Global priorities of civil society for mental health services: findings from a 53 country survey
Notice bibliographique
Résumé
Mental disorders account for 13% of global disease burden, and major depression alone is expected to be the largest burden contributor by 2030 1. For people with mental disorders, life expectancy is reduced by 15-20 years 2. Mental disorders are predicted by 2030 to account for nearly a third of the projected US$47 trillion incurred by all non-communicable diseases 3. They also incur political costs – mental disorders impact on progress towards Millennium Development Goals 4. Services for people with mental disorders are insufficient, inequitably distributed, and inefficiently used 5, especially in less developed countries 6. Most countries allocate less than 2% of their health budgets to mental health 7. This difference between health need (13%) and resource allocation (2%) has become known as the “treatment gap” 8. One approach to reducing the treatment gap is through global policy. The World Federation for Mental Health (WFMH), in strategic alliance with the Movement for Global Mental Health, formed the “Great Push for Mental Health”. A goal of this campaign is to ascertain what people with a personal or professional interest in mental health identify as priorities for services. From June to November 2012, we surveyed 473 WFMH members (comprising organizations and individuals) to establish priorities for mental health services of key civil society stakeholders, specifically including consumers, family members and professionals. The survey comprised general and specific priorities, characteristics of good community mental health care, and progress indicators informed by the Lancet Global Mental Health Group 9. Items were individually rated for importance, and four top priorities within each group were ranked. Organizations were grouped into low, middle or high income band using the World Bank Atlas method. Responses were received from 96 organizations (20%), representing 15 low income (16%), 28 middle income (29%), 43 high income (45%) and 10 multiple (10%) countries. Fifty-nine (62%) represented service users (range 3 to 250,000, total 589,900), 49 (51%) represented family members (range 1 to 400,000, total 530,916), 50 (52%) represented mental health professionals (range 2 to 25,000, total 55,411) and 23 (24%) represented groups of mental health organizations (range 1 to 283, total 519). Sixty (63%) provided mental health services to a total of 681,761 (range 10 to 350,000) people, and 92 (96%) aimed to influence national mental health policy. Respondents represented 53 countries: Afghanistan (n=2), Albania (n=2), Argentina, Australia (n=4), Austria (n=3), Bangladesh, Bosnia/Herzegovina, Brazil (n=2), Burundi, Cambodia, Canada (n=3), Cape Verde, China, Cook Islands, Democratic Republic of Congo, England/UK (n=2), Ethiopia, Fiji, France, Ghana (n=2), Gibraltar, Greece (n=4), Haiti, Hong Kong, Hungary, India (n=4), Ireland, Italy, Ivory Coast, Kenya (n=4), Lebanon, Luxembourg, Madagascar, Malawi, Malaysia (n=2), Malta (n=2), Mexico (n=3), Nepal (n=6), Netherlands, New Zealand (n=2), Nigeria (n=2), Peru, Portugal (n=2), Rwanda (n=2), Slovenia, Somaliland, South Africa (n=3), Spain, South Sudan, Swaziland, Tanzania, Uruguay and USA (n=12). Logistic regression of income group on response showed that the 17% response rate from the 257 high income organizations was significantly (β=.583, p<0.001) lower than from the 38 low income (39%) and the 16 international (63%) organizations, but not from the 162 middle income (17%) organizations. All eleven general priorities achieved consensus, demonstrating global agreement on the general principles for mental health systems. Highest ranked general priorities were “a national mental health policy or strategy” (no. 1), “promoting campaigns to eliminate stigma and discrimination” (no. 2), “strengthening and enabling psychosocial treatments aimed at recovery and where appropriate, return to work” (no. 3) and “facilitating the move from mental hospital to community care” (no. 4). Fourteen out of the 18 specific priorities achieved consensus across income bands. Four (HIV/AIDS, man-made disasters including war, genocide and battle stress, natural disasters and tropical diseases) were rated highest in low income countries and lowest in high income countries. All income groups agreed that the highest priority is “enabling community-based treatment for mental illness”. All eleven characteristics of good community mental health care achieved consensus, indicating global consensus on the meaning of community care. The highest ranking characteristic was “there will be an effective programme for encouraging advocacy and research in the prevention of mental illness and disability and in the promotion of mental health”. All but two (proportion of involuntary admissions and proportion of psychiatrists) progress indicators achieved consensus. Highest ranked indicators were “specified budget for mental health as a proportion of total health budget” (no. 1); “presence of official policy, programmes, or plans for mental health, either including or accompanied by a policy on child and adolescent mental health” (no. 2), and “proportion of total mental health expenditure spent on community-based services, including primary and general health-care services” (no. 3). Respondents were asked to specify a reasonable percentage of health budget to spend on mental health services. Although the response was continuous (i.e., not pre-specified bands), there was consensus across all income groups that 10% of health budget should be allocated for mental health. Electronic technologies, person-centred care and consumer group involvement in policy-making were also all positively supported. Finally, professional groups were rated for value for money. No income group differences were found, and rankings were psychiatric/mental health nurses (best value for money), followed in order by psychiatrists, general medical practitioners, social workers, community health workers, psychologists, support group members and general/physical health nurses (worst value for money). To summarize, in this 53-country survey we demonstrated the emergence at the international level of cross-sectoral agreement on the appropriate structure for mental health services, including a greater orientation towards community rather than hospital care, with psychosocial and pharmacological treatments available from an adequately skilled workforce at primary and secondary care. The highest identified priority was a national mental health strategy. Currently, there are marked differences across regions. Of the fifteen countries in East and South East Asia, fourteen (93%) have policy and ten (67%) have legislation 10. Across 53 European countries, 44 (83%) have policy and 50 (95%) have legislation 11, and across 34 Latin America countries, 24 (70%) have policy and three (10%) have legislation 12. Community-based treatment was universally endorsed, but experience in China illustrates that translating pro-community mental health policy into reduced spend on hospitals remains difficult 13. Challenges identified across Africa include competing priorities, waning community engagement, and the non-sustainability of reliance on community volunteers 14. The importance of person-centred care and consumer input to policy was highlighted. In English-speaking high income countries, this reflects a growing re-orientation of services towards recovery 15. A systematic review identified key recovery processes as connectedness, hope and optimism about the future, identity, meaning in life, and empowerment (giving the acronym CHIME) 16, although data were mainly from English-speaking countries 17. Understanding the meaning of recovery in other cultures is a research priority 18. There is global consensus that a target of 10% of health spend should be allocated to mental health services. Re-distributing resources to be more consistent with disease burden would allow “scaling up” of the coverage of services for mental disorders. Scaling up has emerged as an international priority 9, especially within low and middle income countries 19. The financial resource needed are modest: US$2 per person in low income countries, and US$3-4 in lower middle-income countries 20. These results were conveyed to the World Health Organization for consideration and have been incorporated in the People's Charter for Mental Health. John Copeland1, Graham Thornicroft2, Victoria Bird2, John Bowis1, Mike Slade2 1World Federation for Mental Health: Great Push for Mental Health, P.O. Box 807, Occoquan, VA 22125, USA and Division of Psychiatry, University of Liverpool, UK; 2King's College London, Health Service and Population Research Department, Institute of Psychiatry, Denmark Hill, London SE5 8AF, UK The authors thank Deborah Maguire for invaluable assistance with data collection.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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