Interventions to facilitate return to work in adults with adjustment disorders

BACKGROUND: Adjustment disorders are a frequent cause of sick leave and various interventions have been developed to expedite the return to work (RTW) of individuals on sick leave due to adjustment disorders. OBJECTIVES: To assess the effects of interventions facilitating RTW for workers with acute or chronic adjustment disorders. SEARCH METHODS: We searched the Cochrane Depression, Anxiety and Neurosis Review Group's Specialised Register (CCDANCTR) to October 2011; the Cochrane Central Register of Controlled Trials (CENTRAL) to Issue 4, 2011; MEDLINE, EMBASE, PsycINFO and ISI Web of Science, all years to February 2011; the WHO trials portal (ICTRP) and ClinicalTrials.gov in March 2011. We also screened reference lists of included studies and relevant reviews. SELECTION CRITERIA: We selected randomised controlled trials (RCTs) evaluating the effectiveness of interventions to facilitate RTW of workers with adjustment disorders compared to no or other treatment. Eligible interventions were pharmacological interventions, psychological interventions (such as cognitive behavioural therapy (CBT) and problem solving therapy), relaxation techniques, exercise programmes, employee assistance programmes or combinations of these interventions. The primary outcomes were time to partial and time to full RTW, and secondary outcomes were severity of symptoms of adjustment disorder, work functioning, generic functional status (i.e. the overall functional capabilities of an individual, such as physical functioning, social function, general mental health) and quality of life. DATA COLLECTION AND ANALYSIS: Two authors independently selected studies, assessed risk of bias and extracted data. We pooled studies that we deemed sufficiently clinically homogeneous in different comparison groups, and assessed the overall quality of the evidence using the GRADE approach. MAIN RESULTS: We included nine studies reporting on 10 psychological interventions and one combined intervention. The studies included 1546 participants. No RCTs were found of pharmacological interventions, exercise programmes or employee assistance programmes. We assessed seven studies as having low risk of bias and the studies that were pooled together were comparable. For those who received no treatment, compared with CBT, the assumed time to partial and full RTW was 88 and 252 days respectively. Based on two studies with a total of 159 participants, moderate-quality evidence showed that CBT had similar results for time (measured in days) until partial RTW compared to no treatment at one-year follow-up (mean difference (MD) -8.78, 95% confidence interval (CI) -23.26 to 5.71). We found low-quality evidence of similar results for CBT and no treatment on the reduction of days until full RTW at one-year follow-up (MD -35.73, 95% CI -113.15 to 41.69) (one study with 105 participants included in the analysis). Based on moderate-quality evidence, problem solving therapy (PST) significantly reduced time until partial RTW at one-year follow-up compared to non-guideline based care (MD -17.00, 95% CI -26.48 to -7.52) (one study with 192 participants clustered among 33 treatment providers included in the analysis), but we found moderate-quality evidence of no significant effect on reducing days until full RTW at one-year follow-up (MD -17.73, 95% CI -37.35 to 1.90) (two studies with 342 participants included in the analysis). AUTHORS' CONCLUSIONS: We found moderate-quality evidence that CBT did not significantly reduce time until partial RTW and low-quality evidence that it did not significantly reduce time to full RTW compared with no treatment. Moderate-quality evidence showed that PST significantly enhanced partial RTW at one-year follow-up compared to non-guideline based care but did not significantly enhance time to full RTW at one-year follow-up. An important limitation was the small number of studies included in the meta-analyses and the small number of participants, which lowered the power of the analyses

The prospective association between obesity and major depression in the general population:does single or recurrent episode matter?

