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By older adulthood, the majority of individuals will have experienced at least one traumatic event. Trauma-informed care (TIC) is proposed to improve effectivity of health-care provision and to reduce likelihood of services causing retraumatisation. This study aims to assess the effectiveness of staff training in TIC in older adult services.

TIC training was delivered across eight Older Adult Community Mental Health Teams in the same UK organisation. Questionnaires were administered before and after training: a psychometrically robust measure, the Attitudes Related to Trauma-Informed Care, was used to assess TIC-related attitudes, and a service-developed scale was used to measure changes in TIC competence. Data was analysed using linear mixed effects modelling (LMM). Qualitative data regarding the impact of training was gathered one month after training through a free-text questionnaire.

There were 45 participants, all of whom were white British. LMM on pre- and post-data revealed that staff training significantly increased competencies across all measured TIC domains. Overall, staff attitudes were also significantly more trauma-informed after training. Qualitatively, staff identified time as the only additional resource required to deliver the skills and knowledge gained from training.

Training was found to be effective in increasing TIC-related skills and attitudes. Organisations aiming to become trauma-informed should consider staff training as one aspect of a wider development plan.

To the best of the authors’ knowledge, this paper is the first to examine TIC training for staff working in Older Adults Mental Health Services. Recommendations for services aiming to develop a trauma-informed culture have been provided.

We aimed to identify factors that influence student engagement in distance learning.

The research involved a group of 671 students from economic and technical higher education institutions in Poland. We collected the data with the CAWI technique and an original survey. Next, we processed the data using principal component analysis and then used the extracted components as predictors in the induced smoothing LASSO regression model.

The components of the students’ attitude toward remote classes learning conditions are: satisfaction with teachers’ approach, attitude to distance learning, the system of students’ values and motivation, IT infrastructure of the university, building a network of contacts and communication skills. The final model consisted of seven statistically significant variables, encompassing the student’s sex, level of studies and the first five extracted PCs. Student’s system of values and motivation as well as attitude toward distance learning, were those variables that had the biggest influence on student engagement.

The research result suggests that in addition to students’ system of values and motivation and their attitude toward distance learning, the satisfaction level of teachers’ attitude is one of the three most important factors that influence student engagement during the distance learning process.

The main value of this article is the statistical model of student engagement during distance learning. The article fills the research gap in identifying and evaluating the impact of various factors determining student engagement in the distance learning process.