Evidence map›Paper›PMID 37706101›Full record

ArticleAnnals of neurosciences2023

Development and Validation of Yoga Protocol for Patients with Depression.

Dhamodhini K S, Maheshkumar K, Santhi Silambanan, Suvarna Jyothi Kantipudi, R Sathianathan, Padmavathi R

Abstract read
In one paragraph

Article in Annals of neurosciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Asynchronous Technologies in Mental Health Care and Education.Current treatment options in psychiatry · 2023
    Review
  4. 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

6 authors.

Dhamodhini K SDepartment of Physiology, Sri Ramachandra Medical College and Research Institute, Chennai, Tamil Nadu, India.
Maheshkumar KDepartment of Physiology, Government Yoga and Naturopathy Medical College and Hospital, Chennai, Tamil Nadu, India.ORCID https://orcid.org/0000-0002-5377-7847
Santhi SilambananDepartment of Biochemistry, Sri Ramachandra Medical college and Research institute, SRIHER, Chennai, Tamil Nadu, India.
Suvarna Jyothi KantipudiDepartment of Psychiatry, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, Tamil Nadu, India.ORCID https://orcid.org/0000-0002-9161-3229
R SathianathanDepartment of Psychiatry, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, Tamil Nadu, India.
Padmavathi RDepartment of Physiology, Sri Ramachandra Medical College and Research Institute, Chennai, Tamil Nadu, India.ORCID https://orcid.org/0000-0002-6698-0764

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Scientific evidence suggests that yoga is beneficial for treating mental health disorders. To the best of our knowledge, minimal studies have been done on the development of a yoga module for the specific clinical aspects of depression and there is no particular study on yoga protocol development for mild depression and moderate depression. Purpose: The primary aim of this study is to develop specific yoga protocol modules for treating patients affected with mild and moderate depression. Methods: Yoga protocols for treating mild and moderate depression were developed using classical yoga texts, previous literature, and with the help of yoga experts. 26 practices for mild depression and 35 practices for moderate depression were identified, each of which was scored as (a) not essential, (b) useful but not essential, and (c) essential, and content validity ratio (CVR) determined using Lawshe's formula for the validation. Results: Expert's opinion revealed that 13 out of 28 practices and 12 out of 35 practices showed significant CVR (>0.60) for mild and moderate depression. Conclusions: The yoga practices developed based on experts' opinion is the first step toward the development of a validated protocol for mild and moderate depression. This will be assessed for its effectiveness through a randomized controlled study to confirm the module's efficiency.

Indexed as

Depressionexperts viewvalidationyoga protocol

Identifiers

PMID37706101
PMCPMC10496798

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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.