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Home > RNJ > 2007 > July/August > The Relationship Between Psychosocial State and Exercise Behavior of Older Women 2 Months After Hip Fracture (CE)

The Relationship Between Psychosocial State and Exercise Behavior of Older Women 2 Months After Hip Fracture (CE)
Barbara Resnick, PhD CRNP Denise Orwig, PhD William Hawkes, PhD Michelle Shardell, PhD Justine Golden, MS Michele Werner, BS Sheryl Zimmerman, PhD Jay Magaziner, PhD

Despite the potential benefits associated with exercise after hip fracture, those who have sustained hip fractures are among the least likely to engage in regular exercise (resistive or aerobic). This article describes the psychosocial state, specifically the self-efficacy expectations and outcome expectations related to exercise, mood, fear of falling, pain, and health status of older women who enrolled in either of two Baltimore Hip Studies (BHS), BHS-4 and BHS-5, and to test a self-efficacy–based model to explain exercise behavior after hip fracture. A total of 389 older women with hip fractures participated in these studies. The participants reported moderate confidence in their ability to exercise and a general belief in the benefits of exercise, high perceived health status, limited depressive symptoms, and some pain and fear of falling. Consistently across these two samples, age and mental status or depressive symptoms influenced outcome expectations, such that older women with more depressive symptoms or lower mental health status had weaker outcome expectations for exercise. Self-efficacy expectations consistently influenced exercise behavior across both samples. It was also consistent across both models that age, cognitive status, physical and mental health status, pain, fear, outcome expectations, and depressive symptoms did not directly influence exercise behavior.

More than 350,000 people sustain hip fractures each year, necessitating hospitalization, repair of the fracture, and rehabilitation services (Agency for Health Care Research, 1999; Cauley, Thompson, Ensrud, Scott, & Black, 2000; Haentjens, Autier, Barrett, & Boonen, 2001; Johnson, Kramer, Lin, Kowalsky, & Steiner, 2000; Van Balen et al., 2001). Unfortunately many older adults who sustain a hip fracture do not recover their prefracture level of ambulatory function, with approximately 25% demonstrating a significant functional decline in activities of daily living such as bathing and dressing (Cree, Carriere, Soskolne, & Suarez-Almazor, 2001). Specific functional needs may vary, with 20% needing help with lower extremity dressing and up to 90% needing help climbing the stairs (Magaziner et al., 2000). People who have sustained a hip fracture are noted to be impaired in their ability to rise independently from an armless chair or to step symmetrically (Fox, 1998). Approximately 38%–50% need assistance to walk or are unable to walk at 12 months after hip fracture (Boonen et al., 2004; Michael et al., 2000). These changes can result in a change in level of care needed, and 31% of older adults were noted to be discharged to nursing homes after their hip fracture (Magaziner et al.). Also, 17% of older adults remain in institutions 3 months after fracture (Cree et al.).

A recent Cochrane Report (Cochrane Database System Review, 2004) indicated that there was insufficient evidence to determine the effectiveness of various mobilization strategies after hip fracture. However, regular exercise (resistive or aerobic) does improve mobility (Mangione, Craik, Tomlinson, & Palombaro, 2005; Tsauo, Leu, Chen, & Yang, 2005), increase walking speed (Habris, O’Hara, & Harper, 1995; Henderson et al., 1992), improve quadriceps strength, and increase weight-bearing ability (Habris et al.). Unfortunately, these patients generally do not engage in regular exercise (Frandin, Mellstrom, Sundh, & Grimby, 1995; Scharff, Horman, Kreuter, & Brennan, 1999; Wainright et al., 2005).

