The effect of regulatory focus and time preference on the dual process of physical activity: A cross‐sectional study among nurses

Abstract

Aims:To examine the dual process of physical activity adoption among nurses and its relationships with two personal orientations-regulatory focus-the tendency to focus on promotion (vs. prevention) goals and time preference as measured by delay discounting: the tendency to overvalue immediate rewards over long-term ones. Background:The dual process theory suggests that both conscious and non-conscious processes influence the adoption of physical activity. However, the role of regulatory focus and time preference in this process was not yet examined. Design: A cross-sectional online survey among 143 nurses during August-November 2017.Methods: Validated measures were used to estimate physical activity habit strength (a non-conscious process) and intention, planning and behaviour control (conscious processes), physical activity level, regulatory focus and time preference. Multivariable ordered logit and logistic models were specified to examine determinants of both processes.Results: Promotion focus was positively associated with having a strong habit of physical activity among nurses with moderate-to-low activity levels, but it was negatively associated with habit for active nurses. As for time preference, higher delay discounting was negatively associated with nurses' conscious intention to adopt physical activity and with their action planning. Conclusion: Promotion focus and time preference are associated with both conscious and non-conscious processes of physical activity adoption among nurses and should be considered in future health promotion interventions targeted to this population. Impact: Promotion focus and time preference have a significant role in this dual process. Enhancing physical activity of health providers by adjusting the intervention to personal orientations may improve public health. K E Y W O R D S delay discounting, dual process, habit formation, nurses, physical activity, regulatory focus, time preference | 1405 AVRAHAM et Al.

The Relationship between Sociodemographic, Professional, and Incentive Factors and Self-Reported Level of Physical Activity in the Nurse Population: A Cross-Sectional Study

“…More surprising is that the level of leisure-time PA was significantly higher in nurses not having a clinical specialization than in nurses with such as specialization. Our study confirmed previous observations: While nurses are aware of the benefits of PA and the risks associated with inactivity, they do not implement this knowledge into their own life [ 5 , 6 , 7 ]. However, it is promising that there were more nurses with a masters in nursing in the group motivated to do PA than in the unmotivated group.…”

“…The self-reported TPAS noted in a population of Polish nurses being professionally active is categorized as high, which is consistent with the results of surveys based on self-reported methods [ 33 , 34 ] and in contrast with other studies based on methods considered objective (accelerometers and pedometers), which indicated that the level of PA among nurses is generally low [ 5 , 6 , 7 ]. These analyses have contributed to testing many interventions to improve nurses’ PA, but the results are inconsistent [ 14 ].…”

“…Regular PA improves adults’ overall health, quality of life, weight management, mental health, prevents depression, strengthens bones and muscles, and minimizes the risk of chronic disease and even early mortality [ 2 , 3 , 4 ]. Current research indicates that nurses’ adherence to PA is low despite their awareness of the benefits of PA and the risks associated with physical inactivity—and even though they are perceived as role models [ 5 , 6 , 7 ]. Less than quarter of the nursing population met the WHO physical activity guidelines [ 8 , 9 , 10 ].…”

Evaluation of the reliability and validity of the health regulatory focus scale in Chinese samples

“…It can investigate factors that influence individuals to adopt preventive measures such as vaccination ( Ross, 2022 ), safe sex ( Mao et al, 2021 ), or regular check-ups ( Rodrigues et al, 2023 ). Additionally, HRF can identify factors that motivate health-promoting behaviors like exercise ( Avraham et al, 2020 ), healthy eating ( Lin and Yeh, 2017 ), and medication adherence ( O’Connor et al, 2019 ). Furthermore, HRF can tailor health messages to an individual’s promotion or prevention focus, improving the effectiveness of health communication campaigns ( Ludolph and Schulz, 2015 ).…”