Integrating International Students into Tertiary Education Using Intercultural Peer-to-peer Training at Jacobs University Bremen, Germany

Increasing internationalization of higher education raises the question of how well institutions prepare their students to integrate into and benefit from cultural diversity on any university campus. The aim of this study was to assess an intercultural peer-to-peer training at Jacobs University Bremen, Germany, that aims to facilitate the integration of incoming students into the multicultural environment of this international university. The individual experience of eight undergraduate students was explored using qualitative in-depth interviews. The results suggest that motivation to participate and satisfaction with the training were highest among students with some intercultural experience compared to students with extensive or little intercultural experience. All students supported the overall training format and the peer-trainer scheme. It seems that the training has adequately addressed the issues related to the general social life on the multicultural campus. However, it should focus more specifically on the learning model used and learning-related expectations at Jacobs University Bremen. In conclusion, the current study provides the first qualitative evaluation of an intercultural peer-to-peer training that could be utilized at other educational institutions in Germany and beyond as a method of linking culture-related issues to academic and social life of new students

Does Gender Matter? Female Representation on Corporate Boards and Firm Financial Performance-A Meta-Analysis

In recent years, there has been an ongoing, worldwide debate about the representation of females in companies. Our study aimed to meta-analytically investigate the controversial relationship between female representation on corporate boards and firm financial performance. Following a systematic literature search, data from 20 studies on 3097 companies published in peer-reviewed academic journals were included in the meta-analysis. On average, the boards consisted of eight members and female participation was low (mean 14%) in all studies. Half of the 20 studies were based on data from developing countries and 62% from higher income countries. According to the random-effects model, the overall mean weighted correlation between percentage of females on corporate boards and firm performance was small and non-significant (r = .01, 95% confidence interval: -.04, .07). Similar small effect sizes were observed when comparing studies based on developing vs. developed countries and higher vs. lower income countries. The mean board size was not related to the effect sizes in studies. These results indicate that the mere representation of females on corporate boards is not related to firm financial performance if other factors are not considered. We conclude our study with a discussion of its implications and limitations

Can deep transcranial magnetic stimulation (DTMS) be used to treat substance use disorders (SUD)? a systematic review

Background: Deep transcranial magnetic stimulation (DTMS) is a non-invasive method of stimulating widespread cortical areas and, presumably, deeper neural networks. The current study assessed the effects of DTMS in the treatment of substance use disorders (SUD) using a systematic review. Methods: Electronic literature search (PsycInfo, Medline until April 2017) identified k = 9 studies (k = 4 randomizedcontrolled trials, RCTs, with inactive sham and k = 5 open-label studies). DTMS was most commonly applied using high frequency/intensity (10–20 Hz/100–120% of the resting motor threshold, MT) protocols for 10–20 daily sessions in cases with alcohol, nicotine or cocaine use disorders. The outcome measures were craving and dependence (according to standardized scales) or consumption (frequency, abstinence or results of biological assays) at the end of the daily treatment phases and at the last follow-up. Results: Acute and longer-term (6–12 months) reductions in alcohol craving were observed after 20 sessions (20 Hz, 120% MT) relative to baseline in k = 4 open-label studies with comorbid SUD and major depressive disorder (MDD). In k = 2 RCTs without MDD, alcohol consumption acutely decreased after 10–12 sessions (10–20 Hz, 100– 120% MT) relative to baseline or to sham. Alcohol craving was reduced only after higher frequency/intensity DTMS (20 Hz, 120% MT) relative to sham in k = 1 RCT. Nicotine consumption was reduced and abstinence was increased after 13 sessions (10 Hz, 120% MT) and at the 6-month follow-up relative to sham in k = 1 RCT. Cocaine craving was reduced after 12 sessions (15 Hz, 100% MT) and at the 2-month follow-up relative to baseline in k = 1 open-label study while consumption was reduced after 12 sessions (10 Hz, 100% MT) relative to baseline but not to sham in k = 1 RCT. Conclusions: High-frequency DTMS may be effective at treating some SUD both acutely and in the longer-term. Large RCTs with inactive sham are required to determine the efficacy and the optimal stimulation parameters of DTMS for the treatment of SUD

Funnel plot of the estimated variability (standard error of the mean, <i>SEM</i>) and effect size <i>r</i> (expressed as Fisher’s <i>z</i>) in each study.

<p>This plot shows that the effect sizes in the individual studies (circles) were symmetrically distributed around the overall mean weighted effect size shown on the vertical line.</p

Forest plot of the cumulative analysis.

<p>‘Combined’ refers to the mean effect size of studies that have used multiple measures of firm performance. ‘Total’ refers to the total number of observations (number of firms × number of years) as one study is added to all previous studies in each row. The plot shows how the overall mean weighted effect size <i>r</i> (referred to as ‘Point’) changes as each study is added over time to all previous studies. The diamond depicts the overall mean weighted effect size <i>r</i> of all <i>k</i> = 20 studies.</p

Study characteristics and effect size data in 20 studies included in the meta-analysis.

<p>Abbreviations: AEX = Amsterdam Euronext Stock Exchange; ASX = Australian Securities Exchange; <i>Board</i> = mean size of the board; <i>CACM</i> = China’s A-Share Capital Market; <i>Country</i> = country of data collection; <i>CSE</i> = Colombo Stock Exchange; <i>Data</i> Source = Sampling Source of the studies<i>; DC</i> = developing country; <i>DEV</i> = developed country; <i>FTSE</i> = Financial Times Stock Exchange; <i>GNI</i> = Gross National Income Classification; <i>HI</i> = high-income; <i>IPO</i> = Initial Public Offering; <i>ISE</i> = Indonesian Stock Exchange; <i>LI</i> = low-income; <i>Mean (SD)</i> = mean (and standard deviation) of the performance measure; <i>MFI</i> = Microfinance Institutions; <i>MSE</i> = Madrid Stock Exchange; <i>N</i> = number of observations (number of firms × total length of data collection in years); <i>NSE</i> = Nigerian Stock Exchange; <i>No</i>. <i>Firms</i> = Number of firms in sample; <i>OSE</i> = Oslo Stock Exchange; <i>Period</i> = time frame in which data were collected; <i>% Female</i> = percentage of female board members.</p><p>Study characteristics and effect size data in 20 studies included in the meta-analysis.</p

Search terms and databases (all searches conducted in English).

<p>Search terms and databases (all searches conducted in English).</p

Forest plot of the association between percentage female representation on corporate boards and firm performance.

<p>‘Correlation’ refers to the weighted Pearson product moment correlation coefficient, <i>r</i>. ‘Combined’ refers to the mean effect size in studies using multiple measures of firm performance. ‘Total’ refers to the total number of observations per study (number of firms × number of years). The diamond depicts the overall mean weighted effect size <i>r</i> of all <i>k</i> = 20 studies. There is a small positive, but not statistically significant, relationship between percentage female representation on corporate boards and firm performance (overall mean weighted <i>r</i> = .01, 95% confidence interval, <i>95%CI</i>:-.04, .07).</p