Does a Mobile Phone Depression-Screening App Motivate Mobile Phone Users With High Depressive Symptoms to Seek a Health Care Professional's Help?

The efficacy of automated feedback after internet-based depression screening (DISCOVER): an observer-masked, three-armed, randomised controlled trial in Germany

BACKGROUND

Despite the availability of effective treatments, most depressive disorders remain undetected and untreated. Internet-based depression screening combined with automated feedback of screening results could reach people with depression and lead to evidence-based care. We aimed to test the efficacy of two versions of automated feedback after internet-based screening on depression severity compared with no feedback.

METHODS

DISCOVER was an observer-masked, three-armed, randomised controlled trial in Germany. We recruited individuals (aged ≥18 years) who were undiagnosed with depression and screened positive for depression on an internet-based self-report depression rating scale (Patient Health Questionnaire-9 [PHQ-9] ≥10 points). Participants were randomly assigned 1:1:1 to automatically receive no feedback, non-tailored feedback, or tailored feedback on the depression screening result. Randomisation was stratified by depression severity (moderate: PHQ-9 score 10-14 points; severe: PHQ-9 score ≥15 points). Participants could not be masked but were kept unaware of trial hypotheses to minimise expectancy bias. The non-tailored feedback included the depression screening result, a recommendation to seek professional diagnostic advice, and brief general information about depression and its treatment. The tailored feedback included the same basic information but individually framed according to the participants' symptom profiles, treatment preferences, causal symptom attributions, health insurance, and local residence. Research staff were masked to group allocation and outcome assessment as these were done using online questionnaires. The primary outcome was change in depression severity, defined as change in PHQ-9 score 6 months after random assignment. Analyses were conducted following the intention-to-treat principle for participants with at least one follow-up visit. This trial was registered at ClinicalTrials.gov, NCT04633096.

FINDINGS

Between Jan 12, 2021, and Jan 31, 2022, 4878 individuals completed the internet-based screening. Of these, 1178 (24%) screened positive for depression (mean age 37·1 [SD 14·2] years; 824 [70%] woman, 344 [29%] men, and 10 [1%] other gender identity). 6 months after random assignment, depression severity decreased by 3·4 PHQ-9 points in the no feedback group (95% CI 2·9-4·0; within-group d 0·67; 325 participants), by 3·5 points in the non-tailored feedback group (3·0-4·0; within-group d 0·74; 319 participants), and by 3·7 points in the tailored feedback group (3·2-4·3; within-group d 0·71; 321 participants), with no significant differences among the three groups (p=0·72). The number of participants seeking help for depression or initiating psychotherapy or antidepressant treatment did not differ among study groups. The results remained consistent when adjusted for fulfilling the DSM-5-based criteria for major depressive disorder or subjective belief of having a depressive disorder. Negative effects were reported by less than 1% of the total sample 6 months after random assignment.

INTERPRETATION

Automated feedback following internet-based depression screening did not reduce depression severity or prompt sufficient depression care in individuals previously undiagnosed with but affected by depression.

FUNDING

German Research Foundation.

Asynchronous Versus Synchronous Screening for Depression and Suicidality in a Primary Health Care System: Quality Improvement Study

Background

Despite being a debilitating, costly, and potentially life-threatening condition, depression is often underdiagnosed and undertreated. Previsit Patient Health Questionnaire-9 (PHQ-9) may help primary care health systems identify symptoms of severe depression and prevent suicide through early intervention. Little is known about the impact of previsit web-based PHQ-9 on patient care and safety.

Objective

We aimed to investigate differences among patient characteristics and provider clinical responses for patients who complete a web-based (asynchronous) versus in-clinic (synchronous) PHQ-9.

Methods

This quality improvement study was conducted at 33 clinic sites across 2 health systems in Northern California from November 1, 2020, to May 31, 2021, and evaluated 1683 (0.9% of total PHQs completed) records of patients endorsing thoughts that they would be better off dead or of self-harm (question 9 in the PHQ-9) following the implementation of a depression screening program that included automated electronic previsit PHQ-9 distribution. Patient demographics and providers' clinical response (suicide risk assessment, triage nurse connection, medication management, electronic consultation with psychiatrist, and referral to social worker or psychiatrist) were compared for patients with asynchronous versus synchronous PHQ-9 completion.

Results

Of the 1683 patients (female: n=1071, 63.7%; non-Hispanic: n=1293, 76.8%; White: n=831, 49.4%), Hispanic and Latino patients were 40% less likely to complete a PHQ-9 asynchronously (odds ratio [OR] 0.6, 95% CI 0.45-0.8; P<.001). Patients with Medicare insurance were 36% (OR 0.64, 95% CI 0.51-0.79) less likely to complete a PHQ-9 asynchronously than patients with private insurance. Those with moderate to severe depression were 1.61 times more likely (95% CI 1.21-2.15; P=.001) to complete a PHQ-9 asynchronously than those with no or mild symptoms. Patients who completed a PHQ-9 asynchronously were twice as likely to complete a Columbia-Suicide Severity Rating Scale (OR 2.41, 95% CI 1.89-3.06; P<.001) and 77% less likely to receive a referral to psychiatry (OR 0.23, 95% CI 0.16-0.34; P<.001). Those who endorsed question 9 "more than half the days" (OR 1.62, 95% CI 1.06-2.48) and "nearly every day" (OR 2.38, 95% CI 1.38-4.12) were more likely to receive a referral to psychiatry than those who endorsed question 9 "several days" (P=.002).

Conclusions

Shifting depression screening from in-clinic to previsit led to a dramatic increase in PHQ-9 completion without sacrificing patient safety. Asynchronous PHQ-9 can decrease workload on frontline clinical team members, increase patient self-reporting, and elicit more intentional clinical responses from providers. Observed disparities will inform future improvement efforts.

Monitoring and responding to signals of suicidal ideation in pragmatic clinical trials: Lessons from the GRACE trial for Chronic Sickle Cell Disease Pain

Sickle cell disease (SCD) is a hemoglobin disorder and the most common genetic disorder that affects 100,000 Americans and millions worldwide. Adults living with SCD have pain so severe that it often requires opioids to keep it in control. Depression is a major global public health concern associated with an increased risk in chronic medical disorders, including in adults living with sickle cell disease (SCD). A strong relationship exists between suicidal ideation, suicide attempts, and depression. Researchers enrolling adults living with SCD in pragmatic clinical trials are obligated to design their methods to deliberately monitor and respond to symptoms related to depression and suicidal ideation. This will offer increased protection for their participants and help clinical investigators meet their fiduciary duties. This article presents a review of this sociotechnical milieu that highlights, analyzes, and offers recommendations to address ethical considerations in the development of protocols, procedures, and monitoring activities related to suicidality in depressed patients in a pragmatic clinical trial.

How adults with suspected depressive disorder experience online depression screening: A qualitative interview study

Background

While evidence on the effects and mechanisms of online depression screening is inconclusive, publicly available 'online depression tests' are already frequently used. To further a comprehensive understanding of online depression screening and evince the perspectives of those affected, we aimed to qualitatively explore how adults with undiagnosed but suspected depressive disorder experience the screening process.

Methods

This study is a qualitative follow-up of a German-wide, 3-arm, randomised controlled trial on feedback after online depression screening conducted between Jan 2021 and Sep 2022. A subsample of 26 participants with undiagnosed but suspected depressive disorder (Patient Health Questionnaire-9 ≥ 10; no depression diagnosis/treatment within the last year) were purposefully selected based on maximum variation in gender, age, and study arm. In-depth semi-structured telephone interviews (mean = 37 min) were conducted approximately six months after screening. Data were analysed within a contextualist theoretical framework using inductive reflexive thematic analysis.

Results

Participants were balanced in terms of gender (female/male, n = 15/11), age (range = 22 to 61 years), and study arm (no feedback/standard feedback/tailored feedback, n = 7/11/8). Reported experiences of online depression screening can be described as a two-step process: Step 1 is the initial reaction to the screening procedure and comprises the theme recognition of depressive symptoms: from denial to awareness. Step 2 describes a subsequent self-explorative process encompassing the themes cognitive positioning: rejection vs. acceptance, emotional reaction: between overload and empowerment, and personal activation: from reflection to action.

