Who is Tracking Health on Mobile Devices: Behavioral Logfile Analysis in Hong Kong

The healthy moms and babies app to prevent postpartum depression: analysis of user-profiles and dropout cases

Introduction

Perinatal depression affects mothers, babies and society. Preventive interventions are needed, but face barriers to access. E-health interventions could be an effective and accessible option. To date, few studies have attempted to understand the use of mobile health (m-health) applications and why they are not more widely used. This study aims to understand the demographic characteristics of enrolled participants and examine dropout patterns through the Healthy Moms and Babies app.

Methods

A longitudinal study was conducted with a sample of 511 women recruited between 2020 and 2022. Data were collected from the app, including sociodemographic information, the participant's progress through the modules of the app, and the permissions granted to use the app.

Results

Out of the 511 women who completed the initial form to initiate participation, 279 downloaded the app and completed the evaluation. Results indicated that granting permission to be notified about the module's availability is related to an increase in the use of the first modules.

Conclusion

This study shows the importance of establishing follow-ups in the use of mobile apps during the perinatal period.

Mobile health application for Thai women: investigation and model

Background

Women’s mobile health (m-health) applications are currently widely used for health education, medication, prevention of illness, etcetera. However, women are extremely sensitive to their design. While the number of m-health applications for women is increasing, many are of poor quality and have development issues.

Objective

This paper aims to develop and evaluate an m-health application for Thai women based on a user-centred design (UCD). Current women’s m-health applications were investigated to identify any lack of development in usability, functionality and graphical user interface. The results were evaluated and used to create criteria for the trial of a prototype application.

Methods

UCD methodology was used to design a graphical user interface, analyse the application’s functionality, and enhance its usability. Data from thirty female end-users were collected and maintained locally, and thirteen information technology (IT) experts provided feedback on the prototype trial. Interviews and questionnaires were used to gather user data and identify problems.

Results

The average scores of the evaluation by the end-users (n = 30) and IT experts (n = 13) were compared using a t-test statistical analysis. For the first version, the end-users gave higher usability scores (average = 4.440), with no statistical significance and a P value of 0.05. In comparison, lower scores for functionality were given by the IT experts (average = 4.034), with no statistical significance and a P value of 0.05. For the second version, the average scores from the end-users were higher than those from the IT experts. The highest score was related to usability (average = 4.494), with no statistical significance and a P value of 0.05. The lowest score was for the user interface from the group of IT experts (average = 4.084), with no statistical significance and a P value of 0.05.

Conclusion

A UCD was utilised to construct a process taxonomy to understand, analyse, design and develop an application suitable for Thai women. It was found from an evaluation of the currently-available women’s m-health applications that usability is their main weakness; therefore, this aspect needed to be prioritised in the new design. According to the results, IT experts’ perspective of the development of an m-health application was different from that of end-users. Hence, it was evident that both end-users and IT experts needed to be involved in helping developers to analyse, prioritise and establish a strategy for developing an m-health application, particularly one for women’s health. This would give researchers an in-depth understanding of the end-users’ expectations.

Frequency and correlates of use of applications for monitoring and increasing health and well-being in middle-aged and older adults. Findings from the German Ageing Survey

AIM

To clarify the frequency and correlates of using applications for monitoring and increase of health and well-being among middle-aged and older adults during the COVID-19 pandemic in Germany.

METHODS

Data were used from the nationally representative German Ageing Survey (n = 3,174 individuals in the analytical sample; June/July 2020). The frequency of using applications for monitoring and increasing health and well-being (from daily to never) was used as main outcome measure.

RESULTS

Among individuals with access to the internet, 76% never used applications for monitoring and increase of health and well-being, whereas about 13% were rare and 11% were frequent users of such applications. Multinomial regressions showed that the likelihood of being a rare user (compared to never users of such applications) was positively associated with being male [RRR: 0.74, 95% CI: 0.59-0.93], the frequency of walks [e.g., several times a week compared to never: RRR: 2.76, 95% CI: 1.15-6.59] and worse self-rated health [RRR: 1.33, 95% CI: 1.11-1.59]. Furthermore, the likelihood of being a frequent user (compared to never users) was positively associated with younger age [RRR: 0.96, 95% CI: 0.94-0.98] and the frequency of walks [daily compared to never: RRR: 2.61, 95% CI: 1.07-6.35].

