Ask PCOS: Identifying Need to Inform Evidence-Based App Development for Polycystic Ovary Syndrome

Polycystic Ovary Syndrome and the Internet of Things: A Scoping Review

Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder impacting women's health and quality of life. This scoping review explores the use of the Internet of Things (IoT) in PCOS management. Results were grouped into six domains of the IoT: mobile apps, social media, wearables, machine learning, websites, and phone-based. A further domain was created to capture participants' perspectives on using the IoT in PCOS management. Mobile apps appear to be useful for menstrual cycle tracking, symptom recording, and education. Despite concerns regarding the quality and reliability of social media content, these platforms may play an important role in disseminating PCOS-related information. Wearables facilitate detailed symptom monitoring and improve communication with healthcare providers. Machine learning algorithms show promising results in PCOS diagnosis accuracy, risk prediction, and app development. Although abundant, PCOS-related content on websites may lack quality and cultural considerations. While patients express concerns about online misinformation, they consider online forums valuable for peer connection. Using text messages and phone calls to provide feedback and support to PCOS patients may help them improve lifestyle behaviors and self-management skills. Advancing evidence-based, culturally sensitive, and accessible IoT solutions can enhance their potential to transform PCOS care, address misinformation, and empower women to better manage their symptoms.

Current Use and Discrepancies in the Adoption of Health-Related Internet of Things and Apps Among Working Women in Japan: Large-Scale, Internet-Based, Cross-Sectional Survey

BACKGROUND

Demographic changes and a low birth rate have led to a workforce shortage in Japan. To address this issue, the government has promoted engagement of female employment. However, increased female employment can impact women's health. Using Internet of Things (IoT) and apps to manage women's health has gained attention, but few studies have focused on working women.

OBJECTIVE

This study aimed to clarify the current situation of working women and their use of IoT or apps to manage their health.

METHODS

A large-scale, nationwide internet survey was conducted among 10,000 female participants aged from 20 years to 64 years in Japan. Participants were recruited from a marketing research company's active survey panel of 5.24 million members. The survey included questions about health status, sociodemographic factors, psychological characteristics, and the use of IoT or apps for health management. We compared perceived health status and reasons for current IoT use using t tests and assessed participant characteristics that predicted IoT use using the C5.0 decision tree algorithm. Ethical approval was granted by St. Luke's International University.

RESULTS

Among participants, 14.6% (1455/10,000) currently used IoT or apps, 7% (695/10,000) used them previously, and 78.5% (7850/10,000) had never used them. Current users (42.7 years old) were older than past users (39.7 years old). Discrepancies were observed between participants' perceived health problems and the purpose for using IoT or apps, with 21.3% (2130/10,000) of all women reporting they experienced menstrual symptoms or disorders but only 3.5% (347/10,000) used IoT or apps to manage the same symptom. On the other hand, current users were more likely to use IoT or apps to manage nutrition-related problems such as underweight or obesity (405/1455, 27.8%). Device use was highest among current users, with 87.3% (1270/1455) using smartphones, 19.7% (287/1455) using smartwatches, and 13.3% (194/1455) using PCs. Decision tree analysis identified 6 clusters, the largest consisting of 81.6% (5323/6523) of non-IoT users who did not exercise regularly, while pregnant women were more likely to use IoT or apps.

CONCLUSIONS

Our findings highlight the idea that woman with particular health problems (ie, menstrual symptoms or disorders and premenstrual syndrome) have lower use of IoT or apps, suggesting an unmet need for IoT and apps in specific areas.

Nutritional management recommendation systems in polycystic ovary syndrome: a systematic review

BACKGROUND

People with polycystic ovary syndrome suffer from many symptoms and are at risk of developing diseases such as hypertension and diabetes in the future. Therefore, the importance of self-care doubles. It is mainly to modify the lifestyle, especially following the principles of healthy eating. The purpose of this study is to review artificial intelligence-based systems for providing management recommendations, especially food recommendations.

