Fitness center memberships are on the rise in the USA (17). Though increasing resources are being invested into fitness center memberships, relatively little is known about the sense of motivation toward health self-determinism and how that sense of motivation may relate to levels of resistance training carried out by fitness center participants.
Resistance training can lead to improvements in muscle strength, bone mineral density, and other health benefits (3,14,16,25,28,30). To achieve the benefits of resistance training, national health agencies, including the United States Department of Health and Human Services, American College of Sports Medicine, and American Heart Association, recommend that healthy adults perform 2 or 3 resistance training sessions per week (frequency) for each of the major muscle groups with 8-12 different muscle groups (type) being trained per session for a minimum of 8-12 repetitions per muscle group per session (duration) (1,13,16,27,28,32). The findings of several investigations suggest that the majority of American adults do not meet frequency recommendations by performing resistance training 2 or more times per week (6,7,12). There are many reasons why people may not engage in resistance training such as the high cost of personal equipment, the associated noise, and the space required to accommodate resistance training equipment. The fitness center can hypothetically help alleviate such deterrents to resistance training; however, scarce data exist on the level of resistance training carried out by fitness center participants, and how these levels of resistance training relate to sense of motivation toward health self-determinism.
There is little controversy in the empirical literature concerning the extent to which particular demographic characteristics, especially age, gender, race/ethnicity, income, and education level, are predictive of the amount of aerobic physical activity carried out (31). But although predictors of aerobic physical activity have been well studied, less attention has been directed to investigating the extent to which demographic characteristics of fitness center participants and their sense of motivation to health self-determinism may influence their levels of resistance training. For the general population, some evidence suggests that those persons who are young, male, and highly educated are more likely to report carrying out resistance training activity at least 2 times per week compared to older, female, and less educated counterparts (7, 12). Some evidence suggests that marital status may also be predictive of the amount of resistance training activity carried out (7). Because demographic predictors of resistance training among fitness center participants are not yet well understood, analysis of data collected for this specific purpose can lead to a better understanding of the extent to which demographic predictors of physical activity among the general population are also applicable in the specific context of the fitness center-a setting in which participants have access to resistance training equipment and the intent to exercise. The results of such readily ascertainable analyses can benefit strength training professionals by helping them to succeed in strategizing their motivational plans for the health of their clients.
Sense of motivation toward health behaviors among adults is multifaceted (2). Motivation toward health behavior has previously been defined as a sense of health self-determinism (9, 10). Those persons who are intrinsically motivated to health self-determinism tend to have feelings of competency, control, and a sense of reliance on internal reinforcement for health issues (9). Conversely, those who are extrinsically motivated to health self-determinism do not feel competent or in control of their health issues and instead depend on external reinforcement, such as instructions from health professionals. Intrinsic motivation to health self-determinism is known to be positively associated with beneficial health behaviors such as participation in aerobic physical activity (4, 9, 23). For example, sense of control (an element of intrinsic motivation) was found to be predictive of adherence to a resistance training program among an elderly population (19). To the best of our knowledge, no previous investigations have been conducted to evaluate the extent to which health self-determinism is predictive of resistance training among fitness center participants. It is thus important to study how the sense of motivation toward health behavior relates to resistance training among fitness center participants, such that strength training professionals can optimize plans to sustain and improve the health of their clients.
The fundamental purpose of our study was to investigate the extent to which demographics and health self-determinism were related to resistance training levels among a group of fitness center participants. The second purpose of our investigation was to determine whether self-reported level of resistance training among fitness center participants met nationally established recommendations. This knowledge can be applied by those who work with fitness center participants to better understand factors that influence their clients' resistance training levels so that a healthy lifestyle can be supported and promoted.
Experimental Approach to the Problem
We used a cross-sectional design for this study in which we administered a survey to adult fitness center participants. The survey was designed to elicit information about demographic characteristics of fitness center participants, and their self-reported levels of resistance training and sense of health self-determinism. The survey was designed to be concise and convenient for participants to complete, considering that our target population comprised busy adults to whom exercise is important-most presumably have busy work or school schedules and other possible responsibilities, such as caring for children. Because the profile of the Internet user is similar to that of the fitness center participant (15, 18), participants were recruited via the Internet to complete the online survey. This format permitted busy individuals to respond at their convenience and provided the researchers with access to fitness center participants of varying geographic and demographic characteristics.
