Demographic and Cognitive Determinants of Physical Activity among Iranian Older Adults

doi:10.21203/rs.3.rs-4861891/v1

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Demographic and Cognitive Determinants of Physical Activity among Iranian Older Adults

https://doi.org/10.21203/rs.3.rs-4861891/v1

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Background

Exercise is consistently related to physical and psychological health benefits in older adults. The present study aimed to investigate the cognitive determinants of physical activity (PA) based on social cognitive theory (SCT) in older adults in Iran.

Methods

A cross-sectional survey among 550 older adults was conducted on more than 60-year-old adults, selected randomly from health centers in Isfahan City. Data collection was done using demographic and cognitive (SCT) questionnaires, and the Physical Activity Questionnaire (PASE). For data analysis, Pearson's correlation test and linear regression were used with SPSS.23 software.

Results

The prevalence of physical activity among older adults was low (7.09%). Although the results revealed a significant correlation between self-efficacy, outcome expectancies, outcome values, social support, and physical activity (p < 0.001), the linear regression test showed self-efficacy as the only significant explanatory among the cognitive variables in older adults (β = 0.14, p < 0.01).

Conclusion

These results suggest that self-efficacy is the most important factor affecting PA behavior among SCT constructs in older adults. Healthcare professionals should try more to increase older adults’ perception of their abilities to do PA instead of just training them to do PA.

Social Cognitive Theory

Physical Activity

Older Adult

Physical activity (PA) contributes to healthy aging through the prevention of chronic age-associated illnesses and disabilities [1]. Changing lifestyles, including a brief increase in PA, help improve the quality of life, preserve older adults' physical and mental health, and decrease medical costs [2].

The aging population is expected to almost double by 2050 in the world [3], and there is a growing need for strategies to militate against common health issues associated with aging to reduce the burden on the health system [4]. So it is critical to develop a better understanding of PA behavior in older adults to increase the likelihood of these individuals maintaining their ability to live independently.

Several studies have evaluated the effects of cognitive/personal, environmental/social, behavioral, demographic, and other factors on the level of PA in older adults [5, 6]. Social cognitive theory (SCT; Bandura, 1997, 1986, 2004) [7–9] may be a particularly useful framework for understanding PA behavior in the general population and older adults [10].

Outcome expectations are defined as ‘the perception that a certain behavior will bring out specific outcomes’ [7]. Individuals are more likely to engage in PA when they perceive that these efforts will lead to important positive outcomes such as better health [11]. People who expect positive health benefits as a result of PA are more likely to set goals and plans related to PA [12] However, it is also important to account for the degree to which these outcome expectations are met over time [13].

Surveys proposed that individuals with higher levels of self-efficacy have more positive expectations about what the behavior will bring about, set higher goals for themselves, and are more likely to believe that they are capable of overcoming barriers, resulting in a greater likelihood of engaging and maintaining specific behaviors [14].

To better understand PA behavior and design more effective interventions and programs, the present study was designed to test the utility of social cognitive theory for explaining PA behavior in a sample of older adults in Iran.

Study design and Participants

A quantitative, cross-sectional research design was used for this study. A total of 550 people over 60 years of age (mean age = 71.56, SD = 9.53), who were satisfied with participating in the research, were able to communicate and interview (no severe hearing or speech problems), did not have acute or debilitating disease, and did not have a physical or mental disability were selected using the multistage cluster sampling method. The sample size was measured using the sample size equation at a confidence level of (p = 0.05) [15]. Before entering the study, the participants gave their informed consent in writing. This study was approved by the Ethics Committee of Isfahan University of Medical Sciences, Iran (IR.MUI.RESEARCH.REC.1402.087).

Measures

The data collection tool included a questionnaire consisting of three parts: demographic information; researcher-made questionnaires of self-efficacy; perceived social support; outcome expectancies; and outcome values, as well as the standard PA Scale for older adults (PASE) [16].

The demographic characteristics included the participants' age, education level, job, gender, place of residence, marital status, and income level of the participants.

Participants completed the Leisure-Time, Physical Activity Questionnaire (PASE) designed by Washburn et al. in 1993 as a validated self-measure of PA [16]. In Iran, Hatami et al. confirmed the validity and reliability of the questionnaire with a Cronbach's alpha coefficient of 0.94 [17]. This questionnaire evaluates activities such as older adults’ leisure time, household and outdoor tasks, and light, moderate, and vigorous sports. It has three parts: leisure time, home activities, and job activities.

