MétaCan
Menu
Retour à la cohorte
Enregistrement W3008214477 · doi:10.1016/s2589-7500(20)30058-3

Digital health interventions for children with ADHD

2020· letter· en· W3008214477 sur OpenAlexaff
Ferrán Catalá-López, Brian Hutton

Notice bibliographique

RevueThe Lancet Digital Health · 2020
Typeletter
Langueen
DomaineMedicine
ThématiqueAttention Deficit Hyperactivity Disorder
Établissements canadiensOttawa Public HealthUniversity of OttawaOttawa Hospital
Organismes subventionnairesnon disponible
Mots-clésScopusAttention deficit hyperactivity disorderAtomoxetineImpulsivityPsychiatryPsychological interventionMedicinePsychologyMEDLINEPediatricsMethylphenidate

Résumé

récupéré en direct d'OpenAlex

Attention deficit hyperactivity disorder (ADHD) is a childhood-onset disorder characterised by a persistent pattern of symptoms of inappropriate and impaired inattention, hyperactivity, or impulsivity, with difficulties often continuing into adulthood.1Posner J Polanczyk GV Sonuga-Barke E Attention-deficit hyperactivity disorder.Lancet. 2020; 395: 450-462Summary Full Text Full Text PDF PubMed Scopus (211) Google Scholar It is estimated to affect 37·1 million children and young people (aged ≤20 years) worldwide.2James SL Abate D Abate KH et al.Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017.Lancet. 2018; 392: 1789-1858Summary Full Text Full Text PDF PubMed Scopus (5908) Google Scholar Although multiple ADHD treatments are available and widely used (eg, evidence-based behaviour therapy, medications, or a combination of both),3Catalá-López F Hutton B Núñez-Beltrán A et al.The pharmacological and non-pharmacological treatment of attention deficit hyperactivity disorder in children and adolescents: a systematic review with network meta-analyses of randomised trials.PLoS One. 2017; 12e0180355Crossref PubMed Scopus (150) Google Scholar, 4Cortese S Adamo N Del Giovane C et al.Comparative efficacy and tolerability of medications for attention-deficit hyperactivity disorder in children, adolescents, and adults: a systematic review and network meta-analysis.Lancet Psychiatry. 2018; 5: 727-738Summary Full Text Full Text PDF PubMed Scopus (437) Google Scholar their effectiveness has been questioned because they might not fully address the needs of many children with ADHD. Barriers to evidence-based treatment for ADHD include misconceptions and stigma, time, and complexity of interventions, among others.5French B Sayal K Daley D Barriers and facilitators to understanding of ADHD in primary care: a mixed-method systematic review.Eur Child Adolesc Psychiatry. 2019; 28: 1037-1064Crossref PubMed Scopus (26) Google Scholar Digital health interventions, such as those delivered via mobile-based, tablet-based, and web-based platforms, offer diverse possibilities of treatment to address many of the barriers because these interventions can be accessed from everywhere, might support integration across multiple settings (eg, home, education, and health services), and can empower the individuals (and families) to take care of themselves. The evidence base for digital mental health interventions is rapidly accumulating.6Aref-Adib G McCloud T Ross J et al.Factors affecting implementation of digital health interventions for people with psychosis or bipolar disorder, and their family and friends: a systematic review.Lancet Psychiatry. 2019; 6: 257-266Summary Full Text Full Text PDF PubMed Scopus (47) Google Scholar, 7Hollis C Falconer CJ Martin JL et al.Annual research review: Digital health interventions for children and young people with mental health problems- a systematic and meta-review.J Child Psychol Psychiatry. 2017; 58: 474-503Crossref PubMed Scopus (335) Google Scholar For example, a 2017 overview with an updated systematic review of randomised trials7Hollis C Falconer CJ Martin JL et al.Annual research review: Digital health interventions for children and young people with mental health problems- a systematic and meta-review.J Child Psychol Psychiatry. 2017; 58: 474-503Crossref PubMed Scopus (335) Google Scholar identified 21 reviews and 30 randomised controlled trials of digital health interventions for children and young people with mental health problems. Of these, 10 (33%) trials in 853 participants evaluated digital health interventions (including video game programs or computer programs) aimed at improving ADHD outcomes. The review concluded that the effects of digital mental health interventions in managing children with ADHD were uncertain.7Hollis C Falconer CJ Martin JL et al.Annual research review: Digital health interventions for children and young people with mental health problems- a systematic and meta-review.J Child Psychol Psychiatry. 2017; 58: 474-503Crossref PubMed Scopus (335) Google Scholar In The Lancet Digital Health, Scott Kollins and colleagues8Kollins SH DeLoss DJ Cañadas E et al.A novel digital intervention for actively reducing severity of paediatric ADHD (STARS-ADHD): a randomised controlled trial.Lancet Digital Health. 