Psychiatry Apps

Esketamine, the s(+) enantiomer of ketamine, was approved in 2019 as the first rapid-acting intranasal spray medication for treatment-resistant depression; the drug is given in combination with an antidepressant. The treatment is self-administered in a clinical setting under the supervision of a healthcare provider and usually is well tolerated. Many of its adverse reactions are mild, temporary, and dose-dependent, and they improve with subsequent treatments. Although the prescribing information lists difficulty remembering or thinking as possible adverse reactions, a neurocognitive evaluation is not part of the initial patient evaluation. This case report focuses on a patient whose neurocognitive symptoms worsened with esketamine treatment, necessitating treatment discontinuation.

No randomised controlled trials have evaluated whether the addition of a smartphone app to usual child and adolescent mental health care (CAMHS) can reduce self-harm in adolescents (<18 years) with repeated self-harm. We enrolled 170 participants aged 12-17, receiving CAMHS treatment who had self-harmed ≥2 in the past 12 months. Participants were randomised via an independent web-based system (1:1, minimised for gender, age, self-harm frequency, and depression severity) to treatment as usual (TAU) or treatment as usual plus BlueIce (TAU+BI). BlueIce is a self-harm prevention app that includes techniques from CBT and DBT that was co-designed with adolescents who self-harm. The primary outcome was change from baseline to 12-weeks on the self-harm scale of the Risk Taking and Self-Harm Inventory for Adolescents (RTSHIA), analysed by intention to treat (ITT). Emergency department attendances or admissions for self-harm were assessed over 6-months via a review of clinical records. Both groups improved but there were no statistically significant between group differences at 12 weeks or 6 months on the self-harm scale of the RTSHIA. There were fewer emergency department attendances and admissions in those who received the app, a finding that approached statistical significance. BlueIce can be helpful in some important aspects by contributing to fewer emergency department admissions and attendances. TRIAL REGISTRATION: Trial registration number ISRCTN10541045.

Schizophrenia affects 24 million people worldwide. Digital health interventions drawing on psychological principles have been developed, but their effectiveness remains unclear. This parallel, assessor-blinded, randomized clinical trial aimed to investigate whether a cognitive behaviour therapy-informed digital health intervention (Actissist app) confers added benefit on psychotic symptoms over and above remote symptom monitoring (ClinTouch app). Participants recruited from UK community health services were randomized 1:1 to receive either Actissist plus treatment as usual (TAU) or ClinTouch plus TAU. Eligible participants were adults with schizophrenia-spectrum psychosis within five years of first episode onset meeting a criterion level of positive symptoms severity. The primary outcome was Positive and Negative Syndrome Scale (PANSS) symptoms total score at 12 weeks post-randomization. Intention-to-treat analysis included 172 participants, with 149 participants (86.6 %) providing primary outcome data. Actissist plus TAU was not associated with greater reduction than an active control remote symptom monitoring app (ClinTouch) in PANSS total score at post-randomization. There were no significant effects between groups across secondary measures. There were no serious adverse reactions. Both groups improved on the primary psychotic symptoms measure at primary end-point and on secondary measures over time. The Actissist app is safe but not superior to digital symptom monitoring.

The emergence of long COVID as a COVID-19 sequela was largely syndromic in characterisation. Digital health technologies such as wearable devices open the possibility to study this condition with passive, objective data in addition to self-reported symptoms. We aimed to quantify the prevalence and severity of symptoms across collected mobile health metrics over 12 weeks following COVID-19 diagnosis and to identify risk factors for the development of post-COVID-19 condition (also known as long COVID).

Youth screen media activity is a growing concern, though few studies include objective usage data. Through the longitudinal, U.S.-based Adolescent Brain Cognitive Development (ABCD) Study, youth (m = 14; n = 1415) self-reported their typical smartphone use and passively recorded three weeks of smartphone use via the ABCD-specific Effortless Assessment Research System (EARS) application. Here we describe and validate passively-sensed smartphone keyboard and app use measures, provide code to harmonize measures across operating systems, and describe trends in adolescent smartphone use. Keyboard and app-use measures were reliable and positively correlated with one another (r = 0.33) and with self-reported use (rs = 0.21-0.35). Participants recorded a mean of 5 h of daily smartphone use, which is two more hours than they self-reported. Further, females logged more smartphone use than males. Smartphone use was recorded at all hours, peaking on average from 8 to 10 PM and lowest from 3 to 5 AM. Social media and texting apps comprised nearly half of all use. Data are openly available to approved investigators ( https://nda.nih.gov/abcd/ ). Information herein can inform use of the ABCD dataset to longitudinally study health and neurodevelopmental correlates of adolescent smartphone use.

Individuals with intellectual disabilities often fail to learn complex tasks. Modified Goal Management Training (mGMT) or Errorless Learning combined with assistive technology (App + EL) can help. The goal is to demonstrate the effectiveness of mGMT and/or App + EL in learning complex tasks. We employed a randomized controlled crossover design. One group started with mGMT ( = 16), and the other with App + EL (N = 15). We compared their performance with that of a passive control group (N = 15). The training consisted of six sessions of 30 minutes each. Success was analyzed using the Goal Attainment Scale (GAS). Three different tasks were assessed before and after each intervention period: "Practiced", "Non-Practiced", or "Previously Practiced". Generalization was evaluated through neuropsychological tests. Results indicated that both interventions significantly improved "Practiced" tasks compared with "Non-Practiced" tasks and the control group. Crossing the intervention did not interfere with the stable performance on the "Previously Practiced" task. However, starting with mGMT reduced, but did not eliminate, the efficacy of App + EL after crossing, but this pattern was not observed for the reverse sequence. Only the Tower of London task documented improvements related to interventions. In conclusion, the mGMT and App + EL were effective in learning complex tasks and retaining performance after learning a second task. German Clinical Trials Register identifier: DRKS00021674.

We elucidated the molecular fingerprint of vulnerable excitatory neurons within select cortical lamina of individuals with Down syndrome (DS) for mechanistic understanding and therapeutic potential that also informs Alzheimer's disease (AD) pathophysiology. Frontal cortex (BA9) layer III (L3) and layer V (L5) pyramidal neurons were microisolated from postmortem human DS and age- and sex-matched controls (CTR) to interrogate differentially expressed genes (DEGs) and key biological pathways relevant to neurodegenerative programs. We identified > 2300 DEGs exhibiting convergent dysregulation of gene expression in both L3 and L5 pyramidal neurons in individuals with DS versus CTR subjects. DEGs included over 100 triplicated human chromosome 21 genes in L3 and L5 neurons, demonstrating a trisomic neuronal karyotype in both laminae. In addition, thousands of other DEGs were identified, indicating gene dysregulation is not limited to trisomic genes in the aged DS brain, which we postulate is relevant to AD pathobiology. Convergent L3 and L5 DEGs highlighted pertinent biological pathways and identified key pathway-associated targets likely underlying corticocortical neurodegeneration and related cognitive decline in individuals with DS. Select key DEGs were interrogated as potential hub genes driving dysregulation, namely the triplicated DEGs amyloid precursor protein (APP) and superoxide dismutase 1 (SOD1), along with key signaling DEGs including mitogen activated protein kinase 1 and 3 (MAPK1, MAPK3) and calcium calmodulin dependent protein kinase II alpha (CAMK2A), among others. Hub DEGs determined from multiple pathway analyses identified potential therapeutic candidates for amelioration of cortical neuron dysfunction and cognitive decline in DS with translational relevance to AD.

A key component of stress management and biofeedback training is the use of relaxation exercises, such as slow/deep breathing (6 breaths/minute) in heart coherence exercises (HCEs). Breathing exercises are also increasingly being integrated into smartphones as part of health apps, though their effectiveness in adolescents after acute stress has rarely been validated scientifically. The aim of the current study was to investigate the effectiveness of an app-guided HCE (n = 36) after an acute stress situation (Trier Social Stress Test) compared with natural relaxation (n = 37), among healthy adolescents (aged 11-17 years). Endocrine, autonomic, and psychological stress parameters (cortisol, alpha-amylase, heart rate, heart rate variability, mood) were examined in 73 adolescents (46 female, 27 male; M = 13.86, SD = 1.87). Significant group differences were found in heart rate variability, with higher values in the low frequency band and low-to-high frequency ratio for the HCE condition, possibly indicating improved physiological functions through the stimulation of vagal tone and baroreflex. The use of a general breathing technique (natural and app-guided) also resulted in stronger relaxation reactions in cortisol when controlling for the previous stronger stress reactivity. On the other hand, app-guided slow breathing without a long training may be experienced as more uncomfortable during relaxation. The integration of breathing exercises in health apps for adolescents appears to be useful, offering a helpful and low-threshold coping/relaxation strategy during acute stress situations. Further studies should examine the benefits of app-guided breathing exercises in both psychiatric samples and the general population across a wide age range.

