Disclosure: The authors report no actual or potential conflicts of interest.
Self-efficacy and physical activity in adolescent and parent dyads
Article first published online: 10 NOV 2011
© 2011, Wiley Periodicals, Inc.
Journal for Specialists in Pediatric Nursing
Volume 17, Issue 1, pages 51–60, January 2012
How to Cite
Rutkowski, E. M. and Connelly, C. D. (2012), Self-efficacy and physical activity in adolescent and parent dyads. Journal for Specialists in Pediatric Nursing, 17: 51–60. doi: 10.1111/j.1744-6155.2011.00314.x
- Issue published online: 20 DEC 2011
- Article first published online: 10 NOV 2011
- First Received August 11, 2010; Revision received May 27, 2011; Accepted for publication July 29, 2011.
- physical activity;
Purpose. The study examined the relationships between self-efficacy and physical activity in adolescent and parent dyads.
Design and Methods. A cross-sectional, correlational design was used to explore the relationships among levels of parent physical activity, parent–adolescent self-efficacy, and adolescent physical activity. Descriptive and multivariate regression analyses were conducted in a purposive sample of 94 adolescent/parent dyads.
Results. Regression results indicated the overall model significantly predicted adolescent physical activity (R2= .20, R2adj= .14, F[5, 70]= 3.28, p= .01). Only one of the five predictor variables significantly contributed to the model. Higher levels of adolescent self-efficacy was positively related to greater levels of adolescent physical activity (β= .29, p= .01).
Practice Implications. Practitioners are encouraged to examine the level of self-efficacy and physical activity in families in an effort to develop strategies that impact these areas and ultimately to mediate obesity-related challenges in families seeking care.
Childhood obesity is prevalent, continues to increase, and costs the United States more than 3 billion dollars annually (Centers for Disease Control and Prevention [CDC], 2010). In spite of the empirical evidence supporting the positive relationship between increased physical activity and decreased obesity, the literature is replete with studies showing that the greatest reduction in physical activity occurs during the adolescent years (Valois, Umstattd, Zullig, & Paxton, 2008). In fact, for the past several decades, these generations of adolescents have been described as the most sedentary in the history of the United States (Hill & Trowbridge, 1998; Strauss, Rodzilsky, Burack, & Colin, 2001). The disconnection between effective measures to stem adolescent obesity and the resistance in this age group to adopt a lifestyle that includes exercise is a problem all healthcare providers must confront (Valois et al., 2008).
Extant studies focused on the relationship between obesity and moderators of lifestyle change and have identified the concept of self-efficacy as being an important factor (Strauss et al., 2001), both as an important determinant and as a consequence of physical activity (McAuley & Blissmer, 2002). Although support has been found for the role of this construct in contributing to motivation for physical activity (Weiss & Ferrer-Caja, 2002), there are conflicting results in studies with youth. A clearer understanding of the determinants of adolescent physical activity is important for the promotion of an active lifestyle and the prevention of chronic diseases (CDC, 2010). The purpose of this study was to examine the relationships among parent–adolescent self-efficacy, parent physical activity, and adolescent physical activity among a school-based community sample of adolescents.
The issue of weight management for children and adolescents has been part of the healthcare agenda in the United States since the early 1960s. Yet during the past two decades, a 2-fold increase has been seen in the rate of obesity among children; today, approximately 25% of children in the United States between the ages of 6 and 17 years are overweight (Barlow, 2007; Dietz, 2005). Data from the National Health and Nutrition Examination Survey (NHANES), 1976–1980 and 2003–2006, show that the prevalence of obesity has increased for youth from 6.5% to 17.0% for those ages 6–11 years; and from 5.0% to 17.6% for those ages 12–19 years (NHANES, 2008; Ogden, Carroll, & Flegal, 2008). Although the American Academy of Pediatrics (AAP; 2003) issued a policy statement indicating grave concerns regarding the dramatic increase in the prevalence of childhood obesity and the resultant comorbidities associated with significant lifelong health and financial burdens, the problem continues to escalate. Recently, Ogden, Carroll, Curtin, Lamb, and Flegal (2010) reported that the prevalence of high body mass index (BMI) in childhood has remained steady without a decline for 10 years; alarmingly, heavier boys may be getting even heavier (p. 278).
