The relationship between line manager training in mental health and organisational outcomes

Juliet Hassard; Teixiera Dulal-Arthur; Jane Bourke; Maria Wishart; Stephen Roper; Vicki Belt; Stavroula Leka; Nick Pahl; Craig Bartle; Louise Thomson; Holly Blake

doi:10.1371/journal.pone.0306065

. 2024 Jul 17;19(7):e0306065. doi: 10.1371/journal.pone.0306065

The relationship between line manager training in mental health and organisational outcomes

Juliet Hassard ^1,^#, Teixiera Dulal-Arthur ², Jane Bourke ³, Maria Wishart ⁴, Stephen Roper ⁴, Vicki Belt ⁴, Stavroula Leka ⁵, Nick Pahl ⁶, Craig Bartle ², Louise Thomson ^2,⁷, Holly Blake ^8,^9,^*,^#

Editor: Erum Shaikh¹⁰

PMCID: PMC11253945 PMID: 39018274

Abstract

Background

Line manager (LM) training in mental health is gaining recognition as an effective method for improving the mental health and wellbeing of workers. However, research predominantly focuses on the impacts of training at the employee-level, often neglecting the broader organisational-level outcomes. Most studies derive insights from LMs using self-reported data, with very few studies examining impacts on organisational-level outcomes.

Aim

To explore the relationship between LM training in mental health and organisational-level outcomes using company-level data from a diverse range of organisations.

Methods

This study is a secondary analysis of anonymised panel survey data from firms in England, with data derived from computer-assisted telephone surveys over four waves (2020, 1899 firms; 2021, 1551; 2022, 1904; and 2023, 1902). The analysis merged the four datasets to control for temporal variations. Probit regression was conducted including controls for age of organisation, sector, size, and wave to isolate specific relationships of interest.

Results

We found that LM training in mental health is significantly associated with several organisational-level outcomes, including: improved staff recruitment (β = .317, p < .001) and retention (β = .453, p < .001), customer service (β = .453, p < .001), business performance (β = .349, p < .001), and lower long-term sickness absence due to mental ill-health (β = -.132, p < .05).

Conclusion

This is the first study to explore the organisational-level outcomes of LM training in mental health in a large sample of organisations of different types, sizes, and sectors. Training LM in mental health is directly related to diverse aspects of an organisations’ functioning and, therefore, has strategic business value for organisations. This knowledge has international relevance for policy and practice in workforce health and business performance.

Introduction

In the United Kingdom (UK), one in six workers experience mental health challenges, with 12.7% of all sickness absence days attributed to mental ill-health [1]. The estimated annual cost of poor employee mental health to British employers is £56 billion annually [2]. The importance of employers addressing mental health in the workplace is emphasised in both national (e.g., ‘Mental Wellbeing at Work’, National Institute for Health and Care Guidance [3]) and international (e.g., International Organization for Standardization ‘ISO 45003’ standards on psychological health and safety at work [4]) policies through the implementation of workplace mental health and wellbeing (MH&WB) practices by organisations.

There are diverse MH&WB practices that employers may utilise to promote mental health at work and prevent work-related stress, each with a different target of change. The IGLO model [5] identifies targeted areas of (behavioural and organisational) change necessary to promote mental health at work:

Remedial and resiliency focused strategies targeting Individual behaviour change and health management (e.g., stress management, mindfulness).
Group-level strategies targeting improved social support, work group climate, and increased knowledge and understanding of mental health (e.g., team building exercises).
Improving managers’ and Leaders’ knowledge, skills, and abilities to promote mental health among those they manage (e.g., line manager (LM) training).
Improving Organisations through human-centric working conditions and enhanced job quality, underpinned by a psychosocial risk assessment (e.g., job design, job crafting, flexible work arrangements).

The impact and value of three of these targeted areas of change (individual, group and organisational) has been demonstrated in a burgeoning literature for both individual- (e.g., improved health and work motivation; [6–8]) and organisational-level outcomes (e.g., reduced sickness absence and decreased turnover; [9,10]).

The Job Demand Resource Model (JDR; Fig 1) [11,12]) provides a theoretical framework to understand the conceptual link between working conditions, employee mental health, and work performance and productivity outcomes. The JDR model postulates that work characteristics (categorised as either job demands or job resources) influence workers’ psychological well-being and work engagement. Job demands are those factors that require emotional or cognitive effort, which can result in psychological or physical harm. Conversely, job resources refer to those physical, social, or organisational aspects of the job that may: reduce job demands and their associated physiological and psychological costs; be functional in achieving work goals; and stimulate personal growth, learning, and development [11,12]. This model postulates two pathways that help to understand the link between employees’ working conditions, mental health and well-being, and organisational-level outcomes (e.g., customer service, productivity, absenteeism).

The health impairment pathway postulates that high job demands negatively impact employee mental health and, by extension, results in poor organisational-level outcomes. Conversely, the motivational pathway hypothesises that high levels of job resources improve employee motivation and engagement, and by extension, results in better organisational-level outcomes. Meta-analytic evidence using longitudinal studies finds strong evidence of the link between job demands and resources to individual-level health and motivational outcomes [13]. However, they emphasise the paucity of data examining the link between employee wellbeing and organisational-level outcomes, highlighting this as a key and pervasive gap in knowledge.

MH&WB practises aim to target each of these pathways in slightly different ways. From enhancing employees’ health management skills, to improving and supporting their engagement and performance at work (individual-focused) to the (re)design of work environments, to minimising job demands and enhancing opportunities for job resources. Therefore, understanding and testing the postulated link between MH&WB practises and organisational level outcomes addresses an important gap in knowledge. This is particularly true of interventions targeting leaders and managers.

In 2010, Kelloway and Barling [14] highlighted the need for, and value of, manager-focused interventions to support workplace mental health promotion. More recently, manager training in mental health was specifically identified as a strong recommendation for interventions by the World Health Organization (WHO) in their guidelines on mental health at work [15]. This approach to mental health training is unique and different from Mental Health First Aid (MHFA) training [16], which has become increasingly popular and researched in recent years. MHFA training aims to upskill nominated employees from across the organisation to provide support for a work colleague who is developing a mental health problem, experiencing a worsening of a mental health problem, or is in a mental health crisis. While increasingly popular in practice, recent evidence highlights a lack of high-quality evaluative data investigating its impact on employees or the organisation [17]. MHFA training is focused on remedial care and support, in contrast to prevention focused efforts to improve employees’ working conditions and management practices through the development and upskilling of LMs.

Therefore, the provision of LM training in mental health has emerged as a viable approach to improving the mental health of workers. With the rise in the prevalence of mental ill-health in the UK during the coronavirus (COVID-19) pandemic, there has since been a notable increase in the number of organisations offering LM training for mental health (2020: 50%; 2023: 59% [18]). LM training in mental health is a systematic approach to equipping LMs with the knowledge, skills, and attitudes needed to support the mental health of their team members and individuals they line manage [19]. This training may include a focus on the LMs’ own mental health and wellbeing, as well as that of the individuals they manage [20].

Despite its increasing popularity in practice over recent years, there remains a limited (but growing) literature that has sought to investigate the impact of LM training interventions on employees directly, and indirectly on their organisations. Employee-level benefits of LM training in mental health have previously been reported [20–22]. Such benefits include increased behavioural competencies to support those in their team with mental health challenges [20], behavioural intentions to promote mental health at work [22], and increased confidence to support the mental health of those they manage [21].

Comparatively fewer studies (e.g., [21,23]) have examined the impact and influence of LM training on organisational-level outcomes (e.g., changes to productivity, turnover rates, and absenteeism). To our knowledge, no studies to date have explored these relationships across a diverse range of organisations by size and sector and drawing on company-level (rather than self-reported employee-level) data. Understanding the impact of LM training at both employee- and organisational-levels is vital to appreciating its empirical and practical value in promoting mental health at work. In particular, understanding the organisational-level impact and benefit of LM training informs the business case for workplace mental health promotion. Understanding the economic arguments and benefits of workplace mental health promotion is an important motivator for employers to implement such strategies [24,25].

The aim of our study was, therefore, to investigate the association between the provision of LM training for mental health in organisations and organisational-level outcomes. This was achieved by utilising company-level data derived from an existing longitudinal survey of employers in England examining their MH&WB practices. The research questions (RQs) and hypotheses (Hs) are outlined below:

RQ1: Do organisations that offer LM training in MH have more, or less, sickness absence due to mental ill-health compared with organisations that do not offer this?

H1: Organisations that offer LM training in MH will have less sickness absence due to mental ill-health compared with organisations that do not offer this.
RQ2: How do organisations offering LM training in MH compare with those that do not, on organisational-level outcomes (e.g., recruitment, retention, customer services, business performance).

H2: Offering LM training in MH will be associated with improved organisational-level outcomes (e.g., recruitment, retention, customer services, business performance).

Materials and methods

This study is based on a secondary analysis of anonymised panel survey data from firms in England. Reporting was guided by the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement [26]) (Supplementary file 1) and the Consensus-Based Checklist for Reporting of Survey Studies (CROSS) [27] (Supplementary file 2). The data were derived from UK Computer Assisted Telephone Interview (CATI) surveys (a commonly used approach for reaching business personnel), collected over four time periods. Telephone surveys were used to reduce non-response bias commonly associated with mailed surveys [28].

Interviews were conducted by call centre operatives from a UK-based independent market research company. All telephone interviewers were independently evaluated throughout the fieldwork period, using a scorecard covering all aspects of their interview. The evaluation was based either on supervisory live listening or via audio recordings of the interview. CATI processes are evaluated annually by ISO20252 standard (for market, opinion, and social research) auditors and a minimum of 10% of interviews from each interviewer are evaluated and documented. In this study, approximately 12%-14% of interviews were subject to live listening quality control (QC), with around 5–10% of interviews undergoing full QC (listening to recordings and checking data once the survey is complete). All interviewers were trained in research methods and undertook a half-day training session prior to the study starting, involving role play and survey piloting to identify and resolve ambiguities. To minimise human error in data entry, data checking was undertaken, and outliers were identified and checked.