Conclusions

Findings indicate that online depression screening with and without feedback of results is experienced as a two-step process promoting symptom recognition and subsequent self-exploration. While few participants reported negative effects, the majority described the screening process as insightful, empowering, and activating. Future research should determine to what extent online depression screening may pose a standalone form of low-threshold support for individuals with undiagnosed depressive disorder, while focusing as well on potential negative effects.

Preliminary Clinical Outcomes of the Hello Sunday Morning Alcohol and Wellbeing Self-Assessment: Feasibility and Acceptability Study

BACKGROUND

Alcohol-related injuries and diseases are a leading cause of morbidity and mortality worldwide. Early intervention is essential given the chronic, relapsing nature of alcohol use disorders. There is significant potential for widely accessible web-based screening tools to help individuals determine where they stand in terms of alcohol use and provide support recommendations. Screening and brief interventions (SBIs) provide individuals with a stigma-free opportunity to learn and think about the potential risks of drinking and prompt help-seeking behavior by incorporating behavior change techniques. Furthermore, as excessive alcohol use and mental health problems often occur concurrently, SBIs for both conditions simultaneously can potentially address a critical gap in alcohol and mental health treatment.

OBJECTIVE

We investigated the feasibility, acceptability, and clinical outcomes of participants completing the Alcohol and Wellbeing Self-assessment (A&WS), a web-based SBI.

METHODS

The A&WS is freely available on the Hello Sunday Morning website as part of an uncontrolled observational prospective study. Feasibility was assessed based on the number of respondents who commenced and subsequently completed the A&WS. Acceptability was measured via participant feedback to determine overall satisfaction, perceived helpfulness, and likelihood of recommending the A&WS to others. Clinical outcomes were measured in two ways: (1) self-reported changes in alcohol consumption (Alcohol Use Disorders Identification Test score) or psychological distress (Kessler Psychological Distress Scale score) over time and (2) help seeking-both self-reported and immediate web-based help seeking. Preliminary baseline data collected for the first 9 months (March 2022 to December 2022) of the study were reported, including the 3-month follow-up outcomes.

RESULTS

A total of 17,628 participants commenced the A&WS, and of these, 14,419 (81.8%) completed it. Of those 14,419 who completed the A&WS, 1323 (9.18%) agreed to participate in the follow-up research. Acceptability was high, with 78.46% (1038/1323) reporting high satisfaction levels overall; 95.62% (1265/1323) found the A&WS easy to use and would recommend the tool to others. The 1-, 2-, and 3-month follow-ups were completed by 28.57% (378/1323), 21.09% (279/1323), and 17.61% (233/1323) of the participants, respectively. Significant reductions in the Alcohol Use Disorders Identification Test Consumption subscale (P<.001) and Kessler Psychological Distress Scale scores (P<.001) were observed over the 3-month follow-up period.

CONCLUSIONS

Our results suggest that the A&WS is a highly feasible and acceptable digital SBI that may support individuals in making changes to their alcohol consumption and improve their psychological well-being. In the absence of a control group, positive clinical outcomes cannot be attributed to the A&WS, which should now be subjected to a randomized controlled trial. This scalable, freely available tool has the potential to reach a large number of adults who might not otherwise access help while complementing the alcohol and mental health treatment ecosystem.

User-Centered Design of a Digitally Enabled Care Pathway in a Large Health System: Qualitative Interview Study

BACKGROUND

Major depressive disorder (MDD) is a leading cause of disability worldwide. Management of chronic conditions such as MDD can be improved by enhanced patient engagement, measurement-based care (MBC), and shared decision-making (SDM). A user-centered design approach can improve the understanding of the patient journey and care team workflows and thus aid the development of digital health care innovations optimized for the needs of patients living with MDD and their primary care teams.

OBJECTIVE

This study aims to use qualitative research methods for the user-centered design of a digitally enabled MDD care platform, PathwayPlatform, intended to enhance patient engagement, MBC, and SDM.

METHODS

Insights were gathered through 2 stages of qualitative interviews by a study team with expertise in qualitative research and user-centered design methods. Thematic analysis was used to generate an overarching understanding of a set of shared experiences, thoughts, or behaviors across a broad qualitative data set, including transcripts of interviews, to allow both inductive and deductive insights to emerge. Thematic analysis of interviews was supported by Dedoose (SocioCultural Research Consultants, LLC), a qualitative data analysis software tool that enables systematized coding. Findings and insights were presented based on code frequency, salience, and relevance to the research project.

RESULTS

In stage 1, interviews were conducted with 20 patients living with MDD and 15 health care providers from September 2018 to January 2019 to understand the experiences with and perceptions about the initial functionality of the Pathway app while also exploring the perceptions about potential additional features and functionality. Feedback about care team workflows and treatment approaches was collected in stage-2 interviews with 36 health care providers at 8 primary care sites. Inductive and deductive thematic analyses revealed several themes related to app functionality, patient-provider engagement, workflow integration, and patient education. Both patients and their care teams perceived the remote tracking of patient-reported outcomes via digital tools to be clinically useful and reliable and to promote MBC and SDM. However, there was emphasis on the need to enhance the flow of real-time data shared with the care team, improve trend visualizations, and integrate the data within the existing clinical workflow and educational programs for patients and their care teams. User feedback was incorporated into the iterative development of the Pathway app.

CONCLUSIONS

Ongoing communication with patients living with MDD and their care teams provided an opportunity for user-centric developmental iterations of the Pathway Platform. Key insights led to further development of the patient-facing and care team-facing visit preparation features, collaborative goal-setting and goal-tracking features, patient-reported outcome summaries, and trend visualizations. The result is an enhanced digital platform with the potential to improve treatment outcomes and provide patients living with MDD additional support throughout their treatment journey.

National screening for anxiety and depression in Saudi Arabia 2022

Background

Mental health disorders, such as major depressive disorder (MDD) and generalized anxiety disorder (GAD), represent a significant public health concern in Saudi Arabia. This study aims to provide a recent mental health screening prevalence, including anxiety and depression screening in the general public and to explore the associated risk factors.

Methods

A cross-sectional study was conducted, employing a phone interview survey with 6,015 participants, using a quota sampling strategy to ensure equal representation of both sexes and administrative regions. The study assessed the prevalence of MDD and GAD risk and examined demographic, socioeconomic, and lifestyle factors associated with these mental health disorders.

Results

The national prevalence of people at risk of MDD and GAD were found to be 12.7 and 12.4%, respectively. Low diagnosis and treatment rates were observed, with only 1.5 and 0.5% of participants currently diagnosed and treated for depression and anxiety, respectively. Risk factors for MDD and GAD included female sex, lower education and income levels, smoking, and waterpipe use. Protective factors included physical activity, participation in volunteering activities and the practice of daily hobbies in the last 30 days.

Conclusion

The relatively high prevalence of MDD and GAD risk and low diagnosis and treatment rates in Saudi Arabia emphasize the need for increased mental health promotion, early detection, and treatment accessibility. The study highlights the importance of addressing modifiable risk factors and fostering protective factors through targeted interventions. Future research should focus on longitudinal associations, potential mediators and moderators, and the development of culturally appropriate and evidence-based interventions to enhance mental health outcomes in the region.

Defining the Characteristics of an e-Health Tool for Suicide Primary Prevention in the General Population: The StopBlues Case in France

With over one million deaths per year in the world, suicide is a major public health problem that could be significantly reduced by effective prevention programs. E-health tools are of particular interest for primary prevention as they can address a broad population including people unaware of their own risk and provide information and help without the fear of stigma. Our main objective was to define the overall characteristics of an e-health tool for suicide primary prevention in the French general population by defining the characteristics of the IT features; the content of the information delivered; the best way to structure it; and how it should be relayed and by whom. The research was carried out through a literature review and a co-construction phase with stakeholders. Four types of strategies may guide the construction of e-health tools for suicide primary prevention: education and awareness, (self-)screening, accessing support, and mental health coping. They should be accessible on different devices to reach the most users, and language and content should be adapted to the target population and to the issue being addressed. Finally, the tool should be consistent with ethical and quality best practices. The e-health tool StopBlues was developed following those recommendations.

