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Supplemental material, sj-docx-1-cpx-10.1177_21677026231169659 for Do Symptom Severity, Individual Socioeconomic Status, and Neighborhood Socioeconomic Status Explain Differences in Daily Functioning in Non-Latinx Black, Non-Latinx White, and Latinx People With Serious Mental Illnesses? by Arundati Nagendra, Chih-Wei Joshua Liu, Kim T. Mueser, Philip D. Harvey, Colin A. Depp, Raeanne C. Moore, Beshaun Davis and Amy E. Pinkham in Clinical Psychological Science

Childhood trauma (CT) is associated with suicidal ideation and behaviors (SI/SB) in people with psychosis. The Interpersonal Psychological Theory of Suicide (IPTS) suggests that there are four factors that increase suicide risk: thwarted belonginess, perceived burdensomeness, acquired capacity for suicide, and hopelessness. The IPTS constructs and social cognitive biases are associated with SI/SB in psychotic disorders. However; the role of CT in IPTS constructs and social cognitive biases has not been examined in psychosis. In an outpatient community sample of persons with psychotic disorders (N=96) assessed with the Childhood Trauma Questionnaire, the aims of this study were to (1) evaluate rates of CT in this sample, (2) determine the relationship between CT types and lifetime SI/SB, and (3) explore the relationship between CT types, IPTS constructs, and social cognitive biases. All participants reported experiencing CT. Emotional abuse was associated with greater SI severity and higher rates of lifetime suicide attempts (SAs), as well as with greater perceived burdensomeness and more severe negative social cognitive biases. Other CT types were minimally associated with SI/SB or IPST constructs; hopelessness was not associated. Overall, negative interpersonal beliefs and social cognitive biases may explain how CT increases suicide risk in psychosis.

Background: Mental health (MH) apps are growing in popularity. While MH apps may be helpful, less is known about how crises such as suicidal ideation are addressed in apps. Aims: We examined the proportion of MH apps that contained language mentioning suicide or suicidal ideation and how apps communicated these policies and directed users to MH resources through app content, terms of services, and privacy policies. Method: We chose apps using an Internet search of "top mental health apps," similar to how a user might find an app, and extracted information about how crisis language was presented in these apps. Results: We found that crisis language was inconsistent among apps. Overall, 35% of apps provided crisis-specific resources in their app interface and 10.5% contained crisis language in terms of service or privacy policies. Limitations: This study employed a nonsystematic approach to sampling apps, and therefore the findings may not broadly represent apps for MH. Conclusion: To address the inconsistency of crisis resources, crisis language should be included as part of app evaluation frameworks, and internationally accessible, vetted resources should be provided to app users.

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Additional file 4: Table S2. List of studies evaluating the efficacy or validity of the most commonly nominated mood and sleep self-management apps (n = 9).

Additional file 1. Survey of App Use: Perspectives from people living with bipolar disorder.

Additional file 1.

Additional file 3: Table S3. List of studies evaluating the feasibility of the most commonly nominated mood and sleep self-management apps (n = 9).

Contextual influences on social behavior and affective dynamics are not well understood in schizophrenia. We examined the role of social context on emotions, and the motivation to interact in the future, using dynamic network analysis of ecological momentary assessment (EMA) data. Participants included 105 outpatients with schizophrenia or schizoaffective disorder (SZ) and 76 healthy comparators (HC) who completed 7 days, 7 times a day of EMA. Dynamic networks were constructed using EMA data to visualize causal interactions between emotional states, motivation, and context (e.g., location, social interactions). Models were extended to include the type and frequency of interactions and the motivation to interact in the near future. Results indicated SZ networks were generally similar to HC but that contextual influences on emotion and social motivation were more evident in SZ. Further, feedback loops in HC were likely adaptive (e.g., positive emotions leading to social motivation), but most were likely maladaptive in SZ (e.g., sadness leading to reduced happiness leading to increased sadness). Overall, these findings indicate that network analyses may be useful in specifying emotion regulation problems in SZ and that instability related to contextual influences may be a central aspect of aberrant regulation.