2020; (published online Feb 24.)https://doi.org/10.1016/S2589-7500(20)30017-0Summary Full Text Full Text PDF Scopus (89) Google Scholar sought to provide evidence for the effectiveness of a digital health intervention on attentional functioning and symptoms in children diagnosed with ADHD. The authors did a randomised, double-blind, parallel-group, controlled trial, comprising 348 children with ADHD (aged 8–12 years). Participants were randomised to a video game-like digital health intervention accessed via a tablet-platform (n=180) or a control intervention (n=168). The primary outcome was the mean change in the Attention Performance Index (API), an overall composite score from the Test of Variables of Attention (TOVA). Secondary outcomes included mean changes in non-composite scores on TOVA, spatial working memory (ie, Cambridge Neuropsychological Test Automated Battery), clinician-rated ADHD symptoms (ie, ADHD-Rating Scale [ADHD-RS] subscale and total scale), executive function (ie, parent-completed Behaviour Rating Inventory of Executive Function subscale), impairment (ie, Impairment Rating Scale [IRS]), and global functioning (ie, Clinical Global Impression-Improvement [CGI-I] score). Moreover, treatment response (ie, proportion of responders at appropriate cutoff points on the same rating scales) and safety (ie, any adverse event) were examined. Overall, the authors found that a video game-like digital health intervention resulted in a small but significant effect in improving attention after 4 weeks of treatment (mean change [SD] from baseline on the composite score from the TOVA API was 0·93 [3·15] in the intervention group and 0·03 [3·16] in the control group, adjusted p value 0·0060). However, an effect was not observed in any of the prespecified secondary outcomes, which included some of the most prominent symptom rating scales. As acknowledged by the authors, there were no significant between-group differences in secondary measures (eg, ADHD-RS, CGI-I score, IRS, working memory). Thus, the study was unable to address a major challenge in treatment of children with ADHD, which ultimately should target not only the severity of impairment but also functional outcomes (school performance–social functioning) at that age. The study has several strengths. The research design, which incorporated a randomisation schedule to intervention allocation, masking (of parents, children, and investigators), and its size, which was considerably larger than any of the previous studies in digital mental health.7Hollis C Falconer CJ Martin JL et al.Annual research review: Digital health interventions for children and young people with mental health problems- a systematic and meta-review.J Child Psychol Psychiatry. 2017; 58: 474-503Crossref PubMed Scopus (335) Google Scholar The use of standardised measurement tools, which were applied in two different ways (ie, difference between baseline and post-treatment score, and the proportion of responders as an estimate of clinical relevance). The study is also associated with certain limitations. 4 weeks of treatment exposure (with 25-min daily sessions, approximately) is relatively short. Some difficulties were observed in completing intention-to-treat analysis because of invalid tests or missing data. Thus, the authors excluded participants after the random assignment in their main analyses, which is referred to as modified intention-to-treat.9Abraha I Cherubini A Cozzolino F et al.Deviation from intention to treat analysis in randomised trials and treatment effect estimates: meta-epidemiological study.BMJ. 2015; 350h2445Crossref PubMed Scopus (116) Google Scholar The study also excluded patients with comorbidities and patients receiving concomitant treatments, as have previous studies, and thus there are no data on the efficacy (and safety profile) of the digital health intervention in these populations. However, Kollins and colleagues did give a preliminary indication of the efficacy of a video game-like digital health intervention to improve inattention in a paediatric population with ADHD. What are the implications of these findings for clinical practice? Specifically, how confident should we about the benefits of this digital health intervention for ADHD, and what do the data tell us about the use of the intervention in the target population? The results of Kollins and colleagues' study are interesting and highlight the way for further development of digital health interventions for children with ADHD. Some might argue that efficacy of digital health interventions should be shown on patients with all subtypes of ADHD, and analyses of effects on subtypes (eg, predominantly inattentive ADHD) might be considered secondary. Because of the chronic course of ADHD, in addition to short-term trials, long-term efficacy should be established in future studies.10European Medicines AgencyGuideline on the clinical investigation of medicinal products for the treatment of attention decifit hyperactivity disorder (ADHD). EMEA/CHMP/EWP/431734/2008. European Medicines Agency, London2010Google Scholar Thus, further research is needed to examine ways of sustaining treatment effects over the long-term, in the broader population of children with ADHD including those who have comorbidities and receive evidence-based therapies. For more GBD estimates see https://vizhub.healthdata.org/gbd-compare/ For more GBD estimates see https://vizhub.healthdata.org/gbd-compare/ We declare no competing interests. A novel digital intervention for actively reducing severity of paediatric ADHD (STARS-ADHD): a randomised controlled trialAlthough future research is needed for this digital intervention, this study provides evidence that AKL-T01 might be used to improve objectively measured inattention in paediatric patients with ADHD, while presenting minimal adverse events. Full-Text PDF Open Access

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)0,000
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: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,078
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,002
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 Opus0,107
Tête enseignante GPT0,385
Écart entre enseignants0,277 · 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

Citations3
Publié2020
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueThe Lancet Digital HealthMême sujetAttention Deficit Hyperactivity DisorderTravaux en français237 207