Evidence map›Paper›PMID 39092067›Full record

ArticlePakistan journal of medical sciences2024

Effect of Infra Low Frequency (ILF) neurofeedback training on EEG in children with autism spectrum disorders.

Shemaila Saleem, Syed Hamid Habib

Abstract read
In one paragraph

Article in Pakistan journal of medical sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Shemaila SaleemShemaila Saleem, MBBS, MPH, MPhil. Department of Physiology, Federal Medical College, Shaheed Zulfiqar Ali Bhutto, Medical University (SZABMU), Islamabad, Pakistan.
Syed Hamid HabibSyed Hamid Habib, MBBS, PhD, PGD, DHPE, CHR, CRSM, CME. Department of Physiology, Institute of Basic Medical Sciences, Khyber Medical University, Peshawar, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate whether Infra-low frequency Neurofeedback (ILF-NFB) training can improve brain electrical activity in children with autism spectrum disorders ASD. Method: This single arm pre and post intervention study was carried out at IBMS (Institute of Basic Medical Sciences), Khyber Medical University, Peshawar and Shaheed Zulfiqar Ali Bhutto Medical University (SZABMU), Islamabad from January 2021 to December 2022. A purposive sampling technique was used. Thirty-five ASD children (male=24; female=11; 7-17 years) were provided with 30 sessions of infra low frequency (ILF) neurofeedback training for 15-20 minutes, during 10 weeks. Childhood Autism Rating Scale (CARS) scoring was done and electroencephalogram (EEG) activity was compared before and after ILF-NF training sessions. Results: Around 62.9% participants had mild-moderate autism and 37.1% had severe autism. Wilcoxon Signed rank test revealed a significant decline in delta (Pre-test=47.31±19.22, Post-test=22.07±6.83; p=<0.001), theta (Pre-test=24.75±16.62, Post-test=12.37±3.59; p=<0.001) and alpha (Pre-test=12.01±9.81, Post-test=4.03±1.61; p=< 0.001) waves. Mann Whitney U test exhibited no significant gender differences in EEG pattern before and after neurofeedback except in theta waves ( Conclusion: Decline in delta, theta, beta and alpha waves propose that ILF-NF training can be effective in improving the EEG activity. ILF-NFB can be perceived as a valuable non-invasive, non-pharmacological intervention for improving EEG pattern via reintegration of brain activity resulting in increased the attention and focus, enhanced mental stability and cognitive engagement.

Indexed as

Autism Spectrum DisordersEEGNeurofeedback

Identifiers

PMID39092067
PMCPMC11255799

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.