Depressive disorders appear relatively frequently in older patients, and therefore represent an important disease burden worldwide. Given the high levels of inflammatory parameters found in depressed elderly patients, the “inflammaging” hypothesis is gaining strength. In this systematic review, we summarize current evidence regarding the relationship between inflammatory parameters and late-life depression, with a unique focus on longitudinal studies to guarantee temporality. According to the data summarized in this review, the levels of some proinflammatory parameters—especially interleukin (IL)-8, IL-6, and tumor necrosis factor (TNF)-α—could serve as biomarkers for the future development of depressive symptoms in elderly patients. Proinflammatory cytokines seem to be associated with the future development of clinically significant depression, irrespective of baseline scores, thus indicating that inflammation temporally precedes and increases depression risk. As insufficient research has been conducted in this field, further prospective studies are clearly warranted.

Several studies have investigated the relationship between non-pharmacological interventions (NPIs) and peripheral brain-derived neurotrophic factor (BDNF) in schizophrenia patients. We conducted a systematic review and meta-analysis to review the efficacy of NPIs on peripheral serum and plasma BDNF in subjects with schizophrenia (including schizoaffective disorder). Meta-analyses were conducted to examine the effects of NPIs on blood BDNF levels by using the standardized mean differences (SMDs) between the intervention groups and controls. In total, six randomized controlled trials with 289 participants were included. Of them, five studies used exercise, physical training or diet products. One study used cognitive training. Overall, the BDNF levels in the NPI group increased significantly compared with the control groups (SMD = 0.95, 95% confidence interval (CI) = 0.07 to 1.83, p = 0.03). Subgroup analyses indicated beneficial effects of a non-exercise intervention on peripheral BDNF levels (SMD = 0.41, 95% CI = 0.08 to 0.74, p = 0.01). Meta-regression analyses showed that the completion rate influenced the variation in SMD (p = 0.01). Despite insufficient evidence to draw a conclusion, our results suggest that use of NPIs as adjunctive treatments, specifically non-exercise interventions, may affect positively serum or plasma BDNF in patients with schizophrenia.

Background: Smartphones have become useful tools for medicine, with the use of specific apps making it possible to bring health care closer to inaccessible areas, continuously monitor a patient's pathology at any time and place, promote healthy habits, and ultimately improve patients’ quality of life and the efficiency of the health care system. Since 2020, the use of smartphones has reached unprecedented levels. There are more than 350,000 health apps, according to a 2021 IQVIA Institute report, that address, among other things, the management of patient appointments; communication among different services or professionals; the promotion of lifestyle changes related to adopting healthy habits; and the monitoring of different pathologies and chronic conditions, including smoking cessation. The number of mobile apps for quitting smoking is high. As early as 2017, a total of 177 unique smoking cessation–relevant apps were identified in the iPhone App Store, 139 were identified in Google Play, 70 were identified in the BlackBerry app store, and 55 were identified in the Windows Phone Store, but very few have adequate scientific support. It seems clear that efforts are needed to assess the quality of these apps, as well as their effectiveness in different population groups, to have tools that offer added value to standard practices. Objective: This viewpoint aims to highlight the benefits of mobile health (mHealth) and its potential as an adjuvant tool in health care. Methods: A review of literature and other data sources was performed in order to show the current status of mobile apps that can offer support for smoking cessation. For this purpose, the PubMed, Embase, and Cochrane databases were explored between May and November 2022. Results: In terms of smoking cessation, mHealth has become a powerful coadjuvant tool that allows health workers to perform exhaustive follow-ups for the process of quitting tobacco and provide support anytime and anywhere. mHealth tools are effective for different groups of smokers (eg, pregnant women, patients with chronic obstructive pulmonary disease, patients with mental illness, and the general population) and are cost-effective, generating savings for the health system. However, there are some patient characteristics that can predict the success of using mobile apps in the smoking cessation process, such as the lower age of patients, dependence on tobacco, the number of quit attempts, and the previous use of mobile apps, among others. Therefore, it is preferable to offer these tools to patients with a higher probability of quitting tobacco. Conclusions: mHealth is a promising tool for helping smokers in the smoking cessation process. There is a need for well-designed clinical studies and economic evaluations to jointly assess the effectiveness of new interventions in different population groups, as well as their impact on health care resources.