The Hierarchical Taxonomy of Psychopathology (HiTOP) arranges phenotypes of mental disorders based on empirical covariation, ranging from narrowly defined symptoms to higher-order spectra of psychopathology. Since the introduction of personality functioning (PF) in DSM-5 and ICD-11, several studies have identified PF as a predictor of transdiagnostic aspects of psychopathology. However, the role of PF in the HiTOP classification system has not been systematically examined. This study investigates how PF can be integrated into HiTOP, whether PF accounts for transdiagnostic variance captured in higher-order spectra, and how its predictive value for future affective well-being (AWB) and psychosocial impairment (PSI) compares to the predictive value of specific psychopathology beyond PF. To this end, we examined two years of ambulatory assessed data on psychopathology, PF, PSI, and AWB of N = 27,173 users of a mental health app. Results of bass-ackwards analyses largely aligned with the current HiTOP working model. Using bifactor modeling, aspects of PF were identified to capture most of the internalizing, thought disorder, and externalizing higher-order factor variance. In longitudinal prediction analyses employing bifactor-(S-1) modeling, PF explained 58.6% and 30.6% of variance in PSI and AWB when assessed across one year, respectively, and 33.1% and 23.2% of variance when assessed across two years. Results indicate that personality functioning may largely account for transdiagnostic variance captured in the higher-order components in HiTOP as well as longitudinal outcomes of PSI and AWB. Clinicians and their patients may benefit from assessing PF aspects such as identity problems or internal relationship models in a broad range of mental disorders. Further, incorporating measures of PF may advance research in biological psychiatry by providing empirically sound phenotypes.

Major depressive disorder (MDD) is common worldwide and can be highly disabling. People with MDD face many barriers to treatment and may not experience full symptom relief even when treated. Therefore, new treatment modalities are needed for MDD. Digital therapeutics (DTx) may provide people with MDD an additional treatment option.

 The overall goal of this work is to create a patient-reported outcome (PRO) and decision support system to help postpartum patients determine when to seek care for concerning symptoms. In this case study, we assessed differences in perspectives for application design needs based on race, ethnicity, and preferred language.

There is high comorbidity of opioid use disorder (OUD) and chronic pain (CP), which is often addressed by prescribing buprenorphine (BUP). While BUP is effective in preventing overdose, it does not address the psychological aspects of OUD and CP comorbidity and treatment retention rates are as low as 50%. The Virtual Opioid use disorder Integrated Chronic Pain Treatment (VOICE) study (NCT05039554) is a novel effectiveness-implementation trial to test a 12-week virtual group Acceptance and Commitment Therapy (ACT) protocol and a care management smartphone application (app; Valera Health) on pain and opioid use in patients with OUD and CP receiving BUP. Using a 2 × 2 factorial design, participants (expected N = 280) are randomized into: ACT, Valera app, ACT + Valera, or Treatment as Usual arm. This study is taking place in the Bronx, NY, a racially/ethnically diverse community that faces numerous socioeconomic stressors and is one of the nation's epicenters of the opioid epidemic. We created a culturally responsive ACT group protocol, and Valera psychoeducational material. Outcome measures include NIH HEAL Common Data Elements and ACT and Valera-specific measures. We are conducting a novel 2 × 2 trial investigating augmenting BUP treatment with ACT and Valera, with the goal that improved mental health and access to care will result in decreased and opioid use and pain interference.

Measurement-based care (MBC) comprises collecting patient-reported outcomes data using validated assessments and using that information to support treatment. The Veterans Health Administration (VHA) has developed technology platforms to support MBC, including the Mental Health Checkup (MHC) mobile health application (app). Our objective was to examine VHA mental health provider perspectives on the MHC app. We completed a mixed-methods, sequential explanatory evaluation of MHC. We surveyed 284 VHA mental health providers who used MHC, then conducted semistructured telephone interviews with a purposefully selected subset of survey respondents ( = 20). Approximately half of survey respondents agreed that MHC allowed them to collect assessment data from veterans more frequently than before (51%) and that they more frequently discussed assessment results with veterans because of MHC (50%) and used those results to inform goal-setting discussions (50%) and treatment decision making (51%). Bivariate analyses indicated a positive relationship between frequency of MHC use and the aforementioned impacts on care. Interview data conveyed both advantages (e.g., increased treatment efficiency, improved treatment decision making) and challenges (e.g., limited assessment availability, difficulties engaging veterans in completing assessments through the app) to using MHC. This evaluation demonstrated how MHC supported providers working to implement MBC. The app enhanced their ability to reach and engage veterans and incorporate assessment data into clinical encounters. Still, many did not perceive that MHC was impactful on mental health care delivery; given that providers who used MHC more frequently reported more positive impressions of MHC, this may be related to how frequently they used the app. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

With a renewed focus on health equity in the United States driven by national crises and legislation to improve digital healthcare innovation, there is a need for the designers of digital health tools to take deliberate steps to design for equity in their work. A concrete toolkit of methods to design for health equity is needed to support digital health practitioners in this aim. This narrative review summarizes several health equity frameworks to help digital health practitioners conceptualize the equity dimensions of importance for their work, and then provides design approaches that accommodate an equity focus. Specifically, the Double Diamond Model, the IDEAS framework and toolkit, and community collaboration techniques such as participatory design are explored as mechanisms for practitioners to solicit input from members of underserved groups and better design digital health tools that serve their needs. Each of these design methods requires a deliberate effort by practitioners to infuse health equity into the approach. A series of case studies that use different methods to build in equity considerations are offered to provide examples of how this can be accomplished and demonstrate the range of applications available depending on resources, budget, product maturity, and other factors. We conclude with a call for shared rigor around designing digital health tools that deliver equitable outcomes for members of underserved populations.

A Disintegrin and Metalloproteinase 10 (ADAM10) is a crucial transmembrane protein involved in diverse cellular processes, including cell adhesion, migration, and proteolysis. ADAM10's ability to cleave over 100 substrates underscores its significance in physiological and pathological contexts, particularly in Alzheimer's disease (AD). This review comprehensively examines ADAM10's multifaceted roles, highlighting its critical function in the non-amyloidogenic processing of the amyloid precursor protein (APP), which mitigates amyloid beta (Aβ) production, a critical factor in AD development. We summarize the regulation of ADAM10 at multiple levels: transcriptional, translational, and post-translational, revealing the complexity and responsiveness of its expression to various cellular signals. A standardized nomenclature for ADAM10 isoforms is proposed to improve clarity and consistency in research, facilitating better comparison and replication of findings across studies. We address the challenges in detecting ADAM10 isoforms using antibodies, advocating for standardized detection protocols to resolve discrepancies in results from different biological matrices. This review underscores the potential of ADAM10 as a biomarker for early diagnosis and a therapeutic target in AD. By consolidating current knowledge on ADAM10's regulation and function, we aim to provide insights that will guide future research and therapeutic strategies in the AD context.

Antipsychotic polypharmacy (APP) is frequently prescribed for schizophrenia-spectrum disorders. Despite the inconsistent findings on efficacy, APP may be beneficial for subgroups of psychotic patients. This meta-analysis of individual patient data investigated moderators of efficacy and tolerability of APP in adult patients with schizophrenia-spectrum disorders.

Tinnitus, the perception of sound without an external source, affects 15% of the population, with 2.4% experiencing significant distress. In this review, we summarize the current state of knowledge about tinnitus management with a particular focus on the translation into clinical practice. In the first section, we analyze shortcomings, knowledge gaps, and challenges in the field of tinnitus research. Then, we highlight the relevance of the diagnostic process to account for tinnitus heterogeneity and to identify all relevant aspects of the tinnitus in an individual patient, such as etiological aspects, pathophysiological mechanisms, factors that contribute most to suffering, and comorbidities. In the next section, we review available treatment options, including counselling, cognitive-behavioral therapy (CBT), hearing aids and cochlear implants for patients with a relevant hearing loss, sound generators, novel auditory stimulation approaches, tinnitus retraining therapy (TRT), pharmacological treatment, neurofeedback, brain stimulation, bimodal stimulation, Internet- and app-based digital approaches, and alternative treatment approaches. The evidence for the effectiveness of the various treatment interventions varies considerably. We also discuss differences in current respective guideline recommendations and close with a discussion of how current pathophysiological knowledge, latest scientific evidence, and patient perspectives can be translated in patient-centered care.

Anxiety disorders are prevalent and undertreated among young adults. Digital mental health interventions for anxiety are promising but limited by a narrow range of therapeutic components and low user engagement.

A third of adults in Western countries have impaired sleep quality. A possible solution involves distributing sleep aids through smartphone apps, but most empirical studies are limited to small pilot trials in distinct populations (eg, soldiers) or individuals with clinical sleep disorders; therefore, general population data are required. Furthermore, recent research shows that sleep app users desire a personalized approach, offering an individually tailored choice of techniques. One such aid is Peak Sleep, a smartphone app based on scientifically validated principles for improving sleep quality, such as mindfulness meditation and cognitive behavioral therapy.

