Incorporating professional recommendations into a graduate-level statistical consulting laboratory: A case study

Statistical consulting services have gained prominence in medical research as collaborations between statisticians and clinical teams have increased. Existing guidelines focus on larger organizations with professional staff, but their applicability to student-led services is uncertain. Prior research has shown that structured consulting models improve research quality and efficiency. However, the dual purpose of training and service in graduate-led settings remains underexplored. The CTSA consortium has proposed recommendations for statistical consulting services. These guidelines emphasize structure, communication, and impact assessment. Yet, no prior work had resolved how these could apply to graduate-led models. This gap motivated an investigation into adapting these guidelines for student-led consulting. The study aimed to bridge this knowledge gap by applying CTSA recommendations in a graduate consulting laboratory.

The study aimed to evaluate how professional recommendations for statistical consulting services could be adapted for a graduate-led environment. It focused on a specific challenge: applying guidelines from larger organizations to a setting where students provide statistical support. The motivation was to determine if CTSA recommendations could be successfully implemented in a training-focused laboratory. The researchers sought to assess both service effectiveness and student learning outcomes. They also aimed to measure the volume of consulting requests and investigator feedback. The study addressed a gap in understanding how student-led consulting can meet professional standards. By applying CTSA guidelines, the team aimed to test their transferability to smaller, training-oriented models. The results would help inform best practices for graduate statistical consulting programs.

The study involved applying CTSA guidelines to a graduate-led statistical consulting laboratory. The team adapted these guidelines to fit the dual goals of service and training. They structured the laboratory using organizational principles from the CTSA recommendations. The consulting model was implemented over a period of 3.5 years. During this time, the team tracked the number of new project requests and investigator feedback. They also documented the organizational structure and service delivery processes. Data collection included both quantitative metrics and qualitative feedback from users. The study evaluated whether the CTSA framework could be successfully integrated into a student-led model.

The consulting laboratory received nearly one new project request per week over the study period. This demonstrated a high level of service demand and capacity. Investigators provided positive feedback on the quality of statistical support received. The organizational structure aligned with CTSA guidelines was successfully implemented. The team observed that the guidelines were adaptable to a student-led environment. The study found that graduate students could provide professional-level statistical services. The feedback suggested that the consulting model met the expectations of clinical investigators. The results indicated that CTSA recommendations can be effectively applied in training-focused settings.

The authors concluded that CTSA guidelines for statistical consulting services can be successfully adapted to graduate-led models. The study demonstrated that these recommendations are applicable even in training-focused environments. The consulting laboratory met high service demand and received positive investigator feedback. The results suggest that student-led consulting can align with professional standards. The authors propose that these findings can inform the development of similar programs. They suggest that graduate consulting laboratories can serve both educational and service roles. The study's outcomes support the feasibility of applying CTSA recommendations in student-led settings. The authors recommend further exploration of how these guidelines can be optimized for training environments.