Digital Interventions to Enhance Readiness for Psychological Therapy: Scoping Review

BACKGROUND

Psychological therapy is an effective treatment method for mental illness; however, many people with mental illness do not seek treatment or drop out of treatment early. Increasing client uptake and engagement in therapy is key to addressing the escalating global problem of mental illness. Attitudinal barriers, such as a lack of motivation, are a leading cause of low engagement in therapy. Digital interventions to increase motivation and readiness for change hold promise as accessible and scalable solutions; however, little is known about the range of interventions being used and their feasibility as a means to increase engagement with therapy.

OBJECTIVE

This review aimed to define the emerging field of digital interventions to enhance readiness for psychological therapy and detect gaps in the literature.

METHODS

A literature search was conducted in PubMed, PsycINFO, PsycARTICLES, Scopus, Embase, ACM Guide to Computing Literature, and IEEE Xplore Digital Library from January 1, 2006, to November 30, 2021. The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) methodology was applied. Publications were included when they concerned a digitally delivered intervention, a specific target of which was enhancing engagement with further psychological treatment, and when this intervention occurred before the target psychological treatment.

RESULTS

A total of 45 publications met the inclusion criteria. The conditions included depression, unspecified general mental health, comorbid anxiety and depression, smoking, eating disorders, suicide, social anxiety, substance use, gambling, and psychosis. Almost half of the interventions (22/48, 46%) were web-based programs; the other formats included screening tools, videos, apps, and websites. The components of the interventions included psychoeducation, symptom assessment and feedback, information on treatment options and referrals, client testimonials, expectation management, and pro-con lists. Regarding feasibility, of the 16 controlled studies, 7 (44%) measuring actual behavior or action showed evidence of intervention effectiveness compared with controls, 7 (44%) found no differences, and 2 (12%) indicated worse behavioral outcomes. In general, the outcomes were mixed and inconclusive owing to variations in trial designs, control types, and outcome measures.

CONCLUSIONS

Digital interventions to enhance readiness for psychological therapy are broad and varied. Although these easily accessible digital approaches show potential as a means of preparing people for therapy, they are not without risks. The complex nature of stigma, motivation, and individual emotional responses toward engaging in treatment for mental health difficulties suggests that a careful approach is needed when developing and evaluating digital readiness interventions. Further qualitative, naturalistic, and longitudinal research is needed to deepen our knowledge in this area.

Smartphone as a Disease Screening Tool: A Systematic Review

Disease screening identifies a disease in an individual/community early to effectively prevent or treat the condition. COVID-19 has restricted hospital visits for screening and other healthcare services resulting in the disruption of screening for cancer, diabetes, and cardiovascular diseases. Smartphone technologies, coupled with built-in sensors and wireless technologies, enable the smartphone to function as a disease-screening and monitoring device with negligible additional costs and potentially higher quality results. Thus, we sought to evaluate the use of smartphone applications for disease screening and the acceptability of this technology in the medical and healthcare sectors. We followed a systematic review process using four databases, including Medline Complete, Web of Science, Embase, and Proquest. We included articles published in English examining smartphone application utilisation in disease screening. Further, we presented and discussed the primary outcomes of the research articles and their statistically significant value. The initial search yielded 1046 studies for the initial title and abstract screening. Of the 105 articles eligible for full-text screening, we selected nine studies and discussed them in detail under four main categories: an overview of the literature reviewed, participant characteristics, disease screening, and technology acceptance. According to our objective, we further evaluated the disease-screening approaches and classified them as clinically administered screening (33%, n = 3), health-worker-administered screening (33%, n = 3), and home-based screening (33%, n = 3). Finally, we analysed the technology acceptance among the users and healthcare practitioners. We observed a significant statistical relationship between smartphone applications and standard clinical screening. We also reviewed user acceptance of these smartphone applications. Hence, we set out critical considerations to provide equitable healthcare solutions without barriers when designing, developing, and deploying smartphone solutions. The findings may increase research opportunities for the evaluation of smartphone solutions as valid and reliable screening solutions.

mHealth Solutions for Mental Health Screening and Diagnosis: A Review of App User Perspectives Using Sentiment and Thematic Analysis

Mental health screening and diagnostic apps can provide an opportunity to reduce strain on mental health services, improve patient well-being, and increase access for underrepresented groups. Despite promise of their acceptability, many mental health apps on the market suffer from high dropout due to a multitude of issues. Understanding user opinions of currently available mental health apps beyond star ratings can provide knowledge which can inform the development of future mental health apps. This study aimed to conduct a review of current apps which offer screening and/or aid diagnosis of mental health conditions on the Apple app store (iOS), Google Play app store (Android), and using the m-health Index and Navigation Database (MIND). In addition, the study aimed to evaluate user experiences of the apps, identify common app features and determine which features are associated with app use discontinuation. The Apple app store, Google Play app store, and MIND were searched. User reviews and associated metadata were then extracted to perform a sentiment and thematic analysis. The final sample included 92 apps. 45.65% (n = 42) of these apps only screened for or diagnosed a single mental health condition and the most commonly assessed mental health condition was depression (38.04%, n = 35). 73.91% (n = 68) of the apps offered additional in-app features to the mental health assessment (e.g., mood tracking). The average user rating for the included apps was 3.70 (SD = 1.63) and just under two-thirds had a rating of four stars or above (65.09%, n = 442). Sentiment analysis revealed that 65.24%, n = 441 of the reviews had a positive sentiment. Ten themes were identified in the thematic analysis, with the most frequently occurring being performance (41.32%, n = 231) and functionality (39.18%, n = 219). In reviews which commented on app use discontinuation, functionality and accessibility in combination were the most frequent barriers to sustained app use (25.33%, n = 19). Despite the majority of user reviews demonstrating a positive sentiment, there are several areas of improvement to be addressed. User reviews can reveal ways to increase performance and functionality. App user reviews are a valuable resource for the development and future improvements of apps designed for mental health diagnosis and screening.

Addressing anhedonia to increase depression treatment engagement

Anhedonia, or reward system dysfunction, is associated with poorer treatment outcomes among depressed individuals. The role of anhedonia in treatment engagement, however, has not yet been explored. We review research on components of reward functioning impaired in depression, including effort valuation, reward anticipation, initial responsiveness, reward learning, reward probability, and reward delay, highlighting potential barriers to treatment engagement associated with these components. We then propose interventions to improve treatment initiation and continuation by addressing deficits in each component of reward functioning, focusing on modifications of existing evidence-based interventions to meet the needs of individuals with heightened anhedonia. We describe potential settings for these interventions and times at which they can be delivered during the process of referring individuals to mental health treatment, conducting intakes or assessments, and providing treatment. Additionally, we note the advantages of using screening processes already in place in primary care, workplace, school, and online settings to identify individuals with heightened anhedonia who may benefit from these interventions. We conclude with suggestions for future research on the impact of anhedonia on treatment engagement and the efficacy of interventions to address it. PRACTITIONER POINTS: Many depressed individuals who might benefit from treatment do not initiate it or discontinue early. One barrier to treatment engagement may be anhedonia, a core symptom of depression characterized by loss of interest or pleasure in usual activities. We describe brief interventions to improve treatment engagement in individuals with anhedonia that can be implemented during the referral process or early in treatment. We argue that interventions aiming to improve treatment engagement in depressed individuals that target anhedonia may be particularly effective.

Exploring the Association Between Physical Activity and Risk of Mental Health Disorders in Saudi Arabian Adults: Cross-sectional Study

BACKGROUND

The relationship between physical activity and mental health, especially the symptoms of major depressive disorder (MDD) and generalized anxiety disorder (GAD), has received increasing attention in recent years.

OBJECTIVE

The aim of this study was to explore the association between fulfilling the World Health Organization (WHO) global recommendations on physical activity and the risk and symptoms of MDD and GAD in the Saudi population.

METHODS

This study was a secondary analysis of data from a large nationwide cross-sectional survey conducted via phone interviews in June and July 2020. In this study, a proportional quota sampling technique was used to obtain an equal distribution of participants, stratified by age and gender, across the 13 regions of Saudi Arabia. The main mental health screening tool used for the risk of MDD was the Patient Health Questionnaire-9 (PHQ-9). Risk of GAD was measured using the Generalized Anxiety Disorder-7 (GAD-7) scale. Participants self-reported whether they fulfill the WHO global recommendations on (1) moderate-intensity aerobic physical activity (MIPA) and (2) vigorous-intensity aerobic physical activity (VIPA). The results were then analyzed based on the following two categories: fulfilling the WHO global recommendations or not.

