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Original Investigation |

Counseling for Home-Based Walking and Strength Exercise in Older Primary Care Patients FREE

Patricia M. Dubbert, PhD; Miriam C. Morey, PhD; Kent A. Kirchner, MD; Edward F. Meydrech, PhD; Karen Grothe, PhD
[+] Author Affiliations

Author Affiliations: G. V. (Sonny) Montgomery Veterans Affairs Medical Center (Drs Dubbert, Kirchner, and Grothe); Departments of Psychiatry (Drs Dubbert and Grothe), Medicine (Drs Dubbert, Kirchner, and Grothe), and Preventive Medicine (Dr Meydrech), University of Mississippi School of Medicine, Jackson; and Durham Veterans Affairs Medical Center and Duke University Medical Center, Durham, North Carolina (Dr Morey).


Arch Intern Med. 2008;168(9):979-986. doi:10.1001/archinte.168.9.979.
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Published online

Background  We evaluated the effects of counseling linked with primary care visits on walking and “strength exercise” (the combination of strength-building and flexibility exercise) in aging veterans.

Methods  Male veterans aged 60 to 85 years (N = 224) with physical function limitations were randomized to either counseling for home-based walking and strength exercise (EXC) or discussion of their choice of health education topics (EDUC) with a nurse at baseline, 1 month, and 5 months. The EXC participants recorded exercise on monthly calendars and received brief follow-up calls from the nurse; all participants received bimonthly newsletters throughout the 10-month trial.

Results  Retention was 83% in the EXC group and 97% in the EDUC group (P < .001). With analyses using the last observation carried forward approach, the EXC participants reported more walking time per week at 5 and 10 months (64.5 and 60.6 min/wk, respectively, for the EXC group vs 50.5 and 45.7 min/wk, respectively, for the EDUC group; 2.4 d/wk and 2.3 d/wk, respectively, for the EXC group vs 1.8 and 1.7 d/wk, respectively, for the EDUC group) (P < .001). The EXC participants also reported more strength exercise at 5 and 10 months (44.6 and 41.2 min/wk, respectively, for the EXC group vs 19.8 and 14.7 min/wk, respectively, for the EDUC group; 2.1 and 2.0 d/wk, respectively, for the EXC group vs 0.8 and 0.8 d/wk, respectively, for the EDUC group) (P < .001). The EXC participants reported more frequent moderate- or higher-intensity physical activity (7.1 vs 5.1 sessions/wk) (P < .001). Findings from accelerometer-measured physical activity indicated more EXC than EDUC participants (64% vs 46%), who averaged 30 min/d or more of moderate- or higher-intensity physical activity (P = .03). Participants engaging in strength exercise improved physical performance and reported positive changes in quality of life.

Conclusion  Relatively brief counseling linked with primary care visits can increase home-based walking and strength exercise in aging male veterans.

Trial Registration  clinicaltrials.gov Identifier: NCT00013195

Figures in this Article

In a previous study, we found that clinical and telephone counseling by a nurse case manager increased the frequency of walking for exercise in aging veteran primary care patients.1 Although walking is a popular and safe endurance exercise, strength-building exercises are also an important component of the exercise recommendation for older adults.2,3 There have been few studies of interventions to promote adoption of home-based strength-building exercise, and a recent review found the results of the existing trials to be inconclusive.4 At the time the present study was initiated, we were unaware of any trial evaluating counseling for a combination of walking and strength-building exercise in aging primary carepatients.

The National Institute on Aging (NIA) has developed attractive instructional materials (available in booklet, video, and Internet media) to promote healthy endurance and strength-building exercise for people older than 50 years.5 We believed that nurses and physical therapy staff could use these materials in counseling associated with primary care visits to promote walking and strength-building exercises. This clinical trial was designed to evaluate the effects of counseling based on the NIA materials delivered through 3 clinic visits, 2 to 3 contacts by telephone, motivational automated calls, and newsletters. The primary objective was to evaluate the effects of counseling on adherence to the prescribed walking and “strength exercise” (the combination of strength-building and flexibility exercises). Additional measures were included to assess objectively measured physical activity, overall physical activity, changes in physical performance, perceived quality of life associated with adherence, and costs of providing the interventions.

