Older adults with treatment-resistant depression (TRD) can be treated with augmentation or switched to a different drug.

We aimed to identify factors that moderate the effectiveness of these strategies on treatment outcomes to guide the selection of the optimal strategy for each patient.

We analyzed data from 742 older adults with TRD in the Outcomes of Treatment-Resistant Depression in Older Adults (OPTIMUM) clinical trial. All participants were randomized to one of two treatment strategies, which were augmentation with aripiprazole, bupropion, or lithium; or switching to bupropion or nortriptyline. Treatment outcomes were change in MADRS scores and remission after 10 weeks. Age, burden of comorbid physical illness, number of adequate previous antidepressant trials, presence of executive cognitive impairment, and clinically relevant comorbid anxiety were examined as potential moderators of the effect of the two treatment strategies (augmentation vs. switching) on treatment outcomes.

Overall, augmentation produced more improvement in MADRS scores and produced a higher rate of remission than switching. For change in MADRS scores after 10 weeks of treatment, the number of adequate previous antidepressant trials was the only significant moderator of the superiority of augmentation over switching (b = -1.6, t = -2.1, p = 0.033, 95%CI [-3.0,-0.1]). There were no significant moderators for remission.

Older patients with TRD with less than three previous antidepressant trials benefit more from augmentation than from switching. Future studies validating this finding with different drugs in more diverse samples can facilitate their application in real world settings.

H. Kim Grant / Research support from: Dr. Kim reports grant support from the PSI foundation (R23-21). She is supported by the Canadian Institutes of Health Research (CIHR) and the Temerty Faculty of Medicine (Chisholm Memorial Fellowship)., J. Karp: None Declared, H. Lavretsky Grant / Research support from: Dr. Lavretsky received support from grants (K24 AT009198, R01 AT008383, and R01 MH114981) from the NIH., D. Blumberger Grant / Research support from: Dr. Blumberger reports grants from Canadian Institutes of Health Research (CIHR) and the Temerty family through the Centre for Addiction and Mental Health (CAMH) Foundation during the conduct of the study; nonfinancial support from Magventure (in-kind equipment support for investigator-initiated research); grants from Brainsway (principal investigator of an investigator-initiated study and site principal investigator for sponsored clinical trials), National Institutes of Health (NIH), Brain Canada Foundation, Campbell Family Research Institute, and Patient-Centered Outcomes Research Institute outside the submitted work; received medication supplies for an investigator-initiated trial from Indivior; and has participated in advisory boards for Janssen and Welcony., P. Brown Grant / Research support from: Dr. Brown received additional support from the National Institute of Mental Health OPTIMUM NEURO grant (5R01MH114980)., A. Flint Grant / Research support from: Dr. Flint has received grant support from the US National Institutes of Health, the Patient-Centered Outcomes Research Institute, the Canadian Institutes of Health Research, Brain Canada, the Ontario Brain Institute, and Alzheimer’s Association., E. Lenard: None Declared, P. Miller: None Declared, C. Reynolds Shareolder of: Dr. Reynolds receives payment from the American Association of Geriatric Psychiatry as Editor-in-Chief of the American Journal of Geriatric Psychiatry and royalty income for intellectual property as co-inventor of the Pittsburgh Sleep Quality Index., S. Roose: None Declared, E. Lenze Grant / Research support from: Dr. Lenze received additional support from the Taylor Family Institute for Innovative Psychiatric Research at Washington University School of Medicine, as well as the Washington University Institute of Clinical and Translational Sciences grant (UL1TR002345) from the National Center for Advancing Translational Sciences of the National Institutes of Health (NIH)., B. Mulsant Grant / Research support from: Dr. Mulsant received additional support from the Labatt Family Chair in Biology of Depression in Late-Life Adults at the University of Toronto. He holds and receives support from the Labatt Family Chair in Biology of Depression in Late-Life Adults at the University of Toronto. He currently receives or has received during the past three years research support from Brain Canada, the CAMH Foundation, the Canadian Institutes of Health Research, and the US National Institutes of Health (NIH); Capital Solution Design LLC (software used in a study funded by CAMH Foundation), and HAPPYneuron (software used in a study funded by Brain Canada).

