Contamination in trials of educational interventions

Objectives: To consider the effects of contamination on the magnitude and statistical significance (or precision) of the estimated effect of an educational intervention, to investigate the mechanisms of contamination, and to consider how contamination can be avoided. Data sources: Major electronic databases were searched up to May 2005. Methods: An exploratory literature search was conducted. The results of trials included in previous relevant systematic reviews were then analysed to see whether studies that avoided contamination resulted in larger effect estimates than those that did not. Experts’ opinions were elicited about factors more or less likely to lead to contamination. We simulated contamination processes to compare contamination biases between cluster and individually randomised trials. Statistical adjustment was made for contamination using Complier Average Causal Effect analytic methods, using published and simulated data. The bias and power of cluster and individually randomised trials were compared, as were Complier Average Causal Effect, intention-to-treat and per protocol methods of analysis. Results: Few relevant studies quantified contamination. Experts largely agreed on where contamination was more or less likely. Simulation of contamination processes showed that, with various combinations of timing, intensity and baseline dependence of contamination, cluster randomised trials might produce biases greater than or similar to those of individually randomised trials. Complier Average Causal Effect analyses produced results that were less biased than intention-to-treat or per protocol analyses. They also showed that individually randomised trials would in most situations be more powerful than cluster randomised trials despite contamination. Conclusions: The probability, nature and process of contamination should be considered when designing and analysing controlled trials of educational interventions in health. Cluster randomisation may or may not be appropriate and should not be uncritically assumed always to be a solution. Complier Average Causal Effect models are an appropriate way to adjust for contamination if it can be measured. When conducting such trials in future, it is a priority to report the extent, nature and effects of contamination.We are grateful to the National Health Service Research and Development National Coordinating Centre for Research Methodology for funding this research

Illness Beliefs Predict Mortality in Patients with Diabetic Foot Ulcers

Background - Patients’ illness beliefs have been associated with glycaemic control in diabetes and survival in other conditions. Objective - We examined whether illness beliefs independently predicted survival in patients with diabetes and foot ulceration. Methods - Patients (n = 169) were recruited between 2002 and 2007. Data on illness beliefs were collected at baseline. Data on survival were extracted on 1st November 2011. Number of days survived reflected the number of days from date of recruitment to 1st November 2011. Results - Cox regressions examined the predictors of time to death and identified ischemia and identity beliefs (beliefs regarding symptoms associated with foot ulceration) as significant predictors of time to death. Conclusions - Our data indicate that illness beliefs have a significant independent effect on survival in patients with diabetes and foot ulceration. These findings suggest that illness beliefs could improve our understanding of mortality risk in this patient group and could also be the basis for future therapeutic interventions to improve survival

Deprivation and Variations in Teenage Conceptions in Abortions in England

There are substantial variations between local authorities in the conception rate of teenagers and the proportion of these that end in abortion. This study builds two deprivation models that explain part of the variation in conceptions and abortions. It then identifies outliers, local authorities with teenage conception and abortion rates that are above or below those predicted by the model. It is suggested that the local authorities with lower than expected conceptions are the ones to look to when seeking to discover how to prevent teenage conceptions and those with higher than expected abortion rates may have abortion services that are more accessible. In general, spatial comparisons of conceptions and abortion should take into account variations in deprivation

Deprivation and Variations in Teenage Conceptions in Abortions in England

There are substantial variations between local authorities in the conception rate of teenagers and the proportion of these that end in abortion. This study builds two deprivation models that explain part of the variation in conceptions and abortions. It then identifies outliers, local authorities with teenage conception and abortion rates that are above or below those predicted by the model. It is suggested that the local authorities with lower than expected conceptions are the ones to look to when seeking to discover how to prevent teenage conceptions and those with higher than expected abortion rates may have abortion services that are more accessible. In general, spatial comparisons of conceptions and abortion should take into account variations in deprivation

The use of unequal randomisation ratios in clinical trials: a review

OBJECTIVE To examine reasons given for the use of unequal randomisation in randomised controlled trials (RCTs). MAIN MEASURES Setting of the trial; intervention being tested; randomisation ratio; sample size calculation; reason given for randomisation. METHODS Review of trials using unequal randomisation. DATABASES AND SOURCES Cochrane library, Medline, Pub Med and Science Citation Index. RESULTS A total of 65 trials were identified; 56 were two-armed trials and nine trials had more than two arms. Of the two-arm trials, 50 trials recruited patients in favour of the experimental group. Various reasons for the use of unequal randomisation were given. Six studies stated that they used unequal randomisation to reduce the cost of the trial, with one screening trial limited by the availability of the intervention. Other reasons for using unequal allocation were: avoiding loss of power from drop-out or cross-over, ethics and the gaining of additional information on the treatment. Thirty seven trials papers (57%) did not state why they had used unequal randomisation and only 14 trials (22%) appeared to have taken the unequal randomisation into account in their sample size calculation. CONCLUSION Although unequal randomisation offers a number of advantages to trials the method is rarely used and is especially under-utilised to reduce trial costs. Unequal randomisation should be considered more in trial design especially where there are large differences between treatment costs

Is an intervention using computer software effective in literacy learning? A randomised controlled trial.

BACKGROUND: computer software is widely used to support literacy learning. There are few randomised trials to support its effectiveness. Therefore, there is an urgent need to rigorously evaluate computer software that supports literacy learning. METHODS: we undertook a pragmatic randomised controlled trial among pupils aged 11-12 within a single state comprehensive school in the North of England. The pupils were randomised to receive 10 hours of literacy learning delivered via laptop computers or to act as controls. Both groups received normal literacy learning. A pre-test and two post-tests were given in spelling and literacy. The main pre-defined outcome was improvements in spelling scores. RESULTS: 155 pupils were randomly allocated, 77 to the ICT group and 78 to control. Four pupils left the school before post-testing and 25 pupils did not have both pre- and post-test data. Therefore, 63 and 67 pupils were included in the main analysis for the ICT and control groups respectively. After adjusting for pre-test scores there was a slight increase in spelling scores, associated with the ICT intervention, but this was not statistically significant (0.954, 95% confidence interval (CI) - 1.83 to 3.74, p = 0.50). For reading scores there was a statistically significant decrease associated with the ICT intervention (-2.33, 95% CI -0.96 to -3.71, p = 0.001). CONCLUSIONS: we found no evidence of a statistically significant benefit on spelling outcomes using a computer program for literacy learning. For reading there seemed to be a reduction in reading scores associated with the use of the program. All new literacy software needs to be tested in a rigorous trial before it is used routinely in schools

Psychosocial factors associated with indices of cortisol production in women with breast cancer and controls

The present study was designed to (i) explore which psychosocial factors were associated with indices representing the early morning peak, diurnal cortisol rhythm and area under the curve (AUC); (ii) examine whether the relationships between psychosocial functioning and these cortisol indices were consistent and (iii) explore whether these relationships were influenced by the clinical status of the participant. Newly diagnosed breast cancer patients (n = 85) and healthy control women (n=59) were recruited. State and trait measures of psychosocial functioning (i.e. anxiety, depression, distress, neuroticism, extraversion, marital satisfaction and mastery) were undertaken. In addition, all participants provided four saliva samples (on waking, 30 min later, between 11 and 1 p.m., before lunch and between 8 and 10 p.m., at Least 2 h after evening meal) over two consecutive days to assess cortisol levels. The results highlighted the divergent nature of the four cortisol indices; revealed the presence of some significant relationships between the psychosocial. measures and the cortisol. indices; but highlighted inconsistencies in the relationships evident for patients and those observed for control women. (C) 2005 Elsevier Ltd. All rights reserved