Rotating shiftwork schedules are known to disrupt sleep in a manner that can negatively impact safety. Consumer sleep technologies (CSTs) may be a useful tool for sleep tracking, but the standard feedback provided by CSTs may not be salient to shift-working populations. SleepTank is an app that uses the total sleep time data scored by a CST to compute a percentage that equates hours of sleep to the fuel in a car and warns the user to sleep when the "tank" is low. Royal Australian Navy aircraft maintenance workers operating on a novel rotational shift schedule were given Fitbit Versa 2s to assess sleep timing, duration, and efficiency across a 10-week period. Half of the participants had access to just the Fitbit app while the other half had access to Fitbit and the SleepTank app. The goal of this study was to evaluate differences in sleep behavior between shifts using an off-the-shelf CST and to investigate the potential of the SleepTank app to increase sleep duration during the 10-week rotational shift work schedule.

To address the need for interactive visualization tools and databases in characterizing multimorbidity patterns across different populations, we developed the Phenome-wide Multi-Institutional Multimorbidity Explorer (PheMIME). This tool leverages three large-scale EHR systems to facilitate efficient analysis and visualization of disease multimorbidity, aiming to reveal both robust and novel disease associations that are consistent across different systems and to provide insight for enhancing personalized healthcare strategies.

Sexual and reproductive health is critical for the readiness of the warfighter, as costs of sexually transmitted infections and unintended pregnancy result in added health care costs, lost mission time, and impact on morale. The Multiphase Optimization Strategy (MOST) is an engineering-inspired framework used to optimize biobehavioral interventions. The Military Active-Duty Reproductive and Sexual Health (MARSH) research team applied the MOST framework to develop "Mission Wellness"-an electronic health intervention to promote sexual and reproductive health within the U.S. Military.

As digital phenotyping, the capture of active and passive data from consumer devices such as smartphones, becomes more common, the need to properly process the data and derive replicable features from it has become paramount. Cortex is an open-source data processing pipeline for digital phenotyping data, optimized for use with the mindLAMP apps, which is used by nearly 100 research teams across the world. Cortex is designed to help teams (1) assess digital phenotyping data quality in real time, (2) derive replicable clinical features from the data, and (3) enable easy-to-share data visualizations. Cortex offers many options to work with digital phenotyping data, although some common approaches are likely of value to all teams using it. This paper highlights the reasoning, code, and example steps necessary to fully work with digital phenotyping data in a streamlined manner. Covering how to work with the data, assess its quality, derive features, and visualize findings, this paper is designed to offer the reader the knowledge and skills to apply toward analyzing any digital phenotyping data set. More specifically, the paper will teach the reader the ins and outs of the Cortex Python package. This includes background information on its interaction with the mindLAMP platform, some basic commands to learn what data can be pulled and how, and more advanced use of the package mixed with basic Python with the goal of creating a correlation matrix. After the tutorial, different use cases of Cortex are discussed, along with limitations. Toward highlighting clinical applications, this paper also provides 3 easy ways to implement examples of Cortex use in real-world settings. By understanding how to work with digital phenotyping data and providing ready-to-deploy code with Cortex, the paper aims to show how the new field of digital phenotyping can be both accessible to all and rigorous in methodology.

Emerging adult (EA) cannabis use is associated with increased risk for health consequences. Just-in-time adaptive interventions (JITAIs) provide potential for preventing the escalation and consequences of cannabis use. Powered by mobile devices, JITAIs use decision rules that take the person's state and context as input, and output a recommended intervention (e.g., alternative activities, coping strategies). The mHealth literature on JITAIs is nascent, with additional research needed to identify what intervention content to deliver when and to whom.

Perinatal depression affects a significant number of women during pregnancy and after birth, and early identification is imperative for timely interventions and improved prognosis. Mobile apps offer the potential to overcome barriers to health care provision and facilitate clinical research. However, little is known about users' perceptions and acceptability of these apps, particularly digital phenotyping and ecological momentary assessment apps, a relatively novel category of apps and approach to data collection. Understanding user's concerns and the challenges they experience using the app will facilitate adoption and continued engagement.

Mental health in adolescence is critical in its own right and a predictor of later symptoms of anxiety and depression. To address these mental health challenges, it is crucial to understand the variables linked to anxiety and depression in adolescence.

Amyloid-β (Aβ) is thought to be neuronally derived in Alzheimer's disease (AD). However, transcripts of amyloid precursor protein (APP) and amyloidogenic enzymes are equally abundant in oligodendrocytes (OLs). By cell-type-specific deletion of Bace1 in a humanized knock-in AD model, APP, we demonstrate that OLs and neurons contribute to Aβ plaque burden. For rapid plaque seeding, excitatory projection neurons must provide a threshold level of Aβ. Ultimately, our findings are relevant for AD prevention and therapeutic strategies.

Our prototype system designed for clinical data acquisition and recording of studies is a novel electronic data capture (EDC) software for simple and lightweight data capture in clinical research. Existing software tools are either costly or suffer from very limited features. To overcome these shortcomings, we designed an EDC software together with a mobile client. We aimed at making it easy to set-up, modifiable, scalable and thereby facilitating research. We wrote the software in R using a modular approach and implemented existing data standards along with a meta data driven interface and database structure. The prototype is an adaptable open-source software, which can be installed locally or in the cloud without advanced IT-knowledge. A mobile web interface and progressive web app for mobile use and desktop computers is added. We show the software's capability, by demonstrating four clinical studies with over 1600 participants and 679 variables per participant. We delineate a simple deployment approach for a server-installation and indicate further use-cases. The software is available under the MIT open-source license. Conclusively the software is versatile, easily deployable, highly modifiable, and extremely scalable for clinical studies. As an open-source R-software it is accessible, open to community-driven development and improvement in the future.

Public safety personnel (PSP) such as firefighters, paramedics, and police are exposed to traumatic situations, which increase their risk for mental health issues. However, many PSP do not seek help in a timely manner. Peer support interventions have the potential to decrease stigma and increase treatment-seeking behaviours among PSP. However, little is known regarding how the organizational culture of public safety organizations (PSOs) affects the implementation of a peer-based intervention. This study aims to understand the extent to which organizational culture, including masculinity contest cultures (MCC), within Canadian PSOs could affect implementation of PeerOnCall, a new peer support app for PSP.

Voice features could be a sensitive marker of affective state in bipolar disorder (BD). Smartphone apps offer an excellent opportunity to collect voice data in the natural setting and become a useful tool in phase prediction in BD.

PositiveLinks (PL) is a mHealth platform to support care engagement by people with HIV (PWH). Daily reminders prompt the user to report medication adherence, mood, and daily stress. Higher response rate to PL check-ins has been associated with better suppression of viral load over 6-18 months. We conducted a retrospective chart review for a three-year period collecting demographic information, average mood and stress scores, and all viral loads obtained in usual patient care. We performed multivariable logistic regression modeling to identify factors associated with loss of viral load suppression and a time-to-event survival analysis until first unsuppressed viral load stratified by PL usage. Of the 513 PWH included, 103 had at least one episode of viral non-suppression. Low users of PL were more likely to have an unsuppressed viral load with an adjusted Odds Ratio (aOR) of 5.8 (95% CI 3.0-11.5, p < 0.001). Protective factors included older age (aOR 0.96; 95% CI 0.93-0.98, p = 0.003) and income above the federal poverty level (FPL) (aOR 0.996; 95% CI 0.995-0.998, p < 0.001). High PL use was also associated with better viral load suppression (VLS) over time (p < 0.0001 ((aHR) of 0.437 (95% CI 0.290-0.658, p < 0.001)) after adjusting for age and FPL. High stress scores were related to subsequent loss of viral suppression in an exploratory analysis. High check-in response rate on the PL app, older age, and higher income are associated with sustained VLS over time. Conversely, lack of response to check-ins or increased reported stress may signal a need for additional support.

