scholarly journals Structured psychiatric diagnoses and self-rated symptoms in primary care patients on sick leave for common mental disorders: a clinical study

2019 ◽  
Author(s):  
Sandra Inger Christina af Winklerfelt Hammarberg ◽  
Jeanette Westman ◽  
Dominique Hange ◽  
Anna Finnes ◽  
Cecilia Björkelund ◽  
...  
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Sick Leave ◽  
Symptom Severity ◽  
Rating Scales ◽  
Common Mental Disorders ◽  
Adjustment Disorder ◽  
Psychiatric Interview ◽  
Significant Difference ◽  
Primary Care Patients

Abstract Background: To improve the quality of health care provided to primary care patients with mental disorders, it is crucial to understand more about the mental symptoms that underlie diagnoses on sick leave certificates. This study therefore aimed to: 1) investigate whether diagnoses on sick leave certificates corresponded to the results of a structured psychiatric interview and to self-rated symptom severity and 2) investigate the association between length of sick leave and the diagnoses on sick leave certificates, the diagnoses made in structured psychiatric interviews, and self-rated symptom severity. Methods: The study used data from 480 patients in SAFARI, a study on sick leave in patients with common mental disorders. At baseline, background variables were gathered and structured psychiatric interviews (M.I.N.I.) were performed. Severity of depression and adjustment disorder was assessed via self-rating scales. Data on sick leave were gathered at baseline and at 12 months from the Swedish Social Insurance Agency and patients’ medical records. Results: The diagnostic criteria for depression were fulfilled by a total of 76% of patients with a sick-leave diagnosis of adjustment disorder, 67% with a sick-leave diagnosis of anxiety, and 65% with a sick-leave diagnosis of depression (p=0.04). There was no significant difference in mean net sick leave days between those with a sick-leave certificate diagnosis of adjustment disorder (mean days 119.9), anxiety disorder (107.2), or depression (137.1). However, those with depression diagnosed via structured interview had a shorter mean net sick leave (112.3) than those who did not fulfil the depression criteria (155.9). Symptom severity was strongly associated with net sick leave days; those who rated their depression or adjustment disorder symptoms as more severe had longer net sick leave. Conclusions: Many patients with sick-leave certificate diagnoses of adjustment and anxiety disorders have ongoing depression. Longer sick leave duration was observed in those with adjustment disorder and more severe self-reported symptoms, both of which are appropriate according to Swedish guidelines.

Comorbidity between common mental disorders and chronic somatic diseases in primary care patients

2010 ◽  
Vol 32 (3) ◽  
pp. 240-245 ◽  
Author(s):  
Margalida Gili ◽  
Angels Comas ◽  
Margarita García-García ◽  
Saray Monzón ◽  
Serrano-Blanco Antoni ◽  
...  
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Common Mental Disorders ◽  
Primary Care Patients ◽  
Chronic Somatic Diseases ◽  
Somatic Diseases

Sickness absence: a systematic review and meta-analysis of psychological treatments for individuals on sick leave due to common mental disorders

2018 ◽  
Vol 48 (12) ◽  
pp. 1954-1965 ◽  
Author(s):  
Sigrid Salomonsson ◽  
Erik Hedman-Lagerlöf ◽  
Lars-Göran Öst
Keyword(s):  
Systematic Review ◽  
Mental Disorders ◽  
Sick Leave ◽  
Psychiatric Symptoms ◽  
Common Mental Disorders ◽  
Meta Analysis ◽  
Behavioural Therapy ◽  
Psychological Interventions ◽  
Problem Solving Therapy ◽  
Significant Difference

AbstractSick leave due to common mental disorders (CMDs) increase rapidly and present a major societal challenge. The overall effect of psychological interventions to reduce sick leave and symptoms has not been sufficiently investigated and there is a need for a systematic review and meta-analysis of the field. The aim of the present meta-analysis was to calculate the effect size of psychological interventions for CMDs on sick leave and psychiatric symptoms based on all published randomized controlled trials. Methodological quality, the risk of bias and publication bias were also assessed. The literature searches gave 2240 hits and 45 studies were included. The psychological interventions were more effective than care as usual on both reduced sick leave (g = 0.15) and symptoms (g = 0.21). There was no significant difference in effect between work focused interventions, problem-solving therapy, cognitive behavioural therapy or collaborative care. We conclude that psychological interventions are more effective than care as usual to reduce sick leave and symptoms but the effect sizes are small. More research is needed on psychological interventions that evaluate effects on sick leave. Consensual measures of sick leave should be established and quality of psychotherapy for patients on sick leave should be improved.

Quality of life among patients with common mental disorders attending monk healers and primary care clinics in Thailand

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Supa Pengpid ◽  
Karl Peltzer
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Mental Disorder ◽  
Common Mental Disorders ◽  
Common Mental Disorder ◽  
Health Centre ◽  
Somatization Disorder ◽  
Content Type ◽  
Primary Care Patients

Purpose Common mental disorders are not only highly prevalent in primary health-care settings but also negatively affect patients’ quality of life (QoL). This study aims to assess the levels of QoL among patients with common mental disorders seeking care from a monk healer or primary care setting and to determine the comparative QoL of users in two different types of care settings in Thailand. Design/methodology/approach Consecutively attending clients or patients (N = 1251) of three faith healing or three health centres were assessed with measures of depression, anxiety and somatization disorder and QoL. Findings The overall QoL was 67.8 and among the four QoL domains, social QoL was the highest (72.3), followed by physical QoL (69.4), environmental QoL (64.8) and psychological QoL (64.6). In adjusted linear regression analyses, sociodemographic factors, such as higher educational level, being employed, having high debt and consulting a health centre, were associated with higher overall QoL. Compared to being a client with a monk healer, patients at a health centre had a higher overall QoL, environmental and psychological QoL. Having a general anxiety or major depressive disorder was negatively associated with overall QoL and all four QoL sub-domains, whereas somatization disorder was not associated with any QoL sub-domains. Originality/value To the best of the authors’ knowledge, this is the first study to investigate QoL in common mental disorder attenders with a monk healer in comparison with primary care patients. Primary care patients with a common mental disorder had significantly higher overall QoL (p<0.01), higher psychological QoL (p<0.001) and higher environmental QoL (p<0.001) than clients with a common mental disorder attending monk healers. This study extends previous research showing a negative association between anxiety and depressive disorders and QoL calling for integration of QoL in the management of common mental disorders in both complementary and public primary care in Thailand.