DESIGN

In a prospective experimental design, veterans enrolled in primary care clinics were recruited and randomly assigned to either (1) counseling for home-based walking plus strength exercise targeting functional limitations (EXC) or (2) discussion of their choice of health education topics (EDUC) (control). This study was conducted at the Department of Veterans Affairs Medical Center (VAMC) in Jackson, Mississippi, and was reviewed and approved by the VAMC institutional review board and the research and development committee.

PARTICIPANTS

Male veterans (N = 224) were recruited from VAMC primary care clinics, with 120 randomized to the EXC group and 104 to the EDUC group. (The EXC participants were randomized in a 2:1 ratio during the last 8 months of recruiting to ensure meeting the goal of 120 for this group.) Approximately 55% of each group initiated intervention in the spring or summer. Inclusion criteria included the following: aged 60 to 85 years; noninstitutionalized; referred by a primary care provider; completed a 6-minute walk with no more than 1 stop; current moderate-intensity walking 3 times per week or less or for less than 15 min/wk and strength training once a week or less; and at least 1 response indicating limitation on the 35-Item Short Form Health Survey (SF-36) physical function scale6 or performance below the 25th percentile on one of the physical performance tests.7 Participants with conditions that could make unsupervised exercise unsafe such as uncontrolled arrhythmias or diabetes were excluded using criteria from our previous trial.1 Recruiting began in November 2002, and data collection was completed in February 2006.

MEASURES

Measures were administered by a data collector blinded to intervention assignment and, unless specified otherwise, conducted at baseline, 5 months, and 10 months after randomization.

Health Status and Demographic Characteristics

At baseline, we used the adaptation by Deyo et al8 of the Charlson Comorbidity Index9 as a standardized measure of health status. Demographic information (including race) was obtained by self-reported questionnaire; health history was assessed by interview and medical record. Body mass index was calculated as the patient's clinic body weight in kilograms divided by the self-reported height in meters squared.

Physical Activity and Exercise Behavior

Using a timeline follow-back procedure, we asked participants to recall how many minutes they walked for exercise and how many minutes they spent engaged in strength and/or flexibility exercises for each of the past 7 days. In our previous study,1,10 minutes walking was correlated with exercise diaries (r = 0.93) and with accelerometer-measured physical activity (rs = 0.53). To assess participation in a variety of physical activities for the previous 4 weeks, we also administered the 42-item Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire.11 In the present study, minutes walking per week and minutes per week of strength exercise were correlated with the CHAMPS walking (rs = 0.40) and strength (rs = 0.53) items, respectively.

Objectively Monitored Physical Activity and Physical Performance

Before either the 5- or 10-month follow-up assessment visit (randomly determined), RT3 triaxial accelerometers (Stayhealthy Inc, Monrovia, California) were mailed to participants to be worn for at least 3 full days while awake. Using a cut point for older men of 984 activity counts/min or greater, we estimated how many minutes per day the participants engaged in at least moderate-intensity physical activity.12

Tests used to assess physical performance included the 6-minute walk, 30-second chair stand, arm curls with an 8-lb (3.6-kg) dumbbell, and an 8-ft (2.4-m) up-and-go test.7,13 We also assessed usual gait speed by having participants walk at their normal pace across a 10-m course.14

Quality of Life, Falls and Injuries, Estimation of Costs

The 36 items of the SF-366 instrument comprise 8 scales measuring physical function, role limitations due to physical functioning, bodily pain, general health perceptions, vitality, social functioning, role limitations due to emotional problems, and mental health. Falls, injuries, and illness episodes were ascertained from interviews with participants and notations on mail-back forms. Perceptions of muscle soreness were obtained on a 4-point scale.15 Costs were estimated from logs of interventionist time for counseling visits and expenditures for materials distributed to EXC participants. Decision support system16 estimates of total VAMC health care costs were extracted on a participant-specific basis for the year following randomization.

PROCEDURES

Potential participants were identified by primary care providers, prescreened by telephone, and scheduled for a research visit. After obtaining informed consent, research staff completed baseline assessments. Participants were given a break and light refreshments, while the nurse confirmed eligibility and opened the computer-generated randomization assignment. Interventions for both groups were delivered by study staff located near primary care clinics. The intervention summary is given in Table 1.