Specific moments of lapse among smokers attempting to quit often lead to full relapse, which highlights a need for interventions that target lapses before they might occur, such as just-in-time adaptive interventions (JITAIs). To inform the decision points and tailoring variables of a lapse prevention JITAI, we trained and tested supervised machine learning algorithms that use Ecological Momentary Assessments (EMAs) and wearable sensor data of potential lapse triggers and lapse incidence. We aimed to identify a best-performing and feasible algorithm to take forwards in a JITAI. For 10 days, adult smokers attempting to quit were asked to complete 16 hourly EMAs/day assessing cravings, mood, activity, social context, physical context, and lapse incidence, and to wear a Fitbit Charge 4 during waking hours to passively collect data on steps and heart rate. A series of group-level supervised machine learning algorithms (e.g., Random Forest, XGBoost) were trained and tested, without and with the sensor data. Their ability to predict lapses for out-of-sample (i) observations and (ii) individuals were evaluated. Next, a series of individual-level and hybrid (i.e., group- and individual-level) algorithms were trained and tested. Participants (N = 38) responded to 6,124 EMAs (with 6.9% of responses reporting a lapse). Without sensor data, the best-performing group-level algorithm had an area under the receiver operating characteristic curve (AUC) of 0.899 (95% CI = 0.871-0.928). Its ability to classify lapses for out-of-sample individuals ranged from poor to excellent (AUCper person = 0.524-0.994; median AUC = 0.639). 15/38 participants had adequate data for individual-level algorithms to be constructed, with a median AUC of 0.855 (range: 0.451-1.000). Hybrid algorithms could be constructed for 25/38 participants, with a median AUC of 0.692 (range: 0.523 to 0.998). With sensor data, the best-performing group-level algorithm had an AUC of 0.952 (95% CI = 0.933-0.970). Its ability to classify lapses for out-of-sample individuals ranged from poor to excellent (AUCper person = 0.494-0.979; median AUC = 0.745). 11/30 participants had adequate data for individual-level algorithms to be constructed, with a median AUC of 0.983 (range: 0.549-1.000). Hybrid algorithms could be constructed for 20/30 participants, with a median AUC of 0.772 (range: 0.444 to 0.968). In conclusion, high-performing group-level lapse prediction algorithms without and with sensor data had variable performance when applied to out-of-sample individuals. Individual-level and hybrid algorithms could be constructed for a limited number of individuals but had improved performance, particularly when incorporating sensor data for participants with sufficient wear time. Feasibility constraints and the need to balance multiple success criteria in the JITAI development and implementation process are discussed.

Antipsychotic polypharmacy (APP) is frequent but evidence-based guidelines on reducing APP to antipsychotic monotherapy (APM) are sparse. We aimed to systematically review clinical interventions randomizing patients to reducing APP to APM versus continuing APP.

Alzheimer's disease (AD) is a prevalent neurodegenerative disease characterized by progressive cognitive and functional decline. Nearly all patients with AD develop neuropsychiatric symptoms (NPSs). Agitation is one of the most distressing and challenging NPS. Brexpiprazole is an oral antipsychotic and is the first approved pharmacologic agent in the United States for the treatment of agitation associated with dementia due to AD. Its effect is thought to be from its partial serotonin 5-HT and dopamine D receptor agonist activity and serotonin 5-HT receptor antagonism. Brexpiprazole is a maintenance medication, and it should not be used "as needed" or as a "PRN" treatment for breakthrough agitation. Brexpiprazole is a major substrate of CYP2D6 and CYP3A4. Dose adjustments may be required for drug interactions or impaired renal or hepatic function. Clinical trials found brexpiprazole 2 to 3 mg/d demonstrated significant improvements in agitation, with brexpiprazole showing an approximate 5-point greater reduction on change in the Cohen-Mansfield Agitation Inventory total score at week 12 from baseline compared with placebo. Brexpiprazole is generally well tolerated and safe, and common adverse reactions when used for this indication include dizziness, headaches, insomnia, nasopharyngitis, somnolence, and urinary tract infections. Like other antipsychotics used for agitation in AD, brexpiprazole is associated with higher mortality rates compared with placebo. In a long-term care setting, there are several considerations for its use. Benefits include an oral agent that is well tolerated and clinical data showing statistically significant effects on agitation. However, brexpiprazole has not been studied in head-to-head clinical trials against other antipsychotics, and there are differing opinions if the agitation score reductions translate to a clinically meaningful difference. The approval of brexpiprazole signals favorably for upcoming agents for this indication, including escitalopram and dextromethorphan-bupropion. Both escitalopram and dextromethorphan-bupropion are currently undergoing clinical trials.

Behavioral interventions require considerable practice of treatment skills in between therapy sessions. The effects of these treatments may vary with the degree to which patients are able to implement these practices. In offspring of parents with bipolar and major depressive disorders, we examined whether youth who frequently practiced communication and problem-solving skills between family-focused therapy (FFT) sessions had less severe mood symptoms and better psychosocial functioning over 6 months than youth who practiced less frequently.

Cognitive behavioral therapy for insomnia (CBTi) is the first-line therapy for chronic insomnia. Mobile app-based CBTi (MCBTi) can enhance the accessibility of CBTi treatment; however, few studies have evaluated the effectiveness of MCBTi using a multicenter, randomized controlled trial design.

Smartphone apps may provide an opportunity to deliver mental health resources and interventions in a scalable and cost-effective manner. However, young people from marginalized and underserved groups face numerous and unique challenges to accessing, engaging with, and benefiting from these apps.

Standardized definitions of suicidality phenotypes, including suicidal ideation (SI), attempt (SA), and death (SD) are a critical step towards improving understanding and comparison of results in suicide research. The complexity of suicidality contributes to heterogeneity in phenotype definitions, impeding evaluation of clinical and genetic risk factors across studies and efforts to combine samples within consortia. Here, we present expert and data-supported recommendations for defining suicidality and control phenotypes to facilitate merging current/legacy samples with definition variability and aid future sample creation.

Adolescents and young adults (AYAs) with cancer are at risk of poor psychosocial outcomes. AYAs grew up with the internet and digital technology, and mobile Health (mHealth) psychosocial interventions have the potential to overcome care access barriers.

In China, standard smoking cessation practices are rarely used by healthcare service providers (HSPs). WeChat, a popular social media app, has been widely used in China.

Access to evidence-based interventions is urgently required, especially for individuals of minoritized identities who experience unique barriers to mental health care. Digital mental health interventions have the potential to increase accessibility. Previous pilot studies testing HabitWorks, a smartphone app providing an interpretation bias intervention, have found strong engagement and adherence for HabitWorks; however, previous trials' samples consisted of predominantly non-Hispanic, White individuals.

Transmembrane and coiled-coil 2 (TMCC2) is a human orthologue of the Drosophila gene dementin, mutant alleles of which cause neurodegeneration with features of Alzheimer's disease (AD). TMCC2 and Dementin further have an evolutionarily conserved interaction with the amyloid protein precursor (APP), a protein central to AD pathogenesis. To investigate if human TMCC2 might also participate in mechanisms of neurodegeneration, we examined TMCC2 expression in late onset AD human brain and age-matched controls, familial AD cases bearing a mutation in APP Val717, and Down syndrome AD. Consistent with previous observations of complex formation between TMCC2 and APP in the rat brain, the dual immunocytochemistry of control human temporal cortex showed highly similar distributions of TMCC2 and APP. In late onset AD cases stratified by APOE genotype, TMCC2 immunoreactivity was associated with dense core senile plaques and adjacent neuronal dystrophies, but not with Aβ surrounding the core, diffuse Aβ plaques or tauopathy. In Down syndrome AD, we observed in addition TMCC2-immunoreactive and methoxy-X04-positive pathological features that were morphologically distinct from those seen in the late onset and familial AD cases, suggesting enhanced pathological alteration of TMCC2 in Down syndrome AD. At the protein level, western blots of human brain extracts revealed that human brain-derived TMCC2 exists as at least three isoforms, the relative abundance of which varied between the temporal gyrus and cerebellum and was influenced by APOE and/or dementia status. Our findings thus implicate human TMCC2 in AD via its interactions with APP, its association with dense core plaques, as well as its alteration in Down syndrome AD.

Time-to-event prediction is a key task for biological discovery, experimental medicine, and clinical care. This is particularly true for neurological diseases where development of reliable biomarkers is often limited by difficulty visualising and sampling relevant cell and molecular pathobiology. To date, much work has relied on Cox regression because of ease-of-use, despite evidence that this model includes incorrect assumptions. We have implemented a set of deep learning and spline models for time-to-event modelling within a fully customizable 'app' and accompanying online portal, both of which can be used for any time-to-event analysis in any disease by a non-expert user. Our online portal includes capacity for end-users including patients, Neurology clinicians, and researchers, to access and perform predictions using a trained model, and to contribute new data for model improvement, all within a data-secure environment. We demonstrate a pipeline for use of our app with three use-cases including imputation of missing data, hyperparameter tuning, model training and independent validation. We show that predictions are optimal for use in downstream applications such as genetic discovery, biomarker interpretation, and personalised choice of medication. We demonstrate the efficiency of an ensemble configuration, including focused training of a deep learning model. We have optimised a pipeline for imputation of missing data in combination with time-to-event prediction models. Overall, we provide a powerful and accessible tool to develop, access and share time-to-event prediction models; all software and tutorials are available at www.predictte.org.

Mobile mental health apps are a cost-effective option for managing mental health problems, such as posttraumatic stress disorder (PTSD). The efficacy of mobile health (mHealth) apps depends on engagement with the app, but few studies have examined how users engage with different features of mHealth apps for PTSD.

Mental health problems among workers cause enormous losses to companies in Japan. However, workers have been considered to have limited access to psychological support because of time constraints, which makes it difficult for them to engage in face-to-face psychological support interventions.

Fathers can be a critical source of breastfeeding support for their partner, but little is known about what fathers would like to learn about breastfeeding. Partner's support and encouragement enhances mother's breastfeeding confidence and boost the capacity to address breastfeeding difficulties effectively. The aims of this study were to explore what fathers regard as important to learn around breastfeeding, and their current and preferred sources of information.

