Evidence map›Paper›PMID 39885416›Full record

ArticleBMC public health2025

Experiences of adults with type 2 diabetes mellitus with low socioeconomic status: a qualitative study.

Vahide Semerci Çakmak, Ebru Sönmez Sari, Serap Çetinkaya Özdemir

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Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Vahide Semerci ÇakmakFaculty of Health Sciences, Department of Internal Medicine Nursing, Tokat Gaziosmanpasa University, Tokat, 60100, Turkey. vahide1818@gmail.com.ORCID 0000-0003-3481-9500
Ebru Sönmez SariFaculty of Health Sciences, Department of Nursing, Bayburt University, Bayburt, 69000, Turkey.ORCID 0000-0001-7337-4853
Serap Çetinkaya ÖzdemirFaculty of Health Sciences, Department of Internal Medicine Nursing, Sakarya University, Sakarya, 54050, Turkey.ORCID 0000-0001-7706-4748

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdults with diabetes encounter various challenges related to managing their condition. In this study, we explored the experiences of adults with type 2 diabetes mellitus with low socioeconomic status in Türkiye.

methodsThis study was conducted as a phenomenological qualitative research. The purposive sampling method was used to select adults with type 2 diabetes. Data saturation was achieved with 20 patients. The data were collected through a demographic information form and a semi-structured questionnaire. The participants were interviewed by phone. The interviews were conducted in a quiet environment where the participants could respond comfortably. During the data analysis process, the content analysis approach suggested by Graneheim and Lundman (2004) was used. This method involves identifying meaningful units within the text, coding these units, and developing sub-themes and main themes. The MAXQDA 20 software was used for data management.

resultsThe participants were between 41 and 71 years old. Four main themes and ten subthemes were identified in the analysis. Themes: The identified themes included difficulties with dietary management of diabetes, individual difficulties, difficulties with self-management in diabetes, and coping strategies. According to Theme 1, it was observed that the participants experienced difficulties in managing nutrition in diabetes due to the economic aspect of diet and the inability to adapt to the diet. According to Theme 2, it was observed that the participants faced physical, psychological, and social difficulties. According to Theme 3, it was observed that the participants faced difficulties related to diabetes self-management, including blood glucose monitoring, insulin injection administration, and maintaining glycemic control." According to Theme 4, it was observed that the participants attempted to cope with diabetes-related difficulties through healthy lifestyle habits and family support.

conclusionOur findings indicate that adults with type 2 diabetes in low socioeconomic status face challenges related to biopsychosocial factors, nutrition, and diabetes self-management. However, these individuals managed their difficulties by adopting healthy lifestyle behaviors and relying on family support. The challenges faced by adults with diabetes may be alleviated through awareness training on dietary management and glycemic control.

Indexed as

Diabetes Mellitus, Type 2Social ClassAdaptation, PsychologicalAdultAgedFemaleHumansInterviews as TopicLow Socioeconomic StatusMaleMiddle AgedQualitative ResearchSelf CareSurveys and QuestionnairesAdults with diabetesDiabetesDifficultyQualitative studySocioeconomic status

Identifiers

PMID39885416
PMCPMC11780756

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LicenceCC BY-NC-ND
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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.