Perinatal depression (PND) is a debilitating mood disorder that occurs during or following pregnancy. Information regarding characteristics associated with PND can aid in better understanding the disease.

Examine patient characteristics and comorbidities of PND patients and matched non-PND controls in a UK electronic health record (EHR) database.

Women aged 12-55y with a delivery record (livebirth, stillbirth, mixed birth) during Jan 2017-Dec 2021 were selected from the Clinical Practice Research Datalink (CPRD) GOLD primary care database via a pregnancy algorithm. PND was ascertained using read codes during pregnancy or one year after the end of pregnancy date (EPD). Two ways to define PND were explored: 1) restricted definition (PND-r) where only PND codes were included; 2) broad definition (PND-b) including both PND and 34 other depression codes. For each PND case, two controls were matched on key patient variables such as age, depression history, and pregnancy outcome. Patients were required to have at least 12 months (mo) of continuous enrollment prior to and post EPD. Patient characteristics and select psychiatric and pregnancy-related comorbidities were compared, and prevalence rate ratios (PRR) and 95% Wald confidence intervals (CI) were calculated comparing cases and controls.

The study included 2,214 cases of PND-r and 4,718 cases of PND-b, and their respective non-PND matched controls. PND-r and PND-b cases differed in timing of diagnosis. Of the PND-r cases, 6% were diagnosed during pregnancy and 47% in the first 3mo following delivery; whereas the distribution in the PND-b was, respectively, 18% and 30%. The mean age of the PND-r and PND-b cohorts was consistent (29y, SD=6). A prior recorded history of depression was present in 36% of PND-r cases and 43% of PND-b cases. Approximately 55% of PND-r cases and 65% of PND-b cases had a history of antidepressant use prior to last menstrual period.

During the 12mo pre-EPD, PND-r cases had higher prevalence of hyperemesis gravidarum (PRR=1.5, 95% CI 1.3-1.8), gestational diabetes (PRR=1.4, 95% CI 1.1-1.7), and anxiety/panic disorders (PRR=1.8, 95% CI 1.3-2.3) compared to controls. During the 12mo post-EPD, PND-r cases had higher prevalence of comorbid anxiety/panic disorders (PRR=3.8, 95% CI 3.0-4.9) as well as post-traumatic stress disorder (PRR=3.1, 95% CI 1.5-6.1) compared to controls. Results were similar in the PPD-b analyses, but with higher PRR of anxiety/panic disorders (post-EPD PRR: 11.2, 95% CI 9.7-12.9).

80% of PND-r and 71% of PND-b cases were diagnosed during pregnancy or in the first 6mo following EPD. Cases had higher prevalence of certain pregnancy and psychiatric conditions compared to controls, with comorbid anxiety/panic disorder estimates higher using the PND-b definition. Future research should consider comparing results using both broad and restricted definitions of PND in EHRs.

C. Gillis Shareolder of: Biogen, Employee of: Biogen, S. Chen Shareolder of: Biogen, Employee of: Biogen, C. Mak Shareolder of: Biogen, Employee of: Biogen, E. Tworkoski Shareolder of: Biogen, Employee of: Biogen, L. Li Shareolder of: Biogen, Employee of: Biogen, S. Eaton Shareolder of: Biogen, Employee of: Biogen, C. Green Shareolder of: Biogen, Employee of: Biogen, N. Maserejian Shareolder of: Biogen, Employee of: Biogen, M. Koch Shareolder of: Biogen, Employee of: Biogen.

