Ability Dispersion and Team Performance: a field experiment

This paper studies the impact of diversity in cognitive ability among members of a team on their performance. We conduct a large field experiment in which teams start up and manage real companies under identical circumstances. Exogenous variation in - otherwise random - team composition is imposed by assigning individuals to teams based on their measured cognitive abilities. The setting is one of business management practices in the longer run where tasks are diverse and involve complex decision-making. We propose a model in which greater ability dispersion generates greater knowledge for a team, but also increases the costs of monitoring necessitated by moral hazard. Consistent with the predictions of our model, we find that team performance as measured in terms of sales, profits and profits per share first increases, and then decreases, with ability dispersion. Teams with a moderate degree of ability dispersion also experience fewer dismissals due to fewer shirking members in those teams

A Field Experiment

One of the most salient and relevant dimensions of team heterogeneity is cultural back- ground. We measure the impact of cultural diversity on the performance of business teams using a eld experiment. Companies are set up by teams of undergraduate students in business studies in realistic though similar circumstances. We vary the cultural composition of otherwise randomly composed teams in a multi-cultural stu- dent population. Our data indicate that a moderate level of cultural diversity has no e ect on team performance in terms of business outcomes (sales, pro ts and pro ts per share). However, if at least the majority of team members is culturally diverse then more cultural diversity seems to a ect the performance of teams positively. Our data suggest that this might be related to the more diverse pool of relevant knowledge facilitating (mutual) learning within culturally diverse teams

Ability Dispersion and Team Performance

What is the effect of dispersed levels of cognitive ability of members of a (business) team on their team's performance? This paper reports the results of a field experiment in which 573 students in 49 teams start up and manage real companies under identical circumstances. We ensured exogenous variation in - otherwise random - team composition by assigning students to teams based on their measured cognitive abilities (Raven test). Each team performs a variety of tasks, often involving complex decision making. The key result of the experiment is that the performance of business teams first increases and then decreases with ability dispersion. We seek to understand this finding by developing a model in which team members of different ability levels form sub-teams with other team members with similar ability levels to specialize in different productive tasks. Diversity spreads production over different tasks in order to escape diminishing marginal returns under specialization. The model comes with a boundary condition: our experimental finding is most likely to emerge in settings where different tasks exhibit moderate differences in their productive contributions to total output

Estimating Additive Interaction in Two-Stage Individual Participant Data Meta-Analysis

Individual participant data (IPD) meta-analysis provides important opportunities to study interaction and effect modification for which individual studies often lack power. While previous meta-analyses have commonly focused on multiplicative interaction, additive interaction holds greater relevance for public health and may in certain contexts better reflect biological interaction. Methodological literature on interaction in IPD meta-analysis does not cover additive interaction for models including binary or time-to-event outcomes. We aimed to describe how the Relative Excess Risk due to Interaction (RERI) and other measures of additive interaction or effect modification can be validly estimated within two-stage IPD meta-analysis. First, we explain why direct pooling of study-level RERI estimates may lead to invalid results. Next, we propose a three-step procedure to estimate additive interaction: 1) estimate effects of both exposures and their product term on the outcome within each individual study; 2) pool study-specific estimates using multivariate meta-analysis; 3) estimate an overall RERI and 95% confidence interval based on the pooled effect estimates. We illustrate this procedure by investigating interaction between depression and smoking and risk of smoking-related cancers using data from the PSYchosocial factors and Cancer (PSY-CA) consortium. We discuss implications of this procedure, including the application in meta-analysis based on published data

The Impact of Gender Diversity on the Performance of Business Teams: Evidence from a Field Experiment

This paper reports on a field experiment conducted to estimate the impact of the share of women in business teams on their performance. Teams consisting of undergraduate students in business studies start up a venture as part of their curriculum. We manipulated the gender composition of teams and assigned students randomly to teams, conditional on their gender. We find that teams with an equal gender mix perform better than male-dominated teams in terms of sales and profits. We explore various mechanisms suggested in the literature to explain this positive effect of gender diversity on performance (including complementarities, learning, monitoring, and conflicts) but find no support for them

