Determinants of Poverty Perceptions in Uzbekistan: A Mixed-Methods Approach

This study investigates perceptions of poverty and its underlying determinants among a purposively sampled population of social-benefit recipients in Uzbekistan. For this purpose, a survey was conducted with 1949 respondents who receive social benefits. The collected data were analyzed using an exploratory sequential mixed-methods approach. Initially, thematic analysis was conducted to identify perceptions of poverty. The output of the thematic analysis was the emergence of nine themes that illustrate the characteristics of individualistic, structural, fatalistic, and cultural attributions of poverty perceptions. Based on the output of the thematic analysis, multinomial logistic regression was conducted. The selection of the base category was based on both the theoretical framework and survey output. The regression results indicated that age, regional poverty cluster and place of residence were the most statistically significant demographic factors influencing perceptions of poverty. Among the monetary variables, personal income demonstrated the strongest explanatory power. Overall, the findings suggest that, within this sampled population, perceptions of poverty are predominantly shaped by individualistic attributions rather than structural, fatalistic or cultural ones. However, these results should be considered with caution as they may reflect internalized poverty stigma.

Authors

Institutions

Publication Details

Journal
Societies
Published
2026-10-09
DOI
https://doi.org/10.3390/soc16100336
Primary Topic
Income, Poverty, and Inequality
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Determinants of Poverty Perceptions in Uzbekistan: A Mixed-Methods Approach

Ulugbek Alisher ugli Vosikov, Nodir Hosiyatovich Jumaev, Dilshodjon Alidjonovich Rakhmonov, Aziza Usmanova et al.
Societies
Income, Poverty, and Inequality
article

Determinants of Poverty Perceptions in Uzbekistan: A Mixed-Methods Approach

Ulugbek Alisher ugli Vosikov, Nodir Hosiyatovich Jumaev, Dilshodjon Alidjonovich Rakhmonov, Aziza Usmanova, Ikhtiyor Ochilovich Sattorov
article en

Abstract

This study investigates perceptions of poverty and its underlying determinants among a purposively sampled population of social-benefit recipients in Uzbekistan. For this purpose, a survey was conducted with 1949 respondents who receive social benefits. The collected data were analyzed using an exploratory sequential mixed-methods approach. Initially, thematic analysis was conducted to identify perceptions of poverty. The output of the thematic analysis was the emergence of nine themes that illustrate the characteristics of individualistic, structural, fatalistic, and cultural attributions of poverty perceptions. Based on the output of the thematic analysis, multinomial logistic regression was conducted. The selection of the base category was based on both the theoretical framework and survey output. The regression results indicated that age, regional poverty cluster and place of residence were the most statistically significant demographic factors influencing perceptions of poverty. Among the monetary variables, personal income demonstrated the strongest explanatory power. Overall, the findings suggest that, within this sampled population, perceptions of poverty are predominantly shaped by individualistic attributions rather than structural, fatalistic or cultural ones. However, these results should be considered with caution as they may reflect internalized poverty stigma.

SocietiesVol. 16(10)
Academy of Sciences Republic of Uzbekistan (UZ), International Islamic Academy of Uzbekistan (UZ), Westminster International University in Tashkent (UZ), University of World Economy and Diplomacy (UZ)
Openalex Percentile: Top 5%
Income, Poverty, and Inequality
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.