EXC Intervention

The EXC intervention, based on social cognitive theory and modeled after the Activity Counseling Trial of physical activity promotion in primary care settings,17 was closely linked to the NIA exercise workbook, Exercise: A Guide From the National Institute on Aging.5 The walking program goal was 20 minutes or more for 3 to 5 times per week by the 5-month visit. Participants who reached the 20-minute goal were encouraged to increase the time to 30 minutes. At baseline, up to 3 strength and flexibility exercises were selected from the NIA workbook for their potential to address participants' specific functional limitations, with the goal to perform the exercises on 2 nonconsecutive days per week. (The combination of strength building and flexibility exercises in this report is referred to as “strength exercise.”) At the 1-month follow-up visit, interventionists checked progress, negotiated new walking goals, and typically added up to 5 new exercises from the NIA workbook. Dumbbells up to 8 lb (3.6 kg) and ankle weights up to 5 lb (2.25 kg) were distributed. The 5-month final intervention visit emphasized relapse prevention and using the NIA workbook more independently. The EXC participants were given 1-page monthly exercise calendar forms for recording walking and strength exercise. The nurse initiated 3- to 5-minute problem-solving telephone contacts with EXC participants approximately 1 week after intervention visits. The EXC participants also received brief automated motivational messages (eg, “This is the exercise program research nurse reminding you to do your exercises and drink plenty of fluid in the heat” [or] “dress in layers for the weather”) delivered by a Phone Tree (Personal Communication Systems, Winston-Salem, North Carolina) on a random schedule every 3 to 4 weeks throughout the 10-month study.

EDUC Intervention

The EDUC participants selected NIA “Age Page” brochures to discuss with the nurse. If they chose “Exercise,” advice was limited to the brochure's summary of current health recommendations without specific goal-setting, instructions, or equipment. Both groups received fall prevention safety brochures and bimonthly newsletters that included a survey for reporting adverse events. Participants received $25 for each completed research visit and could earn $10 for returning all mail-back forms.

DATA COLLECTION AND STATISTICAL ANALYSES

Sample size was determined using data from our previous study, indicating 100 participants per group would provide a power of greater than 90% to detect 10-month follow-up differences of 30 minutes or 1.5 days of walking per week between groups. Assuming a 20% dropout rate in each group, we planned to recruit 120 participants per group.

The data collector correctly classified 51% of EDU and 49% of EXC participants, indicating successful masking of intervention assignment. Primary analyses included participants who attended the 10-month follow-up visit (observed cases). In sensitivity analyses, missing data were substituted by the last observation carried forward (LOCF) method. Distributions of outcome variables were not normal. Group and time effects for weekly exercise and CHAMPS measures were evaluated using repeated-measures multivariate analysis of variance (ANOVA) on log and square root transformed values, respectively. In planned post hoc comparisons, we used the nonparametric Wilcoxon 2-sample signed rank test to compare groups on 10-month physical performance and quality-of-life changes based on strength exercise participation. Analyses were conducted using 2-tailed tests, and P < .05 was considered statistically significant.

PARTICIPANT CHARACTERISTICS

Figure 1 shows the participant flow through the study. A total of 39% of participants referred for the study were randomized. Most exclusions were for lack of interest (41%) or being too physically active (26%). Attrition was greater for the EXC (18%) than the EDUC (3%) group (χ2 = 12.44; P < .001). There were 6 medical exclusions for the EXC group and 1 medical exclusion for the EDUC group during follow-up.

Place holder to copy figure label and caption
Figure 1.

Participant flow through the study. EDUC indicates discussion of the participants' choice of health education topics; EXC, counseling for home-based walking and strength exercise.

Graphic Jump Location

The EXC and EDUC groups were not different as randomized at baseline (Table 2). Participants reported a mean of 5.8 functional limitations on the SF-36 physical function scale (most frequent were climbing stairs, walking, or bending/kneeling/stooping). Performance was below normal for 72% of participants in chair stands, 70% in the up-and-go test, 57% in the 6-minute walk, and 31% in arm curls. In both groups, scores for Charlson comorbidity were 0 for 48% and 3 or greater for only 6%. The majority of participants (78% of the EDUC group and 86% of the EXC group) were overweight or obese (body mass index ≥25).

Table Graphic Jump LocationTable 2. Baseline Characteristics of the Intention-to-Treat Participant Sample

Most participants engaged in little or no walking or strength exercise at baseline. Noncompleters had low physical performance and were very inactive at baseline (Table 2).