Research shows a strong correlation between depression and memory disorders, suggesting the potential for cross-questionnaire data use in automated diagnostic systems. This study explores whether the Prospective and Retrospective Memory Questionnaire (PRMQ) can identify depressive symptoms and if the ZUNG Self-Rating Depression Scale (SDS) can predict memory-related disorders.

To evaluate the effectiveness of using questionnaires intended for one mental disorder to diagnose another through machine learning models on data from a large-scale self-assessment online questionaire.

The study is part of the Memory and Depression Study: MANDY, conducted by the 1st Department of Psychiatry and the Department of Neurology of Papageorgiou Hospital, Thessaloniki, Greece. Data from 3340 participants were collected via an online survey containing the PRMQ, SDS, demographic data, and health-related questions. Four predictive tasks were designed: two for predicting depression using memory responses (D-from-M score and class) and two for predicting memory disorders using depression responses (M-from-D score and class). Machine learning models including LightGBM, AdaBoost, Support Vector Machines, and Logistic Regression were evaluated. Performance metrics included precision, recall, F1-score, and AUC-ROC (Figure 1).

The LightGBM classifier was the top-performing model for the D-from-M class prediction task, achieving a precision of 0.75563, recall of 0.79125, an F1-score of 0.77303, and an AUC-ROC of 0.79319 on the test set (Table 1). This indicates a strong predictive capability for diagnosing depression from memory-related responses. The AdaBoost classifier had similar performance but was slightly inferior to LightGBM. For the M-from-D class task, the class imbalance (memory disorder prevalence at 5%) was a significant challenge. The best model, a Support Vector Classifier with ADASYN resampling, achieved a precision of 0.6, recall of 0.375, an F1-score of 0.46154, and an AUC-ROC of 0.86218. However, its performance was notably lower than LightGBM in predicting depression.

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The PRMQ, combined with specific demographic and health-related questions, showed promise in predicting depression, with the LightGBM classifier as the best overall model. This underscores the potential for cross-questionnaire data utilization for diagnosing depression. Conversely, predicting memory disorders using the SDS was less effective, indicating the need for more targeted diagnostic tools. Future research should include neurocognitive and biomarker data to enhance diagnostic accuracy for memory-related conditions.

None Declared

Smartphones, central to modern life, offer a cost-effective tool for gaining patient insights outside the consultation room. Through passive data collection (e.g., sensor data) and active questioning, smartphones enable ecological assessments of psychiatric symptoms and self-reported experiences. This “moment-by-moment quantification of the individual-level human phenotype in situ using data from personal digital devices” via digital phenotyping (DP) has garnered significant research attention, showing potential for early detection and intervention in mental health.

We explore recent DP developments in mental health, highlighting its potential to transform clinical practice while acknowledging challenges and risks.

Narrative literature review resorting to PubMed and Google Scholar using keywords such as “digital phenotyping”, “digital phenotype”, “digital biomarker” and “mobile sensing”.

DP studies, particularly in Mood Disorders and Schizophrenia, mostly rely machine learning for data analysis. Biomarkers from passive data (e.g., GPS, social connectivity, physical activity) correlate with self-reports and clinical measures of depression, anxiety, mania, and psychosis. Speech and text analysis through Natural Language Processing (NLP) offers new research avenues. DP promises early detection, relapse prevention, and treatment monitoring but faces challenges, including privacy concerns, and low user engagement - that could be solved by closing the loop by returning individual research results or a tailor-made intervention. Nevertheless, regulation and good practice standards are still lacking, posing the threat of diagnostic inaccuracy and undeniable iatrogenic risk.

For DP to fully realize its potential, integration with standard care and existing systems is essential. While risks exist, when comparing DP with other medical interventions currently under research, perils are minor. Mental health care urgently needs disruptive innovation to improve access and quality.

