Literature DB >> 2727471

A two-stage trial design for testing treatment, self-selection and treatment preference effects.

G Rücker1.   

Abstract

We propose a two-stage randomized clinical trial design for separating treatment effects from those resulting from choosing treatment. At the first stage all patients are randomly allocated to one of two groups, the random group and the option group. At the second stage, patients in the random group are randomized a second time to treatment A or B, whereas patients in the option group are given a free choice between the two treatments. If there are differences in treatment response between the random group and the option group, there are two potential sources of bias: self-selection by choosing treatment, and effects of suggestion by receiving the preferred treatment. A linear model is presented to estimate these effects separately along with test statistics which are approximately normally distributed.

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Year:  1989        PMID: 2727471     DOI: 10.1002/sim.4780080411

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  27 in total

1.  Preferences and understanding their effects on health.

Authors:  K McPherson; A Britton
Journal:  Qual Health Care       Date:  2001-09

2.  Patients, preferences, and evidence.

Authors:  L Smeeth
Journal:  West J Med       Date:  2001-05

3.  What influences participants' treatment preference and can it influence outcome? Results from a primary care-based randomised trial for shoulder pain.

Authors:  Elaine Thomas; Peter R Croft; Susan M Paterson; Krysia Dziedzic; Elaine M Hay
Journal:  Br J Gen Pract       Date:  2004-02       Impact factor: 5.386

4.  Design and methods of "diaBEAT-it!": a hybrid preference/randomized control trial design using the RE-AIM framework.

Authors:  Fabio A Almeida; Kimberlee A Pardo; Richard W Seidel; Brenda M Davy; Wen You; Sarah S Wall; Erin Smith; Mark H Greenawald; Paul A Estabrooks
Journal:  Contemp Clin Trials       Date:  2014-06-21       Impact factor: 2.226

Review 5.  Effectiveness of psychological treatments for depressive disorders in primary care: systematic review and meta-analysis.

Authors:  Klaus Linde; Kirsten Sigterman; Levente Kriston; Gerta Rücker; Susanne Jamil; Karin Meissner; Antonius Schneider
Journal:  Ann Fam Med       Date:  2015 Jan-Feb       Impact factor: 5.166

6.  Low-level laser therapy for weight reduction: a randomized pilot study.

Authors:  Ivana T Croghan; Ryan T Hurt; Darrell R Schroeder; Shawn C Fokken; Michael D Jensen; Matthew M Clark; Jon O Ebbert
Journal:  Lasers Med Sci       Date:  2019-08-31       Impact factor: 3.161

7.  Preference option randomized design (PORD) for comparative effectiveness research: Statistical power for testing comparative effect, preference effect, selection effect, intent-to-treat effect, and overall effect.

Authors:  Moonseong Heo; Paul Meissner; Alain H Litwin; Julia H Arnsten; M Diane McKee; Alison Karasz; Paula McKinley; Colin D Rehm; Earle C Chambers; Ming-Chin Yeh; Judith Wylie-Rosett
Journal:  Stat Methods Med Res       Date:  2017-11-09       Impact factor: 3.021

8.  Effects of treatment, choice, and preference on health-related quality-of-life outcomes in patients with posttraumatic stress disorder (PTSD).

Authors:  Quang A Le; Jason N Doctor; Lori A Zoellner; Norah C Feeny
Journal:  Qual Life Res       Date:  2018-03-14       Impact factor: 4.147

Review 9.  Effect of Treatment Preference in Randomized Controlled Trials: Systematic Review of the Literature and Meta-Analysis.

Authors:  Dimittri Delevry; Quang A Le
Journal:  Patient       Date:  2019-12       Impact factor: 3.883

10.  Massage Compared with Massage Plus Acupuncture for Breast Cancer Patients Undergoing Reconstructive Surgery.

Authors:  Christina A Dilaveri; Ivana T Croghan; Molly J Mallory; Liza J Dion; Karen M Fischer; Darrell R Schroeder; Jorys Martinez-Jorge; Minh-Doan T Nguyen; Shawn C Fokken; Brent A Bauer; Dietlind L Wahner-Roedler
Journal:  J Altern Complement Med       Date:  2020-07       Impact factor: 2.579

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