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Brief, interactive online mental health training can help teachers better respond to their pupils’ mental health difficulties, according to a new study.

A teacher with school children sitting on a carpet © Shutterstock

Researchers led by Dr Emma Soneson at the University of Oxford’s Department of Psychiatry questioned dozens of primary school teachers and teaching assistants to explore the potential value of a one-hour training programme they had trialled.

It comes at a time of increasing emphasis on school’s role in supporting pupils’ mental health, as growing numbers of children and young people report issues with their wellbeing.

The teaching staff, from six different primary schools in England, were asked to trial Kognito’s At-Risk for Elementary School Educators, which involves taking participants through two different hypothetical scenarios about pupil mental health and aims to improve staff’s knowledge and skills in supporting pupils and parents.

The findings have been published in the Journal of Medical Internet Research.

Dr Soneson said:

While schools in the UK are expected to play a lead role in protecting and promoting pupils’ mental health, many staff do not feel confident in identifying and responding to pupil mental health difficulties and report wanting additional training in this area.

After undertaking the training as part of this study, school staff reported greater confidence and preparedness and said they found it useful and practical.”

Unexpectedly, after the training, school staff identified fewer of their pupils as having mental health difficulties. However, there was also an increase in the accuracy of their assessments of their pupils’ needs.

For pupils who were identified as having mental health needs, the training seemed to help in terms of getting them mental health support at school. There was also better documentation and communication of concerns in schools following the training.

Dr Soneson added: “Training like this, which is affordable and flexible, has the potential to help address the high prevalence of mental health difficulties among primary school-age children by helping facilitate access to care and support.

“While the training provider we used was created in the US, teachers in the UK still found it useful. There may be even greater potential in training that is more culturally relevant.”

A total of 108 members of school staff, from six schools - four in Cambridgeshire, one in Merseyside and one in Greater London - took part in the study.

 Graphical representation of findings of the study, with text as follows:Can an online, low-intensity teacher training programme improve identification of and response to mental health difficulties? A feasibility study of at-risk for elementary school educators.Box 1Aim: To explore the feasibility of a one hour, online, simulation-based mental health training programme in UK primary schools.Box 2Background: School staff often are not confident to identify and respond to mental health difficulties. Kognito’s ‘At-risk for elementary school educators’ has been found to be helpful in the USA but has not been tested in the UKBox 3Methods: Pre-post non-randomised feasibility study with teachers and TAs in six primary schools (1 in London, 1 in Liverpool, 4 in Cabridgeshire). Mixed methods:-	Interviews-	QuestionnairesOutcomes: 1)	Teacher/TA confidence and preparedness2)	Identification rates3)	Mental Health Support4)	Acceptability and practicality programme for schoolsBox 4Results: Identification rates stayed the same but accuracy improvedAfter training…Teachers and Tas discussed and documented concerns more oftenConfidence and preparedness increasedMore pupils received in-class and in-school supportNo increase in external support outcomes (e.g. CAMHS)Training was acceptable and practical for schoolsBox 5Implications for practice and further researchSchools (thumbs up, arrow to) potentially feasible (thumbs up, arrow to) Further development (steps up arrow to) Larger trial.Graphic created by @clinicpsych_ind (on X)

Illustrations: @ClinPsych_Ind


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