INTRODUCTION
As global aging continues to progress, the development of intervention strategies to extend healthy life expectancy in older adults is urgently required. Physical inactivity in older adults is associated with cognitive impairment,1) poor psychological status,1) and reduced social functioning, including smaller social networks and lower participation in social activities.2) Furthermore, physical inactivity is a risk factor for frailty,3) disability,4) and mortality.5) Thus, regular physical activity contributes to the extension of healthy life expectancy in older adults.
To maintain regular physical activity, exercise behavior should be promoted based on the Transtheoretical Model (TTM).6) The TTM consists of three primary components: the stage of change, process of change, and decisional balance. Among these, the stages of change are considered the most critical.7) Moreover, these are categorized into five stages: pre-contemplation, contemplation, preparation, action, and maintenance. Therefore, promoting exercise behavior among older adults requires identifying their stage of change based on the TTM and supporting their transition to the action or maintenance stages.
Musculoskeletal disorders increase with age, leading to adverse health outcomes.8) In Japan, musculoskeletal disorders in older adults are risk factors for long-term care, and the number of hospitalized older patients with musculoskeletal disorders is increasing.9) Some studies have reported that physical activity levels in these patients after hospital discharge are lower than that of those before hospital admission.10) Moreover, a prospective cohort study reported that most older patients with musculoskeletal disorders refrained from going out after hospital discharge.11) These findings suggest that physical activity levels after discharge are likely to decrease in older inpatients with musculoskeletal disorders, highlighting the critical importance of promoting exercise behaviors in this population. Kanai et al.12) reported that age-related conditions such as sarcopenia and malnutrition affected the decline in physical activity levels, as assessed using a triaxial accelerometer, in hospitalized older patients with musculoskeletal disorders. However, to our knowledge, no studies have investigated the factors associated with poor exercise behavior based on the TTM after hospital discharge in older inpatients with musculoskeletal disorders. Previous studies focusing on behavior change based on the TTM have targeted healthy middle-aged adults,13,14) older adults,6) and patients undergoing psychotherapy for alcohol use disorders, eating disorders, or mood disorders.15) However, no studies have specifically focused on older inpatients with musculoskeletal disorders or examined factors influencing their exercise behavior. Consequently, intervention strategies to enhance post-discharge exercise adherence in this population remain unclear. This prospective study aimed to examine predictor variables that identify poor exercise behavior among older inpatients with musculoskeletal disorders based on the TTM after discharge.
MATERIALS AND METHODS
Participants and Study Design
This 6-month prospective cohort study recruited patients admitted to the rehabilitation hospital, including those in the convalescent rehabilitation and community-based integrated care wards of Shonan Keiiku Hospital, to promote functional recovery and support their return home. Eligible individuals were older inpatients aged ≥60 years with musculoskeletal disorders, such as knee or hip osteoarthritis, vertebral compression fractures, lumbar spinal stenosis, and postoperative conditions following knee, hip, or lumbar surgeries. Exclusion criteria included a Mini-Mental State Examination score <23,16) and the presence of psychiatric conditions such as depression. The study protocol was approved by the Ethics Committee of Shonan Keiiku Hospital (Approval No. 22-017), and all participants provided written informed consent before participation.
Assessments
Baseline assessments were conducted within 1 week before discharge, and follow-up assessments were conducted by physical therapists 6 months after discharge from the hospital.
