PCOM Library / Hot Topics in Research / Archive for "Psychology and Psychiatry"

Category: Psychology and Psychiatry

Hot Topics: Computer Models Could Predict Suicide Risk

Jackie Werner Hot Topics in Research, Psychology and Psychiatry

Validation of an Electronic Health Record–Based Suicide Risk Prediction Modeling Approach Across Multiple Health Care Systems

Barak-Corren Y, Castro VM, Nock MK, et al. Validation of an electronic health Record–Based suicide risk prediction modeling approach across multiple health care systems. JAMA Netw Open. 2020;3(3):e201262. https://doi.org/10.1001/jamanetworkopen.2020.1262.

Importance  Suicide is a leading cause of mortality, with suicide-related deaths increasing in recent years. Automated methods for individualized risk prediction have great potential to address this growing public health threat. To facilitate their adoption, they must first be validated across diverse health care settings.

Objective  To evaluate the generalizability and cross-site performance of a risk prediction method using readily available structured data from electronic health records in predicting incident suicide attempts across multiple, independent, US health care systems.

Design, Setting, and Participants  For this prognostic study, data were extracted from longitudinal electronic health record data comprising International Classification of Diseases, Ninth Revision diagnoses, laboratory test results, procedures codes, and medications for more than 3.7 million patients from 5 independent health care systems participating in the Accessible Research Commons for Health network. Across sites, 6 to 17 years’ worth of data were available, up to 2018. Outcomes were defined by International Classification of Diseases, Ninth Revision codes reflecting incident suicide attempts (with positive predictive value >0.70 according to expert clinician medical record review). Models were trained using naive Bayes classifiers in each of the 5 systems. Models were cross-validated in independent data sets at each site, and performance metrics were calculated. Data analysis was performed from November 2017 to August 2019.

Main Outcomes and Measures  The primary outcome was suicide attempt as defined by a previously validated case definition using International Classification of Diseases, Ninth Revision codes. The accuracy and timeliness of the prediction were measured at each site.

Results  Across the 5 health care systems, of the 3 714 105 patients (2 130 454 female [57.2%]) included in the analysis, 39 162 cases (1.1%) were identified. Predictive features varied by site but, as expected, the most common predictors reflected mental health conditions (eg, borderline personality disorder, with odds ratios of 8.1-12.9, and bipolar disorder, with odds ratios of 0.9-9.1) and substance use disorders (eg, drug withdrawal syndrome, with odds ratios of 7.0-12.9). Despite variation in geographical location, demographic characteristics, and population health characteristics, model performance was similar across sites, with areas under the curve ranging from 0.71 (95% CI, 0.70-0.72) to 0.76 (95% CI, 0.75-0.77). Across sites, at a specificity of 90%, the models detected a mean of 38% of cases a mean of 2.1 years in advance.

Conclusions and Relevance  Across 5 diverse health care systems, a computationally efficient approach leveraging the full spectrum of structured electronic health record data was able to detect the risk of suicidal behavior in unselected patients. This approach could facilitate the development of clinical decision support tools that inform risk reduction interventions.

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Hot Topics: Online Resource May Address Suicide Risk

Jackie Werner Hot Topics in Research, Psychology and Psychiatry

Lock to Live—An Interactive Web-Based Lethal Means Safety Decision Aid for Suicidal Adults: Pilot Randomized Controlled Trial

Betz ME, Knoepke CE, Simpson S, et al. Lock to Live—An interactive web-based lethal means safety decision aid for suicidal adults: Pilot randomized controlled trial. J Med Internet Res. 2020;22(1). https://doi.org/10.2196/16253.

Background: Counseling to reduce access to lethal means such as firearms and medications is recommended for suicidal adults but does not routinely occur. We developed the Web-based Lock to Live (L2L) decision aid to help suicidal adults and their families choose options for safer home storage.

Objective: This study aimed to test the feasibility and acceptability of L2L among suicidal adults in emergency departments (EDs).

Methods: At 4 EDs, we enrolled participants (English-speaking, community-dwelling, suicidal adults) in a pilot randomized controlled trial. Participants were randomized in a 13:7 ratio to L2L or control (website with general suicide prevention information) groups and received a 1-week follow-up telephone call.

