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Beverly Cove, MA, United States

Endicott College is a private coeducational college located in Beverly, Massachusetts. Wikipedia.

Kelley J.M.,Harvard University | Kelley J.M.,Endicott College | Kraft-Todd G.,Harvard University | Schapira L.,Harvard University | And 5 more authors.
PLoS ONE | Year: 2014

Objective: To determine whether the patient-clinician relationship has a beneficial effect on either objective or validated subjective healthcare outcomes. Design: Systematic review and meta-analysis. Data Sources: Electronic databases EMBASE and MEDLINE and the reference sections of previous reviews. Eligibility Criteria for Selecting Studies: Included studies were randomized controlled trials (RCTs) in adult patients in which the patient-clinician relationship was systematically manipulated and healthcare outcomes were either objective (e.g., blood pressure) or validated subjective measures (e.g., pain scores). Studies were excluded if the encounter was a routine physical, or a mental health or substance abuse visit; if the outcome was an intermediate outcome such as patient satisfaction or adherence to treatment; if the patient-clinician relationship was manipulated solely by intervening with patients; or if the duration of the clinical encounter was unequal across conditions. Results: Thirteen RCTs met eligibility criteria. Observed effect sizes for the individual studies ranged from d = -.23 to .66. Using a random-effects model, the estimate of the overall effect size was small (d = .11), but statistically significant (p = .02). Conclusions: This systematic review and meta-analysis of RCTs suggests that the patient-clinician relationship has a small, but statistically significant effect on healthcare outcomes. Given that relatively few RCTs met our eligibility criteria, and that the majority of these trials were not specifically designed to test the effect of the patient-clinician relationship on healthcare outcomes, we conclude with a call for more research on this important topic. © 2014 Kelley et al.

Kam-Hansen S.,Beth Israel Deaconess Medical Center | Jakubowski M.,Beth Israel Deaconess Medical Center | Kelley J.M.,Endicott College | Kelley J.M.,Harvard University | And 5 more authors.
Science Translational Medicine | Year: 2014

Information provided to patients is thought to influence placebo and drug effects. In a prospective, withinsubjects, repeated-measures study of 66 subjects with episodic migraine, we investigated how variations in medication labeling modified placebo and drug effects. An initial attack with no treatment served as a control. In six subsequent migraine attacks, each participant received either placebo or Maxalt (10-mg rizatriptan) administered under three information conditions ranging from negative to neutral to positive (told placebo, told Maxalt or placebo, told Maxalt) (N = 459 documented attacks). Treatment order was randomized. Maxalt was superior to placebo for pain relief. When participants were given placebo labeled as (i) placebo, (ii) Maxalt or placebo, and (iii) Maxalt, the placebo effect increased progressively. Maxalt had a similar progressive boost when labeled with these three labels. The efficacies of Maxalt labeled as placebo and placebo labeled as Maxalt were similar. The efficacy of open-label placebo was superior to that of no treatment. Relative to no treatment, the placebo, under each information condition, accounted for more than 50% of the drug effect. Increasing "positive" information incrementally boosted the efficacy of both placebo and medication during migraine attacks. The benefits of placebo persisted even if placebo was honestly described. Whether treatment involves medication or placebo, the information provided to patients and the ritual of pill taking are important components of care.

Livingstone R.M.,Endicott College
Social Science Computer Review | Year: 2016

Through examining established and evolving conceptions of intelligence across natural and social science and applying them to Wikipedia, this article argues that the world’s largest encyclopedia and broadest implementation of the wiki is an online instance of collective intelligence (CI), as it fits key models for this concept. Further, by relying on sociotechnical ensembles of human intelligence, programmed bots, social bureaucracy, and software protocols, a more humanistic CI, as proposed by Lévy, is realized in a virtual knowledge space that embodies information as both product and process while empowering its community to explore the cultural possibilities of its collectivism. © 2015, © The Author(s) 2015.

Livingstone R.M.,Endicott College
First Monday | Year: 2016

Software robots ("bots") play a major role across the Internet today, including on Wikipedia, the world's largest online encyclopedia. Bots complete over 20 percent of all edits to the project, yet often their work goes unnoticed by other users. Their initial integration onto Wikipedia was not uncontested and highlighted the opposing philosophies of "inclusionists" and "deletionists" who influenced the early years of the project. This paper presents an in-depth interview with Wikipedia user Ram-Man, an early bot operator on the site and creator or the rambot, the first mass-editing bot. Topics discussed include the social and technical climate of early Wikipedia, the creation of bot policies and bureaucracy, and the legacy of rambot and Ram-Man's work. © First Monday, 1995-2016.

Kelley J.M.,Endicott College | Kelley J.M.,Harvard University | Kaptchuk T.J.,Beth Israel Deaconess Medical Center
Contemporary Clinical Trials | Year: 2010

The randomized controlled trial (RCT) is the gold standard for assessing the efficacy of medical treatments. Over the past 50. years, RCT methodology has proven to be quite successful in identifying effective treatments and weeding out ineffective ones, thus transforming medicine from an intuitive art into an empirical science. However, the enormous success of the RCT has inadvertently contributed to a common inferential error that is insufficiently appreciated by some clinicians and researchers. Although RCTs can effectively distinguish between placebo and active treatment effects at the level of the group, contrary to intuition, this same disentanglement is much more difficult to achieve at the level of the individual. For individual patients it is surprisingly difficult to determine who is a treatment responder and who is not. Using data from a recent RCT, we illustrate the problem and detail its negative effects for research and clinical practice. Finally, we suggest strategies for minimizing these negative effects. © 2010 Elsevier Inc.

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