Evidence map›Paper›PMID 33916851›Full record

ArticleInternational journal of environmental research and public health2021

An Empirical Study on Diabetes Depression over Distress Evaluation Using Diagnosis Statistical Manual and Chi-Square Method.

Sohail M Noman, Jehangir Arshad, Muhammad Zeeshan, Ateeq Ur Rehman, Amir Haider, Shahzada Khurram, Omar Cheikhrouhou, Habib Hamam, Muhammad Shafiq

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 29% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Machine Learning Techniques for Antimicrobial Resistance Prediction ofComputational intelligence and neuroscience · 2023
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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

9 authors at 9 institutions in 5 countries.

Sohail M NomanDepartment of Cell Biology and Genetics, Shantou University Medical College, Shantou 515041, China.ORCID 0000-0001-6914-5505
Jehangir ArshadDepartment of Electrical & Computer Engineering, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan.ORCID 0000-0002-9196-0458
Muhammad ZeeshanDepartment of Medicine and Surgery, Al-Nafees Medical College and Hospital, Isra University, Islamabad 44000, Pakistan.
Ateeq Ur RehmanDepartment of Electrical Engineering, Government College University, Lahore 54000, Pakistan.ORCID 0000-0001-5203-0621
Amir HaiderDepartment of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Korea.ORCID 0000-0002-1534-061X
Shahzada KhurramFaculty of Computing, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan.ORCID 0000-0001-6924-4220
Omar CheikhrouhouCollege of CIT, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.ORCID 0000-0002-9898-3898
Habib HamamFaculty of Engineering, Moncton University, Moncton, NB E1A3E9, Canada.ORCID 0000-0002-5320-1012
Muhammad ShafiqDepartment of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Korea.ORCID 0000-0001-7337-7608
COMSATS University Islamabad · PKGovernment College University, Lahore · PKIslamia University of Bahawalpur · PKIsra University · PKSejong University · KRShantou University · CNTaif University · SAUniversité de Moncton · CAYeungnam University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes distress is an alternative disorder that is often associated with depression syndromes. Psychosocial distress is an alternative disorder that acts as a resistance to diabetes self-care management and compromises diabetes control. Yet, in Nigeria, the focus of healthcare centers is largely inclined toward the medical aspect of diabetes that neglects psychosocial care. In this retrospective study, specific distress was measured by the Diabetes Distress Screening (DDS) scale, and depression was analyzed by the Beck Depression Inventory (BDI) and Diagnosis Statistics Manual (DSM) criteria in type 2 diabetes mellitus (T2DM) patients of Northwestern Nigeria. Additionally, we applied the Chi-square test and linear regression to measure the forecast prevalence ratio and evaluate the link between the respective factors that further determine the odd ratios and coefficient correlations in five nonintrusive variables, namely age, gender, physical exercise, diabetes history, and smoking. In total, 712 sample patients were taken, with 51.68% male and 47.31% female patients. The mean age and body mass index (BMI) was 48.6 years ± 12.8 and 45.6 years ± 8.3. Based on the BDI prediction, 90.15% of patients were found depressed according to the DSM parameters, and depression prevalence was recorded around 22.06%. Overall, 88.20% of patients had DDS-dependent diabetes-specific distress with a prevalence ratio of 24.08%, of whom 45.86% were moderate and 54.14% serious. In sharp contrast, emotion-related distress of 28.96% was found compared to interpersonal (23.61%), followed by physician (16.42%) and regimen (13.21%) distress. The BDI-based matching of depression signs was also statistically significant with

Indexed as

Diabetes Mellitus, Type 2DepressionEmotionsFemaleHumansMaleNigeriaRetrospective Studiesclinical implicationsdepressiondiabetes distressprevalenceregression correlation factorstype 2 diabetes mellitus forecasting

Identifiers

PMID33916851
PMCPMC8038424
OpenAlexW3142107962

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.