RESULTS

The data analysis included 8333 participants recruited in the main study between June and July 2020. The response rate was 81.45% (8333/10,231). Of them, 50.3% (4192/8333) were female, and the mean age was 36.5 years, with a median age of 36 years and a range from 18 to 90 years. The average total PHQ-9 score was 5.61, and the average total GAD-7 score was 4.18. For men, the average total PHQ-9 and GAD-7 scores were associated with fulfilling recommendations for MIPA; however, there were no associations for VIPA in both sexes. Fulfilling the WHO's recommendations for MIPA was associated with considerably fewer depressive symptoms in six of the nine items in the PHQ-9. Moreover, fulfilling recommendations for MIPA was associated with considerably fewer anxiety symptoms in six of the seven items in the GAD-7. However, fulfilling recommendations for VIPA was significantly associated with more depressive symptoms in one of the PHQ-9 items ("Thoughts that you would be better off dead or thoughts of hurting yourself in some way;" P<.001).

CONCLUSIONS

This study has shown that fulfilling guidelines on MIPA is associated with less overall risk of MDD and GAD in males and fewer depressive and anxiety symptoms generally in a nonclinical population. In the general population, an increase in MIPA may improve well-being and general mental health.

Saudi Arabia Mental Health Surveillance System (MHSS): mental health trends amid COVID-19 and comparison with pre-COVID-19 trends

Background: The impact of the COVID-19 pandemic on populations' mental health has started to emerge. Objectives: To describe the mental health trends of the risk of major depressive disorder (MDD) and generalized anxiety disorder (GAD) between May and August 2020. It also compares the results with pre-COVID-19 results and identifies risk factors associated with increased likelihood of being at risk of MDD and GAD. Method: This study utilizes repeated cross-sectional design, at national-level coverage of mental health screenings via computer-assisted phone interviews conducted in four waves monthly (between May and August 2020). Arabic-speaking adults from Saudi Arabia were recruited via a random phone list. The questionnaire includes the Arabic version of the Patient Health Questionnaire (PHQ-9) and the General Anxiety Disorder-7 (GAD-7). Pre-COVID-19 comparison was done using the PHQ-2 score to allow for comparison with a previous and similar national study conducted in 2018. Results: Across the four waves, 16,513 participants completed the interviews, with an overall response rate of 81.3%. The weighted national prevalence of people at risk of MDD was 14.9% overall, and 13.8%, 13.6%, 16.8%, and 15.3% in Waves 1, 2, 3, and 4, respectively. The weighted national prevalence of people at risk of GAD was 11.4%, overall, and 10.9%, 10.7%, 12.4%, and 11.7% in Waves 1, 2, 3, and 4, respectively. The weighted national proportion of individuals who were at risk of MDD and GAD at the same time was 7.4% overall. The risk of MDD on PHQ-2 increased by 71.2%, from 12.5% in 2018 to 21.4% in 2020. Conclusions: The risks of MDD and GAD in this study are relatively high. These results can help decision makers to understand the impact of the COVID-19 pandemic on the population's mental health and the most-impacted subgroups.

Impact of a Web-Based Psychiatric Assessment on the Mental Health and Well-Being of Individuals Presenting With Depressive Symptoms: Longitudinal Observational Study

BACKGROUND

Web-based assessments of mental health concerns hold great potential for earlier, more cost-effective, and more accurate diagnoses of psychiatric conditions than that achieved with traditional interview-based methods.

OBJECTIVE

The aim of this study was to assess the impact of a comprehensive web-based mental health assessment on the mental health and well-being of over 2000 individuals presenting with symptoms of depression.

METHODS

Individuals presenting with depressive symptoms completed a web-based assessment that screened for mood and other psychiatric conditions. After completing the assessment, the study participants received a report containing their assessment results along with personalized psychoeducation. After 6 and 12 months, participants were asked to rate the usefulness of the web-based assessment on different mental health-related outcomes and to self-report on their recent help-seeking behavior, diagnoses, medication, and lifestyle changes. In addition, general mental well-being was assessed at baseline and both follow-ups using the Warwick-Edinburgh Mental Well-being Scale (WEMWBS).

RESULTS

Data from all participants who completed either the 6-month or the 12-month follow-up (N=2064) were analyzed. The majority of study participants rated the study as useful for their subjective mental well-being. This included talking more openly (1314/1939, 67.77%) and understanding one's mental health problems better (1083/1939, 55.85%). Although most participants (1477/1939, 76.17%) found their assessment results useful, only a small proportion (302/2064, 14.63%) subsequently discussed them with a mental health professional, leading to only a small number of study participants receiving a new diagnosis (110/2064, 5.33%). Among those who were reviewed, new mood disorder diagnoses were predicted by the digital algorithm with high sensitivity (above 70%), and nearly half of the participants with new diagnoses also had a corresponding change in medication. Furthermore, participants' subjective well-being significantly improved over 12 months (baseline WEMWBS score: mean 35.24, SD 8.11; 12-month WEMWBS score: mean 41.19, SD 10.59). Significant positive predictors of follow-up subjective well-being included talking more openly, exercising more, and having been reviewed by a psychiatrist.

CONCLUSIONS

Our results suggest that completing a web-based mental health assessment and receiving personalized psychoeducation are associated with subjective mental health improvements, facilitated by increased self-awareness and subsequent use of self-help interventions. Integrating web-based mental health assessments within primary and/or secondary care services could benefit patients further and expedite earlier diagnosis and effective treatment.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/18453.

Patient and physician perspectives of a smartphone application for depression: a qualitative study

BACKGROUND

Despite an increasing number of smartphone apps, such therapeutic tools have not yet consistently demonstrated their efficacy and many suffer from low retention rates. To ensure the development of efficient apps associated with high adherence, we aimed to identify, through a user-centred design approach, patient and physician expectations of a hypothetical app dedicated to depression.

METHODS

We conducted semi-structured interviews with physicians (psychiatrists and general practitioners) and patients who had experienced a major depressive episode during the last 12 months using the focus group method. The interviews were audio recorded, transcribed and analysed using qualitative content analysis to define codes, categories and emergent themes.

RESULTS

A total of 26 physicians and 24 patients were included in the study. The focus groups showed balanced sex and age distributions. Most participants owned a smartphone (83.3% of patients, 96.1% of physicians) and were app users (79.2% of patients and 96.1% of physicians). The qualitative content analysis revealed 3 main themes: content, operating characteristics and barriers to the use of the app. Expected content included the data collected by the app, aiming to provide information about the patient, data provided by the app, gathering psychoeducation elements, therapeutic tools and functionalities to help with the management of daily life and features expected for this tool. The "operating characteristics" theme gathered aims considered for the app, its potential target users, considered modalities of use and considerations around its accessibility and security of use. Finally, barriers to the use of the app included concerns about potential app users, its accessibility, safety, side-effects, utility and functioning. All themes and categories were the same for patients and physicians.

CONCLUSIONS

Physician and patient expectations of a hypothetical smartphone app dedicated to depression are high and confirmed the important role it could play in depression care. The key points expected by the users for such a tool are an easy and intuitive use and a personalised content. They are also waiting for an app that gives information about depression, offers a self-monitoring functionality and helps them in case of emergency.

Screening accuracy of a 14-day smartphone ambulatory assessment of depression symptoms and mood dynamics in a general population sample: Comparison with the PHQ-9 depression screening

Introduction

Major depression affects over 300 million people worldwide, but cases are often detected late or remain undetected. This increases the risk of symptom deterioration and chronification. Consequently, there is a high demand for low threshold but clinically sound approaches to depression detection. Recent studies show a great willingness among users of mobile health apps to assess daily depression symptoms. In this pilot study, we present a provisional validation of the depression screening app Moodpath. The app offers a 14-day ambulatory assessment (AA) of depression symptoms based on the ICD-10 criteria as well as ecologically momentary mood ratings that allow the study of short-term mood dynamics.

