Evidence map›Paper›PMID 38519534›Full record

ArticleScientific reports2024

Development and validation of the information-motivation-behavioural skills model-based human immunodeficiency virus education kit for adolescents in Malaysia.

Wan Nur Syamimi Wan Mohamad Darani, Aimi Nadira Mat Ruzlin, Zahir Izuan Azhar, Xin Wee Chen

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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

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

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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.

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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

4 authors.

Wan Nur Syamimi Wan Mohamad DaraniDepartment of Public Health Medicine, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh, Malaysia.
Aimi Nadira Mat RuzlinDepartment of Public Health Medicine, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh, Malaysia.
Zahir Izuan AzharDepartment of Public Health Medicine, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh, Malaysia.
Xin Wee ChenDepartment of Public Health Medicine, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh, Malaysia. drchenxw@uitm.edu.my.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The growing Human Immunodeficiency Virus (HIV) incidences and insufficient HIV knowledge among Malaysian late adolescents necessitate immediate attention to HIV prevention via education. This study aims to develop and validate an Information-Motivation-Behavioural skills (IMB) model-based education kit for adolescents, PREM-Kit, to educate on HIV prevention among Malaysian late adolescents. Utilizing the Analysis, Design, Development, Implementation, and Evaluation model, we conducted the study in three phases: needs assessment, development of PREM-Kit, and validation of PREM-Kit by applying the IMB model to map the PREM-Kit's contents. PREM-Kit, developed in Malay language, consisted of an infographic flip chart and videos. Five multi-disciplinary experts validated the PREM-Kit using the content validity index (CVI), and 13 end-users validated the PREM-Kit using the Malay version of the Patient Education Materials Assessment Tool for Printable and Audiovisual Materials. The infographic flip chart comprised three modules covering 15 topics, and an animated video accompanied each module. PREM-Kit achieved CVI scores of 1.0 and median scores of over 80% for understandability and actionability. Overall, the newly developed IMB model-based HIV education kit has good content validity, is simple to comprehend and apply, and is ready for testing its effectiveness in improving adolescents' knowledge, attitudes, and practices for HIV prevention.

Indexed as

HIV InfectionsInformation Motivation Behavioral Skills ModelAdolescentAttitudeHIVHumansMalaysiaReceptor Protein-Tyrosine KinasesReceptor Protein-Tyrosine Kinases

Identifiers

PMID38519534
PMCPMC10959928

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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.