Category: Health Information Technology Studies

In the new article “Exploring the Role of Social Support in Promoting Patient Participation in Health Care Among Women with Breast Cancer” in the journal Health Communication, the Health Information Technology Studies (HITS) group studied how social factors influence a patient’s participation in health care.

Abstract:Scholars have adopted Street’s (2003) ecological model of communication in medical encounters to investigate the factors promoting patient participation in health care. However, factors demonstrated in the ecological model were bounded in the context of medical care primarily focusing on health care providers and patients. Social factors, such as patients’ relationships and supportive communication with others outside the context of health care remain relatively unexplored. To expand the purview of our understanding of factors that influence patient participation, this research integrated social support literature into the research on physician-patient communication and proposed a model which described a process through which social support can enhance patient participation in health care. The data analyzed in this study were a part of two larger clinical trials in which 661 women with breast cancer were recruited from three cancer institutions in the United States. The results from structural equation modeling analysis from cross-sectional and longitudinal data provided strong evidence for the hypotheses predicting that perceived social support was positively associated with health information competence, which in turn fully mediated the association between social support and patient participation in health care. Theoretical and practical implications are discussed.

Full citation: “Exploring the Role of Social Support in Promoting Patient Participation in Health Care Among Women with Breast Cancer,” Mengfei Guan, Jeong Yeob Han, Dhavan V. Shah and David H. Gustafson, D. H., Health Communication, DOI: 10.1080/10410236.2020.1773704.

Access the article: https://pubmed.ncbi.nlm.nih.gov/32500731/

Researchers at the University of Wisconsin—Madison have received a $3.42 million grant from the National Institutes of Health to develop a mobile phone-based app to prevent opioid relapse among those trying to recover.

The project builds on the prior work that Dhavan Shah, Louis A. & Mary E. Maier-Bascom Professor in UW-Madison’s School of Journalism and Mass Communication, and John Curtin, director of clinical training in Department of Psychology, have done detecting and predicting relapse.

The broad goals of this project are to develop and deliver models to forecast the day-by-day probability of opioid and other drug use among people trying to abstain from drugs while in recovery. This lapse risk prediction model will generated using the Addiction-Comprehensive Health Enhancement Support System (A-CHESS) mobile app, a tool developed by researchers in the UW’s Center for Health Enhancement System Studies.

The study will focus on about 500 participants who are abstaining from drug use while in recovery. The study will follow 12 months of their recovery, with observations occurring as early as one-week post-abstinence and as late as 18 months post-abstinence across participants in the sample.

“Relapse can happen early in recovery for alcohol and substance use disorders, but it can also happen months, and even years, after someone quits,” Curtin says. “One of the biggest challenges that people with alcohol and substance use disorders have is to continually monitor their recovery and look out for risks for relapse, essentially for the rest of their lives.”

While relapse often seems to come out of the blue from the perspective of the participant, Shah says, hindsight often yields indicators that the individual was a risk. The clues can come from what they post, who they talk with, and the places they frequent.

“Over the past five years, we have been working to use emerging mobile sensing capabilities from smartphones and wearable sensors to build models that can predict, in real-time, the likelihood that someone will lapse back to drug use,” Shah says. Working with his students, he recently published two articles predicting the risk of relapse based solely on the language that participants used while engaging with the A-CHESS system.

Curtin’s lab is about to complete a first project that has followed people with alcohol use disorder for the first 3 months of their sobriety and can predict with better than 80 percent accuracy whether they will use alcohol on any given day. Using cell phone communications, including voice calls and texts, and GPS data to establish locations where individuals have used alcohol in the past, the researchers can monitor signals about the integrity of an individual’s recovery and abstinence.

“More importantly, we can do this with almost complete passiveness, with no burden placed on the individual,” Curtin says.

Two journal articles from the HITS (Health Information Technology Studies) team, one published in Health Communication and the other in Health Education Research, tackle the role of information technologies in health disparities.

The Health Communication paper led by Juwon Hwang, “Health Information Sources, Perceived Vaccination Benefits, and Maintenance of Childhood Vaccination Schedules,” investigates the associations between evaluations of health information sources, parental perceptions of childhood vaccination benefits, and the maintenance of vaccination schedules for their children. Analyzing a sample of 4,174 parents who have at least one child under the age of 18, including 138 with a childhood autism diagnosis. The study finds social media are negatively associated with their perceptions of vaccination benefits compared with TV, magazines, and interpersonal talk.  The full citation is below:

• Hwang, J., & Shah, D. V. (2018). Health Information Sources, Perceived Vaccination Benefits, and Maintenance of Childhood Vaccination Schedules. Health Communication, 1-10.

The paper led by Dami Ko, “Physical Activity in Persons with Diabetes: Its Relationship with Media Use for Health Information, Socioeconomic Status and Age,” analyzes national survey data of 770 persons with diabetes distinguished into either a low or high SES group. Results reveal television use was associated with increased physical activity levels, whereas Internet use was associated with decreased physical activity, especially in older, low SES persons with diabetes. The findings suggest media targeting strategies to provide PA-related information to low SES persons with diabetes. The full citation is below:

• Ko, D., Myung, E., Moon, T. J., & Shah, D. V. (2019). Physical activity in persons with diabetes: its relationship with media use for health information, socioeconomic status and age. Health Education Research.