Smartphone Users' Persuasion Knowledge in the Context of Consumer mHealth Apps: Qualitative Study

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.

Smartphone application use patterns for mental health disorders: A systematic literature review and meta-analysis

BACKGROUND

Mobile mental health applications play a significant role in mental health care to fill gaps in care for mental disorders. Despite the growth in mobile phone apps for mental health conditions, patients' mental health smartphone application use, perceived usefulness, and future interest in using apps for mental disorders have not been systematically examined.

METHODS

The authors designed and conducted this systematic review and meta-analysis according to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement. Articles reporting mobile/smartphone applications used for mental disorders describing ownership, application use, perceived helpfulness, future interest to use, use patterns, and attitudes were included. PubMed/MEDLINE, EMBASE, PsychINFO, Scopus, and Google Scholar were searched. Published articles from 2014 up to October 2022 were included. The methodological quality was assessed using the Joanna Briggs Institute critical appraisal tool. The heterogeneity test, publication bias, funnel plots and Egger's test were applied. The outcome was calculated by metaprop command using a random-effects model.

RESULTS

Ten studies met the eligibility criteria. The pooled prevalence of smartphone ownership, application use for current mental health disorders, perceived usefulness, and future interest in using the app for their mental health problem was 88.63%, 23.29%, 72.80%, and 78.97%, respectively. Heterogeneity and publication bias were detected.

CONCLUSIONS

The results of this study indicate that despite a considerable number of smartphone users, perceived usefulness, and future interest in using smartphone mental health applications among patients with mental disorders, only about one-fifth use an application for mental health disorders. The results show that there is a large potential to increase the use of apps for patients to support self-care in the growing era of digital mental health. Further research with consumers and mental health professionals is recommended to address barriers and improve mhealth app utilization.

REGISTRATION

Prospero international prospective register of systematic reviews with ID: CRD42022359416.

Importance-performance analysis in fitness apps. A study from the viewpoint of gender and age

Background

We are currently undergoing a profound process of digital transformation that has favoured the development and use of apps in multiple facets of people's daily lives. In the fitness industry, this situation has facilitated the control of exercise and the maintenance of healthier lifestyles. However, it is not known how the perceived quality and importance of fitness apps vary for users based on gender and age, which is the objective of this study conducted among users of fitness centres.

Methods

By means of a convenience sample, 321 users from different centres of the boutique fitness chain Sano Centre (238 females and 83 males) took part in the study. They answered the 16 items of the MARS scale, distributed in four dimensions, in terms of importance and perceived quality. The existence of significant differences was analysed using non-parametrical statistics such as the U-Mann-Whitney (gender) and the H-Kruskal-Wallis (age). In addition, a cluster analysis, combining hierarchical and non-hierarchical methods, was analysed considering as a dependent variable the level of recommendation of fitness apps.

Results

Considering gender, in importance-performance analysis (IPA), credibility was the most important attribute for females and quality of information for males. In the case of age, credibility was the most important attribute in all the ranges. The cluster analysis established two groups (high and low recommendations of the fitness app). In importance, the first group scored better on all factors except entertainment and interest. In valuation, the scores were lower than on importance, especially in the low recommendation group.

Conclusion

Regarding usage behaviour, credibility is the factor to which users attach the highest importance and rating, regardless of gender and age. The main demand focuses on improving the gestural design and visual appeal, which will facilitate a better user experience.

Young adults' adoption and use of mental health apps: efficient, effective, but no replacement for in-person care

Objective: Millions of people use mobile phone or computer-based applications-apps-to maintain their mental health and connect with treatment providers through text- and video-based chat functions. The present study sought to understand young adults' motivations for adopting this technology using the unified theory of acceptance and use of technology (UTAUT), how they use mental health apps, and the gratifications they receive from using mental health apps. Participants: One hundred-eighteen mental health app users responded to an online survey. Methods: A survey was conducted with students at a Midwestern university. The survey included questions regarding current mental health services, mental health apps used, UTAUT and gratifications survey items. Results: A regression analysis suggested users' performance expectancies, effort expectancies, and facilitating conditions predicted the adoption of mental health apps. Young adults most often use mental health apps for stress relief. While they preferred in-person treatment, users described mental health apps as efficient and helpful. Conclusion: Overall, the results reinforce the sense of optimism for the future of mental health apps, suggesting the potential for apps to supplement-but not necessarily replace-in-person care.

