Communication technologies and social interactions

My first line of research examines the effects of using technology for social interactions on our health and well-being, particularly the mediating psychosocial processes that underlie different forms of technology use. I work with theories of computer-mediated communication (e.g., media richness, affordances, hyperpersonal model, social information processing theory), interpersonal communication (e.g., relational stage model, social penetration theory, uncertainty reduction theory), and social influence (e.g., social support, social capital, social presence, social comparison, and social norm). I use quantitative methods, including surveys, experiments, secondary data analysis, and content analysis, in answering my questions.

Along this line, I have conducted research on how international students’ social media use with their home and host country network is related to acculturative stress, the psychosocial processes underlying the relationships between media use and acculturation, social media use and body image, and interpersonal media use and physical activity. Most of these works have been published or presented at national and international conferences.

Related projects

  1. Li, L. (2021). Sharing joy through technology: The effect of synchronicity, nonverbal cues, and persistence on affective well-being. Unpublished doctoral dissertation. [Link][PDF]
  2. Li, L., & Meng, J.B. (2021, May 27-31). Communication with the core and acquaintance network: Association with physical activity and psychosocial mechanisms. International Communication Association Annual Conference. Virtual.
  3. Li, L., & Peng, W. (2019). Transitioning through social media: International students’ SNS use, perceived social support, and acculturative stress. Computers in Human Behavior, 98, 69–79. (IF 5.00) [Link][PDF]
  4. Li, L., & Peng, W. (2019, May 24-28). Learning about America: International students’ SNS use, cultural learning, and sociocultural adaptation. International Communication Association Annual Conference, Washington DC. Top paper. 
  5. Li, L., Rheu, M.J., & Kononova, A. (2019, May 24-28). Viewing females in sexualized clothing on Instagram: Effects on women’s body image. International Communication Association Annual Conference, Washington DC.
  6. Li, L. (2019, August 7-10). A serial mediation model of media exposure on body shame: The role of internalization of appearance ideals and self-objectification. Association for Education in Journalism & Mass Communication Annual Conference, Toronto, Canada. Top Student Paper.
  7. Li, L., & Shao, C. Y. (2018, August 6-9). Asian international students’ mass media use and acculturation strategies: Considering the effects of remote acculturation. Association for Education in Journalism & Mass Communication Annual Conference, Washington DC. Top Student Paper.

Health information technologies and the self-management of health

My second line of research examines how individuals adopt and continue using different health technologies for self-regulation and self-management, especially among vulnerable populations such as older adults or those who suffer from chronic illnesses. I work with theories focusing on the individual- or interpersonal-related variables that affect individuals’ health behavior (e.g., the health belief model, the transtheoretical model, self-regulation theory, social cognitive theory, social networks, social support, social influence), as well as theories explaining individuals’ adoption of technologies (e.g., the diffusion of innovation, unified theory of acceptance and use of technology).

Related projects

  1. Peng, W., Li, L., Kononova, A., Cotten, S., Kamp, K., & Bowen, M. (2021). Habit Formation in Wearable Activity Tracker Use Among Older Adults: Qualitative Study. JMIR MHealth and UHealth, 9(1), e22488. [Link][PDF]
  2. Li, L., Peng, W., Kononova, A., Kamp, K., & Cotten, S. (2021). Rethinking wearable activity trackers as assistive technologies: A qualitative study on long-term use. The 54th Hawaii International Conference on System Sciences (HICSS-54). [Link][PDF]
  3. Li, L., & Peng, W. (2020). Does Health Information Technology Promote Healthy Behaviors? The Mediating Role of Self-Regulation. Health Communication, 35(14), 1772–1781. [Link][PDF]
  4. Kononova, A., Li, L., Kamp, K., Bowen, M., Rikard, R. V., Cotten, S., & Peng, W. (2019). The use of wearable activity trackers among older adults: Focus group study of tracker perceptions, motivators, and barriers in the maintenance stage of behavior change. JMIR MHealth and UHealth, 7(4), e9832. [Link][PDF]
  5. Li, L., Peng, W., Kononova, A., Bowen, M., & Cotten, S. R. (2019). Factors associated with older adults’ long-term use of wearable activity trackers. Telemedicine and E-Health. [Link][PDF]
  6. Li, L., Peng, W., Kamp, K., Bowen, M., Cotten, S., Rikard, R.V., & Kononova, A. (2017). Poster: Understanding long-term adoption of wearable activity trackers among older adults. In Proceedings of the 2017 Workshop on Wearable Systems and Applications (pp. 33–34). ACM. [Link][PDF]