A number of variables have been reported to influence motivation to exercise and adherence to regular exercise in older adults (Conn, Minor, Burks, Rantz, & Pomeroy, 2003; King, Rejeski, & Buchner, 1998; Resnick & Spellbring, 2000). Of these variables, those described in social cognitive theory, specifically the theory of self-efficacy, are most likely to influence behavior (Brawley, Rejeski, & King, 2003; Conn, Minor, et al., 2003; King et al., 1998). Self-efficacy theory incorporates two major concepts: self-efficacy expectations, which is a belief in one’s ability to perform a course of action to attain a desired outcome, and outcome expectations, which are one’s beliefs that a certain consequence will be produced by personal action. Efficacy expectations are dynamic and are both appraised and enhanced by four mechanisms (Bandura, 1986): enactive mastery experience, or successful performance of the activity of interest; verbal persuasion, or verbal encouragement given by a credible source that the person is capable of performing the activity of interest; vicarious experience, or seeing similar people perform a specific activity; and physiological and affective states such as pain, fatigue, or anxiety associated with a given activity. The theory of self-efficacy suggests that the more strongly the person believes in his or her ability to perform a specific activity (i.e., self-efficacy) and the more strongly he or she believes in the benefit of engaging in the activity (i.e., outcome expectations), the more likely it is that he or she will initiate and persist with a given activity.

Additional Factors That Influence Exercise Behavior

Age. Although not always consistent, age has been related to self-efficacy expectations for exercise and exercise behavior, with advancing age being associated with lower self-efficacy for exercise (Resnick et al., 2004; Riebe et al., 2005) and decreased time spent in exercise (Conn et al., 2003; Lim & Taylor, 2005; Riebe et al., 2005). In a large community-based sample of older adults (Lim & Taylor), for example, the adjusted prevalence rate ratio was 0.99, indicating that with increased age there was less likelihood of engaging in adequate physical activity (recommended level of 30 minutes of physical activity 5 days per week).

Cognitive Status. Impaired cognitive status has consistently been associated with poor recovery from a hip fracture (Arinzon, Fidelman, Zuta, Peisakh, & Berner, 2005; Cree et al., 2001; Cree, Yang, Sclater, Johnson, & Carriere, 2002; Dolan et al., 2000; Lenze et al., 2004). Specifically, those who are more impaired cognitively take longer to recover function and are less likely to get back to their baseline function. Impaired cognitive status has also been associated with lower levels of physical activity (deJong & Franklin, 2004; Lytle, Vander Bilt, Pandav, Dodge, & Ganguli, 2004).

Physical and Mental Health. Physical health and mental health status also are associated with exercise. Older adults with lower perceived mental health (e.g., evidence of depression, overall mental health status) are less likely to engage in adequate exercise, as noted by an adjusted prevalence rate ratio of 0.99 (Lim & Taylor, 2005) and significant path estimates in predictive models of exercise (Conn, Burks, et al., 2003; Resnick, Zimmerman, Orwig, Furstenberg, & Magaziner, 2000). Similarly, physical health status influences exercise, such that those with worse perceived health were less likely to exercise, as demonstrated by an adjusted prevalence rate ratio of 1.02 (Lim & Taylor).

Pain. Evidence of pain has also been associated with a limitation in physical activity and exercise (Krein, Heisler, Piette, Makki, & Kerr, 2005; Tu, Stump, Damush, & Clark, 2004; Yamakawa, Tsai, Haig, Miner, & Harris, 2004). Older adults with pain are less likely to engage in exercise or adhere to participation in exercise programs.

Fear of Falling. Fear of falling has been noted to be the most common psychological consequence of having had a fall (Evitt & Quigley, 2004; Murphy, Dubin, & Gill, 2003; Murphy, Williams, & Gill, 2002) and occurs in 42%–73% of those who have fallen (Friedman, Heisel, & Delavan, 2005; Lach, 2006; Murphy et al., 2003). Fear of falling may be a beneficial response for some older adults because it causes them to be cautious and thereby prevent future falls (Murphy et al., 2002). Conversely, the fear of falling can result in negative consequences such as reduced physical activity (Bruce, Devine, & Prince, 2002; Fletcher & Hirdes, 2004; Li et al., 2005), decreased participation in functional activities (Cumming, Salkeld, Thomas, & Szonyi, 2000; Martin, Hart, Spector, Doyle, & Harari, 2005), lower perceived physical health status (Brouwer, Musselman, & Culham, 2004), lower quality of life and poor life satisfaction (Cumming et al.; Li et al.), and increased institutionalization (Cumming et al.; Li et al.).

