Deep neural network technique for automated detection of ADHD and CD using ECG signal.

BACKGROUND AND OBJECTIVE: Attention Deficit Hyperactivity problem (ADHD) is a common neurodevelopment problem in children and adolescents that can lead to long-term challenges in life outcomes if left untreated. Also, ADHD is frequently associated with Conduct Disorder (CD), and multiple research have found similarities in clinical signs and behavioral symptoms between both diseases, making differentiation between ADHD, ADHD comorbid with CD (ADHD+CD), and CD a subjective diagnosis. Therefore, the goal of this pilot study is to create the first explainable deep learning (DL) model for objective ECG-based ADHD/CD diagnosis as having an objective biomarker may improve diagnostic accuracy. METHODS: The dataset used in this study consist of ECG data collected from 45 ADHD, 62 ADHD+CD, and 16 CD patients at the Child Guidance Clinic in Singapore. The ECG data were segmented into 2 s epochs and directly used to train our 1-dimensional (1D) convolutional neural network (CNN) model. RESULTS: The proposed model yielded 96.04% classification accuracy, 96.26% precision, 95.99% sensitivity, and 96.11% F1-score. The Gradient-weighted class activation mapping (Grad-CAM) function was also used to highlight the important ECG characteristics at specific time points that most impact the classification score. CONCLUSION: In addition to achieving model performance results with our suggested DL method, Grad-CAM's implementation also offers vital temporal data that clinicians and other mental healthcare professionals can use to make wise medical judgments. We hope that by conducting this pilot study, we will be able to encourage larger-scale research with a larger biosignal dataset. Hence allowing biosignal-based computer-aided diagnostic (CAD) tools to be implemented in healthcare and ambulatory settings, as ECG can be easily obtained via wearable devices such as smartwatches.

Prevalence and economic burden of depression and anxiety symptoms among Singaporean adults: results from a 2022 web panel.

BACKGROUND: Major depressive disorder (MDD) and generalized anxiety disorder (GAD) are leading causes of disability and premature mortality. At a global level, over 300 million people are estimated to suffer from major depressive disorders, equivalent to 4·4% of the world's population. Pandemic era stressors have increased rates for depression and anxiety by upwards of 25%. The goal of this study is to estimate the prevalence and economic burden of depression and anxiety symptoms in Singapore after the peak of the COVID-19 pandemic. METHODS: An existing web panel was queried between April 2022 and June 2022. Adult participants aged > 21 years old who screened positive for depression and anxiety symptoms based on the Patient Health Questionnaire-4 (PHQ-4) Screener were eligible for participation. Prevalence estimates were quantified by dividing the number of respondents who screened positive for these symptoms by the total number of respondents. Participants who screened positive were asked about healthcare utilization, days missed from work, and reduced productivity due to these symptoms. These values were then monetized and scaled based on prevalence and population counts to generate per capita and total annual costs. RESULTS: Two thousand three hundred forty-eight respondents filled out the PHQ-4 depression/anxiety screener on behalf of the 5,725 adults living in their households (including respondents themselves). Prevalence estimates were calculated based on the responses recorded for these 5,725 adults. 14.1% adults had symptoms consistent with depression and 15.2% had symptoms consistent with anxiety. In total, 20.0% may experience symptoms consistent with at least one of these two conditions, yet approximately half reported never being formally diagnosed. 350 respondents screened positive for depression or anxiety symptoms and thus were eligible to fill out the healthcare utilization, presenteeism, and absenteeism survey. Direct annual healthcare costs due to depression and anxiety symptoms averaged Singapore dollar (SGD) $1,050 for these respondents. The employed subset (n = 304) missed an extra 17.7 days of work on average per year, which translates to SGD $4,980 per worker. These workers also reported being ~ 40% less productive at work, which equates to SGD $28,720 in economic losses annually. In total, these symptoms caused SGD $15.7 billion in increased costs. Presenteeism accounts for 81.6% of this total (SGD $12.8 billion), absenteeism for 14.2% (SGD $2.3 billion) and healthcare accounts for 4.2% (SGD $0.7 billion). CONCLUSIONS: The health and economic burden associated with depression and anxiety symptoms is large in Singapore, representing 2.9% of Singapore's gross domestic product (GDP). Employers and governments should look to identify effective remediation strategies, including strategies to address the high rates of undiagnosed cases. Increasing psychiatric resources, general practitioner mental health competency, access to peer support, and increased efforts to reduce mental health stigma should be considered to address this growing public health crisis.