Healthy People (HP) 2010/2020 includes physical activity as a major focus for improvement as it has for the past 30 years (U.S. Department of Health and Human Services [USDHHS], 2000, 2010). The CDC (2010) recommended 60 min of moderate to vigorous physical activity daily, while the HP 2010/2020 standards identified the adolescent goal as “vigorous physical activity that promotes cardio-respiratory fitness 3 or more days per week for 20 or more minutes per occasion” (USDHHS, 2000, p. 26, 2010). For adults, the 2010/2020 standards target behaviors that “engage regularly, preferably daily, in moderate physical activity for at least 30 min per day” (USDHHS, 2000, p. 26, 2010).
Popular electronic entertainment activities aimed at children and adolescents have been identified as a major contributor to lifestyle choices that continue to diminish physical activities in this age-group (Goran, Reynolds, & Lindquist, 1999). The conveniences of modern lifestyles have all but eradicated the need for moderate or vigorous activities associated with activities of daily living (Hill & Trowbridge, 1998). It is highly unlikely that today's modern conveniences, technological advancements, or use of electronic “hobbies” will give way to “old-fashioned” lifestyles, and, as a result, families are finding it necessary to make conscious efforts to balance sedentary activities with planned or scheduled effective levels of physical activity. AAP recommends enjoyable activities that involve family members and friends to participate in skill development, tactic and strategy activities, and complex sports including track and field, football, basketball, and ice hockey (Council on Sports Medicine and Fitness and Council on School Health, AAP, 2006).
Self-efficacy is the belief that one can perform a specified behavior in a specific situation (Bandura, 1994, 1997) and reflects a level of confidence that the outcomes of the behavior will produce the benefits predicted (Hofstetter, Hovell, & Sallis, 1990). Bandura (1997) argued that self-efficacy beliefs define an individual's capacity to carry out actions and to make decisions that are part of success in progressing to positive outcomes. It is theorized that self-efficacy beliefs influence motivation, affect, and behavior. Self-efficacy is commonly understood as being domain specific, and, although self-efficacy measures often refer to single tasks, some of the acts pertain to a larger domain of what Bandura (1997) defined as generalized self-efficacy. Indeed, some researchers have conceptualized a generalized sense of self-efficacy that refers to a global confidence in one's coping ability across a wide range of demanding or novel situations (Schwarzer & Scholz, 2000). General self-efficacy (GSE) aims at a broad and stable sense of personal competence to deal effectively with a variety of stressful situations (Schwarzer & Scholz, 2000). Spruiji-Metz and Saelens (2006) asserted that GSE for physical activity would include an individuals' level of confidence for competently engaging in physical activity. More specifically, Ryckman, Robbins, Thornton, and Cantrell (1982) suggested that physical self-efficacy influences a more task-specific self-efficacy, which, in turn, affects how well one expects to perform (i.e., prediction of performance) and which ultimately influences performance. Several studies of children have reported that level of self-efficacy was empirically linked to physical activity patterns (Davidson, Simen-Kapeu, & Veugelers, 2010; Strauss et al., 2001). These findings are in direct contrast to those reported by Deforch, Van Dyck, Verloigne, and De Bourdeaudhuij (2010) and Valois and colleagues (2008). These conflicting findings may result from lack of clarity in definition and measurement. In an attempt to clarify and expand the existing knowledge, the study reported here examined GSE in terms of personal competency and exercise patterns of adolescent family dyads and not behavior-specific self-efficacy (e.g., physical activity self-efficacy).