Two randomized controlled trials in the Baltimore Hip Studies Program tested the Exercise Plus Program, a home-based exercise intervention program that includes aerobic and resistance exercises and a motivational component based on self-efficacy theory (Resnick, 2002). The first study, Testing the Impact of the Exercise Plus Program on Recovery Following Hip Fracture (BHS-4), was a development study for assessing exercise effects on functional recovery, bone density, and muscle strength. A subsequent study, Testing the Impact of the Exercise Plus Program on Exercise Behavior in Hip Fracture Patients (BHS-5), focused on improving adherence to exercise in the first 12 months after fracture. In both BHS-4 and BHS-5 the Exercise Plus Program was implemented approximately 2 months after hip fracture, when the participants finished traditional rehabilitation. The purpose of this report was to test a theoretically based model of the psychosocial factors that influence exercise behavior in two different samples of older women 2 months after hip fracture and before initiation of an exercise intervention. Specifically, it was hypothesized that age, physical health status, mental health status, depression, pain, and fear of falling influence self-efficacy and outcome expectations, and all of these variables directly influence exercise behavior after hip fracture (Figure 1). The two similar cohorts provided an opportunity to consider the consistency of these relationships across the two different samples and the generalizability of these findings.

Methods

Design and Procedure

BHS-4 and BHS-5 were randomized clinical trials testing the impact of the Exercise Plus Program, a combined exercise and motivational intervention, on exercise behavior in older women after hip fracture. Participants were interviewed within 15 days of the hip fracture and again at 2, 6, and 12 months after hip fracture. This report used data collected 2 months after hip fracture. This time frame was reflective of when traditional rehabilitation was completed but participants had not yet started the Exercise Plus Program. Interviews were completed by research nurses in the post–acute care discharge setting (home, nursing home, or assisted living). Institutional review board approvals were obtained from the University of Maryland School of Medicine and the study hospitals, and all enrolled subjects provided their own informed consent. A Data and Safety Monitoring Board met quarterly and reviewed all adverse events and safety reports.

Sample

A total of 389 female hip fracture patients (BHS-4 = 180 and BHS-5 = 209) 65 years and older and community-dwelling at the time of fracture were consented within 15 days of the hip fracture (1998–2004). These women were recruited from three acute care facilities in BHS-4 and nine acute care facilities in BHS-5. Eligibility was determined through a medical chart review, medical assessment, and cognitive screen. Eligibility requirements included having a fracture and surgical repair of the hip within 72 hours of admission. Exclusions included specific cardiovascular problems, neuromuscular conditions limiting exercise (e.g., Parkinson’s disease), respiratory conditions, diseases of the bone (e.g., Paget’s disease, osteomalacia), metastatic cancer, cirrhosis, end-stage renal disease, and other medical problems that would increase the risk of falling while exercising independently (e.g., history of seizures, alcohol abuse, chronic narcotic or benzodiazepine use). Subjects also had to be walking without human assistance before the fracture and score higher than 20 on the Folstein Mini–Mental State Exam (Folstein, Folstein, & McHugh, 1975).

Of those who were initially recruited into BHS-4, 149 (83%) were available for 2-month assessments, and 166 women (79%) were available from BHS-5. Reasons for the loss to follow-up at 2 months after hip fracture are shown in Table 1. The majority of the participants in both studies were Caucasian (BHS-4, 94%; BHS-5, 97%), and the average age of the participants was 82.5+ 6.9 years in BHS-4 and 84.0 + 6.9 years in BHS-5. Approximately one third of the participants from both studies were married. The remaining were widowed (54% in BHS-4 and 58% in BHS-5), never married (BHS-4, 7%; BHS-5, 4%), or divorced or separated (BHS-4, 6%; BHS-5, 6%). The average number of years in school was 12.3 + 3.5 in BHS-4 and 12.2 + 2.9 in BHS-5.

Measures

Demographic information included age, ethnicity, marital status, and education. In addition, the Self-Efficacy for Exercise (SEE) scale and the Outcome Expectations for Exercise (OEE) scale were completed along with the Yale Physical Activity Survey and the Short Form Health Survey (SF-36). A single-item question related to fear of falling, restriction of activities related to fear, and a numeric rating of pain were evaluated.

The SF-36 (Ware & Sherbourne, 1992) is a health survey that assesses limitations in physical and social activities or role because of physical or emotional problems, bodily pain, general mental health, vitality, and general health perceptions over the previous week. There is support for the reliability and validity of this measure when used with older adults (Cranney et al., 2005; Osborne, Hawthorne, Lew, & Gray, 2003; Stewart, Hays, & Ware, 1988; Stewart, King, & Haskell, 1993).