INTERVENTION CHARACTERISTICS AND COSTS

The EXC participants had more counseling time and contacts than the EDUC participants (Table 1). The most frequently prescribed exercises were chair stands, arm raises, arm curls, plantar flexion, triceps extension, knee extension, and calf stretches. Costs per EXC participant were $7 for NIA workbooks and $14 for dumbbells and ankle weights. The most popular EDUC topics were high blood pressure (54%), arthritis (51%), sleep (34%), foot care (33%), prostate health (33%), and exercise (31%).

CHANGES IN EXERCISE BEHAVIOR

Analyses using both observed cases and the LOCF approach showed similar patterns of results. MultivariateANOVA showed a significant group × time interaction for past-7-day walking and strength exercise variables (P < .001) (Table 3). The findings from follow-up ANOVAs indicated that both groups reported increased walking and strength exercise, but the increases were greater in the EXC group for all primary measures (Table 3). Figure 1 and Figure 2 show increases in exercise at 5 months that were maintained through 10 months. Findings from multivariate ANOVA also showed a significant group × time interaction for the CHAMPS measures (P < .001), which follow-up ANOVAs revealed was due to greater physical activity frequency in the EXC group (Table 3).

Place holder to copy figure label and caption
Figure 2.

Total weekly walking (A) and strength exercise (B) times by group (last observation carried forward for missing values). EDUC indicates discussion of the participants' choice of health education topics; EXC, counseling for home-based walking and strength exercise.

Graphic Jump Location
Table Graphic Jump LocationTable 3. Effects of the Interventions on Exercise Behaviors
ACCELEROMETER ACTIVITY AND PHYSICAL PERFORMANCE

Usable RT3 data were obtained from 178 of the participants (88 EDUC and 90 EXC participants). There were no significant differences between the groups for 3-day means (SDs) of total minutes of activity or total minutes of moderate- or higher-intensity activity (42.5 [33.8] for the EDUC group vs 46.8 [36.2] for the EXC group). However, 64% of EXC and only 46% of EDUC participants with data at the 10-month follow-up averaged at least 30 min/d of moderate to vigorous physical activity (χ2 = 4.17; P = .03).

Changes in physical performance for observed cases were significantly greater for the EXC group on several measures (Table 4), and the LOCF results were consistent with those for observed cases. The differences did not reach significance for the LOCF results.

Table Graphic Jump LocationTable 4. Physical Performance Changes at 10 Monthsa
CORRELATES OF EXERCISE PARTICIPATION ANALYSES

In planned post hoc analyses, we combined participants from the EXC and EDUC groups and categorized them according to their responses on walking and strength exerciseCHAMPS18 items at the 10-month follow-up visit. Differences were most striking for comparisons based on strength exercise. Table 5 shows that the participants (63% of the EXC and 15% of the EDUC group) who reported strength exercise during the past 4 weeks demonstrated improved physical performance and quality of life.

Table Graphic Jump LocationTable 5. Physical Performance and Quality of Life Changes for Participants by Self-Reported Strength Exercise
ADVERSE EVENTS AND HEALTH CARE COSTS

Falls with injury were reported by 14 EDUC and 4 EXC participants (χ22 = 6.24; P = .04). Mean (SD) muscle soreness ratings were not different but increased slightly over time (1.4 [0.7] to 1.6 [0.8]) in both groups, remaining in the “no” to “slightly sore” range. Mean annual VA decision support system costs per participant for EDUC and EXC differed by less than $100 (P = .79).

This study extends the literature supporting the benefits of exercise counseling in a primary care setting by evaluating counseling for combined home-based walking and strength and flexibility exercise. The mean baseline physical performance test scores for this sample were lower than the reported national average.7 Counseling in the EXC group produced greater increases in weekly frequency and minutes of walking and strength exercises and more frequent physical activity. The magnitude of change in overall and moderate-intensity physical activity reported by the EXC participants was similar to participants completing theCHAMPS II program for older adults.19 Participants who engaged in strength exercise, compared with those who reported none, had significantly greater improvements in physical performance and quality-of-life measures, supporting the value of strength and flexibility exercise as recently recommended for this age group.2 Self-reported gains in physical function were of a magnitude (>6 points) that is considered clinically meaningful and similar to the gains observed following a total hip arthroplasty or heart valve replacement surgery; a comparable loss in physical function is associated with an increased long-term mortality risk.20

In addition to the novel combination of home-based walking and strength exercise counseling, the strengths of this study included the simplicity and relatively low cost of the intervention. The exercise counseling intervention used materials available without Internet cost, did not require highly trained exercise professionals, and was designed for implementation in primary care settings.