Structural and functional changes of the choroid plexus (ChP) have been reported in Alzheimer's disease (AD). Nonetheless, the role of the ChP in the pathogenesis of AD remains largely unknown. We aim to unravel the relation between ChP functioning and core AD pathogenesis using a unique proteomic approach in mice and humans.

The extent to which interventions are perceived as acceptable to users impacts engagement and efficacy.

To pilot test QuitGuide for Natives, a culturally aligned version of the National Cancer Institute's QuitGuide smartphone app for smoking cessation.

This article examines the implementation, participation rates, and potential determinants of participation in the digital addiction prevention program "ready4life." A two-arm cluster-randomized trial recruited German vocational students via class-based strategies. Intervention group received 16 weeks of in-app coaching; the control group received health behavior information, with coaching offered after 12 months. Potential determinants of participation were analyzed based on class and individual characteristics. Out of 525 contacted schools, 35 participated, enrolling 376 classes. Implementation during the pandemic required flexible adjustments, with 49.7% of introductions conducted in person, 43.1% digitally via online streaming, and 7.2% received a video link via email. Despite challenges, 72.3% of the vocational students downloaded the app, and 46.7% gave informed consent. Participation rates were highest among (associate) professionals, vocational grammar school classes, classes introduced by females, younger individuals, members of the project team, and classes introduced face-to-face. Female gender, lower social competencies, lifetime cannabis use, higher problematic internet use, and higher perceived stress were associated with higher individual participation. The study highlights the importance of proactive outreach and personalized interventions for addiction prevention programs in vocational schools. While reached students aligned with the aims of the app, tailored recruitment strategies could enhance engagement among under-represented groups. The trial was registered in the German Clinical Trials Register (DRKS): DRKS00022328; registration date 09.10.2020.

Addressing the limited access to treatments for alcohol dependence, we developed ALM-002, a therapeutic application to be "prescribed" for non-abstinence-oriented treatment in internal medicine settings. Our objective was to preliminarily assess the efficacy and safety of ALM-002.

We present results from a 2-site, randomized clinical trial to assess the efficacy of a brief intervention (As Safe As Possible [ASAP]), a safety plan phone application (BRITE), and their combination on suicide attempts, suicidal ideation, non-suicidal self-injury, re-hospitalizations. and suicidal events among adolescents.

Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used approach for the generation of gene co-expression networks. However, networks generated with this tool usually create large modules with a large set of functional annotations hard to decipher. We have developed TGCN, a new method to create Targeted Gene Co-expression Networks. This method identifies the transcripts that best predict the trait of interest based on gene expression using a refinement of the LASSO regression. Then, it builds the co-expression modules around those transcripts. Algorithm properties were characterized using the expression of 13 brain regions from the Genotype-Tissue Expression project. When comparing our method with WGCNA, TGCN networks lead to more precise modules that have more specific and yet rich biological meaning. Then, we illustrate its applicability by creating an APP-TGCN on The Religious Orders Study and Memory and Aging Project dataset, aiming to identify the molecular pathways specifically associated with APP role in Alzheimer's disease. Main biological findings were further validated in two independent cohorts. In conclusion, we provide a new framework that serves to create targeted networks that are smaller, biologically relevant and useful in high throughput hypothesis driven research. The TGCN R package is available on Github: https://github.com/aliciagp/TGCN .

Neurovascular defects are one of the most common alterations in Alzheimer's disease (AD) pathogenesis, but whether these deficits develop before the onset of amyloid beta (Aβ) accumulation remains to be determined. Using in vivo optical imaging in freely moving mice, we explored activity-induced hippocampal microvascular blood flow dynamics in App knock-in and J20 mouse models of AD at early stages of disease progression. We found that prior to the onset of Aβ accumulation, there was a pathologically elevated blood flow response to context exploration, termed functional hyperemia. After the onset of Aβ accumulation, this context exploration-induced hyperemia declined rapidly relative to that in control mice. Using in vivo electrophysiology recordings to explore the neural circuit mechanism underlying this blood flow alteration, we found that hippocampal interneurons before the onset of Aβ accumulation were hyperactive during context exploration. Chemogenetic tests suggest that hyperactive activation of inhibitory neurons accounted for the elevated functional hyperemia. The suppression of nitric oxide (NO) produced from hippocampal interneurons in young AD mice decreased the accumulation of Aβ. Together, these findings reveal that neurovascular coupling is aberrantly elevated before Aβ deposition, and this hyperactive functional hyperemia declines rapidly upon Aβ accumulation.

The degree of physiological responses to individual antipsychotic drugs is unclear in children and adolescents. With network meta-analysis, we aimed to investigate the effects of various antipsychotic medications on physiological variables in children and adolescents with neuropsychiatric and neurodevelopmental conditions.

The management of stress has evolved in recent years due to widespread availability of mobile-device applications (apps) and their capacity to deliver psychological interventions. We evaluated the efficacy of mental health apps on stress and sought to identify characteristics associated with effect size estimates. Sixty-nine randomised controlled trials (RCTs) were included. Random effects meta-analyses were performed and putative moderators were examined at univariate and multivariate (combinations and interactions) levels. From 78 comparisons, we observed a small but significant pooled effect of apps over control conditions on perceived stress levels ( = 0.27; 95% CI = 0.20, 0.34; = 68%). This effect weakened after taking into account small-study bias according to the trim-and-fill procedure ( = 0.10; 95% CI = 0.02, 0.19; = 78%). Delivery of apps with stress monitoring features produced smaller efficacy estimates, although this association interacted with other trial features (small sample size and inactive control group) in multivariate analyses, suggesting that this effect may have been explained by features characteristic of low-quality trials. Mental health apps appear to have small, acute effects on reducing perceived stress. Future research should shift focus towards identifying change mechanisms, longitudinal outcomes, features that facilitate sustained app usage, and tangible pathways to integrating apps into real-world clinical settings.

Cannabigerol (CBG) is a phytocannabinoid increasing in popularity, with preclinical research indicating it has anxiolytic and antidepressant effects. However, there are no published clinical trials to corroborate these findings in humans. The primary objective of this study was to examine acute effects of CBG on anxiety, stress, and mood. Secondary objectives were to examine whether CBG produces subjective drug effects or motor and cognitive impairments. A double-blind, placebo-controlled cross-over field trial was conducted with 34 healthy adult participants. Participants completed two sessions (with a one-week washout period) via Zoom. In each, they provided ratings of anxiety, stress, mood, and subjective drug effects prior to double-blind administration of 20 mg hemp-derived CBG or placebo tincture (T0). These ratings were collected again after participants ingested the product and completed an online survey (T1), the Trier Social Stress Test (T2), a verbal memory test and the DRUID impairment app (T3). Relative to placebo, there was a significant main effect of CBG on overall reductions in anxiety as well as reductions in stress at T1. CBG also enhanced verbal memory relative to placebo. There was no evidence of subjective drug effects or impairment. CBG may represent a novel option to reduce stress and anxiety in healthy adults.

Intensive longitudinal research-including experience sampling and smartphone sensor monitoring-has potential for identifying proximal risk factors for psychopathology, including suicidal thoughts and behaviors (STB). Yet, missing data can complicate analysis and interpretation. This study aimed to address whether clinical and study design factors are associated with missing data and whether missingness predicts changes in symptom severity or STB. Adolescents ages 13- to 18 years old ( = 179) reporting depressive, anxiety, and/or substance use disorders were enrolled; 65% reported current suicidal ideation and 29% indicated a past-year attempt. Passively acquired smartphone sensor data (e.g., global positioning system, accelerometer, and keyboard inputs), daily mood surveys, and weekly suicidal ideation surveys were collected during the 6-month study period using the effortless assessment research system smartphone app. First, acquisition of passive smartphone sensor data (with data on ∼80% of days across the whole sample) was strongly associated with survey data acquisition on the same day (∼44% of days). Second, STB and psychiatric symptoms were largely not associated with missing data. Rather, temporal features (e.g., length of time in study, weekends, and summer) explained more missingness of survey and passive smartphone sensor data. Last, within-participant changes in missing data over time neither followed nor predicted subsequent change in suicidal ideation and psychiatric symptoms. Findings indicate that considering technical and study design factors impacting missingness is critical and highlight several factors that should be addressed to maximize the validity of clinical interpretations in intensive longitudinal research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

People with serious mental health problems (SMHP) are more likely to be admitted to psychiatric hospital following contact with crisis services. Admissions can have significant personal costs, be traumatic and are the most expensive form of mental health care. There is an urgent need for treatments to reduce suicidal thoughts and behaviours and reduce avoidable psychiatric admissions.

This study explores the experiences of young adults with psychosis using a smartphone application to promote patient activation and support shared decision making in their outpatient treatment.

