Exploring experiences and needs of perinatal women in digital healthcare: A meta-ethnography of qualitative evidence

OBJECTIVE

The aim of this review is to identify, appraise, and synthesize the available qualitative evidence on the experiences and needs of perinatal women by using digital technologies in healthcare.

METHODS

This review was consolidated following the eMERGe meta-ethnography reporting guidance. We conducted a comprehensive search in eight databases from inception to 12 October 2021. Published and unpublished qualitative and mixed-method studies published in English were included. The methodological quality was assessed using the critical appraisal skill program checklist. A meta-ethnographic synthesis was used according to Noblit and Hare's seven-step iterative process.

RESULTS

A total of 3,843 articles were retrieved, and 27 qualitative studies pertaining to 3,775 perinatal women from 13 countries across different ethnicities were included. Four overarching themes emerged for the aspect of experiences: (1) normalization of experience, (2) attainment of valuable knowledge, (3) empowerment and self-confidence boosting, and (4) beneficial features of digital platforms. For the aspect of needs, the derived themes included the following: (1) necessity of credible resources, (2) importance of personalization, (3) concern about cybersecurity, and (4) urging additional support. Our line-of-argument for interpreting the perinatal women's experiences can offer a much greater engagement in digital healthcare, while the findings on the perinatal women's needs can add value for improving the design of digital healthcare in the future.

CONCLUSION

This review offers a deeper understanding of the perinatal women's experiences and needs when using digital technologies in healthcare. Our findings provide meaningful recommendations for clinical practice and future research.

Validity of a Novel Research-Grade Physical Activity and Sleep Monitor for Continuous Remote Patient Monitoring

In the midst of the COVID-19 pandemic, Remote Patient Monitoring technologies are highly important for clinicians and researchers. These connected-health technologies enable monitoring of patients and facilitate remote clinical trial research while reducing the potential for the spread of the novel coronavirus. There is a growing requirement for monitoring of the full 24 h spectrum of behaviours with a single research-grade sensor. This research describes a free-living and supervised protocol comparison study of the Verisense inertial measurement unit to assess physical activity and sleep parameters and compares it with the Actiwatch 2 actigraph. Fifteen adults (11 males, 23.4 ± 3.4 years and 4 females, 29 ± 12.6 years) wore both monitors for 2 consecutive days and nights in the free-living study while twelve adults (11 males, 23.4 ± 3.4 years and 1 female, 22 ± 0 years) wore both monitors for the duration of a gym-based supervised protocol study. Agreement of physical activity epoch-by-epoch data with activity classification of sedentary, light and moderate-to-vigorous activity and sleep metrics were evaluated using Spearman's rank-order correlation coefficients and Bland-Altman plots. For all activity, Verisense showed high agreement for both free-living and supervised protocol of r = 0.85 and r = 0.78, respectively. For physical activity classification, Verisense showed high agreement of sedentary activity of r = 0.72 for free-living but low agreement of r = 0.36 for supervised protocol; low agreement of light activity of r = 0.42 for free-living and negligible agreement of r = -0.04 for supervised protocol; and moderate agreement of moderate-to-vigorous activity of r = 0.52 for free-living with low agreement of r = 0.49 for supervised protocol. For sleep metrics, Verisense showed moderate agreement for sleep time and total sleep time of r = 0.66 and 0.54, respectively, but demonstrated high agreement for determination of wake time of r = 0.83. Overall, our results showed moderate-high agreement of Verisense with Actiwatch 2 for assessing epoch-by-epoch physical activity and sleep, but a lack of agreement for activity classifications. Future validation work of Verisense for activity cut-point potentially holds promise for 24 h continuous remote patient monitoring.