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| Content Provider | ACM Digital Library |
|---|---|
| Author | Chandra, Manasi-Sheth Gore, Ross |
| Abstract | Our PArticipant-centered Clinical Trial (PACT) Framework is a new approach to the design and analysis of clinical trials in the behavioral, social and health sciences. The PACT Framework is based on the idea that data can be privately maintained by participants and never revealed to researchers, while still enabling statistical models to be fit and scientific hypotheses tested. PACT rests on the assumption that clinical trial data should belong to, be controlled by, and remain in the possession of participants. Since data have value, individuals can thus accumulate personal wealth by participating in science. The innovation of the PACT Framework is that statistical models are fit by sending an objective function and vector of parameters to each participants' personal device (e.g., smart-phone), where the likelihood of that individual's data is calculated locally. Only the likelihood value is returned to the central optimizer. The optimizer aggregates likelihood values from all participants and chooses new parameters until the model converges. The PACT Framework solves or simplifies many current problems that plague human participant clinical trials. A PACT study provides significantly greater privacy for participants; automatic management of opt-in and opt-out consent; lower cost for the researcher and funding institute; a larger base of participants; and faster determination of results. PACT facilitates the use of mobile devices that can enable many trials to be performed while participants remain in their normal living environments, thus opening new paths in the way one thinks about research methods. Furthermore, if a participant opts into many clinical trials simultaneously, all of the studies could automatically have access to individual-level longitudinal data sharing. |
| Starting Page | 1 |
| Ending Page | 6 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781510810594 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-07-26 |
| Publisher Place | San Diego |
| Access Restriction | Subscribed |
| Subject Keyword | Data privacy Statistical modeling Clinical trials |
| Content Type | Text |
| Resource Type | Article |
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