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Description
This thesis study aimed to (1) test whether first-year college students' perceived future self-connectedness predicts their interest in continuing premedical studies, (2) assess whether the presence of academic role models predicts their future self-connectedness and (3) pilot-test an experimental manipulation

This thesis study aimed to (1) test whether first-year college students' perceived future self-connectedness predicts their interest in continuing premedical studies, (2) assess whether the presence of academic role models predicts their future self-connectedness and (3) pilot-test an experimental manipulation to increase future self-connectedness and interest in premedical studies. The study included two parts. First, students completed the pre-manipulation measures including future self-connectedness and interest in premed studies. Second, students were randomly assigned to an experimental or a control condition. In the experimental condition, students were asked to imagine that they were licensed doctors and write words of advice to their current selves. In the control condition students were asked to reflect and write about their daily routine. The results from this study showed a significant positive correlation of interest in remaining in premedical studies with both future self-connectedness and the presence of role models and future self-connectedness. Additionally, students in the experimental condition showed a significant increase in future self-connectedness after completing the manipulation. However, their interest in remaining in premedical studies did not change after the manipulation. Together, these findings suggest a method for keeping Freshman undergraduates from dropping out hastily from the premedical track.
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Barrett Honors College theses and creative projects are restricted to ASU community members.

Details

Title
  • Falling short of becoming a doctor: A psychological approach to future self-disconnect and academic role models
Contributors
Date Created
2018-12
Resource Type
  • Text
  • Machine-readable links