Fear of Falling. Fear of falling was evaluated by asking the participant to rate her fear of falling on a scale of 0 to 4. This single question was reported to be reliable and valid in varied samples and settings (Resnick, 1998; Resnick, Jung, & Orwig, in press).

Pain. Pain was measured using the 0–10 Numeric Rating Scale (NRS) (Herr & Mobily, 1991; Herr & Mobily 1993). Use of the NRS with older adults has been noted to have a low incidence of error and to correlate significantly with other pain measures (r = .91) (Herr & Mobily, 1991, 1993; Herr, Spratt, Mobily, & Richardson, 2004).

Self-Efficacy and Outcome Expectations. The SEE scale (Resnick & Jenkins, 2000) is a nine-item measure that focuses on self-efficacy expectations related to the ability to continue to exercise in the face of barriers to exercising. Prior use of this measure with older adults provided evidence of reliability and validity (Harnirattisai & Johnson, 2002; Resnick & Jenkins, 2000).

The OEE (Resnick et al., 2000) is a nine-item measure that focuses on the perceived consequences of exercise for older adults. Prior use has demonstrated sufficient evidence for internal consistency and validity (Harnirattisai & Johnson, 2002; Resnick et al., 2000; Resnick, Zimmerman, Orwig, Furstenberg, & Magaziner, 2001). Evidence of the reliability and validity of these measures with the current sample has been described in detail elsewhere (Resnick et al., 2006).

Yale Physical Activity Survey (YPAS). The YPAS is an interviewer-administered questionnaire that includes five categories of common types of work, exercise, and recreational activities performed during a typical week. Evidence of reliability and validity has been demonstrated (Dipietro, Caspersen, Ostfeld, & Nadel, 1993; Pescatello, DiPietro, Fargo, Ostfeld, & Nadel, 1994; Resnick & Nigg, 2003). The exercise subscale, which includes moderate exercise activities such as brisk walking, swimming, biking, and calisthenics, was used in these analyses. Total time (hours per week) and estimates of kilocalories were calculated using the assigned metabolic equivalent value reported by Ainsworth (Ainsworth, Haskell, & Whitt, 2000; Dipietro et al., 1993).

Depression. The Geriatric Depression Scale (GDS) was used in BHS-4 to screen older adults for depression (Friedman et al., 2005; Sheikh, Yesavage, Brooks, Friedman, & Gratzinger, 1991; Yesavage et al., 1983), and the Center for Epidemiological Studies Depression Scale (CES-D) was used to assess depressive symptoms in BHS-5 (Radloff, 1977; Turk & Okifuji, 1994). Prior use of these measures provides evidence of the reliability and validity of the CES-D (Bohannon, Maljanian, & Goethe, 2003; Caracciolo & Giaquinto, 2002) and the GDS (Onishi et al., 2006; Radloff, 1977; Torres et al., 2004; Turk & Okifuji).

Data Analysis

Descriptive analyses were done to describe the samples (variable means, standard deviations, frequency, and percentage) 2 months after hip fracture. Model testing was done using structural equation modeling and the Amos statistical program. The sample covariance matrix was used as input and a maximum likelihood solution sought. The chi-square statistic, the normed fit index (NFI), and Steigers root mean square error of approximation (RMSEA) were used to estimate model fit. The larger the probability associated with the chi-square, the better the fit of the model to the data (Bollen, 1989; Loehlin, 1998). Because the chi-square statistic is sample size dependent, the chi-square divided by degrees of freedom (df) was used to control for sample size effects (Bollen). The NFI tests the hypothesized model against a baseline model and should be 1.0 if there is perfect model fit. The NFI is normed so that the values cannot be below 0 or above 1. The RMSEA is a population-based index and consequently is insensitive to sample size. An RMSEA of less than .10 is considered good, and less than 0.05 is very good (Loehlin). Path significance (i.e., significance of the lambda values) was based on the critical ratio (CR), which is the parameter estimate divided by an estimate of the standard error. A CR greater than 2 in absolute value was considered significant (Arbuckle, 1997).

