1. Evidence → Social RCTs → Transformational change More progress toward evidence-based social programs. The Laura and John Arnold foundation expanded its funding of low-cost randomized controlled trials. @LJA_Foundation, an advocate for evidence-based, multidisciplinary approaches, has committed $100,000+ for all RCT proposals satisfying its RFP criteria and earning a high rating from its expert review panel.
2. Stakeholder input → Evidence-based health guidelines Canada’s Agency for Drugs and Technologies in Health seeks stakeholder input for its Guidelines for the Economic Evaluation of Health Technologies. The @CADTH_ACMTS guidelines detail best practices for conducting economic evaluations and promote the use of high-quality economic evidence in policy, practice, and reimbursement decision-making.
3. Research evidence → Standards → Mentoring effectiveness At the National Mentoring Summit (January 27, Washington DC), practitioners, researchers, corporate partners, and civic leaders will review how best to incorporate research evidence into practice standards for youth mentoring. Topics at #MentoringSummit2016 include benchmarks for different program models (e.g., school-based, group, e-mentoring) and particular populations (e.g.,youth in foster care, children of incarcerated parents).
4. Feature creep → Too many choices → Decision fatigue Hoa Loranger at Nielsen Norman Group offers an insightful explanation of how Simplicity Wins Over Abundance of Choice in user interface design. “The paradox is that consumers are attracted to a large number of choices and may consider a product more appealing if it has many capabilities, but when it comes to making decisions and actually using the product, having fewer options makes it easier for people to make a selection.” Thanks to @LoveStats.
5. Hot hand → Home run → Another home run? Evidence of a hot hand in baseball? Findings published on the Social Science Research Network suggest that “recent performance is highly significant in predicting performance…. [A] batter who is ‘hot’ in home runs is 15-25% more likely… to hit a home run in his next at bat.” Not so fast, says @PhilBirnbaum on his Sabermetric blog, saying that the authors’ “regression coefficient confounds two factors – streakiness, and additional evidence of the players’ relative talent.”