The data used in this study were collected in four waves as part of a broader prospective study which is funded by the UK Economic and Social Research Council and is ongoing. Wave 1: 6 January to 20 March 2020 (1899 firms), Wave 2: 28 January to 15 April 2021 (1551 firms), Wave 3: 27 January to 20 May 2022 (1904 firms) and Wave 4: 16 January to 5 May 2023 (1902 firms) all including data from non-government funded organisations with 10 or more employees. Organisations were additionally screened to ensure: (a) they were not a local or central government financed body; (b) they had been trading for three or more years. Branches and subsidiaries of larger businesses were included in the survey. Organisations with 10–19 employees were intentionally under-sampled as they accounted for most of the population universe. Larger organisations were over-sampled to ensure they were adequately represented, to reduce sampling bias and to allow more robust sub-analysis. The intention was to obtain as broad a response as possible during the data collection period, and so the final sample was the number of participants that responded between the survey opening and closing dates for each wave. Within each organisation, the most senior person with responsibility for the health and wellbeing of workers was approached and invited to participate as a representative of that organisation.

Organisations participating in Wave 1 were followed up in subsequent waves by the call centre operatives until an appointment was made or the organisation refused. However, as the study utilised unbalanced panel data rather than longitudinal data, new organisations were recruited at each wave to increase the overall sample size. In total, 118 organisations participated in the study across all four waves. The research was conducted in line with the Declaration of Helsinki. Ethical approach for this analysis was granted in August 2023 by the institutional Research Ethics Committee (Ref: HSSREC-144 21–22). Participants in the surveys provided informed oral consent which was documented by the telephone operatives. Although this is not clinical research, the senior author (HB) is trained in Good Clinical Practice (GCP). All researchers were trained in research ethics and research methods. The surveys were anonymised, and all datasets were stored on password protected files and only shared using a password protected OneDrive shared folder. The datasets were accessed on 23 August 2023.

Table 1 provides a summary of the operationalisation of our study variables. Our predictor variable was ‘LM training in mental health’. Quantified as a single, dichotomous variable (coded: no = 0, yes = 1). We tested four organisational-level outcome variables examining staff recruitment, customer service, retention, and business performance. All four variables were measured using a single-item question measured categorically (yes/no).

Table 1. Operationalisation of study variables.

Construct	Item Description	Measurement Level	Sample Size (n)
Sickness absence due to mental ill-health
Presence of sickness absence due to mental ill-health	In the last 12 months, have any staff been off sick, for any length of time, due to mental health problems, including illnesses such as bipolar disorder, depression, anxiety, or stress?	Binary	3385
Proportion of sickness absence due to mental ill-health	What proportion of sickness absence over the last 12 months was accounted for by mental health problems?	Continuous	1116
Repeated sickness absence due to mental ill-health	In the last 12 months have you had any instances where staff took repeated sickness absence because of mental health problems?	Binary	3566
Proportion of long-term sickness absence due to mental ill-health	What proportion of sickness absence due to mental health problems over the last 12 months has been long term (a single absence lasting 4 weeks or more)?	Continuous	3566
Organisational-level outcomes
Staff recruitment	Helped with staff recruitment	Binary	3182
Customer service	Improved customer service	Binary	3178
Staff retention	Improved staff retention/ reduced staff turnover	Binary	3189
Business performance	Improved business performance	Binary	3185

Open in a new tab

Four items quantified sickness absence related to mental ill-health trends, within the last 12 months, for the organisation. These four items allowed us to examine: (1) the presence (or absence) of sickness absence due to mental ill-health in the organisation; (2) the proportion of all sickness absence cases accounted for by mental ill-health; (3) the presence (or absence) of repeated sickness absence cases; and (4) the proportion of sickness absence for mental ill-health that was long-term (>4 weeks). Two items were measured dichotomously (Yes/ No), and two by a reported percentage.

For analysis purposes, the two sickness absence items measured continuously were dichotomised into ‘high’ and ‘low’ classifications. For the proportion of sickness absence (high/low), we utilised the sample mean for each annual survey wave to determine the numeric thresholds delineating high (> sample mean) and low (< = sample mean) classifications: 2020, 17%; 2021, 20%; 2022, 19%; and 2023, 22%. The same approach was utilised to specify ‘high’ and ‘low’ categorisations for our study variable examining the proportion of recurrent, long-term cases of sickness absence due to employee mental ill health within the organisation: 2020, 17%; 2021, 49%; 2022, 45%; and 2023, 40%.

We conducted probit regression analyses using SPSS Version 28 (Armonk, NY: IBM Corp) to determine the probability of specific outcomes occurring based on the presence or absence of LM training in mental health, allowing a deeper understanding of how LM training for mental health predicts various organisational-level outcomes. This analysis was deemed most appropriate due to its capacity to model binary outcomes, specifically yes/no responses, by quantifying probabilities rather than odds ratios [29]. Given the data structure of the study, probit regression was selected in preference to other viable alternatives such as logistic regression.

The four waves of data were merged for the analyses. This approach yielded several benefits such as providing increased statistical power through a larger sample size [30], allowing us to assess the stability and consistency of the relationships over time [31], and enhancing the overall generalisability of the results beyond the specific year in which data were collected [32]. As pooled panel data were used, we did not employ specific strategies to address missing data in the analysis as any missing data points were inherently handled through the nature of the dataset.

The regression analysis controlled for age of the organisation [0–10 years, 11–20 years, more than 20 years], sector [Production, Construction, Wholesale/Retail, Hospitality, Business Services and Other Services], size of the organisation [1–49 employees; 50–249 employees and 250+ employees] and survey wave [2020, 2021, 2022 and 2023]. This recognises that the age of the organisation, the specific sector in which an organisation operates, and its size can impact its performance, culture, decision-making processes, management practices and overall behaviour [33,34]. By controlling for these variables, we account for these differences ensuring a more accurate understanding of the relationship between the predictor and outcomes. The number and typology of organisations offering LM training in mental health (based on analysis of the same dataset) is detailed elsewhere [18].

Results

Table 2 provides an overview of our sample across several key demographics. After merging the four waves of data we had a final sample of n = 7139. The highest proportion of participating organisations came from the business services sector, operated for more than 20 years, and fell within the micro-to-small size category. The response rates were 17% (2020) and 15% (2021–2023). Response rate was calculated as the percentage of people who completed and answered the survey out of the total number of people invited to take part.

Table 2. Characteristics of participating organisations.

Characteristics	2020 (n = 1899)	2021 (n = 1551)	2022 (n = 1904)	2023 (n = 1902)
Sector
Production	364 (19.2%)	362 (23.3%)	411 (21.6%)	414 (21.8%)
Construction	139 (7.3%)	111 (7.2%)	145 (7.6%)	136 (7.2%)
Wholesale, retail	402 (21.2%)	331 (21.3%)	364 (19.1%)	363 (19.1%)
Hospitality	204 (10.7%)	109 (7.0%)	187 (9.8%)	210 (11.0%)
Business services	468 (24.6%)	350 (22.6%)	431 (22.6%)	419 (22.0%)
Other	322 (17.0%)	288 (18.6%)	366 (19.2%)	360 (18.9%)
Length of Operation
0–10 years	301 (16.0%)	236 (15.3%)	263 (13.9%)	250 (13.2%)
11–20 years	508 (27.0%)	378 (24.5%)	510 (27.0%)	541 (28.7%)
20 + years	1072 (57.0%)	929 (60.2%)	1115 (59.1%)	1097 (58.1%)
Size of Organisation
Micro-small (< = 50 employees)	1445 (76.1%)	1225 (79.0%)	1537 (80.7%)	1579 (83.0%)
Medium (51–250)	367 (19.3%)	286 (18.4%)	310 (16.3%)	286 (15.0%)
Large (>250)	87 (4.6%)	40 (2.6%)	57 (3.0%)	37 (1.9%)

Open in a new tab

RQ1: Do organisations that offer LM training in MH have more, or less, sickness absence due to mental ill-health compared with organisations that do not offer this?

To investigate RQ1, we used probit analysis to test whether organisations that offered LM training in mental health have lower reported levels of sickness absence (including, the presence (absence of) sickness absence cases and repeated cases, and high or low levels of sickness absence cases for mental health and long-standing cases (> 4 weeks; see Table 3). We observed only one significant association among the four areas of sickness absence trends tested. We found that offering LM training in mental health significantly predicted below-average levels of long-term sickness absence due to mental ill-health. Significant associations were not observed across the three other examined outcome variables for sickness absence.

Table 3. Probit regression testing the associations between LM training for MH (y/n) and organisational-level sickness absence trends due to mental ill-health.

Outcomes	Results
Presence of sickness absence due to mental ill-health (n = 3385)	β .160 (.0471)
	LR chi² 286.805***
	Log likelihood –493.883
Proportion sickness absence due to mental ill-health (n = 1116)	β -.077 (.0525)
	LR chi² 41.654***
	Log likelihood –414.569
Repeated sickness absence due to mental ill-health (n = 3566)	β .027 (.0803)
	LR chi² 49.490***
	Log likelihood -339.804
Proportion of long-term sickness absence due to mental ill-health (n = 3566)	β -.132* (.0577)
	LR chi² 388.557***
	Log likelihood –390.677

Open in a new tab

Note 1: Analysis controlled for wave, sector, size, and age of organisation.

Note 2: Standard error placed in brackets.

Note 3: LR chi² = Likelihood ratio chi-square.

The bar chart in Fig 2 below displays the regression coefficients which demonstrate the strength and directions of the associations between LM training for MH and the various outcomes related to sickness absence due to mental ill-health, including the presence, proportion, repeated occurrences, and long-term proportions.

RQ2: How do organisations offering LM training in MH compare with those that do not, on organisational-level outcomes (e.g., recruitment, retention, customer services, business performance)

To explore RQ2, we used probit analysis to test whether organisations that offered LM training in MH (as compared to those that did not) reported better efforts to recruit new staff, and improved customer service, staff retention and business performance (see Table 4). We found organisations offering LM training were more likely to report a range of positive outcomes including help with staff recruitment, improved customer service, improved staff retention and improved business performance.

