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Hot Topics of the Day are picked by experts to capture the latest information and publications on public health genomics and precision health for various diseases and health topics. Sources include published scientific literature, reviews, blogs and popular press articles.

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76 hot topic(s) found with the query "Mental health "

Research biobank participants attitudes towards genetic exceptionalism and health record confidentiality.
Victoria Dortenzio et al. J Community Genet 2024 3 (Posted: Apr 08, 2024 9AM)

From the abstract: "The goals of this study were to determine biobank participants’ attitudes towards genetic exceptionalism and confidentiality and whether those attitudes are related to their preference for return of genetic results. An online questionnaire was distributed to patients with an EHR and email address who had previously enrolled in the BioMe Biobank program. Most participants responded with similar levels of concern in scenarios involving the use of genetic information and other types of health information, suggesting that participants want similar protections for genetic data as other types of sensitive health information, particularly mental health and family history records. "

A phenome-wide association and Mendelian randomisation study of alcohol use variants in a diverse cohort comprising over 3 million individuals.
Mariela V Jennings et al. EBioMedicine 2024 4 105086 (Posted: Apr 08, 2024 9AM)

From the abstract: " We performed exploratory phenome-wide association studies (PheWAS) of three of the best studied protective single nucleotide polymorphisms (SNPs) in genes encoding ethanol metabolising enzymes (ADH1B: rs1229984-T, rs2066702-A; ADH1C: rs698-T) using up to 1109 health outcomes across 28 phenotypic categories (e.g., substance-use, mental health, sleep, immune, cardiovascular, metabolic) from a diverse 23andMe cohort, including European (N = 2,619,939), Latin American (N = 446,646) and African American (N = 146,776) populations to uncover new and perhaps unexpected associations. We found that that polymorphisms in genes encoding alcohol metabolising enzymes affect multiple domains of health beyond alcohol-related behaviours. Understanding the underlying mechanisms of these effects could have implications for treatments and preventative medicine."

Systematic review and meta-analysis of AI-based conversational agents for promoting mental health and well-being
H Li, NPJ Digital Medicine, December 19, 2023 (Posted: Dec 20, 2023 9AM)

From the abstract: "Conversational artificial intelligence (AI), particularly AI-based conversational agents (CAs), is gaining traction in mental health care. Despite their growing usage, there is a scarcity of comprehensive evaluations of their impact on mental health and well-being. This systematic review and meta-analysis aims to fill this gap by synthesizing evidence on the effectiveness of AI-based CAs in improving mental health and factors influencing their effectiveness and user experience. "

Epigenome-wide association studies of prenatal maternal mental health and infant epigenetic profiles: a systematic review.
Emily Drzymalla et al. Transl Psychiatry 2023 12 (1) 377 (Posted: Dec 08, 2023 8AM)

From the abstract: "Prenatal stress and poor maternal mental health are associated with adverse offspring outcomes; however, the biological mechanisms are unknown. Epigenetic modification has linked maternal health with offspring development. Epigenome-wide association studies (EWAS) have examined offspring DNA methylation profiles for association with prenatal maternal mental health to elucidate mechanisms of these complex relationships. The objective of this study is to provide a comprehensive, systematic review of EWASs of infant epigenetic profiles and prenatal maternal anxiety, depression, or depression treatment. "

Natural language processing system for rapid detection and intervention of mental health crisis chat messages.
Akshay Swaminathan et al. NPJ Digit Med 2023 11 (1) 213 (Posted: Nov 22, 2023 9AM)

From the abstract: "Patients experiencing mental health crises often seek help through messaging-based platforms, but may face long wait times due to limited message triage capacity. Here we build and deploy a machine-learning-enabled system to improve response times to crisis messages in a large, national telehealth provider network. We train a two-stage natural language processing (NLP) system with key word filtering followed by logistic regression on 721 electronic medical record chat messages, of which 32% are potential crises. "

Social and physical predictors of mental health impact in adult women who have an FMR1 premutation
C Kraan et al, Genetics in Med Open, August 26, 2023 (Posted: Aug 29, 2023 11AM)

From the abstract: "Clear understanding of mental health phenotypes and associated socioeconomic, physical health and wellbeing impacts in adult women with an FMR1 premutation (PM) is needed for counselling and primary healthcare. This is a survey of 137 participants. Depression was found in ~30% and social anxiety in ~38%. With depression status the outcome variable, strongest associations were for low education, diagnosis of migraine, diagnosis of irritable bowel syndrome (IBS) and self-reported hearing loss symptoms."

