Understanding of Sustainable Consumption Among University Students: A Cross‐Sectional Study at Herat, Afghanistan
Bibliographic record
Abstract
ABSTRACT This study examines sustainable consumption (SC) among university students in Herat, Afghanistan, focusing on their knowledge, attitudes, and practices (KAP), while identifying key sociodemographic influencing factors. A cross‐sectional study using stratified random sampling included 594 participants from two universities, representing 7608 male undergraduate students. A structured questionnaire assessed knowledge, attitude, and practice. Data analysis was performed using SPSS 27. Overall, 83.0% classified as having high knowledge, 12.8% moderate knowledge, and 4.2% poor knowledge. Regarding attitude, 49.0% had a high attitude, 49.3% moderate attitude, and only 1.7% had a poor attitude. Regarding practice, 59.4% of participants reported moderate practice, 26.9% high practice, and 13.6% poor practice. Single participants (84.8%) had higher levels of knowledge than married ones (83.4%) ( p < 0.05). Both high (84.1%) and low (83.9%) economic status participants had higher knowledge levels than those with middle economic status (78.0%) ( p < 0.05). High attitude was more frequent among Jami University students (59.9%) than Herat University students (45.1%), and among medical students (58.1%) than non‐medical students (46.0%) ( p < 0.05). High practice was also more common among Jami students (42.7%) than Herat students (21.3%), and among medical (35.8%) than non‐medical students (24.0%) ( p < 0.05). The findings indicate a strong level of knowledge among university students regarding SC, though attitudes were mixed and practices remained suboptimal. Significant associations with sociodemographic factors suggest the need for targeted educational interventions to enhance sustainability‐related attitudes and translate knowledge into consistent behavioral practices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".