Home-based brain-computer interface attention training program for attention deficit hyperactivity disorder: a feasibility trial.

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a prevalent child neurodevelopmental disorder that is treated in clinics and in schools. Previous trials suggested that our brain-computer interface (BCI)-based attention training program could improve ADHD symptoms. We have since developed a tablet version of the training program which can be paired with wireless EEG headsets. In this trial, we investigated the feasibility of delivering this tablet-based BCI intervention at home. METHODS: Twenty children diagnosed with ADHD, who did not receive any medication for the preceding month, were randomised to receive the 8-week tablet-based BCI intervention either in the clinic or at home. Those in the home intervention group received instructions before commencing the program and got reminders if they were lagging on the training sessions. The ADHD Rating Scale was completed by a blinded clinician at baseline and at week 8. Adverse events were monitored during any contact with the child throughout the trial and at week 8. RESULTS: Children in both groups could complete the tablet-based intervention easily on their own with minimal support from the clinic therapist or their parents (at home). The intervention was safe with few reported adverse effects. Clinician-rated inattentive symptoms on the ADHD-Rating Scale reduced by 3.2 (SD 6.20) and 3.9 (SD 5.08) for the home-based and clinic-based groups respectively, suggesting that home-based intervention was comparable to clinic-based intervention. CONCLUSIONS: This trial demonstrated that the tablet version of our BCI-based attention training program can be safely delivered to children in the comfort of their own home. Trial registration This trial is registered at clinicaltrials.gov as NCT01344044.

Association of cardiovascular metabolic risk factor measurements with psychiatric readmission among in-hospital patients with severe mental illness: a retrospective study.

BACKGROUND: Patients with severe mental illness (SMI) and comorbid physical conditions were often associated with higher risks of mortality and hospital readmission. In this study, we aim to examine the association of cardiovascular metabolic risk factor measurements with risks of psychiatric readmissions among in-hospital patients with severe mental illness (SMI). METHODS: We collected the longitudinal information of laboratory investigations, blood pressure and body mass index (BMI) among in-hospital patients who had been diagnosed with schizophrenia, major depression disorder or bipolar disorder and with comorbid diagnosis of hypertension, hyperlipidemia or diabetes from Jan 2014 to Jan 2019. The primary outcome was time to first psychiatric readmission. Cox proportional hazard model was utilized to calculate the hazard risks (HR) of cardiovascular metabolic risk factors with psychiatric readmission. RESULTS: A total of 5,256 patients were included in the analysis. Compared to patients with normal blood parameters, patients with aberrant tests of high-density dyslipidemia (HDL) and diastolic blood pressure (DBP) during in-hospitalization period were associated with higher risks to first psychiatric readmission [ HR (Hazard Ratio), 1.37 95% Confidence interval (CI), 1.03-1.83 for HDL and HR, 1.32 (95% CI, 1.04-1.67])for DBP]. Compared to patients with optimal monitoring, patients with suboptimal monitoring of blood lipids and blood pressure during in-hospitalization period or recommended window period of cardiovascular disease (CVD) risk management were associated with higher risks to first psychiatric readmission. CONCLUSIONS: Aberrant cardiovascular metabolic blood test and blood pressure and missing measurements among in-hospital patients with SMI were associated with increased risks of psychiatric readmissions. This calls for more active screening and monitoring of CVD risk factors for those in-hospital patients in need.

Differences in the Prevalence and Profile of DSM-IV and DSM-5 Alcohol Use Disorders-Results from the Singapore Mental Health Study 2016.