People with epilepsy frequently under- or inaccurately report their seizures, which poses a challenge for evaluating their treatment. The introduction of epilepsy health apps provides a novel approach that could improve seizure documentation. This study assessed the documentation performance of an app-based seizure diary and a conventional paper seizure diary. At two tertiary epilepsy centers patients were asked to use one of two offered methods to report their seizures (paper or app diary) during their stay in the epilepsy monitoring unit. The performances of both methods were assessed based on the gold standard of video-EEG annotations. In total 89 adults (54 paper and 35 app users) with focal epilepsy were included in the analysis, of which 58 (33 paper and 25 app users) experienced at least one seizure and made at least one seizure diary entry. We observed a high precision of 85.7% for the app group, whereas the paper group's precision was lower due to overreporting (66.9%). Sensitivity was similar for both methods. Our findings imply that performance of seizure self-reporting is patient-dependent but is more precise for patients who are willing to use digital apps. This may be relevant for treatment decisions and future clinical trial design.

The aggregation and deposition of amyloid-β (Aβ) peptides in the brain is thought to be the initial driver in the pathogenesis of Alzheimer's disease (AD). Aside from full-length Aβ peptides starting with an aspartate residue in position 1, both N-terminally truncated and elongated Aβ peptides are produced by various proteases from the amyloid precursor protein (APP) and have been detected in brain tissues and body fluids. Recently, we demonstrated that the particularly abundant N-terminally truncated Aβ4-x peptides are generated by ADAMTS4, a secreted metalloprotease that is exclusively expressed in the oligodendrocyte cell population. In this study, we investigated whether ADAMTS4 might also be involved in the generation of N-terminally elongated Aβ peptides.

Home-based psychosocial care has the potential to improving outcomes in patients with schizophrenia and related disorders (SCZ). There is lack of India data for such care in early psychosis. We developed the "Saksham" programme, a bespoke self-managed home-based psychosocial care model, available in two formats: manual-based and mobile-application based. With the anticipated success of recruitment of early psychosis cases in our setting, we plan to test the such intervention in this population in future trials.

Non-compliance to medications remains a challenging problem in schizophrenia. Newer strategies with high feasibility and acceptability are always being researched. This study aimed to assess the effectiveness of technology-based intervention in improving medication compliance in individuals with schizophrenia.

Despite a marked increase in the prevalence of pediatric IgE-mediated food allergy (FA) in recent decades, there is a dearth of age-appropriate management education and support tools for youth with FA. The purpose of this report is to detail our methods for intervention design and refinement of an interactive educational software program for school-aged children with FA.

Traditional cognitive assessments in schizophrenia are time-consuming and necessitate specialized training, making routine evaluation challenging. To overcome these limitations, this study investigates the feasibility and advantages of utilizing smartphone-based assessments to capture both cognitive functioning and digital phenotyping data and compare these results to gold standard measures. We conducted a secondary analysis of data from 76 individuals with schizophrenia, who were recruited across three sites (one in Boston, two in India) was conducted. The open-source mindLAMP smartphone app captured digital phenotyping data and Trails A/B assessments of attention / memory for up to 12 months. The smartphone-cognitive tasks exhibited potential for normal distribution and these scores showed small but significant correlations with the results from the Brief Assessment of Cognition in Schizophrenia, especially the digital span and symbol coding tasks (r2 = 0.21). A small but significant correlation (r2 = 0.29) between smartphone-derived cognitive scores and health-related behaviors such as sleep duration patterns was observed. Smartphone-based cognitive assessments show promise as cross-cultural tools that can capture relevant data on momentary states among individuals with schizophrenia. Cognitive results related to sleep suggest functional applications to digital phenotyping data, and the potential of this multimodal data approach in research.

Microglia activity can drive excessive synaptic loss during the prodromal phase of Alzheimer's disease (AD) and is associated with lowered cyclic adenosine monophosphate (cAMP) due to cAMP phosphodiesterase 4B (PDE4B). This study aimed to investigate whether long-term inhibition of PDE4B by A33 (3 mg/kg/day) can prevent synapse loss and its associated cognitive decline in APPswe/PS1dE9 mice. This model is characterized by a chimeric mouse/human APP with the Swedish mutation and human PSEN1 lacking exon 9 (dE9), both under the control of the mouse prion protein promoter. The effects on cognitive function of prolonged A33 treatment from 20 days to 4 months of age, was assessed at 7-8 months. PDE4B inhibition significantly improved both the working and spatial memory of APPswe/PSdE9 mice after treatment ended. At the cellular level, in vitro inhibition of PDE4B induced microglial filopodia formation, suggesting that regulation of PDE4B activity can counteract microglia activation. Further research is needed to investigate if this could prevent microglia from adopting their 'disease-associated microglia (DAM)' phenotype in vivo. These findings support the possibility that PDE4B is a potential target in combating AD pathology and that early intervention using A33 may be a promising treatment strategy for AD.

The amyloid cascade hypothesis assumes that the development of Alzheimer's disease (AD) is driven by a self-perpetuating cycle, in which β-amyloid (Aβ) accumulation leads to Tau pathology and neuronal damages. A particular mutation (A673T) of the amyloid precursor protein (APP) was identified among Icelandic population. It provides a protective effect against Alzheimer- and age-related cognitive decline. This APP mutation leads to the reduced production of Aβ with A2T (position in peptide sequence) change (Aβ). In addition, Aβ has the capacity to form protective heterodimers in association with wild-type Aβ. Despite the emerging interest in Aβ during the last decade, the impact of Aβ on events associated with the amyloid cascade has never been reported. First, the effects of Aβ were evaluated in vitro by electrophysiology on hippocampal slices and by studying synapse morphology in cortical neurons. We showed that Aβ protects against endogenous Aβ-mediated synaptotoxicity. Second, as several studies have outlined that a single intracerebral administration of Aβ can worsen Aβ deposition and cognitive functions several months after the inoculation, we evaluated in vivo the long-term effects of a single inoculation of Aβ or Aβ-wild-type (Aβ) in the hippocampus of transgenic mice (APP/PS1) over-expressing Aβ peptide. Interestingly, we found that the single intra-hippocampal inoculation of Aβ to mice rescued synaptic density and spatial memory losses four months post-inoculation, compared with Aβ inoculation. Although Aβ load was not modulated by Aβ infusion, the amount of Tau-positive neuritic plaques was significantly reduced. Finally, a lower phagocytosis by microglia of post-synaptic compounds was detected in Aβ-inoculated animals, which can partly explain the increased density of synapses in the Aβ animals. Thus, a single event as Aβ inoculation can improve the fate of AD-associated pathology and phenotype in mice several months after the event. These results open unexpected fields to develop innovative therapeutic strategies against AD.

Specific phobias impact over 400 million people worldwide. Digitalizing mental health could alleviate the burden. Still, although the corporate-driven Metaverse is expanding rapidly, there needs to be more momentum in harnessing virtual reality exposure therapy uptake. This study aims to conceptualize, develop, and deploy a free Virtual Reality Exposure Therapy (VRET) application specifically designed for treating acrophobia and claustrophobia. This pilot study, which holds the promise of a future where mental health is more accessible and effective, explores the feasibility of leveraging transdisciplinary collaboration among specialists to create a safe, accessible, and effective VRET solution. We conducted a Delphi heuristic approach involving bioethicists, neuroscientists, and tech developers. Second, we reviewed the existing psychological theories and therapeutic strategies for addressing phobias in VR. Third, we conceptualized a thematic analysis-derived framework for a safe, adaptive-gamified free exposure to virtual reality acrophobia and claustrophobia (SAFEvR ACT). Finally, we provide an overview of the iterative improvements made during 12 workshops and 76 weekly briefings on developmental implementations. We developed the SAFEvR ACT into a proof-of-concept application freely deployed on the MentalVerse app platform. Our safety-focused approach can benefit from prevalidation perspectives within future randomized control trials. The resulting application derived from the SAFEvR ACT framework represents a blueprint to counter the current lack of iVR mental health uptake by offering a free VRET alternative. Future research should aim towards developing similar free platforms to lessen mental health burdens and gather quantitative data. We conclude with a call to action to researchers to fine-tune our current approach and take a stand for free digital mental health within MentalVeRse.app.

This is a process evaluation of a large UK-based randomised controlled trial (RCT) (n = 5602) evaluating the effectiveness of recommending an alcohol reduction app, Drink Less, compared with usual digital care in reducing alcohol consumption in increasing and higher risk drinkers. The aim was to understand whether participants' engagement ('self-reported adherence') and behavioural characteristics were mechanisms of action underpinning the effectiveness of Drink Less. Self-reported adherence with both digital tools was over 70% (Drink Less: 78.0%, 95% CI = 77.6-78.4; usual digital care: 71.5%, 95% CI = 71.0-71.9). Self-reported adherence to the intervention (average causal mediation effect [ACME] = -0.250, 95% CI = -0.42, -0.11) and self-monitoring behaviour (ACME = -0.235, 95% CI = -0.44, -0.03) both partially mediated the effect of the intervention (versus comparator) on alcohol reduction. Following the recommendation (self-reported adherence) and the tracking (self-monitoring behaviour) feature of the Drink Less app appear to be important mechanisms of action for alcohol reduction among increasing and higher risk drinkers.