Psychosocial factors, health behaviors and risk of cancer incidence: Testing interaction and effect modification in an individual participant data meta-analysis

Depression, anxiety and other psychosocial factors are hypothesized to be involved in cancer development. We examined whether psychosocial factors interact with or modify the effects of health behaviors, such as smoking and alcohol use, in relation to cancer incidence. Two-stage individual participant data meta-analyses were performed based on 22 cohorts of the PSYchosocial factors and CAncer (PSY-CA) study. We examined nine psychosocial factors (depression diagnosis, depression symptoms, anxiety diagnosis, anxiety symptoms, perceived social support, loss events, general distress, neuroticism, relationship status), seven health behaviors/behavior-related factors (smoking, alcohol use, physical activity, body mass index, sedentary behavior, sleep quality, sleep duration) and seven cancer outcomes (overall cancer, smoking-related, alcohol-related, breast, lung, prostate, colorectal). Effects of the psychosocial factor, health behavior and their product term on cancer incidence were estimated using Cox regression. We pooled cohort-specific estimates using multivariate random-effects meta-analyses. Additive and multiplicative interaction/effect modification was examined. This study involved 437,827 participants, 36,961 incident cancer diagnoses, and 4,749,481 person years of follow-up. Out of 744 combinations of psychosocial factors, health behaviors, and cancer outcomes, we found no evidence of interaction. Effect modification was found for some combinations, but there were no clear patterns for any particular factors or outcomes involved. In this first large study to systematically examine potential interaction and effect modification, we found no evidence for psychosocial factors to interact with or modify health behaviors in relation to cancer incidence. The behavioral risk profile for cancer incidence is similar in people with and without psychosocial stress

Psychosocial factors, health behaviors and risk of cancer incidence:Testing interaction and effect modification in an individual participant data meta-analysis

Depression, anxiety and other psychosocial factors are hypothesized to be involved in cancer development. We examined whether psychosocial factors interact with or modify the effects of health behaviors, such as smoking and alcohol use, in relation to cancer incidence. Two-stage individual participant data meta-analyses were performed based on 22 cohorts of the PSYchosocial factors and CAncer (PSY-CA) study. We examined nine psychosocial factors (depression diagnosis, depression symptoms, anxiety diagnosis, anxiety symptoms, perceived social support, loss events, general distress, neuroticism, relationship status), seven health behaviors/behavior-related factors (smoking, alcohol use, physical activity, body mass index, sedentary behavior, sleep quality, sleep duration) and seven cancer outcomes (overall cancer, smoking-related, alcohol-related, breast, lung, prostate, colorectal). Effects of the psychosocial factor, health behavior and their product term on cancer incidence were estimated using Cox regression. We pooled cohort-specific estimates using multivariate random-effects meta-analyses. Additive and multiplicative interaction/effect modification was examined. This study involved 437,827 participants, 36,961 incident cancer diagnoses, and 4,749,481 person years of follow-up. Out of 744 combinations of psychosocial factors, health behaviors, and cancer outcomes, we found no evidence of interaction. Effect modification was found for some combinations, but there were no clear patterns for any particular factors or outcomes involved. In this first large study to systematically examine potential interaction and effect modification, we found no evidence for psychosocial factors to interact with or modify health behaviors in relation to cancer incidence. The behavioral risk profile for cancer incidence is similar in people with and without psychosocial stress.</p

Psychosocial factors, health behaviors and risk of cancer incidence:Testing interaction and effect modification in an individual participant data meta-analysis