The conceptual framework for this study was derived from the literature and was guided by two theoretical perspectives: Bandura's (1997) Social Cognitive Theory (SCT) and Bronfenbrenner's (1979) Ecological Systems Theory (EST). SCT (Bandura, 1994, 1997) describes concepts that are based upon a person's expectations relative to a specific course of action. It is a predictive theory in the sense that it deals with the belief that one can accomplish a specific behavior (Bastable, 2008). The main thrust of this theory states that people will more often be willing to attempt to make changes in their behaviors if they believe that they have the efficacy to accomplish this behavior (Bastable, 2008). EST incorporates the beliefs that health is an outcome dependent upon the quality of the fit between the person and the environment and that there is interdependence between the social and physical environments (Bronfenbrenner, 1979; Grzywacz & Fuqua, 2000). EST describes leverage points for health, one of which is family and health (Grzywacz & Fuqua, 2000). The family is an important niche, and the social interactions within this structure may impact the variables examined in this study. This perspective supports the need to include both the parent and the adolescent in this study; to examine one without the other would generate an incomplete description of the relationships.
A descriptive, correlational, cross-sectional design was used for this study.
Recruitment and setting.
A purposive sample of 94 adolescent/parent dyads was recruited from eight middle schools within a single school district in southern California during fall 2007. A letter of introduction presenting the principal investigator and research study was sent to the middle schools' principals. During “Back to School Night” at each middle school, a meeting took place for parents of students who were interested in learning about and potentially participating in the study. The study protocol was presented, questions addressed, and informed consent was obtained from the parents, as well as obtaining parents' permission to approach their children regarding participation. The inclusion criteria for parent participants specified that they were able to read and speak English, had legal custody of the adolescent participants, and had signed the consent form for participation for themselves and their children. The inclusion criteria for adolescents included being between the ages of 12 and 15 years and able to read and speak English; signed informed assent specified a signed informed parent consent. All study procedures, including protocols for recruiting participants and obtaining informed consent, including child assent, were reviewed and approved by appropriate institutional review boards and administrators. Complete discussion of sampling procedures is described elsewhere (Rutkowski & Connelly, 2011).
Parents self-administered a survey containing demographic questions, the GSE Scale (Schwarzer & Jerusalem, 1992), and the International Physical Activity Questionnaire (IPAQ; 2001). Adolescents self-administered the demographic survey, the GSE (Schwarzer & Jerusalem, 1992), and the Patient-Centered Assessments and Counseling for Exercise Plus Nutrition + Moderate Vigorous Activity (PACE + MVPA; Prochaska, Sallis, & Long, 2001). Additionally, pedometers were worn by the adolescents for quantitative measurement of their physical activity.
Parents provided information regarding age, gender, race/ethnicity, height, weight, household constellation, marital status, employment status, and level of education. Adolescents provided information regarding age, gender, race/ethnicity, height, weight, household constellation, grade in school, and grade-point average.
Self-efficacy was assessed using the 10-item GSE developed by Schwarzer and Jerusalem (1992) to assess a general sense of perceived self-efficacy with the aim to predict coping with daily hassles, as well as adaptation after experiencing stressful life events. The GSE was originally developed in Germany over the course of two decades and has been adapted to 28 languages (Schwarzer & Jerusalem, 1995). Typical items include, “I can always manage to solve difficult problems if I try hard enough”; “It is easy for me to stick to my aims and accomplish my goals.” Possible responses are (a) not at all true, (b) hardly true, (c) moderately true, and (d) exactly true, yielding a total score between 10 and 40. It is designed for testing the general population, including adolescents, but not for children younger than 12 years. The GSE is a validated measure with inter-rater and internal consistency reliability of .76–.90 (Schwarzer & Jerusalem, 1992). In this study, the Cronbach's Alpha scores of .89 for the parents and .83 for adolescents were indicative of good reliability.
Physical activity was measured by (a) the IPAQ (2001) for parents, (b) The PACE + MVPA (Prochaska et al., 2001), and (c) W4L Pedometers (for adolescent participants; Walk 4 Life, Inc., n.d.). The dual measurement for adolescents was chosen per recommendations in the literature (Tudor-Locke & Lutes, 2009; Welk, Corbin, & Dale, 2000). Armstrong and Welsman (2006) have cautioned that discrepancies often occur when including two types of measurements because children tend to overestimate their recall of vigorous physical activities but underestimate their moderate physical activities. Children often do not recall moderate levels of activity because it is often unplanned, sporadic, less memorable, and less quantifiable (Armstrong & Welsman, 2006). Despite the acknowledged limitations, self-report of physical activity and measurement pedometers are the most widely used because of low cost and ease of implementation (Armstrong & Welsman, 2006; Bravata et al., 2007; Welk et al., 2000).