ObjectiveNeuropsychological impairments are observed in individuals with Bipolar Disorder (BD), yet knowledge of how cognitive deficits unfold in real-time remains limited. Given intraindividual variability in mood observed in people with BD, and the potential for mood and cognition to be mutually influential, we employed ambulatory assessment technologies to examine potential contemporaneous (same survey) and lagged (next survey) relationships of congition and mood.MethodsOutpatients with BD (n=46) or no psychiatric disorders (heathy volunteers [HV]; n =20) completed in-laboratory neurobehavioral assessments and 14days of smartphone-administered mobile cognitive tests and ratings of affective variables. Linear mixed-effects models were used to analyze real-time relationships between mobile cognitive test performance and mood.ResultsOn in-laboratory tests, participants with BD showed worse cognitive performance than HVs as well as mild depression severity; mood and cognitive performance were unrelated. On mobile cognitive tests and surveys, participants with BD showed somewhat worse cognitive performance and ratings of lower energy and greater sadness relative to HV participants. Among those with BD, mania and sadness earlier in the day related to worse processing speed and better working memory performance, respectively, on the next survey. In contrast, same survey ratings of greater stress related to better working memory, and greater happiness related to better processing speed.ConclusionsReal-time assessments of mood and cognition provide incremental information beyond what can be gleaned from laboratory assessments. Understanding how these affect-related changes in processing speed emerge and play out in daily life may provide clinically useful information for treatment planning.

Premature mortality and increased physical comorbidity associated with bipolar disorder (BD) may be related to accelerated biological aging. Sleep disturbances and inflammation may be key mechanisms underlying accelerated aging in adults with BD. To our knowledge, these relationships have not been examined rigorously. This cross-sectional study included 50 adults with BD and 73 age- and sex-comparable non-psychiatric comparison (NC) subjects, age 26-65 years. Participants were assessed with wrist-worn actigraphy for total sleep time (TST), percent sleep (PS), and bed/wake times for 7 consecutive nights as well as completing scales for subjective sleep quality. Within-individual variability in sleep measures included intra-individual standard deviation (iSD) and atypicality of one evening's sleep. Blood-based inflammatory biomarkers included interleukin (IL)-6, C-reactive protein (CRP), and tumor necrosis factor-alpha (TNF-α). Linear regression analyses tested relationships of mean and iSD sleep variables with inflammatory marker levels; time-lagged analyses tested the influence of the previous evening's sleep on inflammation. BD participants had worse subjective sleep quality, as well as greater TST iSD and wake time iSD compared to the NC group. In all participants, higher TST iSD and lower mean PS were associated with higher IL-6 levels (p=0.04, ηp2=0.042; p=0.05, ηp2=0.039, respectively). Lower mean PS was associated with higher CRP levels (p=0.05, ηp2=0.039). Atypicality of the previous night's TST predicted next day IL-6 levels (p=0.05, ηp2=0.04). All of these relationships were present in both BD and NC groups and remained significant even after controlling for sleep medications. Overall, sleep measures and their variability may influence inflammatory markers in all adults. Thus, sleep may be linked to the inflammatory processes believed to underlie accelerated aging in BD.

