Heterogeneous peer effects of college roommates on academic performance

Understanding how student peers influence learning outcomes is crucial for effective education management in complex social systems. The complexities of peer selection and evolving peer relationships, however, pose challenges for identifying peer effects using static observational data. Here we use both null-model and regression approaches to examine peer effects using longitudinal data from 5,272 undergraduates, where roommate assignments are plausibly random upon enrollment and roommate relationships persist until graduation. Specifically, we construct a roommate null model by randomly shuffling students among dorm rooms and introduce an assimilation metric to quantify similarities in roommate academic performance. We find significantly larger assimilation in actual data than in the roommate null model, suggesting roommate peer effects, whereby roommates have more similar performance than expected by chance alone. Moreover, assimilation exhibits an overall increasing trend over time, suggesting that peer effects become stronger the longer roommates live together. Our regression analysis further reveals the moderating role of peer heterogeneity. In particular, when roommates perform similarly, the positive relationship between a student's future performance and their roommates' average prior performance is more pronounced, and their ordinal rank in the dorm room has an independent effect. Our findings contribute to understanding the role of college roommates in influencing student academic performance.

Who benefits from quality competition in health care? A theory and a laboratory experiment on the relevance of patient characteristics

We study how competition between physicians affects the provision of medical care. In our theoretical model, physicians are faced with a heterogeneous patient population, in which patients systematically vary with regard to both their responsiveness to the provided quality of care and their state of health. We test the behavioral predictions derived from this model in a controlled laboratory experiment. In line with the model, we observe that competition significantly improves patient benefits as long as patients are able to respond to the quality provided. For those patients, who are not able to choose a physician, competition even decreases the patient benefit compared to a situation without competition. This decrease is in contrast to our theoretical prediction implying no change in benefits for passive patients. Deviations from patient-optimal treatment are highest for passive patients in need of a low quantity of medical services. With repetition, both, the positive effects of competition for active patients as well as the negative effects of competition for passive patients become more pronounced. Our results imply that competition can not only improve but also worsen patient outcome and that patients' responsiveness to quality is decisive.

Providers, peers and patients. How do physicians' practice environments affect patient outcomes?

We study how physicians' practice environments affect their treatment decisions and quality of care. Using clinical registry data from Sweden, we compare stent choices of cardiologists moving across hospitals over time. To disentangle changes in practice styles attributable to hospital- and peer group-specific factors, we exploit quasi-random variation on cardiologists working together on the same days. We find that migrating cardiologists' stent choices rapidly adapt to their new practice environment after relocation and are equally driven by the hospital and peer environments. In contrast, while decision errors increase, treatment costs and adverse clinical events remain largely unchanged despite the altered practice styles.

Physician-Peer Relationships and Patient Experiences With Specialist Care

IMPORTANCE

Peer relationships may motivate physicians to aspire to high professional standards but have not been a major focus of quality improvement efforts.

OBJECTIVE

To determine whether peer relationships between primary care physicians (PCPs) and specialists formed during training motivate improved specialist care for patients.

DESIGN, SETTING, AND PARTICIPANTS

In this quasi-experimental study, difference-in-differences analysis was used to estimate differences in experiences with specialist care reported by patients of the same PCP for specialists who did vs did not co-train with the PCP, controlling for any differences in patient ratings of the same specialists in the absence of co-training ties. Specialist visits resulting from PCP referrals from 2016 to 2019 in a large health system were analyzed, including a subset of undirected referrals in which PCPs did not specify a specialist. Data were collected from January 2016 to December 2019 and analyzed from March 2020 to October 2022.

EXPOSURE

The exposure was PCP-specialist overlap in training (medical school or postgraduate medical) at the same institution for at least 1 year (co-training).

MAIN OUTCOMES AND MEASURES

Composite patient experience rating of specialist care constructed from Press Ganey's Medical Practice Survey.