The IPAQ was developed to provide a set of well-developed instruments that are used internationally to obtain comparable estimates of physical activity (IPAQ, 2001). This instrument is designed in both a short version, including four generic items, and a long version that reflects five activity domains (IPAQ, 2001). Adequate test–retest reliability and criterion validity have been reported (IPAQ, 2001). The study presented here incorporates the short version as it is able to capture the general conditions of parental activity without being burdensome to complete. A typical question from this questionnaire follows (IPAQ, 2001): “During the last 7 days, on how many days did you do vigorous physical activities like heavy lifting, digging, aerobics, or fast bicycling? Think about only those physical activities that you did for at least 10 min at a time” (Table 1). The categories of activity levels were assigned by the IPAQ Research Committee (Guidelines for Data Processing and Analysis of the IPAQ, 2005) as follows:
|Age M (SD) range||12.8 (1.0) 11.8–13.8||44.1 (5.2) 31–60|
|Ethnicity n (%)|
|Caucasian||70 (74.5)||69 (74.2)|
|Hispanic||14 (14.9)||16 (17.2)|
|Asian||5 (5.3)||6 (6.5)|
|Other||5 (5.3)||2 (2.2)|
|Gender n (%)|
|Male||56 (59.6)||19 (20.2)|
|Female||38 (40.4)||75 (79.8)|
|BMI M (SD) range|
|Total||19.4 (2.7) 13.6–32.9||24.1 (4.9) 18.2–43.2|
|Male||19.2 (2.4) 13.6–26.3||26.7 (4.5) 19.1–37.0|
|Female||19.6 (3.1) 15.2–32.9||23.4 (4.8) 18.2–43.2|
|Household Size M (SD) range||4.41 (.9) 2–6||4.41 (.9) 2–6|
|Grade in school n (%)|
|GPA n (%)|
|4.0 or higher||23 (24.5)|
|Marital status n (%)|
|Number of years with partner M (SD) range||17.5 (4.9) 2–31|
|Education n (%)|
|Less than high school||2 (2.3)|
|High school diploma||14 (16.1)|
|Graduate school||26 (29.9)|
|Work outside the home n (%)|
High (category 1)—those who move approximately 12,500 steps per day or 1 hr more of moderate-intensity activity over and above the basal level (5,000 steps) of activity; moderate (category 2)—some activity, more than low-active category; low-walking (category 3)—not meeting any of the criteria for either of the previous categories. In this study, the Cronbach's alpha score of .80 is indicative of good reliability for the IPAQ instrument.
The PACE + MVPA (Prochaska et al., 2001) was originally developed as a screening tool for use by clinical staff to measure physical activity levels in adolescents seeking treatment in primary care settings. This instrument does not comprehensively assess adolescents' levels of physical activity, but rather it identifies adolescents who do not meet the recommended guidelines as addressed in HP 2010 (Prochaska et al., 2001). Reliability (intraclass correlation coefficient [ICC]= .77) and concurrent validity (r= .40) have been reported (Prochaska et al., 2001). Although brief, this instrument is practical and assesses targeted behavior that offers clinical information to practitioners (Prochaska et al., 2001). The two questions included in this measure are “Over the past 7 days, on how many days were you physically active for a total of at least 60 min per day?” and “Over a typical or usual week, on how many days are you physically active for a total of at least 60 min per day?” Each response has a scale of 0–7 days. The scores for each question are summed, and this summed score is divided by 2. A score of less than 5 indicates that the HP 2010 guideline for adolescent physical activity is not being met (Prochaska et al., 2001; see Table 1). In this study, reliability was adequate (ICC = .81).