A Provisional Screening Instrument for Four Common Mental Disorders in Adult Primary Care Patients

2011 ◽  
Vol 52 (1) ◽  
pp. 48-55 ◽  
Author(s):  
John P. Houston ◽  
Kurt Kroenke ◽  
Douglas E. Faries ◽  
Caroline Carney Doebbeling ◽  
Lenard A. Adler ◽  
...  
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Common Mental Disorders ◽  
Screening Instrument ◽  
Primary Care Patients

scholarly journals Detecting common mental disorders in primary care in India: a comparison of five screening questionnaires

2007 ◽  
Vol 38 (2) ◽  
pp. 221-228 ◽  
Author(s):  
V. Patel ◽  
R. Araya ◽  
N. Chowdhary ◽  
M. King ◽  
B. Kirkwood ◽  
...  
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Common Mental Disorders ◽  
General Health Questionnaire ◽  
Diagnostic Interview ◽  
Systematic Sampling ◽  
Health Questionnaire ◽  
Primary Care Settings ◽  
Self Reporting Questionnaire ◽  
Distress Scale

BackgroundScreening of patients for common mental disorders (CMDs) is needed in primary-care management programmes. This study aimed to compare the screening properties of five widely used questionnaires.MethodAdult attenders in five primary-care settings in India were recruited through systematic sampling. Four questionnaires were administered, in pairs, in random order to participants: the General Health Questionnaire (GHQ, 12 items); the Primary Health Questionnaire (PHQ, nine items); the Kessler Psychological Distress Scale (K10, 10 items), and from which we could extract the score of the shorter 6-item K6; and the Self-Reporting Questionnaire (SRQ, 20 items). All participants were interviewed with a structured lay diagnostic interview, the Revised Clinical Interview Schedule (CIS-R).ResultsComplete data were available for 598 participants (participation rate 99.3%). All five questionnaires showed moderate to high discriminating ability; the GHQ and SRQ showed the best results. All five showed moderate to high degrees of correlation with one another, the poorest being between the two shortest questionnaires, K6 and PHQ. All five had relatively good internal consistency. However, the positive predictive value (PPV) of the questionnaires compared with the diagnostic interview ranged from 51% to 77% at the optimal cut-off scores.ConclusionsThere is little difference in the ability of these questionnaires to identify cases accurately, but none showed high PPVs without a considerable compromise on sensitivity. Hence, the choice of an optimum cut-off score that yields the best balance between sensitivity and PPV may need to be tailored to individual settings, with a higher cut-off being recommended in resource-limited primary-care settings.

scholarly journals Assessing and predicting adolescent and early adulthood common mental disorders using electronic primary care data: analysis of a prospective cohort study (ALSPAC) in Southwest England

BMJ Open ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. e053624
Author(s):  
Daniel Smith ◽  
Kathryn Willan ◽  
Stephanie L Prady ◽  
Josie Dickerson ◽  
Gillian Santorelli ◽  
...  
Keyword(s):  
Primary Care ◽  
Cohort Study ◽  
Mental Disorders ◽  
Outcome Measures ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Common Mental Disorders ◽  
Free Text ◽  
Primary Care Data ◽  
Time Point

ObjectivesWe aimed to examine agreement between common mental disorders (CMDs) from primary care records and repeated CMD questionnaire data from ALSPAC (the Avon Longitudinal Study of Parents and Children) over adolescence and young adulthood, explore factors affecting CMD identification in primary care records, and construct models predicting ALSPAC-derived CMDs using only primary care data.Design and settingProspective cohort study (ALSPAC) in Southwest England with linkage to electronic primary care records.ParticipantsPrimary care records were extracted for 11 807 participants (80% of 14 731 eligible). Between 31% (3633; age 15/16) and 11% (1298; age 21/22) of participants had both primary care and ALSPAC CMD data.Outcome measuresALSPAC outcome measures were diagnoses of suspected depression and/or CMDs. Primary care outcome measure were Read codes for diagnosis, symptoms and treatment of depression/CMDs. For each time point, sensitivities and specificities for primary care CMD diagnoses were calculated for predicting ALSPAC-derived measures of CMDs, and the factors associated with identification of primary care-based CMDs in those with suspected ALSPAC-derived CMDs explored. Lasso (least absolute selection and shrinkage operator) models were used at each time point to predict ALSPAC-derived CMDs using only primary care data, with internal validation by randomly splitting data into 60% training and 40% validation samples.ResultsSensitivities for primary care diagnoses were low for CMDs (range: 3.5%–19.1%) and depression (range: 1.6%–34.0%), while specificities were high (nearly all >95%). The strongest predictors of identification in the primary care data for those with ALSPAC-derived CMDs were symptom severity indices. The lasso models had relatively low prediction rates, especially in the validation sample (deviance ratio range: −1.3 to 12.6%), but improved with age.ConclusionsPrimary care data underestimate CMDs compared to population-based studies. Improving general practitioner identification, and using free-text or secondary care data, is needed to improve the accuracy of models using clinical data.

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