Evidence map›Paper›PMID 33117755›Full record

ArticleJournal of public health research2020

A training module to empower marginalised Northern Borneo islanders for tuberculosis control.

Mohammad Saffree Jeffree, Fatimah Ahmedy, Mohd Yusof Ibrahim, Khamisah Awang Lukman, Kamruddin Ahmed, Nelbon Giloi, Daw Khin Saw Naing, Aza Sherin Yusuff

Open access · goldAbstract read
In one paragraph

Article in Journal of public health research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 35% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

8 authors at 2 institutions in 3 countries.

Mohammad Saffree JeffreeCommunity and Family Medicine Department.
Fatimah AhmedyDepartment of Surgery.
Mohd Yusof IbrahimCommunity and Family Medicine Department.
Khamisah Awang LukmanCommunity and Family Medicine Department.
Kamruddin AhmedDepartment of Pathobiology and Medical Diagnostics.
Nelbon GiloiCommunity and Family Medicine Department.
Daw Khin Saw NaingCommunity and Family Medicine Department.
Aza Sherin YusuffDepartment of Biomedical Sciences and Therapeutics, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Kota Kinabalu, Sabah.
Universiti of Malaysia Sabah · MYCommunity Living · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Empowering marginalised urban islanders with limited health accessibility through knowledge transfer program for controlling pulmonary tuberculosis (PTB) requires a specific training module. The study was aimed to develop this training module by adapting and modifying the IMCI (Integrated Management of Childhood Illness) framework. Structuring the content for the knowledge and skills for PTB control in the module was based on the National Strategic Plan for Tuberculosis Control 2016-2020. A total of five knowledge and skills were structured: i) PTB disease and diagnosis, ii) PTB treatment, iii) preventive PTB measures, iv) prevention of malnutrition, and v) psychosocial discrimination. The IMCI framework was modified through 3 ways: i) identifying signs and symptoms of PTB, ii) emphasising the IMCI's 5 steps of integrated management: assess, diagnose, treat, counsel and detect, and iii) counseling on BCG immunisation, malnutrition, environmental modifications and stigma on PTB.

Indexed as

Community empowermentIMCI frameworkmarginalised islanderstraining moduletuberculosis control

Identifiers

PMID33117755
PMCPMC7582020
OpenAlexW3096496831

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.