Results

Table 2 provides the descriptive results for the study variables. Hip fracture participants’ mean self-efficacy scores at 2 months after fracture reflected moderate confidence in their ability to exercise, and outcome expectation means reflect a general belief in the benefits of exercise. In BHS-4 the mean fear of falling score 2 months after hip fracture was 2.2 (SD = 1.5). Of these people 50% (N = 74) said they restricted their activity because of their fear of falling. Similarly in BHS-5, the mean fear of falling score was 2.4 (SD = 1.4), and 35% (N = 57) of these people restricted their physical activity because of their fear. In both BHS-4 and BHS-5, 84% of people reported having some pain, and their mean pain score on a scale of 0 to 10 was 4.0 (BHS-4 SD = 2.8, BHS-5 SD = 2.7). Consistently between the two studies older women 2 months after hip fracture rated their health status as low in areas of physical health and function. BHS-4 participants had a mean GDS score of 3.5 (SD = 2.9), and BHS-5 participants had a mean CES-D score of 10.5 (SD = 9.1), indicating low levels of depressive symptoms in both samples. Specifically, 24% of the participants in BHS-4 were noted to be depressed based on a score greater than 5 on the GDS, and 20% of the participants in BHS-5 were noted to be depressed based on a score of greater than 16 on the CES-D.

In BHS-4 full model testing indicated that only four paths were statistically significant, and there was a poor fit of the data to the model, with (chi)2 = 93.4, df = 14, ratio = 6.6, NFI = .76, and RMSEA = .18. A revised model with significant paths only was tested and is shown in Figure 2. Testing of the revised model showed that mental health status ((lambda) = .20, p = .01), age ((lambda) = (-).22, p = .01), and self-efficacy expectations ((lambda) = .54, p = .01) all influenced outcome expectations and explained 38% of the variance. However, self-efficacy expectations for exercise was the only variable to directly influence time spent in exercise activities ((lambda) = .39, p = .01). Together these variables explained 15% of the variance in exercise behavior. The revised model had (chi)2 = 121.9, df = 32, NFI = .69, and RMSEA = .13. The revised model did not result in an improvement in fit ((chi)2 difference of 28.5, df difference of 18, p > .05), indicating that neither the hypothesized model nor the revised model explained exercise behavior in this sample.

In BHS-5, the full hypothesized model indicated that five hypothesized paths were statistically significant, and there was a poor fit of the model to the data ((chi)2 = 151.1, df = 14, ratio = 10.1, NFI = .68, and RMSEA = .22). Testing of the revised model (Figure 3) showed that cognitive status ((lambda) = .30, p = .01) influenced self-efficacy expectations and explained 9% of the variance in self-efficacy expectations. Depressive symptoms ((lambda) = (-).22, p = .01), age ((lambda) = (-).14, p = .05), and self-efficacy expectations ((lambda) = 0.34, p = .01) influenced outcome expectations and explained 19% of the variance in outcome expectations. Self-efficacy ((lambda) = 0.27, p = .01) was the only variable to directly influence exercise behavior, although cognitive status indirectly influenced exercise through self-efficacy expectations. Taken together, these variables explained only 8% of the variance in exercise behavior. The revised model also showed a poor fit of the model to the data ((chi)2 = 197.3, df = 32, ratio = 6.1, NFI = .58, and RMSEA = .16). There was a statistically significant improvement in model fit between the hypothesized and the revised model ((chi)2 difference of 46.2, df difference of 18, p = .01). Despite this improvement, as noted with model testing in BHS-4, neither the hypothesized model nor the revised model explained exercise behavior in this sample.

Discussion

The findings from this report provide information about what women experience after falls and subsequent hip fractures, their level of pain and fear, their mood, and their beliefs in their ability to exercise and in the benefits of exercise. At 2 months after fracture the women from both studies reported moderately high self-efficacy expectations (mean in the range of 6–7 out of 10) and outcome expectations (mean of 4 in a range of 1–5) for exercise. Even after the experience of falling and sustaining a fracture, these women believed that they were capable of exercising and that there was benefit to doing so. Despite the high self-efficacy and outcome expectations reported, the participants from BHS-4 and BHS-5 engaged in only 2 hours or less of exercise per week, or 17 minutes per day before implementation of the exercise intervention. This low level of exercise is similar to that seen in reports of community-dwelling older adults (Kurozawa et al., 2005; Sims, Duffy, & Hilton, 1999) although somewhat lower than in other studies of older adults who consented to participate in exercise intervention studies (Clark et al., 2002; King, Baumann, O’Sullivan, Wilcox, & Castro, 2002).

