Comparative Analysis of Climate Change Awareness in Climate-Smart and Non-Climate-Smart Villages in the Middle Gangetic Plains of India
- 1School of Social Sciences, College of Post-Graduate Studies in Agricultural Sciences, Central Agricultural University (Imphal), Umiam, Meghalaya (793 103), India
- 2Agricultural Technology Information Centre, Directorate of Extension Education, Dr. Rajendra Prasad Central Agricultural University, Pusa, Bihar (848 125), India
Abstract
This ex-post facto study was conducted from January to August, 2024 in Samastipur and Darbhanga districts of Bihar, India lies within the Middle Gangetic Plains (Agro-Climatic Zone IV) of the Indo-Gangetic Plain, the sole zone where the Climate Smart Agriculture programme had been operationalized. Reliable instruments for quantifying climate change awareness among Indian smallholder farmers remain scarce, limiting the monitoring of adaptation programmes. Hence, the study aimed to adapt, contextualize and validate a 35-item climate change awareness scale and to compare awareness between Climate Smart Village and non-programme farmers. The scale was adapted from an existing climate-awareness interview schedule; the response format was expanded to a five-point continuum, items were re-worded for smallholder farmers, and a fossil-fuels theme was added. Content validity (Lawshe’s ratio, 15 experts) reduced an initial pool of 42 items to 35. The schedule was administered to 200 randomly selected farmers, evenly split between Climate Smart and non-programme villages. Reliability was confirmed through Cronbach’s alpha (0.843), Spearman-Brown split-half (0.762) and Guttman split-half (0.748) coefficients, all significant at the 1% level and supported by analysis of variance with Cochran’s test. Climate Smart Village farmers recorded a significantly higher mean awareness score (93.63) than non-programme farmers (70.33), with lower variance. Among Climate Smart Village farmers, 59% fell in the medium awareness category and 30% in the high, whereas 47% of non-programme farmers remained low. The findings provide a replicable measurement tool and confirm the Climate Smart Village model as effective for building climate literacy.
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BibTeX
@article{borah2026comparative,
title = {{Comparative Analysis of Climate Change Awareness in Climate-Smart and Non-Climate-Smart Villages in the Middle Gangetic Plains of India}},
author = {Abhinab Borah and Sudhanand Prasad Lal and Darathee Das},
journal = {International Journal of Bio-Resource and Stress Management},
year = {2026},
month = oct,
doi = {10.23910/1.2026.7264},
url = {https://doi.org/10.23910/1.2026.7264},
note = {CC BY-NC-SA},
}
RIS
TY - JOUR
TI - Comparative Analysis of Climate Change Awareness in Climate-Smart and Non-Climate-Smart Villages in the Middle Gangetic Plains of India
AU - Abhinab Borah
AU - Sudhanand Prasad Lal
AU - Darathee Das
PY - 2026
DA - 2026/10/31
JO - International Journal of Bio-Resource and Stress Management
DO - 10.23910/1.2026.7264
UR - https://doi.org/10.23910/1.2026.7264
AB - This ex-post facto study was conducted from January to August, 2024 in Samastipur and Darbhanga districts of Bihar, India lies within the Middle Gangetic Plains (Agro-Climatic Zone IV) of the Indo-Gangetic Plain, the sole zone where the Climate Smart Agriculture programme had been operationalized. Reliable instruments for quantifying climate change awareness among Indian smallholder farmers remain scarce, limiting the monitoring of adaptation programmes. Hence, the study aimed to adapt, contextualize and validate a 35-item climate change awareness scale and to compare awareness between Climate Smart Village and non-programme farmers. The scale was adapted from an existing climate-awareness interview schedule; the response format was expanded to a five-point continuum, items were re-worded for smallholder farmers, and a fossil-fuels theme was added. Content validity (Lawshe’s ratio, 15 experts) reduced an initial pool of 42 items to 35. The schedule was administered to 200 randomly selected farmers, evenly split between Climate Smart and non-programme villages. Reliability was confirmed through Cronbach’s alpha (0.843), Spearman-Brown split-half (0.762) and Guttman split-half (0.748) coefficients, all significant at the 1% level and supported by analysis of variance with Cochran’s test. Climate Smart Village farmers recorded a significantly higher mean awareness score (93.63) than non-programme farmers (70.33), with lower variance. Among Climate Smart Village farmers, 59% fell in the medium awareness category and 30% in the high, whereas 47% of non-programme farmers remained low. The findings provide a replicable measurement tool and confirm the Climate Smart Village model as effective for building climate literacy.
SN - 0976-3988
SN - 0976-4038
ER -