MATERIALS AND METHODS

This study started by searching three databases: PubMed, Scopus, and Web of Science, from inception until 6 June 2023. The result was the retrieval of 15,064 articles. First, we removed duplicate studies. After the title and abstract screening, 119 articles remained. Finally, after reviewing the full text of the articles and considering the inclusion and exclusion criteria, 20 studies were selected for the study. To assess the quality of articles, we used criteria proposed by Malhotra, Wen, and Kitchenham. Out of the total number of included studies, seventeen studies were high quality, while three studies were moderate quality.

RESULTS

Most studies were conducted in India in 2021. Out of all the studies, diagnostic recommendation systems were the most frequently researched, accounting for 86% of the total. Precision, sensitivity, specificity, and accuracy were more common than other performance metrics. The most significant challenge or limitation encountered in these studies was the small sample size.

CONCLUSION

Recommender systems based on artificial intelligence can help in fields such as prediction, diagnosis, and management of polycystic ovary syndrome. Therefore, since there are no nutritional recommendation systems for these patients in Iran, this study can serve as a starting point for such research.

Developing a Novel Web-Based Self-Management Support Intervention for Polycystic Ovary Syndrome: Mixed Methods Study With Patients and Health Care Professionals

BACKGROUND

Polycystic ovary syndrome (PCOS) represents a significant global health burden requiring urgent attention. This common chronic endocrine and cardiometabolic condition affects around 1 in 10 women and individuals assigned female at birth, with significant adverse effects on well-being, quality of life, and mental health, as well as serious and complex long-term health consequences. International guidelines for best health care practice recommend the provision of comprehensive cognitive behavioral interventions to support self-management and improve health outcomes for those living with PCOS. Web-based health interventions have the potential to meet this need in an accessible and scalable way.

OBJECTIVE

We aim to identify barriers to self-management and psychological well-being in women with PCOS and adapt a web-based self-management program to provide a prototype digital support intervention for them.

METHODS

We adapted an existing support program (HOPE) for PCOS using the antecedent target measure approach. We conducted qualitative interviews with 13 adult women living with PCOS, 3 trustees of a patients with PCOS advocacy charity, and 4 endocrinologists to identify "antecedents" (barriers) to self-management and psychological well-being. Framework analysis was used to identify potentially modifiable antecedents to be targeted by the novel intervention. At a national conference, 58 key stakeholders (patients and health professionals) voted for the antecedents they felt were most important to address. We used research evidence and relevant theory to design a prototype for the PCOS intervention.

RESULTS

Voting identified 32 potentially modifiable antecedents, relating to knowledge, understanding, emotions, motivation, and behaviors, as priorities to be targeted in the new intervention. A modular, web-based prototype HOPE PCOS intervention was developed to address these, covering six broad topic areas (instilling HOPE for PCOS; managing the stress of PCOS; feeding your mind and body well; body image, intimacy, and close relationships; staying healthy with PCOS; and keeping PCOS in its place).

CONCLUSIONS

We identified barriers to self-management and psychological well-being in women with PCOS and used these to adapt a web-based self-management program, tailoring it for PCOS, which is a comprehensive group intervention combining education, empowerment, lifestyle management, peer support with cognitive behavioral tools, and goal-setting (to be delivered by peers or codelivered with health care professionals). The modular structure offers flexibility to adapt the program further as new clinical recommendations emerge. The intervention has the potential to be delivered, evaluated for feasibility, and, if effective, integrated into health care services. Self-management interventions are not designed to replace clinical care; rather, they serve as an additional source of support. The HOPE PCOS program conveys this message in its content and activities. Future research should evaluate the prototype intervention using primary outcomes such as measures of psychological well-being, self-management self-efficacy, depression, anxiety, and PCOS-related quality of life. They should also assess the intervention's acceptability, scalability, and cost-effectiveness.