The difference in attrition between groups was greater than expected. Other recent trials have similarly observed greater dropout in intervention conditions requiring more effort21,22 or for follow-up visits that involved physical performance testing.23 Noncompleters had low physical performance at baseline, suggesting the need for special attention for such participants in exercise promotion programs.

Although none of the adverse events were directly attributed to the EXC intervention, increased physical activity (and associated fatigue) could possibly have contributed to the exacerbations of joint disease and accidents. There was no evidence of exercise producing an increase in health care costs or falls (most of the falls were reported in the EDUC group).

Accelerometer measures did not indicate differences between the 2 groups for mean time spent in moderate physical activity. We can speculate that this might in part be because the RT3 instrument was not sensitive to strength-training activities. This finding could also be consistent with studies indicating that older adults may compensate for exercise with a decrease in other activities.24 We did not collect RT3 data at baseline and could not examine change over time, and this is a limitation of the study.

Having no female participants is another limitation of this study, but women make up less than 5% of the patients in the clinics from which we recruited.

In conclusion, our findings indicate that older male veterans are receptive to exercise interventions based in primary care. Although 25% of the recruited sample was not interested in participating, our randomization rate of close to 40% is higher than that typically observed in these types of interventions.23 The US Preventive Task Force has concluded insufficient evidence exists regarding the effectiveness of exercise counseling for adults in primary care settings.25 This study provides additional confirmatory evidence of the benefits of primary care–based interventions promoting physical activity. Furthermore, the results suggest that health benefits can be obtained with relatively modest and safe home-based regimens that include walking and strength training. We further note that the clinic time expended by the counselors was relatively short (<2 hours over the 10-month intervention) and that exercise patterns were maintained over the same time frame. We are encouraged by the positive findings of this trial but note that many study participants were still exercising below recommended guidelines. Additional studies will be needed to examine strategies to secure more robust outcomes and successful long-term adherence to these types of interventions.

Correspondence: Patricia M. Dubbert, PhD, Veterans Affairs Medical Center (11M), 1500 E Woodrow Wilson Dr, Jackson, MS 39216 (patricia.dubbert@med.va.gov).

Accepted for Publication: November 12, 2007.

Author Contributions: Drs Dubbert and Meydrech had full access to all of the data in the study and take responsibility for the integrity of the data and accuracy of the data analysis. Study concept and design: Dubbert, Morey, and Kirchner. Acquisition of data: Dubbert and Grothe. Analysis and interpretation of data: Dubbert, Morey, and Meydrech. Drafting of the manuscript: Dubbert, Morey, and Grothe. Critical revision of the manuscript for important intellectual content: Dubbert, Kirchner, and Meydrech. Statistical analysis: Dubbert and Meydrech. Obtained funding: Dubbert. Administrative, technical, and material support: Dubbert, Morey, Kirchner, and Grothe. Study supervision: Dubbert, Morey, and Kirchner.

Financial Disclosure: None reported.

Funding/Support: This research was supported by the Department of Veterans Affairs Health Services Research and Development Service Project NRI 99-334.

Disclaimer: The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs.

Additional Information: Dr Dubbert is the associate chief of Mental Health at the G.V. (Sonny) Montgomery Veterans Affairs Medical Center.

Additional Contributions: Julia Voelkel, BS, MHS, contributed as a study nurse and interventionist; David P. Hawkins, MCP, collected data; Cheryl Robinson, MSN, provided consultation as nurse practitioner; Donald Breckenridge, BS, contributed as a physical therapy interventionist; and Gloria Ransom-Crossley, BS, provided administrative assistance.