Factors associated with healthy aging in Latin American populations.
Hernando Santamaria-Garcia et al. Nat Med 2023 8 (Posted: Aug 11, 2023 11AM)

We investigated the combined impact of social determinants of health (SDH), lifestyle factors, cardiometabolic factors, mental health symptoms and demographics (age, sex) on healthy aging (cognition and functional ability) across LAC countries with different levels of socioeconomic development using cross-sectional and longitudinal machine learning models (n?=?44,394 participants). Risk factors associated with social and health disparities, including SDH (ß?>?0.3), mental health (ß?>?0.6) and cardiometabolic risks (ß?>?0.22), significantly influenced healthy aging more than age and sex.

Predictive evidence of the relevance of epigenetics to PTSD.
Leon Mutesa et al. Nat Rev Genet 2023 8 (Posted: Aug 09, 2023 4PM)

Post-traumatic stress disorder (PTSD) is a complex mental health condition that can occur after a life-threatening or otherwise traumatic event. Although its molecular causes are unclear, its development is thought to involve a range of biological, psychological and environmental factors. In 2009, Yehuda and Bierer posited that epigenetic modifications, such as DNA methylation, may occur in response to environmental influences such as trauma exposure, thus altering the functional expression of genes. These mechanisms may explain the intergenerational transmission of PTSD across affected families.

Mendelian randomization
AJHG, Special collection, April 2023 (Posted: Apr 12, 2023 11AM)

Mendelian randomization (MR) is a statistical technique used to investigate causal relationships between an exposure and an outcome in observational studies. The development of new and more robust MR methods has provided researchers with an important tool to gain new insights into the causal effects of genetic variants on outcomes such as cardiovascular disease, cancer, and mental health. This AJHG collection features recent research and reviews that highlight the utility of MR in exploring the ways in which genetic variation influences a range of health outcomes.

A multicomponent digital intervention to promote help-seeking for mental health problems and suicide in sexual and gender diverse young adults: A randomized controlled trial.
Meng Han et al. PLoS medicine 2023 3 (3) e1004197 (Posted: Mar 10, 2023 3PM)

Psychotic disorders as a framework for precision psychiatry.
Fiona Coutts et al. Nature reviews. Neurology 2023 3 (Posted: Mar 09, 2023 1PM)

Precision psychiatry aims to stratify people with a given disorder according to different clinical outcomes and tailor treatment to their individual needs. At present, interindividual differences in outcomes of psychotic disorders are difficult to predict on the basis of clinical assessment alone. Therefore, current research in psychosis seeks to build models that predict outcomes by integrating clinical information with biological measures. Here, we review recent progress in the application of precision psychiatry to psychotic disorders and consider the challenges associated with implementing this approach in clinical practice.

Smartphone videos of the sit-to-stand test predict osteoarthritis and health outcomes in a nationwide study
MA Boswell et al, NPJ Digital Medicine, March 4, 2023 (Posted: Mar 04, 2023 9AM)

Physical function decline due to aging or disease can be assessed with quantitative motion analysis, but this currently requires expensive laboratory equipment. We introduce a self-guided quantitative motion analysis of the widely used five-repetition sit-to-stand test using a smartphone. Across 35 US states, 405 participants recorded a video performing the test in their homes. We found that the quantitative movement parameters extracted from the smartphone videos were related to a diagnosis of osteoarthritis, physical and mental health, body mass index, age, and ethnicity and race.

Design and Implementation of the All of Us Research Program COVID-19 Participant Experience (COPE) Survey.
Claire E Schulkey et al. American journal of epidemiology 2023 2 (Posted: Feb 20, 2023 6AM)

In response to the rapidly evolving COVID-19 pandemic, the All of Us Research Program longitudinal cohort study developed the COVID-19 Participant Experience (COPE) survey to better understand the pandemic experiences and health impacts of COVID-19 on diverse populations within the United States. Six survey versions were deployed between May 2020 and March 2021 covering mental health, loneliness, activity, substance use, and discrimination, as well as COVID-19 symptoms, testing, treatment, and vaccination. A total of 104,910 All of Us Research Program participants, of whom over 73% were from communities traditionally underrepresented in biomedical research, completed 275,201 surveys; 9,693 completed all six surveys

New and emerging approaches to treat psychiatric disorders.
Katherine W Scangos et al. Nature medicine 2023 2 (Posted: Feb 17, 2023 7AM)

Here we review new and emerging treatment approaches, with a particular emphasis on the revolutionary potential of brain-circuit-based interventions for precision psychiatry. Limitations of circuit models, challenges of bringing precision therapeutics to market and the crucial advances needed to overcome these obstacles are presented.