INTRODUCTION: The Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) criteria for alcohol use disorders (AUD) was a significant shift from the historical DSM-IV Text Revised version. Following this shift in diagnostic criteria, a difference in the prevalence of AUD was expected. The current study aimed to evaluate the consequences of the modification of the diagnostic criteria from DSM-IV to DSM-5 AUD using lifetime diagnosis in Singapore's multi-ethnic population using data from a nationwide epidemiological study. METHODS: Respondents were assessed for lifetime mental disorders using the Composite International Diagnostic Interview (CIDI) administered through face-to-face interviews. Lifetime DSM-IV AUD diagnoses were compared with DSM-5 AUD diagnoses generated by modifying the criteria and the addition of the craving criterion. Sociodemographic correlates of lifetime DSM-IV/DSM-5 AUD were examined using multiple logistic regression analysis. Associations between DSM-IV/DSM-5 AUD, chronic conditions, and the HRQOL summary scores were examined using logistic and linear regression after controlling for significant sociodemographic factors. RESULTS: The lifetime prevalence of DSM-IV AUD was 4.6% (0.5% for dependence and 4.1% for abuse) in the adult population, while the lifetime prevalence of DSM-5 AUD was 2.2%. Younger age, male gender, and lower education were associated with higher odds of both DSM-IV and DSM-5 AUD. However, those who were economically inactive (versus employed) (AOR, 0.4; 95% CI 0.2-0.9) and had a higher monthly household income (SGD 4000-5999 versus below SGD 2000) had lower odds of DSM-IV AUD (AOR, 0.4; 95% CI 0.2-0.7), but this was not observed among those with DSM-5 AUD. Both DSM-IV and DSM-5 AUD were associated with significant comorbidities in terms of other mental disorders; however, those diagnosed with lifetime GAD had significantly higher odds of having DSM-5 AUD (AOR, 5; 95% CI 1.9-13.2) but not DSM-IV AUD. CONCLUSIONS: While using the DSM-5 criteria would result in a lower prevalence of AUD in Singapore, it remains a highly comorbid condition associated with a poor health-related quality of life that is largely untreated, which makes it a significant public health concern.

Automated classification of attention deficit hyperactivity disorder and conduct disorder using entropy features with ECG signals.

BACKGROUND: The most prevalent neuropsychiatric disorder among children is attention deficit hyperactivity disorder (ADHD). ADHD presents with a high prevalence of comorbid disorders such as conduct disorder (CD). The lack of definitive confirmatory diagnostic tests for ADHD and CD make diagnosis challenging. The distinction between ADHD, ADHD + CD and CD is important as the course and treatment are different. Electrocardiography (ECG) signals may become altered in behavioral disorders due to brain-heart autonomic interactions. We have developed a software tool to categorize ADHD, ADHD + CD and CD automatically on ECG signals. METHOD: ECG signals from participants were decomposed using empirical wavelet transform into various modes, from which entropy features were extracted. Robust ten-fold cross-validation with adaptive synthetic sampling (ADASYN) and z-score normalization were performed at each fold. Analysis of variance (ANOVA) technique was employed to determine the variability within the three classes, and obtained the most discriminatory features. Highly significant entropy features were then fed to classifiers. RESULTS: Our model yielded the best classification results with the bagged tree classifier: 87.19%, 87.71% and 86.29% for accuracy, sensitivity and specificity, respectively. CONCLUSION: The proposed expert system can potentially assist mental health professionals in the stratification of the three classes, for appropriate intervention using accessible ECG signals.

Validity of the patient health questionnaire 9-item in autistic youths: a pilot study.

BACKGROUND: Autistic adolescents have greater predisposition to depression and suicidality than neurotypical adolescents. Early detection is essential for timely treatment. The Patient Health Questionnaire 9-item (PHQ-9) is a brief screen for depression. The study examines the validity of the PHQ-9 for detecting major depressive disorder (MDD) in autistic youths. METHODS: English speaking youths aged 10-18 years, with DSM-IV/DSM-5/ICD-10 diagnosis of Autism Spectrum Disorder (ASD), and their parents presenting to a child psychiatric service were invited to participate between May 2018 to August 2020. Participants completed the respective self- and parent-rated PHQ-9 independently. MDD was verified using the MINI-Kid (Mini-International Neuropsychiatric Interview, Kid version). RESULTS: One hundred one youth, mean (SD) age 14.6 (2.3), were enrolled. 27 (27%) met criteria for current MDD. Mean total PHQ-9 scores, percentage ratings for severity of symptoms of depression, functional impairment, dysthymia and suicidality were compared. Areas under the ROC curve and statistically optimal cutoffs were determined. Parents rated depressive symptoms severity lower than their children. The PHQ-9 displayed low sensitivity with high false negative rates at conventional, adjusted and proposed cutoffs. CONCLUSIONS: Future studies should improve on the validity and reliability of existing depression screening tools, or develop more appropriate screening methods of depression, for autistic youths.

Mental Resilience of Medical Practitioners in Singapore during COVID-19: Survey Results from a Webinar Course on Resilience.

