Editors' Comments on the Special Issue "Social Determinants of Mental Health"

Prevalence and associated factors for depressive symptoms among the general population from 31 provinces in China: The utility of social determinants of health theory

BACKGROUND

Depression is one of the most common types of mental disorders. Guided by the theory of social determinants of health (SDH), the study aimed to assess the prevalence of depressive symptoms and to identify factors related to depressive symptoms in the general population of China.

METHODS

A cross-sectional, online survey was conducted among 101,392 residents from 31 provinces of mainland China from January to March 2019, and 97,126 survey responses were included in the final analysis. Multilevel linear regression models were used to identify SDH associated with depressive symptoms.

RESULTS

The prevalence of depressive symptoms (PHQ-9 scores ≥10) in Chinese residents was 15.81 %. The results of the multilevel analysis demonstrated that depressive symptoms were affected by various factors on five levels, including individual characteristics, behavioral lifestyle, community support network, social structural factors, and macro social factors.

LIMITATIONS

The cross-sectional design of the study makes it difficult to establish causality between variables.

CONCLUSIONS

The prevalence of depressive symptoms is high among general population in China. According to the theory of SDH, the study shows that the depressive symptoms are complex and involves all areas of social life. Therefore, adopting a multi-level, cross-sectoral intervention approach will be instrumental to improving the mental health of residents in China.

Breaking the Stigma in Mental Health Nursing through High-Fidelity Simulation Training

The social stigma toward individuals with mental health problems is habitual among nursing students, which can lead to poor quality of health care services for patients with mental illnesses. The purpose of the present study was to learn about nursing students' perceptions of providing care to patients with severe mental disorders before and after participating in a simulated student clinical case. A descriptive qualitative study was conducted through 39 interviews. The difficulties expected by the students and their perceptions about patients were explored before the simulation training. Their perceptions about the use of clinical simulation for learning about the adequate management of these patients were analyzed afterwards. Results: Before the simulation training, the students assessed the case as being complicated, expressed their lack of specific training, and felt fear and insecurity, thus reproducing the stigma towards mental health patients. After this training, they positively valued the usefulness of the clinical simulation for gaining confidence and overcoming the stigma. Discussion: The use of high-fidelity simulation offers nursing students the opportunity to approach patients with mental health conditions, overcoming their fears and normalizing mental disorders. Simulation training allows nursing students to analyze the reasoning of clinical judgment and to detect the influence of previous prejudices about mental illness in their clinical decision. This study was not registered.

The United Nations Convention on the Rights of Persons with Disabilities and Social Work: Evidence for Impact?

The United Nations Convention on the Rights of Persons with Disabilities (hereafter CRPD) has provided a radical imperative for the reform of mental health and capacity legislation around the world. The interpretation of the CRPD has been controversial, ranging from the complete abolition of detention, forcible treatment, and substitute decision-making to accepting that elements of these measures need to be retained based on non-discriminatory criteria, additional safeguards, and a comprehensive shift towards supported decision-making. While the potential effects of the CRPD on mental health social work and social work generally are considerable given their shared commitment towards social justice, to date there has been no review of research evidence exploring their relationship. In addressing this knowledge gap, this study held a preliminary discussion with practitioners and academics at the European Association of Social Work Mental Health Special Interest Group in Amsterdam 2022, followed by a scoping literature review on the question: What impact, if any, has the CRPD had on social work practice? The review produced four main findings: impact on legislation; positive impact on practice; limited impact on practice; and impact on social work education and research. In sum, while there were some positive indications of social work and mental health social work practice being influenced by the CRPD, these were scant. Barriers to change included tendencies among some social workers to practise substitute decision-making, in part related to resourcing and policy contexts, and understandings of disability aligned to individualised/medical rather than social perspectives. The results indicate that legal reform on its own is insufficient to impact social work practice, and that realising the potential of the CRPD will necessitate good quality training, as well as improving social workers' knowledge of the human rights of people with mental impairment.