Table 4. Probit regression analysis testing the associations between LM training for mental health (y/n) and improved organisational-level outcomes.

Dependent Variables	Results
Staff recruitment (n = 3182)	β .317*** (.0467)
	LR chi² 118.377***
	Log likelihood –484.131
Customer service (n = 3178)	β .453*** (.0485)
	LR chi² 184.147***
	Log likelihood –451.901
Staff retention (n = 3189)	β .379*** (.0479)
	LR chi² 95.828
	Log likelihood –476.803
Business performance (n = 3185)	β .359*** (.0496)
	LR chi² 105.963
	Log likelihood –446.303

Open in a new tab

Note 1: Analysis controlled for wave, sector, size and age of organisation.

Note 2: Standard error placed in brackets.

Note 3: LR chi² = Likelihood ratio chi-square.

The bar chart in Fig 3 below shows the regression coefficients (β) for the associations between LM training for mental health (MH) and improved organisational-level outcomes, including staff recruitment, customer service, staff retention, and business performance. Each bar represents the β coefficient value, indicating the strength and direction of the associations.

Table 5 below summarises these results and highlights how it compares to previous research and the unique contributions this study brings to the existing literature.

Table 5. Summary of key findings, comparison to previous research and research contributions.

Key Findings	Comparison to Previous Research	Research Contributions
LM training in mental health was significantly associated with below-average levels of long-term sickness absence due to mental ill-health.	Evidence shows that LM training in mental health may improve managers’ self-reported capabilities to support employees with mental ill-health following return to work [21,22].	Provides an empirical example of the Chain of Impact Model by showing how the provision of LM training for mental health may translate organisation implemented interventions into improved economic outcomes for the organisation.
LM training in mental health was not associated with short-term sickness absence due to mental ill-health or repeated sickness absence due to mental ill-health.	One single site study showed that LM training in mental health reduced work-related sickness absence [21].	Our findings highlight the complexity of LM training’s relationship with various kinds of sickness absences and distinguishes between its relationship with other categories of mental health related absences.
Organisations offering LM training were more likely to report improvements in staff recruitment, customer service, staff retention and business performance.	Research shows that LM training in mental health can lead to improvements in employee-level outcomes [20].	Extends understanding of the benefits of LM training beyond employee well-being to include organisational benefits, thus broadening our understanding of the broader impact of LM training.

Open in a new tab

Discussion

To our knowledge, this study was the first to investigate the provision of LM training for mental health in organisations and its association across organisational-level outcomes including sickness absence, staff recruitment and retention, customer service, and business performance. We found that organisations that train their line managers in mental health have better outcomes across all these areas, which has national and international relevance to research, policy, and practice in workplace health.

A key empirical strength of this study is that we investigated these associations within a diverse sample of British organisations (e.g., company size, type, and sector), using company-level data. This data set allowed us to, uniquely, explore the often discussed and postulated relationship between mental health and well-being practises in the workplace and wider organisational performance indicators (e.g., [2,35–37]), some of which have been rarely examined in a systematic way within the wider workplace health management literature (e.g., customer service and business performance). As such, while the study was conducted with a sample from England, the study makes a significant contribution to the literature in this field with international relevance. Examining organisational-level outcomes is imperative as it helps to build our understanding of the business case for workplace mental health promotion and, in turn, its articulation to employers regarding its strategic business value. Therefore, our study findings make an important contribution to addressing this key gap in knowledge.

The study objective was to explore the relationship between LM training for mental health and organisational-level outcomes using company-level data from a diverse range of organisations. We observed that the provision of LM training for mental health was, on average, associated with improvement across two key organisational performance dimensions, broadly related to workforce activity (defined by dimensions of attendance, effort, quality, and innovation) and organisational outputs (defined by dimensions of productivity, business, and customer satisfaction; [38]). These two key organisational performance dimensions can be conceptually understood to drive the economic outcomes for organisations (such as profit and shareholder value), through a Chain of Impact Model (Fig 4). The Chain of Impact Model therefore provides a useful framework in which to interpret our findings and conceptualise how the provision of LM training for mental health may translate organisational-level outcomes into improved economic outcomes for the organisation.

We observed that, on average, the provision of LM training within organisations was associated with improved workforce activity, evidenced across three key indicators: below average long-term sickness absence spells due to mental ill-health, improved staff retention, and enhanced staff recruitment activities and efforts by the organisation. Our findings align with recent economic estimates observing the costs associated with increased staff turnover and recruitment initiatives due to poor employee mental health at work (e.g., [2]). Uniquely, our study demonstrates that the provision of LM training for mental health is associated with improved organisational metrics regarding retention and recruitment initiatives. Collectively this evidence-base highlights not only the cost of inaction in the wellbeing space, but, importantly, the potential economic benefit of investing in MH&WB practices at work.

In relation to our four indicators of sickness absence, we observe a complex and nuanced picture. We found that LM training in mental health was associated with a below average number of long-term sickness absence cases within the organisation. There is growing evidence of the impact of LM training in mental health on mangers’ self-reported capabilities and confidence in supporting employees with mental ill-health during and following their return to work [21,22,39,40]. These managerial competencies are increasingly understood as a key success factor in facilitating effective return to work processes [41]. However, we did not find a significant association in relation to the three other indicators of sickness absence: the presence (or not) of staff off sick due to mental health problems (e.g., bipolar disorder, depression, anxiety, or stress) and repeated cases, or proportion of sickness absence accounted for by mental ill-health in general.

Reduction in these aspects of sickness absence may be primarily driven by prevention-orientated (rather than remedial-focused) MH&WB practices. Blake and colleagues [42] noted that there are few LM training initiatives that include a prevention-orientated focus (e.g., preventing stress through job quality and workload management), with most interventions targeting resiliency- or remedial-focused activities (e.g., self-care, improved knowledge surrounding mental health at work). Accounting for the nature, content and focus of LM training (rather than just its presence or not) may provide a more nuanced understanding of its association with organisational-level sickness absence indicators. We speculate that those training initiatives with a strong prevention-focus (e.g., [43]) may demonstrate a significant association with these remaining dimensions of sickness absence, as compared to those without although this is yet to be demonstrated. Testing these inferences is imperative to gathering a deeper understanding of the association between LM training and organisations’ sickness absence indicators, globally.

Tamkin’s Chain of Impact Model [38] theorises that these improved workforce activities should drive and influence increased organisational output metrics. While we did not test this causal pathway, we did observe that the provision of LM training for mental health was, on average, associated with improved business performance and overall customer satisfaction–both important and strategic organisational performance outcomes and precursors to improved economic outcomes. Several studies [44,45] and academic commentaries [36,37] have discussed this link, but have not tested it robustly across organisations. This is partly explained by, up until recently [46], the dearth of robust company-level data capturing both mental health and well-being practices within the organisation, as well as key productivity and performance metrics. Therefore, our early findings highlighting the association between LM training for mental health at work and strategic organisational performance outcomes are conceptually important as they provide foundational evidence for what has long been speculated regarding the costs of poor mental health at work to employers.

Strengths, limitations and implications for future research

Workforce mental health is always an important topic, but an organisational focus on mental health was particularly pertinent during the COVID-19 pandemic when population mental-ill health was rising, associated with myriad factors (e.g., viral transmission, economic uncertainty, social isolation). Our positive findings are therefore notable in the context of this global crisis. A significant strength of the study is its large sample size and diversity of organisations included. We are therefore able to report findings across sectors and sizes of organisations, including sectors in which mental ill-health is prevalent, but research evidence relating to workplace mental health interventions is limited (e.g., construction: [47]). Another strength of the study is that around 80% of participating organisations had fewer than 50 employees; our study therefore includes many SMEs that are under-researched and often have fewer resources to be active in mental health promotion.

Our findings provide a robust base from which to infer the potential benefits of LM training in mental health at the organisational-level and as such, are novel, and have high potential for influencing policy and practice internationally. There are several limitations within this study. First, to collect this data enterprise representatives were used to quantify workplace health and well-being practices, as well as organisational-level outcomes—including organisational performance indicators. While this is a common feature of enterprise surveys (e.g., European Survey of Enterprises on New and Emerging Risks; [48,49]), we acknowledge there may be a degree of subjective bias within this self-reporting methodology. Ideally, these associations would also be tested and triangulated with objective, rather than exclusively subjective outcomes. We view this as an important future direction for research in this field. Second, the data available within our data set allows us to test the presence (and absence) of LM training for mental health at work in relation to organisational-level outcomes. However, we anticipate that the nature of this training (in terms of its content, focus, and duration) and its perceived quality as reported by the recipients are also important explanatory variables in relation to quantifying its impact and value to the organisation. This to an important avenue of future research. Third, the use of pooled panel data hinders the capacity to capture the long-term impacts of LM training on organisational outcomes. Fourth, most research on LM training in mental health generally explores outcomes for the manager (e.g., awareness, knowledge, confidence, skills), and our study provides novel data by focusing on outcomes at an organisational level (e.g., indices of business performance). However, few studies have explored the way in which LM training is implemented in practice, and whether (or not) this impacts on mental health at the employee-level. There is currently inconclusive evidence that leadership training impacts on employee outcomes, due to contradictory results [50]. While employee outcomes were not the focus of our study, future research may seek to enhance the evidence-base relating to employee outcomes. Lastly, the low response rate observed across the four time points and the presence of missing data may indicate response bias and limit the generalisability of the findings.