Background: Obesity and major depressive disorder (MDD) are important public health problems. MDD is a heterogeneous disorder and the direction of its association with obesity remains unclear. Evidence grows that recurrent MDD (MDD-R) differs in etiology and prognosis from single episode MDD (MDD-S), which could affect associations with obesity. However, evidence on this differential effect is lacking. The aim of this study was to examine the direction of the association between obesity and MDD, single or recurrent episode. Methods: A longitudinal study was performed in a cohort of 1094 participants of the PREVEND study, on whom data were collected at baseline and at an average 2-year follow-up. MDD-S and MDD-R were assessed by the Composite International Diagnostic Interview (CIDI 2.1). Obesity was defined as Body Mass Index >= 30 kg/m(2). Binary logistic regression analyses were conducted to examine whether obesity predicts MDD-S/MDD-R or vice versa, adjusted for potential confounders. Results: Prospective analyses showed that BMI at baseline was associated with the onset of MDD-R (Odds ratio, OR = 1.32; 95% confidence interval, 95% CI: 1.11; 1.57) during 2-year follow-up, but not with the onset of MDD-S (OR = 0.98; 95% CI: 0.89; 1.07). Obesity at baseline was not associated with the onset of MDD-S during follow-up (OR = 0.75; 95% CI: 0.25; 2.30), but associated with the onset of MDD-R during follow-up (OR = 11.63; 95% CI: 1.05; 128.60). Neither MDD-S nor MDD-R were associated with the development of obesity during 2-year follow-up (OR = 1.67, 95% CI: 0.64; 4.29 and OR = 2.32, 95% CI: 0.82; 6.58, respectively). Conclusions: Our findings add to the available evidence that obesity might specifically be associated with the onset of multiple episodes of major depression (MDD-R). Although the reverse association was not found, MDD-R tends to be also associated with subsequent development of obesity, but larger studies are needed to fully assess this issue. The heterogeneity of MDD should be considered when examining the effect of obesity on MDD

The interaction of socioeconomic position and type 2 diabetes mellitus family history:A cross-sectional analysis of the Lifelines Cohort and Biobank Study

Background Low socioeconomic position (SEP) and family history of type 2 diabetes mellitus (T2DM) contribute to increased T2DM risk, but it is unclear whether they exacerbate each other's effect. This study examined whether SEP reinforces the association of T2DM family history with T2DM, and whether behavioural and clinical risk factors can explain this reinforcement. Methods We used cross-sectional data on 51 725 participants from Lifelines. SEP was measured as educational level and was self-reported, just as family history of T2DM. T2DM was diagnosed based on measured fasting plasma glucose and glycated haemoglobin, combined with self-reported disease and recorded medication use. We assessed interaction on the additive scale by calculating the relative excess risk due to interaction (RERI). Results ORs of T2DM were highest for males (4.37; 95% CI 3.47 to 5.51) and females (7.77; 5.71 to 10.56) with the combination of low SEP and a family history of T2DM. The RERIs of low SEP and a family history of T2DM were 0.64 (-0.33 to 1.62) for males and 3.07 (1.53 to 4.60) for females. Adjustment for behavioural and clinical risk factors attenuated associations and interactions, but risks remained increased. Conclusion Low SEP and family history of T2DM are associated with T2DM, but they also exacerbate each other's impact in females but not in males. Behavioural and clinical risk factors partly explain these gender differences, as well as the associations underlying the interaction in females. The exacerbation by low SEP of T2DM risks in T2DM families deserves attention in prevention and community care

Factors associated with first return to work and sick leave durations in workers with common mental disorders

Background: Associations are examined between socio-demographic, medical, work-related and organizational factors and the moment of first return to work (RTW) (within or after 6 weeks of sick leave) and total sick leave duration in sick leave spells due to common mental disorders. Methods: Data are derived from a Dutch database, build to provide reference data for sick leave duration for various medical conditions. The cases in this study were entered in 2004 and 2005 by specially trained occupational health physicians, based on the physician's assessment of medical and other factors. Odds ratios for first RTW and sick leave durations are calculated in logistic regression models. Results: Burnout, depression and anxiety disorder are associated with longer sick leave duration. Similar, but weaker associations were found for female sex, being a teacher, small company size and moderate or high psychosocial hazard. Distress is associated with shorter sick leave duration. Medical factors, psychosocial hazard and company size are also and analogously associated with first RTW. Part-time work is associated with delayed first RTW. The strength of the associations varies for various factors and for different sick leave durations. Conclusion: The medical diagnosis has a strong relation with the moment of first RTW and the duration of sick leave spells in mental disorders, but the influence of demographic and work-related factors should not be neglected

Mental health among university students: The associations of effort-reward imbalance and overcommitment with psychological distress

