Mental Health in the workplace: Evaluating the impact of counselling services in an Employee Assistance Programme

Introduction

It is estimated that we spend an average of over 84,000 hours at work over our lifetime. While a fulfilling job can enhance mental and physical health, over 15% of workers show signs of a mental health disorder. In the UK, stress, anxiety, and depression led to 16.4 million lost working days in 2023-2024, with each affected individual missing an average of 21.1 days.Lena by Inspire is a subsidiary of the larger Inspire Charity and operates as a social enterprise, offering a variety of wellbeing support services, training, and interventions designed to help organisations, employees, and students thrive. Lena provides employee assistance programmes (EAPs) across the island of Ireland, which include counselling services such as solution-focused brief therapy. From 2012, Lena have built up a large dataset of client journeys including Clinical Outcomes in Routine Evaluation (CORE-10) scores, and client feedback on the service.The aim of this study is to provide an analysis of counselling outcome data based within an employee assistance programme.

Methodology

Data was obtained from Lena, with ethical approval obtained from Ulster University. Descriptive statistics have been derived relating to client characteristics, and CORE outcome scores. R studio was used for analysis, including packages dplyr and tidyverse for data cleaning and wrangling, and ggplot2 for data visualisation.

Results

The sample size consists of 21,405 clients attending EAP counselling from October 2012 to September 2024. The mean age of clients attending the EAP service was 42.5, and over 68% of clients were female. The age ranges represented in the dataset was 35-44 (30.38%), followed by 45-54 (27.88%), 25-34(21.45%), 55-64 (14.4%), 18-24 (4.63%) and 65+ (1.26%). 84% of clients were in full time paid employment, 5.6% were in part-time paid employment. A paired t-test was conducted to compare pre and post counselling CORE10 scores. The results showed a significant improvement in scores with a mean difference of 6.87, finding a statistically significant difference (p < 0.001) between the first and last recorded CORE10 score.

Conclusions

Using these insights, we can gain a deeper understanding of the client's journey through employee mental health services, leading to actionable recommendations for improvement and personalisation of services, ultimately enhancing the overall client experience. Future work will involve identifying further trends and patterns within the dataset and using machine learning to understand client counselling outcomes in more detail.