Evidence map›Paper›PMID 36994032›Full record

ArticleJournal of family medicine and primary care2022

Depressive symptoms in diabetic patients; prevalence, correlates, and moderating effect in Taif, Saudi Arabia.

Ameera Mishal Alosaimi, Nada Hamed Alsulaimani, Wejdan Alotaibi

Open access · goldAbstract read
In one paragraph

Article in Journal of family medicine and primary care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Ameera Mishal AlosaimiDepartment of Family Medicine, Prince Mansour Military Hospital, Taif, Saudi Arabia.
Nada Hamed AlsulaimaniDepartment of Family Medicine, Prince Mansour Military Hospital, Taif, Saudi Arabia.
Wejdan AlotaibiDepartment of Family Medicine, Taif University School of Medicine, Taif, Saudi Arabia.
Taif University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diabetes is associated with a range of psychosocial stressors that could lead to considerable distress and increased risk of depressive symptoms. There is a pressing need to understand the underpinnings of diabetes-related distress and how it evolves in connection with depressive moods, and fears related to hypoglycaemia. Our current study attempts to fill this knowledge gap and further explore the interconnections between distress, fear, and depression among Saudi diabetic patients. Methods: Descriptive questionnaire-based cross-sectional study of type II diabetes patients in a specialist diabetes clinic in Taif, Saudi Arabia. We carried out Poisson regression modelling to evaluate the correlates of depressive and distress symptoms. Results: The study included ( Conclusions: Distress and depression levels are worryingly higher than previous estimates from Saudi Arabia among patients with type II diabetes, indicative of an upward trend and/or a pandemic-related jump. One significant finding from our results is the substantial effect of glycaemic control on increased distress, and depression among our type II diabetes patients. This interaction is likely due to effects on self-care and medication adherence. We also confirmed the association between depressive symptoms and the duration of diabetes. Our results indicated a connection between comorbid medical illness with depressive and distress symptoms.

Indexed as

Depressiondiabetes distress-17 scalediabetes type twoSaudi ArabiaTaif

Identifiers

PMID36994032
PMCPMC10041008
OpenAlexW4318472568

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

None linked

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.