Cluster-Randomized Trials: Methodical and Practical Implications

被引:0
|
作者
Dreyhaupt, Jens [1 ]
Mayer, Benjamin [1 ]
Kaluscha, Rainer [2 ]
Muche, Rainer [1 ]
机构
[1] Univ Ulm, Inst Epidemiol & Med Biometrie, Schwabstr 13, D-89075 Ulm, Germany
[2] Univ Ulm, Inst Rehabil Med Forsch, Ulm, Germany
关键词
cluster randomization; structural equivalence; rehabilitation research; sample size calculation; statistical analysis;
D O I
10.1055/a-0801-5697
中图分类号
R49 [康复医学];
学科分类号
100215 ;
摘要
Quite often critics demand more randomized studies in rehabilitation science to gather methodological evidence of high quality. However, it is also recognized that the design of double-blind, placebo-controlled, randomized studies often cannot simply be transferred into rehabilitation science. Validity concerning the health care is here in the focus. Thus, treatment as-usual is mostly used as placebo treatment and double-blinding is partly not definable. Additionally, it is often difficult to offer 2 similar forms of treatment in one rehabilitation hospital due to lack of capacity. Additionally, contamination effects are to be expected when patients of different study arms communicate. Here cluster-randomized studies may be helpful. However, in comparison to individual randomized studies they need often higher sample sizes, a more complex methodology of sample size calculation as well as extensive methods of statistical analysis. Within this article advantages and disadvantages as well as the characteristics of cluster randomization are described and information is given how they can be implemented into the field of rehabilitation science.
引用
收藏
页码:54 / 61
页数:8
相关论文
共 50 条
  • [41] Power Analysis in Social Work Intervention Research: Designing Cluster-Randomized Trials
    Rose, Roderick A.
    Bowen, Gary L.
    [J]. SOCIAL WORK RESEARCH, 2009, 33 (01) : 43 - 52
  • [42] Illustrating problems faced by stroke researchers: a review of cluster-randomized controlled trials
    Sutton, Christopher J.
    Watkins, Caroline L.
    Dey, Paola
    [J]. INTERNATIONAL JOURNAL OF STROKE, 2013, 8 (07) : 566 - 574
  • [43] Reducing contamination risk in cluster-randomized infectious disease-intervention trials
    McCann, Robert S.
    van den Berg, Henk
    Takken, Willem
    Chetwynd, Amanda G.
    Giorgi, Emanuele
    Terlouw, Dianne J.
    Diggle, Peter J.
    [J]. INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 2018, 47 (06) : 2015 - 2024
  • [44] Analysis of cluster randomized trials in primary care: a practical approach
    Campbell, MK
    Mollison, J
    Steen, N
    Grimshaw, JM
    Eccles, M
    [J]. FAMILY PRACTICE, 2000, 17 (02) : 192 - 196
  • [45] Practical considerations for sample size calculation for cluster randomized trials
    Leyrat, Clemence
    Eldridge, Sandra
    Taljaard, Monica
    Hemming, Karla
    [J]. JOURNAL OF EPIDEMIOLOGY AND POPULATION HEALTH, 2024, 72 (01):
  • [46] A Practical Guide to Cluster Randomized Trials in School Health Research
    Goesling, Brian
    [J]. JOURNAL OF SCHOOL HEALTH, 2019, 89 (11) : 916 - 925
  • [47] Standardized mean differences in individually-randomized and cluster-randomized trials, with applications to meta-analysis
    White, IR
    Thomas, J
    [J]. CLINICAL TRIALS, 2005, 2 (02) : 141 - 151
  • [48] Universal Prevention for Anxiety and Depressive Symptoms in Children: A Meta-analysis of Randomized and Cluster-Randomized Trials
    Ahlen, Johan
    Lenhard, Fabian
    Ghaderi, Ata
    [J]. JOURNAL OF PRIMARY PREVENTION, 2015, 36 (06): : 387 - 403
  • [49] Universal Prevention for Anxiety and Depressive Symptoms in Children: A Meta-analysis of Randomized and Cluster-Randomized Trials
    Johan Ahlen
    Fabian Lenhard
    Ata Ghaderi
    [J]. The Journal of Primary Prevention, 2015, 36 : 387 - 403
  • [50] A mixed model approach to estimate the survivor average causal effect in cluster-randomized trials
    Wang, Wei
    Tong, Guangyu
    Hirani, Shashivadan P.
    Newman, Stanton P.
    Halpern, Scott D.
    Small, Dylan S.
    Li, Fan
    Harhay, Michael O.
    [J]. STATISTICS IN MEDICINE, 2024, 43 (01) : 16 - 33