Evidence map›Paper›PMID 41495160›Full record

ArticleScientific reports2026

Impact of self-efficacy on food waste reduction and its consequences in the solid waste economy using Monte Carlo simulation.

Elham Nejadsadeghi, Maryam Delavari Heravi, Masoud Yousefi, Mohammad Ansarizadeh, Afsaneh Ghasemi

Abstract read
In one paragraph

Article in Scientific reports, 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

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

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

5 authors.

Elham NejadsadeghiBehbahan Faculty of Medical Sciences, Behbahan, Iran.
Maryam Delavari HeraviDepartment of Public Health, Neyshabur University of Medical Sciences, Neyshabur, Iran.
Masoud YousefiDepartment of Environmental Health Engineering, Mamasani Higher Education Complex for Health, Shiraz University of Medical Sciences, Shiraz, Iran.
Mohammad AnsarizadehDepartment of Environmental Health Engineering, Mamasani Higher Education Complex for Health, Shiraz University of Medical Sciences, Shiraz, Iran. mansarizadeh@yahoo.com.
Afsaneh GhasemiDepartment of Public Health, Fasa University of Medical Sciences, Fasa, Iran. naz7899@yahoo.com.

Funding

Behbahan University of Medical Sciences 403007
6 · The paper itself

Abstract

The share of food waste in waste management costs is important because food waste constitutes a significant portion of municipal solid waste. Although the quantity of food waste depends on the food culture and behavior of citizens, but the impact of citizens' dietary behavior on solid waste management costs is a knowledge gap. In this study effect of improving self-efficacy in food management behavior at home on reducing municipal solid waste management costs in Iran was investigated. For this purpose, the proportion of food waste reduction and related financial implications in waste management costs due to change in five main effective factors was calculated based on a financial model and Monte Carlo simulation. Although the cost of food waste management was more than 127,000 USD/year, improving food management behavior due to women's self-efficacy in different scenarios will lead to a reduction in waste production by 45% and reduction in food waste management costs by 5.9-35.7%. Efforts to increase knowledge and modify citizens' attitudes, leading to improved household food management behavior, have an important impact on reducing municipal waste management costs. Therefore, educating citizens is essential, especially in developing regions that are facing increasing solid waste production rates.

Indexed as

FoodRefuse DisposalSelf EfficacySolid WasteWaste ManagementFemaleFood Loss and WasteHumansIranMonte Carlo MethodFood Loss and WasteSolid WasteMunicipal solid wasteSelf-EfficacyWaste management hierarchyWaste reduction

Identifiers

PMID41495160
PMCPMC12864750

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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.