HeartCV: a tool for transferrable, automated measurement of heart rate and heart rate variability in transparent animals.

Heart function is a key component of whole-organismal physiology. Bioimaging is commonly, but not exclusively, used for quantifying heart function in transparent individuals, including early developmental stages of aquatic animals, many of which are transparent. However, a central limitation of many imaging-related methods is the lack of transferability between species, life-history stages and experimental approaches. Furthermore, locating the heart in mobile individuals remains challenging. Here, we present HeartCV: an open-source Python package for automated measurement of heart rate and heart rate variability that integrates automated localization and is transferrable across a wide range of species. We demonstrate the efficacy of HeartCV by comparing its outputs with measurements made manually for a number of very different species with contrasting heart morphologies. Lastly, we demonstrate the applicability of the software to different experimental approaches and to different dataset types, such as those corresponding to longitudinal studies.

Psychological and physiological stress and burnout among maternity providers in a rural county in Kenya: individual and situational predictors.

BACKGROUND: Stress and burnout among healthcare workers has been recognized as a global crisis needing urgent attention. Yet few studies have examined stress and burnout among healthcare providers in sub-Saharan Africa, and even fewer among maternity providers who work under very stressful conditions. To address these gaps, we examined self-reported stress and burnout levels as well as stress-related physiologic measures of these providers, along with their potential predictors. METHODS: Participants included 101 maternity providers (62 nurses/midwives, 16 clinical officers/doctors, and 23 support staff) in western Kenya. Respondents completed Cohen's Perceived Stress Scale, the Shirom-Melamed Burnout scale, and other sociodemographic, health, and work-related items. We also collected data on heart rate variability (HRV) and hair cortisol levels to assess stress-related physiologic responses to acute and chronic stress respectively. Multilevel linear regression models were computed to examine individual and work-related factors associated with stress, burnout, HRV, and cortisol level. RESULTS: 85% of providers reported moderate stress and 11.5% high stress. 65% experienced low burnout and 19.6% high burnout. Average HRV (measured as the root mean square of differences in intervals between successive heart beats: RMSSD) was 60.5 (SD = 33.0) and mean cortisol was mean cortisol was 44.2 pg/mg (SD = 60.88). Greater satisfaction with life accomplishments was associated with reduced stress (ß = - 2.83; CI = -5.47; - 0.18), while motivation to work excessively (over commitment) was associated with both increased stress (ß = 0.61 CI: 0.19, 1.03) and burnout (ß = 2.05, CI = 0.91, 3.19). Female providers had higher burnout scores compared to male providers. Support staff had higher HRV than other providers and providers under 30 years of age had higher HRV than those 30 and above. Although no association between cortisol and any predictor was statistically significant, the direction of associations was consistent with those found for stress and burnout. CONCLUSIONS: Most providers experienced moderate to high levels of stress and burnout. Individuals who were more driven to work excessively were particularly at risk for higher stress and burnout. Higher HRV of support staff and providers under age 30 suggest their more adaptive autonomic nervous system response to stress. Given its impact on provider wellbeing and quality of care, interventions to help providers manage stress are critical.