Quality, Usability, and Effectiveness of mHealth Apps and the Role of Artificial Intelligence: Current Scenario and Challenges.

The use of artificial intelligence (AI) and big data in medicine has increased in recent years. Indeed, the use of AI in mobile health (mHealth) apps could considerably assist both individuals and health care professionals in the prevention and management of chronic diseases, in a person-centered manner. Nonetheless, there are several challenges that must be overcome to provide high-quality, usable, and effective mHealth apps. Here, we review the rationale and guidelines for the implementation of mHealth apps and the challenges regarding quality, usability, and user engagement and behavior change, with a special focus on the prevention and management of noncommunicable diseases. We suggest that a cocreation-based framework is the best method to address these challenges. Finally, we describe the current and future roles of AI in improving personalized medicine and provide recommendations for developing AI-based mHealth apps. We conclude that the implementation of AI and mHealth apps for routine clinical practice and remote health care will not be feasible until we overcome the main challenges regarding data privacy and security, quality assessment, and the reproducibility and uncertainty of AI results. Moreover, there is a lack of both standardized methods to measure the clinical outcomes of mHealth apps and techniques to encourage user engagement and behavior changes in the long term. We expect that in the near future, these obstacles will be overcome and that the ongoing European project, Watching the risk factors (WARIFA), will provide considerable advances in the implementation of AI-based mHealth apps for disease prevention and health promotion.

Impact of anxiety, depression and disease-related distress on long-term glycaemic variability among subjects with Type 1 diabetes mellitus.

BACKGROUND: Anxiety, depression, and disease-related distress are linked to worse overall glycaemic control, in terms of HbA1c. This study was aimed to evaluate whether traits of these emotional disorders are associated with long-term glycaemic variability in subjects with Type 1 diabetes. METHODS: Longitudinal retrospective study. Six-year HbA1c data (2014-2019) from 411 subjects with Type 1 diabetes who had participated in a previous study to design a diabetes-specific quality of life questionnaire in the year 2014 were included. Scores for Spanish versions of the Hospital Anxiety and Depression Scale (HADS) and Problem Areas in Diabetes (PAID) scale were obtained at baseline, along with sociodemographic and clinical data. Long-term glycaemic variability was measured as the coefficient of variation of HbA1c (HbA1c-CV). The association between HADS and PAID scores and HbA1c-CV was analysed with Spearman correlations and multiple regression models, both linear and additive, including other covariates (age, sex, diabetes duration time, type of treatment, baseline HbA1c, use of anxiolytic or antidepressant drugs, education level and employment status). RESULTS: Scores of depression, anxiety and distress were positively and significantly correlated to HbA1c-CV in univariate analyses. Multiple regression study demonstrated an independent association only for diabetes distress score (p < 0.001). Age, diabetes duration time, baseline HbA1c, education level and employment status were also significantly associated with HbA1c-CV. However, when subjects were analyzed separately in two age groups, distress scores were associated with HbA1c-CV only among those aged 25 years or older, while anxiety scores, but not distress, were associated with HbA1c-CV among those younger than 25 years. CONCLUSIONS: Psychological factors, particularly disease-related distress and anxiety, are associated with long-term glycaemic variability in subjects with Type 1 diabetes.

Gender Incongruity in a Person with 46,XY and Complete Androgen Insensitivity Syndrome Raised as a Female.

We present the case of a patient with female sex assignment at birth whose parents consulted with a pediatrician when the child was 12 years old, indicating that despite female sex assignment, she felt that she (henceforth "he") had a male gender identity and was gynephilic. Medical examination revealed a 46XY karyotype, a primary amenorrhea and an appropriate testosterone increase after HCG stimulation test. The patient was diagnosed then with a 46,XY disorder of sex development with androgen insensitivity syndrome, but then he missed subsequent appointments. At the age of 24, he resumed medical follow-up to reaffirm his male gender identity through sex reassignment surgery. His physical examination showed a Tanner stage III-IV breast development, vulva, clitoris, normal-sized vagina, absence of uterus and ovaries on transvaginal ultrasound, bilateral cryptorchidism on abdominal-pelvic MRI and osteoporosis on bone densitometry. The results of the blood tests were LH 24.5 mIU/mL [normal range, 1.7-8.6 mIU/mL for men] and testosterone 8.8 nmol/L [8.7-33 nmol/L]; conversely, FSH, estradiol, progesterone, and prolactin levels were normal. The molecular genetic analysis revealed an androgen receptor gene mutation associated with complete androgen insensitivity syndrome. At present, the patient has undergone bilateral orchiectomy and has initiated treatment with topical testosterone and bisphosphonates. We have yet to evaluate the effects and decide the best therapy taking into account that he has a male gender identity but complete androgen insensitivity syndrome.