Background: Mental health problems are highly prevalent among university students, but little is known about their underlying determinants. This study explores mental health among university students, the association between “effort-reward imbalance” (ERI), overcommitment and mental health, and to what extent ERI and overcommitment explain gender differences in mental health. Methods: Cross-sectional data were analyzed from 4760 Italian university students. The Kessler Psychological Distress Scale-10 was used to measure self-reported psychological distress, as an indicator of mental health, and the ERI – Student Questionnaire to measure effort, reward and overcommitment. The associations between ERI and overcommitment with psychological distress were estimated with multinomial logistic regression analyses. Results: 78.5% of the respondents experienced psychological distress, with 21.3%, 21.1%, and 36.1% reporting respectively mild, moderate and severe psychological distress. Female students were more likely to report moderate and severe psychological distress. ERI and overcommitment were strongly associated with severe psychological distress with ORs respectively up to 19.9 (95% CI: 12.2–32.5) and 22.2 (95% CI: 16.1–30.7). ERI and overcommitment explained part of the higher odds of severe psychological distress among female students comparing to males, attenuating the ORs from 2.3 (95% CI: 1.9–2.7) to 1.4 (95% CI: 1.2–1.7). Limitations: This cross-sectional study was performed on a large, but convenient sample. Discussion: More than one out of three students reported severe psychological distress. Decreasing ERI and overcommitment may be beneficial in the prevention of psychological distress among university students and may reduce gender differences in psychological distress. Longitudinal studies are needed to further investigate these associations

Associations of university student life challenges with mental health and self-rated health: A longitudinal study with 6 months follow-up

Background: Mental health problems are highly prevalent among university students. Stress due to student life challenges may be a risk factor for poorer health. This study investigates to what extent student life challenges and changes therein are associated with mental health and self-rated health. Methods: In a longitudinal study with 568 Italian university students mental health was assessed using the Mental Health Inventory-5 (MHI-5) and self-rated health with a single item from the Short Form 36 Health Survey (SF36) (score ranges: 0-100) at baseline and at six months follow-up. Student life challenges were investigated using six subscales (score ranges: 1-4) of the Higher Education Stress Inventory (HESI). A between-within linear regression model was used to investigate whether a higher exposure to life challenges was associated with poorer health (between individuals) and whether changes in student life challenges were associated with changes in health (within individuals). Results: Higher exposure to student life challenges was associated with poorer mental health (b ranging from -5.3 to -10.3) and self-rated health (b ranging from -3.1 to -9.6). An increase in student life challenges within individuals was associated with poorer mental health and self-rated health, in particular for high workload (b up to -5.9), faculty shortcomings (b up to -5.7), and unsupportive climate (b up to -5.6). Discussion: Exposure to student life challenges and changes therein are associated with university students’ health. Our findings suggest that student life challenges may be a target for interventions to improve mental health and self-rated health among university students

Multicentre validation of frequent sickness absence predictions

A prediction model including age, self-rated health (SRH) and prior sickness absence (SA) has previously been found to predict frequent SA.To further validate the model and develop it for clinical use.A multicentre study of care of the elderly workers employed at one of 14 centres in Aarhus (Denmark). SA episodes recorded in the year prior to baseline and both age and SRH at baseline were included in a prediction model for frequent (three or more) SA episodes during a 1-year follow-up period. The prediction model was developed in the largest centre. Risk predictions and discrimination between high- and low-risk workers were investigated in the other centres. The prediction rule 'SRH-prior SA' was derived from the prediction model and prognostic properties of the prediction rule were investigated for each centre, using score &lt;0 as cut-off.Of 2562 workers, 1930 had complete data for analysis. Predictions were accurate in 4 of 13 centres; discrimination was good in five and fair in another five centres. Prediction rule scores &lt;0 identified workers at risk of frequent SA with sensitivities of 0.17-0.54, specificities of 0.86-0.96 and positive predictive values of 0.54-0.87 across centres.The prediction model discriminated between workers at high and low risk of frequent SA in the majority of centres. The prediction rule 'SRH-prior SA' can be used in clinical practice specifically to identify workers at high risk of frequent SA.</p