Psychosocial and sociodemographic predictors of attrition in a longitudinal study of major depression in primary care: the predictD-Spain study

2009 ◽  
Vol 64 (10) ◽  
pp. 874-884 ◽  
Author(s):  
J. A. Bellon ◽  
J. de Dios Luna ◽  
B. Moreno ◽  
C. Monton-Franco ◽  
M. J. GildeGomez-Barragan ◽  
...  
BMJ Open ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. e024980 ◽  
Author(s):  
Tiia T M Reho ◽  
Salla A Atkins ◽  
Nina Talola ◽  
Markku P T Sumanen ◽  
Mervi Viljamaa ◽  
...  

ObjectivesFrequent attenders (FAs) create a substantial portion of primary care workload but little is known about FAs’ sickness absences. The aim of the study is to investigate how occasional and persistent frequent attendance is associated with sickness absences among the working population in occupational health (OH) primary care.Setting and participantsThis is a longitudinal study using medical record data (2014–2016) from an OH care provider in Finland. In total, 59 676 patients were included and categorised into occasional and persistent FAs or non-FAs. Sick-leave episodes and their lengths were collected along with associated diagnostic codes. Logistic regression was used to analyse associations between FA status and sick leaves of different lengths (1–3, 4–14 and ≥15 days).ResultsBoth occasional and persistent FA had more and longer duration of sick leave than non-FA through the study years. Persistent FAs had consistently high absence rates. Occasional FAs had elevated absence rates even 2 years after their frequent attendance period. Persistent FAs (OR=11 95% CI 7.54 to 16.06 in 2016) and occasional FAs (OR=2.95 95% CI 2.50 to 3.49 in 2016) were associated with long (≥15 days) sickness absence when compared with non-FAs. Both groups of FAs had an increased risk of long-term sick leaves indicating a risk of disability pension.ConclusionBoth occasional and persistent FAs should be identified in primary care units caring for working-age patients. As frequent attendance is associated with long sickness absences and possibly disability pensions, rehabilitation should be directed at this group to prevent work disability.


2021 ◽  
Vol 26 (1) ◽  
pp. 1890901
Author(s):  
Corry McDonald ◽  
Austin Henderson ◽  
Patrick Barlow ◽  
Jerrod Keith

2021 ◽  
pp. 1-8
Author(s):  
Michael Wainberg ◽  
Peter Zhukovsky ◽  
Sean L. Hill ◽  
Daniel Felsky ◽  
Aristotle Voineskos ◽  
...  

Abstract Background Our understanding of major depression is complicated by substantial heterogeneity in disease presentation, which can be disentangled by data-driven analyses of depressive symptom dimensions. We aimed to determine the clinical portrait of such symptom dimensions among individuals in the community. Methods This cross-sectional study consisted of 25 261 self-reported White UK Biobank participants with major depression. Nine questions from the UK Biobank Mental Health Questionnaire encompassing depressive symptoms were decomposed into underlying factors or ‘symptom dimensions’ via factor analysis, which were then tested for association with psychiatric diagnoses and polygenic risk scores for major depressive disorder (MDD), bipolar disorder and schizophrenia. Replication was performed among 655 self-reported non-White participants, across sexes, and among 7190 individuals with an ICD-10 code for MDD from linked inpatient or primary care records. Results Four broad symptom dimensions were identified, encompassing negative cognition, functional impairment, insomnia and atypical symptoms. These dimensions replicated across ancestries, sexes and individuals with inpatient or primary care MDD diagnoses, and were also consistent among 43 090 self-reported White participants with undiagnosed self-reported depression. Every dimension was associated with increased risk of nearly every psychiatric diagnosis and polygenic risk score. However, while certain psychiatric diagnoses were disproportionately associated with specific symptom dimensions, the three polygenic risk scores did not show the same specificity of associations. Conclusions An analysis of questionnaire data from a large community-based cohort reveals four replicable symptom dimensions of depression with distinct clinical, but not genetic, correlates.


1998 ◽  
Vol 55 (7) ◽  
pp. 645 ◽  
Author(s):  
Judith R. Lave ◽  
Richard G. Frank ◽  
Herbert C. Schulberg ◽  
Mark S. Kamlet

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