Materials and methods

N = 113 Moodpath users were selected through consecutive sampling and filled out the Patient Health Questionnaire (PHQ-9) after completing 14 days of AA with 3 question blocks (morning, midday, and evening) per day. The psychometric properties (sensitivity, specificity, accuracy) of the ambulatory Moodpath screening were assessed based on the retrospective PHQ-9 screening result. In addition, several indicators of mood dynamics (e.g. average, inertia, instability), were calculated and investigated for their individual and incremental predictive value using regression models.

Results

We found a strong linear relationship between the PHQ-9 score and the AA Moodpath depression score (r = .76, p < .001). The app-based screening demonstrated a high sensitivity (.879) and acceptable specificity (.745). Different indicators of mood dynamics covered substantial amounts of PHQ-9 variance, depending on the number of days with mood data that were included in the analyses.

Discussion

AA and PHQ-9 shared a large proportion of variance but may not measure exactly the same construct. This may be due to the differences in the underlying diagnostic systems or due to differences in momentary and retrospective assessments. Further validation through structured clinical interviews is indicated. The results suggest that ambulatory assessed mood indicators are a promising addition to multimodal depression screening tools. Improving app-based AA screenings requires adapted screening algorithms and corresponding methods for the analysis of dynamic processes over time.

The CopeNYP program: A model for brief treatment of psychological distress among healthcare workers and hospital staff

In the midst of the Spring 2020 initial surge of the COVID-19 pandemic in New York, members of the Psychiatry Department of Weill Cornell Medicine/NewYork-Presbyterian Hospital rapidly created and implemented a brief, behavioral skills-based intervention program, "CopeNYP", to address the immediate mental health needs of the employees of the hospital and medical school. We describe the development, implementation and evolution of this telehealth-delivered program staffed primarily by in-house clinical psychologists, postdoctoral fellows, pre-doctoral interns and counselors who were redeployed or volunteered their time to provide urgent support for employees. We discuss the challenges and lessons learned in providing brief, skills-based psychological interventions for employees subjected to chronic stress. As the impact of the pandemic became prolonged, employees faced compounding stressors including social isolation, fear of infection, grief and loss, and sequelae of COVID-19-related illness combined with work-related demands. Our goal is to present our program design, implementation, and utilization as a blueprint for other institutions that would like to develop an evidence-based clinician-staffed psychological intervention program to support ongoing employee mental health needs.

Screening for Depression in Mobile Devices Using Patient Health Questionnaire-9 (PHQ-9) Data: A Diagnostic Meta-Analysis via Machine Learning Methods

PURPOSE

Depression is a symptom commonly encountered in primary care; however, it is often not detected by doctors. Recently, disease diagnosis and treatment approaches have been attempted using smart devices. In this study, instrumental effectiveness was confirmed with the diagnostic meta-analysis of studies that demonstrated the diagnostic effectiveness of PHQ-9 for depression using mobile devices.

PATIENTS AND METHODS

We found all published and unpublished studies through EMBASE, MEDLINE, MEDLINE In-Process, and PsychINFO up to March 26, 2021. We performed a meta-analysis by including 1099 subjects in four studies. We performed a diagnostic meta-analysis according to the PHQ-9 cut-off score and machine learning algorithm techniques. Quality assessment was conducted using the QUADAS-2 tool. Data on the sensitivity and specificity of the studies included in the meta-analysis were extracted in a standardized format. Bivariate and summary receiver operating characteristic (SROC) curve were constructed using the metandi, midas, metabias, and metareg functions of the Stata algorithm meta-analysis words.

RESULTS

Using four studies out of the 5476 papers searched, a diagnostic meta-analysis of the PHQ-9 scores of 1099 people diagnosed with depression was performed. The pooled sensitivity and specificity were 0.797 (95% CI = 0.642-0.895) and 0.85 (95% CI = 0.780-0.900), respectively. The diagnostic odds ratio was 22.16 (95% CI = 7.273-67.499). Overall, a good balance was maintained, and no heterogeneity or publication bias was presented.

CONCLUSION

Through various machine learning algorithm techniques, it was possible to confirm that PHQ-9 depression screening in mobiles is an effective diagnostic tool when integrated into a diagnostic meta-analysis.

Mobile health applications for mental illnesses: An Asian context

Advances in digital technologies have created unprecedented opportunities to assess and improve health behavior and health outcomes. Evidence indicates that a majority of the world's population, including traditionally underserved populations and low- and middle-income countries, has access to mobile technologies (phones, tablets, mobile devices). Given the widespread access to mobile technology worldwide, health behavior-change tools delivered on mobile platforms enable broader reach and scalability of evidence-based assessment and interventions, especially for addressing the growing burden of mental health disorders globally. The purpose of this article was to present a qualitative review of mobile mental health applications in an Asian context. We searched on-line databases and included 22 articles in this review. We have identified mobile health applications that address eight categories of mental illnesses. These applications were developed in only six countries and regions in Asia. Future studies from more diverse countries for diverse cultures should be conducted to examine the advantages and disadvantages of mobile health technology.

A Mental Health Surveillance System for the General Population During the COVID-19 Pandemic: Protocol for a Multiwave Cross-sectional Survey Study

Background

The COVID-19 outbreak can potentially be categorized as a traumatic event. Public health surveillance is one of the cornerstones of public health practice, and it empowers decision makers to lead and manage public health crises and programs more effectively by providing timely and useful evidence.

Objective

This paper presents the protocol for a study that aims to identify, track, and monitor trends in the population in Saudi Arabia at risk of major depressive disorders and anxiety during the COVID-19 pandemic.

Methods

This study utilizes continuous, cross-sectional, national-level mental health screening via computer-assisted phone interviews, conducted in four waves on a monthly basis (between May and August 2020). Arabic-speaking adults, aged ≥18 years, and living in Saudi Arabia were recruited via a random phone list. This surveillance system used the proportional quota sampling technique to achieve an equal distribution of participants, stratified by age and gender, and region, within and across the 13 administrative regions of Saudi Arabia. A sample size of 4056 participants per wave was calculated to achieve enough power to detect changes in mental health status. The questionnaire includes the Arabic version of the Patient Health Questionnaire-9 (PHQ-9) to measure depressive symptoms and the General Anxiety Disorder-7 (GAD-7) to measure anxiety. In addition, it will collect data on sociodemographic variables and potential risk factors.

Results

Study recruitment began in May 2020. The data analysis was completed in October 2020, and the final report is expected to be published by the end of December 2020.

Conclusions

Monitoring the population’s mental health status during the COVID-19 pandemic will inform decision makers of any potential deterioration in mental health on a national level and among subgroups, including across regions, age groups, and gender groups. It will allow decision makers to recognize issues and intervene sooner. It will also provide valuable scientific data to help understand the effects of epidemics and pandemics on mental health. As far as we know, this is the only study that attempts to monitor the mental health status of the general population on a monthly basis.

International Registered Report Identifier (IRRID)

DERR1-10.2196/23748

The Association Between App-Administered Depression Assessments and Suicidal Ideation in User Comments: Retrospective Observational Study

Background

Many people use apps to help understand and manage their depression symptoms. App-administered questionnaires for the symptoms of depression, such as the Patient Health Questionnaire-9, are easy to score and implement in an app, but may not be accompanied by essential resources and access needed to provide proper support and avoid potential harm.

Objective

Our primary goal was to evaluate the differences in risks and helpfulness associated with using an app to self-diagnose depression, comparing assessment-only apps with multifeatured apps. We also investigated whether, what, and how additional app features may mitigate potential risks.

Methods

In this retrospective observational study, we identified apps in the Google Play store that provided a depression assessment as a feature and had at least five user comments. We separated apps into two categories based on those having only a depression assessment versus those that offered additional supportive features. We conducted theoretical thematic analyses over the user reviews, with thematic coding indicating the helpfulness of the app, the presence of suicidal ideation, and how and why the apps were used. We compared the results across the two categories of apps and analyzed the differences using chi-square statistical tests.

Results

We evaluated 6 apps; 3 provided only a depression assessment (assessment only), and 3 provided features in addition to self-assessment (multifeatured). User comments for assessment-only apps indicated significantly more suicidal ideation or self-harm (n=31, 9.4%) compared to comments for multifeatured apps (n=48, 2.3%; X²₁=43.88, P<.001). Users of multifeatured apps were over three times more likely than assessment-only app users to comment in favor of the app’s helpfulness, likely due to features like mood tracking, journaling, and informational resources (n=56, 17% vs n=1223, 59% respectively; X²₁=200.36, P<.001). The number of users under the age of 18 years was significantly higher among assessment-only app users (n=40, 12%) than multifeatured app users (n=9, 0.04%; X²₁=189.09, P<.001).

