1 of 1

1Northwestern University Feinberg School of Medicine

Background

  • Participants responded to 72.0% of all EMA prompts and completed a total of 588 EMA surveys

​

  • Participants wore the ECG patch for an average of 6.6 days

​

  • 80.9% of the 5-minute HRV intervals captured during the EMA period were valid (i.e., artifact levels ≤ 5%)

​

  • All participants except one (n=34) reported both stressful and non-stressful experiences while wearing the patch
  • These findings demonstrate that it is feasible to measure stress reactivity by combining EMA and short-term continuous heart rate monitoring via an ECG patch

​

  • Future work should adjust for physical activity, time of day, and recent food consumption in the stress reactivity model

Objective

Methods

Table 2. Stress Reactivity Scores

Results

Conclusions and Future Directions

Feasibility of Using Ecological Momentary Assessment and Continuous Heart Rate Monitoring to Measure Stress Reactivity in Natural Settings

Jessica Yang, BA1, Jay N. Patel, MD1, Kiarri N. Kershaw, PhD, MPH1

Department of Preventive Medicine, Feinberg School of Medicine

​

  • The way people respond to stressful situations (i.e., stress reactivity) varies widely due to differences in environments, cultural norms, and financial constraints

​

  • Researchers typically measure stress reactivity in controlled, laboratory settings, but this is problematic because laboratory stressors cannot capture the variety, severity, or duration of stressors that individuals face in their daily lives

​

  • Capturing the context surrounding stressful experiences is critical for identifying salient targets for intervention

aParticipants were asked how hard it was for them to pay for the very basics like food and heating. High financial burden included the responses “very hard,” “hard,” and “somewhat hard.” Low financial burden included the response “not very hard.”

​

  • To examine the feasibility of using Ecological Momentary Assessment (EMA) and an electrocardiogram (ECG) patch to develop a measure of autonomic stress reactivity in natural settings
  • 35 women (ages 23-51) wore an ECG monitor (Figure 1) and completed surveys on a smartphone about their stressful experiences four times/day for seven consecutive days

​

  • Stressful experience was defined as the presence of at least one stressor during the EMA survey prompt

​

​

Characteristics

N = 35

Age (SD)

36.6 (7.2)

BMI (SD)

30.6 (5.8)

Race/ethnicity [n, (%)]

​

NH white

20 (57.1)

NH black

5 (14.3)

Hispanic

9 (25.7)

HRV measures (SD)

​

RMSSD (ms)

31.2 (19.2)

STD RR (ms)

38.0 (16.6)

​

N

RMSSD (ms)

STD RR (ms)

Mean (SD)

t-value

p-value

Mean (SD)

t-value

p-value

Financial Burdena

​

​

2.41

0.02

​

2.64

0.01

High

9

-0.09 (0.12)

 

 

-0.09 (0.14)

 

 

Low

25

0.03 (0.12)

 

 

0.02 (0.10)

 

 

Education

​

​

-0.57

0.57

​

-0.50

0.62

Less than a

bachelor’s

degree

7

0.02 (0.15)

​

​

0.01 (0.14)

​

​

Bachelor’s

degree

or higher

27

-0.01 (0.12)

​

​

-0.01 (0.11)

​

​

Table 1. Sample Demographics and HRV Characteristics

Abbreviations: ms = milliseconds, SD = standard deviation, RMSSD = root mean square of successive RR interval difference, STD RR = standard deviation of RR intervals

Figure 1. Cardea SOLO monitor

Figure 2. Inter-beat-interval (RR) series

  • Calculated two measures of heart rate variability (HRV)—root mean square of successive RR differences (RMSSD) and standard deviation of RR intervals (STD RR)—during the 5 minutes after the start of the EMA survey (Figure 2)

​

  • Participant-specific stress reactivity scores were derived using linear mixed models from the differences in 5-minute HRV for prompts when participants did and did not report stressful experiences