Evidence map›Paper›PMID 36413007›Full record

ArticleGM crops & food2022

Farmers' knowledge, attitudes, and practices towards the adoption of hybrid rice production in Bangladesh: an PLS-SEM approach.

Paresh Kumar Sarma, Mohammad Jahangir Alam, Ismat Ara Begum

Abstract read
In one paragraph

Article in GM crops & food, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

3 authors.

Paresh Kumar SarmaSenior Scientific Officer (SG), Bangladesh Agricultural University Research System (BAURES), Bangladesh Agricultural University, Mymensingh, Bangladesh.ORCID 0000-0001-9948-1673
Mohammad Jahangir AlamProfessor, Department of Agribusiness and Marketing, Bangladesh Agricultural University, Mymensingh, Bangladesh.ORCID 0000-0003-3412-9438
Ismat Ara BegumProfessor, Department of Agricultural Economics, Bangladesh Agricultural University, Mymensingh, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the government policy supports the adoption of hybrid rice in Bangladesh but there is no significant progress has been made over the last decades. The study aimed to determine farmers' knowledge, attitudes, and practices (KAPs) of hybrid rice adoption, and the causal relationship between them in Bangladesh. Using a stratified random sampling technique, 244 cross-sectional surveys were done from the Sherpur district of Bangladesh. The descriptive statistics, two-round Delphi method, and partial least squares structural equation modeling (PLS-SEM) were used to estimate latent variables and identify the causal relationship between KAPs. The results revealed that farmers' knowledge and attitudes were directly and significantly associated with the adoption of hybrid rice. This implies that farmers who are well informed about the usage of hybrid rice and are likely to embrace it and raise their revenue, can be influenced by knowledge. The study found a significant positive role for knowledge about hybrid rice, attitudes, and practices in adopting hybrid rice. This study provides a primary understanding of the relationship between psychological factors and the adoption of hybrid rice technology to increase rice farm productivity. The findings suggest that policymakers, researchers and development agencies should focus on farmers' psychological factors in improving the adoption of hybrid rice in Bangladesh.

Indexed as

FarmersOryzaBangladeshCross-Sectional StudiesHealth Knowledge, Attitudes, PracticeHumansLatent Class AnalysisLeast-Squares AnalysisHybrid rice adoptionKAPPLS-SEMproductionSmartPLS3 software

Identifiers

PMID36413007
PMCPMC9683048

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.