Conclusions

Apps that diagnose depression by self-assessment without context or other supportive features are more likely to be used by those under 18 years of age and more likely to be associated with increased user distress and potential harm. Depression self-assessments in apps should be implemented with caution and accompanied by evidence-based capabilities that establish proper context, increase self-empowerment, and encourage users to seek clinical diagnostics and outside help.

Identification of Alcohol Risk Drinking Behaviour in Pregnancy Using a Web-Based Questionnaire: Large-Scale Implementation in Antenatal Care

Aims

This study aimed to examine the feasibility of a web-based questionnaire when collecting information on alcohol consumption in pregnancy to identify women with risk drinking behaviour, and to describe factors associated with risk drinking behaviour, and the use of specialized care for prenatal risk drinking.

Methods

In 2413 women referred to antenatal care at Odense University Hospital, Denmark, April–October 2018, self-reported alcohol intake was retrieved from a web-based questionnaire. Replies were screened for risk drinking behaviour: current intake of ≥7 drinks/week, ≥3 binge drinking episodes (intake of ≥5 drinks on a single occasion) in pregnancy, binge drinking after recognition of pregnancy and/or a TWEAK-score ≥ 2 points. Women with risk drinking behaviour were called to clarify the need for specialized care. A summary of the interview was obtained from the medical records.

Results

Overall, 2168 (90%) completed the questionnaire. Of 2097 women providing information on alcohol intake, 77 (4%) had risk drinking behaviour. Risk drinking was associated with higher alcohol intake prior to pregnancy, spontaneous conception, younger age, nulliparity and higher level of physical activity in pregnancy. Amongst 47 women with risk drinking behaviour reached by phone, five (11%, 95% CI 4–23%) accepted examinations of the child by paediatrician and child psychologist, and &lt;3 (not further specified due to small numbers) were referred to specialized antenatal care.

Conclusions

A web-based questionnaire was feasible when collecting information on alcohol consumption in pregnancy to identify risk drinking behaviour. Women with risk drinking behaviour had a low acceptance of referral to specialized care.

Making Self-Management Mobile Health Apps Accessible to People With Disabilities: Qualitative Single-Subject Study

Background

Over the past decade, a large number of mobile health (mHealth) apps have been created to help individuals to better manage their own health. However, very few of these mHealth apps were specifically designed for people with disabilities, and only a few of them have been assessed for accessibility for people with disabilities. As a result, people with disabilities have difficulties using many of these mHealth apps.

Objective

The objective of this study was to identify an approach that can be generally applied to improve the accessibility of mHealth apps.

Methods

We recruited 5 study participants with a primary diagnosis of cerebral palsy or spinal cord injury. All the participants had fine motor impairment or lack of dexterity, and hence, they had difficulties using some mHealth apps. These 5 study participants were first asked to use multiple modules in the client app of a novel mHealth system (iMHere 2.0), during which their performance was observed. Interviews were conducted post use to collect study participants’ desired accessibility features. These accessibility features were then implemented into the iMHere 2.0 client app as customizable options. The 5 participants were asked to use the same modules in the app again, and their performance was compared with that in the first round. A brief interview and a questionnaire were then performed at the end of the study to collect the 5 participants’ comments and impression of the iMHere 2.0 app in general and of the customizable accessibility features.

Results

Study results indicate that the study participants on their first use of the iMHere 2.0 client app experienced various levels of difficulty consistent with the severity of their lack of dexterity. Their performance was improved after their desired accessibility features were added into the app, and they liked the customizable accessibility features. These participants also expressed an interest in using this mHealth system for their health self-management tasks.

Conclusions

The accessibility features identified in this study improved the accessibility of the mHealth app for people with dexterity issues. Our approach for improving mHealth app accessibility may also be applied to other mHealth apps to make those apps accessible to people with disabilities.

Touchscreen typing pattern analysis for remote detection of the depressive tendency

Depressive disorder (DD) is a mental illness affecting more than 300 million people worldwide, whereas social stigma and subtle, variant symptoms impede diagnosis. Psychomotor retardation is a common component of DD with a negative impact on motor function, usually reflected on patients' routine activities, including, nowadays, their interaction with mobile devices. Therefore, such interactions constitute an enticing source of information towards unsupervised screening for DD symptoms in daily life. In this vein, this paper proposes a machine learning-based method for discriminating between subjects with depressive tendency and healthy controls, as denoted by self-reported Patient Health Questionnaire-9 (PHQ-9) compound scores, based on typing patterns captured in-the-wild. The latter consisted of keystroke timing sequences and typing metadata, passively collected during natural typing on touchscreen smartphones by 11/14 subjects with/without depressive tendency. Statistical features were extracted and tested in univariate and multivariate classification pipelines to reach a decision on subjects' status. The best-performing pipeline achieved an AUC = 0.89 (0.72-1.00; 95% Confidence Interval) and 0.82/0.86 sensitivity/specificity, with the outputted probabilities significantly correlating (>0.60) with the respective PHQ-9 scores. This work adds to the findings of previous research associating typing patterns with psycho-motor impairment and contributes to the development of an unobtrusive, high-frequency monitoring of depressive tendency in everyday living.

Response Time as an Implicit Self-Schema Indicator for Depression Among Undergraduate Students: Preliminary Findings From a Mobile App-Based Depression Assessment

Background

Response times to depressive symptom items in a mobile-based depression screening instrument has potential as an implicit self-schema indicator for depression but has yet to be determined; the instrument was designed to readily record depressive symptoms experienced on a daily basis. In this study, the well-validated Korean version of the Center for Epidemiologic Studies Depression Scale-Revised (K-CESD-R) was adopted.

Objective

The purpose of this study was to investigate the relationship between depression severity (ie, explicit measure: total K-CESD-R Mobile scores) and the latent trait of interest in schematic self-referent processing of depressive symptom items (ie, implicit measure: response times to items in the K-CESD-R Mobile scale). The purpose was to investigate this relationship among undergraduate students who had never been diagnosed with, but were at risk for, major depressive disorder (MDD) or comorbid MDD with other neurological or psychiatric disorders.

Methods

A total of 70 participants—36 males (51%) and 34 females (49%)—aged 19-29 years (mean 22.66, SD 2.11), were asked to complete both mobile and standard K-CESD-R assessments via their own mobile phones. The mobile K-CESD-R sessions (binary scale: yes or no) were administered on a daily basis for 2 weeks. The standard K-CESD-R assessment (5-point scale) was administered on the final day of the 2-week study period; the assessment was delivered via text message, including a link to the survey, directly to participants’ mobile phones.

Results

A total of 5 participants were excluded from data analysis. The result of polynomial regression analysis showed that the relationship between total K-CESD-R Mobile scores and the reaction times to the depressive symptom items was better explained by a quadratic trend—F (2, 62)=21.16, P<.001, R²=.41—than by a linear trend—F (1, 63)=25.43, P<.001, R²=.29. It was further revealed that the K-CESD-R Mobile app had excellent internal consistency (Cronbach alpha=.94); at least moderate concurrent validity with other depression scales, such as the Korean version of the Quick Inventory for Depressive Symptomatology-Self Report (ρ=.38, P=.002) and the Patient Health Questionnaire-9 (ρ=.48, P<.001); a high adherence rate for all participants (65/70, 93%); and a high follow-up rate for 10 participants whose mobile or standard K-CESD-R score was 13 or greater (8/10, 80%).

Conclusions

As hypothesized, based on a self-schema model for depression that represented both item and person characteristics, the inverted U-shaped relationship between the explicit and implicit self-schema measures for depression showed the potential of an organizational breakdown; this also showed the potential for a subsequent return to efficient processing of schema-consistent information along a continuum, ranging from nondepression through mild depression to severe depression. Further, it is expected that the updated K-CESD-R Mobile app can play an important role in encouraging people at risk for depression to seek professional follow-up for mental health care.