Public Trust in Artificial Intelligence Applications in Mental Health Care: Topic Modeling Analysis

Background

Mental disorders (MDs) impose heavy burdens on health care (HC) systems and affect a growing number of people worldwide. The use of mobile health (mHealth) apps empowered by artificial intelligence (AI) is increasingly being resorted to as a possible solution.

Objective

This study adopted a topic modeling (TM) approach to investigate the public trust in AI apps in mental health care (MHC) by identifying the dominant topics and themes in user reviews of the 8 most relevant mental health (MH) apps with the largest numbers of reviewers.

Methods

We searched Google Play for the top MH apps with the largest numbers of reviewers, from which we selected the most relevant apps. Subsequently, we extracted data from user reviews posted from January 1, 2020, to April 2, 2022. After cleaning the extracted data using the Python text processing tool spaCy, we ascertained the optimal number of topics, drawing on the coherence scores and used latent Dirichlet allocation (LDA) TM to generate the most salient topics and related terms. We then classified the ascertained topics into different theme categories by plotting them onto a 2D plane via multidimensional scaling using the pyLDAvis visualization tool. Finally, we analyzed these topics and themes qualitatively to better understand the status of public trust in AI apps in MHC.

Results

From the top 20 MH apps with the largest numbers of reviewers retrieved, we chose the 8 (40%) most relevant apps: (1) Wysa: Anxiety Therapy Chatbot; (2) Youper Therapy; (3) MindDoc: Your Companion; (4) TalkLife for Anxiety, Depression & Stress; (5) 7 Cups: Online Therapy for Mental Health & Anxiety; (6) BetterHelp-Therapy; (7) Sanvello; and (8) InnerHour. These apps provided 14.2% (n=559), 11.0% (n=431), 13.7% (n=538), 8.8% (n=356), 14.1% (n=554), 11.9% (n=468), 9.2% (n=362), and 16.9% (n=663) of the collected 3931 reviews, respectively. The 4 dominant topics were topic 4 (cheering people up; n=1069, 27%), topic 3 (calming people down; n=1029, 26%), topic 2 (helping figure out the inner world; n=963, 25%), and topic 1 (being an alternative or complement to a therapist; n=870, 22%). Based on topic coherence and intertopic distance, topics 3 and 4 were combined into theme 3 (dispelling negative emotions), while topics 2 and 1 remained 2 separate themes: theme 2 (helping figure out the inner world) and theme 1 (being an alternative or complement to a therapist), respectively. These themes and topics, though involving some dissenting voices, reflected an overall high status of trust in AI apps.

Conclusions

This is the first study to investigate the public trust in AI apps in MHC from the perspective of user reviews using the TM technique. The automatic text analysis and complementary manual interpretation of the collected data allowed us to discover the dominant topics hidden in a data set and categorize these topics into different themes to reveal an overall high degree of public trust. The dissenting voices from users, though only a few, can serve as indicators for health providers and app developers to jointly improve these apps, which will ultimately facilitate the treatment of prevalent MDs and alleviate the overburdened HC systems worldwide.

The inter-agency standing committee (IASC) guidelines on mental health and psychosocial support (MHPSS) in emergency settings: a critique

The bio-medical model of 'mental health' and 'mental illness' that relates to the relationship between wellbeing and distress informs psychopathology and dominates conceptualisation in many Western Educated Industrialised Rich Democratic (WEIRD) populations. This paper aims to critique the model, questioning the appropriateness of psychopathology as a conceptual framework when working as a Western trained clinician with populations such as in China, Japan, Asia, the Middle-East and Africa. The paper also considers the cultural appropriateness of western notions of psychopathology when working inter-culturally in relation to the Inter-Agency Standing Committee (IASC) Guidelines on Mental Health and Psychosocial Support in Emergency Settings, and the Review of the Implementation of the IASC Guidelines on Mental Health and Psychosocial Support in Emergency Settings.