The study and consent form were approved by the Institutional Review Boards of Touro University International and The Richard Stockton College of New Jersey and conducted as part of a larger study of the behavior of fitness center participants (20).
Participants were recruited for the study by posted invitations on the Internet over a 3-month time period. The invitation was posted on Internet sites related to physical activity including listservs, newsgroups, and discussion groups such as Goldsgymgroupexercisemembers and Ballysworkoutpartners. We employed nonprobability quota sampling to acquire a comparable number of participants by age and gender and to model a realistic profile of Internet users and fitness center participants (15, 18). Participant recruitment continued until there were at least 38 participants in each of the following 4 categories: men 18-39 years old; men 40-64 years old; women 18-39 years old; women 40-64 years old.
The survey was posted on a secure commercial website (www.keysurvey.com). To protect the privacy of subjects and confidentiality of their responses, participants were identified by an assigned number only; contact e-mail addresses of study participants were not retained. A consent form was posted on the first page of the survey, containing all necessary elements to acquire informed consent to participate in the study including contact information, statement of participant's right to refuse or withdraw from the study at any time by logging off of the site at which the survey was posted, or by closing their Internet browser. Participants were urged to print a copy of the consent form and to retain it for their records. Participants were instructed to move to the next page of the survey only after agreeing to the terms described in the consent form.
To be eligible to participate in our study, participants were required to be between 18 and 64 years of age and living in the USA. Participants were also required to be members of a fitness center for at least the last 3 months and void of any known health problems that would interfere with their normal levels of physical activity.
A total of 185 subjects between 18 and 63 years of age (39.1 ± 11.3 years) participated in the study (men: n = 84, women: n = 101). Participants resided in 33 states with a regional distribution of 33, 13, 21, and 33% from the northeast, mid-west, south, and west regions of the USA, respectively. A majority of participants (n = 157) reported holding postsecondary degrees, whereas 15% (n = 28) had a high-school diploma or less education. The vast majority of participants identified themselves as intrinsically motivated to health self-determinism (n = 168). Of those who identified themselves as extrinsically motivated to health self-determinism, 26% reported holding a high school diploma or less and 29% of that education group were non-Caucasian.
The survey contained 43 items and consisted of the following sections: demographics and height and weight (14 questions); physical activity (8 questions); resistance training (4 questions); health self-determinism (17 questions).
The demographics portion of our survey comprised questions designed to elicit responses about participants' age, gender, race/ethnicity, marital status, income, and education level.
As part of a larger study (20), we measured the self-reported physical activity levels of participants by having them complete Paffenbarger's Physical Activity Questionnaire which included an open-ended survey question to assess participants' self-reported frequency and duration of sports and other recreational activities (21). We used Paffenbarger's Physical Activity Questionnaire because it was known to be a reliable instrument with which to measure physical activity. Reliability studies cited for Paffenbarger's Physical Activity Questionnaire have reported correlation coefficients between 0.34 and −0.73 (21).
We measured self-reported levels of resistance training among participants via questions modeled after the recommendations of national health agencies. Specifically, we asked participants 4 questions to quantify the type, frequency, and duration of resistance training performed in a typical week. Question #1-“In a usual week, how many different weight training exercises do you do (includes chest, shoulder, arm, leg, abdomen, and back)? For example, 3 chest (including bench press), 2 leg, forearm, 1 abdomen, and 1 back = 11.” Question #2-“In a usual week, how many times per week do you do each weight training exercise?” Question #3-“In general, how many repetitions do you do for each weight training exercise?” Question #4-“Have you been weight training for the last 3 months?”
From responses to the 4 resistance training questions, we extracted the total resistance training carried out in units of total repetition-muscle groups per week. Total repetition-muscle groups per week was calculated as a product of the following: type (number of different muscle groups exercised per week); duration (number of repetitions of each different muscle group exercised per day); frequency (number of days per week for each muscle group exercised). We based our determination of whether or not participants met national recommendations for resistance training upon a calculation of total repetition-muscle groups per week. We considered participants to have met national recommendations for resistance training if they carried out a minimum total of 128 repetition-muscle groups per week (8 muscle groups per day × 8 repetitions per muscle group × 2 d·wk−1).