Clinicians often ask people with chronic pain about their perceived benefit from interventions designed to improve their pain. The aim of this study is to identify factors that contribute to underestimating or overestimating perceived changes in daily pain intensity over a month of daily assessments. We examined data from individuals with chronic pain who provided at least 28 daily assessments using a pain app as secondary analyses. Participants provided baseline demographic information and completed questionnaires assessing pain, activity interference, mood, pain disability, and catastrophizing. Using the pain app, they entered daily ratings of pain (0 = none, 10 = worst pain possible) and impressions of perceived day-to-day change (0 = better, 5 = same, and 10 = worse). Two hundred fifty-two (N = 252) subjects with chronic pain met the inclusion criteria of completing at least 28 daily assessments. Those who underestimated their improvement tended to have higher pain intensity at baseline (P < .001), reported greater activity interference and disability (P < .001), and were prone to greater catastrophizing and anxiety and depression (P < .01). People who were more accurate in assessing their improvement engaged less with the app with fewer 2-way messages compared with those who either underestimated or overestimated their improvement and who had more 2-way messaging (P < .05). This longitudinal study suggests that those who report greater levels of catastrophizing and anxiety and depression are more likely to underestimate any improvements in their pain over time but seem to engage more with a pain app. Future research will help in our understanding of what magnitude of perceived change in pain ratings is clinically meaningful. PERSPECTIVE: Those who report greater levels of pain, disability, anxiety, depression, and catastrophizing are most prone to underestimate improvements of their pain over time.

Little is known about the social validity of self-harm prevention apps for young adolescents with severe mental health problems who repeatedly self-harm.

Our study aims to delineate the phenotypes of chronic neuropsychiatric symptoms among adult subjects recovering from their first COVID that occurred more than one year ago. We also aim to explore the clinical and socioeconomic risk factors of having a high loading of chronic neuropsychiatric symptoms. We recruited a post-COVID group who suffered from their first pre-Omicron COVID more than a year ago, and a control group who had never had COVID. The subjects completed app-based questionnaires on demographic, socioeconomic and health status, a COVID symptoms checklist, mental and sleep health measures, and neurocognitive tests. The post-COVID group has a statistically significantly higher level of fatigue compared to the control group (p < 0.001). Among the post-COVID group, the lack of any COVID vaccination before the first COVID and a higher level of material deprivation before the COVID pandemic predicts a higher load of chronic post-COVID neuropsychiatric symptoms. Partial correlation network analysis suggests that the chronic post-COVID neuropsychiatric symptoms can be clustered into two major (cognitive complaints -fatigue and anxiety-depression) and one minor (headache-dizziness) cluster. A higher level of material deprivation predicts a higher number of symptoms in both major clusters, but the lack of any COVID vaccination before the first COVID only predicts a higher number of symptoms in the cognitive complaints-fatigue cluster. Our result suggests heterogeneity among chronic post-COVID neuropsychiatric symptoms, which are associated with the complex interplay of biological and socioeconomic factors.

Frontotemporal lobar degeneration (FTLD) is a leading cause of dementia in individuals aged <65 years. Several challenges to conducting in-person evaluations in FTLD illustrate an urgent need to develop remote, accessible, and low-burden assessment techniques. Studies of unobtrusive monitoring of at-home computer use in older adults with mild cognitive impairment show that declining function is reflected in reduced computer use; however, associations with smartphone use are unknown.

General Practitioners (GPs) play a key role in the early detection and management of depression and in preventing suicide risk. They are often the first healthcare professionals that people in crisis contact. However, their effectiveness can be limited by several barriers, including the lack of specific training and appropriate tools.The EAAD-Best project aims to fill these gaps through its iFightDepression tool, an online tool designed to support patients, psychologists, psychiatrists, and GPs in managing depression and preventing suicide. This article examines the implementation of the iFightDepression platform in Italy, assessing its impact on the empowerment of GPs in the fight against depression. Through a qualitative and quantitative analysis of the data collected by the project, the 'unmet need' of GPs' in Italy regarding their specific training in mental health is highlighted.The response of 2,068 Italian GPs in just 7 months after the start of the iFD project is an expression of GPs' engagement to work against depression and for suicide risk prevention.

The purpose of this pilot study was to conduct a process evaluation of a mental health and wellness mobile health (mHealth) application for medical students designed to increase resilience and decrease mental health stigma.

Pediatric oncology patients use totally implantable venous access devices (TIVADs) to enable central venous access. Anxiety, pain and/or discomfort are common despite anesthesia. Virtual reality (VR) is a non-pharmacological approach that may reduce pain and anxiety in these patients. We aimed to assess the use of VR for reducing anxiety/pain in patients with TIVADs while facilitating the task of healthcare providers when accessing a TIVAD.

Parents of children with a neurodevelopmental disorder (NDD) experience more stress than parents of typically developing children. In a cocreation process with experts and parents, a low-threshold application that uses exercises based on the principles of positive psychology and mindfulness was developed. This application, called "Adappt," aims at enhancing the ability to adapt of the parents and caregivers of children with NDDs and at supporting their mental health. This protocol describes the evaluation study of the effectiveness of Adappt, its core working mechanisms and user experiences.

Impaired brain protein synthesis, synaptic plasticity, and memory are major hallmarks of Alzheimer's disease (AD). The ketamine metabolite (2R,6R)-hydroxynorketamine (HNK) has been shown to modulate protein synthesis, but its effects on memory in AD models remain elusive.

Human biological rhythms are commonly assessed through physical activity (PA) measurement, but mental activity may offer a more substantial reflection of human biological rhythms.

Technology improves accessibility of psychological interventions for youth. An ecological momentary intervention (EMI) is a digital intervention geared toward intervening in daily life to enhance the generalizability and ecological validity, and to be able to intervene in moments most needed. Identifying working mechanisms of the use of ecological momentary interventions might generate insights to improve interventions.

To describe the pattern of the prevalence of mental health problems during the first year of the COVID-19 pandemic and examine the impact of containment measures on these trends.

Alzheimer's disease (AD) is a devastating disorder with a global prevalence estimated at 55 million people. In clinical studies administering certain anti-beta-amyloid (Aβ) antibodies, amyloid-related imaging abnormalities (ARIAs) have emerged as major adverse events. The frequency of these events is higher among apolipoprotein ε4 allele carriers () compared to non-carriers. To reflect patients most at risk for vascular complications of anti-Aβ immunotherapy, we selected an APPswe/PS1dE9 transgenic mouse model bearing the human gene (APPPS1:E4) and compared it with the same APP/PS1 mouse model bearing the human gene ( ε3 allele; APPPS1:E3). Using histological and biochemical analyses, we characterized mice at three ages: 8, 12, and 16 months. Female and male mice were assayed for general cerebral fibrillar and pyroglutamate (pGlu-3) Aβ deposition, cerebral amyloid angiopathy (CAA), microhemorrhages, apoE and cholesterol composition, astrocytes, microglia, inflammation, lysosomal dysfunction, and neuritic dystrophy. Amyloidosis, lipid deposition, and astrogliosis increased with age in APPPS1:E4 mice, while inflammation did not reveal significant changes with age. In general, carriers showed elevated Aβ, apoE, reactive astrocytes, pro-inflammatory cytokines, microglial response, and neuritic dystrophy compared to carriers at different ages. These results highlight the potential of the APPPS1:E4 mouse model as a valuable tool in investigating the vascular side effects associated with anti-amyloid immunotherapy.

Manganese (Mn) is an essential heavy metal in the human body, while excess leads to neurotoxicity, as observed in this study, where 100 µM of was administered to the human neuroblastoma (SH-SY5Y) cell model of dopaminergic neurons in neurodegenerative diseases. We quantitated pathway and gene changes in homeostatic cell-based adaptations to exposure. Utilizing the Gene Expression Omnibus, we accessed the GSE70845 dataset as a microarray of SH-SY5Y cells published by Gandhi et al. (2018) and applied statistical significance cutoffs at < 0.05. We report 74 pathway and 10 gene changes with statistical significance. ReactomeGSA analyses demonstrated upregulation of histones (5 out of 10 induced genes) and histone deacetylases as a neuroprotective response to remodel/mitigate -induced DNA/chromatin damage. Neurodegenerative-associated pathway changes occurred. NF-κB signaled protective responses via Sirtuin-1 to reduce neuroinflammation. Critically, activated three pathways implicating deficits in purine metabolism. Therefore, we validated that urate, a purine and antioxidant, mitigated -losses of viability in SH-SY5Y cells. We discuss as a hypoxia mimetic and trans-activator of HIF-1α, the central trans-activator of vascular hypoxic mitochondrial dysfunction. induced a 3-fold increase in mRNA levels for antioxidant metallothionein-III, which was induced 100-fold by hypoxia mimetics deferoxamine and zinc.

