Kathrin Reichel

Mrs. Kathrin Reichel


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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PBPrem Borle
Prem Borle
KRKathrin Reichel
Kathrin Reichel
Fiona NiebuhrFiona Niebuhr
Fiona Niebuhr
SVSusanne Voelter-Mahlknecht
Susanne Voelter-Mahlknecht
The technostress model has introduced different factors to consider when assessing how information and communication technologies impact individuals in different work settings. This systematic review gathers evidence regarding associations between occupational exposure to technostress and health or work outcomes. In addition, we highlight typical methodological constraints of the technostress model. We conducted electronic literature searches in June 2020 (PubMed, PubMed Central, Web of Science, Scopus, PsycInfo, PsycArticles) and independently screened 321 articles. We report on 21 articles meeting eligibility criteria (working population, technostress exposure, health or work outcome, quantitative design). The most frequently examined techno-stressors, i.e., factors of technostress, were techno-overload and techno-invasion. Techno-stressors were consistently associated with adverse health and work outcomes, apart from a positive impact on work engagement. However, studies may be subject to considerable conceptual overlap between exposure and outcome measures. Future technostress research would benefit from reducing heterogeneity in technostress measures, assessing their external validity and focussing on specific techno-stressors.

PBPrem Borle
Prem Borle
KRKathrin Reichel
Kathrin Reichel
SVSusanne Voelter-Mahlknecht
Susanne Voelter-Mahlknecht
Technostress is a widespread model used to study negative effects of using information communication technologies at work. The aim of this review is to assess the role of socioeconomic position (SEP) in research on work-related technostress. We conducted systematic searches in multidisciplinary databases (PubMed, PubMed Central, Web of Science, Scopus, PsycInfo, PsycArticles) in June 2020 and independently screened 321 articles against eligibility criteria (working population, technostress exposure, health or work outcome, quantitative design). Of the 21 studies included in the narrative synthesis, three studies did not collect data on SEP, while 18 studies operationalised SEP as education (eight), job position (five), SEP itself (two) or both education as well as job position (three). Findings regarding differences by SEP are inconclusive, with evidence of high SEP reporting more frequent exposure to overall technostress. In a subsample of 11 studies reporting data on educational attainment, we compared the percentage of university graduates to World Bank national statistics and found that workers with high SEP are overrepresented in nine of 11 studies. The resulting socioeconomic sampling bias limits the scope of the technostress model to high SEP occupations. The lack of findings regarding differences by SEP in technostress can partly be attributed to limitations in study designs. Studies should aim to reduce the heterogeneity of technostress and SEP measures to improve external validity and generalisability across socioeconomic groups. Future research on technostress would benefit from developing context-sensitive SEP measures and quality appraisal tools that identify socioeconomic sampling biases by comparing data to national statistics.