Digital mental health for postpartum women: perils, pitfalls, and promise.
Natalie Feldman et al. NPJ digital medicine 2023 1 (1) 11 (Posted: Jan 27, 2023 7AM)

We explore ways in which digital interventions for postpartum mental health may help with connection to treatment, accessibility, agency, and ease of access. We also note particular concerns for how digital postpartum mental health may encounter issues of low-quality resources, ethical considerations, and equity considerations. We provide suggestions for how to leverage the promise and avoid the pitfalls of digital mental health for postpartum women.

Explainable artificial intelligence for mental health through transparency and interpretability for understandability.
Joyce Dan W et al. NPJ digital medicine 2023 1 (1) 6 (Posted: Jan 21, 2023 6AM)

The literature on artificial intelligence (AI) or machine learning (ML) in mental health and psychiatry lacks consensus on what “explainability” means. In the more general XAI (eXplainable AI) literature, there has been some convergence on explainability meaning model-agnostic techniques that augment a complex model (with internal mechanics intractable for human understanding) with a simpler model argued to deliver results that humans can comprehend.

Systematic review of economic evaluations for internet- and mobile-based interventions for mental health problems
F Kahlke et al, NPJ Digital Medicine, November 2022 (Posted: Nov 28, 2022 11AM)

Of the 4044 studies, 36 economic evaluations were reviewed. Guided IMIs were likely to be cost-effective in depression and anxiety. The quality of most evaluations was good, albeit with some risks of bias. Heterogeneity across studies was high because of factors such as different costing methods, design, comparison groups, and outcomes used. IMIs for anxiety and depression have potential to be cost-effective. However, more research is needed into unguided (preventive) IMIs with active control conditions (e.g., treatment as usual) and longer time horizon across a wider range of disorders.

The phenotypic spectrum associated with loss-of-function variants in monogenic epilepsy genes in the general population
V Smuk et al, EJHG, October 17, 2022 (Posted: Oct 17, 2022 6AM)

We selected 127 established monogenic epilepsy genes and explored rare loss-of-function (LoF) variant associations with 3700 phenotypes across 281,850 individuals from the UK Biobank with whole-exome sequencing data. For 5.5% of epilepsy genes, we found significant associations of LoF variants with non-epilepsy phenotypes, mostly related to mental health. These findings suggest that LoF variants in epilepsy genes are associated with neurological or psychiatric phenotypes in the general population

Can Smartphones Help Predict Suicide?
E Barry, NY Times, September 30, 2022 (Posted: Oct 01, 2022 7AM)

In the field of mental health, few new areas generate as much excitement as machine learning, which uses computer algorithms to better predict human behavior. There is, at the same time, exploding interest in biosensors that can track a person’s mood in real time, factoring in music choices, social media posts, facial expression and vocal expression. A unique research project is tracking hundreds of people at risk for suicide, using data from smartphones and wearable biosensors to identify periods of high danger — and intervene.

Ten challenges for clinical translation in psychiatric genetics.
Derks Eske M et al. Nature genetics 2022 9 (Posted: Sep 29, 2022 8AM)

There are several challenges that must be addressed before genetic findings can be translated into the clinic. In this Perspective, we highlight ten challenges for the field of psychiatric genetics, focused on the robust and generalizable detection of genetic risk factors, improved definition and assessment of psychopathology and achieving better clinical indicators. We discuss recent advancements in the field that will improve the explanatory and predictive power of genetic data and ultimately contribute to improving the management and treatment of patients with a psychiatric disorder.

Potential and Pitfalls of Mobile Mental Health Apps in Traditional Treatment: An Umbrella Review
J koh et al, J Per Med, August 25, 2022 (Posted: Aug 25, 2022 0PM)

A total of 36 reviews published between 2014 and 2022—including systematic reviews, meta-analyses, scoping reviews, and literature reviews—were identified . The majority of results supported the key potential of apps in helping to (1) provide timely support, (2) ease the costs of mental healthcare, (3) combat stigma in help-seeking, and (4) enhance therapeutic outcomes. Our results also identified common themes of apps’ pitfalls (i.e., challenges faced by app users), including (1) user engagement issues, (2) safety issues in emergencies, (3) privacy and confidentiality breaches, and (4) the utilization of non-evidence-based approaches.

