Evidence map›Paper›PMID 29780767›Full record

ArticleJournal of public health research2018

Effectiveness of a multicomponent school based intervention to reduce bullying among adolescents in Chandigarh, North India: A quasi-experimental study protocol.

Monica Rana, Madhu Gupta, Prahbhjot Malhi, Sandeep Grover, Manmeet Kaur

Open access · goldAbstract read
In one paragraph

Article in Journal of public health research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.4field-weighted citation impact, top 17% of its field
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

1 citing paper in PubMed, 14 citations in OpenAlex.

  1. 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

5 authors at 2 institutions in 2 countries.

Monica RanaDepartment of Community Medicine, School of Public Health.
Madhu GuptaDepartment of Community Medicine, School of Public Health.
Prahbhjot MalhiDepartment of Paediatrics.
Sandeep GroverDepartment of Psychiatry, Post Graduate Institute of Medical Education and Research, Chandigarh, India.
Manmeet KaurDepartment of Community Medicine, School of Public Health.
Faculty of Public Health · GBPost Graduate Institute of Medical Education and Research · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBullying perpetration and victimization is associated with significant academic, psychosocial and health related problems among adolescents. There is a need to develop effective interventions to prevent bullying among adolescents, especially in low and middle income countries. This paper presents the study protocol to develop, and evaluate the effect of multi-component school based prevention program for bullying in India.

designQuasi-experimental study.

methodsThe study will be conducted among 846 students of grade 7 EXPECTED IMPACT FOR PUBLIC HEALTH: Bullying is an aggressive behaviour with significant morbidities, including psychological or physical trauma, affecting individuals not only in their adolescence, but also later in their adulthood. This quasi-experimental study is expected to provide evidence on whether multi-component bullying prevention intervention program, can reduce the burden of bullying perpetration and victimization among school adolescents in India. The results of the study will add in the exiting literature on bullying intervention program, especially, from the low middle-income countries, as there are limited studies available on this topic in these countries.

Indexed as

AdolescentsBullyingInterventionSchoolbasedVictimization

Identifiers

PMID29780767
PMCPMC5941258
OpenAlexW2801016275

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.