Background/aimsAge-related cognitive decline is a pervasive problem in our aging population. To date, no pharmacological treatments to halt or reverse cognitive decline are available. Behavioral interventions, such as physical exercise and Mindfulness-Based Stress Reduction, may reduce or reverse cognitive decline, but rigorously designed randomized controlled trials are needed to test the efficacy of such interventions.MethodsHere, we describe the design of the Mindfulness, Education, and Exercise study, an 18-month randomized controlled trial that will assess the effect of two interventions-mindfulness training plus moderate-to-vigorous intensity exercise or moderate-to-vigorous intensity exercise alone-compared with a health education control group on cognitive function in older adults. An extensive battery of biobehavioral assessments will be used to understand the mechanisms of cognitive remediation, by using structural and resting state functional magnetic resonance imaging, insulin sensitivity, inflammation, and metabolic and behavioral assessments.ResultsWe provide the results from a preliminary study (n = 29) of non-randomized pilot participants who received both the exercise and Mindfulness-Based Stress Reduction interventions. We also provide details on the recruitment and baseline characteristics of the randomized controlled trial sample (n = 585).ConclusionWhen complete, the Mindfulness, Education, and Exercise study will inform the research community on the efficacy of these widely available interventions improve cognitive functioning in older adults.

BackgroundThe ultimate goal of artificial intelligence (AI) is to develop technologies that are best able to serve humanity. This will require advancements that go beyond the basic components of general intelligence. The term "intelligence" does not best represent the technological needs of advancing society, because it is "wisdom", rather than intelligence, that is associated with greater well-being, happiness, health, and perhaps even longevity of the individual and the society. Thus, the future need in technology is for artificial wisdom (AW).MethodsWe examine the constructs of human intelligence and human wisdom in terms of their basic components, neurobiology, and relationship to aging, based on published empirical literature. We review the development of AI as inspired and driven by the model of human intelligence, and consider possible governing principles for AW that would enable humans to develop computers which can operationally utilize wise principles and result in wise acts. We review relevant examples of current efforts to develop such wise technologies.ResultsAW systems will be based on developmental models of the neurobiology of human wisdom. These AW systems need to be able to a) learn from experience and self-correct; b) exhibit compassionate, unbiased, and ethical behaviors; and c) discern human emotions and help the human users to regulate their emotions and make wise decisions.ConclusionsA close collaboration among computer scientists, neuroscientists, mental health experts, and ethicists is necessary for developing AW technologies, which will emulate the qualities of wise humans and thus serve the greatest benefit to humanity. Just as human intelligence and AI have helped further the understanding and usefulness of each other, human wisdom and AW can aid in promoting each other's growth.

ObjectivesIndividuals with serious mental illnesses such as bipolar disorder (BD) are at an increased risk for poor medication adherence compared to the general population. Individuals with BD also have high rates of chronic comorbid medical conditions like hypertension (HTN), diabetes, and cardiovascular disease. Cognitive-behavioral therapies often integrate strategies to improve medication adherence by targeting medication attitudes and self-efficacy, but the pathway toward behavior change needs further investigation.MethodsThis 3-month prospective, single-arm cohort study tested an automated SMS intervention entitled Individualized Texting for Adherence Building- Cardiovascular (iTAB-CV) in 38 participants with BD and HTN. The Tablets Routine Questionnaire (TRQ) measures the percentage of BD and HTN non-adherence over the past week and the past month. Attitudinal and habit measures including the Brief Illness Perception Questionnaire (Brief IPQ), the Medication Adherence Self-Efficacy Scale-Revised (MASES-R), the Self-Report Habit Index (SRHI), the Beliefs about Medicines Questionnaire (BMQ), and the Attitudes toward Mood Stabilizers Questionnaire (AMSQ) were given for BD and HTN medications. Correlational analyses were run to determine the associations between BD and HTN attitudinal and habit indices. Additionally, longitudinal analyses were conducted to determine if attitudes changed over time as a function of a 2-month mobile-health intervention.ResultsIllness attitudes towards BD were worse than towards HTN at the start of the study. Attitudes toward BD and towards mood-stabilizing drugs as well as antihypertensives improved following a mHealth intervention aimed at improving adherence. Furthermore, self-efficacy and habit strength for both BD and HTN drugs were correlated and were responsive to the intervention, with most of the change occurring after the first month of the intervention and not requiring the addition of the explicit reminders.ConclusionParticipants who received iTAB-CV showed improved attitudes towards BD and mood-stabilizing medication, and had an improvement in self-efficacy and habit strength towards taking both BD and HTN medications. Increased attention to mechanisms of change in mHealth interventions for adherence may facilitate impact. It should be noted that the methodology of the study limits drawing causal conclusions and suggests the need for a randomized control trial.