The Health Self-Determinism Index consisted of 17 items on a 5-point Likert-like ordinal scale (8). We summed responses for all items on the Health Self-Determinism Index so as to classify each participant as having either intrinsic or extrinsic motivation toward health self-determinism (8). The reliability of the scale that we used to measure health self-determinism is well established; Cronbach's alpha for the Health Self-Determinism Index has previously been reported to be between 0.64 and 0.87 (8,9,22,24,33). Sample statements on the Health Self-Determinism Index included, “For me, it takes more willpower than I have to do the things that I know are good for my health” and “I worry about my health.”
Descriptive statistics including mean and SD were calculated for age, gender, race/ethnicity, income, education, marital status, health self-determinism, and quantity of resistance training. The Kolmogov-Smirnov test was used to examine skewness of the data. A moderate, positive skew was identified in the data; root mean square transformations of the data were performed for bivariate and multivariate analyses (26). An alpha level of ≤0.05 was established for all inferential statistics performed a priori.
For bivariate analyses, a Pearson correlation coefficient was calculated to measure the association between amount of resistance training carried out by subjects and age. Spearman correlation coefficients were calculated to measure the bivariate associations between resistance training, income, and education. Analyses of variance were conducted to relate self-reported levels of resistance training to marital status. A student's t test was performed to relate resistance training to gender, race/ethnicity, and health self-determinism, as intrinsic or extrinsic motivation. Analyses of covariance were performed to assess the relationship between particular demographic characteristics of respondents, levels of resistance training and sense of health self-determinism, controlling for age. A χ2 test was used to determine whether participants' demographic characteristics and sense of health self-determinism were related to meeting or not meeting recommended levels of resistance training.
The relationship between health self-determinism and age was determined using a student's t test. The relationship between health self-determinism and income and education was determined using a Mann-Whitney U test. The relationships between health self-determinism gender, race/ethnicity and marital status were determined through χ2 analyses.
Stepwise multiple regression analysis was performed to identify any variables predictive of quantity of self-reported resistance training. Logistic regression analysis was then performed to determine whether the aforementioned characteristics of participants were predictive of the likelihood of subjects to meet national resistance training recommendations (1,3,16,27,28,32). We also performed logistic regression analyses to determine whether demographic characteristics were predictive of intrinsic vs. extrinsic sense of motivation toward health self-determinism. When conducting regression analyses, an assessment was made of the level of intercorrelation among independent variables. Collinearity tolerance levels exceeded 0.1, revealing a lack of multicollinearity among predictors (26).
The majority of subjects met national resistance training recommendations; the model of demographic and health self-determinism predicted the reported levels of resistance training with health self-determinism significantly contributing to the model.
The total duration of participation in a resistance training program varied widely among subjects from 0 to 30 years (7.7 ± 7.8 years). Among study participants, resistance training was the most frequently cited recreational, sports, or other activity (57%), representing 26% of their total self-reported activity. The overall range of self-reported resistance training levels reported was from 0 up to 6, 678 repetition-muscle group per week (589 ± 976 repetition-muscle group per week); 16% of participants reported that they did not carry out any resistance training whatsoever.
Bivariate analysis revealed participants intrinsically motivated to health self-determinism performed significantly more resistance training than extrinsically motivated participants (t(183) = −2.49, p = 0.01). Resistance training was not significantly correlated to age (r = 0.104, p = 0.080); gender (t(183) = 0.046, p = 0.963); marital status (F(3, 181) = 0.407, p = 0.748); income (rs = 0.087, p = 0.119); level of education (rs = 0.105, p = 0.077). Participants of non-Caucasian race/ethnicity reported having carried out 18% more resistance training than Caucasian participants; however, the difference was not statistically significant (t(183) = −0.037, p = 0.971).