PCOS health-related quality-of-life and depressive symptoms across the lifespan: Comparative study

The purpose of this cross-sectional study was to compare health-related quality of life (HRQoL) and depressive symptoms among peri-postmenopausal women with polycystic ovary syndrome (PCOS) aged ≥43 years relative to premenopausal women with PCOS aged 18-42 years. An online survey link comprising questionnaires about demographics, HRQoL, and depressive symptoms was posted onto two PCOS-specific Facebook groups. Respondents (n = 1,042) were separated into two age cohorts: women with PCOS aged 18-42 years (n = 935) and women with PCOS aged ≥43 years (n = 107). Data from the online survey were analyzed using descriptive statistics, Pearson correlations, and multiple regression via SAS. Results were interpreted through the lens of life course theory. All demographic variables, except for the number of comorbidities, significantly differed between groups. HRQoL among older women with PCOS was significantly better as compared to those aged 18-42 years. Results indicated significant positive linear associations between the HRQoL psychosocial/emotional subscale and other HRQoL subscales and a significant negative association with age. The fertility and sexual function HRQoL subscales were not significantly associated with the psychosocial/emotional subscale among women aged ≥43 years. Women in both groups had moderate depressive symptoms. Study findings demonstrate the need to tailor PCOS management to women's life stage. This knowledge can inform future research about peri-postmenopausal women with PCOS and age-appropriate and patient-centered healthcare, including requisite clinical screenings (e.g., depressive symptoms) and lifestyle counseling across the lifespan.

Neural substrates underlying rhythmic coupling of female reproductive and thermoregulatory circuits

Coordinated fluctuations in female reproductive physiology and thermoregulatory output have been reported for over a century. These changes occur rhythmically at the hourly (ultradian), daily (circadian), and multi-day (ovulatory) timescales, are critical for reproductive function, and have led to the use of temperature patterns as a proxy for female reproductive state. The mechanisms underlying coupling between reproductive and thermoregulatory systems are not fully established, hindering the expansion of inferences that body temperature can provide about female reproductive status. At present, numerous digital tools rely on temperature to infer the timing of ovulation and additional applications (e.g., monitoring ovulatory irregularities and progression of puberty, pregnancy, and menopause are developed based on the assumption that reproductive-thermoregulatory coupling occurs across timescales and life stages. However, without clear understanding of the mechanisms and degree of coupling among the neural substrates regulating temperature and the reproductive axis, whether such approaches will bear fruit in particular domains is uncertain. In this overview, we present evidence supporting broad coupling among the central circuits governing reproduction, thermoregulation, and broader systemic physiology, focusing on timing at ultradian frequencies. Future work characterizing the dynamics of reproductive-thermoregulatory coupling across the lifespan, and of conditions that may decouple these circuits (e.g., circadian disruption, metabolic disease) and compromise female reproductive health, will aid in the development of strategies for early detection of reproductive irregularities and monitoring the efficacy of fertility treatments.

Effectiveness of an Integrated Mobile Application for Lifestyle Modifications in Overweight Women with Polycystic Ovarian Syndrome: A Randomized Controlled Trial

Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women, characterized by hormonal imbalances and metabolic disturbances. Lifestyle modifications, including weight loss, are crucial for the management of PCOS symptoms. Mobile applications have emerged as promising tools to support lifestyle modifications. This study aimed to evaluate the effectiveness of a 12-week integrated lifestyle modification program, which used a mobile application, among overweight women with PCOS. A randomized controlled trial was conducted with 28 participants, who were assigned to either treatment group, which received a 12-week lifestyle modification program facilitated by a mobile application, or the control group, who were instructed to maintain their usual lifestyle and received an evidence-based leaflet containing information on PCOS. The primary outcome measure was a change in weight over 12 weeks. Insulin resistance, levels of sex hormones, hirsutism, acne, and depressive symptoms were measured as secondary outcomes. The results showed significant weight loss in the treatment group compared to the control group (3.19 vs. 0.79 kg; p < 0.05). Similarly, significant improvements were observed across time in postprandial insulin levels (22.25 vs. 9.29 μIU/mL), hirsutism (2.98 vs. -0.16 points), and depression (7.73 vs. 1.7 points) (p < 0.05) between the two groups. This study highlights the potential benefits of using a mobile application to support lifestyle modifications, including weight loss and improvement in depressive symptoms, in overweight women with PCOS. Further research is needed to explore the long-term effects and incorporation of advanced technologies to enhance PCOS management outcomes. Mobile applications for lifestyle modifications offer a promising avenue for addressing the unique challenges faced by women with PCOS and provide accessible and personalized support for their health needs.

