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Record W4381795473 · doi:10.4314/aamed.v16i3.8

Accès aux technologies digitales pour le traitement ou la gestion thérapeutique des troubles anxieux et dépressifs en Afrique : Une revue systématique de la littérature

2023· article· en· W4381795473 on OpenAlexaboutno aff
Péguy Nkunku, Alain Pesage, Magloire Nkosi Mpembi

Bibliographic record

VenueAnnales Africaines de Medecine · 2023
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsTelepsychiatryContext (archaeology)Psychological interventionTelemedicineAnxietyHumanitiesCoronavirus disease 2019 (COVID-19)Mental healthPsychologyPolitical scienceHealth careMedicinePsychotherapistPsychiatryArtHistory

Abstract

fetched live from OpenAlex

The health measures taken as part of COVID-19 have made access to treatment for anxiety and depressive disorders, including face-to-face consultations, difficult. Faced with this pitfall, the use of digital or virtual care has grown, especially in developed countries such as Canada. In Africa, despite poverty and difficulties in accessing mental health care, some breakthroughs in the use of digital information technologies for the treatment of anxiety and depressive disorders have been made in some countries. In the present work, an update of the recent literature review was carried out through a narrative review dealing with access to effective internet applications for the treatment or therapeutic management of anxiety and depressive disorders in the context of primary health care in Africa during the period of 2010 to 2020. The interventions included the old technologies represented by telepsychiatry and new technologies including smartphones. Despite the absence of virtual platforms for the treatment of anxiety and depressive disorders, the future remains promising thanks to high acceptability and feasibility, as well as the effectiveness of the interventions found in various studies. French Abstract Les mesures sanitaires prises dans le cadre de la COVID- 19 ont rendu l’accès aux traitements des troubles anxieux et dépressifs, notamment les consultations en face à face, difficile. Face à cet écueil, l’usage des soins numériques ou virtuels a pris de l’ampleur, surtout dans les pays développés tels que le Canada. En Afrique, malgré la pauvreté et les difficultés d’accès aux soins de santé mentale, on note quelques percées dans l’usage des technologies digitales de l’information pour le traitement des troubles anxieux et dépressifs dans certains pays. L’objectif poursuivi dans cette revue est de faire un état des lieux de l’usage de ces applications internet en Afrique au cours de cette dernière décennie en se basant sur des critères d’acceptabilité, d’efficacité, d’amélioration clinique, de faisabilité ainsi que d’implantation. La présente revue de littérature a porté sur l’accès à des applications internet efficaces de traitement ou de gestion thérapeutique des troubles anxieux et dépressifs en contexte de santé primaire en Afrique durant la période de 2010 à 2020. Quatorze articles remplissant les critères ont été inclus. Les interventions comprenaient les anciennes technologies représentées par la télé-psychiatrie et les nouvelles technologies incluant les smartphones. A notre connaissance, aucun article n’a été consacré à l’utilisation d’une application virtuelle (ou des nouvelles technologies) dans le traitement exclusif des troubles anxieux et dépressifs en Afrique. Dans la majorité des études, ces technologies étaient essentiellement utilisées pour la détection de la dépression et la gestion thérapeutique. Malgré l’absence des plateformes virtuelles de traitement de troubles anxieux et dépressifs, le futur reste prometteur grâce à une forte acceptabilité et faisabilité, ainsi qu’à l’efficacité des interventions retrouvées dans différentes études. Mots-clés: troubles mentaux courants; gestion thérapeutique; accès à distance; technologies de l'information numérique

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0080.010
Science and technology studies0.0010.003
Scholarly communication0.0080.009
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.379
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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Same venueAnnales Africaines de MedecineSame topicDigital Mental Health InterventionsFrench-language works237,207