Conclusion

Training line managers in mental health is associated with better organisational-level outcomes including long-term sickness absence, staff recruitment and retention, customer service, and business performance. This study is the first to provide confirmation of the strategic value of providing LM training in mental health for organisational-level outcomes, and as such provides novel evidence with the potential to influence policy and practice internationally. Our findings strengthen the business case for organisational investment in workplace mental health and wellbeing and have relevance for diverse stakeholders including business owners and managers, professional bodies, charities, and policymakers. This study provides evidence that taking a proactive approach to workforce wellbeing has the potential to improve a diverse range of factors associated with business productivity and performance. Our primary recommendation from this study is a clear call to action for organisations to establish workplace mental health policy that outlines the role of LMs in preventing and supporting mental health at work and invest in (or provide access to) mental health training for their LMs. This is advocated in the WHO guidelines on mental health at work [15] but not yet consistently implemented across organisation types and sectors. New, evidence-based training in mental health for LMs has been developed [42] and is currently being tested in a cluster randomised trial [23] to explore acceptability and outcomes for managers and employees.

Supporting information

S1 Table. STROBE statement: Checklist of items that should be included in reports of observational studies.

(DOCX)

pone.0306065.s001.docx^{(34.2KB, docx)}

S2 Table. Checklist for Reporting of Survey Studies (CROSS).

(DOCX)

pone.0306065.s002.docx^{(21.5KB, docx)}

Data Availability

The dataset used in this study is available from the Nottingham Research Data Management Repository (http://doi.org/10.17639/nott.7419).

Funding Statement

The data used here were originally collected as part of an Economic and Social Research Council funded project ‘Workplace mental-health and well-being practices, outcomes and productivity’ (Grant number: ES/W010216/1). This secondary analysis project ‘Mental health at work: a longitudinal exploration of line manager training provisions and impacts on productivity, individual and organizational outcomes’ was supported by the Economic and Social Research Council [The Productivity Institute: grant number: ES/V002740/1]. There was no additional external funding received for this study.

References

1.Mental Health at Work. Mental Health at work: Statistics. Mental Health Foundation. 2023. Available from: https://www.mentalhealth.org.uk/explore-mental-health/statistics/mental-health-work-statistics#:~:text=1%20in%206.8%20people%20experience,in%20the%20workplace%20(14.7%25). [Google Scholar]
2.Deloitte. Poor mental health costs UK employers up to 56 billion a year. 2022. Available from: https://www2.deloitte.com/uk/en/pages/press-releases/articles/poor-mental-health-costs-uk-employers-up-to-pound-56-billion-a-year.html. [Google Scholar]
3.National Institute for Health and Care Guidance. Mental Wellbeing at Work. NICE. March 2, 2022. Available from: https://www.nice.org.uk/guidance/ng212#:~:text=This%20guideline%20covers%20how%20to,risk%20of%20poor%20mental%20health. [PubMed] [Google Scholar]
4.ISO. Occupational health and safety management. 2021. Available from: https://www.iso.org/standard/64283.html. [Google Scholar]
5.Nielsen K, Yarker J, Munir F, Bültmann U. IGLOO: An integrated framework for sustainable return to work in workers with common mental disorders. Work & Stress. 2018;32(4):400–417. [Google Scholar]
6.Richardson KM, Rothstein HR. Effects of occupational stress management intervention programs: a meta-analysis. J Occup Health Psychol. 2008;13(1):69. doi: 10.1037/1076-8998.13.1.69 [DOI] [PubMed] [Google Scholar]
7.Montano D, Hoven H, Siegrist J. Effects of organisational-level interventions at work on employees’ health: a systematic review. BMC Public Health. 2014;14(1):1–9. doi: 10.1186/1471-2458-14-135 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Fox KE, Johnson ST, Berkman LF, Sianoja M, Soh Y, Kubzansky LD, et al. Organisational- and group-level workplace interventions and their effect on multiple domains of worker well-being: A systematic review. Work Stress. 2022. [Google Scholar]
9.Lamontagne AD, Keegel T, Louie AM, Ostry A, Landsbergis PA. A systematic review of the job-stress intervention evaluation literature, 1990–2005. Int J Occup Environ Health. 2007;13(3):268–280. doi: 10.1179/oeh.2007.13.3.268 [DOI] [PubMed] [Google Scholar]
10.Brunner B, Igic I, Keller AC, Wieser S. Who gains the most from improving working conditions? Health-related absenteeism and presenteeism due to stress at work. Eur J Health Econ. 2019;20:1165–1180. doi: 10.1007/s10198-019-01084-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Demerouti E, Bakker AB, Peeters MC, Breevaart K. New directions in burnout research. European Journal of Work and Organizational Psychology. 2021. Sep 3;30(5):686–91. [Google Scholar]
12.Bakker AB, Demerouti E. The job demands‐resources model: State of the art. Journal of managerial psychology. 2007. Apr 3;22(3):309–28. [Google Scholar]
13.Lesener T, Gusy B, Wolter C. The job demands-resources model: A meta-analytic review of longitudinal studies. Work & Stress. 2019. Jan 2;33(1):76–103. [Google Scholar]
14.Kelloway EK, Barling J. Leadership development as an intervention in occupational health psychology. Work & Stress. 2010;24(3):260–279. [Google Scholar]
15.World Health Organization. Guidelines on mental health at work. 28 September 2022. WHO, Geneva, Switzerland. Available at: https://www.who.int/publications/i/item/9789240053052. [Google Scholar]
16.Costa, Oliveira Tiago Filipe, Francisco Miguel Correia Sampaio, Carlos Alberto da Cruz Sequeira, Isilda Maria Oliveira Carvalho Ribeiro, and Vitor Sérgio de Oliveira Parola. "Review of Mental health first aid programs." Western Journal of Nursing Research 43, no. 12 (2021): 1146–1156. [DOI] [PubMed] [Google Scholar]
17.Richardson R., Dale H. E., Robertson L., Meader N., Wellby G., McMillan D., et al. (2023). Mental Health First Aid as a tool for improving mental health and well‐being. Cochrane Database of Systematic Reviews, (8). doi: 10.1002/14651858.CD013127.pub2 [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Blake H, Hassard J, Dulal-Arthur T, Wishart M, Roper S, Bourke J, et al. Typology of employers offering line manager training for mental health. Occupational Medicine, 2024;74(3):242–250, doi: 10.1093/occmed/kqae025 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Martin A, Woods M, Dawkins S. How managers experience situations involving employee mental ill-health. Int J Workplace Health Manage. 2018;11(6):442–463. [Google Scholar]
20.Gayed A, Milligan-Saville J, Nicholas J, Bryan B, Lamontagne A, Milner A, et al. Effectiveness of training workplace managers to understand and support the mental health needs of employees: a systematic review and meta-analysis. Occupational and Environmental Medicine. 2018;75:462–470. doi: 10.1136/oemed-2017-104789 [DOI] [PubMed] [Google Scholar]
21.Milligan-Saville JS, Tan L, Gayed A, Barnes C, Madan I, Dobson M, et al. Workplace mental health training for managers and its effect on sick leave in employees: a cluster randomised controlled trial. The Lancet Psychiatry. 2017;4(11):850–858. doi: 10.1016/S2215-0366(17)30372-3 [DOI] [PubMed] [Google Scholar]
22.Dimoff JK, Kelloway EK, Burnstein MD. Mental health awareness training (MHAT): The development and evaluation of an intervention for workplace leaders. International Journal of Stress Management. 2016;23(2):167. [Google Scholar]
23.Thomson L, Hassard J, Frost A, Bartle C, Yarker J, Munir F, et al. Digital Training Program for Line Managers (Managing Minds at Work): Protocol for a Feasibility Pilot Cluster Randomized Controlled Trial. JMIR Res Protoc. 2023;12(1):e48758. doi: 10.2196/48758 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Hassard J, Muylaert K, Namysl A, Kazenas A, Flaspoler E. Motivation for employers to carry out workplace health promotion: literature review. Luxembourg: Publications Office of the European Union, 2012. ISBN: 978-92-9191-999-4 doi: 10.2802/50267 [DOI] [Google Scholar]
25.Law R, St George A, King L, Rissel C. Employer Perspectives of Workplace Health Promotion. 2013. [Google Scholar]
26.von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. PLoS Med. 2007;4(10):e296. doi: 10.1371/journal.pmed.0040296 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Sharma A, Minh Duc NT, Luu Lam Thang T, Nam NH, Ng SJ, Abbas KS, et al. A Consensus-Based Checklist for Reporting of Survey Studies (CROSS). J Gen Intern Med. 2021. doi: 10.1007/s11606-021-06737-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Fowler FJ Jr, Gallagher PM, Stringfellow VL, Zaslavsky AM, Thompson JW, Cleary PD. Using telephone interviews to reduce nonresponse bias to mail surveys of health plan members. Medical care. 2002. Mar 1:190–200. doi: 10.1097/00005650-200203000-00003 [DOI] [PubMed] [Google Scholar]
29.Cleophas TJ, Zwinderman AH, Cleophas TJ, Zwinderman AH. Probit Regression, Binary Data as Response Rates (14 Tests). SPSS for Starters and 2nd Levelers. 2016:287–96. [Google Scholar]
30.Eng J. Sample size estimation: how many individuals should be studied?. Radiology. 2003;227(2):309–13. doi: 10.1148/radiol.2272012051 [DOI] [PubMed] [Google Scholar]
31.Rafferty A, Walthery P, King-Hele S. Analysing change over time: repeated cross-sectional and longitudinal survey data. 2015. [Google Scholar]
32.Tooth L, Ware R, Bain C, Purdie DM, Dobson A. Quality of reporting of observational longitudinal research. Am J Epidemiol. 2005;161(3):280–288. doi: 10.1093/aje/kwi042 [DOI] [PubMed] [Google Scholar]
33.Nazarian A, Atkinson P. How size affects organizational culture in a national context. Pensee. 2013;75(12). [Google Scholar]
34.Jain S, Gautam A. Comparison of Performance Management Systems in Public and Private Sector: A Study of Manufacturing Organizations. Int J Manag IT Eng. 2016;6:111–128. [Google Scholar]
35.Deloitte. Refreshing the case for investment.2023. Available from: https://www2.deloitte.com/uk/en/pages/consulting/articles/mental-health-and-employers-refreshing-the-case-for-investment.html. [Google Scholar]
36.Hassard J, Thomson L, Blake H. Understanding the cost of mental health at work: an integrative framework. The SAGE handbook of organizational wellbeing. 1st edn. London: SAGE. 2021:9–25. [Google Scholar]
37.Hassard J, Thomson L, Blake H. Understanding and Exploring the Cost of Poor Mental Health at Work for Organizations and Society. In: The Routledge Companion to Mental Health at Work. Routledge. 2023:77–96. [Google Scholar]
38.Tamkin P. The Contribution of Skills to Business Performance. DfES publication RW39. August 2005. [Google Scholar]
39.Lampe M. Empowering managers: are mental health training programmes the key to a healthier workplace? Science for work. November 2023. Available from: https://scienceforwork.com/blog/empowering-managers-are-mental-health-training-programs-the-key-to-a-healthier-workplace/. [Google Scholar]
40.Mousseau M. Elevating Leadership: The Importance of Mental Health Training in the Workplace. 2023. Available from: https://www.ajg.com/us/news-and-insights/2023/oct/elevating-leadership-the-importance-of-mental-health-training-in-the-workplace/. [Google Scholar]
41.Johnston V, Way K, Long MH, Wyatt M, Gibson L, Shaw WS. Supervisor competencies for supporting return to work: a mixed-methods study. J Occup Rehabil. 2015;25:3–17. doi: 10.1007/s10926-014-9511-z [DOI] [PubMed] [Google Scholar]
42.Blake H, Hassard J, Bartle C, Thomson L. Training for line managers should focus on primary prevention of mental ill-health at work. Perspectives in Public Health. 2023. May;143(3):124–5. doi: 10.1177/17579139231157528 [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Blake H, Vaughan B, Bartle C, Yarker J, Munir F, Marwaha S, et al. Managing Minds at Work: Development of a Digital LM Training Program. International Journal of Environmental Research and Public Health. 2022;19. doi: 10.3390/ijerph19138006 [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Hassard J, Teoh K, Thomson L, & Blake H. Organizational uncertainty and stress among teachers in Hong Kong: work characteristics and organizational justice. Health Promot Int. 2017;32(5):860–870. doi: 10.1093/heapro/daw018 [DOI] [PubMed] [Google Scholar]
45.Hassard J, Teoh KR, Visockaite G, Dewe P, Cox T. The cost of work-related stress to society: A systematic review. J Occup Health Psychol. 2018;23(1):1. doi: 10.1037/ocp0000069 [DOI] [PubMed] [Google Scholar]
46.Stanfield C, Wishart M, Sissons P, Ferreira J, Roper S, Belt V. A baseline study for the Mental Health and Productivity Pilot project. Enterprise Research. 2020. Available from: https://www.enterpriseresearch.ac.uk/wp-content/uploads/2020/05/Employee-Wellbeing-Mental-Health-and-Productivity-in-Midlands-Firms-May-2020.pdf. [Google Scholar]
47.Greiner BA, Leduc C, O’Brien C, Cresswell-Smith J, Rugulies R, Wahlbeck K, et al. The effectiveness of organisational-level workplace mental health interventions on mental health and wellbeing in construction workers: A systematic review and recommended research agenda. PLoS One. 2022. Nov 16;17(11):e0277114. doi: 10.1371/journal.pone.0277114 [DOI] [PMC free article] [PubMed] [Google Scholar]
48.EU-OSHA. Third European Survey of Enterprises on New and Emerging Risks (ESENER 2019): Overview Report. 2019. Available from: https://osha.europa.eu/sites/default/files/esener-2019-overview-report.pdf. [Google Scholar]
49.EU-OSHA. European Survey of Enterprises on New and Emerging Risks–Managing safety and health at work. 2010. Available from: https://osha.europa.eu/en/publications/european-survey-enterprises-new-and-emerging-risks-managing-safety-and-health-work. [Google Scholar]
50.Aust B, Møller JL, Nordentoft M, Frydendall KB, Bengtsen E, Jensen AB, et al. How effective are organizational-level interventions in improving the psychosocial work environment, health, and retention of workers? A systematic overview of systematic reviews. Scand J Work Environ Health. 2023. Jul 1;49(5):315–329. doi: 10.5271/sjweh.4097 [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0306065.r001

