Examining a 5 Factor Model of Future Time Perspective

Event Center BC

This study examines the psychometric properties of a five-factor model of future time perspective (FTP). Perceptions of time and the future have implications for individual behaviors and decisions, yet the role of FTP is not well understood. Results provide support for a five-factor structure of FTP for use in future research. Individuals perceive time differently, particularly in their consideration of the future. In the context of goal setting, for example, some individuals focus on the immediate future while others look many years ahead. This construct has been identified as future time perspective (FTP, Nuttin, 1964). Differences in FTP have implications for motivation, yet its impact is not well understood. The current study describes the psychometric assessment of a five-factor measure of FTPdeveloped from existing scales. In developing a broad measure of FTP, we integrated two approaches. First, we included Husman and Shell’s (2008) description of FTP, which identifies four dimensions including speed, which is defined as a person’s ability to manage future events without external pressure; extension, defined as the extent in time for an individual to think about the future; value, defined as attainability of future goals; and connectedness, which is an individual’s ability to associate his/her present action to future goals. Second, based on the literature, we included perceptions of future opportunities (Carstensen & Lang, 1996) as a fifth dimension of FTP. The final scale examined in the present study comprised 35 FTP items comprising 5 factors. Participants (n= 280) were undergraduate students at a comprehensive university in the southwestern United States. All participants completed an online survey that contained 35 items representing the FTP construct, as well as 105 items representing several other established measures psychological constructs. Participants received class extra-credit for their time (approximately 30 minutes). Mplus with maximal likelihood estimation was used to evaluate the fit of the 35 items to three measurement models: one-factor model, five-factor model, and higher order factor model. The five-factor model showed the best fit (CFI = .76, RMSEA = .07), compared to the higher order factor model (CFI = .74, RMSEA = .08) and single factor model (CFI = .41, RMSEA = .12). Subsequently, post-hoc modifications were made based on the five-factor model in which items with variance explained less than 10% variance being removed. Additionally, items with coefficients less than .50 were also removed. The revised 28-item model demonstrated a modest fit (.85 CFI and .07 REMSEA) to the five-factor structure.