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Record W3026271884 · doi:10.1186/s12888-020-02615-y

Depression, anxiety, and associated factors in patients with diabetes: evidence from the anxiety, depression, and personality traits in diabetes mellitus (ADAPT-DM) study

2020· article· en· W3026271884 on OpenAlexaff
Luke Sy‐Cherng Woon, Hatta Sidi, Arun Ravindran, Paula Junggar Gosse, Roslyn Laurie Mainland, Emily Samantha Kaunismaa, Nurul Hazwani Hatta, Puteri Arnawati, Amelia Yasmin Zulkifli, Norlaila Mustafa, Mohammad Farris Iman Leong Bin Abdullah

Bibliographic record

VenueBMC Psychiatry · 2020
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsCanada Research ChairsUniversity of Toronto
FundersUniversiti Kebangsaan Malaysia
KeywordsAnxietyDepression (economics)Beck Anxiety InventoryMedicineOdds ratioNeuroticismPsychiatryBeck Depression InventoryDiabetes mellitusPopulationOutpatient clinicClinical psychologyInternal medicinePsychologyPersonalityEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: Depression and anxiety are common psychiatric complications affecting patients with diabetes mellitus. However, data on the prevalence of depression, anxiety, and associated factors among Malaysian diabetic patients is scarce. The Anxiety, Depression, and Personality Traits in Diabetes Mellitus (ADAPT-DM) study aimed to determine the prevalence of depression and anxiety, and their associated factors in the Malaysian diabetic population. METHODS: This cross-sectional study recruited 300 diabetic patients via convenience sampling from the Endocrine outpatient clinic of Universiti Kebangsaan Malaysia Medical Centre, a tertiary referral healthcare facility in Kuala Lumpur. Socio-demographic characteristics and clinical history were obtained from each participant. The Generalised Anxiety Disorder-7 (GAD-7) was administered to assess anxiety symptoms, the Beck Depression Inventory (BDI) to assess depressive symptoms, the Big Five Inventory (BFI) to evaluate personality traits, and the World Health Organization Quality of Life-BREF (WHOQOL-BREF) to measure quality of life (QOL). Stepwise multiple logistic regression analyses were performed to determine the association between various factors, and depression and anxiety. RESULTS: The prevalence of depression was 20% (n = 60) while anxiety was 9% (n = 27). Co-morbid depression (adjusted odds ratio [OR] = 9.89, 95% confidence interval [CI] = 2.63-37.14, p = 0.001) and neuroticism (adjusted OR = 11.66, 95% CI = 2.69-50.47, p = 0.001) increased the odds of developing anxiety, while conscientiousness (adjusted OR = 0.45, 95% CI = 0.23-0.80, p = 0.004) and greater psychological-related QOL (adjusted OR = 0.47, 95% CI = 0.29-0.75, p = 0.002) were protective. Co-morbid anxiety (adjusted OR = 19.83, 95% CI = 5.63-69.92, p < 0.001) increased the odds of depression, while older age (adjusted OR = 0.96, 95% CI = 0.93-0.98, p = 0.002), social relationship-related QOL (adjusted OR = 0.84, 95% CI = 0.71-.0.99, p = 0.047), and physical health-related QOL (adjusted OR = 0.69, 95% CI = 0.58-0.83, p < 0.001) were protective. CONCLUSIONS: The study findings signify the need to screen for co-morbid depression and anxiety, as well as personality traits and QOL, and to include psychosocial interventions when planning a multidisciplinary approach to managing diabetes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.253
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations60
Published2020
Admission routes1
Has abstractyes

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