Decision Letter 0

Erum Shaikh

3 May 2024

PONE-D-24-06886The Relationship between Line Manager Training in Mental Health and Organisational OutcomesPLOS ONE

Dear Dr. Blake,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Reviewer 1The paper "The Relationship between Line Manager Training in Mental Health and Organisational Outcomes" examines the effects of managerial training on organizational outcomes. While the introduction adequately establishes the research, incorporating a discussion on existing mental health training practices could improve its context. The literature review could be strengthened by including a variety of viewpoints and conflicting research according to the variables. The methodology section, centered around probit regression, could benefit from a discussion on its limitations and potential biases and it could be analyse using confirming statistical multivariate analysis methods. The results section is well-articulated and comprehensive, though adding visual data representations and concentrating data in tables can enhance understanding. The conclusions effectively recap the study’s findings; however, elaborating on their practical applications could enhance their utility in real-world settings; increasing references to previous studies are needed to confirm research assumptions. Finally, the references are comprehensive, yet updating them to include more of the latest studies would ensure the research's relevance and show the top industry standards.

Suggestions for Enhancement:

Introduction:

I'd like you to add insights on prevailing mental health training practices in the industry to anchor the research's significance better. Include a clear definition of your research questions, objectives, and hypothesis, perhaps in a table.

Literature Review:

Broaden the scope to include diverse research and a more comprehensive array of theoretical perspectives to enrich the narrative. Explain each of your research variables and define a table of authors where you include the top publications for each variable and dimension of your study.

Methodology:

Include more details on the selection of probit regression and address any inherent methodological weaknesses or biases. Explain why it was the best alternative for analyzing this data and if there's any other possible alternative method to validate your assumptions.

Results:

I'd like you to introduce graphical elements like charts or graphs to summarize and clarify key findings, compare your results with previous research, and determine if this study covers any gap in theory, methodology, or research methods.

Conclusions:

Detail the practical implications of the research findings, suggesting specific training or policy changes that could be derived from the study. Describe the stakeholder who are having the best use for your fingins. Describe how you achieve your results and goals.

References:

Update and verify that all references reflect the most current research, ensuring the study's alignment with the latest developments in the field.Reviewer 2This is an interesting study investigating the organizational level effects of line manager trainings for mental health. The authors found a way to assess these outcomes by analysing data from an existing dataset (panel survey data from firms in England) thereby adding important information about the effects of these trainings that go beyond an assessment by the participants.

The manuscript is well written and clearly structured and adds important information to this area of research.

However, I have some comments that I would like the authors to respond to before publication:

The authors are right in pointing out (page 5 line 90) that only few studies have examined the impact and influence of LM training on organisational-level outcomes (e.g., changes to productivity, turnover rates, and absenteeism). However, also the impact of LM training on employee outcomes is often not assessed. This also applies to the “Employee-level benefits” that the authors describe have been found (page 5 line 85). It does not look like employees have been asked about these benefits. Instead, the results describe managers’ own assessment of their gained competencies, their intentions to promote mental health at work and their increased confidence to support employees with mental health problems. I understand that this often is what can be measured in studies about manager training as asking employees would often result in a much larger study. However, since the authors address this topic I think it is important to mention that we actually know surprisingly little about the effects of LM trainings for employees, as most studies assess how the participants themselves (the managers) evaluate what they gained from having been trained. Results often show increased knowledge, confidence and good intentions, however, we most of the time do not know if this leads to actual implementing this in daily practice (for example more support for employees with mental health problems) and we know even less about if this leads to better outcomes for employees.

This lack of knowledge of manager training for employee outcome is discussed in for example the two papers below but can also be found in several reviews about manager training for employee mental health:

Rugulies, R., Aust, B., Greiner, B. A., Arensman, E., Kawakami, N., LaMontagne, A. D., & Madsen, I. E. (2023). Work-related causes of mental health conditions and interventions for their improvement in workplaces. The Lancet, 402(10410), 1368-1381.

Aust, B., Møller, J. L., Nordentoft, M., Frydendall, K. B., Bengtsen, E., Jensen, A. B., ... & Jaspers, S. Ø. (2023). How effective are organizational-level interventions in improving the psychosocial work environment, health, and retention of workers? A systematic overview of systematic reviews. Scandinavian Journal of Work, Environment & Health, 49(5), 315.

My next comment is about missing data. The authors report on page 11, line 200 that the sample consisted of 7139 participants after the four waves were merged. However, the numbers of answers for the different questions are much lower. In Table 3 the number of responses for the sickness absence related outcomes are between 1116 and 3566. In Table 4 the numbers for the responses for the organisational-level outcomes are between 3178 and 3189. Does that mean that only around half of the participants answered these questions? Please explain.

In addition, the number of answers for the questions about the proportion of sickness absence due to mental health is particularly low (n=1116). Do you have any explanation for why this question was not answered by most of the participants? An explanation could be that employers might not have that information. They might only have information about sickness absence in general, but not about the reason for sickness absence.

On page 10, line 186 the authors write: “As pooled panel data were used, we did not employ specific strategies to address missing data in the analysis as any missing data points were inherently handled through the nature of the dataset.” Could you please explain, what is meant by “were inherently handled through the nature of the dataset”?

Response rate: As reported in the result section (page 11, line 202), the response rate for the four waves was between 17% (2020) and 15% (2021-2023). This low response rate together with the high degree of missing data among those who answered should be addressed as a limitation of the study in the section strengths and limitations.