Results: Baseline characteristics were similar between the intervention (n=33) and control (n=16) groups. At baseline, many participants reported having access to firearms (33/49, 67%), medications (46/49, 94%), or both (29/49, 59%). Participants viewed L2L for a median of 6 min (IQR 4-10 min). L2L also had very high acceptability; almost all participants reported that they would recommend it to someone in the same situation, that the options felt realistic, and that L2L was respectful of values about firearms. In an exploratory analysis of this pilot trial, more participants in the L2L group reported reduced firearm access at follow-up, although the differences were not statistically significant.

Conclusions: The L2L decision aid appears feasible and acceptable for use among adults with suicide risk and may be a useful adjunct to lethal means counseling and other suicide prevention interventions. Future large-scale studies are needed to determine the effect on home access to lethal means.

Hot Topics: Novel Target for Addiction Treatment

Jackie Werner Hot Topics in Research, Neurology, Pharmaceutical Sciences, Substance Use Disorders

Dopamine-Evoked Synaptic Regulation in the Nucleus Accumbens Requires Astrocyte Activity

Corkrum M, Covelo A, Lines J, et al. Dopamine-evoked synaptic regulation in the nucleus accumbens requires astrocyte activity. Neuron. 2020. https://doi.org/10.1016/j.neuron.2019.12.026.

Dopamine is involved in physiological processes like learning and memory, motor control and reward, and pathological conditions such as Parkinson’s disease and addiction. In contrast to the extensive studies on neurons, astrocyte involvement in dopaminergic signaling remains largely unknown. Using transgenic mice, optogenetics, and pharmacogenetics, we studied the role of astrocytes on the dopaminergic system. We show that in freely behaving mice, astrocytes in the nucleus accumbens (NAc), a key reward center in the brain, respond with Ca2+ elevations to synaptically released dopamine, a phenomenon enhanced by amphetamine. In brain slices, synaptically released dopamine increases astrocyte Ca2+, stimulates ATP/adenosine release, and depresses excitatory synaptic transmission through activation of presynaptic A1 receptors. Amphetamine depresses neurotransmission through stimulation of astrocytes and the consequent A1 receptor activation. Furthermore, astrocytes modulate the acute behavioral psychomotor effects of amphetamine. Therefore, astrocytes mediate the dopamine- and amphetamine-induced synaptic regulation, revealing a novel cellular pathway in the brain reward system.

Hot Topics: Flavored Vapes Hook Teens

Jackie Werner Hot Topics in Research, Pediatrics, Substance Use Disorders

Flavored E-cigarette Use and Progression of Vaping in Adolescents

Leventhal, A. M., Goldenson, N. I., Cho, J., Kirkpatrick, M. G., McConnell, R. S., Stone, M. D., . . . Barrington-Trimis, J. L. (2019). Flavored E-cigarette use and progression of vaping in adolescents. Pediatrics. https://dx.doi.org/10.1542/peds.2019-0789

OBJECTIVES: Electronic cigarettes (e-cigarettes) are available in nontraditional flavors (eg, fruit and candy) that are banned in combustible cigarettes in the United States. Whether adolescent use of e-cigarettes in nontraditional flavors prospectively predicts continuation of vaping and progression to more frequent vaping is unknown.

METHODS: High school students in Los Angeles, California, completed 5 semiannual surveys (2014–2017 [10th grade to 12th grade]). Among past-6-month e-cigarette users at survey waves 1 to 4 (N = 478), e-cigarette flavor (or flavors) used was coded into 2 mutually exclusive categories at each wave (use of ≥1 nontraditional flavors [fruit, candy, sweet or dessert, buttery, blends or combinations, and other] versus exclusive use of tobacco, menthol or mint, or flavorless). Flavor used during waves 1 to 4 was modeled as a time-varying, time-lagged regressor of vaping status and frequency outcomes 6 months later at waves 2 to 5.