The Effect of Tailored Short Message Service (SMS) on Physical Activity: Results from a Three-Component Randomized Controlled Lifestyle Intervention in Women with PCOS

This analysis of secondary outcome measures of a randomized controlled trial was conducted to study the effect of a one-year three-component (cognitive behavioural therapy, diet, exercise) lifestyle intervention (LSI), with or without additional Short Message Service (SMS) support, on physical activity and aerobic capacity in overweight or obese women with polycystic ovary syndrome (PCOS). Women diagnosed with PCOS and a BMI > 25 kg/m² were randomly assigned to LSI with SMS support (SMS+, n = 60), LSI without SMS support (SMS-, n = 63) or care as usual (CAU, n = 60) in order to lose weight. Based on results from the International Physical Activity Questionnaire (IPAQ), we found a significant within-group increase after one year for SMS+ in the high physical activity category (+31%, p < 0.01) and sitting behaviour decreased (Δ -871 min/week, p < 0.01). Moreover, the peak cycle ergometer workload increased within SMS+ (Δ +10 watts, p < 0.01). The SMS+ group also demonstrated a significantly different increase in walking metabolic equivalent of task minutes (METmin)/week compared with CAU after one year (Δ 1106 METmin/week, p < 0.05). Apart from this increase in walking activity, no other between-group differences were found in this trial. Overall, based on within-group results, SMS support seemed to help with improving physical activity and aerobic capacity and decreasing sedentary behaviour.

Better care for women with polycystic ovary syndrome - a proposal for an international evidence based best practice framework to improve care

PURPOSE OF REVIEW

Polycystic ovary syndrome (PCOS) is the most common endocrinopathy in reproductive-age women and has reproductive, pregnancy, metabolic, dermatologic, and psychologic complications. Here we summarize current challenges and gaps in PCOS care, and propose a pathway forward to implement high quality international guideline recommendations and resources, through development of a best practice framework and benchmarking for evidence-based, patient-centric models of care (MoC).

RECENT FINDINGS

The majority of women with PCOS are unsatisfied with their healthcare experience due to delayed diagnosis, inadequate information provision and inconsistent advice from diverse healthcare providers. The 2018 International Evidence-based PCOS Guideline recommended co-development of evidence-based, patient centric MoC. High-quality guidelines and resources are now available to help women understand and manage PCOS and to assist healthcare professionals to partner in their care. Leveraging these and developing a best practice framework for patient centric PCOS MoC is now a vital to optimise care and outcomes in this common and neglected condition.

SUMMARY

Collaborative interdisciplinary efforts from academic leads, healthcare professionals and consumers are now needed to co-develop a framework and benchmarking performance indicators to guide evidence-based, patient centric PCOS MOC to improve experience and outcomes.

Transtheoretical model-based mobile health application for PCOS

Background

Lifestyle modification (diet, exercise, and behavioral interventions) is the first-line treatment for polycystic ovary syndrome (PCOS). The benefits of face-to-face lifestyle modification intervention in a short time have been demonstrated. However, few studies have investigated the mobile technology effects on lifestyle modification in PCOS. Therefore, we examined the effect of transtheoretical model-based mobile health application intervention program for PCOS.

Methods

A randomised controlled, single-blind trial, was carried out from October 2018 to March 2019, which included 122 participants recruited from gynecology outpatient clinics of affiliated Hospital of Zunyi Medical University in Guizhou. The study participants were randomised into intervention (n = 61) and control groups (n = 61). Participants in the intervention group undertook a TTM-based mobile health application program in addition to routine care, and participants in the control group received only routine care.

Results

Fifty-one participants in the intervention group and 49 in the control group completed the study. Compared to the control group, participants in the intervention group showed statistically significant decrease for BMI (P < 0.05), WC (P < 0.05), SAS (P < 0.05), and SDS (P < 0.05) scores at 6-month and 12-month, respectively. Behavior stage change of exercise and diet among paticipants with PCOS was significant at 6 months (c² = 43.032, P < 0.05) and 12th months (c² = 49.574, P < 0.05) between the intervention and control groups.