Integrative analysis of genomic and exposomic influences on youth mental health.
Choi Karmel W et al. Journal of child psychology and psychiatry, and allied disciplines 2022 8 (Posted: Aug 11, 2022 7AM)

Understanding complex influences on mental health problems in young people is needed to inform early prevention strategies. Both genetic and environmental factors are known to influence youth mental health, but a more comprehensive picture of their interplay, including wide-ranging environmental exposures – that is, the exposome – is needed. We perform an integrative analysis of genomic and exposomic data in relation to internalizing and externalizing symptoms in a cohort of 4,314 unrelated youth from the Adolescent Brain and Cognitive Development (ABCD) Study.

The performance of artificial intelligence-driven technologies in diagnosing mental disorders: an umbrella review
A Abd-Alrazak et al, NPJ Digital Medicine, July 7, 2022 (Posted: Jul 08, 2022 7AM)

We included 15 systematic reviews of 852 citations identified. The included reviews assessed the performance of AI models in diagnosing Alzheimer’s disease (n?=?7), mild cognitive impairment (n?=?6), schizophrenia (n?=?3), bipolar disease (n?=?2), autism spectrum disorder (n?=?1), obsessive-compulsive disorder (n?=?1), post-traumatic stress disorder (n?=?1), and psychotic disorders (n?=?1). The performance of the AI models in diagnosing these mental disorders ranged between 21% and 100%. AI technologies offer great promise in diagnosing mental health disorders. The reported performance metrics paint a vivid picture of a bright future for AI in this field.

Mendelian randomization analysis for attention deficit/hyperactivity disorder: studying a broad range of exposures and outcomes.
Soler Artigas María et al. International journal of epidemiology 2022 6 (Posted: Jun 18, 2022 10AM)

We used genome-wide association study (GWAS) summary statistics for ADHD (n?=?53?293) and 124 traits related to anthropometry, cognitive function and intelligence, early life exposures, education and employment, lifestyle and environment, longevity, neurological, and psychiatric and mental health or personality and psychosocial factors available in the MR-Base database (16?067 =n?=766?345). Our findings strengthen previous evidence of a causal effect of ADHD liability on smoking and major depression, and are consistent with a causal effect on odds of decreased average total household income [odds ratio (OR)?=?0.966, 95% credible interval (CrI)?=?(0.954, 0.979)] and increased lifetime number of sexual partners [OR?=?1.023, 95% CrI?=?(1.013, 1.033)].

Machine learning paves the way toward the prevention of mental health crises
Nature Medicine, May 18, 2022 (Posted: May 19, 2022 10AM)

Experiencing a mental health crisis has a detrimental impact on a patient’s life. A machine learning algorithm trained retrospectively with electronic health records can predict almost 60% of mental health crises 4 weeks in advance. Prospective evaluation of the algorithm in clinical practice reveals its potential to enable preemptive interventions.

Machine learning model to predict mental health crises from electronic health records
R Garriga et al, Nature Medicine, May 16, 2022 (Posted: May 17, 2022 11AM)

We developed a machine learning model that uses electronic health records to continuously monitor patients for risk of a mental health crisis over a period of 28?days. The model achieves an area under the receiver operating characteristic curve of 0.797 and an area under the precision-recall curve of 0.159, predicting crises with a sensitivity of 58% at a specificity of 85%. A follow-up 6-month prospective study evaluated our algorithm’s use in clinical practice and observed predictions to be clinically valuable in terms of either managing caseloads or mitigating the risk of crisis in 64% of cases.

Built environment’s impact on COVID-19 transmission and mental health revealed by COVID-19 Participant Experience data from the All of Us Research Program
W Luo et al, MEDRXIV, April 8, 2022 (Posted: Apr 09, 2022 8AM)

Machine learning of language use on Twitter reveals weak and non-specific predictions
SW Kelley et al, NPJ Digital Medicine, March 25, 2022 (Posted: Mar 26, 2022 3PM)

Depressed individuals use language differently than healthy controls and it has been proposed that social media posts can be used to identify depression. Much of the evidence behind this claim relies on indirect measures of mental health and few studies have tested if these language features are specific to depression versus other aspects of mental health. We analysed the Tweets of 1006 participants who completed questionnaires assessing symptoms of depression and 8 other mental health conditions.

