Dataset Information

Dismantling cognitive-behavioural therapy components for attention-deficit hyperactivity disorder in adolescents and adults: protocol for a network meta-analysis.

ABSTRACT:

Introduction

Cognitive-behavioural therapy (CBT) consists of multiple treatment techniques for each treatment model and is tailored to the patient's characteristics. Randomised controlled trials (RCTs) have reported that CBT is effective for attention-deficit/hyperactivity disorder (ADHD); however, which CBT components are effective is unknown. In order to provide the best treatment technique, it is important to know which therapeutic component or combination thereof is more effective and what the specific effect size is.

Methods and analysis

We will perform component network meta-analysis (cNMA). The search will include studies published from database inception up to 31 March 2022, in English. The electronic databases of MEDLINE (via PubMed), EMBASE, PsycINFO, ClinicalTrials.gov and Cochrane Library will be searched. We will systematically identify all RCTs in the treatment of ADHD between the ages of 10 and 60 years, comparing interventions composed of various CBT components with controlled interventions. We will perform pairwise and network meta-analysis with random effects to estimate summary ORs and standardised mean differences. We will assess the risk of bias in selected studies using the Cochrane risk of bias tool.

Ethics and dissemination

Since we will review published papers, ethical approval is not required. The results from this cNMA will provide a panorama of the CBT-based ADHD studies. The results of this study will be published in a peer-reviewed journal.

Prospero registration number

CRD42022323898.

SUBMITTER: Hamatani S

PROVIDER: S-EPMC10124286 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dismantling cognitive-behavioural therapy components for attention-deficit hyperactivity disorder in adolescents and adults: protocol for a network meta-analysis.

Hamatani Sayo S Matsumoto Kazuki K Kunisato Yoshihiko Y Okawa Sho S Yamashita Masatoshi M Mizuno Yoshifumi Y

BMJ open 20230419 4

<h4>Introduction</h4>Cognitive-behavioural therapy (CBT) consists of multiple treatment techniques for each treatment model and is tailored to the patient's characteristics. Randomised controlled trials (RCTs) have reported that CBT is effective for attention-deficit/hyperactivity disorder (ADHD); however, which CBT components are effective is unknown. In order to provide the best treatment technique, it is important to know which therapeutic component or combination thereof is more effective an ...[more]

PMID: 37076162

Similar Datasets

Project description:Functional Magnetic Resonance Imaging Neurofeedback (fMRI-NF) targeting brain areas/networks shown to be dysfunctional by previous fMRI research is a promising novel neurotherapy for ADHD. Our pioneering study in 31 adolescents with ADHD showed that fMRI-NF of the right inferior frontal cortex (rIFC) and of the left parahippocampal gyrus (lPHG) was associated with clinical improvements. Previous studies using electro-encephalography-NF have shown, however, that not all ADHD patients learn to self-regulate, and the predictors of fMRI-NF self-regulation learning are not presently known. The aim of the current study was therefore to elucidate the potential predictors of fMRI-NF learning by investigating the relationship between fMRI-NF learning and baseline inhibitory brain function during an fMRI stop task, along with clinical and cognitive measures. fMRI-NF learning capacity was calculated for each participant by correlating the number of completed fMRI-NF runs with brain activation in their respective target regions from each run (rIFC or lPHG); higher correlation values were taken as a marker of better (linear) fMRI-NF learning. Linear correlations were then conducted between baseline measures and the participants' capacity for fMRI-NF learning. Better fMRI-NF learning was related to increased activation in left inferior fronto-striatal regions during the fMRI stop task. Poorer self-regulation during fMRI-NF training was associated with enhanced activation in posterior temporo-occipital and cerebellar regions. Cognitive and clinical measures were not associated with general fMRI-NF learning across all participants. A categorical analysis showed that 48% of adolescents with ADHD successfully learned fMRI-NF and this was also not associated with any baseline clinical or cognitive measures except that faster processing speed during inhibition and attention tasks predicted learning. Taken together, the findings suggest that imaging data are more predictive of fMRI-NF self-regulation skills in ADHD than behavioural data. Stronger baseline activation in fronto-striatal cognitive control regions predicts better fMRI-NF learning in ADHD.

Dataset Information

Dismantling cognitive-behavioural therapy components for attention-deficit hyperactivity disorder in adolescents and adults: protocol for a network meta-analysis.

Introduction

Methods and analysis

Ethics and dissemination

Prospero registration number

Publications

Dismantling cognitive-behavioural therapy components for attention-deficit hyperactivity disorder in adolescents and adults: protocol for a network meta-analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets