This cluster randomisation study will evaluate the effectiveness of online training course, targeted to unit leaders. The intervention will be delivered at the level of the cluster, i.e. professionals within clusters (education of unit leaders). Cluster randomisation study fits our purposes because our intention is to enhance the application of evidence by entire unit teams; the whole groups of collections of individuals in ward units are randomly assigned to receive educational intervention in groups, referred to as clusters.
This cluster trial will be conducted in two Finnish Wellbeing Services counties in southern Finland. The target group of study are unit leaders working in social and health care sector in a managerial position.
The units will be randomised into two groups: evidence-based leadership training (experimental group) or passive control group. The participants in the experimental group will join a seven months online course aiming to improve the evidence-based leadership competences.
All eligible unit leaders who have shown their interest to participate the study will receive an invitation email from the contact person of the study (the Chief Executive Officer). The email will include a link to study information and electronic informed consent in the Research Electronic Data Capture tool (REDCap). After given an electronic informed consent, the REDCap will lead to a baseline survey (background information of the participants of the specific units, baseline data). Unit leaders will be allocated into the study group as their unit.
All staff members who are working in the same unit with the unit leaders will be invited to join the study. First, staff members will receive an invitation email (sent by a Contact person) to explain the purpose of the study and its practical arrangements. If the staff member is willing to join the study, she or he will give an electronic content (REDCap) and respond to electronic surveys - but they do not join online training. After filling electronic forms, each staff members will be allocated into the same study group as their unit.
The outcomes are targeted to evaluate the effectiveness of the evidence-based online course on individual, team, and organisational level. The data will be formed based on characteristics of the unit and its participants, outcome data, course feedback, and feasibility data of the online training course. The primary endpoint with respect to effectiveness of the training course are an improvement in EBP from baseline to follow-up (month 7), measured immediately after the intervention using electronic survey administered to the unit leaders and staff.
The analysis will be carried out on an intent-to-treat (ITT) basis. Assumptions of normality of the residuals will be investigated. The characteristics of the units and respondents (staff members) will be summarized with descriptive statistics for each group. All individuals within the cluster will be included in the trial. In the sample size calculation, a clustering effect was assumed and accounted as the ICC coefficient. For data analysis the mixed effects model or two-level multilevel models that take into account clustering effects will be used. In the model analysis, the variation in the outcomes among clusters will be estimated and tested for its significance. The intra-cluster coefficient (ICC) will be reported. The overall efficacy of the outcomes will be estimated after taking into account the clustering effects. A descriptive summary of the baseline information for both clusters and individuals will be presented first as tables of summary data. Sensitivity analyses will be conducted on units in which participation in online training was low to evaluate whether intervention fidelity has any effect to the results of the primary outcome. Results will be expressed using rate ratios, odds ratios, or least-squares mean differences with corresponding 95% CIs, depending on the type of outcome. The intracluster (or intraclass) correlation coefficient (ICC) will also be calculated.
Covariate analysis will be conducted to control for potential confounding factors in statistical modelling. Participants' age, gender, and the number of returned task (by each participant in intervention group) will be included in the analysis.