When adjusting for age, participants who were intrinsically motivated to health self-determinism (Adjusted Mean = 20.60) performed significantly more resistance training compared to participants who were extrinsically motivated to health self-determinism (p = 0.010) (Adjusted Mean = 9.39). When adjusting for age, there were no significant association between demographic characteristics of study participants (gender, race/ethnicity, marital status, income, and education level) and reported quantity of resistance training.
For the majority of participants (68%), the self-reported levels of resistance training were sufficient to meet recommended levels of at least 128 repetition-muscle groups per week. The age of participants was unrelated to the likelihood of their meeting recommended levels of resistance training (t(183) = −1.20, p = 0.231). The results of bivariate analyses in which the relationships between various demographic and health self-deterministic characteristics of subjects were related to the likelihood that their levels of resistance training would meet recommendations are summarized in Table 1. No significant associations were detected between demographic characteristics of study participants and the likelihood that they would meet recommended levels of resistance training. By contrast, motivation toward health self-determinism was related to the likelihood that participants would meet recommended levels of resistance training. Specifically, participants who were extrinsically motivated to health self-determinism were significantly less likely to meet resistance training recommendations compared to participants who were intrinsically motivated to health self-determinism (p = 0.002).
Stepwise multiple regression analysis for the model of demographics and health self-determinism revealed that sense of health self-determinism indeed explained a small, but significant proportion of the variance in reported levels of resistance training (R2 = 0.033, F 6.199 [1, 183], p = 0.014). None of the demographic characteristics of study participants were predictive of quantity of reported resistance training.
Logistic regression analyses revealed that demographic characteristics of study participants (age, gender, race/ethnicity, marital status, income, and education level) were not predictive of the likelihood to carry out recommended levels of resistance training (Table 2). By contrast, the logistic regression analyses revealed that the sense of health self-determinism of participants was significantly predictive of the likelihood of participants to meet recommended levels of resistance training. The overall model, which included demographics and health self-determinism, did not significantly distinguish between meeting or not meeting recommendations, χ2 = 13.117 (7), p = 0.069.
Those participants extrinsically motivated to health self-determinism tended to be younger (age = 34.1 ± 12.5 years) than those intrinsically motivated to health self-determinism (age = 39.7 ± 11.1 years) (t(183) = −1.974, p = 0.050). Intrinsically motivated participants tended to have a higher level of education than those extrinsically motivated (Mann-Whitney U, U = 907.000, p = 0.008) and reported having lower annual income than those intrinsically motivated (Mann-Whitney U, U = 930.000, p = 0.014). Having an education level of high-school diploma or less was only slightly, but significantly, predictive of the likelihood that a study participant would be extrinsically motivated toward health self-determinism (OR = 0.286, 95% confidence interval = 0.110-0.747, p = 0.011).
We found that the sense of motivation toward health self-determinism of study participants was predictive of the likelihood that they would meet national guidelines for resistance exercise. Our findings indicated that the overall self-reported levels of resistance training among most members of this sample of fitness center participants was sufficient to meet national recommendations for resistance training. Many subjects reported having made a long-term commitment to this activity. Yet, approximately one-third of participants in our present study reported that they either carry out no resistance training whatsoever, or they carry out inadequate levels of resistance training to meet national recommendations.
Demographics (age, gender, race/ethnicity, education, income, and marital status) were not predictive of the resistance training reported by our study participants. Presumably, fitness center participants are not deterred by certain barriers to exercise, such as lack of access or heightened self-consciousness about being seen while exercising; removal of such barriers (inherent to the fitness center experience) may partially explain the lack of influence of demographic characteristics upon resistance training behavior among this group.
In the current study, participants with an intrinsic sense of motivation to health self-determinism were more likely than their extrinsically motivated counterparts to carry out higher levels of resistance training and to meet national recommendations for resistance exercise. Also, having a high-school education or less was the only demographic characteristic predictive of whether subjects were extrinsically motivated toward health self-determinism. It should be noted that sense of health determinism is commonly studied in the health sciences literature, but it has been less widely examined as a predictor of resistance training. To the best of our knowledge, ours was the first study of fitness center participants to specifically investigate which combination of demographic characteristics and sense of health self-determinism among subjects might predict levels of resistance training. For those fitness center participants who are extrinsically motivated, the components of health self-determinism may hold a key to strategies for intervention to improve resistance training activity. For example, there is likely a need to specifically address external reinforcement on health issues, lack of perceived competency in health matters, and reliance on others for health care decision making and health actions among extrinsically motivated fitness center participants (9, 10).
