A comparative study of effectiveness, safety and cost effectiveness of olanzapine, risperidone and aripiprazole therapy in schizophrenia

Background: Schizophrenia is the most common psychotic disorder and responsible for approximately half of long-term psychiatric hospitalizations. Antipsychotic medications reduce the psychotic symptoms and prevent relapses. The choice of drug for treatment of schizophrenia depends on many issues, including effectiveness, cost, side-effect burden, availability, and tolerability. Many studies have compared antipsychotic drugs with one another, but no broad consensus has been reached. Our study compares the clinical effectiveness, safety and cost effectiveness of atypical antipsychotics in our setting.Methods: This was an observational, prospective study in which schizophrenia patients receiving either olanzapine, risperidone or aripiprazole were enrolled. Patients were followed up for 3 months. Evaluation of effectiveness was done by analysing mean reduction in PANSS score. Analysis of ADRs was done using WHO causality scale and Hartwig and Siegel severity scale. Cost analysis was done by comparing all three groups in term of cost range of antipsychotic drugs per improvement in PANSS score during the study period.Results: In the present study, the average dose of antipsychotic drugs received by a patient per day was 8.83±2.98 mg in olanzapine group, 4.76±1.12 mg in risperidone group and 20.43±8.5 mg in aripiprazole group. Mean reduction in PANSS score from baseline to 12 weeks was 23.79% in olanzapine group, 25.41% in risperidone group and 24.65% in aripiprazole group. Conclusions: All the groups were equally effective in reduction in PANSS score while risperidone was the most cost effective

Opening up the ‘black-box’:What strategies do community mental health workers use to address the social dimensions of mental health?

Purpose: Community-based workers promote mental health in communities. Recent literature has called for more attention to the ways they operate and the strategies used. For example, how do they translate biomedical concepts into frameworks that are acceptable and accessible to communities? How do micro-innovations lead to positive mental health outcomes, including social inclusion and recovery? The aim of this study was to examine the types of skills and strategies to address social dimensions of mental health used by community health workers (CHWs) working together with people with psychosocial disability (PPSD) in urban north India. Methods: We interviewed CHWs (n = 46) about their registered PPSD who were randomly selected from 1000 people registered with a local non-profit community mental health provider. Notes taken during interviews were cross-checked with audio recordings and coded and analyzed thematically. Results: CHWs displayed social, cultural, and psychological skills in forming trusting relationships and in-depth knowledge of the context of their client's lives and family dynamics. They used this information to analyze political, social, and economic factors influencing mental health for the client and their family members. The diverse range of analysis and intervention skills of community health workers built on contextual knowledge to implement micro-innovations in a be-spoke way, applying these to the local ecology of people with psychosocial disabilities (PPSD). These approaches contributed to addressing the social and structural determinants that shaped the mental health of PPSD. Conclusion: Community health workers (CHWs) in this study addressed social aspects of mental health, individually, and by engaging with wider structural factors. The micro-innovations of CHWs are dependent on non-linear elements, including local knowledge, time, and relationships. Global mental health requires further attentive qualitative research to consider how these, and other factors shape the work of CHWs in different locales to inform locally appropriate mental health care.</p

Women\u27s freedom of movement and participation in psychosocial support groups: Qualitative study in northern India