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In the present era, technology and medicine have become deeply intertwined, forming inseparable scientific disciplines. The mobile phone has become an omnipresent device, serving functions such as financial management, job organization, social networking, and internet access. While its benefits are undeniable, there is growing evidence of its potential pathological effects. One of the most recently identified issues is nomophobia—a term combining “no mobile,” “phone,” and “phobia,” which refers to the fear or anxiety of being without one’s mobile phone.

Nomophobia is considered a situational phobia of the contemporary era. Its symptoms include excessive reliance on mobile phones and pervasive anxiety about losing internet connectivity. Related conditions include “Ringxiety” and “phantom vibration syndrome,” where individuals perceive false notifications from their devices.

This study aims to assess the relationship between eating disorders (ED) and nomophobia. Additionally, it seeks to analyze the psychopathological components of nomophobia and evaluate the characteristics of the Nomophobia Questionnaire (NMP-Q), currently used for its assessment.

A questionnaire was administered at the Study and Care Unit for ED in Bologna, Italy, between January 2023 and May 2024. Alongside tests evaluating the social and psychopathological characteristics of the outpatients (including the STAI-Y for anxiety assessment), the Italian version of the NMP-Q was employed.

The study included 104 patients (97 females and 7 males) with an average age of 21.8 years (range 18-44). The results showed that 100% of the subjects exhibited symptoms of nomophobia, with 21.3% displaying severe nomophobia. Among these, 94.4% tested positive for state anxiety, and 100% for clinically significant trait anxiety. This suggests that nomophobia may reflect not only current anxiety symptoms but also an anxious trait, indicating a predisposition to heightened reactivity and anxiety in response to environmental stimuli.

The data highlight the alarming pervasiveness of internet addiction in contemporary society, with nomophobia being a significant manifestation. Given its substantial consequences, it is crucial to deepen our understanding of this condition and its underlying psychosocial determinants. This will enhance our knowledge and aid in developing more effective prevention strategies. However, a paradox arises: if nearly everyone is affected by nomophobia, it challenges the traditional definition of a disease. Further research into the NMP-Q test’s structure and specificity is necessary, as high prevalence rates may question its current measurement validity.

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Many patients with mental health and emotional problems often see the transition period in the community after hospital discharge as a test of their resilience and a threat to their recovery. Most often, some doubt their ability to cope with the everyday challenges that may confront them in the community.

This paper assesses how demographic and clinical characteristics predicted resilience, personal recovery and quality of life.

Data were collected from psychiatric inpatients prior to their discharge into the community using the REDCap, an online survey platform. Resilience, personal recovery, and quality of life were assessed using the Brief Resilience Scale (BRS), Recovery Assessment Scale (RAS), and EQ-Visual Analogue Scale (EQ-VAS), respectively. One-way analysis of covariance between groups (ANCOVA) was conducted to compare the relationships between groups. The dependent variables comprised mean scores of BRS, RAS and EQ-VAS. Demographic and clinical variables such as age, gender, ethnicity, and mental health diagnosis groups were independent variables, and covariates comprised demographic/clinical factors such as gender, ethnicity, and mental health diagnosis

The survey results indicate that males had significantly higher resilience scores compared to females ( Mdiff = 0.270, CI= 0.144– 0.397, p=.<.001) and others (Mdiff =0.470, 0.093- 0.846, p=<.001); Black people indicated significantly higher quality of life than Caucasians (Mdiff = 8.79, 2.73- 14.85, P= <.001), and Indigenous people (Mdiff = 14.50, 6.45 - 22.51, p=<.001), respectively. In terms of relative recovery, participants with depression had significantly lower recovery compared to those with bipolar disorder (Mdiff = -10.25, -14.40- -6.10, p=<.001), schizophrenia (Mdiff f = -8.60, -13.20- -3.99, p=<.001), and substance use disorder (Mdiff = -8.30, -15.50- -1.42, p=<.005).

