Behavioral and Cognitive Impacts of Mindfulness-Based Interventions on Adults with Attention-Deficit Hyperactivity Disorder: A Systematic Review
Bibliographic record
Abstract
Mindfulness-based interventions (MBIs) are becoming increasingly popular as treatments for physical and psychological problems. Recently, several studies have suggested that MBIs may also be effective in reducing symptoms of attention-deficit hyperactivity disorder (ADHD). Most studies have examined the effectiveness in children, but there are now a sufficient number of individual treatment trials to consider a systematic review in adults. Majority of existing systematic reviews and meta-analyses only consider ADHD symptoms as an outcome, and most of them do not fully report potential biases of included studies, thus limiting considerably their conclusions. This is an important facet because some studies could be found ineligible to be included in future analysis due to their low quality. In this systematic review, we followed the PRISMA/PICO criteria and we thoroughly assessed the risks of bias for each of the selected studies according to Cochrane guidelines. We searched the available literature concerning MBIs in adult participants with ADHD using PsycINFO, PubMed, Scopus, and ERIC databases. In total, 13 studies conducted with 753 adults (mean age of 35.1 years) were identified as eligible. Potential moderators such as participants' age, ADHD subtypes, medication status, comorbidity, intervention length, mindfulness techniques, homework amount, and training of therapists were carefully described. Aside from measuring the symptoms of ADHD, outcome measures were categorized into executive/cognitive functioning, emotional disturbances, quality of life, mindfulness, and grade point average at school. According to presented descriptive results, all the studies (100%) showed improvement of ADHD symptoms. In addition, mindfulness meditation training improves some aspects of executive function and emotion dysregulation. Although these are promising findings to support treatment efficacy of MBIs for ADHD, various biases such as absence of randomization and lack of a control group may affect the actual clinical value and implications of the studies. Moreover, the relatively low quality of selection and performance criteria in several studies, as well as relatively high attrition bias across studies, call for caution before considering conducting further analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".