PURPOSE OF REVIEW:Artificial intelligence (AI) technology holds both great promise to transform mental healthcare and potential pitfalls. This article provides an overview of AI and current applications in healthcare, a review of recent original research on AI specific to mental health, and a discussion of how AI can supplement clinical practice while considering its current limitations, areas needing additional research, and ethical implications regarding AI technology. RECENT FINDINGS:We reviewed 28 studies of AI and mental health that used electronic health records (EHRs), mood rating scales, brain imaging data, novel monitoring systems (e.g., smartphone, video), and social media platforms to predict, classify, or subgroup mental health illnesses including depression, schizophrenia or other psychiatric illnesses, and suicide ideation and attempts. Collectively, these studies revealed high accuracies and provided excellent examples of AI's potential in mental healthcare, but most should be considered early proof-of-concept works demonstrating the potential of using machine learning (ML) algorithms to address mental health questions, and which types of algorithms yield the best performance. As AI techniques continue to be refined and improved, it will be possible to help mental health practitioners re-define mental illnesses more objectively than currently done in the DSM-5, identify these illnesses at an earlier or prodromal stage when interventions may be more effective, and personalize treatments based on an individual's unique characteristics. However, caution is necessary in order to avoid over-interpreting preliminary results, and more work is required to bridge the gap between AI in mental health research and clinical care.

ObjectiveTo investigate the feasibility, safety, and utility of tablet devices as novel nonpharmacologic tools in managing older psychiatric inpatients with agitation and dementia.MethodsThirty-six patients at a geriatric psychiatry inpatient unit were provided with tablets when agitated and used various apps on the tablet related to communication, games, music, web browser, and photography during their stay. Study staff documented the frequency, duration, and app usage history and rated the extent to which agitation improved after tablet use.ResultsAll participants, regardless of dementia severity, were able to use apps and were rated by staff to have clinical benefit. Dementia severity was negatively associated with app complexity. Age was negatively associated with frequency and duration of tablet use.ConclusionTablet use as a nonpharmacologic intervention for agitation in older adults, including those with severe dementia, appears to be feasible, safe, and of potential utility.

ObjectiveThis study aimed to examine the feasibility, acceptability, and initial validity of using smartphone-based ecological momentary assessment (EMA) to assess daily functioning and other behavioral factors among older HIV+ adults.MethodsTwenty older HIV+ adults (mean age: 59 years) completed laboratory-based neurobehavioral and functional assessments then completed EMA surveys via smartphones five times per day for one week.ResultsExcellent EMA adherence (86.4%) was found, and participants rated their experience with EMA methods positively. Time-use data indicated participants were spending 74% of their waking-sampled time at home, 63% of their time alone, and 32% of their time engaged in passive leisure activities (e.g., watching TV). Better neurocognitive and functional capacity abilities were correlated with less time spent in passive leisure activities. Lastly, mood and cognitive symptom data collected via EMA were significantly associated with scores from laboratory-based assessments of these same constructs.ConclusionsEMA via smartphones is a feasible and acceptable data collection method among older HIV+ adults and appears to be a promising mobile tool to assess daily functioning behaviors in HIV. These preliminary findings indicate older HIV+ adults are spending a considerable amount of time at home, alone, and engaged in passive leisure activities, primarily watching TV. EMA may contribute to future research examining functional disability among the growing population of older HIV+ adults.