The present results indicate that women, younger adults, and Indigenous peoples may be more challenged in adapting to the challenges of post-discharge life in the community. Our data may be helpful in communicating to policymakers and providers of funds the need to implement and evaluate outcomes of inpatient and community programs focusing on supporting resilience to improve recovery outcomes after discharge from the patient setting.

None Declared

The COVID-19 pandemic prompted a significant shift in our approach to healthcare, leading to the widespread adoption of virtual healthcare services, including mental healthcare. In this context, understanding and incorporating the unique perspectives of youths is crucial for improving virtual mental health services for this population.

This qualitative study explores the ideal features of virtual mental health services among youths.

Nine focus group discussions and eight semi-structured interviews were conducted with 65 individuals aged 15-35 in Singapore. To ensure the comprehensive representation of youths’ perspectives, participants from diverse ethnicities (mainly Chinese, Malay, and Indian), ages, and genders were included using purposive sampling. The data was analysed using content analysis through both inductive and deductive approaches.

Four main themes were identified from the data. First, technology and platform: youths stressed the importance of a credible and government-endorsed service provider to deliver a comprehensive and trustworthy experience facilitated by qualified professionals. Second, functionality: they wanted credible affiliations to be displayed prominently on the home page and various tools such as calls, chats, moderated forums, profiles of healthcare professionals, and educational resources. Confidentiality, anonymity, and privacy were also highlighted as necessary. Third, user interface: youths preferred an intuitive and age-tailored interface to ensure a seamless and user-friendly experience, with organised content, appealing aesthetics, and engaging elements on video call sessions. Fourth, usability: they emphasised the need for an affordable and widely compatible operating system to promote accessibility of services.

Virtual mental health services, with their great potential, can expand and effectively meet the needs of youths. By prioritizing credible platforms, comprehensive functionality, confidentiality, an intuitive interface, and broad accessibility, we can enhance help-seeking among youths and create a more effective support system.

None Declared

In the post-migration period, individuals from diverse religious, linguistic, cultural, and traditional backgrounds strive to coexist in a shared social space. However, numerous adaptation challenges arise during this process. Additionally, individual personality traits significantly influence experiences during this time. For those suffering from psychiatric disorders, the integration process becomes even more complex, as these conditions can diminish an individual’s ability to cope with stress, making societal integration more difficult. This study aims to examine the level of integration among individuals with psychiatric disorders who have faced challenges after migration, with the goal of contributing to initiatives that facilitate their adaptation process.

This study aims to assess the integration levels of individuals with psychiatric disorders into society. In addition to examining psychiatric conditions, sociodemographic data will also be collected from participants to explore how additional factors influence the integration process. By doing so, the study seeks to provide insights that can inform efforts to facilitate the integration of these individuals into society.

Data were collected from 91 participants, primarily first- and second-generation Turkish immigrants with at least one psychiatric disorder, at the Neuro Psychiatric Center Riem (NPZR) clinic. The study employed the “Community Integration Scale for Adults with Psychiatric Disorders” along with a sociodemographic questionnaire, with informed consent obtained from all participants. SPSS analysis software was utilized to examine the relationship between integration levels and other relevant variables.

Statistical analyses indicate that variables such as age, education level, smoking, and drug use significantly affect the total score.

These findings reveal that individuals’ demographic and behavioral characteristics play a significant role in overall performance and achievement measures.

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Diabetes burnout refers to the physical and emotional fatigue resulting from the challenges of living with and managing diabetes. It is a prevalent issue that significantly affects diabetes care. Unfortunately, it often receives less attention and is frequently underestimated.

This study examined the prevalence and predictors of burnout, diabetes distress and depression in adults with diabetes mellitus.

In this cross-sectional study, investigated the Turkish validity and reliability of the Diabetes Burnout Scale and determined prevalence and predictors burnout, diabetes stress, and depression among adults with DM. The study sample consisted of 315 adults and a Personal Information Form, the Diabetes Burnout Scale, the Diabetes Distress Scale, and the Patient Health Questionnaire-8 were administered. Data analysis involved descriptive tests, Pearson correlation analysis, and the use of SPSS (v.29).

