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Enregistrement W3184776326 · doi:10.1016/j.jadohealth.2021.04.024

You Can’t Manage What You Do Not Measure - Why Adolescent Mental Health Monitoring Matters

2021· article· en· W3184776326 sur OpenAlexaboutno aff
Joseph Hayes, Liliana Carvajal-Vélez, Zeinab Hijazi, Jill W. Åhs, P. Murali Doraiswamy, Fatima Azzahra El Azzouzi, Cameron Fox, Helen Herrman, Charlotte Petri Gornitzka, Brandon Staglin, Miranda Wolpert

Notice bibliographique

RevueJournal of Adolescent Health · 2021
Typearticle
Langueen
DomainePsychology
ThématiqueChild and Adolescent Psychosocial and Emotional Development
Établissements canadiensnon disponible
Organismes subventionnairesWellcome TrustUNICEFBill and Melinda Gates Foundation
Mots-clésMeasure (data warehouse)Mental healthPsychologyAdolescent healthPsychiatryMedicineComputer scienceNursingData mining

Résumé

récupéré en direct d'OpenAlex

Despite growing awareness of mental health conditions in recent years, funding for mental health science has not increased. The 2020 International Alliance of Mental Health Research Funders report “The Inequities of Mental Health Research Funding” [[1]Woelbert E. White R. Lundell-Smith K. et al.The inequities of mental health research (IAMHRF). Digital Science. Report.https://doi.org/10.6084/m9.figshare.13055897.v2Date: 2020Date accessed: January 20, 2021Google Scholar] reveals some stark inequalities and highlights issues with resource allocation. Although the global cost of mental health conditions is projected to exceed $6 trillion by 2030 [[2]Bloom D.E. Cafiero E.T. Jané-Llopis E. et al.The global economic burden of non-communicable diseases. World Economic Forum, Geneva2011Google Scholar], global investments in mental health research have remained approximately $3.7 billion per year in real terms between 2015 and 2019, equating to roughly 50 cents per person per year. Only 2.4% of this research funding is spent in low- and middle-income countries (LMICs), despite accounting for 84% of the world’s population. Only 33% of the total is invested in mental health research involving young people, despite this being the peak age of onset of the majority of mental health conditions, and where prevention and early intervention can avert the lifelong disability and suffering that underlie the tremendous cost. Because research expenditure is so at odds with the burden of mental ill-health experienced globally, major knowledge gaps persist: (1) data on prevalence of adolescent mental health conditions is sparse, especially in LMICs. Data about mental health conditions among adolescents that are available are representative of a very small proportion of the population and more than 100 countries have no data [[3]Erskine H. Baxter A. Patton G. et al.The global coverage of prevalence data for mental disorders in children and adolescents.Epidemiol Psychiatr Sci. 2017; 26: 395-402Crossref PubMed Scopus (212) Google Scholar]; (2) solid evidence on scalable approaches for mental health care, for prevention of mental health conditions in children and adolescents, promotive mental health strategies, and for addressing mental health determinants is limited, particularly from LMICS. These data and evidence are urgently needed to guide strategic actions to address the burden of mental health problems among adolescents through effective national policies and programs. Better collection and management of mental health data, through routine data collection platforms, has become a major focus of large research agencies including the US National Institute of Mental Health and the Wellcome Trust. Together they have formed the Common Measures in Mental Health Science Governance board and outlined an initial core list of research questionnaires that should be used by funded researchers. UNICEF has made extensive efforts, in collaboration with academic and institutional partners, including the World Health Organisation, to adapt and validate these common measures for use at the population level in LMICs, through the MMAP initiative (Measurement of Mental health among Adolescents at the Population level) [[4]Carvajal L. Increasing data and understanding of adolescent mental health worldwide: UNICEF’s measurement of mental health among adolescents at the population level initiative.J Adolesc Health. 