Smartphones dependency risk analysis using machine-learning predictive models

Recent technological advances have changed how people interact, run businesses, learn, and use their free time. The advantages and facilities provided by electronic devices have played a major role. On the other hand, extensive use of such technology also has adverse effects on several aspects of human life (e.g., the development of societal sedentary lifestyles and new addictions). Smartphone dependency is new addiction that primarily affects the young population. The consequences may negatively impact mental and physical health (e.g., lack of attention or local pain). Health professionals rely on self-reported subjective information to assess the dependency level, requiring specialists' opinions to diagnose such a dependency. This study proposes a data-driven prediction model for smartphone dependency based on machine learning techniques using an analytical retrospective case-control approach. Different classification methods were applied, including classical and modern machine learning models. Students from a private university in Cali-Colombia (n = 1228) were tested for (i) smartphone dependency, (ii) musculoskeletal symptoms, and (iii) the Risk Factors Questionnaire. Random forest, logistic regression, and support vector machine-based classifiers exhibited the highest prediction accuracy, 76-77%, for smartphone dependency, estimated through the stratified-k-fold cross-validation technique. Results showed that self-reported information provides insight into predicting smartphone dependency correctly. Such an approach opens doors for future research aiming to include objective measures to increase accuracy and help to reduce the negative consequences of this new addiction form.

A survey of women’s experiences of using period tracker applications: Attitudes, ovulation prediction and how the accuracy of the app in predicting period start dates affects their feelings and behaviours

Introduction:

Using an online survey, the aim of this study was to ask women about their real-life experiences of using period tracker apps, their attitudes towards using their app, the information the app provided regarding ovulation and how the accuracy of the app in predicting period start dates affects their feelings and behaviours if their period comes earlier or later than predicted.

Methods:

This mixed-methods observational study was conducted by an online survey of 50 multiple-choice and open-ended questions. The survey was generated with Qualtrics XM^® and promoted via social media. It was open to any person who had used a period tracker.

Results:

From 375 total responses, 330 complete responses were obtained, giving a completion rate of 88.0%. Respondents were aged between 14 and 54, with a mean age of 26.0 (±7.81). When asked what was the best thing about using the app, 29.7% (98/330) of respondents selected ‘To know when I’m ovulating’. Respondents were asked if their period ever started earlier than the app predicted; 54.9% (189/330) said it had and 72.1% (238/330) said it had started later than predicted. When asked how they felt if their period arrived earlier or later than expected, thematic analysis of periods starting earlier revealed four themes: feeling unaffected, being frustrated/unprepared, feeling anxious/stressed and feeling confused/intrigued. Thematic analysis when their period arrived later revealed six themes: anxious/concerned about pregnancy, disappointed about pregnancy, seeking advice/informing healthcare professionals, thoughts about menopause, feeling unaffected and being better prepared.

Conclusion:

Period trackers need to be clearer on their intended use and reliability, especially for period due date and ovulation. Qualitative analysis shows the impact of inaccurate predictions on aspects of the users’ health. This study calls for period tracker app companies to update their apps to provide transparency to their users about their intended use and capabilities.

Dementia Caregiver Experiences and Recommendations for Using the Behavioral and Environmental Sensing and Intervention System at Home: Usability and Acceptability Study

Background

Caregiver burden associated with dementia-related agitation is one of the most common reasons for a community-dwelling person living with dementia to transition to a care facility. The Behavioral and Environmental Sensing and Intervention (BESI) for the Dementia Caregiver Empowerment system uses sensing technology, smartwatches, tablets, and data analytics to detect and predict agitation in persons living with dementia and to provide just-in-time notifications and dyad-specific intervention recommendations to caregivers. The BESI system has shown that there is a valid relationship between dementia-related agitation and environmental factors and that caregivers prefer a home-based monitoring system.

Objective

The aim of this study is to obtain input from caregivers of persons living with dementia on the value, usability, and acceptability of the BESI system in the home setting and obtain their insights and recommendations for the next stage of system development.

Methods

A descriptive qualitative design with thematic analysis was used to analyze 10 semistructured interviews with caregivers. The interviews comprised 16 questions, with an 80% (128/160) response rate.

Results

Postdeployment caregiver feedback about the BESI system and the overall experience were generally positive. Caregivers acknowledged the acceptability of the system by noting the ease of use and saw the system as a fit for them. Functionality issues such as timeliness in agitation notification and simplicity in the selection of agitation descriptors on the tablet interface were identified, and caregivers indicated a desire for more word options to describe agitation behaviors. Agitation intervention suggestions were well received by the caregivers, and the resulting decrease in the number and severity of agitation events helped confirm that the BESI system has good value and acceptability. Thematic analysis suggested several subjective experiences and yielded the themes of usefulness and helpfulness.

Conclusions

This study determined preferences for assessing caregiver strain and burden, explored caregiver acceptance of the technology system (in-home sensors, actigraph or smart watch technology, and tablet devices), discerned caregiver insights on the burden and stress of caring for persons living with dementia experiencing agitation in dementia, and solicited caregiver input and recommendations for system changes. The themes of usefulness and helpfulness support the use of caregiver knowledge and experience to inform further development of the technology.