Waist-mounted W4L Pedometers were used by the adolescents to capture validation data for physical activity. The W4L pedometer uses average stride lengths and counts approximately 2,000 steps as equal to 1 mile (Walk 4 Life, Inc., n.d.).
Data were analyzed using the software package PASW 18.0 (Statistical Package for Social Sciences, 2010). The sample size for the analysis was 94 dyads, which is sufficient to detect a moderate-standardized effect size (d= .32) using a two-tailed significance test with a power of .80 and a significance level of .05 (Cohen, 1988; Polit & Beck, 2008). There were some differences in sample sizes for specific analyses because of missing data for specific questions.
Parents ranged in age from 31 to 60 years with a mean age of 44.1 (standard deviation [SD]= 5.2) and included 79.8% mothers. Approximately three quarters (74.2%) self-identified as Caucasian, 17.2% self-identified as Hispanic, 6.5% self-identified as Asian, and 2.2% self-identified as other. The mean adult BMI was 24.1 (SD= 4.9). Adolescents reported a mean age of 12.8 years (SD= 1.0); racial/ethnic distribution was 74.5% Caucasian, 14.9% Hispanic, 5.3% Asian, and 5.3% other. The mean adolescent BMI was 19.38 (SD= 2.7): 19.2 (2.4) range 13.6–26.3 for boys, and 19.6 (3.1) range 15.2–32.9 for girls. See Table 1.
The mean score for parent self-efficacy was M= 34.45 (SD= 4.1). The mean score for adolescent self-efficacy was M= 31.78 (SD= 4.5).
The results for parental physical activity were calculated by following the instructions for both the continuous and the categorical analysis of the IPAQ (Guidelines for Data Processing and Analysis of the IPAQ, 2005). Mean minutes of parent physical activity per week was 3,741.07 (SD= 3,135.43), range 0–12,558. Sixty-two percent of the parents rated their activity level as “high” with a metabolic equivalents (MET)-minutes/week mean of 1,960.8; “moderate” levels were reported by 18% of the parents with a MET-minutes/week mean of 872.2, and 15% of the parents reported “low” or “walking” levels of activity with a mean MET-minutes/week of 1,068.7.
The results for the adolescents as measured by the PACE + MVPA indicated that 70% of the adolescent participants met the 5-day expected level of activity to meet physical activity guidelines as put forth in HP 2010 (USDHHS, 2000). The pedometer data and the PACE+ scores were not significantly correlated (r= .09, p= .39). Pedometer data for the 3 days are presented in Table 2.
|Day 1||88||11562.5 (6212.8)||600–51,388|
|Day 2||88||11245.1 (5172.0)||1094–40,000|
|Day 3||86||12435.2 (6472.7)||812–50,000|
Self-efficacy and level of physical activity
Pearson's product–moment correlations were used to examine the relationships between the study variables. In this sample, parent physical activity and parent GSE scores were positively correlated (r= .22, p < .05), and adolescent physical activity measured by the PACE+ was positively correlated with adolescent GSE (r= .35, p < .01). A statistically significant inverse relationship was found between parent activity level and the PACE+ score for activity level of adolescents (r=−.23, p < .05). Parent reports of increased levels of parent physical activity were associated with adolescents' reported lower levels of physical activity. Simultaneous multiple regression was used to determine the accuracy of the independent variables (parent physical activity, parent self-efficacy, adolescent self-efficacy, and adolescent age and gender) in predicting adolescent physical activity. This standard multiple regression strategy was appropriate because all independent variables were viewed as having equal importance, there were no a priori hypotheses, and regression diagnostic procedures did not detect problems with multicollinearity among the predictor variables. All tolerance values were greater than .10. Given that adolescent race/ethnicity did not correlate at a level of significance with parent physical activity, parent self-efficacy, adolescent self-efficacy, adolescent age, gender, and adolescent physical activity, it was excluded to preserve statistical power.
