Mental health literacy of Indonesian health practitioners and implications for mental health system development

Praharso, Nurul; Pols, Hans; Tiliopoulos, Nikolaos

doi:10.1016/j.ajp.2020.102168

Cited by 25 publications

(22 citation statements)

References 37 publications

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“…In the field of community psychiatry, research has examined the perception of the community and health professionals regarding ADHD and mental health literacy (Julivia Murtani et al, 2020; Praharso, Pols, & Tiliopoulos, 2020). These works suggest that addressing stigma should remain a priority in mental health education.…”

Section: Methodsmentioning

confidence: 99%

The state of psychiatric research in the Asia Pacific region

Roche

Fung

Ransing

et al. 2020

Asia-Pacific Psychiatry

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Introduction This study aims to review recent scientific publications and research output in the field of psychiatry, from a series of countries in the Asia‐Pacific region (Australia, India, Indonesia, Iran, Lebanon, Malaysia, and Nepal), with a view to identify themes and similarities across regions, as well as to examine the barriers and challenges in mental health research faced by countries in the region. Methods Seven psychiatrists from seven countries reviewed recent published and ongoing research in psychiatry in their respective nations, with respect to themes, as well as any barriers or challenges faced by mental health researchers. Results While the seven nations included in this review vary in terms of research capabilities and economic development level, they share many similarities both in terms of research direction, and with regards to challenges faced. Limitations in the form of sociocultural differences from the West, and a lack of funding were some of the barriers identified. Discussion Mental health research in the region has been progressing well. However, more varied research in the form of qualitative or economic studies are lacking, as are multi‐center studies. The similar issues that nations face with regards to research could perhaps benefit from collaborative efforts and initiatives for the furtherance of research in the region.

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Section: Methodsmentioning

confidence: 99%

The state of psychiatric research in the Asia Pacific region

Roche

Fung

Ransing

et al. 2020

Asia-Pacific Psychiatry

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“…Of 15 completed studies, nine reported reductions in one or more measures of stigma, even where health worker knowledge or skills were unchanged. [17][18][19][20][21][22][23][24][25] Economic studies identified the scale of the mental health gap, its financial 26 and disability impacts, 27 and calculated the workforce requirements [28][29][30] and costs of treatment.…”

Section: System Level Facilitators Barriersmentioning

confidence: 99%

WHO mental health gap action programme (mhGAP) intervention guide: updated systematic review on evidence and impact

Keynejad

Spagnolo

Thornicroft

2021

Evid Based Mental Health

104

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QuestionThere is a large worldwide gap between the service need and provision for mental, neurological and substance use disorders. WHO’s Mental Health Gap Action Programme (mhGAP) intervention guide (IG), provides evidence-based guidance and tools for assessment and integrated management of priority disorders. Our 2017 systematic review identified 33 peer-reviewed studies describing mhGAP-IG implementation in low-income and middle-income countries.Study selection and analysisWe searched MEDLINE, Embase, PsycINFO, Web of Knowledge, Scopus, CINAHL, LILACS, ScieELO, Cochrane, PubMed databases, 3ie, Google Scholar and citations of our review, on 24 November 2020. We sought evidence, experience and evaluations of the mhGAP-IG, app or mhGAP Humanitarian IG, from any country, in any language. We extracted data from included papers, but heterogeneity prevented meta-analysis.FindingsOf 2621 results, 162 new papers reported applications of the mhGAP-IG. They described mhGAP training courses (59 references), clinical applications (n=49), research uses (n=27), contextual adaptations (n=13), economic studies (n=7) and other educational applications (n=7). Most were conducted in the African region (40%) and South-East Asia (25%). Studies demonstrated improved knowledge, attitudes and confidence post-training and improved symptoms and engagement with care, post-implementation. Research studies compared mhGAP-IG-enhanced usual care with task-shared psychological interventions and adaptation studies optimised mhGAP-IG implementation for different contexts. Economic studies calculated human resource requirements of scaling up mhGAP-IG implementation and other educational studies explored its potential for repurposing.ConclusionsThe diverse, expanding global mhGAP-IG literature demonstrates substantial impact on training, patient care, research and practice. Priorities for future research should be less-studied regions, severe mental illness and contextual adaptation of brief psychological interventions.

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“…Sebanyak 11,6% populasi di Indonesia mengidap gangguan mental dan emosional dan sebagian besar yang dialami oleh pengidap gangguan mental dan emosional tidak mendapatkan pengobatan yang sama dengan penyakit lainnya sehingga mengakibatkan kegagalan dalam memberikan standar layanan kesehatan mental di Indonesia, hal tersebut membuat sistem kesehatan di Indonesia masih tertinggal dengan negara tetangganya di asia tenggara (Praharso, Pols, & Tiliopoulos, 2020). Depresi merupakan salah satu penyakit gangguan mental yang serius dan biasa terjadi pada negara yang berpenghasilan rendah dan menengah (Brathwaite, et al, 2020).…”

Section: Pendahuluanunclassified

Classification of Sad Emotions and Depression Through Images Using Convolutional Neural Network (CNN)

Prayuda

2021

JIUP

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The human face has various functions, especially in expressing something. The expression shown has a unique shape so that it can recognize the atmosphere of the feeling that is being felt. The appearance of a feeling is usually caused by emotion. Research on the classification of emotions has been carried out using various methods. For this study, a Convolutional Neural Network (CNN) method was used which serves as a classifier for sad and depressive emotions. The CNN method has the advantage of preprocessing convolution so that it can extract a hidden feature in an image. The dataset used in this study came from the Facial expression dataset image folders (fer2013) where the dataset used for classification was taken with a ratio of 60% training and 40% validation with the results of the trained model of 60% total loss and 68% test accuracy.

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Mental health literacy of Indonesian health practitioners and implications for mental health system development

Cited by 25 publications

References 37 publications

The state of psychiatric research in the Asia Pacific region

The state of psychiatric research in the Asia Pacific region

WHO mental health gap action programme (mhGAP) intervention guide: updated systematic review on evidence and impact

Classification of Sad Emotions and Depression Through Images Using Convolutional Neural Network (CNN)

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