Because health self-determinism only accounted for a small proportion of the variance in resistance training in our study, other factors may contribute to why fitness center participants tend to be motivated or unmotivated to engage in resistance training. For example, Trost et al. (12) suggested that social influence, satisfaction with the facility, and time for exercise may all be relevant factors for predicting aerobic physical activity (31) and may also be relevant factors for resistance training.
By employing resistance training questions that were modeled after health agency recommendations, we were able to quantitatively assess subjects' self-reported quantities of resistance training to the recommended level of 128 muscle-group repetitions per week. Previous studies have elucidated the frequency of resistance training but omitted the other component (type and duration) of national recommendations for resistance training (5-7, 12). By virtue of inclusion of resistance training questions on a health self-determinism questionnaire, the survey instrument that we employed for our study could easily be used in the future to assess the likelihood of an individual to meet such recommendations for resistance training, based on his or her self-reported sense of motivation toward health behaviors.
In this section, we address limitations of our study. First, we could not calculate a true response rate to our survey because of the open-ended nature of the invitation to participate in the study over the Internet (11). We were able to access participants from all regions with a regional distribution of United States fitness center membership being 19, 23, 30, and 28% for the northeast, mid-west, south, and west regions, respectively (18). Second, participants in our study were self-selected to participate in our study. Third, there is a potential for misclassification bias by virtue of the self-reported nature of data collection. For example, a highly motivated participant may overestimate his or her true level of resistance training (11). There is also the potential for social desirability bias in our study. For example, subjects may tend to overstate their true levels of resistance training to please the researchers. A fourth limitation to our approach was that participants self-reported their levels of resistance training. We did not measure the levels of resistance training of study participants directly. Indeed, the results of previous investigations have suggested that participants tend to overestimate their levels of physical activity through self-reports (29). It should be noted that any potential overestimates of self-reported resistance training may have been offset by the exclusion of everyday resistive activities from our data collection instrument. Indeed, empirical evidence suggests that resistive activities may be carried out as part of a person's work environment or daily living activities (12). In addition, we reported race/ethnicity only in terms of Caucasian vs. non-Caucasian.
There are various other possible explanations as to why fitness center participants tend to carry out varying levels of resistance training that we did not measure in our study. For example, fitness center participants who work out with a personal trainer may tend to carry out higher levels of resistance training compared to their counterparts who do not work out with a personal trainer. There may also be various other characteristics of particular fitness centers that influence whether or not participants engage in resistance training. For example, there may be a preference among participants to accomplish resistance training through either free weights, resistance training machines, or some mixture. We also did not assess particular characteristics of fitness centers, such as cost or membership size. Thus, we were unable to assess whether or not such factors impacted the motivation of fitness center participants that could ultimately affect external validity of the findings.
This investigation adds to the body of knowledge in the emerging study of resistance training and the understudied fitness center population by identifying that the majority of participants report meeting national recommendations for resistance training. We have also discovered that demographic characteristics of fitness center participants are not necessarily predictive of the levels of resistance training carried out. We found that sense of motivation toward health self-determinism is a significant predictor of whether subjects meet national resistance training recommendations. We have demonstrated the utility of an Internet-based health questionnaire to investigate patterns of resistance training behavior.
Most participants in our study reported carrying out sufficient quantities of resistance training to meet national recommendations. Notably, however, approximately one-third of participants in our study did not. By contrast to the findings of many previous investigations among the general population in which demographic characteristics of subjects were significantly related to quantity of physical activity carried out (31), subjects in our study who were older, female, less educated, non-Caucasian, and of lower income, were no less likely than their counterparts to carry out resistance training. Thus, strength training professionals will note that factors such as age, gender, ethnicity, income, and education level do not preclude fitness center participants from carrying out satisfactory amounts of resistance training.