Conclusions

This study showed that the TTM-based mobile health application program can decrease BMI, WC, anxiety, and depression, and improve exercise and diet adherence in patients with PCOS in the long term. The TTM-based mobile health application program can be applied for lifestyle modification in women with PCOS.

Trial registration This study was approved by the ethics committee NO.[2019]1-028 in March 2018 and was registered at the Chinese Clinical Trial Registry (website: www.chictr.org.cn, registry number: ChiCTR2000034572)

Poor adherence of life management in patients with PCOS and many then go on to adherence poor health outcomes as a result. There is an urgent need for new approach to enhance to life management compliance for patients with PCOS. TTM is a common behavior change model, which can effectively promote the behavior change of patients, but it has not been used in the life management of PCOS patients. Meanwhile, the traditional life management of PCOS is mainly face-to-face intervention, few studies have investigated the mobile technology effects on lifestyle modification in PCOS. This study aimed to evaluate the long-term effects of TTM-based mobile technology (for lifestyle modification) on the maintenance of health-related behavior changes among women with PCOS. This study confirmed that the TTM-based mobile health application program can decrease BMI, WC, anxiety, and depression, and improve exercise and diet adherence in patients with PCOS in the long term. Our study conducted TTM-based mobile health application program can provide a reference for other researchers or research organizations.

Comparison of a Mobile Health Electronic Visual Analog Scale App With a Traditional Paper Visual Analog Scale for Pain Evaluation: Cross-Sectional Observational Study

Background

Accurate quantification of pain in a clinical setting is vital. The use of an electronic pain scale enables data to be collected, analyzed, and utilized much faster compared with traditional paper-based scales. The advancement of smart technology in pediatric and adult pain evaluation may offer opportunities to introduce easy-to-use and reliable pain assessment methods within different clinical settings. If promptly introduced within different pediatric and adult pain clinic services, validated and easily accessible mobile health pain apps may lead to early pain detection, promoting improvement in patient’s quality of life and leading to potentially less time off from school or work.

Objective

This cross-sectional observational study aimed to investigate the interchangeability of an electronic visual analog scale (eVAS) app with a traditional paper visual analog scale (pVAS) among Australian children, adolescents, and adults for pain evaluation.

Methods

Healthy participants (age range 10-75 years) were recruited from a sporting club and a secondary school in Melbourne (Australia). The data collection process involved application of pressure (8.5 kg/cm²) from a Wagner Force Dial FDK 20 to the midpoint of the thumb. The pressure was applied twice with a 5-minute interval. At each pressure application, participants were asked to randomly record their pain perception using the “eVAS” accessible via the “Interactive Clinics” app and the traditional pVAS. Statistical analysis was conducted to determine intermethod and intramethod reliabilities.

Results

Overall, 109 healthy participants were recruited. Adults (mean age 42.43 years, SD 14.50 years) had excellent reliability, with an intraclass correlation coefficient (ICC) of 0.94 (95% CI 0.91-0.96). Children and adolescents (mean age 13.91 years, SD 2.89 years) had moderate-to-good intermethod and intramethod reliabilities, with an ICC of 0.80 (95% CI 0.70-0.87) and average ICC of 0.80 (95% CI 0.69-0.87), respectively.

Conclusions

The eVAS app appears to be interchangeable compared with the traditional pVAS among children, adolescents, and adults. This pain evaluation method may offer new opportunities to introduce user-friendly and validated pain assessment apps for patients, clinicians, and allied health professionals.

Assessing Apps for Patients with Genitourinary Tumors Using the Mobile Application Rating Scale (MARS): Systematic Search in App Stores and Content Analysis

BACKGROUND

The large number of available cancer apps and their impact on the population necessitates a transparent, objective, and comprehensive evaluation by app experts, health care professionals, and users. To date, there have been no analyses or classifications of apps for patients with genitourinary cancers, which are among the most prevalent types of cancer.