Evidence Used to Update the List of Underlying Medical Conditions Associated with Higher Risk for Severe COVID-19
CDC Science Brief, October 14, 2021 Brand (Posted: Oct 16, 2021 8AM)

Chronic lung disease (including bronchiectasis, bronchopulmonary dysplasia, interstitial lung disease, pulmonary hypertension, pulmonary embolism, tuberculosis) and chronic liver disease (including cirrhosis, non-alcoholic fatty liver disease, alcoholic liver disease, and autoimmune hepatitis) were added September 2021 based on evidence published between December 1, 2019 and August 31, 2021 using the updated review methods outlined below. Mental health disorders (such as mood disorders including depression, and schizophrenia spectrum disorders) were added September 2021 based on evidence published between December 1, 2019 and August 31, 2021. No conditions were removed from the previous underlying medical conditions list.

Short-term and Long-term Rates of Postacute Sequelae of SARS-CoV-2 Infection A Systematic Review
D Groff et al, JAMA Network Open, October 13, 2021 (Posted: Oct 13, 2021 4PM)

In this systematic review of 57 studies comprising more than 250?000 survivors of COVID-19, more than half of COVID-19 survivors experienced PASC 6 months after recovery. The most common PASC involved functional mobility impairments, pulmonary abnormalities, and mental health disorders. These long-term PASC effects occur on a scale that could overwhelm existing health care capacity, particularly in low- and middle-income countries.

The maternal microbiome: another bridge linking mothers and infants
Ebiomedicine editorial, September 30, 2021, (Posted: Oct 01, 2021 7AM)

A total of 10–100 trillion microbes live symbiotically within each human host and are thought to affect our physical and mental health. The health effects are thought to begin as early as the gestational period. Research shows that maternal gut microbes may have both direct and indirect effects during pregnancy.

Cultural adaptation: a framework for addressing an often-overlooked dimension of digital health accessibility
JS Marwaha et al, NPJ Digital Medicine, October 1, 2021 (Posted: Oct 01, 2021 6AM)

Relatively little is known about how to make digital health tools accessible to different populations from a cultural standpoint. Alignment with cultural values and communication styles may affect these tools’ ability to diagnose and treat various conditions. In this Editorial, we highlight the findings of recent work to make digital tools for mental health more culturally accessible, and propose ways to advance this area of study.

Mental health: build predictive models to steer policy Combine economic, social and medical data to forecast need and design services to address the growing crisis.
JA Occhipinti et al, Nature, September 26, 2021 (Posted: Sep 27, 2021 7AM)

We argue that a systems-modelling approach should be used to tackle the mental-health challenge. Drawing together qualitative and quantitative evidence and data, models should capture changes triggered by the pandemic — such as education loss, job loss, domestic violence, social isolation, fear and uncertainty. Models should forecast demand for community mental-health services and acute care, including emergency-department presentations and psychiatric hospitalizations, as well as outcomes such as suicidal behavior.

Identification of social determinants of health using multi-label classification of electronic health record clinical notes.
Stemerman Rachel et al. JAMIA open 2021 4(3) ooaa069 (Posted: Sep 17, 2021 6AM)

Social determinants of health (SDH), key contributors to health, are rarely systematically measured and collected in the electronic health record (EHR). We investigate how to leverage clinical notes using novel applications of multi-label learning (MLL) to classify SDH in mental health and substance use disorder patients who frequent the emergency department.

Cultural adaptation of internet- and mobile-based interventions for mental disorders: a systematic review
K Spanhel et al, NPJ Digital Medicine, August 25, 2021 (Posted: Aug 26, 2021 7AM)

Providing accessible and effective healthcare solutions for people living in low- and middle-income countries, migrants, and indigenous people is central to reduce the global mental health treatment gap. Internet- and mobile-based interventions (IMI) are considered scalable psychological interventions to reduce the burden of mental disorders and are culturally adapted for implementation in these target groups.

To benefit diverse groups, AI must address bias, researchers say
J Lee, Stanford Scope Blog, June 8, 2021 (Posted: Jun 10, 2021 7AM)

Artificial intelligence has the potential to transform health and medicine, from improving access to mental health care to tagging molecular details in tumor images. AI algorithms can spot patterns in massive troves of data -- even better than humans, in some cases. These technologies, however, are susceptible to bias. Biases in sex, gender and race within datasets can produce models that are poor predictors for certain groups, and the use of such biased models could exacerbate existing structural health disparities.

