Student’s Perspectives on Prevention Strategies of Social Media Addiction Effects in Selected Colleges of Education on the Copperbelt Zambia

Social Media Addiction (SMA) effects have been recognised as a significant psychological health problem in many countries. Yet, few investigations have been conducted on SMA effects intervention strategies globally and almost none in Zambia. This study sought to explore strategies that may lessen the adverse effects of SMA on student’s psychological well-being in selected colleges of education on the Copperbelt province of Zambia. The study employed a qualitative case study research design involving 64 participants. Data were collected using the Focus Group Discussion (FGD), and interviews, whereas, the analysis was done with the help of a framework analysis approach to generate study themes. The results revealed that the student’s addictive usage of social media adversely affected their psychological well-being. The study spelt out various intervention strategies centred on government, colleges and guidance and counselling interventions levels. Practically, it has been anticipated that the ideas discussed under each level may facilitate effective and tailored intervention programs to reduce SMA effects among the students. DOI: 10.7176/JEP/12-3-17 Publication date: January 31st 202

Factors in the Use of Workplace Health Promotion on Back Health. Results of the Survey “German Health Update”

Background: The influence of the working environment on the back health of employees is well-documented. Many companies have begun to offer employees access to services to promote back health. Factors affecting the use of these offers at the population level have received little investigation to date. The current study examined the socio-demographic factors, physical activity and health-related factors, and work-related factors associated with the use of offers of workplace health promotion for back health in Germany. Materials and Methods: In the representative population-based cross-sectional survey “German Health Update” (GEDA 2014/2015-EHIS) conducted by the Robert Koch Institute, 12,072 employees aged 18–64 years old were surveyed from November 2014 to July 2015 regarding the use of back health services in their companies. In addition to socio-demographic factors, the survey examined working hours, physical activity in leisure time, health awareness, and subjective complaints in the lower back or other chronic back problems in the last 12 months. The interaction of these factors with the utilization of back health services was tested using multiple logistic regression models. Results: Women used back health services more often than men (women: 25.5%; men: 18.1%). Female gender was associated with part-time employment (OR 0.72) and a strong to very strong level of health awareness (OR 1.40). Male gender was associated with age between 30 and 44 years (OR 1.99) and 45–64 years (OR 2.02), low socioeconomic status (OR 0.48), endurance activity of <2.5 h per week (OR 0.62), and absence of lower back pain or other chronic back conditions for the last 12 months (OR 0.48). Conclusion: The present study is the first to provide findings regarding the factors associated with the utilization of workplace health promotion to promote back health at the population level, and from the perspective of employees in Germany. The results revealed that the relevant factors for participating in offers differ for women and men. To reach more employees, workplace health promotion offers for back health should be designed specifically for each individual, considering gender and age, working hours, health awareness and behavior, and health state.Peer Reviewe

Ensemble Forecasting of Major Solar Flares: Methods for Combining Models

One essential component of operational space weather forecasting is the prediction of solar flares. With a multitude of flare forecasting methods now available online it is still unclear which of these methods performs best, and none are substantially better than climatological forecasts. Space weather researchers are increasingly looking towards methods used by the terrestrial weather community to improve current forecasting techniques. Ensemble forecasting has been used in numerical weather prediction for many years as a way to combine different predictions in order to obtain a more accurate result. Here we construct ensemble forecasts for major solar flares by linearly combining the full-disk probabilistic forecasts from a group of operational forecasting methods (ASAP, ASSA, MAG4, MOSWOC, NOAA, and MCSTAT). Forecasts from each method are weighted by a factor that accounts for the method's ability to predict previous events, and several performance metrics (both probabilistic and categorical) are considered. It is found that most ensembles achieve a better skill metric (between 5\% and 15\%) than any of the members alone. Moreover, over 90\% of ensembles perform better (as measured by forecast attributes) than a simple equal-weights average. Finally, ensemble uncertainties are highly dependent on the internal metric being optimized and they are estimated to be less than 20\% for probabilities greater than 0.2. This simple multi-model, linear ensemble technique can provide operational space weather centres with the basis for constructing a versatile ensemble forecasting system -- an improved starting point to their forecasts that can be tailored to different end-user needs

Influence of Land Management on Soil Erosion, Connectivity and Sediment Delivery in Agricultural Catchments:Closing the Sediment Budget

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Influence of Land Management on Soil Erosion, Connectivity and Sediment Delivery in Agricultural Catchments:Closing the Sediment Budget

Peer-reviewedAgricultural land, and arable farming in particular, is commonly associated with increased soil erosion risk. Such systems are most vulnerable during low groundcover periods, but downstream delivery is ultimately controlled by connectivity. This study provides a catchment-scale sediment budget integrating three discrete but complementary investigations spanning different temporal and spatial scales. The first gives details on suspended sediment fluxes at the catchment outlet (2009–2012). The second provenances sources of fluxes using quantitative sediment fingerprinting. The third sets recent data in a multidecadal (60-year) context using radiometric (137Cs) field-scale soil loss estimates. The catchment observatory (11 km2) is low relief with predominantly well-drained soils and dominated by spring-sown cereal cropping through the study period. Modelling 137Cs inventory losses across 30 fields provided a catchment-wide mean soil loss of 2.0 Mg ha−1 yr−1. Although such rates are not atypical of intensively managed agriculture across Europe, they are considerably higher than contemporary sediment export yields of 0.12 Mg ha−1 yr−1 of which fingerprinting revealed that contemporary slope erosion contributed less than 25% (0.03 Mg ha−1 yr−1). No evidence of floodplain or in-channel sediment storage was consistent with disconnectivity. Instead, it is hypothesised that soil loss is associated with coextraction from root crop harvesting of previously widespread sugar beet crops. Considering that the highest mass-specific 137Cs concentration occurred during the 1960s, there appears to have been significant depletion of the cumulative 137Cs inventory where root crop harvesting occurred as compared with atmospheric fallout ‘reference sites.' The study highlights the value of multiple methodologies when seeking to understand legacy issues within agricultural catchment settings

Ensemble Forecasting of Major Solar Flares: Methods for Combining Models

One essential component of operational space weather forecasting is the prediction of solar flares. With a multitude of flare forecasting methods now available online it is still unclear which of these methods performs best, and none are substantially better than climatological forecasts. Space weather researchers are increasingly looking towards methods used by the terrestrial weather community to improve current forecasting techniques. Ensemble forecasting has been used in numerical weather prediction for many years as a way to combine different predictions in order to obtain a more accurate result. Here we construct ensemble forecasts for major solar flares by linearly combining the full-disk probabilistic forecasts from a group of operational forecasting methods (ASAP, ASSA, MAG4, MOSWOC, NOAA, and MCSTAT). Forecasts from each method are weighted by a factor that accounts for the method's ability to predict previous events, and several performance metrics (both probabilistic and categorical) are considered. It is found that most ensembles achieve a better skill metric (between 5\% and 15\%) than any of the members alone. Moreover, over 90\% of ensembles perform better (as measured by forecast attributes) than a simple equal-weights average. Finally, ensemble uncertainties are highly dependent on the internal metric being optimized and they are estimated to be less than 20\% for probabilities greater than 0.2. This simple multi-model, linear ensemble technique can provide operational space weather centres with the basis for constructing a versatile ensemble forecasting system -- an improved starting point to their forecasts that can be tailored to different end-user needs.Comment: Accepted for publication in the Journal of Space Weather and Space Climat

A recentering approach for interpreting interaction effects from logit, probit, and other nonlinear models

Research SummaryStrategic management has seen numerous studies analyzing interaction terms in nonlinear models since Hoetker’s (Strat Mgmt J., 2007, 28(4), 331- 343) best- practice recommendations and Zelner’s (Strat Mgmt J., 2009, 30(12), 1335- 1348) simulation- based approach. We suggest an alternative recentering approach to assess the statistical and economic importance of interaction terms in nonlinear models. Our approach does not rely on making assumptions about the values of the control variables; it takes the existing model and data as is and requires fewer computational steps. The recentering approach not only provides a consistent answer about statistical meaningfulness of the interaction term at a given point of interest, but also helps to assess the effect size using the template that we offer in this study. We demonstrate how to implement our approach and discuss the implications for strategy researchers.Managerial SummaryIn industry settings, the relationship between multiple corporate strategy- related inputs and corporate performance is often nonlinear in nature. Furthermore, such relationships tend to vary for different types of firms represented within the broader population of firms in a given industry. It is thus imperative for managers to know how to take nonlinear relationships between related business factors into account when they make strategic decisions. We suggest a simple and easily implementable way of assessing and interpreting interactions in a nonlinear setting, which we term a recentering approach. We demonstrate how to apply our approach to a strategic management setting.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163421/3/smj3202.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163421/2/smj3202-sup-0001-Supinfo.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163421/1/smj3202_am.pd