Front-line doctors are at high risk of exposure to COVID-19. The mental resilience of general practitioners and their areas of concerns and support required are important during this COVID-19 period. A total of 403 general practitioners attending a webinar on resiliency, hosted by the College of Family Physicians, Singapore, participated in the survey anonymously. Participants provided responses to questions relating to COVID-19 in the domains of Family and friends, Myself, Practice, and Community. Responses are categorized into LEARNING, FEAR, and GROWTH zones. The majority of the doctors reported to be in the GROWTH zone in relation to Family and friends (39%) and Myself (38%) as compared to Practice and Community, aOR = 4.5 (95% CI 3.4 to 5.9), p < 0.001. 34% of the participants reported being in the FEAR zone in relation to Family and friends, aOR = 8.0 (95% CI = 5.6 to 11.2), p < 0.001; at least 81% reported being in the LEARNING zone in relation to Practice and Community, aOR = 7.5 (95% CI = 5.8 to 9.6), p < 0.001, compared to other domains. Supporting and protecting the doctors is important in strategic planning and management of the current pandemic and building preparedness and an effective response towards future crises.

Our children then and now: Changes in mental health symptoms among Singaporean children from 2003 to 2017.

In recent years, there appears to be a rise in the diagnosis and treatment of child mental health disorders in many countries, including Singapore. While this increase may be alarming, it could possibly be attributed to factors such as changes in diagnostic criteria, improved screening in schools and primary health settings, changes in clinical practices, and an increase in help-seeking behaviour. Hence, an examination of community-level trends in mental health symptoms can elucidate how child psychopathology has changed over the years. This study aimed to investigate differences in symptoms of mental health between two cohorts of young Asian children aged six to eight living in Singapore. Child Behaviour Checklist (CBCL) scores from a sample in 2003 (Cohort 1; n = 524) were compared to another sample taken in 2017 (Cohort 2; n = 655). Cohort 2 had lower externalizing scale scores as compared to Cohort 1, but there were no significant differences in total problem scores or internalizing scale scores. Among the CBCL subscales, Cohort 2 had comparatively lower levels of aggressive behaviour and withdrawn/depressed symptoms, but higher levels of thought problems and somatic complaints as compared to Cohort 1. Our findings suggest that children in Singapore are progressing as well as, or even better than, children 14 years ago on most aspects of mental well-being.

Comparison of mental-physical comorbidity, risk of death and mortality among patients with mental disorders - A retrospective cohort study.

AIM: To compare the risk of death, the prevalence of comorbid chronic physical illness and mortality among an Asian population of patients with mental disorders. METHODS: This was a retrospective data analysing of medical records of patients with schizophrenia, depression, anxiety, bipolar disorder, alcohol use disorder (AUD) or substance use disorder and the comorbid chronic physical illnesses. The hazard risk of death was calculated with Cox regression and compared between patients with and without comorbid chronic physical illness(es). Odds ratios of specific comorbid chronic physical illness were calculated with logistic regression and mean crude death rate was calculated for patients with different mental disorders. RESULTS: A total of 56,447 patients with mental disorders were included in the analysis. Compared to patients without comorbid physical illness, patients with mental-physical comorbidity were associated with a higher risk of death [2.36 (2.22-2.52); hazard ratio (95% CI)] and less estimated survival days [2157 (2142-2172) vs 2508 (2504-2513)]. Compared to other mental disorders, those with AUD had the highest prevalence of two or more comorbid chronic physical illnesses and associated with the highest odds of comorbid hypertension, diabetes mellitus, stroke, nephritis, chronic kidney disease, and cancer. The highest one-year crude death rate was similarly observed in patients with AUD. CONCLUSIONS: Mental-physical comorbidity was associated with a higher risk of death compared to patients with mental disorders only. The highest prevalence of mental-physical comorbidity and mortality were observed in patients with AUD. More attention and resources may be needed to tackle the burden of AUD.

The Relationship between Suicidality and Socio-Demographic Variables, Physical Disorders, and Psychiatric Disorders: Results from the Singapore Mental Health Study 2016.

Suicidality encompasses suicidal ideation, plans, and attempts. This paper aims to establish associations between suicidality and sociodemographic variables, physical disorders, and psychiatric disorders. The Singapore Mental Health Study 2016 was a population-level epidemiological survey, which determined the prevalence of physical disorders, psychiatric disorders, and suicidality. Questionnaires were used to determine socio-demographic information. A total of 6216 respondents were interviewed. Lifetime prevalence of suicidal ideation, planning, and attempts were 7.8%, 1.6%, and 1.6%, respectively. All components of suicidality were more likely in those with major depressive disorder, bipolar disorder, generalized anxiety disorder, alcohol use disorder, and chronic pain. Suicidal ideation and attempts were more likely in those with diabetes. Age above 65, being male, and a monthly household income of ≥ SGD 10,000 were associated with a lower likelihood of suicidal ideation. These findings indicate that there are high-risk groups for whom suicidality is a concern, and for whom interventions may be needed.