Mobile apps provide a unique platform for mental health assessment and monitoring. They can provide real time, accessible data on symptoms of mental disorders that may yield rich data for detailed clinical assessment and help individuals gain insight into their current mental state. We developed one of the first apps for tracking symptoms of prolonged grief disorder.

The chapter explores the role of neuropsychology in understanding brain fog as a subjective complaint in the context of COVID-19. It discusses the historical and medical significance of the term "brain fog" and its psychological and neurological aspects. The chapter identifies the cognitive domains commonly affected by brain fog, such as attention, executive function, memory, and language. Additionally, it emphasizes the impact of societal changes during the COVID-19 pandemic on the general population as a crucial backdrop for understanding the issue. The chapter also highlights the important role of clinical and research neuropsychologists in gaining clarity on grouped data and individual patients' cognitive and emotional difficulties after COVID-19 infection. It discusses indications for neuropsychological rehabilitation and therapy and describes typical therapy phases and methods, including new approaches like telemedicine, virtual reality, and mobile app-based rehabilitation and self-tracking. The chapter underscores that experiences of brain fog can vary among COVID-19 patients and may change over time. It provides clinicians and interested parties with an in-depth understanding of brain fog and its manifestations, concomitant subtypes, and concrete strategies for addressing it. The chapter emphasizes the critical role of neuropsychology in scientifically examining brain fog and advocating for personalized approaches to cognitive rehabilitation.

Trace amine-associated receptor 1 (TAAR1) agonism shows promise for treating psychosis, prompting us to synthesise data from human and non-human studies.

Modulation of physical activity represents an important intervention that may delay, slow, or prevent mild cognitive impairment (MCI) or dementia due to Alzheimer's disease (AD). One mechanism proposed to underlie the beneficial effect of physical exercise (PE) involves the apparent stimulation of adult hippocampal neurogenesis (AHN). BCI-838 is a pro-drug whose active metabolite BCI-632 is a negative allosteric modulator at group II metabotropic glutamate receptors (mGluR2/3). We previously demonstrated that administration of BCI-838 to a mouse model of brain accumulation of oligomeric Aβ ( = "") reduced learning behavior impairment and anxiety, both of which are associated with the phenotype of mice.

Neuroinflammation includes the activation of immune glial cells in the central nervous system, release pro-inflammatory cytokines, which disrupt normal neural function and contribute to various neurological disorders, including Alzheimer's disease (AD), Parkinson's disease, multiple sclerosis, and stroke. AD is characterized by various factors including amyloidogenesis, synaptic dysfunction, memory impairment and neuroinflammation. Lipopolysaccharide (LPS) constitutes a vital element of membrane of the gram-negative bacterial cell, triggering vigorous neuroinflammation and facilitating neurodegeneration. Lupeol, a naturally occurring pentacyclic triterpene, has demonstrated several pharmacological properties, notably its anti-inflammatory activity. In this study, we evaluated the anti-inflammatory and anti-Alzheimer activity of lupeol in lipopolysaccharide (LPS)-injected mice model. LPS (250ug/kg) was administered intraperitoneally to C57BL/6 N male mice for 1 week to induce neuroinflammation and cognitive impairment. For biochemical analysis, acetylcholinesterase (AChE) assay, western blotting and confocal microscopy were performed. AChE, western blot and immunofluorescence results showed that lupeol treatment (50 mg/kg) along with LPS administration significantly inhibited the LPS-induced activation of neuroinflammatory mediators and cytokines like nuclear factor (NF-κB), tumor necrosis factor (TNF-α), cyclooxygenase (COX-2) and interleukin (IL-1β). Furthermore, we found that LPS-induced systemic inflammation lead to Alzheimer's symptoms as LPS treatment enhances level of amyloid beta (Aβ), amyloid precursor protein (APP), Beta-site APP cleaving enzyme (BACE-1) and hyperphosphorylated Tau (p-Tau). Lupeol treatment reversed the LPS-induced elevated level of Aβ, APP, BACE-1 and p-Tau in the hippocampus, showing anti-Alzheimer's properties. It is also determined that lupeol prevented LPS-induced synaptic dysfunction via enhanced expression of pre-and post-synaptic markers like SNAP-23, synaptophysin and PSD-95. Overall, our study shows that lupeol prevents memory impairment and synaptic dysfunction via inhibition of neuroinflammatory processes. Hence, we suggest that lupeol might be a useful therapeutic agent in prevention of neuroinflammation-induced neurological disorders like AD.

There is scant empirical work on associations between current and past cannabis use and parenting skills in parents of young children. As recreational cannabis use is now legal in nearly half of states in the U.S., cannabis use is becoming more ubiquitous.

Depression is prevalent among individuals who smoke cigarettes and increases risk for relapse. A previous clinical trial suggests that Goal2Quit, a behavioral activation-based smoking cessation mobile app, effectively increases smoking abstinence and reduces depressive symptoms. Secondary analyses were conducted on these trial data to identify predictors of success in depression-specific digitalized cessation interventions. Adult who smoked cigarettes (age = 38.4 ± 10.3, 53% women) were randomized to either use Goal2Quit for 12 weeks ( = 103), paired with a 2-week sample of nicotine replacement therapy (patch and lozenge) or to a Treatment-As-Usual (TAU) control ( = 47). The least absolute shrinkage and selection operator was utilized to identify a subset of baseline variables predicting either smoking or depression intervention outcomes. The retained predictors were then fitted linear regression models to determine relations to each intervention outcome. Relative to TAU, only individuals who spent significant time using Goal2Quit (56 ± 46 min) were more likely to reduce cigarette use by at least 50% after 12 weeks, whereas those who spent minimal time using Goal2Quit (10 ± 2 min) did not exhibit significant changes. An interaction between educational attainment and treatment group revealed that, as compared to TAU, only app users with an educational degree beyond high school exhibited significant reductions in depression. The findings highlight the importance of tailoring depression-specific digital cessation interventions to individuals' unique engagement needs and educational level. This study provides a potential methodological template for future research aimed at personalizing technology-based treatments for cigarette users with depressive symptoms.

Informal caregivers of persons with dementia (PWD) often suffer adverse impacts on their mental health and require interventions for effective support. As they are often occupied with providing care, web-based interventions could be more convenient and efficient for them. However, there is currently a dearth of evidence-based mobile interventions to enhance the mental well-being of dementia caregivers locally, especially ones that are user-centered and culturally relevant. Hence, having designed an app based on feedback from local dementia caregivers, this study will evaluate the effectiveness of this mobile app in promoting the mental health of informal caregivers of PWD in Singapore.

Paranoia is relatively common but can lead to significant distress, impairment and need for care. Digital technologies offer a valuable extension to service provision and are increasingly being integrated into healthcare. This systematic review evaluated feasibility, acceptability, and effectiveness of digitally enhanced psychological assessments and treatments for paranoia across the paranoia continuum (PROSPERO: CRD42023393257).

Children with cleft palate, with or without cleft lip (CP±L), exhibit language delays on average compared to children without clefts. Interventions to address these disparities are scarce. In this multi-center study, Book Sharing for Toddlers with Clefts (BOOST), we will test a remote, parent-focused intervention to promote language development in children with CP±L.

In our times of smartphone ubiquity, mobile applications are an inescapable daily life tool, including in health care. Music therapy has already proven its worth, notably in mental health. Hence, we were interested in the mobile app format for this type of therapy, its level of evidence, how to use it in daily psychiatric care and the leads for future research and innovation.

The mobile health application "Stress Autism Mate" (SAM) was designed to support adults with autism in identifying and managing daily stress. SAM measures stress four times daily, provides a daily and weekly stress overview, and provides personalised stress reduction advice. This study aimed to assess the effectiveness of SAM over four weeks in reducing perceived stress and internalised stigma, and enhancing coping self-efficacy, quality of life, and resilience among adults with autism.

Anhedonia is a key symptom of depression, and it has been suggested as a potential target for future individualised treatments. However, much is unknown about how interventions enhancing dopaminergic pathways may affect anhedonia symptoms in the context of depression. We will perform independent searches in multiple electronic databases to identify clinical and animal experimental studies on pro-dopaminergic interventions in individuals with depression or animal models for depression. The primary outcomes will be overall anhedonia symptoms and their behavioural proxies in animals. Secondary outcomes will include side effects and neurobiological measures. At least two independent reviewers will conduct the study selection, data extraction, and risk of bias assessments using pre-defined tools according to each record's study design. We will develop ontologies to facilitate study identification and data extraction. We will synthesise data from clinical and animal studies separately. If appropriate, we will use random-effects meta-analyses, or synthesis without meta-analyses. We will investigate study characteristics as potential sources of heterogeneity. We will evaluate the confidence in the evidence for each outcome and source of evidence, considering the summary of the association, potential concerns regarding internal and external validity, and reporting biases. When multiple sources of evidence are available for an outcome, we will draw an overall conclusion in a triangulation meeting involving a multidisciplinary team of experts. We plan updates of the review every 6 months, and any future modifications to the protocol will be documented. We will co-produce this review with multiple stakeholders. CRD42023451821.