 165. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||