Consistently across these two samples of women after hip fracture, age and mental status or depressive symptoms influenced outcome expectations such that older women with more depressive symptoms or lower mental health status had weaker outcome expectations for exercise. Cognitive status was noted to influence self-efficacy expectations only in BHS-5 and may be more sample specific. Self-efficacy expectations consistently influenced exercise behavior across both samples. It was also consistent across both models that age, cognitive status, physical and mental health status, pain, fear, outcome expectations, and depressive symptoms did not directly influence exercise behavior at 2 months after hip fracture.

Taken together, the variables in this model explained only a very small amount of the variance in exercise behavior: 15% in BHS-4 and 8% in BHS-5. Although the influence is small, these findings suggest that psychosocial factors have some influence on whether older women after hip fracture will engage in exercise activities. This supports prior work indicating that self-efficacy expectations had the greatest influence on exercise when compared with other psychosocial variables (Conn, Burks, et al., 2003; Cress et al., 2005; King et al., 2000; Sharma, Sargent, & Stacy, 2005; Taylor-Piliae & Frolicher, 2005). The importance of the relationship between self-efficacy expectations and behavior is in the potential impact that self-efficacy–based interventions can have on exercise behavior (Albright et al., 2005; Collins, Lee, Albright, & King, 2004; Gary, 2006; Hicken, Lossing, & Amelli, 2000; Resnick, 2002; Tseng, Jaw, Lin, & Ho, 2003). Interventions include verbal encouragement, reducing barriers such as the unpleasant sensations associated with exercise, providing positive role models, and educating older adults about the benefits of exercise.

It is important to consider the nonsignificant findings in these models because it may not be worthwhile to focus interventions on factors that are less likely to influence exercise behavior. Pain and fear of falling in these women 2 months after hip fracture did not influence self-efficacy expectations or exercise behavior. Prior research has been inconsistent with regard to the impact of fear and pain on exercise behavior. Pain was not noted to influence exercise among a group of adults with chronic fatigue syndrome (Nijs, Vanherberghen, Duquet, & De Meirleir, 2004), nor was pain related to physical activity among older adults with osteoarthritis (Thomas, Pagura, & Kennedy, 2003). Conversely, some studies have noted a relationship between pain and participation in exercise programs (Cooper, Bilbrew, Dubbert, Kerr, & Kirchner, 2001; Damush, Perkins, Mikesky, Roberts, & O’Dea, 2005; Strine, Hootman, Chapman, Okoro, & Balluz, 2005). Specifically, those who reported pain were less motivated to participate in exercise and engaged in less physical activity. Likewise, in some studies fear of falling was noted to be related to mobility and physical activity (Bruce et al., 2002; Martin et al., 2005; Simonsick, Guralnik, & Fried, 1999), whereas in others there was no relationship (Liu-Ambrose, Khan, Eng, Lord, & McKay, 2004; Resnick, Vogel, & Luisi, 2006). Variations may result from the individuals’ interpretations of pain and fear after hip fracture and how these influence exercise behavior. Ongoing research is needed to explore the impact of pain and fear on participation in exercise after hip fracture.

The findings from this report demonstrated a consistent pattern (no statistically significant relationship) with regard to the relationship between outcome expectations and exercise behavior in BHS-4 and BHS-5. In previous studies with healthy community-dwelling older adults, outcome expectations independently influenced exercise behavior (Burton, Shapiro, & German, 1999; Caserta & Gillett, 1998; Jette et al., 1998; O’Connor, Rousseau, & Maki, 2004). However, it is possible that in the early recovery period after hip fracture the participants had strong outcome expectations associated with exercise but were still unwilling to exercise or perceived themselves as unable to exercise. Further along the recovery trajectory, outcome expectations may have a greater influence on exercise behavior in older women.