"It seems like COVID-19 now is the only disease present on Earth": living with a rare or undiagnosed disease during the COVID-19 pandemic.
Halley Meghan C et al. Genetics in medicine : official journal of the American College of Medical Genetics 2021 1 (5) 837-844 (Posted: May 10, 2021 7AM)

Respondents (n?=?413), including 274 RUD patients and 139 family members, were predominantly female and white, though income varied. Impacts of the pandemic included (1) barriers to accessing essential health care, (2) specific impacts of restrictive COVID-19 visitation policies on ability to advocate in health-care settings, (3) uncertainty and fear regarding COVID-19 risk, (4) exacerbated physical and mental health challenges, (5) magnified impacts of reduced educational and therapeutic services, and (6) unexpected positive changes due to the pandemic.

Engagement and return of results preferences among a primarily African American genomic sequencing research cohort.
Lewis Katie L et al. American journal of human genetics 2021 4 (Posted: Apr 26, 2021 8AM)

Many focus group members preferred engagement modalities that are offered to all participants and allow them to share the nuances of their perspectives over the use of participant representatives and surveys. All groups created a consensus ranking for result return priorities. Results for life-threatening conditions were the highest priority to return, followed by those related to treatable conditions that affect physical or mental health.

High-dimensional characterization of post-acute sequalae of COVID-19.
Al-Aly Ziyad et al. Nature 2021 4 (Posted: Apr 23, 2021 10AM)

We use the national healthcare databases of the US Department of Veterans Affairs to systematically and comprehensively identify 6-month incident sequalae including diagnoses, medication use, and laboratory abnormalities in 30-day survivors of COVID-19. We show that beyond the first 30 days of illness, people with COVID-19 exhibit higher risk of death and health resource utilization. Our high dimensional approach identifies incident sequalae in the respiratory system and several others including nervous system and neurocognitive disorders, mental health disorders, metabolic disorders, cardiovascular disorders, gastrointestinal disorders, malaise, fatigue, musculoskeletal pain, and anemia.

Mental health inequalities in healthcare, economic, and housing disruption during COVID -19: an investigation in 12 longitudinal studies
G Di Gessa et al, MEDRXIV, April 7, 2021 (Posted: Apr 07, 2021 7AM)

Those suffering from psychological distress before the pandemic were more likely to experience healthcare disruptions, economic disruptions related to unemployment and loss of income, and to clusters of disruptions across multiple domains during the pandemic. The pandemic may exacerbate existing mental health inequalities. Individuals with poor mental health may need additional support to manage these pandemic-associated disruptions.

Social Media Toolkit: COVID-19 & Mental Health
CDC, December 28, 2020 Brand (Posted: Dec 29, 2020 2PM)

Everyone reacts differently to stressful situations like COVID-19. You may feel anxiousness, anger, sadness, or overwhelmed. Find ways to reduce your stress to help yourself and the people you care about. Learn the common signs of stress. Make time to unwind and do activities you enjoy. Talk with family and friends by phone, text, or email.

Social Media Insights Into US Mental Health Amid the COVID-19 Pandemic. A Longitudinal Twitter Analysis (JANUARY-APRIL 2020)
D Valdez et al, MEDRXIV, December 10, 2020 (Posted: Dec 11, 2020 9AM)

COVID-19 Pandemic Health Disparities and Pediatric Health Care—The Promise of Telehealth
DU Menon et al, JAMA Pediatrics, December 7, 2020 (Posted: Dec 07, 2020 11AM)

What can we do to bridge the physical and mental health care gaps exacerbated during mitigation strategies to reduce COVID-19? Telehealth may provide part of the answer. The ubiquity of cell phones across the US, with approximately 96% of US citizens owning cell phones, supports the expansion of telehealth. The Pew Research Center found an equal distribution of cell phone ownership across White, Black, and Hispanic/Latinx populations and urban, suburban, and rural environments.

COVID-19 and Psychological Distress-Changes in Internet Searches for Mental Health Issues in New York During the Pandemic.
Stijelja Stefan et al. JAMA internal medicine 2020 Oct (Posted: Oct 19, 2020 8AM)

Searches for anxiety, panic attack, and insomnia rose significantly during the lockdown, then eventually reverted to their mean. Assuming this is indicative of significant increases in these symptoms, this suggests the need to provide focused competent online and telemedicine services during quarantines.

Preventive digital mental health interventions for children and young people: a review of the design and reporting of research
AD Bergin et al, NPJ Digital Medicine, October 15, 2020 (Posted: Oct 17, 2020 0PM)

Twenty-one different interventions were identified from 30 publications, which took a universal (n?=?12), selective (n?=?3) and indicative (n?=?15) approach to preventing poor mental health. Most interventions targeted adolescents, with only two studies including children aged =10?years. Barriers and facilitators to implementation varied across the delivery settings.

An Exploration of Impact of COVID 19 on mental health -Analysis of tweets using Natural Language Processing techniques
S Sengupta et al, MEDRXIV, August 4, 2020 (Posted: Aug 04, 2020 9AM)

The association of alcohol polygenic risk scores with mental health outcomes: A multi-generational analysis in the Avon Longitudinal Study of Parents and Children
KE Easey et al, MEDRXIV, July 7, 2020 (Posted: Jul 08, 2020 6AM)

An alcohol PRS derived from GWAS of alcohol use in the general population was shown to be associated with frequency and amount of alcohol consumed during pregnancy, and maternal depression at 32 weeks gestation.

A pragmatic randomized waitlist-controlled effectiveness and cost-effectiveness trial of digital interventions for depression and anxiety
D Richards et al, NPJ Digital Medicine, June 15, 2020 (Posted: Jun 16, 2020 9AM)

Utilization of internet-delivered cognitive behavioral therapy (iCBT) for treating depression and anxiety disorders in stepped-care models, such as the UK’s Improving Access to Psychological Therapies (IAPT), is a potential solution for addressing the treatment gap in mental health.

A Development Pathway Towards Precision Mental Health Care
J Delgadillo et al, JAMA Psychiatry, May 27, 2020 (Posted: May 30, 2020 7AM)

Precision mental health care evolves in environments where clinicians are trained and required to measure outcomes. Within such a context, developing prognostic models becomes feasible and inexpensive because health care records and patient-reported data are leveraged for this purpose.

A Framework for Advancing Precision Medicine in Clinical Trials for Mental Disorders
EJ Lenze et al, JAMA Psychiatry, March 26, 2020 (Posted: Mar 29, 2020 8AM)

Getting the right treatment to the right patient is a frustrating goal in mental health: treatment is a trial-and-error endeavor, often yielding disappointing outcomes. Why? Traditional randomized clinical trials (RCTs) do not adequately capture the dynamic complexity of the brain and behavior during treatment.

Methods in predictive techniques for mental health status on social media: a critical review
S Chancellor, NPJ Digital Medicine, March 24, 2020 (Posted: Mar 25, 2020 10AM)

Standalone smartphone apps for mental health—a systematic review and meta-analysis
KK Weisel et al, NPJ DIgital Medicine, December 2, 2019 (Posted: Dec 03, 2019 8AM)

Although some trials showed potential of apps targeting mental health symptoms, using smartphone apps as standalone psychological interventions cannot be recommended based on the current level of evidence.

What health records data are required for accurate prediction of suicidal behavior?
Simon Gregory E et al. Journal of the American Medical Informatics Association : JAMIA 2019 Sep (Posted: Sep 25, 2019 9AM)

The study sought to evaluate how availability of different types of health records data affect the accuracy of machine learning models predicting suicidal behavior.Records from 7 large health systems identified 19 061 056 outpatient visits to mental health specialty or general medical providers between 2009 and 2015.

How Artificial Intelligence Can Save Your Life
D Brooks, NY Times, June 24, 2019 (Posted: Jun 25, 2019 9AM)

One area where A.I. can most immediately improve our lives may be in the area of mental health. Unlike many illnesses, there?s no simple physical test you can give someone to tell if he or she is suffering from depression.

Pharmacogenetic Testing: Why Is It So Disappointing?
Limandri Barbara J et al. Journal of psychosocial nursing and mental health services 2019 Apr 57(4) 9-12 (Posted: Apr 03, 2019 9AM)

Big Data From Health Records in Mental Health Care- Hardly Clairvoyant But Already Useful
GE Simon, JAMA Psychiatry, March 2019 (Posted: Mar 03, 2019 10AM)

Links between gut microbes and depression strengthened- The once-wild idea that intestinal bacteria influence mental health has transformed into a major research pursuit
Nature editorial, February 4, 2019 (Posted: Feb 04, 2019 11AM)

If genomics is the answer, what's the question? A commentary on PsychENCODE
K Mitchell, Wiring the Brain, December 20, 2018 (Posted: Dec 21, 2018 9AM)

How data science can advance mental health research
TC Russ et al, Nature Human Behavior, December 10, 2018 (Posted: Dec 11, 2018 10AM)

