The SoCAP (Social Communication, Affiliation, and Presence) Taxonomy of Social Features: Scoping Review of Commercially Available eHealth Apps.

BACKGROUND: eHealth interventions have proven to be valuable resources for users with diverse mental and behavioral health concerns. As these technologies continue to proliferate, both academic researchers and commercial app creators are leveraging the use of features that foster a sense of social connection on these digital platforms. Yet, the literature often insufficiently represents the functionality of these key social features, resulting in a lack of understanding of how they are being implemented. OBJECTIVE: This study aimed to conduct a methodical review of commercially available eHealth apps to establish the SoCAP (social communication, affiliation, and presence) taxonomy of social features in eHealth apps. Our goal was to examine what types of social features are being used in eHealth apps and how they are implemented. METHODS: A scoping review of commercially available eHealth apps was conducted to develop a taxonomy of social features. First, a shortlist of the 20 highest-rated eHealth apps was derived from One Mind PsyberGuide, a nonprofit organization with trained researchers who rate apps based on their (1) credibility, (2) user experience, and (3) transparency. Next, both mobile- and web-based versions of each app were double-coded by 2 trained raters to derive a list of social features. Subsequently, the social features were organized by category and tested on other apps to ensure their completeness. RESULTS: Four main categories of social features emerged: (1) communication features (videoconferencing, discussion boards, etc), (2) social presence features (chatbots, reminders, etc), (3) affiliation and identity features (avatars, profiles, etc), and (4) other social integrations (social network and other app integrations). Our review shows that eHealth apps frequently use resource-intensive interactions (eg, videoconferencing with a clinician and phone calls from a facilitator), which may be helpful for participants with high support needs. Furthermore, among commercially available eHealth apps, there is a strong reliance on automated features (eg, avatars, personalized multimedia, and tailored content) that enhance a sense of social presence without requiring a high level of input from a clinician or staff member. CONCLUSIONS: The SoCAP taxonomy includes a comprehensive list of social features and brief descriptions of how these features work. This classification system will provide academic and commercial eHealth app creators with an understanding of the various social features that are commonly implemented, which will allow them to apply these features to enhance their own apps. Future research may include comparing the synergistic effects of various combinations of these social features.

Apigenin Alleviates Autistic-like Stereotyped Repetitive Behaviors and Mitigates Brain Oxidative Stress in Mice.

Studying the involvement of nicotinic acetylcholine receptors (nAChRs), specifically α7-nAChRs, in neuropsychiatric brain disorders such as autism spectrum disorder (ASD) has gained a growing interest. The flavonoid apigenin (APG) has been confirmed in its pharmacological action as a positive allosteric modulator of α7-nAChRs. However, there is no research describing the pharmacological potential of APG in ASD. The aim of this study was to evaluate the effects of the subchronic systemic treatment of APG (10-30 mg/kg) on ASD-like repetitive and compulsive-like behaviors and oxidative stress status in the hippocampus and cerebellum in BTBR mice, utilizing the reference drug aripiprazole (ARP, 1 mg/kg, i.p.). BTBR mice pretreated with APG (20 mg/kg) or ARP (1 mg/g, i.p.) displayed significant improvements in the marble-burying test (MBT), cotton-shredding test (CST), and self-grooming test (SGT) (all p < 0.05). However, a lower dose of APG (10 mg/kg, i.p.) failed to modulate behaviors in the MBT or SGT, but significantly attenuated the increased shredding behaviors in the CST of tested mice. Moreover, APG (10-30 mg/kg, i.p.) and ARP (1 mg/kg) moderated the disturbed levels of oxidative stress by mitigating the levels of catalase (CAT) and superoxide dismutase (SOD) in the hippocampus and cerebellum of treated BTBR mice. In patch clamp studies in hippocampal slices, the potency of choline (a selective agonist of α7-nAChRs) in activating fast inward currents was significantly potentiated following incubation with APG. Moreover, APG markedly potentiated the choline-induced enhancement of spontaneous inhibitory postsynaptic currents. The observed results propose the potential therapeutic use of APG in the management of ASD. However, further preclinical investigations in additional models and different rodent species are still needed to confirm the potential relevance of the therapeutic use of APG in ASD.

Curcumin Potentiates α7 Nicotinic Acetylcholine Receptors and Alleviates Autistic-Like Social Deficits and Brain Oxidative Stress Status in Mice.

Autistic spectrum disorder (ASD) refers to a group of neurodevelopmental disorders characterized by impaired social interaction and cognitive deficit, restricted repetitive behaviors, altered immune responses, and imbalanced oxidative stress status. In recent years, there has been a growing interest in studying the role of nicotinic acetylcholine receptors (nAChRs), specifically α7-nAChRs, in the CNS. Influence of agonists for α7-nAChRs on the cognitive behavior, learning, and memory formation has been demonstrated in neuro-pathological condition such as ASD and attention-deficit hyperactivity disorder (ADHD). Curcumin (CUR), the active compound of the spice turmeric, has been shown to act as a positive allosteric modulator of α7-nAChRs. Here we hypothesize that CUR, acting through α7-nAChRs, influences the neuropathology of ASD. In patch clamp studies, fast inward currents activated by choline, a selective agonist of α7-nAChRs, were significantly potentiated by CUR. Moreover, choline induced enhancement of spontaneous inhibitory postsynaptic currents was markedly increased in the presence of CUR. Furthermore, CUR (25, 50, and 100 mg/kg, i.p.) ameliorated dose-dependent social deficits without affecting locomotor activity or anxiety-like behaviors of tested male Black and Tan BRachyury (BTBR) mice. In addition, CUR (50 and 100 mg/kg, i.p.) mitigated oxidative stress status by restoring the decreased levels of superoxide dismutase (SOD) and catalase (CAT) in the hippocampus and the cerebellum of treated mice. Collectively, the observed results indicate that CUR potentiates α7-nAChRs in native central nervous system neurons, mitigates disturbed oxidative stress, and alleviates ASD-like features in BTBR mice used as an idiopathic rodent model of ASD, and may represent a promising novel pharmacological strategy for ASD treatment.