RESULTS

Of 9920 specialist visits for 8655 patients (62.9% female; mean age, 57.4 years) with 502 specialists in 13 specialties, 3.1% (306) involved PCP-specialist dyads with a co-training tie. Co-training ties between PCPs and specialists were associated with a 9.0 percentage point higher adjusted composite patient rating of specialist care (95% CI, 5.6-12.4 percentage points; P < .001), analogous to improvement from the median to the 91st percentile of specialist performance. This association was stronger for PCP-specialist dyads with full temporal overlap in training (same class or cohort) and consistently strong for 9 of 10 patient experience items, including clarity of communication and engagement in shared decision-making. In secondary analyses of objective markers of altered specialist practice in an expanded sample of visits not limited by the availability of patient experience data, co-training was associated with changes in medication prescribing, suggesting behavioral changes beyond interpersonal communication. Patient characteristics varied minimally by co-training status of PCP-specialist dyads. Results were similar in analyses restricted to undirected referrals (in which PCPs did not specify a specialist). Concordance between PCPs and specialists in physician age, sex, medical school graduation year, and training institution (without requiring temporal overlap) was not associated with better care experiences.

CONCLUSIONS AND RELEVANCE

In this quasi-experimental study, PCP-specialist co-training elicited changes in specialist care that substantially improved patient experiences, suggesting potential gains from strategies encouraging the formation of stronger physician-peer relationships.

Eigenvalue productivity: Measurement of individual contributions in teams

While the output of a team is evident, the productivity of each team member is typically not readily identifiable. In this paper we consider the problem of measuring the productivity of team members. We propose a new concept of coworker productivity, which we refer to as eigenvalue productivity (EVP). We demonstrate the existence and uniqueness of our concept and show that it possesses several desirable properties. Also, we suggest a procedure for specifying the required productivity matrix of a team, and illustrate the operational practicability of EVP by means of three examples representing different types of available data.

The Effect of Expert Feedback on Antibiotic Prescribing in Pediatrics: Experimental Evidence

Background. Inappropriate prescribing of antibiotics, which is common in pediatric care, is a key driver of antimicrobial resistance. To mitigate the development of resistance, antibiotic stewardship programs often suggest the inclusion of feedback targeted at individual providers. Empirically, however, it is not well understood how feedback affects individual physicians’ antibiotic prescribing decisions. Also, the question of how physicians’ characteristics, such as clinical experience, relate to antibiotic prescribing decisions and to responses to feedback is largely unexplored. Objective. To analyze the causal effect of descriptive expert feedback (and individual characteristics) on physicians’ antibiotic prescribing decisions in pediatrics. Design. We employed a randomized, controlled framed field experiment, in which German pediatricians (n=73) decided on the length of first-line antibiotic treatment for routine pediatric cases. In the intervention group (n=39), pediatricians received descriptive feedback in form of an expert benchmark, which allowed them to compare their own prescribing decisions with expert recommendations. The recommendations were elicited in a survey of pediatric department directors (n=20), who stated the length of antibiotic therapies they would choose for the routine cases. Pediatricians’ characteristics were elicited in a comprehensive questionnaire. Results. Providing pediatricians with expert feedback significantly reduced the length of antibiotic therapies by 10% on average. Also, the deviation of pediatricians’ decisions from experts’ recommendations significantly decreased. Antibiotic therapy decisions were significantly related to pediatricians’ clinical experience, risk attitudes, and personality traits. The effect of feedback was significantly associated with physicians’ experience. Conclusion. Our results indicate that descriptive expert feedback can be an effective means to guide pediatricians, especially those who are inexperienced, toward more appropriate antibiotic prescribing. Therefore, it seems to be suitable for inclusion in antibiotic stewardship programs.

Causal peer effects in police misconduct

We estimate causal peer effects in police misconduct using data from about 35,000 officers and staff from London's Metropolitan Police Service for the period 2011-2014. We use instrumental variable techniques and exploit the variation in peer misconduct that results when officers switch peer groups. We find that a 10% increase in prior peer misconduct increases an officer's later misconduct by 8%. As the police are empowered to enforce the law and protect individual liberties, integrity and fairness in policing are essential for establishing and maintaining legitimacy and public consent^1-5. Understanding the antecedents of misconduct will help to develop interventions that reduce misconduct.