Risk Assessment for Parents Who Suspect Their Child Has Autism Spectrum Disorder: Machine Learning Approach

Background

Parents are likely to seek Web-based communities to verify their suspicions of autism spectrum disorder markers in their child. Automated tools support human decisions in many domains and could therefore potentially support concerned parents.

Objective

The objective of this study was to test the feasibility of assessing autism spectrum disorder risk in parental concerns from Web-based sources, using automated text analysis tools and minimal standard questioning.

Methods

Participants were 115 parents with concerns regarding their child’s social-communication development. Children were 16- to 30-months old, and 57.4% (66/115) had a family history of autism spectrum disorder. Parents reported their concerns online, and completed an autism spectrum disorder-specific screener, the Modified Checklist for Autism in Toddlers-Revised, with Follow-up (M-CHAT-R/F), and a broad developmental screener, the Ages and Stages Questionnaire (ASQ). An algorithm predicted autism spectrum disorder risk using a combination of the parent's text and a single screening question, selected by the algorithm to enhance prediction accuracy.

Results

Screening measures identified 58% (67/115) to 88% (101/115) of children at risk for autism spectrum disorder. Children with a family history of autism spectrum disorder were 3 times more likely to show autism spectrum disorder risk on screening measures. The prediction of a child’s risk on the ASQ or M-CHAT-R was significantly more accurate when predicted from text combined with an M-CHAT-R question selected (automatically) than from the text alone. The frequently automatically selected M-CHAT-R questions that predicted risk were: following a point, make-believe play, and concern about deafness.

Conclusions

The internet can be harnessed to prescreen for autism spectrum disorder using parental concerns by administering a few standardized screening questions to augment this process.

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).

Transitioning from learning healthcare systems to learning health care communities

The learning healthcare system (LHS) model framework has three core, foundational components. These include an infrastructure for health-related data capture, care improvement targets and a supportive policy environment. Despite progress in advancing and implementing LHS approaches, low levels of participation from patients and the public have hampered the transformational potential of the LHS model. An enhanced vision of a community-engaged LHS redesign would focus on the provision of health care from the patient and community perspective to complement the healthcare system as the entity that provides the environment for care. Addressing the LHS framework implementation challenges and utilizing community levers are requisite components of a learning health care community model, version two of the LHS archetype.

Smartphone Smoking Cessation Application (SSC App) trial: a multicountry double-blind automated randomised controlled trial of a smoking cessation decision-aid 'app'

OBJECTIVE

To assess the efficacy of an interactive smoking cessation decision-aid application (pp) compared with a smoking cessation static information app on continuous abstinence.

DESIGN

Automated double-blind randomised controlled trial with 6 months follow-up (2014-2015).

SETTING

Smartphone-based.

PARTICIPANTS

684 participants (daily smokers of cigarettes, 18 years old or over) recruited passively from app stores in the USA, Australia, UK and Singapore, and randomised to one of two sub-apps.

INTERVENTIONS

Behavioural, decision-aid, smartphone application.

MAIN OUTCOMES

Continuous abstinence at 10 days, 1 month, 3 months and 6 months.

RESULTS

Smokers who received the decision-aid app were more likely to be continuously abstinent at 1 month compared with the information-only app (28.5% vs 16.9%; relative risk (RR) 1.68; 95% CI 1.25 to 2.28). The effect was sustained at 3 months (23.8% vs 10.2%; RR 2.08; 95% CI 1.38 to 3.18) and 6 months (10.2% vs 4.8%; RR 2.02; 95% CI 1.08 to 3.81). Participants receiving the decision-aid app were also more likely to have made an informed choice (31.9% vs 19.6%) and have lower decisional conflict (19.5% vs 3.9%).

CONCLUSION

A smartphone decision-aid app with support features significantly increased smoking cessation and informed choice. With an increasing number of smokers attempting to quit, unassisted evidence-based decision-aid apps can provide an effective and user-friendly option to many who are making quit decisions without healthcare professionals.

TRIAL REGISTRATION NUMBER

ACTRN12613000833763.

Mental health apps in a college setting: openness, usage, and attitudes

BACKGROUND

The ubiquity of smartphones and the development of mental health apps (MHAs) calls for evaluation of consumers' attitudes towards and usage of MHAs. Due to the increasing demand for mental health services on college campuses, research is especially needed to evaluate MHAs as a potentially viable treatment modality in that setting.

METHODS

The study team developed survey questions related to MHAs, added these to the Healthy Minds Study, and used Qualtrics as the platform. The participants were 741 students, age 18 and older, from a large Midwest public university. Students could answer a varying number of multiple choice questions based on embedded display logic, and the survey required 20-25 minutes for most participants to complete. Based on embedded display logic in the survey and how questions were answered, students could receive anywhere from 1-20 questions. Questions were primarily categorical (e.g., "Yes", "Maybe", "No"), with the remaining questions in free response format. The survey was fielded in April, 2016.

RESULTS

26.1% of respondents were open to using an MHA yet only 7.3% had used an MHA. 9.0% of respondents preferred to use an MHA versus seeing a mental health professional. 13.2% of respondents felt that MHAs do have an evidence base. 23.8% of users felt that MHAs helped with their mental health. Those who reported receiving mental health services within the past 12 months were significantly more open to using MHAs than those who had not received services. Convenience, immediate availability, and confidentiality were common reasons for interest in MHAs.

CONCLUSIONS

There is interest in, but limited usage, of MHAs among university students, providing evidence of MHAs as a potentially untapped treatment modality for this population. Further research could help assess how best to integrate this technology into the university and college mental health system.

Identifying Asbestos-Containing Materials in Homes: Design and Development of the ACM Check Mobile Phone App

Background

Asbestos-containing materials (ACMs) can still be found in many homes in Australia and other countries. ACMs present a health risk when they are damaged or disturbed, such as during do-it-yourself home renovations. However, community members lack knowledge and awareness about asbestos identification and its safe management in residential settings.

Objective

The objective of our study was to describe the process of developing a mobile phone app, ACM Check, that incorporates a questionnaire designed to identify and assess ACMs located in residential settings.

Methods

A multidisciplinary team was involved in the formative development and creation of the mobile phone app. The formative development process comprised 6 steps: defining the scope of the app; conducting a comprehensive desktop review by searching online literature databases, as well as a wider online search for gray literature; drafting and revising the content, questionnaire, conditional branching rules, and scoring algorithms; obtaining expert input; manually pretesting the questionnaire; and formulating a final content document to be provided to the software development company. We then constructed ACM Check on the iOS platform for use in a validation study, and then updated the app, replicated it on Android, and released it to the public.

Results

The ACM Check app identifies potential ACMs, prioritizes the materials based on their condition and likelihood of disturbance, and generates a summary report for each house assessed.

Conclusions

ACM Check is an initiative to raise community members’ awareness of asbestos in the residential environment and also serves as a data collection tool for epidemiologic research. It can potentially be modified for implementation in other countries or used as the basis for the assessment of other occupational or environmental hazards.

Supportive Mental Health Self-Monitoring among Smartphone Users with Psychological Distress: Protocol for a Fully Mobile Randomized Controlled Trial

Mobile health (mHealth) could be widely used in the population to improve access to psychological treatment. In this paper, we describe the development of a mHealth intervention on the basis of supportive self-monitoring and describe the protocol for a randomized controlled trial to evaluate its effectiveness among smartphone users with psychological distress. Based on power analysis, a representative quota sample of N = 186 smartphone users will be recruited, with an over-sampling of persons with moderate to high distress. Over a 4-week period, the intervention will be compared to a self-monitoring without intervention group and a passive control group. Telephone interviews will be conducted at baseline, post-intervention (4 weeks), and 12-week follow-up to assess study outcomes. The primary outcome will be improvement of mental health. Secondary outcomes will include well-being, intentions toward help-seeking and help-seeking behavior, user activation, attitudes toward mental-health services, perceived stigmatization, smartphone app quality, user satisfaction, engagement, and adherence with the intervention. Additionally, data from the user's daily life as collected during self-monitoring will be used to investigate risk and protective factors of mental health in real-world settings. Therefore, this study will allow us to demonstrate the effectiveness of a smartphone application as a widely accessible and low-cost intervention to improve mental health on a population level. It also allows to identify new assessment approaches in the field of psychiatric epidemiology.