As a result of confirmatory factor analysis, it was determined that the Turkish version of the Diabetes Burnout Scale had 3 sub-dimensions and consisted of 12 items. The Cronbach alpha reliability coefficient of the total scale was found to be 0.814. Participants had a mean (±SD) age of 48.63 (±8.23) years, with a majority (54.6%) being male and (±93.7%) diagnosed with type 2 diabetes mellitus. The median duration of diabetes among them was 4.41 (±2.48) years, and their median HbA1c level was 8.99 (±0.68). The prevalence rates for burnout, diabetes distress, and depression were found as 2.69 (±0.28), 4.64 (±0.40), and 15.20 (±3.88), respectively. Additionally, the total burnout score showed a positive correlation with both the diabetes distress score (r = 0.556, p = 0.033) and depression (r = 0.325, p = 0.027).

The study revealed a high prevalence of burnout, distress, and depression, highlighting the need for a prevention strategy. Monitoring high-risk groups for pre-diabetes and diabetes is crucial for informing health programs and resource distribution to manage the condition effectively.

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Patients following traumatic injury (TI) are at increased risk of developing dementias, yet an efficient, validated screening instrument is lacking.

In the current study, we developed the Dementias following Traumatic Injury Screening (DEMTIS) score, a brief post-TI dementias screening tool.

We identified 270,843 electronic health records from Hong Kong patients admitted for TI between 2001 and 2021. The records were randomly split into training (80%; n=258,739) and testing cohort (20%; n=50,883). The DEMTIS was developed based on a backward stepwise multivariate Cox proportional hazard model predicting first-ever dementia diagnosis. Competing risk survival analyses were used to predict the risk of Alzheimer’s disease (AD) and vascular dementia (VD), while taking the risk of other dementias into account. Model discrimination of the three scores was evaluated using concordance statistics (c-statistic) calculated as the area under the receiver operating characteristic curve. Statistical significance was set at p<.01.

The 5-year, 10-year, and 20-year risk of all-cause dementias following TI was 2.1% (95% CI 0.020-0.021), 3.8% (95% CI 0.037-0.039), and 6.5% (95% CI 0.063-0.066), respectively. The final model included sex, TI characteristics, physical covariates, history of mood and anxiety disorders, and cerebral degenerative disease (See Table 1). The population mean of DEMTIS was 59.45 (SD=21.29). The optimal threshold of DEMTIS predicting dementia was determined at 75 using the closest top left rule. Individuals at high risk (DEMTIS≥75) were associated with a 6.0% (95% CI 0.059-0.061) risk of dementia in 5 years, whereas those at low risk were associated with a 0.5% (95%CI 0.004-0.005) risk (see Figure 1; Figure 2). The model predicting 5-year dementia has an overall c-statistic of 0.835 (95% CI 0.832-0.839) in the testing data (see Figure 3). We further developed risk scores for 5-year AD and VD based on the findings from competing risk models; the c-statistics of model for AD and VD are 0.857 (95% CI 0.844-0.871) and 0.837 (95%CI 0.821-0.853) respectively.Table 1:

Calculation of the DEMTIS

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As a novel, easily accessible screening instrument, DEMTIS can identify patients at elevated risk of dementia following TI. It assists clinicians in evaluating patients’ risk of dementia and providing personalized care.

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The admission of a patient to the Intensive Care Unit (ICU) often triggers intense stress symptoms in their family members, leading to anxiety, depression, and emotional distress.

To investigate the coping mechanisms employed by family members of critically ill patients, considering their sociodemographic characteristics and the closeness of their relationship to the patient.

The study included first-degree relatives, close relatives, and intimate friends of ICU patients. Data were collected through written questionnaires completed by family members who visited patients during the first week of treatment. A sociodemographic questionnaire and the Family Crisis Oriented Personal Evaluation (F-COPES) scale were used to assess coping strategies.