The reliability and validity of researcher-made questionnaires on cognitive factors were evaluated by the research team. A panel of 8 experts, including 5 health education experts, and 3 gerontologists, evaluated the content validity of the questionnaire in the qualitative phase. In the quantitative phase, the questionnaire was appraised regarding its content validity index (CVI) and content validity ratio (CVR). The clarity, simplicity, and relevance of the items were measured in the CVI assessment (according to Lawshe, CVIs greater than 0.7 are acceptable) [18]. CVR was used to ensure that the items had been developed in the best possible way for measuring the mentioned factors (according to Waltz & Bausell, CVRs greater than 0.75 were acceptable) [19]. To ensure face validity, the first draft of the questionnaire was evaluated by 15 older participants who were not expected to participate in this study. They informed the research team if any of the items in the questionnaire were not clear or difficult to comprehend. Comments and feedback provided were considered by the research team and then incorporated where appropriate to develop the final version of the questionnaire. Finally, Cronbach’s (values above 0.7) [20]. internal consistency was used to identify possible variables with a low contribution to the questionnaire. The final version of the questionnaire was organized into three sections including:

Self-efficacy was assessed with 10 questions on a 5-point Likert scale (from not sure to completely sure), (Cronbach's alpha coefficient of 0.829) and (CVI > 0.9, CVR > 0.8), which measured self-efficacy for PA in older adults.

The nine-item scale assessed social support on a 4-point Likert scale from 1 (strongly disagree) to 4 (strongly agree) and measures social support for PA in older adults (Cronbach's alpha coefficient of 0.844). This scale was designed in two sections (family and friend support).

To evaluate the outcome expectancies and values, fourteen questions were designed to assess positive and negative expected outcomes from engaging in PA in three dimensions, on a 5-point Likert scale (from never likely to very likely). The participants were also asked to rate the degree of importance of each possible outcome on a 5-point Likert scale (from unimportant to very important). A higher score indicates higher outcome expectations and outcome values (Cronbach's alpha coefficients of 0.827 and 0.820, respectively).

Statistical analysis

The data were analyzed using IBM SPSS 23. Descriptive statistics are presented as the mean ± SD unless otherwise noted (e.g., number [%]). We examined the associations between SCT variables and PA using Pearson rank-order correlations. The hierarchical linear regression analysis was used to predict PA with SCT variables in Step 1. Then, the variables of age, gender, marital status, and occupation were entered in the second step.

The average age of the participants was 71.56 ± 9 years (range 60 to 102). The participants mainly had low levels of PA (90.9%), were married (69.27%), were illiterate and below diploma education (71.83%), and were unemployed (76.50%). The data for the full sample are detailed in Table 1. [Table 1 near here]

The descriptive statistics used to measure cognitive variables are based on older adults’ demographic factors (Table 2). The results showed that PA was significantly higher among men, married, educated, and more income older adults (p<0.01). all cognitive variables including self-efficacy, social support, outcome expectancies, and values in the same way were significantly in married, highly educated, and more income elder people (p<0.01). [Table 2 near here]

Correlation analysis revealed a positive significant correlation between PA, and all cognitive factors (p<0.01). The most correlation was seen between self-efficacy and other cognitive variables including outcome expectancies (R = 0.23), outcome values (R = 0.53), social support (R = 0.41), and PA (R = 0.23) (Table 3). [Table 3 near here]

Linear regression analysis was done in the last step to determine the most important factors affecting PA in older adults. Although a model with all cognitive variables could predict PA among older adults, its value was small (R²1=0.06, P<0.01) and when demographic variables were entered into the model in the second stage, the variance of the model reached (R²2=0.17, P<0.01), self-efficacy was the only significant cognitive variable that predicts PA behavior along with job status, age, and gender (P<0.01) (Table 4). [Table 4 near here]

This study proposed a research model based on SCT to examine the factors linked to PA behavior in older adults. These relationships revealed a significant positive effect between PA, and cognitive factors including self-efficacy, outcome expectancies and values, and social support. Still, self-efficacy was determined as the only important determinant of PA among older Iranian adults based on the results of regression analysis. 92.90% of the participants in this study were at low PA levels, which is a worrying finding that deserves discussion. Many previous studies in Iran have examined PA levels in older populations and similarly stated that the prevalence of inactivity is high in older adults [21]. Therefore, the PA of the older adults in this study has not progressed to a favorable state. Perhaps the lifestyle changes and social isolation caused by the COVID-19 pandemic have increased the inactivity of older adults in Isfahan in these years.

Nik-Nasir et al. in 2022 conducted a study involving 1711 Malaysians aged 60 and above. They found that nearly 27.1% of Malaysian older adults were physically inactive. Similarly, Pengpid and Peltzer reported that 36.7% of middle-aged and older adult residents in Indian communities were physically inactive. and also in 2023, a study by Lai et al. in England, showed that only 18% of older adults were at a low level of PA [22–24]. These results may be explained by more social support, and policies that support older adults to do PA in these countries.

