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Analysis of the All of Me Mental Health Application

Addressing the importance of mental health care in the workforce Whitepaper 1

Dr Helen Cripps Dr Susan Standing Dr Ghialy Yap

School of Business and Law Edith Cowan University

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Introduction The white paper focuses on the research conducted by Edith Cowan University into the implementation of the All of Me application. All of Me was designed as an early intervention, multiple device, software solution for the workplace. The online platform educates and increases mental health literacy and it offers ‘one click away’ help and support. The application is able to track staff’s stress, anxiety and depression levels longitudinally if used on a regular basis. The platform encourages user engagement through animated scenarios, gaming techniques and self-paced adult learning principles.

Rationale How employees manage the various strains of their occupation and how organisations manage the dual demands of their employees’ psychosocial health alongside organisational goals is attracting global attention. Psychological and behavioural issues in the workplace are increasingly accepted as managerial and organisational responsibilities (Macik-Frey, Quick, & Nelson, 2007). All of Me was developed using evidence-based best practice to assist both employees and employers manage mental health in the work context. It is generally recognised that employee assistance programs for mental health issues have positive outcomes (Richmond, Pampel, Wood, & Nunes, 2016). The theoretical underpinnings of All of Me are from Occupational Health Psychology (OHP). The World Health Organisation (2014) report on mental health policies and programmes in the workplace recognises the importance of mental health in the work context and is consequently in-line with the OHP perspective.

Mental health in the work context The most common mental health disorders amongst the working population are depression, substance misuse, anxiety disorders and work-related stress; these disorders often occur together (Australian Bureau of Statistics, March, 2016; World Health Organisation, 2014). For this reason, All of Me includes an assessment of depression, anxiety and stress symptoms as well as scenario training about topics such as substance misuse, stress, work overload and relationship breakdowns.

Mental health in the work context has substantial effects on organisational performance outcomes and significant benefits and costs. Good mental health and high work performance are not simply the opposite of poor mental health and low work performance, because different mechanisms are involved. These include stressor-stress-strain versus engagement-motivation pathways put forward in the Job Demands-Resources model of workplace well-being (JD-R) (Demerouti & Bakker, 2006; Demerouti, Bakker, Nachreiner, & Schaufeli, 2001) and Psychosocial Safety Climate (PSC) model (Dollard et al., 2009; Dollard et al., 2012).

It is now being recognized that organizations have a responsibility for employees’ health and well-being. Pressure on organisations to increase performance and productivity and maintain employee well-being is leading to the redesign of human resource management practices (Guest, 2017; Kowalski & Loretto, 2017). The goal is to implement practices that promote employee well-being and build a positive employment relationship. This compliments the theory presented in the PSC model (figure 2). PSC reflects “organisational policies, practices, and procedures for the

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protection of worker psychological health and safety” (Bailey, Dollard, & Richards, 2015, pp.16). Personal health issues affect home and work situations and can be exacerbated by stress and anxiety at work. Grawitch et al. (2017) report the association between productivity loss due to mental health decline with cognitive or emotional work-related outcomes such as life-satisfaction and work engagement, but found that productivity loss due to physical health decline was not associated with these outcomes. Mental health issues such as stress, anxiety, burnout, alcohol and drug related behaviours reduce well-being and result in lost productivity through absenteeism (i.e. does not attend work) or presenteeism (i.e. attends works but cannot perform because of physical or mental illness) and low work engagement (Grawitch et al., 2017). Workers compensation and insurance claims resulting from health issues linked to job demands and stressors are a significant cost for organisations. Mental health outcomes from work related stressors have been well documented in recent Occupational Health Psychology (OHP) research (for example, see McTernan, Dollard, & LaMontagne, 2013). While there is a need for further financial modelling to determine the direct costs of mental health problems to organisations, the most recent and reputable report in Australia estimated a cost of $20 billion annually, including lost productivity and reduced labour force participation (Australian Bureau of Statistics, August, 2009). Safe Work Australia published a graphic illustrating the effects of work related mental disorders (figure 1) and highlights the need to make mental health a national and organisational priority. 43% of compensation claims are related to a reaction to job stressors, 33% of work related mental stress is from work pressures, and estimates of business and personal costs from mental health issues are estimated as $22,200 and 13.3 weeks of absenteeism per claim, amounting to $10.9 billion in lost productivity.

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Figure 1: Mental disorders in Australia (infographic). Source: Safe Work Australia (2015)

A 2014 report conducted by Beyond Blue and PwC estimates that a 2.3 return on investment (ROI) can be achieved from organisational spending on workplace mental health (PriceWaterhouseCoopers, 2014). This results from reductions in presenteeism, absenteeism and workers’ compensation claims by 33 per cent. A key assumption for the ROI is the effective implementation of an action as part of an organisation’s broader commitment to a mentally healthy workplace. Seven types of actions organisations can take are shown in table 1. The All of Me application can encourage employee involvement and lead to self-identification of issues, further engagement with work initiated programs or help-seeking from external sources.

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Action Scope of action

Worksite physical activity program

A fitness provider provides 1 hour per week of exercise outside of work hours for 20 weeks

Provided to ~50% of employees in classes of 6 – 8 people

1, 2 and 25 classes run in small, medium and large organisations

respectively

Coaching and mentoring,

e.g. cognitive behavioural-based leadership coaching

The action is provided to executives (~5% of the workforce)

The action has three components: a 360 feedback tool, a half-day leadership workshop and 4 individual coaching sessions

Mental health first aid and education

Selected employees are trained to provide support to others in the

workplace

The action provides training to ~30% of the employees who

volunteer for the training twice per year

Resilience training The action provides training to develop resilience for stressful situations

1-2 employees are instructed in becoming drivers of and instructors for

the training

The training is provided to 1, 3 and 50 people within an

organisation (small, medium and large respectively)

CBT based return-to- work programs

Occupational therapists provide training to those returning to work from long leave of absence

~5% of workforce have a long leave of absence which will be equivalent

to 1, 2 and 26 people within small, medium and large organisations

Well-being checks or health screening

The action targets people with a substance use condition in the previous 12 month period

An external service provider discusses policies, and provides a supervisory training program and a helper program

Policies are discussed on a whole-of-organisation basis

Programs are provided to ~20% of employees

Encouraging employee involvement

The action uses a web-based psychological assessment survey to assess measures relating to job control, health, absence and acceptance

The survey is provided to all employees in the organisation and reviewed on an individual level and on an aggregate basis

Table 1: Seven actions that can be implemented to create a mentally healthy workplace.

Source: PwC (2014) The cost of poor mental health extend beyond organisational cost and there is a need for reform in the Australian mental health sector (Medibank Private Limited and Nous Group, 2013) The direct costs of supporting mental health are estimated at 28.6 billion dollars (2.2 per cent of GDP). Organisational support of employees in the workplace and the provision of early intervention would have an impact on national mental health care spending.

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Evidence of different mechanisms Figure of the Jobs Demands Resources (JD-R) model

Source: Demerouti & Bakker (2011, pp.3)

Figure of the Psychosocial Safety Climate (PSC) model

Figure 2: Psychosocial Safety Climate model Source: Dollard et al. 2012, page number))

The principal that good mental health and high work performance is not simply the opposite of poor mental health and low work performance was demonstrated in a comprehensive study (Schaufeli, Leiter, & Maslach, 2009). Results of structural equation modelling found that burnout and engagement relate negatively and share 10-25% of their variances. The study also identified that burnout is mainly predicted by job demands and a lack of job resources, where available job resources solely predicted engagement. Burnout relates to health problems and turnover intention, yet engagement relates only to turnover intention. Further, the relationship between job

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demands and health problems is mediated by burnout, while the relationship between job resources and turnover intention is mediated by engagement. The authors assert that because burnout and engagement exhibit different patterns of causes and consequences, different intervention strategies should be used, depending on whether the aim is to reduce burnout or increase engagement (Schaufeli & Bakker, 2004).

Bakker, Demerouti and Sanz-Vergel (2014) review the literature on burnout and engagement and use the JD-R model to integrate their findings. Burnout generally describes a progressive loss of energy and enthusiasm, reduced personal efficacy and cynicism towards work. The Oldenburg Burnout Inventory (OLBI) incorporates dimensions of exhaustion and disengagement to measure burnout (Demerouti, Mostert, & Bakker, 2010) and the Shirom-Melamed Burnout Measure (SMBM, Shirom & Melamed 2006) assesses physical fatigue and cognitive awareness. An analysis of four measures of burnout: the MBIGS, the Burnout Measure (BM), the SMBM, and the OLBI confirms that burnout is a multifaceted construct consisting of withdrawal and exhaustion as two related but distinct aspects of burnout (Qiao & Schaufeli, 2011). The JD-R model segments all job characteristics into two underlying categories of job demands and job resources that instigate the processes of health impairment and motivation (figure 1). Job demands represent the physical, social or organisational aspects of a job requiring sustained physical or mental effort and the association with physiological and psychological costs. For example, hospital emergency department staff experience high work pressure and emotional demands. Job demands play a crucial role in the health impairment process but not in the motivational process although distinguishing between challenging and hindering job demands could affect health impairment (Bakker & Demerouti, 2017). Job resources represent the physical, psychological, social or organisational aspects of a job that are used to achieve work goals, reduce job demands and associated psychological or psychological costs, or stimulate personal growth and development. Examples of job resources are task autonomy, performance feedback, skills, and training opportunities. JD-R theory proposes that job resources influence motivation most when job demands are high. Job resources have been shown to buffer the impact of job demands on strain (Bakker, Demerouti, & Euwema, 2005).

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Figure 3: Job Demands Resources model Source: Bakker and Demerouti (2017)

Studies have investigated the links between various job demands, job resources and the associated health impairment and motivational processes. A recently updated JD-R model (figure 3) and review of JD-R literature by Bakker and Demerouti (2017) outlines the development of the theory over the last 15 years, suggests areas for investigation and discusses practical applications of the theory. The expanded model integrates research from studies that have used the JD-R perspective to include personal resources, job crafting and self-undermining as mediating factors in the stressor-strain relationships. Personal resources are the beliefs about how much control can be exerted over the environment and includes optimism, self-efficacy and self-esteem. These act in a similar way to job resources having a positive impact on work engagement and buffering the impact of job demand on strain. Motivation has a positive impact on job performance but strain has a negative impact on motivation. However job crafting involves individuals adapting their job role by seeking new challenges that enhance their capabilities and build personal and job resources. Self-undermining occurs when strain caused by job demands induces employees to put more pressure on themselves to perform and intensify feelings of exhaustion. Job demand control theory (JD-C) categorises jobs as demands with quantifiable measures such as workload and time; job control is the decision latitude embedded in the job, such as decision authority and authority to manage the skills needed to complete workload (Karasek 1989; Karasek, 1979). The level of control and demand are used to categorise the risk of strain not the psychological reaction. High strain jobs are those with high demands and low control and are conducive to ill health such as emotional exhaustion and psychosomatic problems; whereas jobs with high demands and high control (active jobs) lead to positive outcomes such as job challenge and job

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satisfaction (de Jonge, Dollard, Dormann, Le Blanc, & Houtman, 2000). Job challenges can build positive motivation or hinder personal growth. Predicting job risk has to be applied at a practical level to determine if changes in work conditions will improve the health and well-being of employees (Van der Doef & Maes, 1999) but building positive organisational attachment, and social support within the organisation, contributes to good mental health outcomes and strengthens work engagement (Avanzi, Schuh, Fraccaroli, & van Dick, 2015). The psychosocial safety climate model (PSC) (figure 2) builds upon the JD-C model to develop a predictor of mental health risk in an organisation specifically linked to organisational climate and job role. PSC identifies four domains of organisational climate as foundations for employee mental health: management support and commitment, organisational communication, organisational participation and involvement and management priority. The PSC has been shown to negatively predict psychosocial risks and employee mental health in the workplace (Maureen F. Dollard & Bakker, 2010). Bailey, Dollard and Richards (2015) measure the relationship between organisational climate, job design risk factors and depression to benchmark levels of psychosocial risk that indicate job strain. PSC was measured by surveying employees using a 12-item scale (PSC-12) consisting of 4 subscales containing three items to measure: senior management commitment, management priority and organisational communication. They conclude that a low risk of depression and job strain is indicated by a PSC score of 41. Organisations with scores below 37 should consider interventions to improve the score. This can be achieved by adopting supportive actions such as those outlined in table 1 to build an organisation committed to improving employee mental health. Managing stress at work is important to counter the effects of ongoing mental health issues, promote well-being and avoid lost productivity. Psychological detachment from work is also needed to reduce stress levels and maintain or improve individual well-being. Job demands and their association with work detachment are considered in the stressor-detachment model (Sonnentag & Fritz, 2015). Sonnentag and Fritz propose that when employees are exposed to job stressors, they find it more difficult to psychologically detach from work during nonwork hours and leisure time. Workload is proposed as a significant factor affecting detachment ability: high workload stresses over long periods of time increases the inability to detach from work and produce strain symptoms, low life satisfaction and low work engagement. They propose that job stressor-strain and work detachment can be moderated by talking and thinking positively about work problems even if this occurs outside work hours. Benefits of positive mental health in the work context are thriving employees who are well engaged with their work and colleagues, high personal performance that positively effects the organisation's performance, job satisfaction and extra-role activities (Cameron, 2012; Luthans, Youssef, & Avolio, 2007). The substantial costs and benefits associated with mental health in the work context highlight the importance for organisations to mitigate psychosocial risk factors. Protecting employees’ mental health may assist to achieve high individual and organisational outcomes as well as avoid the array of negative outcomes. However, concerning evidence suggests that employees experiencing mental disorders are reluctant to seek support.

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Help-seeking Help seeking is a complex process involving problem focus, planned behaviour and interpersonal interaction (Cornally & McCarthy, 2011). A critical component of help-seeking is problem focus and for this reason mental health literacy (MHL) is associated with the intention to seek mental health care. Lack of knowledge about symptoms, services and treatments available are common barriers to help-seeking behaviour (Choudhry, Mani, Ming, & Khan, 2016). The MHL framework (figure 4) illustrates the connections between recognition, knowledge and attitudes underpinning mental health literacy research. Improving MHL and providing social support for mental health issues will promote positive attitudes and encourage help-seeking behaviour (Jung, von Sternberg, & Davis, 2017).

Figure 4: Mental health literacy framework Source: O’Connor, Casey and Clough (2014, p. 198) Job security and workplace satisfaction were found to be additional stressors affecting help-seeking behaviour in an industry sector experiencing upheaval (Tynan et al., 2016). For the employee, not seeking help early can incur increased symptom severity (Britt & McFadden, 2012; Rickwood, Deane, & Wilson, 2007), occupational impairment, suicide, health-risk behaviours and disrupted family relationships (Tanielian et al., 2008; Zinzow, Britt, McFadden, Burnette, & Gillispie, 2012). Conversely, early prevention and treatment intervention is demonstrated to successfully reduce the long-term effects of a number of mental health problems (Rickwood et al., 2007) which highlights the importance of promoting help-seeking. Therefore, there are substantial and important reasons to actively promote employee help-seeking.

Recognition Ability to recognise specific disorders

Knowledge of how to seek information

Knowledge of risk factors

Knowledge Knowledge of causes of mental illness Mental Health Literacy (MHL)

Knowledge of self-treatment

Knowledge of professional help available

Attitudes Attitudes that promote recognition or appropriate help seeking behaviour

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Self-help based interventions can be effective in treating depression but further help may be required (Smith et al., 2017). Employee assistance services for depression, anxiety and alcohol use have generally been found to have positive effects on mental health outcomes (Richmond et al., 2016). Cognitive behaviour therapy (CBT) is a self-awareness program that can be guided by trained councillors in the workplace. CBT helps individuals modify their behaviour by recognizing how their thoughts and behaviours are related and triggered. Work-related CBT for employees on sick leave was found to decrease the number of incapacity to work days more than normal CBT and both treatments resulted in increased life satisfaction scores (Kröger et al., 2014). The “All of Me” application helps individuals identify possible mental health issues by assessing responses to the situational scenarios presented in the application. The use of information technology for personal health issues and behaviour intervention is becoming more prevalent (East & Havard, 2015). Mobile health applications are widely used on smartphones and on wearable devices such as the Apple Fitbit. Portability and convenience have made these devices and health and fitness applications popular tools for recording and tracking personal health goals. Mobile applications for behaviour mental health interventions have been shown to be useful tools to decrease levels of depression and reduce stress, but two studies on managing stress and alcohol provided conflicting results (Payne, Lister, West, & Bernhardt, 2015). There is a need for further research into behavioural interventions using online tools to determine their efficacy.

Stigma Help seeking and stigma are closely related and stigma is thought to be a barrier to help-seeking behaviour. If the social context is more supportive of mental health issues and help-seeking, the stigma associated with mental health issues should be reduced (Martin, Hobman, Howarth, & McDonald, 2016). There are contradictory findings on the strength of the connection and further work has to be done to understand how different types of stigma (public, self and structural) work together to influence mental health help-seeking behaviour (Jung et al., 2017). However, anti-stigma interventions in the workplace improves employee knowledge and strengthens supportive behaviour towards people with mental-health problems (Hanisch et al., 2016). The attitude of an employer is critical in discrimination against individuals with mental disorders. Managers have been found to discriminate against workers with mental disorders more than those with physical illness (Mendel, Kissling, Reichhart, Bühner, & Hamann, 2015). Research reveals public expectations of discrimination in Australia are high with 53.5% expecting discrimination of individuals who experience depression (Griffiths et al., 2006). The decision to disclose a mental disorder to an employer can be difficult and fear of stigmatisation has a significant impact on the decision (Toth & Dewa, 2014). An Australian survey advised that 38% of participants had not disclosed their mental disorder to their employer and cited the primary reasons for this as embarrassment, fear of discrimination, fear of job loss and receiving different treatment. As 53% had in fact experienced stigma at work, their reluctance is understandable and the decision to disclose mental disorders is not arbitrary (SANE Australia, 2011). This emphasises that mental health assessments in a work contexts should be completed confidentially.

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Taken together, the ideas expressed here indicate a three-pronged approach is needed. First, reducing stigma. Second, training employees in mental health literacy. Third, promoting help-seeking. Further, there are advantages to assessing the mental health of the workforce for strategic planning and risk/cost analysis. This approach is designed to provide early intervention for mental health issues through reducing stigma and promoting mental health literacy and help-seeking behaviour. Following this approach may assist organisations to reduce negative effects of job demands through employee burnout and associated reduced health/energy. This approach has led the development of the All of Me Workplace application. It is anticipated this application will mitigate a percent of Employee Assistance Program use, workers compensation claims for mental stress and reduced work productivity.

Format of the All of Me Application All of Me contains a number of animated modules that present escalating scenarios of psychological stressors within common workplace topics. For example: Workplace Bullying, Relationship Breakdown and Grief and Loss. The large-scale implementation of All of Me was through a large labour hire group to 3,000 staff across the Western Australian, South Australian and Northern Territory workforce. Two training modules Change & Burnout and Alcohol & Depression were made available between March and September 2017. The All of Me application was available. The labour supply company with contracted staff across all sectors including for example: mining, construction, hospitality, retail and government administration.

All of Me Implementation Timeframe

Prior to the roll out of the first training module an extensive awareness campaign was conducted for one month to introduce All of Me and to provide information about the data the software collects and its use by the organisation. The campaign was conducted through the organisations newsletter, email and social media forums. All staff had anonymous access to the software across multiple devices including computer, tablet and mobile phone. The first module “Change and Burnout” was made available from 1st March 2017 to 2nd June 2017. The second module “Alcohol and Depression” was made available from 19th June to 5th September 2017. The total completion rate was 636 results for staff across Resources (305), Transport &

Newsletter awareness campaign

March 2017

Module 1

Change & Burnout

March-June 2017

Module 2

Alcohol & Depression

June-September 2017

Whole Staff Survey

August-September

2017

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Warehousing (53), Government (35), Utilities (26), Manufacturing (33), Construction (27), Hospitality (11), Retail (5) and Other (136). Most completions occurred within the first thirty days after each module’s release. The modules were completed by 401 male workers and 235 female workers who were either blue collar (336) or white collar workers (300) with 25 workers identifying as Aboriginal or Torres Straight Islanders. The ages of staff were: 18-24 year olds (61), 25-34 year olds (206), 35-44 year olds (142), 45-54 year olds (146) and over 55 years (81).

Follow up Survey to the Launch of All of Me

As part of the rollout of the All of Me application (app), a survey tool was constructed to measure usability of the app and the benefits to staff. The survey was constructed using previously developed scales from Unified Theory of Acceptance and Use of Technology (UTAUT2) by Venkatesh, Thong et al. (2012) and questions sourced from a recent publication relating to use of online tools for mental health (Stoyanov, Hides, Kavanagh & Wilson, 2016). An invitation to participate in the survey was distributed via staff newsletters using an online link and an article that encouraged employees to review the app. As the use of the app is completely anonymous so even though the survey was distributed widely but there was no guarantee that any of the uses of All of Me would actually see and answer the survey. In order to maintain the high level of privacy required in such a sensitive research there was not linking of the app data will the survey. The survey was available for four weeks and during that time 70 people commence the survey but only 46 completed the actual survey. While this response rate may be considered low appointing, it is a product with the desire to maintain confidentiality, which is so critical in the area of mental health. This first distribution of the survey was also a pilot process and with the intention to administer further surveys as part of the ongoing development of the All of Me application. Due to the small sample size statistical analysis conducted on the data is predominantly descriptive. The following tables relate to the demographics of the respondents of whom over two thirds were male. 1. Gender

Answer % Count

Male 68.09% 32

Female 31.91% 15

Total 100% 47

The profile of the respondents showed 40% were between 25 and 34 years of age and 25% between 45 and 54. Interestingly only 13% of respondents were between 35 and 44 years of age. 2. Age group (years):

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Overwhelmingly the majority of the respondents identified themselves of Australian nationality. Of those being of another nationality they identify themselves as Indian, Philippine, New Zealand, French, Greek, Nepali and Welsh.

Age Group % Number

20-24 4.26% 2

25-29 21.28% 10

30-34 21.28% 10

35-39 8.51% 4

40-44 4.26% 2

45- 49 14.89% 7

50-54 12.77% 6

More than 55 years 12.77% 6

Total 100% 47

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3. What is your Nationality?

# Answer % Count

1 Australian 78.72% 37

2 Other (please state below) 17.02% 8

3 Rather not say 4.26% 2

Total 100% 47

Demographics: of the 67 staff that commenced the survey one was under 18 and had to be excluded from the survey. Going forward into survey 35 respondents said that they had use the application and 12 respondents said that they have not. 4. Have you used All of Me?

# % Count

3 Yes I have 74.47% 35

4 No I have not (please go to question 4) 25.53% 12

Total 100% 47

Of the respondents that did use the application, 17 used the application once and 19 use the application more than once. 5. How many times have you used All of Me?

# Answer % Count

1 Once (skip to question 5) 47.22% 17

2 Twice 41.67% 15

3 Three time 5.56% 2

4 More than 3 times 5.56% 2

Total 100% 36

Of those that used more than once the reasons for doing this included the desire to complete all the modules as requested by their manager and also the desire to go on and complete all modules within the application.

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6. Why did you use All of Me more than once?

In answer to the question: Why the respondents had never tried the All of Me application they said they had never heard of it or that they did not feel the need to use the application. One respondent commented that there are too many modules, another said that the application did not keep them engaged. 7. Why did you never try All of Me?

Did not think they need it

Can’t see how this can help me Did not have to Didn’t feel the need Haven't needed to Haven't had the need to Never needed it

Had not heard of it Never heard of it and haven't had the time Never heard of it Never heard of it

To many modules Too many modules. 1 is enough & I don't feel having 4 keeps you engaged. Because this was my first time

The responders to survey within asked a series of scale questions about the experience of using the application. The scales contained ranged from Strongly disagree (1) to Strongly Agree (7 or 10) so the higher the mean the stronger level of agreement with the statement. Some of the statements are phrased negatively and

Interested in the apps content

It was food for thought I found it interesting Because the subject interests me Validate tool before wider distribution

Want to complete all the modules

Do all modules Link problems To complete learning modules To study all modules Completed both modules Multiple modules were made available There have been 2 modules which we were asked to complete Multiple learning modules The first was to work through change & burnout. The second was to work through alcohol/depression.

Responding to Management request

Requested by manager My agency wanted to participate in All of Me I & II Because you asked me to Work asked me to Part of the company policy

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these are highlighted with a (*). The responses have been sorted with the highest mean at the top. The lower the standard deviation the more consistent answers. In relation to the effort required to use the application the respondents had a high level of agreement with the statements provided. As indicated by the table below the respondents also disagreed with the statement that it is complicated and difficult to understand hence the low mean. 8. Effort required to use All of Me (10 point scale)

Questions Mean Std Deviation

1 Learning how to use All of Me is easy for me 7.87 2.23

4 It has been easy for me to become skilful at using All of Me

7.81 2.11

3 I find All of Me easy to use 7.74 2.30

2 My interactions with All of Me are clear and understandable

7.71 2.23

10 The All of Me app has a great look about it 7.46 1.81

5 I find All of Me flexible to interact with 7.37 2.13

6 Using All of Me does not interrupt my work flow 7.30 1.97

8 The arrangement and size of buttons, icons, menus and content on the screen of the All of Me app is appropriate

7.27 2.43

9 The quality/resolution of graphics used for the All of Me app is High

7.16 2.29

7 Using All of Me is complicated and I find it difficult to understand

3.89* 3.19

The data was further analysed by gender and it was found that in relation to ease-of-use that women are more strongly agreed with the statement. This is in contrast with their lower-level disagreement with the statement relating to being difficult to understand. The female respondents had a high level high level of agreement concerning the layout of the user interface of the All of Me app but did not think of the graphic quality of the app was high. The small sample size means these results at only indicative. If further research is undertaken it may be interesting to ascertain if women respond differently to the content of than men.

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Respondents were asked about their motivations are using the application. Over 50% of the respondents either agreed or strongly agree with the statement “my supervisors encouraged me to use All of Me. Interestingly there is a reasonable level of agreement with the statement “I have found it easy to discuss my results with others” and can and the conversely the high-level disagreement with the statement “I would never tell anyone that I use”. This is encouraging considering the stigma around mental health and maybe a reflection of the way is designed to incorporate scenarios and animations that lend themselves to discussion on a social level. 9. Motivations to use All of Me (7 point scale)

Questions Mean Std Deviation

2 My supervisors have encouraged me to use All of Me 5.00 1.87

6 I have found it easy to discussed my results from All of Me with others

4.83 1.57

3 The people whose opinions I value motivate me to use All of Me

4.49 1.90

1 The people who are important to me encourage me to use All of Me

4.26 1.82

4 I consider using All of Me is a status symbol within my circle of friends and work colleagues

3.83 1.98

5 I would never tell anyone that I use All of Me 2.62* 1.58

0

1

2

3

4

5

6

7

8

9

Learning how touse AllofMe is easy

for me

Using AllofMe iscomplicated and Ifind it difficult to

understand

The arrangementand size of

buttons, icons,menus and content

on the screen ofthe AllofMe app is

appropriate

Thequality/resolution

of graphics usedfor the AllofMe app

is high

Male Mean

Female Mean

Total Mean

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The respondents found it easy to use and did not require any additional knowledge to use it. The item relating to having a necessary time had the lowest level of agreement of the four questions relating to ease of use. 10. Ease of Use of All of Me (7 point scale)

Questions Mean Std Deviation

2 I have the knowledge necessary to use All of Me 5.97 1.06

3 All of Me is compatible with other technologies I use in my life

5.69 1.08

4 All of Me fits with my style of using applications online 5.58 1.34

1 I have the time necessary to use All of Me 5.05 1.61

As part of the research, respondents were asked about their motivation to use that app and if it was habit forming. These kinds of questions are usually asked in relation to consumer technology such a social media. At this point in time the users of All of Me do not consider it to be habit forming. As the app is developed it is anticipated that the users will see the application as more than something on their “to do list” but more about maintaining their mental health and well-being. 11. Motivation and Habit (7 point scale)

Questions Mean Std Deviation

2 Using All of Me enjoyable 4.44 1.48

1 Using All of Me is fun 4.39 1.50

3 Using All of Me is very entertaining 4.17 1.54

5 Using All of Me has become natural to me 3.83 1.61

4 The use of All of Me has become a habit for me 3.44 1.50

The respondents found All of Me to be trustworthy and were not suspicious or cynical about the application. Particularly encouraging is the level of trust in the information provided by the application, as trust is one of the key components required to address mental health issues. 12. Information on All of Me (7 point scale)

# Questions Mean Std Deviation

1 I find directions provided on the use of All of Me clear and easy to follow

5.86 1.05

2 I believe my interactions on All of Me provide me with trustworthy information

5.77 1.10

3 In general, All of Me is very trustworthy 5.74 1.13

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As privacy and confidentiality are central to mental health applications so the high levels of agreement by the respondents indicate their belief that any information provided by using the application would be kept confidential and would not be released to the employer. This is suggested that this could be attributed to the design of the application and the process by which it has been deployed by the external organisation. 13. Privacy and Security of All of Me (7 point scale)

# Questions Mean Std Deviation

3 I am confident that my personal information and results from All of Me will not be released to my employer or a third party

5.65 1.44

1 I am confident that the information I provided during my use of All of Me remains secure and confidential

5.59 1.30

2 I am aware of the exact nature of information that will be collected during my use of All of Me

5.38 1.42

When asked about their intention to use in the future respondents generally showed a low level of agreement and did not see it being part of the daily life. Interestingly, when the means are compared based on gender, the female respondents had a lower level of agreement for each of the four statements. Again this may warrant some further investigation in a larger scale study to ascertain the thinking behind these responses. As there is no way of mapping the All of Me data to the survey it is hard to determine if their unwillingness to use the app in the future is due to their current good state of mental health. Perhaps further research could ask the survey respondents to give us an overall rating of their perceived current state of mental health. 14. Use of All of Me in the Future (7 point scale)

# Questions Mean Std Deviation

1 I intend to continue using All of Me in the future 4.81 1.72

3 I plan to continue to use All of Me frequently for gathering information about my well being

4.35 1.66

4 I plan to continue to use All of Me frequently to track my well-being over time.

4.30 1.71

2 I will try to use All of Me regularly in my daily life 4.14 1.66

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The final question dealt with the overall usefulness to the employer to the respondents of the application. What is interesting in these results is that the respondents have the highest level agreement with the statement “I would recommend to people that might benefit from it” and the lowest level of agreement with the statement “I feel the use of all me has improved my mental health”. This result may be due to only a small number of the respondents who were experiencing a mental health issues at the time of using the application. Conversely they acknowledge the usefulness of the tool to address these issues, as they were willing to recommend it to other people to use that maybe experiencing mental health issues at work. Respondents showed a high level agreement that they felt All of Me had increased their awareness of the importance of addressing mental health behaviour and increase their knowledge and understanding of mental health behaviour.

0

1

2

3

4

5

6

I intend tocontinue usingAllofMe in the

future

I will try to useAllofMe regularly

in my daily life

I plan to continueto use AllofMefrequently for

gatheringinformation about

my wellbeing

I plan to continueto use AllofMefrequently to

track mywellbeing over

time.

Male Mean

Female Mean

Total Mean

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15. Usefulness of All of Me (7 point scale)

# Questions Mean Std Deviation

1 I would recommend All of Me to people who might benefit from it

5.29 1.60

2 All of Me has increased my awareness of the importance of addressing mental health behaviour

5.24 1.60

3 All of Me has increases my knowledge/understanding of mental health behaviour

5.24 1.60

4 All of Me has changed my attitudes toward improving my health behaviour

5.00 1.49

6 All of Me app would encourage me to seek further help to address my mental health behaviour (if I needed it)

4.89 1.75

5 All of Me has increased my intentions/motivation to address my mental health

4.70 1.52

7 I feel my use of All of Me has improved my mental health 4.22 1.56

When the responses are analysed according to gender, the female respondents showed a higher level of agreement in relation to All of Me increasing their motivation to address mental health issues and to seek further help if required. However, when an Anova was run the difference between the means not found to be statically significant. Though the results re inconclusive the researchers suggest that further research be conducted to investigate if there are difference is based on gender in relation to mental health behaviours.

The respondents were asked if I had any more comments about the all of the app, predominantly the comments were about the construction of the app, however the feedback from one respondent that they enjoy the images/cartoons used and the humour which is encouraging.

4.2

4.4

4.6

4.8

5

5.2

5.4

5.6

AllofMe has increased myintentions/motivation to address

my mental health

AllofMe app would encourage meto seek further help to address

my mental health behaviour (if Ineeded it)

Male Mean

Female Mean

Total Mean

23

16. Do you have any further comments about the All of Me app

All these web site try to help people but the real problem is the government talking the talk wasting money but no listening what is really needed

I will check it out properly

Make it 1 module you lose interest as it goes for too long.

Really enjoyed the images/cartoons used for the app, very quirky and funny in parts. Final exit button needs to be reviewed, as what is written is incorrect relating to how to exit.

Very slow to load. Control buttons not specified. Answers are obvious. A waste of my time

Concluding Comments Stress, anxiety, depression and drug use are recognised as the most common mental health disorders (Australian Bureau of Statistics, March, 2016; World Health Organisation, 2014). These disorders are negatively affected by high job demand, burnout, a lack of job resources and personal health issues exacerbated by stress and anxiety at while at work. Mental health issues such as stress, anxiety, burnout, alcohol and drug related behaviours reduce well-being and result in lost productivity through absenteeism, presenteeism and low work engagement (Grawitch, et al., 2017). The loss of productivity and high cost of rehabilitation (13.3 weeks off work and $22,200 average costs per claim) has seen organisations seeking increased mechanisms within their well-being programmes. All of Me is a software solution that has been developed to provide organisations with an additional measure of staff stress, anxiety and depression while increasing mental health literacy and encouraging help-seeking. The software has been designed to reduce the stigma associated with poor mental health that inhibits help-seeking for support. Following the JD-R perspective, the animated refresher training scenarios have been designed to equip staff with strategies to empower them to make the changes they need in order to improve their well-being when faced with difficult and challenging work and life events (change, relationship breakdown, bullying). All of Me utilises the psychosocial safety climate model (PSC) built upon the JD-C model to develop a predictor of mental health risk in an organisation specifically linked to organisational climate and job role. All of me does this using animated scenarios and reinforced by good coping strategies. All of Me works within a positive organisational climate identified within the PSC model that encourages management support and commitment, organisational communication, organisational participation and involvement and management priority. Mobile health applications are becoming widely used by individuals accessed via smart and wearable devices. Portability and convenience have made these devices and health and fitness applications popular tools for recording and tracking personal health goals. Mobile applications for behavioural mental health interventions have

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been shown to be useful tools to decrease levels of depression and reduce stress, but two studies on managing stress and alcohol provided conflicting results (Payne, Lister, West, & Bernhardt, 2015). There is a need for further research into behavioural interventions using online tools to determine their efficacy. To this end the purpose of this evaluation was to determine the usefulness of All of Me according to the experience of the end user. Although the data collected by the survey was limited, it did provide some valuable insights. Overall, most respondents used All of Me because their employer had asked them to. It is not an unusual organisational expectation to encourage employees to participate in well-being surveys and programmes. Some users were genuinely interested in the topics and sought to learn more. Staff generally found All of Me to be easy to use (especially by female users), enjoyable, trustworthy and were not suspicious or cynical about the application. They strongly believed that any information provided in using the application would be kept confidential and would not be released to the employer. Particularly encouraging is the level of trust in the information provided by the application, as trust is one of the key components required to address mental health issues to break down help-seeking barriers. All of Me has been designed to increase mental health literacy using work examples. What is interesting in the results is that the respondents have the highest level agreement with the statement “I would recommend to people that might benefit from it” and the lowest level of agreement with the statement “I feel the use of All of Me has improved my mental health”. This result may be due to only a small number of respondents who were experiencing mental health issues at the time of using the application. Conversely, they acknowledge the usefulness of the tool to address these issues, as they were willing to recommend it to other people to use that maybe experiencing mental health issues at work. Respondents felt that All of Me had increased their awareness of the importance of addressing mental health behaviour and increased their knowledge and understanding about negative mental health behaviour and good coping strategies. When the responses are analysed according to gender, the female respondents showed a higher level of agreement in relation to All of Me increasing their motivation to address mental health issues and to seek further help if required. All of Me goes some way to meet organisational goals to train and inform staff and it appears from this evaluation that the application was generally well received. Uptake of the app is yet to become a habit, however it is expected that this could form over time with continued use. From this evaluation, All of Me would not be adequate as a stand-alone solution, it is however, an additional means to engage staff in a very sensitive topic using an alternative delivery method. It is therefore recommended that All of Me be used within a developed well-being programme. E-mental health is an emerging field of study and further research as to the impact of mental health solutions delivered via mobile devices is needed.

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References

Australian Bureau of Statistics. (August, 2009). National health survey: Summary of Results, 2007-2008 Catalog 4364.0.

Australian Bureau of Statistics. (March, 2016). National health survey: First results Catalog 4364.0.

Avanzi, L., Schuh, S. C., Fraccaroli, F., & van Dick, R. (2015). Why does organisational identification relate to reduced employee burnout? The mediating influence of social support and collective efficacy. Work & Stress, 29(1), 1-10.

Bailey, T. S., Dollard, M. F., & Richards, P. A. M. (2015). A national standard for psychosocial safety climate (PSC): PSC 41 as the benchmark for low risk of job strain and depressive symptoms. Journal of Occupational Health Psychology, 20(1), 15-26.

Bakker, A. B., & Demerouti, E. (2017). Job demands–resources theory: Taking stock and looking forward. Journal of Occupational Health Psychology, 22(3), 273-285.

Bakker, A. B., Demerouti, E., & Euwema, M. C. (2005). Job Resources Buffer the Impact of Job Demands on Burnout. Journal of Occupational Health Psychology, 10(2), 170-180.

Bakker, A. B., Demerouti, E., & Sanz-Vergel, A. I. (2014). Burnout and work engagement: The JD–R approach. Annual Review of Organisational Psychology and Organisational Behavior, 1, 389-411.

Britt, T. W., & McFadden, A. C. (2012). Understanding mental health treatment seeking in high stress occupations. Contemporary occupational health psychology: Global perspectives on research and practice, 2, 57-73.

Cameron, K. S. (2012). Positive leadership: Strategies for extraordinary performance: Berrett-Koehler Publishers.

Choudhry, F. R., Mani, V., Ming, L. C., & Khan, T. M. (2016). Beliefs and perception about mental health issues: a meta-synthesis. Neuropsychiatric Disease and Treatment, 12, 2807-2818.

Cornally, N., & McCarthy, G. (2011). Help-seeking behaviour: A concept analysis. International Journal of Nursing Practice, 17, 280-288.

de Jonge, J., Dollard, M. F., Dormann, C., Le Blanc, P. M., & Houtman, I. L. D. (2000). The demand-control model: Specific demands, specific control, and well-defined groups. International Journal of Stress Management, 7(4), 269-287.

Demerouti, E., & Bakker, A. B. (2006). Employee well-being and job performance: Where we stand and where we should go. Occupational health psychology: European perspectives on research, education and practice, 1, 83-111.

Demerouti, E., & Bakker, A. B. (2011). The job demands-resources model: Challenges for future research. SA Journal of Industrial Psychology, 37(2), 01-09.

Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001). The job demands-resources model of burnout. Journal of Applied Psychology, 86(3), 499-512..

Demerouti, E., Mostert, K., & Bakker, A. B. (2010). Burnout and work engagement: A thorough investigation of the independency of both constructs. Journal of Occupational Health Psychology, 15(3), 209-222. doi: 10.1037/a0019408

Dollard, M. F., & Bakker, A. B. (2010). Psychosocial safety climate as a precursor to conducive work environments, psychological health problems, and employee

26

engagement. Journal of Occupational and Organisational Psychology, 83(3), 579-599. doi: 10.1348/096317909X470690

Dollard, M. F., Hall, G., LaMontagne, A. D., Taylor, A. W., Winefield, A. H., Smith, P., & Bakker, A. B. (2009). Australian Workplace Barometer (AWBQ2009). Adelaide, Australia: Centre for Applied Psychological Research, University of South Australia.

Dollard, M. F., Opie, T., Lenthall, S., Wakerman, J., Knight, S., Dunn, S., . . . MacLeod, M. (2012). Psychosocial safety climate as an antecedent of work characteristics and psychological strain: A multilevel model. Work & Stress, 26(4), 385-404.

East, M. L., & Havard, B. C. (2015). Mental Health Mobile Apps: From Infusion to Diffusion in the Mental Health Social System. JMIR Mental Health, 2(1), e10. doi: 10.2196/mental.3954

Grawitch, M. J., Waldrop, J. S., Erb, K. R., Werth, P. M., & Guarino, S. N. (2017). Productivity loss due to mental and physical-health decrements: Distinctions in research and practice. Consulting Psychology Journal, 69(2), 112-129. doi: 10.1037/cpb0000089

Griffiths, K. M., Nakane, Y., Christensen, H., Yoshioka, K., Jorm, A. F., & Nakane, H. (2006). Stigma in response to mental disorders: a comparison of Australia and Japan. BMC Psychiatry, 6(6), 1-10. doi: 10.1186/1471-244X-6-21

Guest, D. E. (2017). Human resource management and employee well-being: towards a new analytic framework. Human Resource Management Journal, 27(1), 22-38. doi: 10.1111/1748-8583.12139

Hanisch, S. E., Twomey, C. D., Szeto, A. C. H., Birner, U. W., Nowak, D., & Sabariego, C. (2016). The effectiveness of interventions targeting the stigma of mental illness at the workplace: A systematic review. BMC Psychiatry, 16(1). doi: 10.1186/s12888-015-0706-4

Jung, H., von Sternberg, K., & Davis, K. (2017). The impact of mental health literacy, stigma, and social support on attitudes toward mental health help-seeking. International Journal of Mental Health Promotion, 19(5), 252-267. doi: 10.1080/14623730.2017.1345687

Karasek, R. (1989). Control in the workplace and its health-related aspects. In S. L. Sauter, J. J. Hurrell & C. L. Cooper (Eds.), Job Control and Worker Health (pp. 129-160). Chichester: Wiley.

Karasek, R. A. (1979). Job demands, job decision latitude, and mental strain: Implications for job redesign. Administrative Science Quarterly, 24(2), 285-308. doi: 10.2307/2392498

Kowalski, T. H. P., & Loretto, W. (2017). Well-being and HRM in the changing workplace. International Journal of Human Resource Management, 28(16), 2229-2255. doi: 10.1080/09585192.2017.1345205

Kröger, C., Bode, K., Wunsch, E.-M., Kliem, S., Grocholewski, A., & Finger, F. (2014). Work-related treatment for major depressive disorder and incapacity to work: Preliminary findings of a controlled, matched study. Journal of Occupational Health Psychology, 20(2), 248-258. doi: 10.1037/a0038341

Luthans, F., Youssef, C. M., & Avolio, B. J. (2007). Psychological capital: Developing the human competitive edge: Oxford University Press.