OBJECTIVE

The objective of our study was to analyze the quality of apps for patients diagnosed with genitourinary cancers using the Mobile Application Rating Scale (MARS) and identify high-quality apps.

METHODS

We performed an observational cross-sectional descriptive study of all smartphone apps for patients diagnosed with genitourinary cancers available on iOS and Android platforms. In July 2019, we searched for all available apps for patients with genitourinary cancers (bladder, prostate, cervical, uterine, endometrial, kidney, testicular, and vulvar) or their caregivers. Apps were downloaded and evaluated, and the general characteristics were entered into a database. The evaluation was performed by 2 independent researchers using the MARS questionnaire, which rates 23 evaluation criteria clustered in 5 domains (Engagement, Functionality, Esthetics, Information, and Subjective Quality) on a scale from 1 to 5.

RESULTS

In total, 46 apps were analyzed. Of these, 31 (67%) were available on Android, 6 (13%) on iOS, and 9 (20%) on both platforms. The apps were free in 89% of cases (41/46), and 61% (28/46) had been updated in the previous year. The apps were intended for prostate cancer in 30% of cases (14/46) and cervical cancer in 17% (8/46). The apps were mainly informative (63%, 29/46), preventive (24%, 11/46), and diagnostic (13%, 6/46). Only 7/46 apps (15%) were developed by health care organizations. The mean MARS score for the overall quality of the 46 apps was 2.98 (SD 0.77), with a maximum of 4.63 and a minimum of 1.95. Functionality scores were quite similar for most of the apps, with the greatest differences in Engagement and Esthetics, which showed acceptable scores in one-third of the apps. The 5 apps with the highest MARS score were the following: "Bladder cancer manager," "Kidney cancer manager," "My prostate cancer manager," "Target Ovarian Cancer Symptoms Diary," and "My Cancer Coach." We observed statistically significant differences in the MARS score between the operating systems and the developer types (P<.001 and P=.01, respectively), but not for cost (P=.62).

CONCLUSIONS

MARS is a helpful methodology to decide which apps can be prescribed to patients and to identify which features should be addressed to improve these tools. Most of the apps designed for patients with genitourinary cancers only try to provide data about the disease, without coherent interactivity. The participation of health professionals in the development of these apps is low; nevertheless, we observed that both the participation of health professionals and regular updates were correlated with quality.

Identifying Women at Risk for Polycystic Ovary Syndrome Using a Mobile Health App: Virtual Tool Functionality Assessment

Background

Polycystic ovary syndrome (PCOS) is an endocrine disrupting disorder affecting about 10% of reproductive-aged women. PCOS diagnosis may be delayed several years and may require multiple physicians, resulting in lost time for risk-reducing interventions. Menstrual tracking apps are a potential tool to alert women of their risk while also prompting evaluation from a medical professional.

Objective

The primary objective of this study was to develop and pilot test the irregular cycle feature, a predictive model that generated a PCOS risk score, in the menstrual tracking app, Clue. The secondary objectives were to run the model using virtual test subjects, create a quantitative risk score, compare the feature’s risk score with that of a physician, and determine the sensitivity and specificity of the model before empirical testing on human subjects.

Methods

A literature review was conducted to generate a list of signs and symptoms of PCOS, termed variables. Variables were then assigned a probability and built into a Bayesian network. Questions were created based on these variables. A total of 9 virtual test subjects were identified using self-reported menstrual cycles and answers to the feature’s questions. Upon completion of the questionnaire, a Result Screen and Doctor’s Report summarizing the probability of having PCOS was displayed. This provided information about PCOS and data to facilitate diagnosis by a medical professional. To assess the accuracy of the feature, the same set of 9 virtual test subjects was assigned probabilities by the feature and the physician, who served as the gold standard. The feature recommended individuals with a score greater than or equal to 25% to follow-up with a physician. Differences between the feature and physician scores were evaluated using a t test and a Pearson correlation coefficient in 8 of the 9 virtual test subjects. A second iteration was conducted to assess the feature’s probability capabilities.

