Evidence map›Paper›PMID 42338772›Full record

SynthesisFrontiers in cognition2026

Cognitive mapping to decode farmers' mindsets in agricultural decision-making: a systematic review.

Arunachalam Panchatcharam SriVidhya, Paul J Mansingh

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in cognition, 2026. 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
–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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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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

2 authors.

Arunachalam Panchatcharam SriVidhyaDepartment of Agricultural Extension and Economics, VIT School of Agricultural Innovations and Advanced Learning (VAIAL), Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Paul J MansinghDepartment of Agricultural Extension and Economics, VIT School of Agricultural Innovations and Advanced Learning (VAIAL), Vellore Institute of Technology, Vellore, Tamil Nadu, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Farmers decision-making processes are critical to the implementation of technologies and climate-resilient sustainable practices. These decisions are subject to complex thinking processes, which include risk perception and belief systems. This systematic review explains the decision-making process of farmers, through cognitive mapping. Moreover, it examines mental models, perception, belief system and cause-effect relationship of farmers with particular attention given to their behavior and practices. Methods: The research adopted the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) framework. It utilized Scopus and Web of Science databases to retrieve 80 articles. The main aim was to identify research trends and gaps through bibliometric analysis and the TCCM framework by focusing on major theories, contexts, characteristics, and methodologies of agricultural cognitive-mapping research. Results: The major trends identified in this study are risk perception in agricultural economics, climatic change, technology adoption, conservative agricultural and sustainability. The major stakeholders considered included farmers (cattle, pig, rice, and date farmers), extension agents, policymakers, NGOs, rural households, agro-industries, technology providers, and the holders of indigenous knowledge. There are still major gaps in understanding the psychological and cognitive processes underlying the decisions of farmers: longitudinal studies are limited, the role of gender is not studied thoroughly, particularly in the conditions of climate-change effects and policy shifts. Discussion: Though, the mental model, perceptions, and belief systems have a significant impact on agricultural decision-making, there are still gaps in the comprehension of psychological and cognitive mechanisms involved since it is a persistent problem in the agricultural decision-making process. Future studies must incorporate the behavioral psychology, mixed-methods and cross-cultural research designs to develop integrated models that support agricultural sustainability and resilience.

Indexed as

agriculturebehaviorcognitive mappingdecision-makingfarmersTCCM

Identifiers

PMID42338772
PMCPMC13281049

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.