Person-Generated Health Data in Women's Health: Protocol for a Scoping Review

Effectiveness of mobile applications in improving insomnia symptoms among adults from multi-community: A systematic review and meta-analysis

OBJECTIVE/BACKGROUND

To clarify whether mobile sleep applications alleviate insomnia symptoms among adults from multi-community.

PATIENTS/METHODS

A literature search was conducted using the PubMed, Cochrane, PsycINFO, and Web of Science databases for articles related to mobile technology and sleep interventions published between database inceptions and March 27, 2023. We pooled relevant data using a random-effects model, and a meta-analysis was performed using a web version of the Cochrane Review Manager. The effect size was estimated and reported as the combined overall effect (weighted average). Forest plots were created, and the Cochrane risk-of-bias tool and Newcastle-Ottawa Scale were used to evaluate studies.

RESULTS

After an initial screening and full-text reviews, seven studies were identified with a total of 10,139 participants (females n = 8844, 87.2 %) recruited from multi-community and not diagnosed with sleep disorders or taking medications. These studies included one cross-sectional study investigating mindfulness meditation apps and six randomized-controlled trials (RCTs), including one with sleep-feedback messaging, one comparing sleep applications with or without a wearable device, and four with multicomponent interventions based on cognitive theory and subsequent behavioral change techniques. In a meta-analysis of three cognitive behavior therapy (CBT)-based RCTs, the intervention group showed statistically significant improvements in insomnia symptoms according to the Pittsburgh Sleep Quality Index but with high heterogeneity, while two CBT-based RCTs showed no significant improvements in the Insomnia Severity Index with low heterogeneity.

CONCLUSIONS

A small body of evidence supports the use of CBT-based sleep applications to improve insomnia symptoms among adults from multi-community.

Person-Generated Health Data in Women's Health: Scoping Review

BACKGROUND

The increased pervasiveness of digital health technology is producing large amounts of person-generated health data (PGHD). These data can empower people to monitor their health to promote prevention and management of disease. Women make up one of the largest groups of consumers of digital self-tracking technology.

OBJECTIVE

In this scoping review, we aimed to (1) identify the different areas of women's health monitored using PGHD from connected health devices, (2) explore personal metrics collected through these technologies, and (3) synthesize facilitators of and barriers to women's adoption and use of connected health devices.

METHODS

Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for scoping reviews, we searched 5 databases for articles published between January 1, 2015, and February 29, 2020. Papers were included if they targeted women or female individuals and incorporated digital health tools that collected PGHD outside a clinical setting.

RESULTS

We included a total of 406 papers in this review. Articles on the use of PGHD for women steadily increased from 2015 to 2020. The health areas that the articles focused on spanned several topics, with pregnancy and the postpartum period being the most prevalent followed by cancer. Types of digital health used to collect PGHD included mobile apps, wearables, websites, the Internet of Things or smart devices, 2-way messaging, interactive voice response, and implantable devices. A thematic analysis of 41.4% (168/406) of the papers revealed 6 themes regarding facilitators of and barriers to women's use of digital health technology for collecting PGHD: (1) accessibility and connectivity, (2) design and functionality, (3) accuracy and credibility, (4) audience and adoption, (5) impact on community and health service, and (6) impact on health and behavior.

CONCLUSIONS

Leading up to the COVID-19 pandemic, the adoption of digital health tools to address women's health concerns was on a steady rise. The prominence of tools related to pregnancy and the postpartum period reflects the strong focus on reproductive health in women's health research and highlights opportunities for digital technology development in other women's health topics. Digital health technology was most acceptable when it was relevant to the target audience, was seen as user-friendly, and considered women's personalization preferences while also ensuring accuracy of measurements and credibility of information. The integration of digital technologies into clinical care will continue to evolve, and factors such as liability and health care provider workload need to be considered. While acknowledging the diversity of individual needs, the use of PGHD can positively impact the self-care management of numerous women's health journeys. The COVID-19 pandemic has ushered in increased adoption and acceptance of digital health technology. This study could serve as a baseline comparison for how this field has evolved as a result.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/26110.

Effectiveness of mHealth interventions to promote physical activity and reduce sedentary behaviours on work-related productivity and performance: a systematic review protocol

INTRODUCTION

Technologies such as health and fitness applications (apps) and wearable activity trackers have recently gained popularity and may play a key role in promoting physical activity and reducing sedentary behaviours. Although several systematic reviews have investigated their efficacy in physical activity and sedentary behaviours, few studies have focused on their impact on work-related outcomes among workers. Here, to explore the effects of mHealth interventions designed to encourage physical activity and decrease sedentary behaviours on work-related outcomes, including absenteeism, presenteeism, productivity, work performance and workability among workers, we will conduct a systematic review based on recent articles and an extensive literature search.

METHODS AND ANALYSIS

The literature search will be performed using PubMed, Web of Science, the Cochrane Library and the Japan Medical Abstracts Society from inception to 23 September 2023. We will select studies that (1) investigated the impact of mHealth interventions to promote physical activity and reduce sedentary behaviours on work-related outcomes such as absenteeism, presenteeism, productivity, work performance and workability; (2) were designed as a randomised controlled trial (RCT) or non-randomised study of interventions (NRSI); (3) were conducted among workers and (4) were published as full-text original articles in Japanese or English. We will assess the review quality with the AMSTAR 2 tool. The risk of bias will be assessed with the RoB tool 2.0 and ROBINS-I.

ETHICS AND DISSEMINATION

Ethical approval is unnecessary as the study will rely solely on previously published articles. The research results will be submitted for publication in a peer-reviewed scientific journal.

TRIAL REGISTRATION NUMBER

The study protocol has been registered with the UMIN Clinical Trials Registry (ID=UMIN000052290).

Experiences of users of period tracking apps: which app, frequency of use, data input and output and attitudes

RESEARCH QUESTION

What are the experiences of users of period tracking apps in relation to which apps they use, their frequency of use, the type of data and their attitudes to period tracking apps?

DESIGN

This was an observational mixed-methods study using an online survey designed using Qualtrics XM. The survey included 50 open-ended and multiple choice questions, but only specific questions were analysed in this study. The survey was promoted via social media for 22 days between 30 June and 21 July 2021.

RESULTS

Of the 375 total participants, 326 responses were complete and included in analysis. In the results section further down, this is explained as 330 complete responses, with 4 additional responses excluded due to data inconsistencies. The participants' age range was 14-54 years, with a mean of 26.0 (±7.81) years. Most participants (61.9%) had been using a period tracking app for 2 years or longer. Of these 85.6% entered more data when on their period, 31% at a frequency of once a day. There were approximately equivalent proportions of participants who felt that entering data into their app was either 'part of their normal routine' (43.3%) or 'not a priority' (38.0%). Thematic analysis of the participants' experiences of using period-tracking apps revealed five main themes: symptom tracking and understanding general health; concerns with period start date predictions; the problems with fertility tracking; concerns about cost; and concerns about data privacy.

CONCLUSIONS

The infrequency of data inputting and the wide range of symptoms tracked reflects the differing needs of participants from their period-tracking apps. This highlights the need for increased education and research into understanding the realities of variations in using apps.