Regression results indicated the overall model significantly predicted adolescent physical activity (R2= .20, R2adj= .14, F[5, 70]= 3.28, p= .01). This model accounted for 20% of the variance in adolescent physical activity. A summary of the regression coefficients in Table 3 indicated that only one of the five variables (adolescent self-efficacy) significantly contributed to the model.
|Parent physical activity||.000||.001||−.03||−.30||.76|
The purpose of this study was to investigate the association of parent physical activity, parent–adolescent self-efficacy, and adolescent physical activity. Consistent with self-efficacy theory (Bandura, 1989), there were positive relationships between higher levels of self-efficacy and greater involvement with exercise. A statistically significant inverse relationship was found between parent physical activity level and the PACE+ scores of adolescents (Rutkowski & Connelly, 2011). Higher levels of parent physical activity were associated with lower levels of adolescent physical activity.
The high scores on the GSE for both parents and adolescents are an indication that these participants should be able to pursue challenges and call upon their own resourcefulness when confronted with challenges (Araujo-Soares, McIntyre, & Sniehotta, 2009; Bandura, 1997; Spruiji-Metz & Saelens, 2006). A commonly described challenge in many families is finding the time to be physically active because of the busy schedules of today's parents and adolescents (Styles, Meier, Sutherland, & Campbell, 2007). The parents and adolescents in this study with high self-efficacy levels might have been able to negotiate the logistics of their daily lives to accommodate physical activity despite the difficulty identified in many families to find the time required to do so (Styles et al., 2007). Families with high levels of self-efficacy will more readily make decisions concerning their physical activity behaviors as opportunities for health rather than focusing on the obstacles competing for time with these types of activities (Schwarzer & Luszczynska, 2006).
Previous studies have supported the notion that among youth, both confidence in skills and self-efficacy are important factors affecting physical activity levels (Luepker, 1999). Schwarzer and Luszczynska (2006) maintained that self-efficacy is not only reflective of current levels of adolescent physical activity but also “a very strong predictor of future activity in these adolescents” (p. 148). Adolescent physical activity, as measured by the PACE+, and increased GSE scores in the study reported here support this previous empirical work. Adolescent participants reported increased self-efficacy, and 70% can be described as meeting recommended activity levels as measured by the PACE+. Their average number of steps taken per day is reflective of an “active” category of physical activity as defined by Tudor-Locke and Bassett (2004). The remaining 30% may have actually been physically less active, or they may have failed to report their step counts accurately. The lack of significance between the pedometer data and the PACE+ scores may be due to the inability of the pedometer to measure any physical activity where the foot is not striking the ground (e.g., swimming, bike riding, and jumping).
The elevated GSE scores in the parent population are consistent with the findings in their children. Just as there was a positive relationship between the adolescent's self-efficacy and his/her physical activity level, so was there the same positive correlation between the parent's self-efficacy and his/her physical activity level. An interesting finding in this study is that although the parent self-efficacy was related to his/her own physical activity, it does not appear to be related to that of his/her child; parent's self-efficacy did not have a relationship with his/her child's physical activity level in this study's sample. This finding may be a result of these adolescent participants having role models other than parents who were impacting the self-efficacy levels, which has been reported in previous research (Ievers-Landis et al., 2003). There may have been teachers, coaches, siblings, or peers that were encouraging the adolescents to be more physically active (Salvy et al., 2008); unfortunately, our data did not allow for these analyses. Further studies are needed to examine specific relationships other than parents that may influence adolescents in the area of self-efficacy for physical activity.
The findings of this study must be considered in relation to the study's limitations. First, the sample was a purposive convenience sample that was relatively homogeneous with respect to ethnicity, geographic location, social economic status (SES), and BMI and was not randomly selected or matched. There are also limitations regarding potential for school effects; however, we were recruiting “a cohort” of adolescents. To obtain our target sample, it was necessary to recruit from multiple sites within a school district. Identification of school was not collected. Notably, schools within the district were fairly homogeneous in SES and diversity. This nonrandom procedure may have influenced the findings through self-selection bias. Second, the cross-sectional design disallowed for changes over time and may not have captured the complex phenomena under study. Additionally, a different “parental configuration” including more fathers, grandparents, etc., would have strengthened the study. Further research is needed to include a group of family dyads who are not associated with an educational setting. This would allow findings to be viewed without the bias regarding level of physical activity and self-efficacy inherent in using a sample associated with a physical education class. Indeed, in our sample of adolescents, only one was outside of normal weight, thus precluding any analyses to discern differences in self-efficacy or physical activity level by normal and overweight status.
