SELF-MONITORING HEART RATE BIOFEEDBACK: A SECONDARY PREVENTION STRATEGY FOR MANAGING ANXIETY IN COLLEGE STUDENTS

Abstract

Intro: Anxiety is often a chronic condition that will affect approximately 29% of individuals during their lifetimes (Dennis & O’Toole, 2014). Unfortunately, numerous barriers to treatment exist, especially when treating children (Dennis & O’Toole, 2014). Wearable technology, particularly utilizing heart rate monitoring, can potentially aid in the treatment of anxiety, allowing for greater recognition of symptoms and interventions in any setting. Hypothesis: Hypothesis one: College students with mild to moderate levels of anxiety will be able to utilize self-monitoring heart rate biofeedback (SMHRB) consistently (e.g., respond to at least 70% of Maximum HR alerts utilizing relaxation breathing). Hypothesis two: participants who consistently implement relaxation breathing in response to a Maximum HR alert will significantly reduce symptoms of anxiety from baseline levels on a global anxiety scale. Methods: A series of individual AB designs were used with random assignment to baseline phases to track 7 participants on a global measure of anxiety (CUXOS). Participants with mild to moderate anxiety were measured in pre-baseline, baseline, and intervention phases to examine change due to the self-monitoring heart rate biofeedback intervention. After the baseline phases were completed, participants were trained to use the wrist-worn heart rate monitor to assist with the identification and remediation of symptoms of anxiety. In addition to reporting their weekly CUXOS score through a Google Form via a text message, participants also reported usage information two times daily. Results: The intervention was considered Effective for four out of seven participants (57%), while it was considered Ineffective for two out of seven (29%) and Minimally Effective for one out of seven (14%). The 4/7 participants who responded well to treatment showed an average reduction on the CUXOS of 15 points. Moreover, most participants (5/7) showed a favorable increase in HRV, which also corresponded to a decrease in CUXOS scores. All seven participants reported the intervention was easy to use, helpful, and that they would continue to use a version of it in the future. However, four out of seven participants stated they had some trouble with the device initially, and three participants noted that the flashing red light (HR alert) sometimes contributed to anxiety. In the reporting of usage information, just under half of all twice daily text message data was submitted by participants on average. This usage data revealed that participants reported wearing the device 90 % of the time during their intervention periods. Of all the heart rate alerts participants received, 37% of them corresponded with subjective feelings of anxiety. Participants intervened with anxiety using the intervention 83% of the indicated times. Conclusion: Wearable biofeedback interventions may be promising. However, key design features are essential to consider for future research. The ideal design for future research would include using a device compatible with automatic collection of usage and biofeedback data and the use of multiple control groups to verify effective components of an intervention. Lastly, improving the correlation between physiological measures such as heart rate alerts and subjective emotional states is essential. Improving the accuracy of devices may be accomplished through the use of more complex alert measures such as HRV instead of HR. Alternatively, an extended reporting period, whereby users allow HR measures to become more reliable and provide feedback to researchers in order to select a more accurate beats per minute (BPM) threshold that indicates increased anxiety, could be promising