Sense of motivation to health self-determinism indeed predicted the extent to which fitness center participants would carry out adequate quantities of resistance training. Strength training professionals may wish to focus on early identification of participants who are extrinsically motivated to health self-determinism and are thus less likely to carry out adequate quantities of resistance training. The survey employed in this study can easily be administered either at the gym or online to identify extrinsically motivated fitness center participants. We also found that participants with a high-school education or less were more likely to be extrinsically motivated. Thus, it is important that any written materials that are designed to motivate fitness center participants be presented in such a manner that is understandable. The wording of advertisements, instructional handouts, and marketing campaigns should be geared at an appropriate reading level in fitness centers. Efforts should be placed on heightening the sense of motivation among those fitness center participants who do not currently carry out sufficient quantities of resistance training; previous empirical research suggests that this can be achieved by encouraging heightened feelings of competency and control (9). From a practical standpoint, support and encouragement by a personal trainer may be particularly effective at encouraging those in need of heightened motivation. For example, by working with a personal trainer to master fitness equipment, participants may achieve heightened sense of competency and control.
The fact that fitness center participants may be strongly motivated intrinsically toward health self-determinism suggests that they might also be receptive to various other supplementary forms of health improvement beyond resistance training.
This study was partially funded through Research and Professional Development Funds and Graduate Assistantships from The Richard Stockton College of New Jersey. The authors acknowledge Dr. Afrooz Afghani and Dr. Mickey Shachar for their assistance throughout the project; Dr. Richard Kathrins for technical assistance; Richard Stockton College of New Jersey for financial support toward the project.
1. American College of Sports Medicine. Guidelines for Exercise Testing and Prescription
. Philadelphia, PA: Lippincott, Williams and Wilkins, 2006.
2. Bouchard, C, Shephard, RJ, and Stephens, T. Physical Activity, Fitness, and Health Consensus Statement
.Champaign, IL: Human Kinetics, 1993.
3. Braith, RW and Stewart, KJ. Resistance exercise training its role in the prevention of cardiovascular disease. Circulation
113: 2642-2650, 2006.
4. Carter, KF and Kulbok, PA. Motivation for health behaviours: A systematic review of the nursing literature. J Adv Nurs
40: 316-330, 2002.
5. Centers for Disease Control and Prevention. Youth risk behavior surveillance: National college health risk behavior survey-U.S., 1995. MMWR Morb Wkly Rep
46: 1-54, 1997.
6. Centers for Disease Control and Prevention. Trends in strength training-United States, 1998-2004. MMWR Morb Mortal Wkly Rep
55: 769-772, 2006.
7. Chevan, J. Demographic determinants of participating in strength training activities among U.S. adults. J Strength Cond Res
22: 553-558, 2008.
8. Cox, CL. The health self-determinism index. Nurs Res
34: 177-183, 1985.
9. Cox, CL, Miller, EH, and Mull, CS. Motivation in health behavior: Measurement, antecedents, and correlations. Adv Nurs Sci
9: 1-15, 1987.
10. Deci, E. Intrinsic Motivation
. New York, NY: Plenum Press, 1975.
11. Eysenbach, G and Wyatt, J. Using the internet for surveys and health research. J Med Internet Res
4, e3-13, 2002. Available at: http://www.jmir.org/2002/2/e13/
. Accessed May 5, 2005.
12. Galuska, DA, Earle, D, and Fulton, JE. The epidemiology of U.S. adults who regularly engage in resistance training. Res Q Exerc Sport
73: 330-334, 2002.
13. Haas, CJ, Feigenbaum, MS, and Franklin, BA. Prescription of resistance training for healthy populations. Sport Med
31: 953-964, 2001.
14. Hamdy, RC, Anderson, JS, Whalten, KE, and Harvill, LM. Regional differences in bone density of young men involved in different exercises. Med Sci Sports Exerc
7: 884-888, 1994.
15. Harris. The Harris Poll, 40, 2005, May 12, 2005. Available at: http://www.harrisinteractive.com/harris_poll/index.asp?PID=569
. Accessed May 21, 2005.
16. Haskell, WL, Lee, IM, Pate, RR, Powell, KE, Blaire, SN, Franklin, BA, Macera, CA, Heath, GW, Thompson, PD, and Bauman, A. Physical activity and public health: Updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc
39: 1423-1434, 2007.
