Self-reported well-being assessment approach for healthcare workers

In this project, the conceptual framework developed by Brigham et al, (2018) and adopted by the National Academy of Medicine (NAM) was used. It focuses on factors affecting the well-being of healthcare workers representing a diversity of healthcare settings and types of healthcare workers.

This conceptual framework proposes two categories of factors affecting human resource well-being: external factors and individual factors.

This conceptual framework is designed to encompass comprehensively the factors that influence the well-being of healthcare workers, with the main aim of supporting the development of interventions and policies to reduce the risk of burnout and improve quality of life for healthcare workers.

(Brigham et al., 2018)

Based on data from Statistics Canada’s Survey of Healthcare Workers’ Experiences of the Pandemic, in this study the concept of “Well-being” is measured through three dependent variables: self-reported mental health, depression and anxiety. The database used to carry out the study did not include a variable for directly measuring the well-being of healthcare workers. The choice of these three variables to assess this concept comes from previous studies that have analyzed the well-being of healthcare workers using these same indicators (Chen et al., 2020; Suryavanshi et al., 2020).

Self-reported mental health: In the study database, general mental health status is a self-reported variable on a 5-level scale (excellent, very good, good, fair, poor).

Depression: The depression threshold was calculated from data collected using the PHQ-2 depression scale. ThePatient Health Questionnaire-2(PHQ-2) is a brief, simple screening tool used to assess the presence of depressive symptoms. It comprises two questions on mood and anhedonia, which assess the frequency of basic depressive symptoms. A score of 3 or more is the standard threshold for a positive result, i.e. if the score is 3 or more, major depressive disorder is likely. It has good sensitivity and specificity for identifying major depression (Löwe et al., 2005).

Anxiety: The anxiety threshold was calculated from marks obtained from healthcare workers using the Generalized Anxiety Disorder score – GAD-2. The Generalized Anxiety Disorder-2 (GAD-2) is a tool used to identify potential symptoms of generalized anxiety in population surveys. It consists of two questions, one on the frequency of nervousness or anxiety and the other on the frequency of inability to control worry. A threshold score is determined to screen for anxiety disorders. However, a score of 3 points is the preferred threshold for identifying possible cases in which further diagnostic evaluation of generalized anxiety disorder is warranted. Using a threshold of 3, the GAD-2 has a sensitivity of 86% and a specificity of 83% for the diagnosis of generalized anxiety disorder (Kroenke et al., 2007).

In the healthcare context, preventing psychological distress among workers is crucial to maintaining a healthy work environment and improving the quality of care provided. While Statistics Canada’s Survey of Healthcare Workers’ Experiences of the Pandemic (SHEWP) has measured mental health indicators such as depression and anxiety, it is essential to diversify screening tools in order to provide a more comprehensive assessment of this distress and prevent its occurrence. Several other scientifically validated tools can complement the assessment of distress symptoms in healthcare workers.

The Maslach Burnout Inventory (MBI) is one of the most widely used tools for measuring burnout, a major component of distress in healthcare workers. This tool assesses three dimensions: emotional exhaustion, depersonalization, and personal accomplishment, offering a broad view of burnout (Maslach & Jackson, 1981; Soares et al., 2023). Studies have shown that the MBI is particularly relevant for assessing burnout in healthcare workers during periods of prolonged stress, such as during the COVID-19 pandemic (Houdmont et al., 2022; Rizzo et al., 2023).

The Perceived Stress Scale (PSS) , developed by Cohen et al. (1983), is another effective tool for measuring the subjective perception of stress (Cohen et al., 1983). It has been used in various populations to assess the intensity of perceived stress, independently of objective factors. Recent studies have demonstrated that SSP is a valuable indicator for predicting mental health disorders, including depression and anxiety, in healthcare workers (Jiang et al., 2023; Yılmaz Koğar & Koğar, 2024).

To detect anxiety and depression in hospital settings, the Hospital Anxiety and Depression Scale (HADS), developed by Zigmond and Snaith (1983), offers a rapid and reliable method (Zigmond & Snaith, 1983). Comprising 14 questions divided into two subscales (anxiety and depression), it has been widely used to assess emotional distress in healthcare workers (Bjelland et al., 2002; Budzyńska & Moryś, 2023; Tasnim et al., 2021). A meta-analysis confirmed that the HADS has high sensitivity and specificity for screening for psychological distress in healthcare workers (Bjelland et al., 2002).

Assessing workers’ resilience, defined as the ability to adapt to stressful situations, is also crucial in preventing distress. The Connor-Davidson Resilience Scale (CD-RISC) (Connor & Davidson, 2003) is a frequently used tool for measuring this ability. Recent studies have highlighted that higher levels of resilience are associated with reduced occupational distress in healthcare workers (Alrjoub et al., 2023; Setiawati et al., 2021; Tugade & Fredrickson, 2004; West et al., 2020), suggesting that interventions aimed at strengthening resilience could help prevent burnout and anxiety.

Finally, the Professional Quality of Life Scale (ProQOL) is a tool that measures job satisfaction, but also compassion fatigue, an important indicator of distress in patient-facing healthcare workers (Nazari et al., 2024; Stamm, 2010). It is a 30-item self-report tool, divided into three subscales: compassion fatigue (including burnout and secondary traumatic stress) and compassion satisfaction, which assesses the pleasure derived from helping others. This tool is widely used to identify early signs of burnout and emotional distress in healthcare workers (Heritage et al., 2018; Rikos et al., 2024; Su et al., 2021), facilitating preventive interventions (Stamm, 2010).

In addition to these screening tools, programs such as Mindfulness-Based Stress Reduction (MBSR), although not specifically a screening tool, have shown significant effects in preventing distress in healthcare workers. These programs, popularized by Kabat-Zinn (1990), teach participants meditation techniques to manage stress and are widely used in healthcare settings to reduce burnout and improve overall well-being (Kabat-Zinn & Hanh, 2009; Kemper et al., 2015).

These various tools offer a multidimensional approach to assessing and preventing psychological distress in healthcare workers, enabling better detection of risk factors and early intervention.

For data analysis by specific sub-groups of healthcare workers, stratified analysis is a particularly useful statistical method for understanding how external and individual factors influence types of healthcare workers in distinct ways.

Finally, to get around the limitations of this study carried out in a pandemic context, a study with longitudinal data. Longitudinal data would also make it possible to analyze trends.