Self-efficacy had a stronger relationship with PA than other cognitive variables. According to the statistical tests of Anderson et al. in America and Tulloch in Canada, low self-efficacy is usually one of the reasons for low PA in older adults and has the strongest correlation with PA [25, 26]. According to Bandura's findings, PA behavior and self-efficacy have a two-way algebraic relationship [7]. Unfortunately, it is difficult for older adults to follow a regular PA schedule. Hence, several tests have pointed out the prominent role of self-efficacy in older adult individuals’ participation in PA. According to McAuley, it helps to consider and operationalize self-efficacy beliefs about PA in older adults because these beliefs influence the motivation to engage in PA [27, 28].

Among demographic factors, gender was significantly associated with self-efficacy, and males were more likely to have greater self-efficacy related to PA. This is not surprising, as older men are more likely to be familiar with and feel confident in their ability to perform PA because of past experiences with it. Older women, conversely, were likely not encouraged or even allowed to perform PA regularly when they were younger. Therefore, barriers to self-efficacy prevent the initiation of suitable PA PA [29, 30]. Ethison et al. reported that older adults' PA has a multifactorial nature. Thus, a wide range of social, cognitive, and demographic factors help explain PA behavior [31].

Additionally, people who are employed, are married, have income, and have a higher education level have higher SCT-related cognitive variables, especially self-efficacy. Resnick also reported that cognitive variables in the PA of older adults are, male sex, marital status, employment status, income level, and education level [11]. Therefore, demographic differences among older adults, in addition to directly affecting PA, indirectly affect PA by affecting SCT-related cognitive variables.

SCT variables accounted for 6% of the variance in PA behavior, gender, age, marital status, and job status increased the effect size (17%), and gender, age, occupation, and self-efficacy were associated with greater variance. The model could not explain PA behavior optimally (R2 > 0.6) but showed the ability to predict PA behavior through self-efficacy and demographic variables. Contrary to these results, the study of Moeini et al. in 2023 showed that 62% of changes in the physical activity behavior of the participants were predicted by the extended SCT [32].

These findings show that to increase the level of participation of older adults in physical activity, the development of different intervention programs, tailored to individual needs and considering the differences in motivational incentives related to SCT cognitive variables (especially self-efficacy) and demographic variables are essential. Therefore, a unified guiding resource providing information on factors affecting the physical activity of older adults, as has been attempted in this study, may help program directors and instructors meet the needs and interests of participants by creating tailor-made programs.

According to research findings, older adults in Isfahan did not have desirable PA levels. The analyses indicated that self-efficacy was significantly associated with PA and consistently explained the largest portion of the variance in PA outcomes. These results support continued research on self-efficacy, for informing behavioral interventions that target PA and its secondary benefits in older adults. Therefore, a unified guiding resource providing information on factors affecting the physical activity of older adults, as has been attempted in this study, may help program directors and instructors meet the needs and interests of participants by creating tailor-made programs.

The research limitations included incorrect responses by some older adults due to illiteracy. To solve this problem, the questionnaires were read by the researcher, and older adults answered their questions. Another limitation was that the responses were from Isfahan, Iran; hence, the results may not be generalizable to all older adults. The use of self-reported measures indicates possible limitations; however, these methods remain acceptable for obtaining information. The cross-sectional design of the study does not allow causal deduction.

Author Contributions

All authors contributed to the study's conception and design. Author Contributions: Z. M. contributed to the data acquisition, performed the data analysis, and wrote the article. M. J. T. contributed to the analysis and interpretation of the data, revised the article critically for important intellectual content, and revised the manuscript. Z. F. D. contributed to the study conception and design and data acquisition, revised the article critically for important intellectual content, and revised the manuscript.

Declarations of interest

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Transparency statement

The corresponding author, affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

Conflict of interest statement

The authors declare no conflicts of interest.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Ethical approval and consent to participate

All procedures were carried out by the ethical standards of the Helsinki Declaration of 2013, and approved by the Ethics Committee of the Isfahan University of Medical Sciences (IR.MUI.RESEARCH.REC.1402.087).

Informed consent

All participants provided written informed consent to participate.

Statement of man and animal

This study does not violate the rights of human participants

Consent for publication

All authors consented to the submission of this manuscript for publication.

Competing interests

No issues regarding the journal policies. All authors declare no competing interests. All authors approved the manuscript for submission. The content of the systematic review has not been published, or submitted for publication elsewhere.

Acknowledgments

The present study cooperated with the health centers affiliated with Isfahan Health Centers. The authors are grateful to the staff and older adult participants in this study.

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You are reading this latest preprint version

Demographic and Cognitive Determinants of Physical Activity among Iranian Older Adults

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Abstract

Introduction

Methods

Study design and Participants

Measures

Statistical analysis

Results

Discussion

Conclusion

Research limitations

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

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