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Identifying predictors of career success is one of the most considered topics in career research and practice. However, the existing literature suggests a vast array of potential predictors that cannot be economically measured. This significantly limits research and practice. To address this issue, we have integrated theoretical and meta-analytic research to propose an integrative framework of career resources, including human capital, environmental, motivational, and career management behavior resources represented by 13 distinct factors. In a multistep process, we have developed the career resources questionnaire to assess these factors in workers and college students. In two studies encompassing 873 workers and 691 students, we have confirmed reliability and factor structure, convergent validity with existing scales, and criterion validity with indicators of subjective and objective career success. The developed measure can provide researchers and practitioners with a reliable, concise, and comprehensive measure to assess the key predictors of career success.

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Career development increasingly demands a successful integration of work and nonwork domains. Based on work-nonwork conflict and enrichment theories, this study explored the relationship between nonwork orientations (i.e., family, personal life, and community) and both objective (i.e., salary) and subjective (i.e., career satisfaction) career success and life satisfaction over a period of six months among a sample of 548 employees from Germany. The results generally support the enrichment perspective. Family orientation showed a positive relationship with career satisfaction. All three nonwork orientations, especially family orientation, were positively related to life satisfaction. We also explored gender and age effects but found no differences in nonwork orientations between young employees aged 25-34 years and older workers aged 50-59 years. Men showed lower levels of personal life orientation than women, but no differences in family or community orientation based on gender were found. We also did not observe gender x age interaction effects. We discuss the study's implications for a whole-life perspective on career development, career success, and well-being.

The purpose of the current study was to evaluate the usefulness of a radiofrequency (RF) personal exposimeter (dosimeter) for assessing individual RF exposure in an urban environment. Measurements taken by RF personal dosimeter were also compared to preliminary site measurements taken around mobile base stations. The results from personal exposure showed that one third of the participants spent 40-70% of 24 h recording time above the detection limits (0.05 V/m), and half of subjects spent less than 10%. The highest exposure was detected during the traveling period and the lowest in bed at home. Based on our results, we concluded that site measurements cannot be used to accurately determine personal exposure. We also concluded that duration of time exposed to RF levels above the detection limit of the personal dosimeter is a useful exposure metric to compare and contrast individual RF exposure of study subjects.

Do we act as old as we feel? An examination of subjective age and job crafting behaviour of late career employees.

Exposure to 50 Hz magnetic field (MF) was evaluated in 31 multi-level apartment buildings with built-in step-down transformer stations. In each building, three apartments were selected: one apartment located immediately above the transformer room (index apartment), one located on the same floor and one on a higher floor. The mean value of measured MFs was 0.98 microT in apartments above transformers, 0.13 microT on the same floor, and 0.1 microT in on higher floors. The mean measured MF value was higher than 0.2 microT in 30 (97%) index apartments, 4 (14%) on the same floor as the index apartments and 4 (13%) on higher floors. The corresponding numbers were 25 (81%), 0 and 0, respectively, when 0.4 microT was used as cut-point. It is concluded that apartments in building with built-in transformers can be reliably classified into high and low-exposure categories based on their location in relation to transformers.