Mania

To enhance interpretation of all presented graphical and numerical summaries we used three worked examples of NMAs. The first example compares 14 antimanic drugs for acute mania [14] (link). The network included 47 studies reporting on efficacy (measured as the number of responders out of total randomized) and 64 studies reporting on acceptability (measured as the number of dropouts out of total randomized). The second example is a network of 62 studies that evaluate the effectiveness of four different percutaneous coronary interventions for non-acute coronary artery disease [15] (link). The third example is a network of 27 studies forming a star-shaped network (i.e. all active treatments are compared only with placebo) that evaluated the effectiveness of six biologic agents for rheumatoid arthritis [16] (link). The outcome in this network was benefit from treatment defined as a 50% improvement in patient- and physician-reported criteria of the American College of Rheumatology (ACR50). The datasets and the STATA routines can be found online in www.mtm.uoi.gr and more detail is provided in the Appendix S1. To be able to carry out the analysis described below, version 3.01 (or later) of the command metan, version 2.6.1 (or later) of metareg and version 2.5.5 (or later) of mvmeta are required.

After informing the patients and obtaining their consent, the investigator recorded their socio-demographic and clinical variables and administered the Spanish version of the Young Mania Rating Scale (YMRS) [18 (link)], Spanish version of the 17-item Hamilton Depression Rating Scale (HDRS-17) [19 (link)] and the Global Assessment Functioning (GAF) [20 ] to confirm the stability of the patient's condition and overall functioning. They also recorded all the medication prescribed to the patients for this visit. Finally, the investigator administered the FAST. Interviewers administering the FAST and the GAF were blinded to each other.
Sixty one control subjects were screened using the SCID (DSM-IV TR) to exclude current or lifetime psychiatric disorders. Controls had no first-degree relatives with bipolar disorder or other psychiatric disorders. The healthy comparison group was recruited from the general population within the catchment area of the Hospital Clinic, Barcelona, and gave written informed consent to participate in this study.

Stable outpatients under regular treatment received prior psychiatric diagnosis after a three-step procedure consisting of the following: (a) careful clinical observation with at least three evaluations; (b) a family interview; and (c) a review of their medical records performed by a trained psychiatrist. All met the following inclusion criteria: Diagnostic and Statistical Manual of Mental Disorders, DSM-5; (14 ) diagnosis of schizophrenia; aged between 18 and 65 years; under stable drug treatment adjusted to their clinical state for at least 3 months; and not involved in any other physical activity programs during the intervention. Patients were recruited from the services where they were being clinically followed (HCPA or CAPES) and were allocated to the intervention group (individuals from HCPA underwent IF, and individuals from CAPES underwent IA) (Figure 1).
The exclusion criteria were as follows: alcohol or other drug abuse in the previous month; major systemic or neurological diseases; physical disability contraindicating physical activity or any physical condition that makes physical activity unsafe; suicide risk confirmed by direct contact with the patient and family; pregnancy or women of reproductive age that did not use a contraception method; and not agreeing to participate in the study after full explanation of the program.
Controls were recruited through specific social networks (Figure 2). Then, they were paired by sex, age (3 years older or younger), and social class [we followed the classification criteria by classes of the Brazilian Institute of Geography and Statistics (IBGE), which uses the monthly income of all the residents of the same house to list from the richest to the poorest]. Thus, they were divided into the following classes: A (monthly income above R$ 20,900), B (monthly income between R$ 10,450.01 and R$ 20,900), C (monthly income above R$ 4,180 but up to R$ 10,450), D (monthly income between R$ 2,090.01 and R$ 4,180), and E (monthly income of no more than R$ 2,090).
The absence of any major mental illness was defined by a direct interview in which questions about life experiences of memory loss, psychosis (delusions and/or hallucinations), depression, mania, generalized anxiety disorder, and obsessive-compulsive symptoms were asked. Additionally, the subjects were asked about regular physical activity as they were supposed to be sedentary. Exclusion criteria were the same as those applied to patients with SCZ.

All patients installed the Mindstrong Health app and provided informed consent for the use of data in research and product development before enrolling for services. This analysis was conducted under a secondary data analysis protocol to identify clinically relevant associations in active and passive data collection at Mindstrong.
As part of routine clinical care, patients were asked to report their mental illness symptoms every 60 days through the mobile app via the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5) Self-Rated Level 1 Cross-Cutting Symptom Measure-Adult Survey (DSM L1). Due to possible patient burden given the serious mental illness population, the DSM L1 was chosen as a routine clinical screener to comprehensively assess a wide range of clinical domains while ensuring assessment brevity. Specifically, the DSM L1 consists of 23 questions that assess 13 clinical domains, including depression, anger, mania, anxiety, somatic symptoms, suicidal ideation, psychosis, sleep problems, memory, repetitive thoughts and behaviors, dissociation, personality functioning, and substance use (on average, 1-3 items are present per clinical domain) [25 (link)]. The depression domain in the DSM L1 has 2 items, which assess loss of interest in pleasurable activities and depressed mood (feeling sad). These 2 items are comparable to the short-form Patient Health Questionnaire (PHQ2) [26 (link)]. The DSM L1 questionnaire was completed by patients every 60 days via the Mindstrong app. Screenshots of the DSM L1 survey in the Mindstrong app are shown in Figure 1. A total of 984 assessments of depressive symptoms over a 1-year period were included in this analysis.
In this retrospective observational study, patients were selected based on high compliance with the DSM L1. We intentionally selected individuals with higher compliance because higher compliance (or more repeated measures within the same person) allows examination of the within-person association between self-reports of depressive symptoms and the behavioral measures computed from human-smartphone interactions.
Because the DSM L1 prompted participants to report their depressive symptoms that occurred during the past 2 weeks (or 14 days), we included 14 days of smartphone interaction data prior to each depressive symptom measurement date (symptom-date) in the analysis. The temporal alignment between the DSM L1 survey and smartphone metadata is shown in Figure 2A.
The app collects smartphone metadata and contains information about interactions with smartphones in an unobtrusive manner. These metadata of device usage and its touchscreen are collected unobtrusively by proprietary software on the Android operating system. The metadata include various touchscreen behaviors (eg, clicking and scrolling), device-level behaviors (eg, turning the smartphone screen on and turning the smartphone screen off), masked keyboard behaviors (eg, typing characters from the left or right side of the smartphone’s keyboard and not the exact character), and change of foreground apps (eg, text messaging apps and entertainment apps). The starting time of each instance of usage of the smartphone device and its touchscreen was recorded with a timestamp at the millisecond level. These metadata are collected locally on the patient’s smartphone and are then transmitted with encryption to a Health Insurance Portability and Accountability Act (HIPAA)– and ISO 27001–compliant cloud storage service (Amazon Web Services). All personnel who can access patients’ metadata and assessment data (including diagnosis, demographics, and self-reported survey data) complete annual HIPAA training. Data were deidentified prior to analysis.