Peers at work: Evidence from the lab

This paper reports the results of a lab experiment designed to study the role of observability for peer effects in the setting of a simple production task. In our experiment, participants in the role of workers engage in a team real-effort task. We vary whether they can observe, or be observed by, one of their co-workers. In contrast to earlier findings from the field, we find no evidence that low-productivity workers perform better when they are observed by high-productivity co-workers. Instead, our results imply that peer effects in our experiment are heterogeneous, with some workers reciprocating a high-productivity co-worker but others taking the opportunity to free ride.

The effects of competition on medical service provision

We explore how competition between physicians affects medical service provision. Previous research has shown that, without competition, physicians deviate from patient-optimal treatment under payment systems like capitation and fee-for-service. Although competition might reduce these distortions, physicians usually interact with each other repeatedly over time and only a fraction of patients switches providers at all. Both patterns might prevent competition to work in the desired direction. To analyze the behavioral effects of competition, we develop a theoretical benchmark that is then tested in a controlled laboratory experiment. Experimental conditions vary physician payment and patient characteristics. Real patients benefit from provision decisions made in the experiment. Our results reveal that, in line with the theoretical prediction, introducing competition can reduce overprovision and underprovision, respectively. The observed effects depend on patient characteristics and the payment system, though. Tacit collusion is observed and particularly pronounced with fee-for-service payment, but it appears to be less frequent than in related experimental research on price competition.

The dynamics of behavior in modified dictator games

We investigate the dynamics of individual pro-social behavior over time. The dynamics are tested by running the same experiment with the same subjects at several points in time. To exclude learning and reputation building, we employ non-strategic decision tasks and a sequential prisoners-dilemma as a control treatment. In the first wave, pro-social concerns explain a high share of individual decisions. Pro-social decisions decrease over time, however. In the final wave, most decisions can be accounted for by assuming pure selfishness. Stable behavior in the sense that subjects stick to their decisions over time is observed predominantly for purely selfish subjects. We offer two explanation for our results: diminishing experimenter demand effects and moral self-licensing.

How Simple Hypothetical-Choice Experiments Can Be Utilized to Learn Humans' Navigational Escape Decisions in Emergencies

How humans resolve non-trivial tradeoffs in their navigational choices between the social interactions (e.g., the presence and movements of others) and the physical factors (e.g., spatial distances, route visibility) when escaping from threats in crowded confined spaces? The answer to this question has major implications for the planning of evacuations and the safety of mass gatherings as well as the design of built environments. Due to the challenges of collecting behavioral data from naturally-occurring evacuation settings, laboratory-based virtual-evacuation experiments have been practiced in a number of studies. This class of experiments faces the traditional question of contextual bias and generalizability: How reliably can we infer humans' behavior from decisions made in hypothetical settings? Here, we address these questions by making a novel link between two different forms of empirical observations. We conduct hypothetical emergency exit-choice experiments framed as simple pictures, and then mimic those hypothetical scenarios in more realistic fashions through staging mock evacuation trials with actual crowds. Econometric choice models are estimated based on the observations made in both experimental contexts. The models are contrasted with each other from a number of perspectives including their predictions as well as the sign, magnitude, statistical significance, person-to-person variations (reflecting individuals' perception/preference differences) and the scale (reflecting context-dependent decision randomness) of their inferred parameters. Results reveal a surprising degree of resemblance between the models derived from the two contexts. Most strikingly, they produce fairly similar prediction probabilities whose differences average less than 10%. There is also unexpected consensus between the inferences derived from both experimental sources on many aspects of people's behavior notably in terms of the perception of social interactions. Results show that we could have elicited peoples' escape strategies with fair precision without observing them in action (i.e., simply by using only hypothetical-choice data as an inexpensive, practical and non-invasive experimental technique in this context). As a broader application, this offers promising evidence as to the potential applicability of the hypothetical-decision experiments to other decision contexts (at least for non-financial decisions) when field or real-world data is prohibitively unavailable. As a practical application, the behavioral insights inferred from our observations (reflected in the estimated parameters) can improve how accurately we predict the movement patterns of human crowds in emergency scenarios arisen in complex spaces. Fully-generic-in-parameters, our proposed models can even be directly introduced to a broad range of crowd simulation software to replicate navigation decision making of evacuees.