Automated detection of conduct disorder and attention deficit hyperactivity disorder using decomposition and nonlinear techniques with EEG signals.

BACKGROUND AND OBJECTIVES: Attention deficit hyperactivity disorder (ADHD) is often presented with conduct disorder (CD). There is currently no objective laboratory test or diagnostic method to discern between ADHD and CD, and diagnosis is further made difficult as ADHD is a common neuro-developmental disorder often presenting with other co-morbid difficulties; and in particular with conduct disorder which has a high degree of associated behavioural challenges. A novel automated system (AS) is proposed as a convenient supplementary tool to support clinicians in their diagnostic decisions. To the best of our knowledge, we are the first group to develop an automated classification system to classify ADHD, CD and ADHD+CD classes using brain signals. METHODS: The empirical mode decomposition (EMD) and discrete wavelet transform (DWT) methods were employed to decompose the electroencephalogram (EEG) signals. Autoregressive modelling coefficients and relative wavelet energy were then computed on the signals. Various nonlinear features were extracted from the decomposed coefficients. Adaptive synthetic sampling (ADASYN) was then employed to balance the dataset. The significant features were selected using sequential forward selection method. The highly discriminatory features were subsequently fed to an array of classifiers. RESULTS: The highest accuracy of 97.88% was achieved with the K-Nearest Neighbour (KNN) classifier. The proposed system was developed using ten-fold validation strategy on EEG data from 123 children. To the best of our knowledge this is the first study to develop an AS for the classification of ADHD, CD and ADHD+CD classes using EEG signals. POTENTIAL APPLICATION: Our AS can potentially be used as a web-based application with cloud system to aid the clinical diagnosis of ADHD and/or CD, thus supporting faster and accurate treatment for the children. It is important to note that testing with larger data is required before the AS can be employed for clinical applications.

The Mental Health Trigger Tool: Development and Testing of a Specialized Trigger Tool for Mental Health Settings.

OBJECTIVE: Tools generally used in measuring patient safety incidents in general healthcare settings are not considered suitable for mental health settings. The aim of this study was to develop and evaluate a specialized trigger tool for mental health settings that could detect both traditionally defined adverse events (AEs) and other mental health-related patient safety incidents (MHPSIs). METHODS: We first defined and categorized AEs and MHPSIs based on existing literature and then developed a trigger list, initially consisting of 50 items, which was subsequently reduced to 25 items after a pilot study. We then explored the properties of this final 25-item trigger tool, the Mental Health Trigger Tool (MHTT), through a retrospective review of 515 patient records with a two-stage review process similar to Global Trigger Tool methodology. We used findings of an alternative method of review which consisted of page-to-page reviews of patient records in the analysis of properties of MHTT. RESULTS: Using the MHTT, at least one AE was identified in 98 patient records (19%) and at least one MHPSI was identified in 58 patient records (11%). The MHTT had a sensitivity of 98.6% and its specificity was 100%. The probability of finding an AE/MHPSI when any trigger was detected in a patient record with MHTT was 33.8% and that of individual triggers ranged from 0% to 100%. CONCLUSIONS: The MHTT may offer an effective, practical, and easy-to-use method in identifying and measuring safety incidents in mental health settings.

Smoking and Mental Illness: Prevalence, Patterns and Correlates of Smoking and Smoking Cessation among Psychiatric Patients.

This study aims to understand (a) the prevalence and correlates of smoking in a psychiatric population, (b) factors that encourage smoking cessation, and (c) awareness towards cessation programmes. This study captured data (n = 380) through a modified version of the Global Adult Tobacco Survey (GATS). A descriptive analysis of the data was performed. The prevalence of smoking was 39.5% (n = 150) and 52.3% of the smokers were dependent on nicotine. More than half of the smokers had made at least one attempt to quit in the past 12 months and 56% reported no immediate plans to quit smoking. The awareness towards institutional smoking cessation programmes was fair (44%), with 49.7% of smokers having indicated that they were willing to use the service upon referral. Smokers endorsed that increasing the cost of cigarettes, restricting availability, and increasing knowledge of health harms could encourage smoking cessation. Past smokers reported that self-determination/willpower followed by substitution of smoking with other types of foods and drinks were factors that helped them achieve successful cessation. Given that the readiness to quit and awareness towards cessation programmes are low among the smokers, concerted efforts through educational programmes and policy changes are crucial to achieve successful cessation.