2021; 69https://doi.org/10.1016/j.jadohealth.2021.03.019Abstract Full Text Full Text PDF Scopus (13) Google Scholar]. Field work for the MMAP initiative currently involves implementation of the MMAP protocol for transcultural translation, adaptation, and clinical validation in four settings: Belize, South Africa, Kenya, and Nepal. Transcultural translation and adaptation work is ongoing in Angola. However, this project and similar attempts to improve our understanding of adolescent mental health in LMICs require sustained engagement at the country level, sustained advocacy at all levels, and sustained funding. Each of these elements is precarious; however, the two former components cannot occur without the latter. There is some evidence that certain research funding sectors, including philanthropists, are reluctant to invest in mental health, which can be taken as an indication for a low position on the agenda. This may be due to fragmentation of advocacy efforts around the issue of parity, and perceived complexity, and may also relate to stigma and insufficient mobilization of persons and their families with mental health conditions to form powerful constituencies, and to press for the availability of effective and humane mental healthcare [[5]Future GenerationAustralia’s mental health crisis: Why private funders are not answering the call.https://futuregeninvest.com.au/wp-content/uploads/2019/10/AustraliasMentalHealthCrisis.pdfDate: 2019Date accessed: January 25, 2021Google Scholar]. The International Alliance of Mental Health Research Funders report shows the inequalities that exist in this area, and the UNICEF initiative shows what is possible if research funding is allocated to such major public health issues. Prior to the COVID-19 pandemic, there was evidence of increasing adolescent mental health needs in high-income countries [[6]Lipson S.K. Lattie E.G. Eisenberg D. Increased rates of mental health service utilization by US college students: 10-year population-level trends (2007–2017).Psychiatr Serv. 2019; 70: 60-63Crossref PubMed Scopus (417) Google Scholar,[7]Wiens Canadian Wiens K. Bhattarai A. et al.A growing need for youth mental health services in Canada: Examining trends in youth mental health from 2011 to 2018.Epidemiol Psychiatr Sci. 2020; 29: e115https://doi.org/10.1017/S2045796020000281Crossref PubMed Scopus (87) Google Scholar]. We are yet to see the full effects of the pandemic, the necessary restrictive measures, or longer term economic consequences on mental health. However, it seems likely that there will be significant increases in mental health problems [[8]Pfefferbaum B. North C.S. Mental health and the Covid-19 pandemic.New Engl J Med. 2020; 383: 510-512Crossref PubMed Scopus (2745) Google Scholar]. It is unclear if LMICs will follow this pattern, but their recovery may be more protracted [[9]Kelley M. Ferrand R.A. Muraya K. et al.An appeal for practical social justice in the COVID-19 global response in low-income and middle-income countries.The Lancet Glob Health. 2020; 8: e888-e889Abstract Full Text Full Text PDF PubMed Scopus (61) Google Scholar] and addressing mental health problems may be more challenging [[10]Kola L. Global mental health and COVID-19.The Lancet Psychiatry. 2020; 7: 655-657Abstract Full Text Full Text PDF PubMed Scopus (96) Google Scholar]. In 2020, UNICEF and the World Health Organization signed a joint programme agreement for the 2020-2030 period on Mental Health and Psychosocial Wellbeing and Development of Children and Adolescents, in which one of the four core programme strategies is to strengthen information systems, evidence and research [[11]United Nations Children’s FundWorld Health OrganizationUNICEF/WHO Joint Programme Document, 2020-2030 on Mental Health and Psychosocial Wellbeing and Development of Children and Adolescents. World Health Organization, 2021https://www.corecommitments.unicef.org/mhpssDate accessed: June 28, 2021Google Scholar]. We agree that this is imperative, and that research funding allocation needs to be considered as a key element of achieving the “Grand Challenges in Global Mental Health” [[12]Collins P.Y. Patel V. Joestl S.S. et al.Grand challenges in global mental health.Nature. 2011; 475: 27-30Crossref PubMed Scopus (1410) Google Scholar]. We believe that, to catalyze sustained, large-scale investment in the science and services that will lead to preventions and cures, funders need to first commit to support for the data generation that will crystallize global knowledge of the crisis. The ultimate metric of impact, of course, is the research-driven reduction of the global burden of mental health conditions, but this impact can only be measured with the sustained funding for projects that will close the data gap. This work was funded by the Wellcome Trust grant 211085/Z/18/Z (J.H.).

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,677
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,038
Tête enseignante GPT0,319
Écart entre enseignants0,281 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations28
Publié2021
Routes d'admission1
Résumé présentoui

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