226 research outputs found

    New Rights and Remedies: The Federal Crime Victims\u27 Rights Act of 2004

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    Proposed Maryland Jury Instructionon Cross-Racial Identification

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    Proposed Maryland Jury Instructionon Cross-Racial Identification

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    Statement of David E. Aaronson in Support of HB 1075 to Repeal the Death Penalty

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    The Grizzly, April 27, 1979

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    Honorary Degrees Given to Speakers: College to Graduate 272 at Commencement • Anti-nuclear Crowd Rallies at Limerick • Middle States Visitation Completed • Grosh Wins Award • Comment: Defrost Frozen Rooms; No Deans in Quad; Pay for Wismer • Letters to the Editor: Wilson Rebutted; Why APO Won; Inaccuracy; Students\u27 Fault; POD Responds; Clouser Revisited • Roving Reporter: Who Should be Ugly Man? • Security Change • Breakfast in America: Supertramp\u27s Masterwork • Wismer Eggs Never Break • Well Flung Spring Fling • Men\u27s Lacrosse Falls Hard • News in Brief: Espadas Receives Grant; College Hosts Prospectives; Zucker Premiers Composition • Paradise Lost: A Dump for All Seasons • Linksmen Victorious • Court Aces Down Foes • Marathon Men • Lacrosse Continues Winning Streak • Women\u27s Tennis Up and Down • Bears Fall to Widener • Cindermen Rip Uphttps://digitalcommons.ursinus.edu/grizzlynews/1019/thumbnail.jp

    Increasing recruitment to randomised trials: a review of randomised controlled trials

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    BACKGROUND: Poor recruitment to randomised controlled trials (RCTs) is a widespread and important problem. With poor recruitment being such an important issue with respect to the conduct of randomised trials, a systematic review of controlled trials on recruitment methods was undertaken in order to identify strategies that are effective. METHODS: We searched the register of trials in Cochrane library from 1996 to end of 2004. We also searched Web of Science for 2004. Additional trials were identified from personal knowledge. Included studies had to use random allocation and participants had to be allocated to different methods of recruitment to a 'real' randomised trial. Trials that randomised participants to 'mock' trials and trials of recruitment to non-randomised studies (e.g., case control studies) were excluded. Information on the study design, intervention and control, and number of patients recruited was extracted by the 2 authors. RESULTS: We identified 14 papers describing 20 different interventions. Effective interventions included: telephone reminders; questionnaire inclusion; monetary incentives; using an 'open' rather than placebo design; and making trial materials culturally sensitive. CONCLUSION: Few trials have been undertaken to test interventions to improve trial recruitment. There is an urgent need for more RCTs of recruitment strategies

    Estimation of minimally important differences in EQ-5D utility and VAS scores in cancer

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    <p>Abstract</p> <p>Background</p> <p>Understanding what constitutes an important difference on a HRQL measure is critical to its interpretation. The aim of this study was to provide a range of estimates of minimally important differences (MIDs) in EQ-5D scores in cancer and to determine if estimates are comparable in lung cancer.</p> <p>Methods</p> <p>A retrospective analysis was conducted on cross-sectional data collected from 534 cancer patients, 50 of whom were lung cancer patients. A range of minimally important differences (MIDs) in EQ-5D index-based utility (UK and US) scores and VAS scores were estimated using both anchor-based and distribution-based (1/2 standard deviation and standard error of the measure) approaches. Groups were anchored using Eastern Cooperative Oncology Group performance status (PS) ratings and FACT-G total score-based quintiles.</p> <p>Results</p> <p>For UK-utility scores, MID estimates based on PS ranged from 0.10 to 0.12 both for all cancers and for lung cancer subgroup. Using FACT-G quintiles, MIDs were 0.09 to 0.10 for all cancers, and 0.07 to 0.08 for lung cancer. For US-utility scores, MIDs ranged from 0.07 to 0.09 grouped by PS for all cancers and for lung cancer; when based on FACT-G quintiles, MIDs were 0.06 to 0.07 in all cancers and 0.05 to 0.06 in lung cancer. MIDs for VAS scores were similar for lung and all cancers, ranging from 8 to 12 (PS) and 7 to 10 (FACT-G quintiles).</p> <p>Discussion</p> <p>Important differences in EQ-5D utility and VAS scores were similar for all cancers and lung cancer, with the lower end of the range of estimates closer to the MID, i.e. 0.08 for UK-index scores, 0.06 for US-index scores, and 0.07 for VAS scores.</p
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