A total of 223 family members, with a mean age of 41.5 ± 11.9 years, participated in the study. This sample represented 147 critically ill patients. Of the participants, 81 (36.3%) were men and 142 (63.7%) were women. The majority were the patients’ children (40.8%), siblings (19.3%), or companions (16.1%). The most frequently employed coping strategies were seeking social support (mean score 31.27 ± 4.72), mobilizing the family for help (mean score 14.26 ± 3.17), and adopting a passive approach (mean score 14.04 ± 2.81). Offspring and male relatives were less effective in using coping strategies compared to other relatives and female participants, respectively.

Family members of critically ill patients are psychologically vulnerable, experiencing significant emotional distress. They often rely on external support to cope with the family crisis. Health professionals should prioritize understanding and addressing the specific needs of these relatives to provide appropriate support.

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Emergency departments (ED) and intensive care units (ICU) are high-stress environments where healthcare professionals are continuously exposed to critical situations. This results in substantial mental health burdens, leading to increased levels of depression, anxiety, stress, and burnout. These issues negatively affect both the well-being of professionals and patient care.

This study aims to evaluate the prevalence and severity of depression, anxiety, stress, and burnout among ED and ICU professionals. The goal is to understand mental health issues and identify contributing factors to improve prevention and support systems.

A total of 242 healthcare professionals from Bezmialem Vakif University Hospital were included: 120 ICU staff (80 females, 40 males), 66 ED personnel (42 females, 24 males), and 56 office personnel (38 females, 18 males) serving as a control group. The study employed validated instruments: the Beck Depression Inventory, the Beck Anxiety Inventory, Perceived Stress Scale, and Maslach Burnout Inventory. Non-parametric tests (Kruskal-Wallis H and Chi-Square) were used due to non-normal data distribution, with pairwise comparisons adjusted using Bonferroni correction. The significance level was set at p < 0.05.

The results showed significant differences in age, depression scores, stress levels, and burnout indicators between the ICU, ED, and control groups. ICU and ED staff reported significantly higher depression scores compared to the control group (p < 0.001). Stress levels were also significantly elevated in ICU workers compared to office personnel (p = 0.001). Burnout indicators were notably higher in ICU professionals (p = 0.011). Conversely, no significant differences were observed in anxiety scores, emotional exhaustion, and hours of sleep.Table 1:

Summary of Key Results

The findings underscore the necessity for targeted interventions to reduce psychological distress among ED and ICU professionals. Implementing support systems, promoting work-life balance, and improving mental health resources can significantly alleviate the mental burden on these professionals, thereby enhancing both their well-being and patient care quality.

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As of January 1, 2020, the new Dutch Mental Health Compulsory Care Act (WVGGZ) came into effect, replacing the Special Admissions to Psychiatric Hospitals Act (Wet BOPZ).

One of the expectations of the WVGGZ was that earlier (medication-based) involuntary intervention in outpatient settings would lead to fewer or shorter hospital admissions. The most important change was the outpatient use of involuntary medication, which was not allowed before the law.

Data from the Argus rating scale (Noorthoorn et al, 2016) and its successor, the compulsory care registration were combined with background data on admissions and wards. For this study, patients with a court order (RM) in 2016 and 2017 and a cumpulsory care authorization (ZM) in 2022 and 2023 were selected.

In 2016 and 2017, 549 patients received an RM, and 958 RM’s were issued. In 2022 and 2023, there were 405 patients, and 546 ZM’s were implemented. The total number of admission days for these patients before the law was 78,183 compared to 76,099 after the law. The average length of stay increased from 81 days per patient to 140 days per patient (t=-8.93, p<0.001). Seclusion decreased from 45,893 hours to 2,985 hours (t=4.93, p<0.001). Intramuscular (IM) medication was administered 137 times before the law and 369 times in clinical settings after the law (2022-2023) (chi-square= 325.10, p<0.001). IM medication was administered 777 times in outpatient settings.

