Расстройства сексуального здоровья при воспалительных заболеваниях внутренних гениталий у женщин

При обследовании гинекологических больных выявлены развивающиеся у них разные варианты и формы сексуальной дезадаптации супружеской пары. Показаны их причины, механизмы формирования и клинические проявления.The investigation of gynecological patients revealed development of different variants and forms of sexual dysadaptation of the married couple. Their causes, formation mechanisms and clinical manifestations are shown

External validation of a prediction model and decision tree for sickness absence due to mental disorders

Purpose: A previously developed prediction model and decision tree were externally validated for their ability to identify occupational health survey participants at increased risk of long-term sickness absence (LTSA) due to mental disorders. Methods: The study population consisted of N = 3415 employees in mobility services who were invited in 2016 for an occupational health survey, consisting of an online questionnaire measuring the health status and working conditions, followed by a preventive consultation with an occupational health provider (OHP). The survey variables of the previously developed prediction model and decision tree were used for predicting mental LTSA (no = 0, yes = 1) at 1-year follow-up. Discrimination between survey participants with and without mental LTSA was investigated with the area under the receiver operating characteristic curve (AUC). Results: A total of n = 1736 (51%) non-sick-listed employees participated in the survey and 51 (3%) of them had mental LTSA during follow-up. The prediction model discriminated (AUC = 0.700; 95% CI 0.628–0.773) between participants with and without mental LTSA during follow-up. Discrimination by the decision tree (AUC = 0.671; 95% CI 0.589–0.753) did not differ significantly (p = 0.62) from discrimination by the prediction model. Conclusion: At external validation, the prediction model and the decision tree both poorly identified occupational health survey participants at increased risk of mental LTSA. OHPs could use the decision tree to determine if mental LTSA risk factors should be explored in the preventive consultation which follows after completing the survey questionnaire

Development of Prediction Models for Sickness Absence Due to Mental Disorders in the General Working Population

PurposeThis study investigated if and how occupational health survey variables can be used to identify workers at risk of long-term sickness absence (LTSA) due to mental disorders.MethodsCohort study including 53,833 non-sicklisted participants in occupational health surveys between 2010 and 2013. Twenty-seven survey variables were included in a backward stepwise logistic regression analysis with mental LTSA at 1-year follow-up as outcome variable. The same variables were also used for decision tree analysis. Discrimination between participants with and without mental LTSA during follow-up was investigated by using the area under the receiver operating characteristic curve (AUC); the AUC was internally validated in 100 bootstrap samples.Results30,857 (57%) participants had complete data for analysis; 450 (1.5%) participants had mental LTSA during follow-up. Discrimination by an 11-predictor logistic regression model (gender, marital status, economic sector, years employed at the company, role clarity, cognitive demands, learning opportunities, co-worker support, social support from family/friends, work satisfaction, and distress) was AUC = 0.713 (95% CI 0.692-0.732). A 3-node decision tree (distress, gender, work satisfaction, and work pace) also discriminated between participants with and without mental LTSA at follow-up (AUC = 0.709; 95% CI 0.615-0.804).ConclusionsAn 11-predictor regression model and a 3-node decision tree equally well identified workers at risk of mental LTSA. The decision tree provides better insight into the mental LTSA risk groups and is easier to use in occupational health care practice

Inter-physician agreement on the readiness of sick-listed employees to return to work

Purpose: To determine the agreement between occupational physician (OP) ratings of an employee's readiness to return to work (RRTW). Method: Anonymized written vignettes of 132 employees, sick-listed for at least 3 weeks, were reviewed by 5 OPs. The OPs intuitively rated RRTW as the ability (knowledge and skills) and willingness (motivation and confidence) of sick-listed employees to resume work. Inter-OP percentages of agreement were calculated and Cohen's kappas (kappa) were determined to correct for agreement by chance. Results: The percentage of agreement between OPs was 57% (range 39-89%) on the ability and 63% (range 48-87%) on the willingness of sick-listed employees to resume work. The mean. was 0.14 (range from -0.21 to 0.79) for ability and 0.25 (range from -0.11 to 0.74) for willingness. The OP-rating of RRTW of employees sick-listed with mental disorders did not differ from the OP-rating of RRTW of employees with musculoskeletal disorders. Conclusion: The inter-OP agreement on intuitively rated RRTW showed a wide variability, which accentuates the need for instruments to establish an employee's RRTW and for training in giving well founded return to work recommendations

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

Sickness absence frequency among women working in hospital care

Background Frequent short sickness absences result in understaffing and interfere with work processes. We need more knowledge about factors associated with this type of absence. Aims To investigate associations between the frequency of previous sickness absence and self-reported perceptions of health and work. Methods Cross-sectional study of female hospital care workers in which health, work characteristics and coping styles were assessed by questionnaire and linked to the number of sickness absence episodes recorded in the preceding 5 years using negative binomial regression analysis for counts distinguishing between short (1-7 days) and long (>7 days) episodes of absence after adjusting for age and duration of employment in December 2007 and hours worked between 2003 and 2007. Results Of 350 women employed for at least 5 years, 237 (68%) answered the questionnaire. The hours worked over the 5 year period [rate ratio (RR) = 1.2] and problem solving coping style score (RR = 1.1) were positively associated with the number of short sickness absence episodes. Age (RR = 0.8) and good general health (RR = 0.7) were inversely related to the number of both short and long episodes. Self-reported mental health and work characteristics were not shown to be related to the frequency of sickness absence. Conclusions Hours worked, problem-solving coping style, age and general health showed associations with the frequency of previous sickness absence among women who had worked at least 5 years in health care. Future prospective studies on the frequency of sickness absence should consider the impact of these factors further