RESULTS: Across waves 1 to 4, there were 739 (93.8%) observations of nontraditional-flavor use and 49 (6.2%) observations of exclusive use of tobacco, mint or menthol, or flavorless e-cigarettes. Use of e-cigarettes in nontraditional flavors (versus only tobacco, mint or menthol, or flavorless) was positively associated with vaping continuation (64.3% vs 42.9%; adjusted odds ratio = 3.76 [95% confidence interval 1.20 to 10.31]) and past-30-day number of puffs per nicotine vaping episode (mean: 3.1 [SD 5.5] vs 1.5 [SD 3.8]; adjusted rate ratio = 2.41 [95% confidence interval 1.08 to 5.92]) 6 months later. Flavor used was not associated with the subsequent number of past-30-day vaping days or episodes per day.

CONCLUSIONS: Adolescents who vaped e-cigarettes in nontraditional flavors, compared with those who exclusively vaped tobacco-flavored, mint- or menthol-flavored, or flavorless e-cigarettes, were more likely to continue vaping and take more puffs per vaping occasion 6 months later.

Hot Topics: Stress Influences Circadian Clock

Jackie Werner Hot Topics in Research, Psychology and Psychiatry

The eIF2α Kinase GCN2 Modulates Period and Rhythmicity of the Circadian Clock by Translational Control of Atf4

Pathak, S. S., Liu, D., Li, T., de Zavalia, N., Zhu, L., Li, J., . . . Cao, R. (2019). The eIF2α kinase GCN2 modulates period and rhythmicity of the circadian clock by translational control of Atf4https://doi.org/10.1016/j.neuron.2019.08.007

The integrated stress response (ISR) is activated in response to diverse stress stimuli to maintain homeostasis in neurons. Central to this process is the phosphorylation of eukaryotic translation initiation factor 2 alpha (eIF2α). Here, we report a critical role for ISR in regulating the mammalian circadian clock. The eIF2α kinase GCN2 rhythmically phosphorylates eIF2α in the suprachiasmatic circadian clock. Increased eIF2α phosphorylation shortens the circadian period in both fibroblasts and mice, whereas reduced eIF2α phosphorylation lengthens the circadian period and impairs circadian rhythmicity in animals. Mechanistically, phosphorylation of eIF2α promotes mRNA translation of Atf4. ATF4 binding motifs are identified in multiple clock genes, including Per2Per3Cry1Cry2, and Clock. ATF4 binds to the TTGCAGCA motif in the Per2 promoter and activates its transcription. Together, these results demonstrate a significant role for ISR in circadian physiology and provide a potential link between dysregulated ISR and circadian dysfunction in brain diseases.

Hot Topics: Autism Linked to High Estrogen in Womb

Jackie Werner Developmental Disorders, Hot Topics in Research, Psychology and Psychiatry

Foetal oestrogens and autism

Baron-Cohen S, Tsompanidis A, Auyeung B, et al. Foetal oestrogens and autism. Mol Psychiatry. 2019. https://doi.org/10.1038/s41380-019-0454-9.

Elevated latent prenatal steroidogenic activity has been found in the amniotic fluid of autistic boys, based on measuring prenatal androgens and other steroid hormones. To date, it is unclear if other prenatal steroids also contribute to autism likelihood. Prenatal oestrogens need to be investigated, as they play a key role in synaptogenesis and corticogenesis during prenatal development, in both males and females. Here we test whether levels of prenatal oestriol, oestradiol, oestrone and oestrone sulphate in amniotic fluid are associated with autism, in the same Danish Historic Birth Cohort, in which prenatal androgens were measured, using univariate logistic regression (n= 98 cases, n= 177 controls). We also make a like-to-like comparison between the prenatal oestrogens and androgens. Oestradiol, oestrone, oestriol and progesterone each related to autism in univariate analyses after correction with false discovery rate. A comparison of standardised odds ratios showed that oestradiol, oestrone and progesterone had the largest effects on autism likelihood. These results for the first time show that prenatal oestrogens contribute to autism likelihood, extending the finding of elevated prenatal steroidogenic activity in autism. This likely affects sexual differentiation, brain development and function.