Codesigning a mobile gamified attention bias modification intervention: research protocol.

INTRODUCTION: Advances in experimental psychology has highlighted the need to modify underlying automatic cognitive biases, such as attentional biases. While prior research has documented the effectiveness of cognitive bias modification, such interventions tend to be highly repetitive and individuals lack motivation to train over time. Participatory action research methods have been more widely applied in psychiatry to help design interventions that are of relevant to key stakeholders and end users. This study aimed to involve both healthcare professionals and patients in the joint codesign of a gamified mobile attention bias modification intervention. METHODS AND ANALYSIS: The participatory design research method adopted is that of a use-oriented design approach, in the form of a future workshop. 20 participants, comprising 10 healthcare professionals, 5 inpatients and 5 outpatients will be recruited to participate in three separate codesign workshops. In the first phase of the workshop, the participants share their critique of an attention bias modification intervention. In the second phase of the workshop, participants are asked to brainstorm features. The participants are also shown gamification approaches and are asked to consider if gaming elements could enhance the existing application. In the last phase, the participants are asked to sketch a new prototype. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the National Healthcare Group's Domain Specific Research Board (approval number 2018/01363). The findings arising from this study will be disseminated by means of conferences and publications.

An Outbreak of Streptococcus pyogenes in a Mental Health Facility: Advantage of Well-Timed Whole-Genome Sequencing Over emm Typing.

OBJECTIVEWe report the utility of whole-genome sequencing (WGS) conducted in a clinically relevant time frame (ie, sufficient for guiding management decision), in managing a Streptococcus pyogenes outbreak, and present a comparison of its performance with emm typing.SETTINGA 2,000-bed tertiary-care psychiatric hospital.METHODSActive surveillance was conducted to identify new cases of S. pyogenes. WGS guided targeted epidemiological investigations, and infection control measures were implemented. Single-nucleotide polymorphism (SNP)-based genome phylogeny, emm typing, and multilocus sequence typing (MLST) were performed. We compared the ability of WGS and emm typing to correctly identify person-to-person transmission and to guide the management of the outbreak.RESULTSThe study included 204 patients and 152 staff. We identified 35 patients and 2 staff members with S. pyogenes. WGS revealed polyclonal S. pyogenes infections with 3 genetically distinct phylogenetic clusters (C1-C3). Cluster C1 isolates were all emm type 4, sequence type 915 and had pairwise SNP differences of 0-5, which suggested recent person-to-person transmissions. Epidemiological investigation revealed that cluster C1 was mediated by dermal colonization and transmission of S. pyogenes in a male residential ward. Clusters C2 and C3 were genomically diverse, with pairwise SNP differences of 21-45 and 26-58, and emm 11 and mostly emm120, respectively. Clusters C2 and C3, which may have been considered person-to-person transmissions by emm typing, were shown by WGS to be unlikely by integrating pairwise SNP differences with epidemiology.CONCLUSIONSWGS had higher resolution than emm typing in identifying clusters with recent and ongoing person-to-person transmissions, which allowed implementation of targeted intervention to control the outbreak.Infect Control Hosp Epidemiol 2018;852-860.

Current status of postnatal depression smartphone applications available on application stores: an information quality analysis.

OBJECTIVES: It is the aim of the current research to identify some common functionalities of postnatal application, and to determine the quality of the information content of postnatal depression application using validated scales that have been applied for applications in other specialties. SETTINGS AND PARTICIPANTS: To determine the information quality of the postnatal depression smartphone applications, the two most widely used smartphone application stores, namely Apple iTunes as well as Google Android Play store, were searched between 20May and 31 May. No participants were involved. The inclusion criteria for the application were that it must have been searchable using the keywords 'postnatal', 'pregnancy', 'perinatal', 'postpartum' and 'depression', and must be in English language. INTERVENTION: The Silberg Scale was used in the assessment of the information quality of the smartphone applications. PRIMARY AND SECONDARY OUTCOMES MEASURE: The information quality score was the primary outcome measure. RESULTS: Our current results highlighted that while there is currently a myriad of applications, only 14 applications are specifically focused on postnatal depression. In addition, the majority of the currently available applications on the store have only disclosed their last date of modification as well as ownership. There remain very limited disclosures about the information of the authors, as well as the references for the information included in the application itself. The average score for the Silberg Scale for the postnatal applications we have analysed is 3.0. CONCLUSIONS: There remains a need for healthcare professionals and developers to jointly conceptualise new applications with better information quality and evidence base.