Developmental Evaluation in Practice: Lessons from Evaluating a Market-Based Employment Initiative

Developmental evaluation (DE) has emerged as an approach that is well suited to evaluating innovative early-stage or market-based initiatives that address complex social issues. However, because DE theory and practice are still evolving, there are relatively few examples of its implementation on the ground. This paper reviews the practical experience of a monitoring and evaluation (M&E) team in conducting a developmental evaluation of a Rockefeller Foundation initiative in the field of digital employment for young people, and offers observations and advice on applying developmental evaluation in practice.Through its work with The Rockefeller Foundation's team and its grantees, the M&E team drew lessons relating to context, intentional learning, tools and processes, trust and communication, and adaption associated with developmental evaluation. It was found that success depends on commissioning a highly qualified DE team with interpersonal and communication skills and, whenever possible, some sectoral knowledge. The paper also offers responses to three major criticisms frequently leveled against developmental evaluation, namely that it displaces other types of evaluations, is too focused on "soft" methods and indicators, and downplays accountability.Through its reporting of lessons learned and its response to the challenges and shortcomings of developmental evaluation, the M&E team makes the case for including developmental evaluation as a tool for the evaluation toolbox, recommending that it be employed across a wide range of geographies and sectors. With its recommendation, it calls for future undertakings to experiment with new combinations of methods within the DE framework to strengthen its causal, quantitative, and accountability dimensions

Evaluating Interprofessional Competencies and Knowledge of and Confidence in Addressing Social Determinants of Health

Promoting health requires coordinated, team-based interventions responsive to multiple determinants of health. This study aimed to determine if interprofessional competencies and knowledge of and confidence in addressing the social determinants of health improved following an interprofessional learning event. A two-group randomized controlled trial was used to determine study outcomes among 408 health science students from 14 health profession programs in the Midwest. Formed groups were randomly assigned to the customary medical-based (control) or social determinants of health focused (experimental) case study. In small groups students engaged in a case study simulation and offered recommendations for intervention. Small improvements in knowledge of the social determinants of health were found among participants in both groups. Interprofessional competencies largely showed no significant differences between using the case study which emphasized social determinants of health compared to a medically based case study. The suggestions for interventions resulted in more frequent recommendations related to socioeconomic status and access to health care among students in the experimental group versus the recommendation of medically based health services among students in the control group. Additional qualitative research is recommended to learn more about how groups collaborated to form these recommendations

Clinical Decision-Making for Discharge Recommendations for a 63 Year Old Male with Foot Drop Status Post Great Toe Amputation: A Case Report

Background and Purpose: Making a discharge recommendation from an acute care setting involves many factors and a coordinated team effort, and discharging a patient to an inappropriate setting can have adverse effects. Physical therapists have shown to be able to make appropriate and accurate discharge recommendations. The purpose of this case report is to apply a model of discharge decision making and analyze the results in the case of an older adult male with foot drop status post great toe amputation. Case Description: SF was a 63-year old male with a history of Type II diabetes mellitus, alcohol abuse, and cerebrovascular attack. He was seen in acute care status post left great toe amputation. Approach: Clinical decision-making in discharge planning was based on his function and disability, wants and needs, ability to participate, and life context. Information was analyzed in light of therapist experience, health care regulations, and opinions of medical team members. SF was recommended to be discharged to a subacute rehabilitation facility. Discussion: Although the patient’s personal wants were not consistent with the other three constructs, the physical therapists were able to exercise skilled clinical reasoning to recommend the appropriate discharge setting through the use of the implemented model of discharge decision making. Further studies are needed to establish the model’s validity and reliability

Detailed empirical studies of student information storing in the context of distributed design team-based project work

This paper presents the findings of six empirical case studies investigating the information stored by engineering design students in distributed team-based Global Design Projects. The aim is to understand better how students store distributed design information in order to prepare them for work in today‟s international and global context. This paper outlines the descriptive element of the work, the qualitative and quantitative research methods used and the results. It discusses the issues around the emergent themes of information storing; information storing systems; information storing patterns; and information strategy, making recommendations; establishing that there is a need for more prescriptive measures to supporting distributed design information management. This work will be of great value to industry also

Replacing the Irreplaceable: Fast Algorithms for Team Member Recommendation

In this paper, we study the problem of Team Member Replacement: given a team of people embedded in a social network working on the same task, find a good candidate who can fit in the team after one team member becomes unavailable. We conjecture that a good team member replacement should have good skill matching as well as good structure matching. We formulate this problem using the concept of graph kernel. To tackle the computational challenges, we propose a family of fast algorithms by (a) designing effective pruning strategies, and (b) exploring the smoothness between the existing and the new team structures. We conduct extensive experimental evaluations on real world datasets to demonstrate the effectiveness and efficiency. Our algorithms (a) perform significantly better than the alternative choices in terms of both precision and recall; and (b) scale sub-linearly.Comment: Initially submitted to KDD 201