Effect of Career Guidance on Employee Performance in Kenyan Private Universities: A Case of Religious Based Private Universities

From the employees’ perspective, the lack of career guiding can lead to frustration, feelings of not being appreciated by the company and not identifying the right position leads to the need of a job change and / or the company. This is particularly more pronounced in such settings as universities, where employee performance determines the quality of graduates who are likely to be placed in positions of important decision making in their professional endeavors. It is more so more important in private universities where employees do not have the kind of job security as is the case in public universities. It is under this background that the study set out to investigate the effects of career guidance on employee performance in Kenyan private universities, with a particular interest in the religious based Private Universities in Kenya. This was a descriptive study design targeting all the employees of religious based private universities in Kenya which included Daystar, CUEA, St. Pauls and KeMU and totaled 2336. The established sample size was 341. The main data collection tool was questionnaires, from which the obtained quantitative data was analyzed by both descriptive and inferential analyses. Results indicate that career guidance is a significant predictor of employee performance) (β =.204, p<0.05). It is concluded that that career guidance as regards counseling and mentorship is inadequately practiced across a majority of the institutions surveyed. There is need for the study area and similar institutions to institute policies that will enhance career growth opportunities especially for employees

Ecuadorian Journalists Mental Health Influence on Changing Job Desire: A Cross Sectional Study

Journalist’s mental health could predict their job change. This study aims at determining the prevalence of mental health issues and their association with perception of aptitude for covering emergencies and difficulty in seeing a corpse, and also to determine the mental health factors associated with job change. An ad hoc survey, GHQ-28 (Somatization, Anxiety-Insomnia, Social Dysfunction, Depression), MBI-P (Burnout, Emotional Exhaustion, Depersonalization, personal accomplishment) and Brief scale to diagnose Post-Traumatic Stress Disorder and Suicide Risk were applied to 196 journalists (female = 51.6%). Descriptive analysis, correlations (Pearson and Spearman), T-test and binary logistic regression were performed. It was found that one third part of journalists perceive themselves as having low aptitude to cover emergencies and difficulty in seeing a corpse, 17.3% would consider changing jobs and 42.1% could only access free mental health services. The most frequent mental health problems are: low personal accomplishment, emotional exhaustion and post-traumatic stress disorder (11.2 to 17.3%). People who want to change jobs present more: social dysfunction, depression, emotional exhaustion, depersonalization, low personal accomplishment, post-traumatic stress disorder and suicide risk. The two mental health factors associated with desire of changing jobs are high emotional exhaustion, and low personal accomplishment. These results guide the psychosocial risk prevention processes for journalists, as well as the training needs that universities could consider to protect the mental health of this vulnerable group.

Workforce Analytics: A Data-Driven Machine Learning Approach to Predict Job Change of Data Scientists

Today the total amount of data created, captured, and consumed in the world is increasing at a rapid rate, as digitally driven organizations continue to contribute to the ever- growing global data sphere. (Holst, Statista Report 2020). This data brings with it a plethora of opportunities for organizations across different sectors. Hence, their hiring outlook is shifting towards candidates who possess the abilities to decode data and generate actionable insights to gain a competitive advantage. A career in data science offers great scope and the demand for such candidates is expected to rise steeply. When companies hire for big data and data science roles, they often provide training. From an HR perspective, it is important to understand how many of them would work for the company in the future or how many look at the training with an upskilling perspective for new jobs. HR has the aim of reducing costs and time required to conduct trainings by designing courses aligning to the candidate’s interest and needs. In this paper, we explored the data based on features including demographics, education and prior experience of the candidates. We made use of machine learning algorithms, viz. Logistic Regression, Naive Bayes, K Nearest-Neighbours Classifier, Decision Trees, Random Forest, Support Vector Machine, Gradient Descent Boosting, and XGBoost to predict whether a candidate will look for a new job or will stay and work for the company.

Risk of pain in the neck and shoulders and job change among hairdressers: a combined questionnaire and register-based Danish prospective cohort study

Objective To investigate whether intensity of work as a hairdresser was associated with treatments for pain, and if musculoskeletal pain was associated with leaving the hairdressing trade. Methods We formed two cohorts of hairdressers covered in the PensionDanmark Health Scheme (PDHS). Cohort 1 consisted of 1304 active hairdressers in 2009. Self-reported weekly haircuts were used as work intensity measure and treatments for pain in the neck and shoulders in PDHS were used as outcome. We used a Cox regression model with robust sandwich estimates adjusted for age, sex, employment status and prior treatment < 1 year before July 2009. Cohort 2 consisted of all hairdressers ever covered in the PDHS from 2006 to 2016 (n = 11,162). Exposure were treatments in PDHS within the last year. Outcome was leaving the trade within the following year. Adjustments were made for sex, calendar-year and age in Cox regression models. Results The adjusted hazard ratio of treatments in PDHS compared to the lowest work intensity was 0.95 (95% CI 0.58–1.55) and 0.74 (0.43–1.29) for medium and highest intensity, respectively. The risk of leaving the trade was lower, HR 0.80 (0.72–0.90) among hairdressers with treatments in PDHS within the last year, mainly driven by hairdressers aged < 56 years. Conclusion We found no association between intensity of work as a hairdresser, measured as self-reported weekly haircuts, and treatments for pain in PDHS. Furthermore, we found a protective effect of treatments in the PDHS within the last year on risk of leaving the trade.

Effect of Gender Differences and Other Factors on Remuneration of Employees in EU Countries

The aim of the paper is to verify gender income differences and to reveal factors influencing differences in remuneration. Gender income differences across the EU range from 6% in Romania to 27% in the Czech Republic. Data from 178,878 employees filtered from the EU-SILC database were used for calculations. Stepwise regression analysis was used to identify factors that affect gender income differences. The greatest effect was shown in the “Absolute Income”, then the “Job Change in the Last Year” factor, but the “Education” and “Age” showed a strongly negative tendency. Extraordinary attention is devoted to the effect of the “Job sector” factor, which also significantly contributes to the difference in income. Different representation of gender appears in different industries, which can be caused by preferences and be a consequence of persisting society-wide stereotypes. Social policies are not in line with changes in society and lag behind the development of society.

Overqualification as Moderator for the Link Between Job Changes and Job Satisfaction Among Immigrated and Native-born People in Germany

Job satisfaction is a major driver of an individual’s subjective well-being and thus affects public health, societal prosperity, and organizations, as dissatisfied employees are less productive and more likely to change jobs. However, changing jobs does not necessarily lead to higher job satisfaction in the long run: instead, previous studies have shown that changing jobs only increases job satisfaction for a shorter period of time before it gradually falls back to similar levels as before. This phenomenon is known as the honeymoon-hangover pattern. In our study, we identify an important new moderator of the relation between job changes and job satisfaction: the job-education match of job change. Based on relative deprivation theory, we argue that a job change out of overqualification lowers the likelihood of negative comparisons and thus increases the honeymoon period and lessens the hangover. In addition, we investigate whether this moderating effect is weaker for immigrants, since the phenomenon of overqualification occurs more frequently among them. We use data from the Socio-Economic Panel ranging from 1994-2018 and focus specifically on individual-periods of employees before and after job changes (N=134,417). Our results confirm that a change to a qualificationadequate job has a stronger and longer-lasting effect on job satisfaction which is lower for respondents born abroad.

Work and Personality Change

Can your job change your personality? This book provides an overview on how personality can be changed at work by societal, organisational and job-related factors, while considering how individuals can take an active approach in changing their personality at work.