The use of the pedometer is another limitation. As pointed out by Rowlands, Eston, and Ingledew (1997), pedometers are thought to be too inaccurate for research purposes as they (a) have low reliability when the user's pace is either too slow or too fast; (b) are not capable of collecting energy expenditure information when physical activity includes carrying weight or engaging in activities where one must negotiate climbing or pedaling; and (c) are not waterproof, and therefore water-based activities are not measured. As a result, many physical activities could not be measured such as biking, stair climbing, swimming, etc. (Rowlands et al., 1997), which may have resulted in skewed levels of physical activities for some of the adolescents and the inability to report accurate data for this variable.
Despite these limitations, the results of this study contribute to our understanding of these correlates with adolescent physical activity. Notably, the inverse relationship between parental and adolescent physical activity levels may provide insight into how families can adjust their time to impact the adolescents' level of activity by reorganizing time spent among family members to include “shared” time in some type of physical activity. Study findings also supported prior research indicating the influence of self-efficacy on physical activity.
This study underscored the need for continued studies in the area of physical activity for families with adolescents. As noted earlier, the effects of role modeling beyond the parental dyad is one area of particular interest for future research. Additionally, our study did not include any determinates of adolescent physical activity beyond self-efficacy or obesity risk knowledge (Rutkowski & Connelly, 2011). Further studies including nutrition, especially the impact of physical activity on levels of insulin, would further strengthen the body of literature regarding adolescent obesity.
How might this information affect nursing practice?
It is important for practitioners to study the issues affecting or contributing to obesity in families with adolescents because obesity becomes more difficult to prevent and treat after children enter the teenage years (Lytle et al., 2009). The steady increase in the number of obese children every year since 1975 is graphically unquestionable and should give warning that a cohort of Americans with underlying cardiovascular disease is inevitable (Davidson et al., 2010). Severely obese individuals, compared with normal weight people, have twice the number of chronic health conditions (Rand Corporation, 2007). With the looming nursing shortage, the increasing numbers of potential patients with chronic healthcare needs because of obesity will further burden an over-taxed healthcare delivery system (Rand Corporation, 2007).
During visits to primary healthcare settings, practitioners may explore the adolescent's perceptions of control over his/her environment and behavior as both of these influence levels of self-efficacy (Schwarzer & Luszczynska, 2006). Discussions with the adolescent and his/her caregiver regarding overcoming obstacles for being physically active will help the adolescent to set goals and to increase his/her skill-set for activities, which is the essence of self-efficacy (Schwarzer & Luszczynska, 2006). On subsequent visits, practitioners can offer positive reinforcement to families who report their attempts at increasing their activity levels. This in turn will create a perception that being physically active is achievable and manageable within the context of their busy lives.
Practitioners may perceive that highly active, “fit” parents inoculate their children against a lifestyle that is different than their own. Our findings suggest that it is important for nurses to acknowledge parents who are highly committed to their personal fitness routines and to encourage those who are engaging in them at times that their children are not “interfering,” to also carve out time to be physically active with their children. Our findings do not include information specific to whether “highly” active parents exclude their adolescent by exercising outside family time; however, pediatric specialists can help parents to think through how they can include their children in some aspect of their time dedicated to working out (e.g., have the child bike as they do part of their run; take the child to the pool/beach with them; and cool down or warm up with their child). Surprisingly, in our study, both parents and adolescents reported high levels of self-efficacy, yet they were not significantly related. This lack of association is puzzling, as we know that simple activities with parents may result in building confidence and in generating the self-efficacy that adolescents will use to maintain lifelong healthy lifestyles. Further research is needed in this area.
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