It is however positive that the sample included a lot of small to medium sized workplaces (SMEs). In fact, around 80% of the participating organisations had less than 50 employees. Most studies about mental health at work are conducted in larger organisations, so it is clearly a strength that this study includes many SMEs that often have fewer resources to be active in mental health promotion. This strength could also be mentioned in the discussion part. Another strength is the mix of sectors, as there often is an overrepresentation of studies about mental health at work conducted in the health care sector. In this study, it is therefore good to see that sectors such as production and construction are represented. (See for example the study by Greiner et al. that calls for more research about mental health interventions in the construction sector. (Greiner, B. A., Leduc, C., O’Brien, C., Cresswell-Smith, J., Rugulies, R., Wahlbeck, K., ... & Aust, B. (2022). The effectiveness of organisational-level workplace mental health interventions on mental health and wellbeing in construction workers: A systematic review and recommended research agenda. Plos one, 17(11), e0277114.).

However, it would also be good to know how many organisations actually offered Line Manager training in mental health, that is, how was the question “LM training in mental health” (page 8, line 158) answered by the organisations? Could you report this and also shown it by size of organisation? This would be very valuable additional information for this topic: How widespread are LM training in mental health in these organisations (especially in in this sample representing sectors often not studied)? Are LM trainings just as common among SME businesses than they are among larger organisations? Please add this information.

Another issue that should be addressed is that at least some of the survey waves were conducted during the COVID-19 pandemic (see page 7, from line 131). The first wave (January to March 2020) was probably not affected, especially since the questions are about the past 12 months, so before the pandemic came to Europe. However, wave 2 and 3 conducted in 2021 and 2022 and thereby asking about 2020 and 2021 were conducted while most workplaces were affected by the pandemic in one way or the other. The authors probably have no specific knowledge about how this affected these workplaces, but it could be mentioned that the need for more awareness for employee mental health might have been even higher during these years (because for example more social isolation) and therefore it is good to see that the effects of this study were found despite of this. The topic is mentioned in the introduction but could also be mentioned again in the discussion with regard to the results.

I also noticed that the mean of recurrent long-term cases of sickness-absence due to mental health was 17% in 2020, but 49% in 2021, 45% in 2022 and 40% in 2023 (page 10, line 177). Could that maybe be seen as an increase in mental health problems severity among those that were suffering from mental health problems due to the pandemic? The proportion of sickness absence due to mental health only increased slightly during the four waves.

Minor comment: On page 11, line 202 the authors write “Response rate was calculated as the percentage of people who completed and returned the survey out of the total number of people invited to take part.” Was there something to return? Or should it be “answered” since the survey was done by telephone interview

Please submit your revised manuscript by Jun 17 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Erum Shaikh

Academic Editor

PLOS ONE

Journal Requirements:

1. When submitting your revision, we need you to address these additional requirements.

Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match.

When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section.

3. Thank you for stating in your Funding Statement:

The data used here were originally collected as part of an Economic and Social Research Council funded project ‘Workplace mental-health and wellbeing practices, outcomes and productivity’ (Grant number: ES/W010216/1). This secondary analysis project ‘Mental health at work: a longitudinal exploration of line manager training provisions and impacts on productivity, individual and organisational outcomes’ was supported by the Economic and Social Research Council [Productivity Institute: grant number: ES/V002740/1].

Please provide an amended statement that declares all the funding or sources of support (whether external or internal to your organization) received during this study, as detailed online in our guide for authors at http://journals.plos.org/plosone/s/submit-now. Please also include the statement “There was no additional external funding received for this study.” in your updated Funding Statement.

Please include your amended Funding Statement within your cover letter. We will change the online submission form on your behalf.

4. When completing the data availability statement of the submission form, you indicated that you will make your data available on acceptance. We strongly recommend all authors decide on a data sharing plan before acceptance, as the process can be lengthy and hold up publication timelines. Please note that, though access restrictions are acceptable now, your entire data will need to be made freely accessible if your manuscript is accepted for publication. This policy applies to all data except where public deposition would breach compliance with the protocol approved by your research ethics board. If you are unable to adhere to our open data policy, please kindly revise your statement to explain your reasoning and we will seek the editor's input on an exemption. Please be assured that, once you have provided your new statement, the assessment of your exemption will not hold up the peer review process.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: I Don't Know

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The paper "The Relationship between Line Manager Training in Mental Health and Organisational Outcomes" examines the effects of managerial training on organizational outcomes. While the introduction adequately establishes the research, incorporating a discussion on existing mental health training practices could improve its context. The literature review could be strengthened by including a variety of viewpoints and conflicting research according to the variables. The methodology section, centered around probit regression, could benefit from a discussion on its limitations and potential biases and it could be analyse using confirming statistical multivariate analysis methods. The results section is well-articulated and comprehensive, though adding visual data representations and concentrating data in tables can enhance understanding. The conclusions effectively recap the study’s findings; however, elaborating on their practical applications could enhance their utility in real-world settings; increasing references to previous studies are needed to confirm research assumptions. Finally, the references are comprehensive, yet updating them to include more of the latest studies would ensure the research's relevance and show the top industry standards.

Suggestions for Enhancement:

Introduction:

Literature Review:

Methodology:

Results:

Conclusions:

References:

Update and verify that all references reflect the most current research, ensuring the study's alignment with the latest developments in the field.

Reviewer #2: This is an interesting study investigating the organizational level effects of line manager trainings for mental health. The authors found a way to assess these outcomes by analysing data from an existing dataset (panel survey data from firms in England) thereby adding important information about the effects of these trainings that go beyond an assessment by the participants.

The manuscript is well written and clearly structured and adds important information to this area of research.

However, I have some comments that I would like the authors to respond to before publication:

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2024 Jul 17;19(7):e0306065. doi: 10.1371/journal.pone.0306065.r002

Author response to Decision Letter 0

16 May 2024

May, 2024.

Dear Editor,

Thank you for the opportunity to revise and resubmit our paper for PLOS ONE. We have responded to each comment below:

PONE-D-24-06886

The Relationship between Line Manager Training in Mental Health and Organisational Outcomes

Reviewer 1

The paper "The Relationship between Line Manager Training in Mental Health and Organisational Outcomes" examines the effects of managerial training on organizational outcomes. While the introduction adequately establishes the research, incorporating a discussion on existing mental health training practices could improve its context. The literature review could be strengthened by including a variety of viewpoints and conflicting research according to the variables. The methodology section, centered around probit regression, could benefit from a discussion on its limitations and potential biases and it could be analyse using confirming statistical multivariate analysis methods. The results section is well-articulated and comprehensive, though adding visual data representations and concentrating data in tables can enhance understanding. The conclusions effectively recap the study’s findings; however, elaborating on their practical applications could enhance their utility in real-world settings; increasing references to previous studies are needed to confirm research assumptions. Finally, the references are comprehensive, yet updating them to include more of the latest studies would ensure the research's relevance and show the top industry standards.

Thank you for these comments, we have responded to each suggestion below.

Introduction:

I'd like you to add insights on prevailing mental health training practices in the industry to anchor the research's significance better.

We have integrated additional discussion regarding prevailing mental health training practises and industry. The particular and most prevalent form of training is mental health first aid. Although this is commonly observed in practice, its focus enrichment is notably different and unique from line manager training interventions - which we aim to draw out in this newly added text.

Include a clear definition of your research questions, objectives, and hypothesis, perhaps in a table.

We have clearly defined our research questions and hypotheses at the end of the introduction (although we preferred to state these in the text rather than in a table, as the former is a more common approach).

Literature Review:

Broaden the scope to include diverse research and a more comprehensive array of theoretical perspectives to enrich the narrative.

We have integrated in a discussion regarding the job demand resource model to provide an additional theoretical lens in relation to this study. In particular, our aim here is to highlight the conceptual understanding between working conditions, important mental health, and performance and productivity; and the theorised role played by mental health and well-being practises in facilitating these relationships. A paucity of research exists exploring the postulated link between employees’ well-being and organisational level outcomes within this model. Therefore, we believe this study provides an important contribution to this wider theoretical discussion and validation surrounding JDR.

Explain each of your research variables and define a table of authors where you include the top publications for each variable and dimension of your study.

We have carefully considered this comment although the research team was unclear what the reviewer was asking for here.

Our Table 1 already includes each construct and its description. We understood the reviewer’s comment to be a request that we add the authors/citations for variables which are based on standardised measures. However, these items were developed by our project team and are not taken from standardised measures, and so there are no associated publications to add.

An alternative interpretation would be that the reviewer is asking for some kind of bibliometric analysis for each of the constructs measured, however this would be entirely new research (with its own aims and objectives) and is far beyond the scope of our study.

Methodology:

Thank you for this, we have included some additional information in the Methods section.

Results:

Thank you for this. We believe this information is best presented in a Table. To compare our findings with previous research and determine the unique contributions of this research to the evidence-base, we have included a new Table in the results section.

Conclusions:

Detail the practical implications of the research findings, suggesting specific training or policy changes that could be derived from the study. Describe the stakeholder who are having the best use for your findings. Describe how you achieve your results and goals.

We have included the key stakeholders to whom are findings are relevant (i.e., business owners and managers, professional bodies, charities, and policymakers). Specific implications have been added including recommendations for organisations to establish policies and practices related to workplace mental health and line managers. We have signposted to current research in which relevant evidence-based line manager training has been developed.

References:

Update and verify that all references reflect the most current research, ensuring the study's alignment with the latest developments in the field.

This has been actioned.

Reviewer 2

This is an interesting study investigating the organizational level effects of line manager trainings for mental health. The authors found a way to assess these outcomes by analysing data from an existing dataset (panel survey data from firms in England) thereby adding important information about the effects of these trainings that go beyond an assessment by the participants. The manuscript is well written and clearly structured and adds important information to this area of research.

Thank you for this positive comment.

The authors are right in pointing out (page 5 line 90) that only few studies have examined the impact and influence of LM training on organisational-level outcomes (e.g., changes to productivity, turnover rates, and absenteeism). However, also the impact of LM training on employee outcomes is often not assessed. This also applies to the “Employee-level benefits” that the authors describe have been found (page 5 line 85). It does not look like employees have been asked about these benefits. Instead, the results describe managers’ own assessment of their gained competencies, their intentions to promote mental health at work and their increased confidence to support employees with mental health problems. I understand that this often is what can be measured in studies about manager training as asking employees would often result in a much larger study. However, since the authors address this topic, I think it is important to mention that we actually know surprisingly little about the effects of LM trainings for employees, as most studies assess how the participants themselves (the managers) evaluate what they gained from having been trained. Results often show increased knowledge, confidence and good intentions, however, we most of the time do not know if this leads to actual implementing this in daily practice (for example more support for employees with mental health problems) and we know even less about if this leads to better outcomes for employees.