Exercise behavior
Exercise behavior was assessed using the stage of behavioral change based on the TTM at baseline and at the 6-month follow-up assessment. Participants were classified into one of the following categories: “I am not currently exercising and do not intend to start in the foreseeable future” (precontemplation), “I am not currently exercising but intend to start within 6 months” (contemplation), “I am exercising but not regularly” (preparation), “I am exercising regularly but for <6 months” (action) and “I am exercising regularly and have been doing so for >6 months” (maintenance).17) Poor exercise behavior was defined as pre-contemplation, contemplation, and preparation at both baseline and follow-up, or those who transitioned from action and maintenance at baseline to pre-contemplation, contemplation, and preparation at follow-up.18)
Demographics
Participants completed questionnaires and measurements, including age, sex, height, weight, body mass index (BMI), Charlson Comorbidity Index,19) length of hospital stay, number of prescribed medications, primary musculoskeletal diagnosis, and presence of musculoskeletal pain at baseline. The presence of musculoskeletal pain in the torso and upper and lower extremities was determined using the simple question, “Do you currently have any pain that persists longer than 4 weeks?”20,21) Findings from the National Health and Aging Trends Study conducted in the United States suggests that pain lasting >4 weeks is associated with clinically significant decrements in function.21,22)
Physical function
At baseline, physical function was assessed using grip strength, the five times sit-to-stand test (FTSS), 10-m walking time, and the timed up-and-go (TUG) test. Grip strength was measured in the standing position by using a digital dynamometer (TKK-5401; Matsuyoshi Medical Instrument Co., Tokyo, Japan).23) The FTSS was measured as the time taken by a patient to rise from a chair five times as fast as possible, with their arms folded across their chests.24) Ten-meter walking time was measured as the time in seconds taken to walk the middle 10 m of a 16-m path at a fast walking speed.25) TUG was measured as the time taken in seconds to stand up from a standard chair, walk 3 m at a fast pace, turn, walk back to the chair, and sit down again.26)
Cognitive function and psychological status
A series of cognitive and psychological status assessments was administered at baseline. Attention, executive function, and processing speed were assessed using the Trail Making Test Part A (TMT-A),27) Trail Making Test Part B (TMT-B)27) and Symbol Digit Modalities Test (SDMT),28) respectively. Psychological status was evaluated using the 15-item Geriatric Depression Scale (GDS-15)29) and exercise self-efficacy (SE) scale,30) which is a partially modified version developed by Oka17) and created based on the scale by Marcus et al.14) The modified exercise SE scale included four question items, such as “I am confident that I can participate in regular exercise even when I feel I don’t have the time” to assess the degree of confidence in being able to engage in physical activity. A 5-point Likert scale was used, with responses ranging from “I do not think so at all” (1 point) to “I very much think so” (5 points). The scores were totaled for the four exercise SE scale items and ranged from 5 to 20 points, with higher scores indicating higher SE. Oka’s exercise SE scale was created in Japanese, and its reliability and validity have been demonstrated.17)
Statistical Analyses
All variables were assessed for normality using quantile-quantile (Q-Q) plots. Student t-test or Mann–Whitney U-test and chi-squared test for cross-tabulation tables were used to examine differences in continuously scored and categorical measures, respectively, between patients with and without poor exercise behavior. Variables shown to have significant between-group differences in the above tests were used as independent variables in logistic regression analyses, with poor exercise behavior (yes or no) as a dependent variable. Based on prior literature,33) the initial model (Model 1) was unadjusted; Model 2 was adjusted for age, sex, BMI, and the Charlson Comorbidity Index; and Model 3 was further adjusted for 10-m walking time in addition to the Model 2 covariates. All analyses were performed using SPSS 26.0 for Windows (IBM, Armonk, NY, USA); the significance level was set at p<0.05.
RESULTS
The flowchart in Fig. 1 outlines the recruitment process for participants. Of the 2,486 inpatients who were admitted to the rehabilitation hospital, including convalescent and community-based integrated care wards, 256 had musculoskeletal disorders. Of the 256 older inpatients, 103 were excluded because of cognitive impairment or psychiatric conditions such as depression, and 12 declined to participate, resulting in 141 inpatients being included in the baseline assessments. During the follow-up period, 24 inpatients could not complete the follow-up assessments because of refusal to participate (n=1), death (n=1), or inability to be contacted via telephone (n=22). Therefore, 117 participants were included in the final analysis.
Exercise Behavior Changes over the Follow-Up Period and Baseline Characteristics of the Participants with and without Poor Exercise Behavior
At baseline, the number of participants in precontemplation, contemplation, preparation, action, and maintenance stages based on the TTM were 4 (3.5%), 15 (12.8%), 26 (22.2%), 41 (35.0%), and 31 (26.5%), respectively. At the 6-month follow-up, the number of participants in precontemplation, contemplation, preparation, action, and maintenance stages based on the TTM were 25 (21.4%), 5 (4.3%), 23 (19.7%), 9 (7.6%), and 55 (47.0%), respectively. The number of participants with precontemplation, contemplation, and preparation at both baseline and follow-up were 31 (26.5%), and those who transitioned from action and maintenance at baseline to pre-contemplation, contemplation, and preparation at follow-up were 22 (18.8%). Thus, 53 (45.3%) of the 117 participants were classified as having poor exercise behavior.