Dubbert  PMCooper  KMKirchner  KAMeydrech  EFBilbrew  D Effects of nurse counseling on walking for exercise in elderly primary care patients. J Gerontol A Biol Sci Med Sci 2002;57 (11) M733- M740
PubMed
Nelson  MERejeski  WJBlair  SN  et al.  Physical activity and public health in older adults: recommendations from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007;39 (8) 1435- 1445
PubMed
Seguin  RNelson  ME The benefits of strength training for older adults. Am J Prev Med 2003;25 (3) ((suppl 2)) 141- 149
PubMed
Conn  VSValentine  JCCooper  HM Interventions to increase physical activity among aging adults: a meta-analysis. Ann Behav Med 2002;24 (3) 190- 200
PubMed
National Institute on Aging, Exercise: A Guide From the National Institute on Aging.  Bethesda, MD National Institute on Aging2001;
Ware  JESnow  KKKosinski  MGandek  B SF-36 Health Survey Manual and Interpretation Guide.  Boston, MA Health Institute New England Medical Center1992;
Rikli  REJones  CJ Functional fitness normative scores for community-residing older adults, ages 60-94. J Aging Phys Act 1999;7160- 179
Deyo  RACherkin  DCCiol  MA Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992;45 (6) 613- 619
PubMed
Charlson  MEPompei  PAles  KLMacKenzie  CR A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40 (5) 373- 383
PubMed
Rhudy  JLDubbert  PMKirchner  KAWilliams  AE Efficacy of a program to encourage walking in VA elderly primary care patients: the role of pain. Psychol Health Med 2007;12 (3) 289- 298
PubMed
Stewart  ALMills  KMKing  ACHaskell  WLGillis  DRitter  PL CHAMPS physical activity questionnaire for older adults: outcomes for interventions. Med Sci Sports Exerc 2001;33 (7) 1126- 1141
PubMed
Rowlands  AVThomas  PWMEston  RGTopping  R Validation of the RT3 triaxial accelerometer for the assessment of physical activity. Med Sci Sports Exerc 2004;36 (3) 518- 524
PubMed
Rikli  REJones  JJ Assessing physical performance in independent older adults: issues and guidelines. J Aging Phys Act 1997;5244- 261
Guralnik  JMFerrucci  LPieper  CF  et al.  Lower extremity function and subsequent disability: consistency across studies, predictive models, and value of gait speed alone compared with the short physical performance battery. J Gerontol A Biol Sci Med Sci 2000;55 (4) M221- M231
PubMed
Kaelin  MESwank  AMAdams  KJBarnard  KLBerning  JMGreen  A Cardiopulmonary responses, muscle soreness and injury during the one repetition maximum assessment in pulmonary rehabilitation patients. J Cardiopulm Rehabil 1999;19 (6) 366- 372
PubMed
Barnett  PG Determination of VA health care costs. Med Care Res Rev 2003;60 (3) ((suppl)) 124S- 141S
PubMed
King  ACSallis  JFDunn  AL  et al.  Overview of the Activity Counseling Trial (ACT) intervention for promoting physical activity in primary health care settings. Med Sci Sports Exerc 1998;30 (7) 1086- 1096
PubMed
Stewart  ALMills  KMSepsis  PG  et al.  Evaluation of CHAMPS, a physical activity promotion program for older adults. Ann Behav Med 1997;19 (4) 353- 361
PubMed
Stewart  ALVerboncoeur  CJMcLellan  BY  et al.  Physical activity outcomes of CHAMPS II: a physical activity promotion program for older adults. J Gerontol A Biol Sci Med Sci 2001;56 (8) M465- M470
PubMed
Ware  JEBayliss  MSRogers  WHKosinski  MTarlov  AR Differences in 4-year health outcomes for elderly and poor, chronically ill patients treated in HMO and fee for services systems. JAMA 1996;276 (13) 1039- 1047
PubMed
Pinto  BMGoldstein  MGAshba  JSciamanna  CNJette  A Randomized controlled trial of physical activity counseling for older primary care patients. Am J Prev Med 2005;29 (4) 247- 255
PubMed
Taylor  AHFox  KR Effectiveness of a primary care exercise referral intervention for changing physical self-perceptions over 9 months. Health Psychol 2005;24 (1) 11- 21
PubMed
Writing Group for the Activity Counseling Trial Research Group, Effects of physical activity counseling in primary care. JAMA 2001;286 (6) 677- 687
PubMed
Westerterp  KRMeijer  EP Physical activity and parameters of aging: a physiological perspective. J Gerontol A Biol Sci Med Sci 2001;56 ((spec No. 2)) 7- 12
PubMed
Eden  KBOrleans  TMulrow  CDPender  NJTeutsch  SM Does counseling by clinicians improve physical activity? a summary of the evidence for the US Preventive Services Task Force. Ann Intern Med 2002;137 (3) 208- 215
PubMed

Figures

Place holder to copy figure label and caption
Figure 1.