We agree. Our study collected data from organisational representatives so we cannot comment on employee-level outcomes as this was not the focus of our study.

However, it is an important gap in knowledge, and we have added text to the discussion:

“Fourth, most research on LM training in mental health generally explores outcomes for the manager (e.g., awareness, knowledge, confidence, skills), and our study provides novel data by focusing on outcomes at an organisational level (e.g., indices of business performance). However, few studies have explored the way in which LM training is implemented in practice, and whether (or not) this impacts on mental health at the employee-level. There is currently inconclusive evidence that leadership training impacts on employee outcomes, due to contradictory results (Aust et al, 2023). While employee outcomes were not the focus of our study, future research may seek to enhance the evidence-base relating to employee outcomes”.

Thank you for this question. The questionnaire asked participants to indicate the proportions of the specific outcomes which occurred in their organisations (For e.g., sickness absence due to mental ill health). Not all the participating organisations indicated that they experienced this, hence, the corresponding numbers were smaller. For example, to give a response to the question ‘what is the proportion of sickness absence due to mental ill-health’, the participant first had to indicate that the organisation experienced sickness absence due to mental ill health. If they did not, this question would automatically be skipped – hence resulting in a smaller number of participants. For purposes of transparency, we reported these numbers to not mislead readers into thinking that the full sample size completed these questions.

The reason for the smaller sample size here is the same as the reason given above. Either the participant reported that the organisation did not have sickness absence due to mental ill health or as you suggested, it is possible that they did not have the information and hence the question was skipped.

Pooled panel data typically combines both time series data and cross sectional data into a single dataset. As mentioned in the Methods section, strategically pooling this data together granted us greater statistical power which meant that missing data from a few points would not have a significant impact on the overall variance and mean estimates, hence eliminating the need for missing data techniques.

We have now included this as a limitation of the study.

Thank you for raising this. We have added text to the study strengths section and included the suggested reference:

“A significant strength of the study is its large sample size and diversity of organisations included. We are therefore able to report findings across sectors and sizes of organisations, including sectors in which mental ill-health is prevalent, but research evidence relating to workplace mental health interventions is limited (e.g., construction: [Greiner et al, 2022]). Another strength of the study is that around 80% of participating organisations had fewer than 50 employees; our study therefore includes many SMEs that are under-researched and often have fewer resources to be active in mental health promotion”.

An analysis on the same dataset has recently been published providing this information. We have now cited this article and referred to it in the introduction (showing the % increase from 2020-2023) and methods:

Blake H, Hassard J, Dulal-Arthur T, Wishart M, Roper S, Bourke J, Belt V, Bartle C, Pahl N, Leka S, Thomson L. Typology of employers offering line manager training for mental health. Occupational Medicine, 2024;74(3):242–250, https://doi.org/10.1093/occmed/kqae025

Attachment

Submitted filename: Response to reviewers.docx

pone.0306065.s003.docx^{(26.2KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0306065.r003

Decision Letter 1

Erum Shaikh

11 Jun 2024

The Relationship between Line Manager Training in Mental Health and Organisational Outcomes

PONE-D-24-06886R1

Dear Dr. Blake,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Erum Shaikh

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0306065.r004

Acceptance letter

Erum Shaikh

24 Jun 2024

PONE-D-24-06886R1

PLOS ONE

Dear Dr. Blake,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Erum Shaikh

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. STROBE statement: Checklist of items that should be included in reports of observational studies.

(DOCX)

pone.0306065.s001.docx^{(34.2KB, docx)}

S2 Table. Checklist for Reporting of Survey Studies (CROSS).

(DOCX)

pone.0306065.s002.docx^{(21.5KB, docx)}

Attachment

Submitted filename: Response to reviewers.docx

pone.0306065.s003.docx^{(26.2KB, docx)}

Data Availability Statement

The dataset used in this study is available from the Nottingham Research Data Management Repository (http://doi.org/10.17639/nott.7419).

[pone.0306065.ref001] 1.Mental Health at Work. Mental Health at work: Statistics. Mental Health Foundation. 2023. Available from: https://www.mentalhealth.org.uk/explore-mental-health/statistics/mental-health-work-statistics#:~:text=1%20in%206.8%20people%20experience,in%20the%20workplace%20(14.7%25). [Google Scholar]

[pone.0306065.ref002] 2.Deloitte. Poor mental health costs UK employers up to 56 billion a year. 2022. Available from: https://www2.deloitte.com/uk/en/pages/press-releases/articles/poor-mental-health-costs-uk-employers-up-to-pound-56-billion-a-year.html. [Google Scholar]

[pone.0306065.ref003] 3.National Institute for Health and Care Guidance. Mental Wellbeing at Work. NICE. March 2, 2022. Available from: https://www.nice.org.uk/guidance/ng212#:~:text=This%20guideline%20covers%20how%20to,risk%20of%20poor%20mental%20health. [PubMed] [Google Scholar]

[pone.0306065.ref004] 4.ISO. Occupational health and safety management. 2021. Available from: https://www.iso.org/standard/64283.html. [Google Scholar]

[pone.0306065.ref005] 5.Nielsen K, Yarker J, Munir F, Bültmann U. IGLOO: An integrated framework for sustainable return to work in workers with common mental disorders. Work & Stress. 2018;32(4):400–417. [Google Scholar]

[pone.0306065.ref006] 6.Richardson KM, Rothstein HR. Effects of occupational stress management intervention programs: a meta-analysis. J Occup Health Psychol. 2008;13(1):69. doi: 10.1037/1076-8998.13.1.69 [DOI] [PubMed] [Google Scholar]

[pone.0306065.ref007] 7.Montano D, Hoven H, Siegrist J. Effects of organisational-level interventions at work on employees’ health: a systematic review. BMC Public Health. 2014;14(1):1–9. doi: 10.1186/1471-2458-14-135 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0306065.ref008] 8.Fox KE, Johnson ST, Berkman LF, Sianoja M, Soh Y, Kubzansky LD, et al. Organisational- and group-level workplace interventions and their effect on multiple domains of worker well-being: A systematic review. Work Stress. 2022. [Google Scholar]

[pone.0306065.ref009] 9.Lamontagne AD, Keegel T, Louie AM, Ostry A, Landsbergis PA. A systematic review of the job-stress intervention evaluation literature, 1990–2005. Int J Occup Environ Health. 2007;13(3):268–280. doi: 10.1179/oeh.2007.13.3.268 [DOI] [PubMed] [Google Scholar]

[pone.0306065.ref010] 10.Brunner B, Igic I, Keller AC, Wieser S. Who gains the most from improving working conditions? Health-related absenteeism and presenteeism due to stress at work. Eur J Health Econ. 2019;20:1165–1180. doi: 10.1007/s10198-019-01084-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0306065.ref011] 11.Demerouti E, Bakker AB, Peeters MC, Breevaart K. New directions in burnout research. European Journal of Work and Organizational Psychology. 2021. Sep 3;30(5):686–91. [Google Scholar]

[pone.0306065.ref012] 12.Bakker AB, Demerouti E. The job demands‐resources model: State of the art. Journal of managerial psychology. 2007. Apr 3;22(3):309–28. [Google Scholar]

[pone.0306065.ref013] 13.Lesener T, Gusy B, Wolter C. The job demands-resources model: A meta-analytic review of longitudinal studies. Work & Stress. 2019. Jan 2;33(1):76–103. [Google Scholar]

[pone.0306065.ref014] 14.Kelloway EK, Barling J. Leadership development as an intervention in occupational health psychology. Work & Stress. 2010;24(3):260–279. [Google Scholar]

[pone.0306065.ref015] 15.World Health Organization. Guidelines on mental health at work. 28 September 2022. WHO, Geneva, Switzerland. Available at: https://www.who.int/publications/i/item/9789240053052. [Google Scholar]

[pone.0306065.ref016] 16.Costa, Oliveira Tiago Filipe, Francisco Miguel Correia Sampaio, Carlos Alberto da Cruz Sequeira, Isilda Maria Oliveira Carvalho Ribeiro, and Vitor Sérgio de Oliveira Parola. "Review of Mental health first aid programs." Western Journal of Nursing Research 43, no. 12 (2021): 1146–1156. [DOI] [PubMed] [Google Scholar]

[pone.0306065.ref017] 17.Richardson R., Dale H. E., Robertson L., Meader N., Wellby G., McMillan D., et al. (2023). Mental Health First Aid as a tool for improving mental health and well‐being. Cochrane Database of Systematic Reviews, (8). doi: 10.1002/14651858.CD013127.pub2 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0306065.ref018] 18.Blake H, Hassard J, Dulal-Arthur T, Wishart M, Roper S, Bourke J, et al. Typology of employers offering line manager training for mental health. Occupational Medicine, 2024;74(3):242–250, doi: 10.1093/occmed/kqae025 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0306065.ref019] 19.Martin A, Woods M, Dawkins S. How managers experience situations involving employee mental ill-health. Int J Workplace Health Manage. 2018;11(6):442–463. [Google Scholar]

[pone.0306065.ref020] 20.Gayed A, Milligan-Saville J, Nicholas J, Bryan B, Lamontagne A, Milner A, et al. Effectiveness of training workplace managers to understand and support the mental health needs of employees: a systematic review and meta-analysis. Occupational and Environmental Medicine. 2018;75:462–470. doi: 10.1136/oemed-2017-104789 [DOI] [PubMed] [Google Scholar]