Depression, anxiety and other psychosocial factors are hypothesized to be involved in cancer development. We examined whether psychosocial factors interact with or modify the effects of health behaviors, such as smoking and alcohol use, in relation to cancer incidence. Two-stage individual participant data meta-analyses were performed based on 22 cohorts of the PSYchosocial factors and CAncer (PSY-CA) study. We examined nine psychosocial factors (depression diagnosis, depression symptoms, anxiety diagnosis, anxiety symptoms, perceived social support, loss events, general distress, neuroticism, relationship status), seven health behaviors/behavior-related factors (smoking, alcohol use, physical activity, body mass index, sedentary behavior, sleep quality, sleep duration) and seven cancer outcomes (overall cancer, smoking-related, alcohol-related, breast, lung, prostate, colorectal). Effects of the psychosocial factor, health behavior and their product term on cancer incidence were estimated using Cox regression. We pooled cohort-specific estimates using multivariate random-effects meta-analyses. Additive and multiplicative interaction/effect modification was examined. This study involved 437,827 participants, 36,961 incident cancer diagnoses, and 4,749,481 person years of follow-up. Out of 744 combinations of psychosocial factors, health behaviors, and cancer outcomes, we found no evidence of interaction. Effect modification was found for some combinations, but there were no clear patterns for any particular factors or outcomes involved. In this first large study to systematically examine potential interaction and effect modification, we found no evidence for psychosocial factors to interact with or modify health behaviors in relation to cancer incidence. The behavioral risk profile for cancer incidence is similar in people with and without psychosocial stress.</p

Depression, anxiety, and the risk of cancer:An individual participant data meta-analysis

Background: Depression and anxiety have long been hypothesized to be related to an increased cancer risk. Despite the great amount of research that has been conducted, findings are inconclusive. To provide a stronger basis for addressing the associations between depression, anxiety, and the incidence of various cancer types (overall, breast, lung, prostate, colorectal, alcohol-related, and smoking-related cancers), individual participant data (IPD) meta-analyses were performed within the Psychosocial Factors and Cancer Incidence (PSY-CA) consortium. Methods: The PSY-CA consortium includes data from 18 cohorts with measures of depression or anxiety (up to N = 319,613; cancer incidences, 25,803; person-years of follow-up, 3,254,714). Both symptoms and a diagnosis of depression and anxiety were examined as predictors of future cancer risk. Two-stage IPD meta-analyses were run, first by using Cox regression models in each cohort (stage 1), and then by aggregating the results in random-effects meta-analyses (stage 2). Results: No associations were found between depression or anxiety and overall, breast, prostate, colorectal, and alcohol-related cancers. Depression and anxiety (symptoms and diagnoses) were associated with the incidence of lung cancer and smoking-related cancers (hazard ratios [HRs], 1.06–1.60). However, these associations were substantially attenuated when additionally adjusting for known risk factors including smoking, alcohol use, and body mass index (HRs, 1.04–1.23). Conclusions: Depression and anxiety are not related to increased risk for most cancer outcomes, except for lung and smoking-related cancers. This study shows that key covariates are likely to explain the relationship between depression, anxiety, and lung and smoking-related cancers. Preregistration number: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=157677.</p

Non-operative vs. operative treatment for multiple rib fractures after blunt thoracic trauma: a multicenter prospective cohort study

Background: Patients with multiple rib fractures without a clinical flail chest are increasingly being treated with rib fixation; however, high-quality evidence to support this development is lacking. Methods: We conducted a prospective multicenter observational study comparing rib fixation to non-operative treatment in all patients aged 18 years and older with computed tomography confirmed multiple rib fractures without a clinical flail chest. Three centers performed rib fixation as standard of care. For adequate comparison, the other three centers performed only non-operative treatment. As such clinical equipoise formed the basis for the comparison in this study. Patients were matched using propensity score matching. Results: In total 927 patients with multiple rib fractures were included. In the three hospitals that performed rib fixation, 80 (14%) out of 591 patients underwent rib fixation. From the nonoperative centers, on average 71 patients were adequately matched to 71 rib fixation patients after propensity score matching. Rib fixation was associated with an increase in hospital length of stay (HLOS) of 4.9 days (95%CI 0.8–9.1, p = 0.02) and a decrease in quality of life (QoL) measured by the EQ5D questionnaire at 1 year of 0.1 (95% CI − 0.2–0.0, p = 0.035) compared to non-operative treatment. A subgroup analysis of patients who received operative care within 72 h showed a similar decrease in QoL. Up to 22 patients (28%) who underwent surgery experienced implant-related irritation. Conclusions: We found no benefits and only detrimental effects associated with rib fixation. Based on these results, we do not recommend rib fixation as the standard of care for patients with multiple rib fractures. Trial registration: Registered in the Netherlands Trial Register NTR6833 on 13/11/2017