Non-mental Conditions Research Articles

Workplace discrimination as risk factor for long-term sickness absence: Longitudinal analyses of onset and changes in workplace adversity.

Workplace discrimination may affect the health of the exposed employees, but it is not known whether workplace discrimination is also associated with an increased risk of long-term sickness absence. The aim of this study was to examine the longitudinal associations of changes in and onset of workplace discrimination with the risk of long-term sickness absence. Data on workplace discrimination were obtained from 29,597 employees participating in survey waves 2004, 2006, 2008 and/or 2010 of the Finnish Public Sector Study. Four-year changes in long-term sickness absence (≥10 days of medically certified absence with a mental or non-mental diagnosis) were assessed. This covered successive study waves in analyses of onset of workplace discrimination as well as fixed effect analyses of change in workplace discrimination (concurrent i.e. during the exposure year and 1-year lagged i.e. within one year following exposure), by using each employee as his/her own control. The risk of long-term sickness absence due to mental disorders was greater for employees with vs. without onset of workplace discrimination throughout the 4-year period, reaching a peak at the year when the onset of discrimination was reported (adjusted risk ratio 2.13; 95% confidence interval (CI) 1.80-2.52). The fixed effects analyses showed that workplace discrimination was associated with higher odds of concurrent, but not 1-year lagged, long-term sickness absence due to mental disorders (adjusted odds ratio 1.61; 95% CI 1.33-1.96 and adjusted odds ratio 1.02; 95% CI 0.83-1.25, respectively). Long-term sickness absence due to non-mental conditions was not associated with workplace discrimination. In conclusion, these findings suggest that workplace discrimination is associated with an elevated risk of long-term sickness absence due to mental disorders. Supporting an acute effect, the excess risk was confined to the year when workplace discrimination occurred.

Prediction of Autism Risk From Family Medical History Data Using Machine Learning: A National Cohort Study From Denmark

BackgroundA family history of specific disorders (e.g., autism, depression, epilepsy) has been linked to risk for autism spectrum disorder (ASD). This study examines whether family history data could be used for ASD risk prediction. MethodsWe followed all Danish live births, from 1980 to 2012, of Denmark-born parents for an ASD diagnosis through April 10, 2017 (N = 1,697,231 births; 26,840 ASD cases). Linking each birth to three-generation family members, we identified 438 morbidity indicators, comprising 73 disorders reported prospectively for each family member. We tested various models using a machine learning approach. From the best-performing model, we calculated a family history risk score and estimated odds ratios and 95% confidence intervals for the risk of ASD. ResultsThe best-performing model comprised 41 indicators: eight mental conditions (e.g., ASD, attention-deficit/hyperactivity disorder, neurotic/stress disorders) and nine nonmental conditions (e.g., obesity, hypertension, asthma) across six family member types; model performance was similar in training and test subsamples. The highest risk score group had 17.0% ASD prevalence and a 15.3-fold (95% confidence interval, 14.0–17.1) increased ASD risk compared with the lowest score group, which had 0.6% ASD prevalence. In contrast, individuals with a full sibling with ASD had 9.5% ASD prevalence and a 6.1-fold (95% confidence interval, 5.9–6.4) higher risk than individuals without an affected sibling. ConclusionsFamily history of multiple mental and nonmental conditions can identify more individuals at highest risk for ASD than only considering the immediate family history of ASD. A comprehensive family history may be critical for a clinically relevant ASD risk prediction framework in the future.

Clinical Test of Pyrroles: Usefulness and Association with Other Biochemical Markers

Background: Psychiatrists started using urine pyrroles (hydroxyhemopyrrolin-2-one, HPL) to diagnose mental disorders many years ago. The biological origins of HPL are not known, nor are the causes of elevated urinary pyrrole excretion well understood. Methods: In the present study we analyzed the level of pyrroles in 148 patients with schizophrenia, 135 patients with bipolar disorder, 97 patients with depression, and 119 patients with ADHD and compared these data with the results of pyrrole tests for patients with non-mental conditions and healthy volunteers. Results: According to our data, urinary pyrrole concentrations tended to be high in patients with mental illnesses, but elevated level of pyrroles was not specific for only these patients. We found evidence of an allergy related component in the fact that elevated pyrrole levels were significantly more prevalent in subjects with elevated histamine values. A role of intestinal bacteria, or imbalances in intestinal bacterial metabolism, was also suggested based on the found relationship between elevated pyrrole levels and elevations in indicans and urobilinogens. In addition, our data demonstrated that subjects with severely elevated pyrrole levels were deficient in nutrients such as zinc, vitamin B3, and vitamin C. Conclusion: Thus, pyrrole excretion seems to be a component of illness in general and not strictly mental illness.

Competence to know

I argue against traditional virtue epistemology on which knowledge is a success due to a competence to believe truly, by revealing an in-principle problem with the traditional virtue epistemologist’s explanation of Gettier cases. The argument eliminates one of the last plausible explanation of Gettier cases, and so of knowledge, in terms of non-factive mental states and non-mental conditions. I then I develop and defend a different kind of virtue epistemology, on which knowledge is an exercise of a competence to know. I show how the account, while circular, is not viciously so. It explains both how knowledge is a mental state, as well as the relationship between knowledge and justification, including justified false beliefs and Gettier cases. Moreover, although direct virtue epistemology is compatible with many views on the nature of belief, it can explain how knowledge might be metaphysically more fundamental than belief as well.