Multiorgan failure syndrome in newborns: role of social and anatomico-functional features (literature review).

Protection of maternal health as well as protection of fetal and newborn health is a strategic objective in all countries. It ensures the formation of healthy generation as the basis of gene pool preservation and further development of the nation. It is known that the progress of critical conditions in newborns is different from classical concepts. Аnatomicofunctional features of the newborns (especially premature newborns), the effect of prenatal pathological factors are provocative and background factors of the multiorgan failure syndrome begining in these patients, which probably affects frequency of appearance of this syndrome, the mechanisms of development, clinical manifestations, the final of the disease and makes doctors to consider newborns in critical conditions as high-risk group for multiorgan failure syndrome appearance.

A deep learning approach for predicting the quality of online health expert question-answering services.

Recently, online health expert question-answering (HQA) services (systems) have attracted more and more health consumers to ask health-related questions everywhere at any time due to the convenience and effectiveness. However, the quality of answers in existing HQA systems varies in different situations. It is significant to provide effective tools to automatically determine the quality of the answers. Two main characteristics in HQA systems raise the difficulties of classification: (1) physicians' answers in an HQA system are usually written in short text, which yields the data sparsity issue; (2) HQA systems apply the quality control mechanism, which refrains the wisdom of crowd. The important information, such as the best answer and the number of users' votes, is missing. To tackle these issues, we prepare the first HQA research data set labeled by three medical experts in 90days and formulate the problem of predicting the quality of answers in the system as a classification task. We not only incorporate the standard textual feature of answers, but also introduce a set of unique non-textual features, i.e., the popular used surface linguistic features and the novel social features, from other modalities. A multimodal deep belief network (DBN)-based learning framework is then proposed to learn the high-level hidden semantic representations of answers from both textual features and non-textual features while the learned joint representation is fed into popular classifiers to determine the quality of answers. Finally, we conduct extensive experiments to demonstrate the effectiveness of including the non-textual features and the proposed multimodal deep learning framework.

Exploring the forest instead of the trees: An innovative method for defining obesogenic and obesoprotective environments.

Past research has assessed the association of single community characteristics with obesity, ignoring the spatial co-occurrence of multiple community-level risk factors. We used conditional random forests (CRF), a non-parametric machine learning approach to identify the combination of community features that are most important for the prediction of obesogenic and obesoprotective environments for children. After examining 44 community characteristics, we identified 13 features of the social, food, and physical activity environment that in combination correctly classified 67% of communities as obesoprotective or obesogenic using mean BMI-z as a surrogate. Social environment characteristics emerged as most important classifiers and might provide leverage for intervention. CRF allows consideration of the neighborhood as a system of risk factors.

Personal features and dropout from diabetic care.

OBJECTIVE: To investigate the personal features associated with dropout from regular outpatient care among persons with type 2 diabetes mellitus (DM). METHODS: A total of 160 DM patients were enrolled in the study. As a retrospective analysis, outpatient's clinical characteristics, lifestyle, or social features were gathered from their medical records or interview sheets. All the subjects were divided into two groups by adherence to diabetic care, namely, 'dropout case' (DC), or 'ongoing case' (OC), and were subjected to comparative analysis. We called the patients who did not receive outpatient treatment from the clinic on a regular basis, including treatment from other clinics or dropout of diabetic care, as DC. In contrast, patients who regularly visited the clinic were defined as OC. An unconditional multiple logistic regression analysis was performed to analyze the association of a dherence to diabetic care with several personal features. RESULTS: Sixty-eight of 160 subjects (42.5%) were recognized as DC. The remaining 92 subjects (57.5%) were considered as OC. Young age (p=0.045), low plasma glucose (p=0.005) and hemoglobin A1c (HbA1c) levels (p=0.005), nonmedication (p<0.001) and no past history of DM (p=0.007) at the initial visit were the features related to dropout by crude analysis. Even after adjustment for age and gender by multivariate analysis, there remained significant inverse associations of dropout with HbA1c level, medical treatment (oral agents or insulin) and previous DM history. Neither occupation, distance from residence to clinic, smoking habit nor drinking habit was associated with dropout. Dropout mostly occurred after the initial or second visit. CONCLUSIONS: A mild condition of DM may be related to dropout from regular outpatient care. It may be necessary to clearly show the objectives and importance of regular visit to an outpatient clinic for diabetic care, particularly for screened mild DM cases in public health activities.