CONCLUSIONS

Applications for monitoring and increasing health and well-being are used by about one out of four middle-aged and older individuals with access to the internet in Germany during the COVID-19 pandemic. In international comparison, the proportion of users is rather low. Determining the factors associated with such use may help to address non-users.

Characterization and Correction of Bias Due to Nonparticipation and the Degree of Loyalty in Large-Scale Finnish Loyalty Card Data on Grocery Purchases: Cohort Study

Background

To date, the evaluation of diet has mostly been based on questionnaires and diaries that have their limitations in terms of being time and resource intensive, and a tendency toward social desirability. Loyalty card data obtained in retailing provides timely and objective information on diet-related behaviors. In Finland, the market is highly concentrated, which provides a unique opportunity to investigate diet through grocery purchases.

Objective

The aims of this study were as follows: (1) to investigate and quantify the selection bias in large-scale (n=47,066) loyalty card (LoCard) data and correct the bias by developing weighting schemes and (2) to investigate how the degree of loyalty relates to food purchases.

Methods

Members of a loyalty card program from a large retailer in Finland were contacted via email and invited to take part in the study, which involved consenting to the release of their grocery purchase data for research purposes. Participants’ sociodemographic background was obtained through a web-based questionnaire and was compared to that of the general Finnish adult population obtained via Statistics Finland. To match the distributions of sociodemographic variables, poststratification weights were constructed by using the raking method. The degree of loyalty was self-estimated on a 5-point rating scale.

Results

On comparing our study sample with the general Finnish adult population, in our sample, there were more women (65.25%, 30,696/47,045 vs 51.12%, 2,273,139/4,446,869), individuals with higher education (56.91%, 20,684/36,348 vs 32.21%, 1,432,276/4,446,869), and employed individuals (60.53%, 22,086/36,487 vs 52.35%, 2,327,730/4,446,869). Additionally, in our sample, there was underrepresentation of individuals aged under 30 years (14.44%, 6,791/47,045 vs 18.04%, 802,295/4,446,869) and over 70 years (7.94%, 3,735/47,045 vs 18.20%, 809,317/4,446,869), as well as retired individuals (23.51%, 8,578/36,487 vs 31.82%, 1,414,785/4,446,869). Food purchases differed by the degree of loyalty, with higher shares of vegetable, red meat & processed meat, and fat spread purchases in the higher loyalty groups.

Conclusions

Individuals who consented to the use of their loyalty card data for research purposes tended to diverge from the general Finnish adult population. However, the high volume of data enabled the inclusion of sociodemographically diverse subgroups and successful correction of the differences found in the distributions of sociodemographic variables. In addition, it seems that food purchases differ according to the degree of loyalty, which should be taken into account when researching loyalty card data. Despite the limitations, loyalty card data provide a cost-effective approach to reach large groups of people, including hard-to-reach population subgroups.

An opportunity for patient-centered care: Results from a secondary analysis of sex- and gender-based data in mobile health trials for chronic medical conditions

Traditional medical practice has suffered from male bias, which can lead to sub-optimal treatment options for female patients and increase the incidence of severe side-effects in this population. Mobile health applications, mHealth apps, represent one essential component of the shift towards consumer-centered self-administered individualized health. To prevent sex-specific bias it is important that trials consider sex and gender when developing mHealth apps. We evaluated the inclusion and reporting of sex and gender at all levels in mHealth randomized controlled trials (RCTs). To this end, we conducted a secondary analysis of a large study database addressing the effectiveness of app interventions on clinical outcomes in patients with chronic medical conditions. We followed the 5 steps described in the framework by Arksey and O'Malley and the guidelines of the PRISMA-ScR. Of the 72 app-based RCTs which reported information about sex overall, 62 included individuals of both sexes. The concept of gender was not addressed in any of the studies. The consideration of sex aspects in the design, execution and reporting of mHealth RCTs was minimal or absent. To adequately address the health and preventative needs of the mHealth user population, sex and gender should be systematically included in the research, development and evaluation of mHealth applications.