Participant flow through the study. EDUC indicates discussion of the participants' choice of health education topics; EXC, counseling for home-based walking and strength exercise.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Total weekly walking (A) and strength exercise (B) times by group (last observation carried forward for missing values). EDUC indicates discussion of the participants' choice of health education topics; EXC, counseling for home-based walking and strength exercise.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 2. Baseline Characteristics of the Intention-to-Treat Participant Sample
Table Graphic Jump LocationTable 3. Effects of the Interventions on Exercise Behaviors
Table Graphic Jump LocationTable 4. Physical Performance Changes at 10 Monthsa
Table Graphic Jump LocationTable 5. Physical Performance and Quality of Life Changes for Participants by Self-Reported Strength Exercise

References

Dubbert  PMCooper  KMKirchner  KAMeydrech  EFBilbrew  D Effects of nurse counseling on walking for exercise in elderly primary care patients. J Gerontol A Biol Sci Med Sci 2002;57 (11) M733- M740
PubMed
Nelson  MERejeski  WJBlair  SN  et al.  Physical activity and public health in older adults: recommendations from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007;39 (8) 1435- 1445
PubMed
Seguin  RNelson  ME The benefits of strength training for older adults. Am J Prev Med 2003;25 (3) ((suppl 2)) 141- 149
PubMed
Conn  VSValentine  JCCooper  HM Interventions to increase physical activity among aging adults: a meta-analysis. Ann Behav Med 2002;24 (3) 190- 200
PubMed
National Institute on Aging, Exercise: A Guide From the National Institute on Aging.  Bethesda, MD National Institute on Aging2001;
Ware  JESnow  KKKosinski  MGandek  B SF-36 Health Survey Manual and Interpretation Guide.  Boston, MA Health Institute New England Medical Center1992;
Rikli  REJones  CJ Functional fitness normative scores for community-residing older adults, ages 60-94. J Aging Phys Act 1999;7160- 179
Deyo  RACherkin  DCCiol  MA Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992;45 (6) 613- 619
PubMed
Charlson  MEPompei  PAles  KLMacKenzie  CR A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40 (5) 373- 383
PubMed
Rhudy  JLDubbert  PMKirchner  KAWilliams  AE Efficacy of a program to encourage walking in VA elderly primary care patients: the role of pain. Psychol Health Med 2007;12 (3) 289- 298
PubMed
Stewart  ALMills  KMKing  ACHaskell  WLGillis  DRitter  PL CHAMPS physical activity questionnaire for older adults: outcomes for interventions. Med Sci Sports Exerc 2001;33 (7) 1126- 1141
PubMed
Rowlands  AVThomas  PWMEston  RGTopping  R Validation of the RT3 triaxial accelerometer for the assessment of physical activity. Med Sci Sports Exerc 2004;36 (3) 518- 524
PubMed
Rikli  REJones  JJ Assessing physical performance in independent older adults: issues and guidelines. J Aging Phys Act 1997;5244- 261
Guralnik  JMFerrucci  LPieper  CF  et al.  Lower extremity function and subsequent disability: consistency across studies, predictive models, and value of gait speed alone compared with the short physical performance battery. J Gerontol A Biol Sci Med Sci 2000;55 (4) M221- M231
PubMed
Kaelin  MESwank  AMAdams  KJBarnard  KLBerning  JMGreen  A Cardiopulmonary responses, muscle soreness and injury during the one repetition maximum assessment in pulmonary rehabilitation patients. J Cardiopulm Rehabil 1999;19 (6) 366- 372
PubMed
Barnett  PG Determination of VA health care costs. Med Care Res Rev 2003;60 (3) ((suppl)) 124S- 141S
PubMed
King  ACSallis  JFDunn  AL  et al.  Overview of the Activity Counseling Trial (ACT) intervention for promoting physical activity in primary health care settings. Med Sci Sports Exerc 1998;30 (7) 1086- 1096
PubMed
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