IntroductionBipolar disorder is a severe and chronic mental health problem that persists into older adulthood. The number of people living with this condition is set to rise as the UK experiences a rapid ageing of its population. To date, there has been very little research or service development with respect to psychological therapies for this group of people.Methods and analysisA parallel two-arm randomised controlled trial comparing a 14-session, 6-month Recovery-focused Cognitive-Behavioural Therapy for Older Adults with bipolar disorder (RfCBT-OA) plus treatment as usual (TAU) versus TAU alone. Participants will be recruited in the North-West of England via primary and secondary mental health services and through self-referral. The primary objective of the study is to evaluate the feasibility and acceptability of RfCBT-OA; therefore, a formal power calculation is not appropriate. It has been estimated that randomising 25 participants per group will be sufficient to be able to reliably determine the primary feasibility outcomes (eg, recruitment and retention rates), in line with recommendations for sample sizes for feasibility/pilot trials. Participants in both arms will complete assessments at baseline and then every 3 months, over the 12-month follow-up period. We will gain an estimate of the likely effect size of RfCBT-OA on a range of clinical outcomes and estimate parameters needed to determine the appropriate sample size for a definitive, larger trial to evaluate the effectiveness and cost-effectiveness of RfCBT-OA. Data analysis is discussed further in the Analysis section in the main paper.Ethics and disseminationThis protocol was approved by the UK National Health Service (NHS) Ethics Committee process (REC ref: 15/NW/0330). The findings of the trial will be disseminated through peer-reviewed journals, national and international conference presentations and local, participating NHS trusts.Trial registration numberISRCTN13875321; Pre-results.

© 2015 Elsevier B.V. Schizophrenia is characterized by physical (mainly metabolic and cardiovascular) comorbidity and shortened lifespan. High sensitivity C-reactive protein (hs-CRP), an inflammatory marker of hepatic origin linked to metabolic and cardiovascular diseases and mortality in the general population, has been reported to be elevated in people with schizophrenia. However, the relationship of hs-CRP to psychiatric and medical risk factors, after controlling for potentially confounding variables such as smoking, is not well established in schizophrenia. We assessed hs-CRP levels along with various demographic, psychiatric, and metabolic measures in 88 clinically stable outpatients with schizophrenia or schizoaffective disorder and 71 age epoch-matched comparison subjects with no history of a major psychiatric illness. hs-CRP levels were significantly higher in individuals with schizophrenia than in comparison subjects. Higher hs-CRP levels in the schizophrenia group were associated with female gender, more severe negative symptoms, greater medical comorbidity, and worse metabolic risk factors including BMI, fasting glucose, and hemoglobin A1c levels. hs-CRP was not related to age, race, education, smoking status, antipsychotic dosage, or cognitive impairment. Longitudinal studies are needed to investigate the relationship between hs-CRP and long-term health outcomes including metabolic syndrome, cardiovascular disease, and mortality in schizophrenia.

BackgroundSexual health and function is an important yet understudied aspect of overall health and well-being in older adults. There are limited data on the relative strength of associations between various aspects of sexual health with the physical, emotional, and cognitive function in older adults. Additionally, there is little information on how these associations differ by age and sex.MethodsIn this Successful Aging Evaluation (SAGE) study, 606 community-dwelling adults in San Diego County, aged 50-99 years and who had a partner, were included in the analysis. Evaluations included a phone-based cognitive screening followed by a comprehensive mail-in survey including rating scales of sexual health, depression, anxiety, and physical function.ResultsThe mean age of the sample was 75.2 years. Over 80% of respondents had engaged in sexual activity in the past year, over 70% engaged in sexual activity weekly or more than once a week, and over 60% were somewhat or very satisfied with their sex lives. No sex differences were evident on dimensions of sexual health except for a higher rate of rejection of sexual overtures by women. Depressive symptoms were negatively associated with all assessed aspects of sexual health, even after adjusting for age, physical functioning, anxiety, cognitive ability, or perceived stress in both men and women.ConclusionsIn this population-based study older men and women who had a partner reported frequent engagement in and satisfaction with sexual activity. Depressive symptoms were broadly associated with worse sexual health, more so than physical function, anxiety or stress, or age itself.

