Effectiveness of a healthy lifestyle intervention for low back pain and osteoarthritis of the knee: protocol and statistical analysis plan for two randomised controlled trials

• Autor(a) principal: O’Brien,Kate M.
• Data de Publicação: 2016
• Outros Autores: Williams,Amanda, Wiggers,John, Wolfenden,Luke, Yoong,Serene, Campbell,Elizabeth, Kamper,Steven J., McAuley,James, Attia,John, Oldmeadow,Chris, Williams,Christopher M.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Brazilian Journal of Physical Therapy
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-35552016000500477
• topic: low back pain; knee osteoarthritis; lifestyle; telephone; randomised controlled trial; statistical analysis plan

ABSTRACT Background These trials are the first randomised controlled trials of telephone-based weight management and healthy lifestyle interventions for low back pain and knee osteoarthritis. This article describes the protocol and statistical analysis plan. Method These trials are parallel randomised controlled trials that investigate and compare the effect of a telephone-based weight management and healthy lifestyle intervention for improving pain intensity in overweight or obese patients with low back pain or knee osteoarthritis. The analysis plan was finalised prior to initiation of analyses. All data collected as part of the trial were reviewed, without stratification by group, and classified by baseline characteristics, process of care and trial outcomes. Trial outcomes were classified as primary and secondary outcomes. Appropriate descriptive statistics and statistical testing of between-group differences, where relevant, have been planned and described. Conclusions A protocol for standard analyses was developed for the results of two randomised controlled trials. This protocol describes the data, and the pre-determined statistical tests of relevant outcome measures. The plan demonstrates transparent and verifiable use of the data collected. This a priori protocol will be followed to ensure rigorous standards of data analysis are strictly adhered to.