Twenty years of research on attention-deficit/hyperactivity disorder (ADHD): looking back, looking forward.
Cortese Samuele et al. Evidence-based mental health 2018 Nov (4) 173-176 (Posted: Nov 27, 2018 10AM)

The use of pharmacogenetic testing in patients with schizophrenia or bipolar disorder: A systematic review.
Routhieaux Melanie et al. The mental health clinician 2018 Nov 8(6) 294-302 (Posted: Nov 07, 2018 11AM)

Overview of pharmacogenomic testing in clinical practice.
Gross Tonya et al. The mental health clinician 2018 Sep 8(5) 235-241 (Posted: Sep 19, 2018 9AM)

Suicide rising across the US- More than a mental health concern
CDC Vital Signs, June 2018 Brand (Posted: Jun 07, 2018 4PM)

Mental disorders may share molecular origins
NIH Research Matters, Feb 27, 2018 Brand (Posted: Feb 27, 2018 11AM)

What is Post-Traumatic Stress Disorder
National Institute for Mental Health Brand (Posted: Sep 07, 2017 3PM)

Epigenetics, nutrition and mental health. Is there a relationship?
Stevens Aaron J et al. Nutritional neuroscience 2017 May 1-12 (Posted: Jul 12, 2017 6PM)

Genetics of Schizophrenia: Overview of Methods, Findings and Limitations.
Henriksen Mads G et al. Frontiers in human neuroscience 2017 322 (Posted: Jul 12, 2017 6PM)

Mental Health Public Health Information
Brand (Posted: Jul 12, 2017 6PM)

Reviewing the epigenetics of schizophrenia.
Cromby John et al. Journal of mental health (Abingdon, England) 2016 Aug 1-9 (Posted: Sep 25, 2016 8PM)

More harm than good? Use of genetic mental health tests has grown rapidly. But evidence they work is scant. (+documentation)
B Daley, NECIR, Health and Safety, October 3, 2015 (Posted: Oct 05, 2015 11AM)

What is Post-traumatic Stress Disorder (PTSD)?
Health Topics from the National Institute for Mental Health Brand (Posted: May 17, 2015 10AM)

Mental Health Awareness Month: By the Numbers
NIMH Director's Blog, May 2015 Brand (Posted: May 16, 2015 7AM)

New NIMH strategic plan aims to focus, accelerate mental health research
NIH News, March 26, 2015 Brand (Posted: Apr 06, 2015 10AM)

The National Institute of Mental Health Strategic Plan
Brand (Posted: Apr 05, 2015 9AM)

Mental health: thinking from the gut
Charles Schmidt, Nature, February 26, 2015 (Posted: Feb 25, 2015 3PM)

Cardiac Rehabilitation
From NHLBI health topic site Brand (Posted: Jan 01, 2014 0AM)

Cardiac rehabilitation, also called cardiac rehab, is a medically supervised program for people who have had a heart attack, heart failure, heart valve surgery, coronary artery bypass grafting, or percutaneous coronary intervention. Overview Cardiac rehab involves adopting heart-healthy lifestyle changes to address risk factors for cardiovascular disease. To help you adopt lifestyle changes, this program includes exercise training, education on heart-healthy living, and counseling to reduce stress and help you return to an active life. Cardiac rehab can improve your health and quality of life, reduce the need for medicines to treat heart or chest pain, decrease the chance you will go back to a hospital or emergency room for a heart problem, prevent future heart problems, and even help you live longer. Cardiac rehab is provided in an outpatient clinic or in a hospital rehab center. The cardiac rehab team includes doctors, nurses, exercise specialists, physical and occupational therapists, dietitians or nutritionists, and mental health specialists. Sometimes a case manager will help track your care. Your cardiac rehab team will design a program to meet your needs. Before starting your program, the rehab team will take your medical history, do a physical exam, and perform tests. Possible tests include an electrocardiogram (EKG), cardiac imaging tests, and a treadmill or stationary bike exercise test. You also may have tests to measure your cholesterol and blood sugar levels. During cardiac rehab, you will learn to exercise safely and increase your physical activity. The length of time that you spend in cardiac rehab depends on your condition. Medicare and most insurance plans cover a standard cardiac rehab program that includes 36 supervised sessions over 12 weeks. The heart-healthy lifestyle changes in cardiac rehab have few risks. Very rarely, physical activity during rehab can cause serious problems, such as injuries to your muscles and bones, or possibly life-threatening heart rhythm problems. If serious problems occur during the supervised sessions, the rehab team will immediately stop the physical activity, administer appropriate treatment, and contact your doctor.


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