[pone.0306065.ref021] 21.Milligan-Saville JS, Tan L, Gayed A, Barnes C, Madan I, Dobson M, et al. Workplace mental health training for managers and its effect on sick leave in employees: a cluster randomised controlled trial. The Lancet Psychiatry. 2017;4(11):850–858. doi: 10.1016/S2215-0366(17)30372-3 [DOI] [PubMed] [Google Scholar]

[pone.0306065.ref022] 22.Dimoff JK, Kelloway EK, Burnstein MD. Mental health awareness training (MHAT): The development and evaluation of an intervention for workplace leaders. International Journal of Stress Management. 2016;23(2):167. [Google Scholar]

[pone.0306065.ref023] 23.Thomson L, Hassard J, Frost A, Bartle C, Yarker J, Munir F, et al. Digital Training Program for Line Managers (Managing Minds at Work): Protocol for a Feasibility Pilot Cluster Randomized Controlled Trial. JMIR Res Protoc. 2023;12(1):e48758. doi: 10.2196/48758 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0306065.ref024] 24.Hassard J, Muylaert K, Namysl A, Kazenas A, Flaspoler E. Motivation for employers to carry out workplace health promotion: literature review. Luxembourg: Publications Office of the European Union, 2012. ISBN: 978-92-9191-999-4 doi: 10.2802/50267 [DOI] [Google Scholar]

[pone.0306065.ref025] 25.Law R, St George A, King L, Rissel C. Employer Perspectives of Workplace Health Promotion. 2013. [Google Scholar]

[pone.0306065.ref026] 26.von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. PLoS Med. 2007;4(10):e296. doi: 10.1371/journal.pmed.0040296 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0306065.ref027] 27.Sharma A, Minh Duc NT, Luu Lam Thang T, Nam NH, Ng SJ, Abbas KS, et al. A Consensus-Based Checklist for Reporting of Survey Studies (CROSS). J Gen Intern Med. 2021. doi: 10.1007/s11606-021-06737-1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0306065.ref028] 28.Fowler FJ Jr, Gallagher PM, Stringfellow VL, Zaslavsky AM, Thompson JW, Cleary PD. Using telephone interviews to reduce nonresponse bias to mail surveys of health plan members. Medical care. 2002. Mar 1:190–200. doi: 10.1097/00005650-200203000-00003 [DOI] [PubMed] [Google Scholar]

[pone.0306065.ref029] 29.Cleophas TJ, Zwinderman AH, Cleophas TJ, Zwinderman AH. Probit Regression, Binary Data as Response Rates (14 Tests). SPSS for Starters and 2nd Levelers. 2016:287–96. [Google Scholar]

[pone.0306065.ref030] 30.Eng J. Sample size estimation: how many individuals should be studied?. Radiology. 2003;227(2):309–13. doi: 10.1148/radiol.2272012051 [DOI] [PubMed] [Google Scholar]

[pone.0306065.ref031] 31.Rafferty A, Walthery P, King-Hele S. Analysing change over time: repeated cross-sectional and longitudinal survey data. 2015. [Google Scholar]

[pone.0306065.ref032] 32.Tooth L, Ware R, Bain C, Purdie DM, Dobson A. Quality of reporting of observational longitudinal research. Am J Epidemiol. 2005;161(3):280–288. doi: 10.1093/aje/kwi042 [DOI] [PubMed] [Google Scholar]

[pone.0306065.ref033] 33.Nazarian A, Atkinson P. How size affects organizational culture in a national context. Pensee. 2013;75(12). [Google Scholar]

[pone.0306065.ref034] 34.Jain S, Gautam A. Comparison of Performance Management Systems in Public and Private Sector: A Study of Manufacturing Organizations. Int J Manag IT Eng. 2016;6:111–128. [Google Scholar]

[pone.0306065.ref035] 35.Deloitte. Refreshing the case for investment.2023. Available from: https://www2.deloitte.com/uk/en/pages/consulting/articles/mental-health-and-employers-refreshing-the-case-for-investment.html. [Google Scholar]

[pone.0306065.ref036] 36.Hassard J, Thomson L, Blake H. Understanding the cost of mental health at work: an integrative framework. The SAGE handbook of organizational wellbeing. 1st edn. London: SAGE. 2021:9–25. [Google Scholar]

[pone.0306065.ref037] 37.Hassard J, Thomson L, Blake H. Understanding and Exploring the Cost of Poor Mental Health at Work for Organizations and Society. In: The Routledge Companion to Mental Health at Work. Routledge. 2023:77–96. [Google Scholar]

[pone.0306065.ref038] 38.Tamkin P. The Contribution of Skills to Business Performance. DfES publication RW39. August 2005. [Google Scholar]

[pone.0306065.ref039] 39.Lampe M. Empowering managers: are mental health training programmes the key to a healthier workplace? Science for work. November 2023. Available from: https://scienceforwork.com/blog/empowering-managers-are-mental-health-training-programs-the-key-to-a-healthier-workplace/. [Google Scholar]

[pone.0306065.ref040] 40.Mousseau M. Elevating Leadership: The Importance of Mental Health Training in the Workplace. 2023. Available from: https://www.ajg.com/us/news-and-insights/2023/oct/elevating-leadership-the-importance-of-mental-health-training-in-the-workplace/. [Google Scholar]

[pone.0306065.ref041] 41.Johnston V, Way K, Long MH, Wyatt M, Gibson L, Shaw WS. Supervisor competencies for supporting return to work: a mixed-methods study. J Occup Rehabil. 2015;25:3–17. doi: 10.1007/s10926-014-9511-z [DOI] [PubMed] [Google Scholar]

[pone.0306065.ref042] 42.Blake H, Hassard J, Bartle C, Thomson L. Training for line managers should focus on primary prevention of mental ill-health at work. Perspectives in Public Health. 2023. May;143(3):124–5. doi: 10.1177/17579139231157528 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0306065.ref043] 43.Blake H, Vaughan B, Bartle C, Yarker J, Munir F, Marwaha S, et al. Managing Minds at Work: Development of a Digital LM Training Program. International Journal of Environmental Research and Public Health. 2022;19. doi: 10.3390/ijerph19138006 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0306065.ref044] 44.Hassard J, Teoh K, Thomson L, & Blake H. Organizational uncertainty and stress among teachers in Hong Kong: work characteristics and organizational justice. Health Promot Int. 2017;32(5):860–870. doi: 10.1093/heapro/daw018 [DOI] [PubMed] [Google Scholar]

[pone.0306065.ref045] 45.Hassard J, Teoh KR, Visockaite G, Dewe P, Cox T. The cost of work-related stress to society: A systematic review. J Occup Health Psychol. 2018;23(1):1. doi: 10.1037/ocp0000069 [DOI] [PubMed] [Google Scholar]

[pone.0306065.ref046] 46.Stanfield C, Wishart M, Sissons P, Ferreira J, Roper S, Belt V. A baseline study for the Mental Health and Productivity Pilot project. Enterprise Research. 2020. Available from: https://www.enterpriseresearch.ac.uk/wp-content/uploads/2020/05/Employee-Wellbeing-Mental-Health-and-Productivity-in-Midlands-Firms-May-2020.pdf. [Google Scholar]

[pone.0306065.ref047] 47.Greiner BA, Leduc C, O’Brien C, Cresswell-Smith J, Rugulies R, Wahlbeck K, et al. The effectiveness of organisational-level workplace mental health interventions on mental health and wellbeing in construction workers: A systematic review and recommended research agenda. PLoS One. 2022. Nov 16;17(11):e0277114. doi: 10.1371/journal.pone.0277114 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0306065.ref048] 48.EU-OSHA. Third European Survey of Enterprises on New and Emerging Risks (ESENER 2019): Overview Report. 2019. Available from: https://osha.europa.eu/sites/default/files/esener-2019-overview-report.pdf. [Google Scholar]

[pone.0306065.ref049] 49.EU-OSHA. European Survey of Enterprises on New and Emerging Risks–Managing safety and health at work. 2010. Available from: https://osha.europa.eu/en/publications/european-survey-enterprises-new-and-emerging-risks-managing-safety-and-health-work. [Google Scholar]

[pone.0306065.ref050] 50.Aust B, Møller JL, Nordentoft M, Frydendall KB, Bengtsen E, Jensen AB, et al. How effective are organizational-level interventions in improving the psychosocial work environment, health, and retention of workers? A systematic overview of systematic reviews. Scand J Work Environ Health. 2023. Jul 1;49(5):315–329. doi: 10.5271/sjweh.4097 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

The relationship between line manager training in mental health and organisational outcomes

Juliet Hassard

Teixiera Dulal-Arthur

Jane Bourke

Maria Wishart

Stephen Roper

Vicki Belt

Stavroula Leka

Nick Pahl

Craig Bartle

Louise Thomson

Holly Blake

Roles

Abstract

Background

Aim

Methods

Results

Conclusion

Introduction

Fig 1. Job Demand Resource Model.

Materials and methods

Table 1. Operationalisation of study variables.

Results

Table 2. Characteristics of participating organisations.

RQ1: Do organisations that offer LM training in MH have more, or less, sickness absence due to mental ill-health compared with organisations that do not offer this?

Table 3. Probit regression testing the associations between LM training for MH (y/n) and organisational-level sickness absence trends due to mental ill-health.

Fig 2. Probit regression testing the associations between LM training for MH (y/n) and organisational-level sickness absence trends due to mental ill-health.

RQ2: How do organisations offering LM training in MH compare with those that do not, on organisational-level outcomes (e.g., recruitment, retention, customer services, business performance)

Table 4. Probit regression analysis testing the associations between LM training for mental health (y/n) and improved organisational-level outcomes.

Fig 3. Probit regression analysis testing the associations between LM training for MH (y/n) and improved organisational-level outcomes.

Table 5. Summary of key findings, comparison to previous research and research contributions.

Discussion

Fig 4. Adapted Chain of Impact Model [38] based on our study focus and findings.

Strengths, limitations and implications for future research

Conclusion

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Erum Shaikh

Roles

Author response to Decision Letter 0

Decision Letter 1

Erum Shaikh

Roles

Acceptance letter

Erum Shaikh

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases