Personalized Help-Seeking Web Application for Chinese-Speaking International University Students: Development and Usability Study.

BACKGROUND: The mental health of international students is a growing concern for education providers, students, and their families. Chinese international students have low rates of help seeking owing to language, stigma, and mental health literacy barriers. Web-based help-seeking interventions may improve the rate of help seeking among Chinese international students. OBJECTIVE: This study aimed to describe the development of a mental well-being web app providing personalized feedback and tailored psychoeducation and resources to support help seeking among international university students whose first language is Chinese and test the web application's uptake and engagement. METHODS: The bilingual MindYourHead web application contains 6 in-app assessments for various areas of mental health, and users are provided with personalized feedback on symptom severity, psychoeducation tailored to the person's symptoms and information about relevant interventions, and tailored links to external resources and mental health services. A feasibility study was conducted within a school at the University of Sydney to examine the uptake and engagement of the web application among Chinese international students and any demographic characteristics or help-seeking attitudes or intentions that were associated with its engagement. RESULTS: A total of 130 Chinese international students signed up on the web application. There was an uptake of 13.4% (122/908) in the schools' Chinese student enrollment. Most participants (76/130, 58.5%) preferred to use the web application in Chinese and used informal but not formal help for their mental health. There was considerable attrition owing to a design issue, and only 46 students gained access to the full content of the web application. Of these, 67% (31/46) of participants completed 1 or more of the in-app mental well-being assessments. The most commonly engaged in-app assessments were distress (23/31, 74%), stress (17/31, 55%), and sleep (15/31, 48%), with the majority scoring within the moderate- or high-risk level of the score range. In total, 10% (9/81) of the completed in-app assessments led to clicks to external resources or services. No demographic or help-seeking intentions or attitudes were associated with web-application engagement. CONCLUSIONS: There were promising levels of demand, uptake, and engagement with the MindYourHead web application. The web application appears to attract students who wished to access mental health information in their native language, those who had poor mental health in the past but relied on informal support, and those who were at moderate or high risk of poor mental well-being. Further research is required to explore ways to improve uptake and engagement and to test the efficacy of the web application on Chinese international students' mental health literacy, stigma, and help seeking.

Trends in Effectiveness of Organizational eHealth Interventions in Addressing Employee Mental Health: Systematic Review and Meta-analysis.

BACKGROUND: Mental health conditions are considered the leading cause of disability, sickness absence, and long-term work incapacity. eHealth interventions provide employees with access to psychological assistance. There has been widespread implementation and provision of eHealth interventions in the workplace as an inexpensive and anonymous way of addressing common mental disorders. OBJECTIVE: This updated review aimed to synthesize the literature on the efficacy of eHealth interventions for anxiety, depression, and stress outcomes in employee samples in organizational settings and evaluate whether their effectiveness has improved over time. METHODS: Systematic searches of relevant articles published from 2004 to July 2020 of eHealth intervention trials (app- or web-based) focusing on the mental health of employees were conducted. The quality and bias of all studies were assessed. We extracted means and SDs from publications by comparing the differences in effect sizes (Hedge g) in standardized mental health outcomes. We meta-analyzed these data using a random-effects model. RESULTS: We identified a tripling of the body of evidence, with 75 trials available for meta-analysis from a combined sample of 14,747 articles. eHealth interventions showed small positive effects for anxiety (Hedges g=0.26, 95% CI 0.13-0.39; P<.001), depression (Hedges g=0.26, 95% CI 0.19-0.34; P<.001), and stress (Hedges g=0.25, 95% CI 0.17-0.34; P<.001) in employees' after intervention, with similar effects seen at the medium-term follow-up. However, there was evidence of no increase in the effectiveness of these interventions over the past decade. CONCLUSIONS: This review and meta-analysis confirmed that eHealth interventions have a small positive impact on reducing mental health symptoms in employees. Disappointingly, we found no evidence that, despite the advances in technology and the enormous resources in time, research, and finance devoted to this area for over a decade, better interventions are being produced. Hopefully, these small effect sizes do not represent optimum outcomes in organizational settings. TRIAL REGISTRATION: PROSPERO CRD42020185859; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=185859.

Apprentices' Attitudes Toward Using a Mental Health Mobile App to Support Healthy Coping: Mixed Methods Study.

BACKGROUND: Apprenticeships are a common pathway for young people transitioning into the workforce. Apprentices often face many employment-related challenges and have high levels of psychological distress, drug and alcohol use, and suicidal ideation. Little is known about the attitudes of apprentices toward using smartphone apps to support their mental health and the content that would engage them. OBJECTIVE: This study explored (1) apprentices' interest in using an app to support their mental health and (2) the healthy coping strategies used to manage their mental well-being in the face of workplace challenges, in order to inform future app content. METHODS: A mixed methods study was conducted with 54 apprentices (50/54 male, 93%) with a mean age of 22.7 (SD 5.7) years. Participants completed a survey on preferred ways of using an app to support mental health. Across 8 focus groups, participants were asked to describe healthy strategies they used to cope with occupational stressors. RESULTS: Only 11% (6/54) of participants currently used a well-being app, but there was high interest in using an app to support their friends (47/54 participants, 87%) and develop self-help strategies to manage or prevent mental health issues (42/54 participants, 78%). Four major types of coping behaviors were identified: (1) social connection for disclosure, advice, and socializing; (2) pleasurable activities, such as engaging in hobbies, time-outs, and developing work-life separation; (3) cognitive approaches, including defusing from thoughts and cognitive reframing; and (4) self-care approaches, including exercise, a healthy diet, and getting adequate sleep. CONCLUSIONS: There is interest among apprentices to use an app with a positive well-being focus that helps them to develop self-management skills and support their friends. Apprentices utilized a range of healthy behaviors to cope with workplace stressors that can be incorporated into mental health apps to improve uptake and engagement. However, many of the preferred coping strategies identified are not those focused on by currently available apps, indicating the need for more targeted digital interventions for this group.

Preventing depression using a smartphone app: a randomized controlled trial.

BACKGROUND: There is evidence that depression can be prevented; however, traditional approaches face significant scalability issues. Digital technologies provide a potential solution, although this has not been adequately tested. The aim of this study was to evaluate the effectiveness of a new smartphone app designed to reduce depression symptoms and subsequent incident depression amongst a large group of Australian workers. METHODS: A randomized controlled trial was conducted with follow-up assessments at 5 weeks and 3 and 12 months post-baseline. Participants were employed Australians reporting no clinically significant depression. The intervention group (N = 1128) was allocated to use HeadGear, a smartphone app which included a 30-day behavioural activation and mindfulness intervention. The attention-control group (N = 1143) used an app which included a 30-day mood monitoring component. The primary outcome was the level of depressive symptomatology (PHQ-9) at 3-month follow-up. Analyses were conducted within an intention-to-treat framework using mixed modelling. RESULTS: Those assigned to the HeadGear arm had fewer depressive symptoms over the course of the trial compared to those assigned to the control (F3,734.7 = 2.98, p = 0.031). Prevalence of depression over the 12-month period was 8.0% and 3.5% for controls and HeadGear recipients, respectively, with odds of depression caseness amongst the intervention group of 0.43 (p = 0.001, 95% CI 0.26-0.70). CONCLUSIONS: This trial demonstrates that a smartphone app can reduce depression symptoms and potentially prevent incident depression caseness and such interventions may have a role in improving working population mental health. Some caution in interpretation is needed regarding the clinical significance due to small effect size and trial attrition.Trial Registration Australian and New Zealand Clinical Trials Registry (www.anzctr.org.au/) ACTRN12617000548336.

Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual participant data.

BACKGROUND: Internet cognitive behavioural therapy (iCBT) is a viable delivery format of CBT for depression. However, iCBT programmes include training in a wide array of cognitive and behavioural skills via different delivery methods, and it remains unclear which of these components are more efficacious and for whom. METHODS: We did a systematic review and individual participant data component network meta-analysis (cNMA) of iCBT trials for depression. We searched PubMed, PsycINFO, Embase, and the Cochrane Library for randomised controlled trials (RCTs) published from database inception to Jan 1, 2019, that compared any form of iCBT against another or a control condition in the acute treatment of adults (aged ≥18 years) with depression. Studies with inpatients or patients with bipolar depression were excluded. We sought individual participant data from the original authors. When these data were unavailable, we used aggregate data. Two independent researchers identified the included components. The primary outcome was depression severity, expressed as incremental mean difference (iMD) in the Patient Health Questionnaire-9 (PHQ-9) scores when a component is added to a treatment. We developed a web app that estimates relative efficacies between any two combinations of components, given baseline patient characteristics. This study is registered in PROSPERO, CRD42018104683. FINDINGS: We identified 76 RCTs, including 48 trials contributing individual participant data (11 704 participants) and 28 trials with aggregate data (6474 participants). The participants' weighted mean age was 42·0 years and 12 406 (71%) of 17 521 reported were women. There was suggestive evidence that behavioural activation might be beneficial (iMD -1·83 [95% credible interval (CrI) -2·90 to -0·80]) and that relaxation might be harmful (1·20 [95% CrI 0·17 to 2·27]). Baseline severity emerged as the strongest prognostic factor for endpoint depression. Combining human and automated encouragement reduced dropouts from treatment (incremental odds ratio, 0·32 [95% CrI 0·13 to 0·93]). The risk of bias was low for the randomisation process, missing outcome data, or selection of reported results in most of the included studies, uncertain for deviation from intended interventions, and high for measurement of outcomes. There was moderate to high heterogeneity among the studies and their components. INTERPRETATION: The individual patient data cNMA revealed potentially helpful, less helpful, or harmful components and delivery formats for iCBT packages. iCBT packages aiming to be effective and efficient might choose to include beneficial components and exclude ones that are potentially detrimental. Our web app can facilitate shared decision making by therapist and patient in choosing their preferred iCBT package. FUNDING: Japan Society for the Promotion of Science.

Internet-Based Cognitive Behavioral Therapy for Depression: A Systematic Review and Individual Patient Data Network Meta-analysis.

Importance: Personalized treatment choices would increase the effectiveness of internet-based cognitive behavioral therapy (iCBT) for depression to the extent that patients differ in interventions that better suit them. Objective: To provide personalized estimates of short-term and long-term relative efficacy of guided and unguided iCBT for depression using patient-level information. Data Sources: We searched PubMed, Embase, PsycInfo, and Cochrane Library to identify randomized clinical trials (RCTs) published up to January 1, 2019. Study Selection: Eligible RCTs were those comparing guided or unguided iCBT against each other or against any control intervention in individuals with depression. Available individual patient data (IPD) was collected from all eligible studies. Depression symptom severity was assessed after treatment, 6 months, and 12 months after randomization. Data Extraction and Synthesis: We conducted a systematic review and IPD network meta-analysis and estimated relative treatment effect sizes across different patient characteristics through IPD network meta-regression. Main Outcomes and Measures: Patient Health Questionnaire-9 (PHQ-9) scores. Results: Of 42 eligible RCTs, 39 studies comprising 9751 participants with depression contributed IPD to the IPD network meta-analysis, of which 8107 IPD were synthesized. Overall, both guided and unguided iCBT were associated with more effectiveness as measured by PHQ-9 scores than control treatments over the short term and the long term. Guided iCBT was associated with more effectiveness than unguided iCBT (mean difference [MD] in posttreatment PHQ-9 scores, -0.8; 95% CI, -1.4 to -0.2), but we found no evidence of a difference at 6 or 12 months following randomization. Baseline depression was found to be the most important modifier of the relative association for efficacy of guided vs unguided iCBT. Differences between unguided and guided iCBT in people with baseline symptoms of subthreshold depression (PHQ-9 scores 5-9) were small, while guided iCBT was associated with overall better outcomes in patients with baseline PHQ-9 greater than 9. Conclusions and Relevance: In this network meta-analysis with IPD, guided iCBT was associated with more effectiveness than unguided iCBT for individuals with depression, benefits were more substantial in individuals with moderate to severe depression. Unguided iCBT was associated with similar effectiveness among individuals with symptoms of mild/subthreshold depression. Personalized treatment selection is entirely possible and necessary to ensure the best allocation of treatment resources for depression.

The impact of communicating personal mental ill-health risk: A randomized controlled non-inferiority trial.

AIM: Risk algorithms predicting personal mental ill-health will form an important component of digital and personalized preventive interventions, yet it is unknown whether informing people of personal risk may cause unintended harm. This trial evaluated the comparative effect of communicating personal mental ill-health risk profiles on psychological distress. METHODS: Australian participants using a mood-monitoring app were randomly allocated to receiving their current personal mental ill-health risk profile (n = 119), their achievable personal risk profile (n = 118) or to a control group (n = 118) in which no risk information was communicated, in a non-inferiority trial design. The primary outcome was psychological distress at four-weeks as assessed on the Kessler Psychological Distress Scale. RESULTS: There was high attrition in the trial with 64% of data missing at follow up. Per-protocol (completer) analysis found that the lower bounds of the confidence intervals of the estimated mean change of the current risk (m = 0.19, 95% CI: -2.59- 2.98) and achievable risk (m = -0.09, 95% CI: -2.84 to 2.66) groups were within the non-inferiority margin of the control group's mean at follow up. Supplementary intention-to-treat analysis using Multivariate Imputation by Chained Equations (MICE) found that 98/100 imputed datasets of the current risk profile group, and all imputed datasets of the achievable risk profile group showed non-inferiority to the control group. CONCLUSIONS: This study provides preliminary support that providing personal mental health risk profiles does not lead to unacceptable worsening of distress compared to no risk feedback, although this needs to be replicated in a fully powered RCT.

Co-Designing a Web-Based Decision Aid Tool for Employees Disclosure of Mental Health Conditions: A Participatory Study Design Using Employee and Organizational Preferences.

BACKGROUND: Decisions of whether to disclose mental health conditions are extremely personal and require the consideration of multiple factors associated with the disclosure process (eg, weighing the risks and benefits). Decision aid tools help people make these complex decisions. Such an aid needs to be confidential, easily accessible, and easy to use with the potential to access the tool on multiple occasions. Web programs are well suited to meet these requirements and, if properly developed, can provide feasible, accessible, affordable, and effective workplace interventions. OBJECTIVE: This study aims to gain insights from potential end users, in this case both employees and organizations, into what type of components including language, style, and content would avoid potential stigma and ensure that elements of clear value for users would be built into a web-based decision aid tool that aims to assist employees in making decisions about the disclosure of their mental health condition at work. METHODS: A participatory design approach was used to allow developers, researchers, experts, and end users to collaborate in co-designing the tool. During the user research phase of the development of the web-based tool, a participatory design workshop approach was selected as a part of a larger study of focus groups. Australian employees and managers in rural, suburban, and urban locations participated in an exploratory qualitative study involving participatory workshops designed to elicit their perspectives and preferences for a decision aid tool. RESULTS: A total of 2 workshops were conducted with 13 participants. The majority were from a transport company (9/13, 69%), male (8/13, 62%), and employed full time (11/13, 85%). Six employees had previous experience disclosing their own mental health condition, and 7 were in a supervisory role and had previously been disclosed to. In any co-design development, there are certain trade-offs that need to be made between the views of experts, developers, end users, and the available budget. In this specific instance of a very delicate, personal decision, the end users provided valuable design insights into key areas such as language, and they were very antipathetic to a key feature, the avatar, which was thought to be desirable by experts and developers. Findings including aspects of the tool where all stakeholders were in agreement, aspects where some stakeholders disagreed and adaptations were implemented, where disagreements could not be implemented because of financial constraints, and misalignment between stakeholders and how to decide on a balance were shared. CONCLUSIONS: The co-design with a lived experience approach is useful for contributing much to the design, language, and features. The key in this study was balancing the needs of the workers and the potential impact for the managers and organizations, while ensuring legislation and regulation requirements were upheld.

The Utility of a Mental Health App in Apprentice Workers: A Pilot Study.

Background: Young people are at heightened risk for mental health problems. Apprenticeships are common pathways into the workforce at a critical developmental period. However, in some cases the working conditions for apprentices present significant challenges to mental wellness. As apprentices are unlikely to utilize traditional services, eHealth and mHealth interventions are a useful means of delivering interventions to this group. The aim of the current paper is to: (1) qualitatively explore the utility of an existing mental health app within an apprentice population; and (2) evaluate the usability, acceptability, feasibility and preliminary efficacy of a modified version of the app (HeadGear Apprentice), designed to reduce depressive symptoms in an apprentice working population. Methods: Study One: Twenty-six apprentices (aged 18-30) took part in one of eight (90-min) focus groups. Participants explored the HeadGear app, took part in group discussions, and completed uMARS questionnaires. Modifications were made to the app based on feedback. Study Two: In the follow-up pilot testing, 47 apprentices downloaded and used the modified app over 30 days. Assessment occurred online at baseline, 5-weeks, and 3-months post-baseline. Feasibility was evaluated using consent rates, adherence and attrition. Acceptability was assessed using questionnaires and a post-study interview. Depression, anxiety, well-being, and work performance scores were used to assess preliminary efficacy. Results: Overall, the app was well-received in both studies, with high self-reported scores for acceptability and utility. However, engagement-both in terms of self-report and adherence-was an issue in both studies. In Study Two, users completed approximately one-third of the app's therapeutic content, with increased usage associated with improved outcomes. This had implications for the preliminary effectiveness of the app [depression as measured by the PHQ-9 Cohen's d = 0.27 (95%CI:-0.16-0.69)]. At follow-up users reported improvements in all outcomes, but overall only change in well-being reached statistical significance [Cohen's d = -0.29 (95%CI:-0.72-0.14)]. Conclusion: Overall, findings from the two studies suggest that an eHealth tool, HeadGear Apprentice, was an acceptable and well-received intervention when adapted to young apprentices. However, questions remain regarding how to improve engagement and adherence to the program. These questions appear critical to effectiveness. The two studies also have implications for awareness raising in this population. Whilst preliminary results were encouraging, these improvements, along with a full-scale efficacy trial, are needed to better understand the utility of smartphone applications for mental health in this population. Trial registration: ACTRN12618001475235 https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375875&isReview=true.

Web-based decision aid tool for disclosure of a mental health condition in the workplace: a randomised controlled trial.

OBJECTIVES: Making decisions about disclosing a mental illness in the workplace is complicated. Decision aid tools are designed to help an individual make a specific choice. We developed a web-based decision aid to help inform decisions about disclosure for employees. This study aimed to examine the efficacy of this tool. METHOD: We conducted a randomised controlled trial with recruitment, randomisation and data collection all online. Participants had access to the intervention for 2 weeks. Assessments occurred at baseline, postintervention and 6 weeks' follow-up. The primary outcome was decisional conflict. Secondary outcomes were stage and satisfaction of decision-making and mental health symptoms. RESULTS: 107 adult employees were randomised to READY (n=53) or the control (n=54). The sample was predominantly female (83.2%). Participants using READY showed greater reduction in decisional conflict at postintervention (F(1,104)=16.8, p<0.001) (d=0.49, 95% CI 0.1 to 0.9) and follow-up (F(1,104)=23.6, p<0.001) (d=0.61, 95% CI 0.1 to 0.9). At postintervention the READY group were at a later stage of decision-making (F(1,104)=6.9, p=0.010) which was sustained, and showed a greater reduction in depressive symptoms (F(1,104)=6.5, p=0.013). Twenty-eight per cent of READY users disclosed, and reported a greater improvement in mental health than those who did not disclose. CONCLUSIONS: READY provides a confidential, flexible and effective tool to enhance employee's decision-making about disclosure. Its use led to a comparative improvement in depressive symptoms compared with the current information provided by a leading mental health non-governmental organisation, without apparent harm. READY seems worth evaluating in other settings and, if these results are replicated, scaling for wider use. TRIAL REGISTRATION NUMBER: ACTRN12618000229279.

The impact of trauma exposure on the development of PTSD and psychological distress in a volunteer fire service.

Emergency service workers (ESWs) are at increased risk of trauma-related mental disorders. However, volunteer ESWs, who comprise the majority of firefighters in Western countries, have limited access to the necessary support services for mental health problems. This study aimed to examine the impact of the level and types of trauma exposure on the development of mental disorders in a volunteer fire service. Members of an Australian volunteer fire service (N = 459) completed a cross-sectional survey. Information on the number and types of distressing critical incidents involved within the last year was collected. Validated, self-report measures were used to determine probable post-traumatic stress disorder (PTSD) and psychological distress caseness. The risk of probable PTSD was significantly higher for those with the most frequent involvement with distressing incidents and the highest levels of cumulative trauma exposure. Being trapped in a dangerous situation or being assaulted by other people, resulted in the greatest odds of developing a mental disorder. Volunteer fire service members with the highest levels of trauma exposure and involvement with particular types of critical incidents are at elevated risk of mental health problems. The implications for the provision of psychological support measures amongst volunteer emergency services are discussed.

Smartphone application for preventing depression: study protocol for a workplace randomised controlled trial.

INTRODUCTION: Depression is the leading cause of life years lost due to disability. Appropriate prevention has the potential to reduce the incidence of new cases of depression, however, traditional prevention approaches face significant scalability issues. Prevention programmes delivered by via smartphone applications provide a potential solution. The workplace is an ideal setting to roll out this form of intervention, particularly among industries that are unlikely to access traditional health initiatives and whose workplace characteristics create accessibility and portability issues. The study aims to evaluate the effectiveness of a smartphone application designed to prevent depression and improve well-being. The effectiveness of the app as a universal, selective and indicated prevention tool will also be evaluated. METHODS AND ANALYSIS: A multicentre randomised controlled trial, to determine the effectiveness of the intervention compared with an active mood monitoring control in reducing depressive symptoms (primary outcome) and the prevalence of depression at 3 months, with secondary outcomes assessing well-being and work performance. Employees from a range of industries will be invited to participate. Participants with likely current depression at baseline will be excluded. Following baseline assessment, participants, blinded to their allocation, will be randomised to receive one of two versions of the application: headgear (a 30-day mental health intervention) or a control application (mood monitoring for 30 days). Both versions of the app contain a risk calculator to provide a measure of future risk. Analyses will be conducted within an intention-to-treat framework using mixed modelling, with additional analyses conducted to compare the moderating effect of baseline risk level and depression symptom severity on the intervention's effectiveness. ETHICS AND DISSEMINATION: The current trial has received ethics approval from the University of New South Wales Human Research Ethics Committee (HC17021). Study results will be disseminated through peer-reviewed journals and conferences. TRIAL REGISTRATION NUMBER: ACTRN12617000548336; Results.

Do guided internet-based interventions result in clinically relevant changes for patients with depression? An individual participant data meta-analysis.

Little is known about clinically relevant changes in guided Internet-based interventions for depression. Moreover, methodological and power limitations preclude the identification of patients' groups that may benefit more from these interventions. This study aimed to investigate response rates, remission rates, and their moderators in randomized controlled trials (RCTs) comparing the effect of guided Internet-based interventions for adult depression to control groups using an individual patient data meta-analysis approach. Literature searches in PubMed, Embase, PsycINFO and Cochrane Library resulted in 13,384 abstracts from database inception to January 1, 2016. Twenty-four RCTs (4889 participants) comparing a guided Internet-based intervention with a control group contributed data to the analysis. Missing data were multiply imputed. To examine treatment outcome on response and remission, mixed-effects models with participants nested within studies were used. Response and remission rates were calculated using the Reliable Change Index. The intervention group obtained significantly higher response rates (OR = 2.49, 95% CI 2.17-2.85) and remission rates compared to controls (OR = 2.41, 95% CI 2.07-2.79). The moderator analysis indicated that older participants (OR = 1.01) and native-born participants (1.66) were more likely to respond to treatment compared to younger participants and ethnic minorities respectively. Age (OR = 1.01) and ethnicity (1.73) also moderated the effects of treatment on remission.Moreover, adults with more severe depressive symptoms at baseline were more likely to remit after receiving internet-based treatment (OR = 1.19). Guided Internet-based interventions lead to substantial positive treatment effects on treatment response and remission at post-treatment. Thus, such interventions may complement existing services for depression and potentially reduce the gap between the need and provision of evidence-based treatments.

Impact of Mental Health Screening on Promoting Immediate Online Help-Seeking: Randomized Trial Comparing Normative Versus Humor-Driven Feedback.

BACKGROUND: Given the widespread availability of mental health screening apps, providing personalized feedback may encourage people at high risk to seek help to manage their symptoms. While apps typically provide personal score feedback only, feedback types that are user-friendly and increase personal relevance may encourage further help-seeking. OBJECTIVE: The aim of this study was to compare the effects of providing normative and humor-driven feedback on immediate online help-seeking, defined as clicking on a link to an external resource, and to explore demographic predictors that encourage help-seeking. METHODS: An online sample of 549 adults were recruited using social media advertisements. Participants downloaded a smartphone app known as "Mindgauge" which allowed them to screen their mental wellbeing by completing standardized measures on Symptoms (Kessler 6-item Scale), Wellbeing (World Health Organization [Five] Wellbeing Index), and Resilience (Brief Resilience Scale). Participants were randomized to receive normative feedback that compared their scores to a reference group or humor-driven feedback that presented their scores in a relaxed manner. Those who scored in the moderate or poor ranges in any measure were encouraged to seek help by clicking on a link to an external online resource. RESULTS: A total of 318 participants scored poorly on one or more measures and were provided with an external link after being randomized to receive normative or humor-driven feedback. There was no significant difference of feedback type on clicking on the external link across all measures. A larger proportion of participants from the Wellbeing measure (170/274, 62.0%) clicked on the links than the Resilience (47/179, 26.3%) or Symptoms (26/75, 34.7%) measures (χ2=60.35, P<.001). There were no significant demographic factors associated with help-seeking for the Resilience or Wellbeing measures. Participants with a previous episode of poor mental health were less likely than those without such history to click on the external link in the Symptoms measure (P=.003, odds ratio [OR] 0.83, 95% CI 0.02-0.44), and younger adults were less likely to click on the link compared to older adults across all measures (P=.005, OR 0.44, 95% CI 0.25-0.78). CONCLUSIONS: This pilot study found that there was no difference between normative and humor-driven feedback on promoting immediate clicks to an external resource, suggesting no impact on online help-seeking. Limitations included: lack of personal score control group, limited measures of predictors and potential confounders, and the fact that other forms of professional help-seeking were not assessed. Further investigation into other predictors and factors that impact on help-seeking is needed. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12616000707460; https://www.anzctr.org.au/ Trial/Registration/TrialReview.aspx?id=370187 (Archived by WebCite at http://www.webcitation.org/6y8m8sVxr).

Deciding to Disclose a Mental Health Condition in Male Dominated Workplaces; A Focus-Group Study.

Objectives: Deciding to disclose a mental illness in the workplace requires thoughtful informed decision making. Decision aids are increasingly used to help people make complex decisions, but need to incorporate relevant factors for the context. This study aimed to identify factors and processes that influence decision making about such disclosure to inform the development of a disclosure decision aid tool for employees in male dominated industries. Methods: We invited 15 partner organisations in male dominated industries to facilitate the recruitment of employees who either had disclosed a mental health condition in their workplace; or occupied a position to whom employees disclosed to focus groups addressing the aims. Results: The majority of the organisations had explicit policies that employees must disclose and so were unable to be seen countenancing non-disclosure as an option. Two focus groups were conducted (n = 13) with mainly male (62%), full-time employees (85%), and both disclosed (46%) and authority (54%) groups. Six themes, all barriers, were identified as influencing decision making processes: knowledge about symptoms, and self-discrimination (internal), stigma and discrimination by others, limited managerial support, dissatisfaction with services, and/or a risk of job or financial loss (external). Conclusion: Decisions to disclose mental health conditions, even by those who had done so, appear driven entirely by consideration of negative aspects. This suggests that anti-discrimination policy, legislation, awareness campaigns, and manager training have yet to change negative perceptions, and that any decision aid tool needs to incorporate counterfactual positive aspects that appear not to be an important consideration in such male dominated workplaces. There is a disconnect between organisational policies favouring disclosure and employees favouring non-disclosure that has caused tension within the organisational culture. Decision aid tools may assist employees with an active disclosure without waiting for an event to occur, giving the control of the decision back to the employee.

Development and validation of a prediction algorithm for the onset of common mental disorders in a working population.

OBJECTIVE: Common mental disorders are the most common reason for long-term sickness absence in most developed countries. Prediction algorithms for the onset of common mental disorders may help target indicated work-based prevention interventions. We aimed to develop and validate a risk algorithm to predict the onset of common mental disorders at 12 months in a working population. METHODS: We conducted a secondary analysis of the Household, Income and Labour Dynamics in Australia Survey, a longitudinal, nationally representative household panel in Australia. Data from the 6189 working participants who did not meet the criteria for a common mental disorders at baseline were non-randomly split into training and validation databases, based on state of residence. Common mental disorders were assessed with the mental component score of 36-Item Short Form Health Survey questionnaire (score ⩽45). Risk algorithms were constructed following recommendations made by the Transparent Reporting of a multivariable prediction model for Prevention Or Diagnosis statement. RESULTS: Different risk factors were identified among women and men for the final risk algorithms. In the training data, the model for women had a C-index of 0.73 and effect size (Hedges' g) of 0.91. In men, the C-index was 0.76 and the effect size was 1.06. In the validation data, the C-index was 0.66 for women and 0.73 for men, with positive predictive values of 0.28 and 0.26, respectively Conclusion: It is possible to develop an algorithm with good discrimination for the onset identifying overall and modifiable risks of common mental disorders among working men. Such models have the potential to change the way that prevention of common mental disorders at the workplace is conducted, but different models may be required for women.

Effectiveness of eHealth interventions for reducing mental health conditions in employees: A systematic review and meta-analysis.

BACKGROUND: Many organisations promote eHealth applications as a feasible, low-cost method of addressing mental ill-health and stress amongst their employees. However, there are good reasons why the efficacy identified in clinical or other samples may not generalize to employees, and many Apps are being developed specifically for this group. The aim of this paper is to conduct the first comprehensive systematic review and meta-analysis evaluating the evidence for the effectiveness and examine the relative efficacy of different types of eHealth interventions for employees. METHODS: Systematic searches were conducted for relevant articles published from 1975 until November 17, 2016, of trials of eHealth mental health interventions (App or web-based) focused on the mental health of employees. The quality and bias of all identified studies was assessed. We extracted means and standard deviations from published reports, comparing the difference in effect sizes (Hedge's g) in standardized mental health outcomes. We meta-analysed these using a random effects model, stratified by length of follow up, intervention type, and whether the intervention was universal (unselected) or targeted to selected groups e.g. "stressed". RESULTS: 23 controlled trials of eHealth interventions were identified which overall suggested a small positive effect at both post intervention (g = 0.24, 95% CI 0.13 to 0.35) and follow up (g = 0.23, 95% CI 0.03 to 0.42). There were differential short term effects seen between the intervention types whereby Mindfulness based interventions (g = 0.60, 95% CI 0.34 to 0.85, n = 6) showed larger effects than the Cognitive Behaviour Therapy (CBT) based (g = 0.15, 95% CI 0.02 to 0.29, n = 11) and Stress Management based (g = 0.17, 95%CI -0.01 to 0.34, n = 6) interventions. The Stress Management interventions however differed by whether delivered to universal or targeted groups with a moderately large effect size at both post-intervention (g = 0.64, 95% CI 0.54 to 0.85) and follow-up (g = 0.69, 95% CI 0.06 to 1.33) in targeted groups, but no effect in unselected groups. INTERPRETATION: There is reasonable evidence that eHealth interventions delivered to employees may reduce mental health and stress symptoms post intervention and still have a benefit, although reduced at follow-up. Despite the enthusiasm in the corporate world for such approaches, employers and other organisations should be aware not all such interventions are equal, many lack evidence, and achieving the best outcomes depends upon providing the right type of intervention to the correct population.

Using different Facebook advertisements to recruit men for an online mental health study: Engagement and selection bias.

A growing number of researchers are using Facebook to recruit for a range of online health, medical, and psychosocial studies. There is limited research on the representativeness of participants recruited from Facebook, and the content is rarely mentioned in the methods, despite some suggestion that the advertisement content affects recruitment success. This study explores the impact of different Facebook advertisement content for the same study on recruitment rate, engagement, and participant characteristics. Five Facebook advertisement sets ("resilience", "happiness", "strength", "mental fitness", and "mental health") were used to recruit male participants to an online mental health study which allowed them to find out about their mental health and wellbeing through completing six measures. The Facebook advertisements recruited 372 men to the study over a one month period. The cost per participant from the advertisement sets ranged from $0.55 to $3.85 Australian dollars. The "strength" advertisements resulted in the highest recruitment rate, but participants from this group were least engaged in the study website. The "strength" and "happiness" advertisements recruited more younger men. Participants recruited from the "mental health" advertisements had worse outcomes on the clinical measures of distress, wellbeing, strength, and stress. This study confirmed that different Facebook advertisement content leads to different recruitment rates and engagement with a study. Different advertisement also leads to selection bias in terms of demographic and mental health characteristics. Researchers should carefully consider the content of social media advertisements to be in accordance with their target population and consider reporting this to enable better assessment of generalisability.