Consideration of future consequences and predictability: Examining six health behaviors with different levels of perceived severity

ABSTRACT

Research has shown that consideration of future consequences can successfully predict different health behaviors. Prior studies, however, have yielded inconsistent findings. This study aimed to address these inconsistencies by examining the associations between consideration of future consequences and different health behaviors involving different levels of severity. The main study sample consisted of 385 college students. Using a paper-and-pencil survey, a cross-sectional study was conducted. The survey addressed six behaviors under three health topics including vaccination (flu vaccination, HPV vaccination), smoking (smoking, signing for a smoke-free campus policy), and energy drink consumption (energy drink consumption, energy drink consumption mixed with alcohol). Behavioral status and consideration of future consequences were measured. Consideration of future consequences predicted health behaviors involving greater severity whereas it failed to predict health behaviors involving relatively less severity. This study found that the ability of consideration of future consequences to predict different health behaviors depends on the perceived severity associated with the behaviors.

KEYWORDS:

• Consideration of future consequences
• vaccination
• smoking
• energy drink
• perceived severity

Highlights

• Research has shown that CFC, a personality trait, predicts various health behaviors.

• This study identified the reasons for the inconsistencies found in prior studies.

• CFC’s associations with six behaviors involving different severities were tested.

• CFC predicted health behaviors involving greater severity.

• CFC failed to predict health behaviors involving relatively less severity.

Disclosure statement

No potential competing interest was reported by the authors.

Data availability statement

Data cannot be shared because there are embargoes on datasets. Anonymized data will be shared by request from any qualified investigator.

Additional information

Funding

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2018S1A5A2A03038195); and Yonsei University Research Fund of 2019 (#2019-22-0185).