There is an app for that! The current state of mobile applications (apps) for DSM-5 obsessive-compulsive disorder, posttraumatic stress disorder, anxiety and mood disorders

Mental health apps are viewed as a promising modality to extend the reach of mental health care beyond the clinic. They do so by providing a means of assessment, tracking, and treatment through a smartphone. Given that nearly 2/3 of the American population owns a smartphone, mental health apps offer the possibility of overcoming treatment barriers such as geographic location or financial barriers. Unfortunately, the excitement surrounding mental health apps may be premature as the current supporting literature regarding their efficacy is limited. The app marketplace is littered with apps claiming to treat or assess symptoms, but even those created by reputable organizations or those incorporating components of evidence-based treatments have not yet been validated in terms of their efficacy. This review aims to provide a comprehensive review of the current state of the mental health app literature by examining published reports of apps designed for DSM-5 anxiety and mood disorders, OCD, and PTSD. The breadth of apps reviewed includes those oriented around assessment, symptom tracking, and treatment as well as "multipurpose" apps, which incorporate several of these components. This review will also present some of the most popular mental health apps which may have clinical utility and could be prescribed to clients. While we discuss many potential benefits of mental health apps, we focus on a number of issues that the current state of the app literature presents. Overall there is a significant disconnect between app developers, the scientific community and health care, leaving the utility of existing apps questionable.

A bespoke mobile application for the longitudinal assessment of depression and mood during pregnancy: protocol of a feasibility study

INTRODUCTION

Depression is a common mental health disorder during pregnancy, with important consequences for mothers and their children. Despite this, it goes undiagnosed and untreated in many women attending antenatal care. Smartphones could help support the prompt identification of antenatal depression in this setting. In addition, these devices enable the implementation of ecological momentary assessment techniques, which could be used to assess how mood is experienced during pregnancy. With this study, we will assess the feasibility of using a bespoke mobile application (app) running on participants' own handsets for the longitudinal (6 months) monitoring of antenatal mood and screening of depression.

METHODS AND ANALYSIS

We will use a randomised controlled study design to compare two types of assessment strategies: retrospective + momentary (consisting of the Edinburgh Postnatal Depression Scale plus five momentary and two contextual questions), and retrospective (consisting of the Edinburgh Postnatal Depression Scale only). We will assess the impact that these strategies have on participant adherence to a prespecified sampling protocol, dropout rates and timeliness of data completion. We will evaluate differences in acceptance of the technology through a short quantitative survey and open-ended questions. We will also assess the potential effect that momentary assessments could have on retrospective data. We will attempt to identify any patterns in app usage through the analysis of log data.

ETHICS AND DISSEMINATION

This study has been reviewed and approved by the National Research Ethics Service Committee South East Coast-Surrey on 15 April 2016 as a notice of substantial amendment to the original submission (9 July 2015) under the Research Ethics Committee (REC) reference 15/LO/0977. This study is being sponsored by Imperial College London under the reference number 15IC2687 and has been included in the UK Clinical Research Network Study Portfolio under the Central Portfolio Management System number 19280. The findings of this study will be disseminated through academic peer-reviewed publications, poster presentations and abstracts at academic and professional conferences, discussion with peers, and social media. The findings of this study will also inform the PhD theses of JSMB and KD.

eMindLog: Self-Measurement of Anxiety and Depression Using Mobile Technology

Background

Quantifying anxiety and depressive experiences permits individuals to calibrate where they are and monitor intervention-associated changes. eMindLog is a novel self-report measure for anxiety and depression that is grounded in psychology with an organizing structure based on neuroscience.

Objective

Our aim was to explore the psychometric properties of eMindLog in a nonclinical sample of subjects.

Methods

In a cross-sectional study of eMindLog, a convenience sample of 198 adults provided informed consent and completed eMindLog and the Hospital Anxiety and Depression Scale (HADS) as a reference. Brain systems (eg, negative and positive valence systems, cognitive systems) and their functional states that drive behavior are measured daily as emotions, thoughts, and behaviors. Associated symptoms, quality of life, and functioning are assessed weekly. eMindLog offers ease of use and expediency, using mobile technology across multiple platforms, with dashboard reporting of scores. It enhances precision by providing distinct, nonoverlapping description of terms, and accuracy through guidance for scoring severity.

Results

eMindLog daily total score had a Cronbach alpha of .94. Pearson correlation coefficient for eMindLog indexes for anxiety and sadness/anhedonia were r=.66 (P<.001) and r=.62 (P<.001) contrasted with the HADS anxiety and depression subscales respectively. Of 195 subjects, 23 (11.8%) had cross-sectional symptoms above the threshold for Generalized Anxiety Disorder and 29 (29/195, 14.9%) for Major Depressive Disorder. Factor analysis supported the theoretically derived index derivatives for anxiety, anger, sadness, and anhedonia.

Conclusions

eMindLog is a novel self-measurement tool to measure anxiety and depression, demonstrating excellent reliability and strong validity in a nonclinical population. Further studies in clinical populations are necessary for fuller validation of its psychometric properties. Self-measurement of anxiety and depressive symptoms with precision and accuracy has several potential benefits, including case detection, tracking change over time, efficacy assessment of interventions, and exploration of potential biomarkers.

Development of a Modular Research Platform to Create Medical Observational Studies for Mobile Devices

Background

Observational studies have proven to be a valuable resource in medical research, especially when performed on a large scale. Recently, mobile device-based observational studies have been discovered by an increasing number of researchers as a promising new source of information. However, the development and deployment of app-based studies is not trivial and requires profound programming skills.

Objective

The aim of this project was to develop a modular online research platform that allows researchers to create medical studies for mobile devices without extensive programming skills.

Methods

The platform approach for a modular research platform consists of three major components. A Web-based platform forms the researchers’ main workplace. This platform communicates via a shared database with a platform independent mobile app. Furthermore, a separate Web-based login platform for physicians and other health care professionals is outlined and completes the concept.

Results

A prototype of the research platform has been developed and is currently in beta testing. Simple questionnaire studies can be created within minutes and published for testing purposes. Screenshots of an example study are provided, and the general working principle is displayed.

Conclusions

In this project, we have created a basis for a novel research platform. The necessity and implications of a modular approach were displayed and an outline for future development given. International researchers are invited and encouraged to participate in this ongoing project

Implementation of depression screening in antenatal clinics through tablet computers: results of a feasibility study

Background

Mobile devices may facilitate depression screening in the waiting area of antenatal clinics. This can present implementation challenges, of which we focused on survey layout and technology deployment.

Methods

We assessed the feasibility of using tablet computers to administer a socio-demographic survey, the Whooley questions and the Edinburgh Postnatal Depression Scale (EPDS) to 530 pregnant women attending National Health Service (NHS) antenatal clinics across England. We randomised participants to one of two layout versions of these surveys: (i) a scrolling layout where each survey was presented on a single screen; or (ii) a paging layout where only one question appeared on the screen at any given time.

Results

Overall, 85.10% of eligible pregnant women agreed to take part. Of these, 90.95% completed the study procedures. Approximately 23% of participants answered Yes to at least one Whooley question, and approximately 13% of them scored 10 points of more on the EPDS. We observed no association between survey layout and the responses given to the Whooley questions, the median EPDS scores, the number of participants at increased risk of self-harm, and the number of participants asking for technical assistance. However, we observed a difference in the number of participants at each EPDS scoring interval (p = 0.008), which provide an indication of a woman’s risk of depression. A scrolling layout resulted in faster completion times (median = 4 min 46 s) than a paging layout (median = 5 min 33 s) (p = 0.024). However, the clinical significance of this difference (47.5 s) is yet to be determined.

Conclusions

Tablet computers can be used for depression screening in the waiting area of antenatal clinics. This requires the careful consideration of clinical workflows, and technology-related issues such as connectivity and security. An association between survey layout and EPDS scoring intervals needs to be explored further to determine if it corresponds to a survey layout effect. Future research needs to evaluate the effect of this type of antenatal depression screening on clinical outcomes and clinic workflows.

Trial registration

This study was registered in ClinicalTrials.gov under the identifier NCT02516982 on 20 July 2015.

Electronic supplementary material

The online version of this article (doi:10.1186/s12911-017-0459-8) contains supplementary material, which is available to authorized users.