Macik-Frey, M., Quick, J. C., & Nelson, D. L. (2007). Advances in Occupational Health: From a Stressful Beginning to a Positive Future†. Journal of Management, 33(6), 809-840. doi: 10.1177/0149206307307634

Martin, A., Hobman, E., Howarth, E., & McDonald, K. (2016). Organisational support for mental health, stigmatization of employees with depression and

27

performance appraisal: A management simulation study, In Shimazu, A., Bin Nordin, R., Dollard, M., Oakman, J. (Eds.) Psychosocial Factors at Work in the Asia Pacific: From Theory to Practice (267-288).

McTernan, W., Dollard, M, & LaMontagne, A. (2013). Depression in the workplace: An economic cost analysis of depression-related productivity loss attributable to job strain and bullying. Work & Stress, 27(4), 321-338. http://dx.doi.org/10.1080/02678373.2013.846948

Medibank Private Limited and Nous Group (2013). The case for mental health reform in Australia: a review of expenditure and system design. . www.medibankhealth.com.au/Mental_Health_Reform

Mendel, R., Kissling, W., Reichhart, T., Bühner, M., & Hamann, J. (2015). Managers' reactions towards employees' disclosure of psychiatric or somatic diagnoses. Epidemiology and Psychiatric Sciences, 24(2), 146-149. doi: 10.1017/S2045796013000711

O'Connor, M., Casey, L., & Clough, B. (2014). Measuring mental health literacy - a review of scale-based measures. Journal of Mental Health, 23(4), 197-204. doi: 10.3109/09638237.2014.910646

Payne, H. E., Lister, C., West, J. H., & Bernhardt, J. M. (2015). Behavioral functionality of mobile apps in health interventions: A systematic review of the literature. JMIR mHealth uHealth, 3(1: e20). doi: 10.2196/mhealth.3335

PricewaterhouseCoopers (2014). Creating a mentally healthy workplace: Return on investment analysis. Beyond Blue & PwC. https://www.headsup.org.au/docs/default-source/resources/beyondblue_workplaceroi_finalreport_may-2014.pdf

Qiao, H., & Schaufeli, W. B. (2011). The convergent validity of four burnout measures in a Chinese sample: A confirmatory factor-analytic approach. Applied Psychology: An International Review, 60(1), 87-111. doi: 10.1111/j.1464-0597.2010.00428.x

Richmond, M. K., Pampel, F. C., Wood, R. C., & Nunes, A. P. (2016). Impact of employee assistance services on depression, anxiety, and risky alcohol use a quasi-experimental study. Journal of Occupational and Environmental Medicine, 58(7), 641-650. doi: 10.1097/JOM.0000000000000744

Rickwood, D. J., Deane, F. P., & Wilson, C. J. (2007). When and how do young people seek professional help for mental health problems? Medical Journal of Australia, 187(7), S35.

SafeWorkAustralia. (2015). Mental disorders - Work related mental disorders are a national priority. Australia: Safe Work Australia.

SANE Australia. (2011). Research bulletin 14: Working life and mental illness. Melbourne: SANE Australia.

Schaufeli, W. B., & Bakker, A. B. (2004). Job demands, job resources, and their

relationship with burnout and engagement: A multi‐sample study. Journal of

Organisational Behavior, 25(3), 293-315. Schaufeli, W. B., Leiter, M. P., & Maslach, C. (2009). Burnout: 35 years of research

and practice. Career development international, 14(3), 204-220. Smith, J., Newby, J. M., Burston, N., Murphy, M. J., Michael, S., Mackenzie, A., . . .

Andrews, G. (2017). Help from home for depression: A randomised controlled trial comparing internet-delivered cognitive behaviour therapy with bibliotherapy for depression. Internet Interventions, 9, 25-37. doi: 10.1016/j.invent.2017.05.001

28

Sonnentag, S., & Fritz, C. (2015). Recovery from job stress: The stressor-detachment model as an integrative framework. Journal of Organisational Behavior, 36, S72-S103. doi: 10.1002/job.1924

Stoyanov, S.R., Hides, L., Kavanagh, D.J., Wilson, H. (2016). Development and Validation of the User Version of the Mobile Application Rating Scale (uMARS) JMIR Mhealth Uhealth, 4(2):e72.

TANIELIAN, T., & JAYCOX, L. (Eds.). (2008). Invisible Wounds of War: Summary and Recommendations for Addressing Psychological and Cognitive Injuries. RAND Corporation. Retrieved from http://www.jstor.org/stable/10.7249/mg720-1ccf

Toth, K. E., & Dewa, C. S. (2014). Employee decision-making about disclosure of a mental disorder at work. Journal of occupational rehabilitation, 24(4), 732-746. doi: 10.1007/s10926-014-9504-y

Tynan, R.J., Considine, R., Rich, J.L., Skehan, J., Wiggers, J., Lewin, T.J., James, C., Inder, K., Baker, A.L., Kay-Lambkin, F., Perkins, D. & Kelly, B.J. (2016). Help-seeking for mental health problems by employees in the Australian Mining Industry. BMC Health Services Research, 16(1), 498.doi: 10.1186/s12913-016-1755-1

Van der Doef, M., & Maes, S. (1999). The Job Demand-Control (-Support) Model and psychological well-being: A review of 20 years of empirical research. Work & Stress, 13(2), 87-114. doi: 10.1080/026783799296084

Venkatesh, V., Thong, J.Y. and Xu, X., 2012. Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 36(1), pp. 157-178.

World Health Organisation. (2014). Mental health policies and programmes in the workplace. Geneva, WHO Press, Switzerland.

Zinzow, H. M., Britt, T. W., McFadden, A. C., Burnette, C. M., & Gillispie, S. (2012). Connecting active duty and returning veterans to mental health treatment: Interventions and treatment adaptations that may reduce barriers to care. Clinical psychology review, 32(8), 741-753.