This cross-sectional investigation was part of a larger study that is federally funded by the National Institute on Minority Health and Health Disparities (R01MD018025) and has been pre-registered on ClinicalTrials.gov (NCT05778604). The protocol for the study has been previously published elsewhere [16]. The study was conducted in the Greater Orlando, metropolitan area, FL and recruitment was accomplished through word-of-mouth, flyer distribution, and partnership with local communities. A total of 141 community-dwelling older adults were recruited. Participants were included in this study if they were at least 60 years of age, could stand on their own, had low-income status based on the 2019 poverty thresholds relative to family size [17], had fully completed the Regulatory Focus Questionnaire (RFQ), and had at least 4 days of valid recorded ActiGraph data (each day≥10 hours of wear time). Participants who were unable to perform PA, receiving treatment from a rehabilitation facility, or hospitalized more than 3 times in the past 12 months were excluded. After screening for inclusion criteria, 93 participants were included and analyzed in this study.

Minitab (version 21.4.3; Minitab LLC) and R software (version 4.3.1; R Foundation for Statistical Computing) were used to perform statistical analyses for this study. Each factor was checked for normality before analysis using descriptive statistics and Anderson-Darling normality tests through Minitab. Spearman rank correlation coefficients (ρ) were used due to the nonnormal distribution of each variable. R software was used to calculate correlation coefficients, compare statistically significant correlation values using Fisher Z transformation, and perform power analysis using the pwr package (version 1.3‐0) [25]. The threshold for statistical significance was set at P<.05.

This study was approved by the Institutional Review Board of the University of Central Florida (STUDY00003206), preregistered on ClinicalTrials.gov (NCT05778604), and carried out in accordance with the Declaration of Helsinki. The protocol has also been previously published elsewhere [16]. All participants gave written informed consent prior to participation. The data for this study were stored and managed using Research Electronic Data Capture (REDCap), a secure, web-based application that is designed to store data for research studies [26,27], and all participant data were deidentified. Participants were compensated US$50 in the form of a gift card upon completion of the study.

The purpose of this study was to determine the association between prevention and promotion focus with SB in older adults, as well as to compare those associations with two factors that are commonly known to have an association with SB among older adults(ie, age and BMI). Analysis showed that SB has a significant positive association with BMI and prevention focus. This finding supports our initial hypothesis. Consistent with the hypothesis, promotion focus was not significantly associated with SB. Contrary to expectations, we did not observe an association between age and SB. BMI was associated with SB, but this association with SB was relatively weaker than that of prevention focus. Overall, the associations were weaker than expected. Comparative analysis of the significant correlation values using Fisher Z transformation showed that the correlation between prevention focus and SB was not significantly higher than the correlation between BMI and SB.

A key finding of this study is the observation of a weak, but positive association between a prevention-focused regulatory style and SB, indicating that individuals with a primarily prevention-focused mindset may engage in increased amounts of SB. This result may be attributed to the cautious, safe, and loss-avoidant mindset associated with the prevention focus orientation. This result aligns with previous work, which found that safety concerns of older adults are a barrier to reducing their sedentary time, whether in their own homes or in their neighborhoods [28,29]. Individuals that exhibit such personality traits may be more likely to avoid engaging in PA and overall movement due to the possibility of injury. An injury may result in losses, specifically the possible expenses associated with recovery, as well as the loss of time needed for physical recovery and possible loss of independence. Individuals with such mindsets may view PA or increased movement as dangerous or unsafe, thus leading to avoidance. Environmental factors such as a neighborhood safety can also contribute to this mindset, further preventing PA and movement outside of one’s home if an individual perceives that their safety in their neighborhood could be at risk.

The promotion focus scores and total SB were weakly associated, which may have been attributed to the possibility that decreased SB, as well as the benefits associated with it, are not considered as growth or advancement to older adults. Furthermore, older adults’ decision to engage in SB may be more influenced by a prevention focus because the desires associated with it (eg, desires for safety, avoidance of negative consequences, and avoidance of losses) are perceived as more of a “need” rather than a desire. In contrast, the desires associated with a promotion motivation orientation (eg, desire to achieve growth, advancement, and maximize potential gains), which could be considered as less of a “need.”

It was expected that BMI would have a significant positive association with SB, due to the directly proportional association between BMI and weight. Increased time in SB can potentially lead to weight gain and has been positively related to the risk of obesity and diabetes [30-33]. Furthermore, studies have shown that SB is positively associated with BMI [34,35]. Interestingly, despite the difference being statistically insignificant, the prevention focus scores from the RFQ had a relatively greater correlation coefficient value than BMI when compared to total SB. For years, BMI has been used as an index of obesity to classify individuals based on their body weight relative to height. BMI continues to be used in medical practice and research due to being an affordable and readily obtained metric [36]. However, BMI has faced numerous backlashes, primarily due to its inability to differentiate between body lean mass and body fat mass [36-39]. For example, an individual with a greater amount of body lean mass could have the same BMI as an individual with a greater amount of body fat mass. This variability present in BMI could explain the relatively lower correlation value when relating to SB. Furthermore, the motivation orientation of an individual, specifically an older adult can influence their decision-making and behavior, which could drive them to engage in SB, therefore directly resulting in changes to their BMI.

Various studies have shown a positive correlation between age and SB in older adults [40,41]. However, a nonsignificant association between the two variables was observed in this study. Previous work has found that a multitude of factors contribute to the SB levels of older adults beyond age, such as accessibility to transportation, living environment, and weather [42]. The sites from which participants in this study were recruited from, varied in terms of social life. Some sites held weekly social activities (eg, exercise classes and bingo nights), while others did not hold any social events. These differences could adversely affect the decision of older adults to engage in SB and could explain the weak and nonsignificant association between age and total SB in this study.

Overall, despite the weak associations, the findings of this study show that the characteristics associated with a prevention focus may be a factor that leads older adults to engage in SB. The results from this study support the idea that older adults might be less inclined to engage in SB if they are given suggestions on how to maintain safety during PA or reassured that it is acceptable to make mistakes. This idea can be used to create new or improve existing intervention programs aimed toward improving the PA levels of older adults, which can ultimately result in a reduction in their fall risk. Spearman rank correlation was chosen for the analysis of this study due to its ability to adequately manage both normally and nonnormally distributed data. Although an appropriate test was used to perform correlation analysis, certain limitations exist within this study. First, a power analysis showed that only the association between the prevention focus score from the RFQ and total SB produced adequate power (82.86%). Although this value indicates reasonable sensitivity for detecting the observed association, all other associations produced a power significantly below this value (<50%).

Second, this study did not identify the causal relationship between the considered factors and only focused on pairwise correlations, as opposed to considering confounding effects. For example, there was a significantly greater number of females included in the sample than male participants (83/93). It has been previously found that female participants tend to be more prevention-focused than male participants [43], which explains the larger number of prevention-focused individuals (62/93). The exploration of confounding effects could provide a deeper understanding of the associations presented in this study. Future work should involve increasing the sample size to include more promotion-focused individuals and raising the power of the correlation tests to adequately determine the associations between the factors, as well as using techniques such as regression to incorporate confounders and conduct formal causal analysis.

Although many environmental factors drive older adults to engage in SB, psychological factors also play a role in influencing this behavior. Prevention focus, as determined by the RFQ was found to have a weak but significant positive association with SB in older adults. The association between BMI and SB was relatively weaker in comparison, but no significant differences were found between the two associations. These findings suggest that older adults may be driven to engage in increased amounts of SB due to having a dominant prevention focus, which revolves around thoughts of safety and the avoidance of negative consequences. Identifying an older adult’s motivational orientation can provide useful insight into understanding their decisions to engage in SB and further identify what strategic approach would be most effective when setting goals and implementing safeguards to decrease SB.