Hot Topics: Medical Selfies Empower Patients

Jackie Werner Family Medicine, Hot Topics in Research, Psychology and Psychiatry

Creating Consumer-Generated Health Data: Interviews and a Pilot Trial Exploring How and Why Patients Engage

Burns K, McBride CA, Patel B, FitzGerald G, Mathews S, Drennan J. Creating consumer-generated health data: Interviews and a pilot trial exploring how and why patients engage. Journal of Medical Internet Research. 2019;21(6):e12367. https://doi.org/10.2196/12367

Background: Consumer-generated health data (CGHD) are any clinically relevant data collected by patients or their carers (consumers) that may improve health care outcomes. Like patient experience measures, these data reflect the consumer perspective and is part of a patient-centric agenda. The use of CGHD is believed to enhance diagnosis, patient engagement, and thus foster an improved therapeutic partnership with health care providers.

Objective: The aim of this study was to further identify how these data were used by consumers and how it influences engagement via a validated framework. In addition, carer data has not been explored for the purpose of engagement.

Methods: Study 1 used interviews with CGHD-experienced patients, carers, and doctors to understand attitudes about data collection and use, developing an ontological framework. Study 2 was a pilot trial with carers (parents) of children undergoing laparoscopic appendectomy. For 10 days carers generated and emailed surgical site photographs to a tertiary children’s hospital. Subsequently, carers were interviewed about the engagement framework. In total, 60 interviews were analyzed using theme and content analysis.

Results: This study validates a framework anchored in engagement literature, which categorizes CGHD engagement outcomes into 4 domains: physiological, cognitive, emotional, and behavioral. CGHD use is complex, interconnected, and can be organized into 10 themes within these 4 domains.

Conclusions: CGHD can instigate an ecosystem of engagement and provide clinicians with an enhanced therapeutic relationship through an extended view into the patient’s world. In addition to clinical diagnosis and efficient use of health care resources, data offer another tool to manage consumers service experience, especially the emotions associated with the health care journey. Collection and use of data increases consumers sense of reassurance, improves communication with providers, and promotes greater personal responsibility, indicating an empowering consumer process. Finally, it can also improve confidence and satisfaction in the service.

Hot Topics: Tobacco plus Cannabis Lowers Functioning

Jackie Werner Hot Topics in Research, Substance Use Disorders

Types of cannabis and tobacco/nicotine co-use and associated outcomes in young adulthood

Tucker JS, Pedersen ER, Seelam R, Dunbar MS, Shih RA, D’Amico EJ. Types of cannabis and tobacco/nicotine co-use and associated outcomes in young adulthood. Psychology of Addictive Behaviors. 2019. https://doi.org/10.1037/adb0000464

Cannabis and tobacco/nicotine use are highly comorbid. Given expanding access to cannabis through legalization for recreational use, it is important to understand how patterns of cannabis and tobacco/nicotine co-use are associated with young adult outcomes. A predominantly California-based sample of 2,429 young adults (mean age = 20.7) completed an online survey. Based on past-year reports of cannabis and tobacco/nicotine use, we defined 5 mutually exclusive groups: (a) single-product use; (b) concurrent use only (using both products, but only on separate occasions); (c) sequential use only (using both products on the same occasion, one right after the other, but not mixing them together); (d) coadministration only (using both products on the same occasion by mixing them in the same delivery device); and (e) both sequential use and coadministration. We examined group differences in use patterns, dependence, consequences of use, and psychosocial functioning. Fifty percent of respondents reported cannabis use, 43% tobacco/nicotine use, and 37% co-use of both substances. The most prevalent method of co-use involved smoking combustible products. Overall, individuals who co-used both substances on the same occasion in some way reported heavier use and greater problematic behaviors than those who did not. Sequential use (especially among those that also engaged in coadministration) was typically associated with worse physical and mental functioning overall compared to using each substance separately. Findings illuminate both prevalence and risks associated with co-use of cannabis and tobacco/nicotine products and can inform policies for states considering regulation of cannabis and tobacco/nicotine products.