© 2019 The Author(s). Background: Depression, the world\u27s leading cause of disability, disproportionately affects women. Women in India, one of the most gender unequal countries worldwide, face systemic gender disadvantage that significantly increases the risk of common mental disorders. This study\u27s objective was to examine the factors influencing women\u27s participation in psychosocial support groups, within an approach where community members work together to collectively strengthen their community\u27s mental health. Methods: This community-based qualitative study was conducted from May to July 2016, across three peri-urban sites in Dehradun district, Uttarakhand, Northern India. Set within an NGO-run mental health project, data were collected through focus group discussions with individuals involved in psychosocial support groups including women with psychosocial disabilities as well as caregivers (N = 10, representing 59 women), and key informant interviews (N = 8) with community members and mental health professionals. Data were analyzed using a thematic analysis approach. Results: The principal barrier to participating in psychosocial support groups was restrictions on women\u27s freedom of movement. Women in the community are not normally permitted to leave home, unless going to market or work, making it difficult for women to leave their home to participate in the groups. The restrictions emanated from the overall community\u27s attitude toward gender relations, the women\u27s own internalized gender expectations, and most significantly, the decision-making power of husbands and mothers-in-law. Other factors including employment and education shaped women\u27s ability to participate in psychosocial support groups; however, the role of these additional factors must be understood in connection to a gender order limiting women\u27s freedom of movement. Conclusions: Mental health access and gender inequality are inseparable in the context of Northern India, and women\u27s mental health cannot be addressed without first addressing underlying gender relations. Community-based mental health programs are an effective tool and can be used to strengthen communities collectively; however, attention towards the gender constraints that restrict women\u27s freedom of movement and their ability to access care is required. To our knowledge, this is the first study to clearly document and analyze the connection between access to community mental health services in South Asia and women\u27s freedom of movement

Voice Feature Extraction for Gender and Emotion Recognition

Voice recognition plays a key role in spoken communication that helps to identify the emotions of a person that reflects in the voice. Gender classification through speech is a widely used Human Computer Interaction (HCI) as it is not easy to identify gender by computer. This led to the development of a model for “Voice feature extraction for Emotion and Gender Recognition”. The speech signal consists of semantic information, speaker information (gender, age, emotional state), accompanied by noise. Females and males have different voice characteristics due to their acoustical and perceptual differences along with a variety of emotions which convey their own unique perceptions. In order to explore this area, feature extraction requires pre- processing of data, which is necessary for increasing the accuracy. The proposed model follows steps such as data extraction, pre- processing using Voice Activity Detector (VAD), feature extraction using Mel-Frequency Cepstral Coefficient (MFCC), feature reduction by Principal Component Analysis (PCA) and Support Vector Machine (SVM) classifier. The proposed combination of techniques produced better results which can be useful in the healthcare sector, virtual assistants, security purposes and other fields related to the Human Machine Interaction domain.&nbsp

Participatory mental health interventions in low-income and middle-income countries:A realist review protocol

INTRODUCTION: The launch of the Movement for Global Mental Health brought long-standing calls for improved mental health interventions in low-and middle-income countries (LMICs) to centre stage. Within the movement, the participation of communities and people with lived experience of mental health problems is argued as essential to successful interventions. However, there remains a lack of conceptual clarity around 'participation' in mental health interventions with the specific elements of participation rarely articulated. Our review responds to this gap by exploring how 'participation' is applied, what it means and what key mechanisms contribute to change in participatory interventions for mental health in LMICs. METHODS AND ANALYSIS: A realist review methodology will be used to identify the different contexts that trigger mechanisms of change, and the resulting outcomes related to the development and implementation of participatory mental health interventions, that is: what makes participation work in mental health interventions in LMICs and why? We augment our search with primary data collection in communities who are the targets of global mental health initiatives to inform the production of a programme theory on participation for mental health in LMICs. ETHICS AND DISSEMINATION: Ethical approval for focus group discussions (FGDs) was obtained in each country involved. FGDs will be conducted in line with WHO safety guidance during the COVID-19 crisis. The full review will be published in an academic journal, with further papers providing an in-depth analysis on community perspectives on participation in mental health. The project findings will also be shared on a website, in webinars and an online workshop

Finding a sustainable prototype for integrative medicine

Mainstreaming traditional systems of medicine and integrating them with the established health delivery mechanisms is an important step in accelerating advancement of health sciences to achieve current global health care goals. This paper proposes the "axial-model" of Integrative Medicine (IM). A replicable model, viable across multiple IM possibilities, which are clinically beneficial, supports evidence-based evolution and is socially acceptable. Axial model may be implemented to integrate two or more systems of medicines, provided they are legally regulated and approved for clinical administration. It proposes three consecutively phased clinical processes, named parallel, complementary and protocol, respectively. The model supports translational medicine by mainstreaming beneficial practices of traditional medicine as a part of its process of execution