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Enregistrement W3013513826 · doi:10.2196/14030

Controlling for Placebo Effects in Computerized Cognitive Training Studies With Healthy Older Adults From 2016-2018: Systematic Review

2020· review· en· W3013513826 sur OpenAlex
Alexander Masurovsky

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

venuePublié dans une revue dont le pays d'attache est le Canada.
no affAucune affiliation canadienne : ce travail est invisible pour une base fondée sur la seule affiliation.
Aucune affiliation canadienne. Une base fondée sur la seule affiliation (le devis habituel) n'aurait jamais vu ce travail. C'est l'un des travaux qui justifient l'inversion de la base.

Notice bibliographique

RevueJMIR Serious Games · 2020
Typereview
Langueen
DomainePsychology
ThématiqueCognitive Abilities and Testing
Établissements canadiensnon disponible
Organismes subventionnairesMax-Planck-Institut für Kognitions- und NeurowissenschaftenHumboldt-Universität zu BerlinBerlin School of Mind and BrainDeutsche ForschungsgemeinschaftPurdue University
Mots-clésCognitionCognitive trainingPlaceboPsychologyMeta-analysisSystematic reviewMedicineClinical psychologyPhysical medicine and rehabilitationMEDLINEPhysical therapyPsychiatryAlternative medicine

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Computerized cognitive training has been proposed as a potential solution to age-related cognitive decline. However, published findings from evaluation studies of cognitive training games, including metastudies and systematic reviews, provide evidence both for and against transferability from trained tasks to untrained cognitive ability. There continues to be no consensus on this issue from the scientific community. Some researchers have proposed that the number of results supporting the efficacy of cognitive training may be inflated due to placebo effects. It has been suggested that placebo effects need to be better controlled by using an active control and measuring participant expectations for improvement in outcome measures. OBJECTIVE: This review examined placebo control methodology for recent evaluation studies of computerized cognitive training programs with older adult subjects, specifically looking for the use of an active control and measurement of expectations. METHODS: Data were extracted from PubMed. Evaluation studies of computerized cognitive training with older adult subjects (age ≥50 years) published between 2016 and 2018 were included. Methods sections of studies were searched for (1) control type (active or passive) and subtype (active: active-ingredient or similar-form; passive: no-contact or passive-task); (2) if expectations were measured, how were they measured, and whether they were used in analysis; and (3) whether researchers acknowledged a lack of active control and lack of expectation measurement as limitations (where appropriate). RESULTS: Of the 19 eligible studies, 4 (21%) measured expectations, and 9 (47%) included an active control condition, all of which were of the similar-form type. The majority of the studies (10/19, 53%) used only a passive control. Of the 9 studies that found results supporting the efficacy of cognitive training, 5 were for far transfer effects. Regarding the limitations, due to practical considerations, the search was limited to one source (PubMed) and to search results only. The search terms may have been too restrictive. Recruitment methods were not analyzed, although this aspect of research may play a critical role in systematically forming groups with different expectations for improvement. The population was limited to healthy older adults, while evaluation studies include other populations and cognitive training types, which may exhibit better or worse placebo control than the studies examined in this review. CONCLUSIONS: Poor placebo control was present in 47% (9/19) of the reviewed studies; however, the studies still published results supporting the effectiveness of cognitive training programs. Of these positive results, 5 were for far transfer effects, which form the basis for broad claims by cognitive training game makers about the scientific validity of their product. For a minimum level of placebo control, future evaluation studies should use a similar-form active control and administer a questionnaire to participants at the end of the training period about their own perceptions of improvement. Researchers are encouraged to think of more methods for the valid measure of expectations at other time points in the training.

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.

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)0,002
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: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,381
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0090,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
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 Opus0,064
Tête enseignante GPT0,390
Écart entre enseignants0,326 · 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