PurposeWith a growing need for developing future physician scientists, identifying characteristics of medical students who are likely to benefit from research training programs is important. This study assessed if specific learning styles of medical students, participating in federally funded short-term research training programs, were associated with research self-efficacy, a potential predictor of research career success.MethodSeventy-five first-year medical students from 28 medical schools, selected to participate in two competitive NIH-supported summer programs for research training in aging, completed rating scales to evaluate learning styles at baseline, and research self-efficacy before and after training. We examined associations of individual learning styles (visual-verbal, sequential-global, sensing-intuitive, and active-reflective) with students' gender, ranking of medical school, and research self-efficacy.ResultsResearch self-efficacy improved significantly following the training programs. Students with a verbal learning style reported significantly greater research self-efficacy at baseline, while visual, sequential, and intuitive learners demonstrated significantly greater increases in research self-efficacy from baseline to posttraining. No significant relationships were found between learning styles and students' gender or ranking of their medical school.ConclusionsAssessments of learning styles may provide useful information to guide future training endeavors aimed at developing the next generation of physician-scientists.

Population aging is an enormous public health issue and there is clear need for strategies to maximize opportunities for successful aging. Many psychiatric illnesses are increasingly thought to be associated with accelerated aging, therefore emerging data on individual and policy level interventions that alter typical aging trajectories are relevant to mental health practitioners. Although the determinants and definition of successful aging remain controversial, increasing data indicate that psychiatric illnesses directly impact biological aging trajectories and diminish lifestyle, psychological, and socio-environmental factors that seem to reduce risk of morbidity and mortality. Many interventions designed to enhance the normal course of aging may be adjunctive approaches to management of psychiatric illnesses. We highlight recent data on interventions seeking to promote healthy aging, such as cognitive remediation, physical activity, nutrition, and complementary and alternative treatments for older people with and without psychiatric illnesses.

Mobile health (mHealth) interventions to promote antiretroviral therapy (ART) adherence have shown promise; however, among persons living with HIV who abuse methamphetamine (MA), effective tailoring of content to match the expressed needs of this patient population may be necessary. This study aimed (1) to understand patient perspectives of barriers and facilitators of ART adherence among people with HIV who use MA, and (2) to obtain feedback on the thematic content of an mHealth intervention in order to tailor the intervention to this subgroup. Two separate focus groups, each with 10 HIV+/MA+ individuals, were conducted. Transcribed audio recordings were qualitatively analyzed to identify emergent themes. Inter-rater reliability of themes was high (mean Kappa = .97). Adherence barriers included MA use, misguided beliefs about ART adherence, memory and planning difficulties, social barriers and perceived stigma, and mental heath issues. Facilitators of effective ART adherence were cognitive compensatory strategies, promotion of well-being, health-care supports, adherence education, and social support. Additionally, the focus groups generated content for reminder text messages to be used in the medication adherence intervention. This qualitative study demonstrates the feasibility of using focus groups to derive patient-centered intervention content to address the health challenge at hand in targeted populations.

Recognition and timely action around “warning signs” of illness exacerbation is central to the self-management of bipolar disorder. Due to its heterogeneity and fluctuating course, passive and active mobile technologies have been increasingly evaluated as adjunctive or standalone tools to predict and prevent risk of worsening of course in bipolar disorder. As predictive analytics approaches to big data from mobile health (mHealth) applications and ancillary sensors advance, it is likely that early warning systems will increasingly become available to patients. Such systems could reduce the amount of time spent experiencing symptoms and diminish the immense disability experienced by people with bipolar disorder. However, in addition to the challenges in validating such systems, we argue that early warning systems may not be without harms. Probabilistic warnings may be delivered to individuals who may not be able to interpret the warning, have limited information about what behaviors to change, or are unprepared to or cannot feasibly act due to time or logistic constraints. We propose five essential elements for early warning systems and provide a conceptual framework for designing, incorporating stakeholder input, and validating early warning systems for bipolar disorder with a focus on pragmatic considerations.