Beauvericin alters the expression of genes coding for key proteins of the mitochondrial chain in ovine cumulus-oocyte complexes

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Validation of the Work Role Functioning Questionnaire 2.0 in cancer patients

Objective The Work Role Functioning Questionnaire 2.0 (WRFQ), measuring the percentage of time a worker has difficulties in meeting the work demands for a given health state, has shown strong reliability and validity in various populations with different chronic conditions. The present study aims to validate the WRFQ in working cancer patients. Methods A validation study of the WRFQ 2.0 was conducted, using baseline data from the longitudinal Work Life after Cancer study. Structural validity (Confirmatory Factor Analysis, CFA), internal consistency (Cronbach's alpha) and discriminant validity (hypothesis testing) were evaluated. Results 352 working cancer patients, most of them diagnosed with breast cancer (48%) and 58% in a job with mainly non-manual tasks, showed a mean WRFQ score of 78.6 (SD = 17.1), which means that they had on average difficulties for 78.6% of the time they spent working. Good internal consistency (alpha = 0.96) and acceptable to good fit for both the four and five-factor model (CFA) was found. The WRFQ distinguished between cancer patients reporting good vs. poor health (80.3 vs. 73.0, p = 0.001), low vs. high fatigue (82.0 vs. 72.2, p <0.001), no vs. clinical depression (80.4 vs. 58.8, p <0.001) and low vs. high cognitive symptoms (86.1 vs. 64.7, p <0.001). Conclusions The WRFQ 2.0 is a reliable and valid instrument to measure work functioning in working cancer patients. Further psychometric research on responsiveness is needed to support its use in health practice

Framingham score and work-related variables for predicting cardiovascular disease in the working population

Background: The Framingham score is commonly used to estimate the risk of cardiovascular disease (CVD). This study investigated whether work-related variables improve Framingham score predictions of sickness absence due to CVD. Methods: Eleven occupational health survey variables (descent, marital status, education, work type, work pace, cognitive demands, supervisor support, co-worker support, commitment to work, intrinsic work motivation and distress) and the Framingham Point Score (FPS) were combined into a multi-variable logistic regression model for CVD sickness absence during 1-year follow-up of 19 707 survey participants. The Net Reclassification Index (NRI) was used to investigate the added value of work-related variables to the FPS risk classification. Discrimination between participants with and without CVD sickness absence during follow-up was investigated by the area under the receiver operating characteristic curve (AUC). Results: A total of 129 (0.7%) occupational health survey participants had CVD sickness absence during 1-year follow-up. Manual work and high cognitive demands, but not the other work-related variables contributed to the FPS predictions of CVD sickness absence. However, work type and cognitive demands did not improve the FPS classification for risk of CVD sickness absence [NRI = 2.3%; 95% confidence interval (CI) -2.7 to 9.5%; P = 0.629]. The FPS discriminated well between participants with and without CVD sickness absence (AUC = 0.759; 95% CI 0.724-0.794). Conclusion: Work-related variables did not improve predictions of CVD sickness absence by the FPS. The non-laboratory Framingham score can be used to identify health survey participants at risk of CVD sickness absence

Risk reclassification analysis investigating the added value of fatigue to sickness absence predictions

Prognostic models including age, self-rated health and prior sickness absence (SA) have been found to predict high (a parts per thousand yen30) SA days and high (a parts per thousand yen3) SA episodes during 1-year follow-up. More predictors of high SA are needed to improve these SA prognostic models. The purpose of this study was to investigate fatigue as new predictor in SA prognostic models by using risk reclassification methods and measures. This was a prospective cohort study with 1-year follow-up of 1,137 office workers. Fatigue was measured at baseline with the 20-item checklist individual strength and added to the existing SA prognostic models. SA days and episodes during 1-year follow-up were retrieved from an occupational health service register. The added value of fatigue was investigated with Net Reclassification Index (NRI) and integrated discrimination improvement (IDI) measures. In total, 579 (51 %) office workers had complete data for analysis. Fatigue was prospectively associated with both high SA days and episodes. The NRI revealed that adding fatigue to the SA days model correctly reclassified workers with high SA days, but incorrectly reclassified workers without high SA days. The IDI indicated no improvement in risk discrimination by the SA days model. Both NRI and IDI showed that the prognostic model predicting high SA episodes did not improve when fatigue was added as predictor variable. In the present study, fatigue increased false-positive rates which may reduce the cost-effectiveness of interventions for preventing SA