17. International Health, Racquet, and Sportsclub Association. 2004 International Health, Racquet, and Sportsclub Association/Sports Data Health Club Trend Report. Available at: http://www.getactivemagazine.com/index.cfm/fuseaction/page.viewpage/pageid/11044
. Accessed January 8, 2009.
18. International Health, Racquet, and Sportsclub Association. 2006 Profiles of Success. Available at: http://cms.ihrsa.org/index.cfm?fuseaction=Page.viewPage&pageId=18420&nodeID=15
. Accessed January 8, 2009.
19. Jette, AM, Rooks, D, Lackman, M, Lin, TH, Levenson, C, Heislein, D, Girgetti, MM, Harris, BA. Home-based resistance training: Predictors of participation and adherence. Gerontologist
38: 412-421, 1998.
20. Kathrins, B. The relationship between physical activity, demographics and health self-determinism among fitness center participants. Dissertation, Touro University International, Cypress, CA, 2007.
21. Kriska, AM and Caspersen, CJ. A collection of physical activity questionnaires for health-related research. Med Sci Sports Exerc
29 (Suppl.): 83-88, 1997.
22. Loeb, SJ, O'Neill, J, and Gueldner, SH. Health motivation: A determinant of older adults' attendance at health promotion programs. J Comm Health Nurs
18: 151-165, 2001.
23. Lucas, IA, Orsham, SA, and Cook, F. Determinant of health-promoting behavior among women ages 65 and above living in the community. Sch Inq Nurs Pract Intl J
14: 77-109, 2000.
24. MacLeod, P and Stewart, NJ. Predictors of participation in a peer-led exercise program for senior women. Can J Nurs Res
26: 13-25, 1994.
25. Menkes, A, Mazel, S, Redmond, RA, Koffler, K, Libanati, CR, Gundberg, CM, Zizic, TM, Hagberg, JM, Pratley, RE, and Hurley, BF. Strength training increases regional bone mineral density and bone remodeling in middle-aged and older men. J Appl Physiol
74: 2478-2484, 1993.
26. Mertler, CA and Vannatta, RA. Advanced and Multivariate Statistical Methods (2nd ed.). Los Angeles, CA: Pyrczak, Publishing, 2002.
27. Pollock, ML, Franklin, BA, Balady, GJ, Chaitman, BL, Fleg, JL, Fletcher, B, Limacher, M, Pina, IL, Stein, RA, Williams, M, and Bazzarre, T. Resistance exercise in individuals with and without cardiovascular disease. Benefits, rationale, safety, and prescription. An advisory from the committee on exercise, rehabilitation, and prevention, council on clinical cardiology, American Heart Association. Circulation
101: 828-833, 2000.
28. Pollock, ML, Gaesser, GA, Butcher, JD, Despres, JP, Dishman, RK, Franklin, BA, and Garber, CE. The recommended quantity and quality of exercise for developing and maintaining cardiorespiratory and muscle fitness, and flexibility in healthy adults. Med Sci Sports Exerc
30: 975-991, 1998.
29. Sallis, JF and Saelens, BE. Assessment of physical activity by self-report: Status, limitations, and future directions. Res Q Exerc Sport
71: 1-15, 2000.
30. Smutok, MA, Reece, C, Kokkinos, PF, Famer, C, Dawson, P, Shulman, R, Devane-Bell, J, Patterson, J, Charabogos, C, Goldberg, AP, and Hurley, BF. Aerobic versus strength training for risk factor intervention in middle-aged men at high risk for coronary heart disease. Metabolism
42: 177-184, 1993.
31. Trost, SG, Owen, N, Bauman, AE, Sallis, JF, and Brown, W. Correlates of adults' participation in physical activity: Review and update. Med Sci Sports Exerc
34: 1996-2001, 2002.
32. United States Department of Health and Human Services. 2008 Physical Activity Guidelines for Americans. 2008. Available at: www.health.gov/paguidelines
. Accessed January 9, 2009.
33. Wilbur, J, Miller, AM, Chandler, P, and McDevitt, J. Determinants of physical activity and adherence to a 24-week home-based walking program in African American and Caucasian women. Res Nurs Health
26: 213-224, 2003.