MétaCan
Menu
Retour à la cohorte
Enregistrement W4205326310 · doi:10.1111/add.15797

Commentary on Song <i>et al</i>: Brain stimulation for addictions‐ optimizing impact via strategic interleaving with pharmacotherapy, cognitive behavioral therapy, and restructuring the micro‐environment

2022· letter· en· W4205326310 sur OpenAlexaffabout
Peter A. Hall, Amer M. Burhan

Notice bibliographique

RevueAddiction · 2022
Typeletter
Langueen
DomaineNeuroscience
ThématiqueTranscranial Magnetic Stimulation Studies
Établissements canadiensOntario Shores Centre for Mental Health SciencesUniversity of Waterloo
Organismes subventionnairesnon disponible
Mots-clésContext (archaeology)Brain stimulationAddictionPsychologyIntervention (counseling)PsychotherapistModalitiesDeep brain stimulationPharmacotherapyPsychiatryCognitionTranscranial direct-current stimulationStimulationNeuroscienceMedicineClinical psychology

Résumé

récupéré en direct d'OpenAlex

Song and colleagues[1] may be helping us to finally answer basic questions about efficacy of brain stimulation methods and move toward equally pressing questions as to how we can obtain optimal synergies between brain stimulation methods and other modalities, including the restructuring of the microenvironment. How does one go about strategically combining brain stimulation with pharmacotherapy, psychotherapy and other addictions treatment modalities? Issues related to risks and benefits, optimum timing and parameter selection of brain stimulation in relation to medical and psychosocial addiction intervention need to be considered carefully. Some psychotropic medications used in the context of addiction can lower the seizure threshold, and while this does not seem to add major risk of seizures when rTMS is used to treat depression [2], the risk of seizure might increase in the context of acute toxicity or withdrawal from substances of abuse [3]. On the other hand, some psychotropics used to manage addiction (e.g. benzodiazepine) can reduce efficacy of brain stimulation by interfering with the underlying mechanism of treatment [4]. Increasingly there are attempts to integrate rTMS with cognitive behavioral therapy. Indeed this happens incidentally in clinical practice on a routine basis, by virtue of the fact that many individuals undergoing brain stimulation treatment are also receiving ongoing psychotherapeutic intervention, either in group or individual format. What is largely missing is the strategic timing of sessions and phases of therapy with stimulation such as to maximize their impact. For instance, early in CBT treatment it might be important to bolster brain networks supporting self-regulatory processes in craving control, long enough for the individual to gain a foothold and benefit from the skills offered for craving control by the therapist. Likewise, an argument could be made that stimulation sessions should be timed such that peak benefit coincides with the most taxing phase of therapy, wherein self-regulation of emotional responses is especially important; in the case of cue exposure sessions, this might mean that stimulation should reach its maximum impact before exposure is attempted. The same logic could support timing the sessions so that maximum benefit is received before reintegration back into a risky environment, following release from an inpatient treatment program. The primary point is that strategic interleaving of rTMS and psychotherapeutic intervention seems to be potentially very important, and yet we know very little about it. Only careful empirical research can inform questions about optimal timing of stimulation in relation to psychotherapeutic interventions like CBT. Finally, an important future avenue for intervention is pairing brain stimulation with strategic changes in the micro-environment (i.e., the context in which the craving object is routinely encountered in everyday life). Using the example of eating, we have found that indulgent food consumption is jointly impacted by both stimulation type and the nature of cues in the eating environment [5]. Engineering the micro-environment to reduce cued cravings may optimize the impact of strengthening of brain networks using brain stimulation methods. Beyond this, the wider macro-environment supporting or mitigating indulgence of various types is the province of public health, meaning that multi-level interventions—from brain to society—may be critical for managing addictions of all types. Ultimately, brain stimulation research and public health research may be mutually reinforcing. The first author wishes to acknowledge funding support from the Natural Sciences and Engineering Research Council of Canada (NSERC). None. PAH wrote the initial draft; PAH and AMB contributed to the final draft.

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: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,294
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)0,0000,000
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 Opus0,062
Tête enseignante GPT0,328
Écart entre enseignants0,266 · 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
GenreEmpirique

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

En bref

Citations0
Publié2022
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueAddictionMême sujetTranscranial Magnetic Stimulation StudiesTravaux en français237 207