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BackgroundDepressive and neurocognitive disorders are debilitating conditions that account for the leading causes of years lived with disability worldwide. Overcoming these disorders is an extremely important public health problem today. However, there are no biomarkers that are objective or easy-to-obtain in daily clinical practice, which leads to difficulties in assessing treatment response and developing new drugs. Due to advances in technology, it has become possible to quantify important features that clinicians perceive as reflective of disorder severity. Such features include facial expressions, phonic/speech information, body motion, daily activity, and sleep. The overall goal of this proposed study, the Project for Objective Measures Using Computational Psychiatry Technology (PROMPT), is to develop objective, noninvasive, and easy-to-use biomarkers for assessing the severity of depressive and neurocognitive disorders.MethodsThis is a multi-center prospective study. DSM-5 criteria for major depressive disorder, bipolar disorder, and major and minor neurocognitive disorders are inclusion criteria for the depressive and neurocognitive disorder samples. Healthy samples are confirmed to have no history of psychiatric disorders by Mini-International Neuropsychiatric Interview, and have no current cognitive decline based on the Mini Mental State Examination. Participants go through approximately 10-minute interviews with a psychiatrist/psychologist, where participants talk about non-specific topics such as everyday living, symptoms of disease, hobbies, etc. Interviews are recorded using RGB and infrared cameras, and an array microphone. As an option, participants are asked to wear wrist-band type devices during the observational period. The interviews take place ≤10 times within up to five years of follow-up. Various software is used to process the raw video, voice, infrared, and wearable device data. A machine learning approach is used to predict the presence of symptoms, severity, and the improvement/deterioration of symptoms.DiscussionThe PROMPT goal is to develop objective digital biomarkers for assessing the severity of depressive and neurocognitive disorders in the hopes of guiding decision-making in clinical settings as well as reducing the risk of clinical trial failure. Challenges may include the large variability of samples, which makes it difficult to extract the features that commonly reflect disorder severity.Trial RegistrationUMIN000021396, University Hospital Medical Information Network (UMIN)

The present study examined whether a web-based intervention could promote weight-loss maintenance, after weight loss. The study was a two-phase, 27-month, randomized controlled trial conducted in Ibaraki, Japan, from 2014 to 2017; 133 participants were recruited through local newspaper advertisements. The eligibility criteria were as follows: age of 40–64 years, body mass index of 25–40 kg/m2, and having at least one metabolic syndrome component. In phase 1, a 3-month, group-based weight-loss program was provided to all eligible participants (n = 119). We then randomly assigned (1:1) participants who had lost 5% or more of their weight during phase 1 (n = 95) to either the self-help (mean 3-month weight loss 7.30 kg) or the web-support group (7.00 kg). Participants in the web-support group regularly reported their body weight and physical activity through a web-based system. They received monthly personalized feedback from a study staff for 24 months. The primary outcome, 27-month body-weight change (mean ± standard deviation), in the self-help and web-support groups were − 5.3 ± 5.0 kg and −4.5 ± 4.9 kg, respectively. There was no significant difference. An exploratory secondary analysis demonstrated that those with greater 27-month increases in their step count, assessed with an accelerometer, lost more weight with no difference in changes in energy intake. The mean 27-month body-weight change in the 4th quartile of changes in step count was −7.78 kg. Although web-based intervention using an activity monitor failed to promote weight-loss maintenance, increased physical activity was associated with successful weight-loss maintenance., Highlights • Web-based intervention using an activity monitor delivered no benefit on weight. • Participants with larger increases in step count lost more weight. • Increased physical activity was associated with successful weight loss maintenance.

Highlights • We compared the effects of volunteer- and expert-led weight-loss intervention. • Participants were instructed to maintain a well-balanced, low-energy diet. • The completion proportions was significantly higher in the expert-led group. • The degree of body weight change was similar for both groups. • Such programs could be an alternative strategy for low-cost obesity management., This study compared the effect of volunteer- and expert-led versions of a community-based weight-loss intervention in a non-randomized comparative trial conducted in Ibaraki, Japan from 2016 to 2017. Participants were 145 Japanese adults with overweightness or obesity, aged 20–69 years, with 77 in a volunteer-led group and 68 in an expert-led group. Both groups received the same program content and intervention period. Community volunteers were trained in four or five 3-hour training sessions while experts were highly trained and experienced professionals in the fields of exercise and nutrition prescription. Participants were also instructed to maintain a well-balanced, low-energy diet. The primary outcome measure was body weight change. In the volunteer- and expert-led groups, 58 of 77 (75%) and 61 of 68 (95%) participants completed the 12-week intervention, respectively. The mean (95% confidence interval, CI) weight loss of the volunteer-led group was 6.4 (95% CI: 5.6–7.2) kg, corresponding to 8.9% of initial body weight, while that of the expert-led group was 6.3 (95% CI: 5.5–7.1) kg, corresponding to 8.2% of the initial body weight. The proportion of participants who completed the course was significantly higher in the expert-led group (P