Understanding what influences human behaviors such as exercise is complex and, as noted by the findings from this study, is not fully explained by the theory of self-efficacy. This theory should be considered in the broader context of social cognitive theory (Bandura, 1977) and even more comprehensively by using a social ecological model (Sallis et al., 2006; Smedley & Syme, 2000). Social cognitive theory, from which the theory of self-efficacy was derived, states that there is a reciprocal relationship among the person, environment, and behavior. Through feedback and reciprocity, a person’s own reality is formed by the interaction of the environment and one’s cognitions. The addition of a social ecological model further helps to elucidate behavior by suggesting that a person’s behavior is affected by a wide sphere of influences: intrapersonal, interpersonal, institutional or organizational, public policy, and the environment. Social ecological models provide an overarching framework or set of theoretical principles for understanding the relationships between diverse personal and environmental factors in human health and illness. Other factors particularly relevant to women 2 months after hip fracture that may influence exercise behavior are the recommendations provided by the woman’s orthopedist or primary healthcare provider, family and other social support, general beliefs about recovery after hip fracture, physical factors such as underlying chronic illnesses, and physiological factors such as anemia or inflammatory factors.

Study Limitations and Future Implications

This study was limited by the small and very selective sample, including mainly Caucasian older women who lived in the community before fracture, ambulated without human assistance, and were free of medical problems that would put them at risk for adverse events when exercising in the home. Moreover, these women all consented to participate in an exercise intervention study and therefore had strong self-efficacy and outcome expectations. The subjective reporting of exercise behavior and bivariate correlations further limit the findings and do not allow us to test the direction of relationships or establish causation. In addition, the study included only a single cross-sectional analysis of the factors that are related to exercise, and these factors may change over the course of the hip fracture recovery trajectory.

Despite these limitations, this report provides a description of older women after hip fracture and identifies factors that are related to exercise behavior and areas where further research may be useful. Generally, 2 months after hip fracture the women reported high outcome expectations for exercise and moderately high self-efficacy expectations (i.e., confidence) related to their ability to exercise, high perceived health status, limited depressive symptoms, and some pain and fear of falling. Self-efficacy was the only variable to consistently directly influence exercise behavior 2 months after hip fracture. Future research will consider these models at 6 and 12 months after hip fracture. This will be critical for understanding the relationship between the initiation of exercise in the early post–hip fracture period (2- to 6-month time period) and the factors that influence adherence to exercise over time (6- to 12-month time period).

We recommend that future work with hip fracture patients move beyond a self-efficacy–based approach to explain exercise and consider the impact of additional factors, such as those guided by a social ecological model. A greater understanding of the factors that influence exercise behavior during the early post–hip fracture period and consideration of the factors that influence adherence to exercise over time are critical to the development of interventions to increase time spent in exercise and overall physical activity and ultimately to ensure optimal recovery for older women after hip fracture.

Acknowledgments

Support for this project was provided by National Institute on Aging grants R37 AG09901, R01-AG18668, R01 AG17082, and the Claude D. Pepper Older Americans Independence Center P60-AG12583. The authors would like to thank Thera-Band Academy for their generous contribution of the Thera-Band® resistive bands used by study participants, hospitals and personnel participating in the Baltimore Hip Studies, and research staff who worked with study patients and their families. The authors also would like to thank the hip fracture patients and their families for volunteering their time and information for this work.

About the Authors

Barbara Resnick, PhD CRNP, is a professor at the University of Maryland School of Nursing. Address correspondence to her at University of Maryland School of Nursing, 655 West Lombard Street, Baltimore, MD 21201 or at barbresnick@aol.com.

Denise Orwig, PhD, is an assistant professor at the University of Maryland School of Medicine.

William Hawkes, PhD, is an assistant professor at the University of Maryland School of Medicine.

Michelle Shardell, PhD, is an assistant professor at the University of Maryland School of Medicine.

Justine Golden, MS, is an academic coordinator at the University of Maryland School of Medicine.

Michele Werner, BS, is a project manager, Baltimore HIP Studies at the University of Maryland School of Medicine.

Sheryl Zimmerman, PhD, is a professor at the University of North Carolina Chapel Hill.

Jay Magaziner, PhD, is a professor at the University of Maryland School of Medicine.

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