Results

The irregular cycle feature’s first iteration produced 1 false-positive compared with the physician score and had an absolute mean difference of 15.5% (SD 15.1%) among the virtual test subjects. The second iteration had 2 false positives compared with the physician score and had an absolute mean difference of 18.8% (SD 13.6%). The feature overpredicted the virtual test subjects’ risk of PCOS compared with the physician. However, a significant positive correlation existed between the feature and physician score (Pearson correlation coefficient=0.82; P=.01). The second iteration performed worse, with a Pearson correlation coefficient of 0.73 (P=.03).

Conclusions

The first iteration of the feature outperformed the second and better predicted the probability of PCOS. Although further research is needed with a more robust sample size, this pilot study indicates the potential value for developing a screening tool to prompt high-risk subjects to seek evaluation by a medical professional.

Assessing the potential of a Virtual Patient Advocate to provide preconception care and health advice to women living in Australia

A preconception Virtual Patient Advocate (VPA) called "Gabby" supported African-American women to decrease their preconception health risks and may be a scalable resource to increase women's access to preconception care. Aims were to assess the acceptability of a preconception VPA in women living in Australia and document the changes required to adapt Gabby to suit an Australian context. Taking a descriptive qualitative approach, nonpregnant female participants (n = 31), aged 18-45 years, living in metropolitan and regional Victoria, Australia interacted with Gabby. Focus groups (n = 7) that gathered participants' perspectives of their experience with Gabby ran in July-August 2019 before being transcribed verbatim and thematically analyzed. Six interrelated themes and 12 subthemes were identified. Participants found VPAs to be an acceptable provider of health information with potential to increase women's access preconception health advice. Gabby was considered to be trustworthy and was able to develop rapport with participants in a relatively short time. Context-specific, relevant, tailored and trustworthy information and advice were considered more important that Gabby's physical appearance. Participants had strong opinions about potential technological advancements (e.g., reminders and rewards) and addressing navigation issues to increase Gabby's acceptability. Participants envisaged that they would use Gabby for readily available and evidence-based information before seeking advice from a health professional if required. Overall, the concept VPAs to provide preconception advice and Gabby were acceptable to participants. Future development of VPAs, Gabby, and other online technology-based resources should consider women's high expectations of the online health information they choose to interact with.

International ResearchKit App for Women with Menstrual Pain: Development, Access, and Engagement

BACKGROUND

Primary dysmenorrhea is a common condition in women of reproductive age. A previous app-based study undertaken by our group demonstrated that a smartphone app supporting self-acupressure introduced by a health care professional can reduce menstrual pain.

OBJECTIVE

This study aims to evaluate whether a specific smartphone app is effective in reducing menstrual pain in 18- to 34-year-old women with primary dysmenorrhea in a self-care setting. One group of women has access to the full-featured study app and will be compared with 2 control groups who have access to fewer app features. Here, we report the trial design, app development, user access, and engagement.

METHODS

On the basis of the practical implications of the previous app-based study, we revised and reengineered the study app and included the ResearchKit (Apple Inc) framework. Behavior change techniques (BCTs) were implemented in the app and validated by expert ratings. User access was estimated by assessing recruitment progress over time. User evolution and baseline survey respondent rate were assessed to evaluate user engagement.

RESULTS

The development of the study app for a 3-armed randomized controlled trial required a multidisciplinary team. The app is accessible for the target population free of charge via the Apple App Store. In Germany, within 9 months, the app was downloaded 1458 times and 328 study participants were recruited using it without external advertising. A total of 98.27% (5157/5248) of the app-based baseline questions were answered. The correct classification of BCTs used in the app required psychological expertise.

CONCLUSIONS

Conducting an innovative app study requires multidisciplinary effort. Easy access and engagement with such an app can be achieved by recruitment via the App Store. Future research is needed to investigate the determinants of user engagement, optimal BCT application, and potential clinical and self-care scenarios for app use.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03432611; https://clinicaltrials.gov/ct2/show/NCT03432611 (Archived by WebCite at http://www.webcitation.org/75LLAcnCQ).