Hot Topics: Anti-Stress Receptors Linked to PTSD

Jackie Werner Hot Topics in Research, Psychology and Psychiatry

Decreased Nociceptin Receptors Are Related to Resilience and Recovery in College Women Who Have Experienced Sexual Violence: Therapeutic Implications for Posttraumatic Stress Disorder

Narendran R, Tollefson S, Fasenmyer K, et al. Decreased nociceptin receptors are related to resilience and recovery in college women who have experienced sexual violence: Therapeutic implications for posttraumatic stress disorder. Biological Psychiatry. 2019. https://doi.org/10.1016/j.biopsych.2019.02.017.

Background

Posttraumatic stress disorder (PTSD) is a stress disorder that develops in only some individuals following a traumatic event. Data suggest that a substantial fraction of women recover after sexual violence. Thus, the investigation of stress and antistress neuropeptides in this sample has the potential to inform the neurochemistry of resilience following trauma. Nociceptin is an antistress neuropeptide in the brain that promotes resilience in animal models of PTSD.

Methods

[11C]NOP-1A positron emission tomography was used to measure the in vivobinding to nociceptin receptors in 18 college women who had experienced sexual violence irrespective of whether they met DSM-5 diagnostic criteria for PTSD. [11C]NOP-1A data from 18 healthy control subjects were also included to provide a contrast with the sexual violence group. [11C]NOP-1A total distribution volume (VT) in the regions of interest were measured with kinetic analysis using the arterial input function. The relationships between regional VT and Clinician-Administered PTSD Scale for DSM-5 total symptom and subscale severity were examined using correlational analyses.

Results

No differences in [11C]NOP-1A VT were noted between the sexual violence and control groups. VT in the midbrain and cerebellum were positively correlated with PTSD total symptom severity in the past month before positron emission tomography. Intrusion/re-experiencing and avoidance subscale symptoms drove this relationship. Stratification of subjects by a DSM-5 PTSD diagnosis and contrasting their VT with that in control subjects showed no group differences.

Conclusions

Decreased midbrain and cerebellum nociceptin receptors are associated with less severe PTSD symptoms. Medications that target nociceptin should be explored to prevent and treat PTSD.

Hot Topics: New Schizophrenia Model May Aid Prevention

Jackie Werner Hot Topics in Research, Psychology and Psychiatry, Schizophrenia

Towards Artificial Intelligence in Mental Health by Improving Schizophrenia Prediction with Multiple Brain Parcellation Ensemble-Learning

Kalmady SV, Greiner R, Agrawal R, et al. Towards artificial intelligence in mental health by improving schizophrenia prediction with multiple brain parcellation ensemble-learning. npj Schizophrenia. 2019;5(1):2. https://doi.org/10.1038/s41537-018-0070-8.

In the literature, there are substantial machine learning attempts to classify schizophrenia based on alterations in resting-state (RS) brain patterns using functional magnetic resonance imaging (fMRI). Most earlier studies modelled patients undergoing treatment, entailing confounding with drug effects on brain activity, and making them less applicable to real-world diagnosis at the point of first medical contact. Further, most studies with classification accuracies >80% are based on small sample datasets, which may be insufficient to capture the heterogeneity of schizophrenia, limiting generalization to unseen cases. In this study, we used RS fMRI data collected from a cohort of antipsychotic drug treatment-naive patients meeting DSM IV criteria for schizophrenia (N = 81) as well as age- and sex-matched healthy controls (N = 93). We present an ensemble model — EMPaSchiz (read as ‘Emphasis’; standing for ‘Ensemble algorithm with Multiple Parcellations for Schizophrenia prediction’) that stacks predictions from several ‘single-source’ models, each based on features of regional activity and functional connectivity, over a range of different a priori parcellation schemes. EMPaSchiz yielded a classification accuracy of 87% (vs. chance accuracy of 53%), which out-performs earlier machine learning models built for diagnosing schizophrenia using RS fMRI measures modelled on large samples (N > 100). To our knowledge, EMPaSchiz is first to be reported that has been trained and validated exclusively on data from drug-naive patients diagnosed with schizophrenia. The method relies on a single modality of MRI acquisition and can be readily scaled-up without needing to rebuild parcellation maps from incoming training images.