Baseline characteristics and test results of individuals with and without poor exercise behavior are presented in Table 1. At baseline, the mean exercise SE scale score in participants with poor exercise behavior was lower than that in participants without poor exercise behavior (p=0.001). Additionally, the mean GDS-15 score in participants with poor exercise behavior was higher than that in participants without poor exercise behavior (p=0.036). No significant differences in other variables were observed between participants with and without poor exercise behavior at baseline (p>0.05).
Logistic Regression Analyses to Determine Predictors of Poor Exercise Behavior
Poor exercise behavior was significantly associated with lower exercise SE scale scores and higher GDS-15 scores in both the unadjusted (Model 1) and adjusted models including relevant covariates (Models 2 and 3) (Table 2).
DISCUSSION
This prospective study analyzed the factors predicting poor exercise behavior after discharge from a rehabilitation hospital for older inpatients with musculoskeletal disorders. Our analyses revealed that lower exercise self-efficacy and more depressive symptoms were associated with poor exercise behavior. This study is novel and significant because, to our knowledge, it is the first to identify predictors of poor exercise behavior among older inpatients with musculoskeletal disorders, assessed using the stage of exercise behavior change based on TTM. These findings offer valuable insights into rehabilitation strategies aimed at promoting exercise behaviors in this population.
In a middle-aged population of healthy adults and individuals with chronic musculoskeletal disorders, some cross-sectional studies have reported that lower exercise self-efficacy is associated with poor exercise behavior14) and lower physical activity levels.34,35) Our longitudinal study targeting older inpatients with musculoskeletal disorders revealed that lower exercise SE at baseline predicted poor exercise behavior during the 6-month follow-up after discharge from the rehabilitation hospital. These findings indicate that the causality between lower exercise SE and poor exercise behavior can contribute to the identification of strategies to promote exercise behavior in older inpatients with musculoskeletal disorders.
The present study demonstrated that more depressive symptoms are predictors of poor exercise behavior in older inpatients with musculoskeletal disorders. Some cross-sectional studies indicated an association between depressive symptoms and reduced physical activity in community-dwelling older adults.36,37) Although no longitudinal evidence exists for a relationship between depressive symptoms and poor exercise behavior in older inpatients with musculoskeletal disorders, our findings are consistent with existing literature. Moreover, depressive symptoms were associated with lower exercise self-efficacy in community-dwelling older adults.38) Thus, the association between depressive symptoms and lower exercise self-efficacy at baseline may also explain poor exercise behavior during the 6-month follow-up after discharge from the rehabilitation hospital.
Educational interventions including four elements—vicarious experience, verbal persuasion, performance accomplishment, and physiological/emotional persuasion—are effective in enhancing exercise self-efficacy.39) Interventions to promote social support and improve self-rated health are beneficial in reducing depressive symptoms.40) Based on these findings, intervention strategies to create pamphlets incorporating vicarious experiences and verbal persuasion, using activity diaries to record performance accomplishment and physiological/emotional persuasion, and establishing opportunities for community interaction may be effective for simultaneously addressing both self-efficacy and depressive symptoms, resulting in promoting exercise behavior in older inpatients with musculoskeletal disorders. For example, self-management programs that increase physical activity using diaries to record daily step counts, along with participation in community-based exercise classes providing opportunities for social interaction, may enhance post-discharge exercise adherence in this population.
This study had certain limitations. First, we did not examine the factors that predict poor exercise behavior, focusing on the differences in musculoskeletal disorders among older inpatients, owing to small sample sizes. Second, our study had a single-center prospective design, and caution should be exercised regarding its generalizability. Third, the follow-up period in this prospective study was short. Finally, we did not examine psychosocial factors, such as social support, living situation, or post-discharge supervision, which may influence exercise adherence. Future research, utilizing detailed analyses to investigate the differences in musculoskeletal disorders, a multicenter prospective design, long-term follow-up, and potential confounding factors, is required to confirm the current findings.
In conclusion, lower exercise self-efficacy and more depressive symptoms were predictors of poor exercise behavior after hospital discharge among older inpatients with musculoskeletal disorders. These results underscore the importance of implementing strategies to enhance mental well-being and sustain exercise behavior following discharge among older inpatients with musculoskeletal disorders.
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