Contrary to expectations, the legislative change did not result in shorter admissions for patients with a ZM. The data indicate significant differences in involuntary treatment for patients before and after the legal change. The presentation will explore possible factors influencing these figures.

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Research indicates that for psychiatric services to be generally effective, individuals have to complete the treatment. Although treatment completion does not necessarily equate to treatment success, it has been found to consistently lead to improved outcomes including improved rates of recovery and reduced risk of involvement with the justice system and other adverse outcomes. Treatment non-completion, on the other hand, has been associated with a higher risk of readmissions for inpatient care, legal, and other health-related problems (Dreyer et al. S Afr J Psychiatr 2020; 26 a1255). These findings underscore the importance of examining factors associated with treatment completion.

The goal of the study was to identify predictors for treatment completion among individuals receiving psychiatric services from state-administered behavioral health systems in Indiana, USA. Three domains of predictors were examined, including sociodemographic characteristics, comorbid conditions, and the type of treatment patients received.

Statewide records from merged administrative data sets were used for this analysis. Multivariate logistic regression was conducted using a sample of 15,412 adults receiving behavioral health services in fiscal year 2020.

Among demographic characteristics only race was associated with treatment completion. Individuals who were non-Hispanic White were 20% more likely to complete their treatment compared to their minority (e.g., Black, Hispanic) counterparts (p < .05, OR = 1.20). Having more than one mental health disorder was associated with 16% decreased odds of completing treatment (p < .05, OR = 0.87). Individuals who were institutionalized for psychiatric conditions had 26% decreased odds of completing the treatment (p < .05, OR = 0.80), but those who received inpatient substance abuse related care were over four times more likely to complete their treatment (p < .05, OR = 4.61). Finally, individuals who attended any self-help groups had 63% greater odds of completing the treatment.

Findings suggest that individuals who simultaneously received substance abuse and mental health treatment had the greatest chances to complete treatment successfully. Study implications also suggest that self-help or support groups should be promoted as ways to motivate patients to adhere to treatment.

None Declared

Schizophrenia and bipolar disorder are severe psychiatric disorders influenced by genetic and environmental factors, sharing clinical features, risk factors, and genetic predispositions. Cognitive impairment is a central aspect of both disorders, affecting various domains like memory, attention and executive function. Distinguishing disorder-specific cognitive impairments from those shared across psychoses is challenging. Research on Clinical High Risk (CHR) and Familial High Risk (FHR) populations is vital for identifying cognitive impairments related to vulnerability. CHR populations exhibit cognitive changes, but the evidence on FHR populations remains less clear, even though offspring of individuals with severe mental disorders face a high risk of developing these conditions.

This study aims to perform a meta-analysis of neurocognitive functioning in offspring of individuals with affective psychoes and non-affective psychoses, compared to healthy controls (HC-Off). This meta-analysis seeks to improve statistical power of individual studies and offer more reliable estimates of cognitive deficits related to genetic vulnerability to psychotic disorders.

Following PRISMA, MOOSE, and EQUATOR guidelines, a systematic literature search was conducted up to December 12th 2023. Articles were screened, and those relevant were assessed for eligibility. The inclusion criteria focused on original studies comparing neurocognitive performance between offspring of individuals with affective or non-affective psychoses and healthy controls. The primary outcome was the difference in performance across neurocognitive domains. Meta-analyses were conducted on the overall sample and separately for affective and non-affective offspring, using a random-effects model.

Within the analyzed domains, individuals with affected parents performed significantly worse in every domain in comparison with control group, except in Motor Functioning domain. When studied separatley, offspring of parents with affective psychosis showed significant cognitive impairments in visual and verbal learning, processing speed, and memory, with smaller deficits in other domains. In contrast, offspring of parents with non-affective psychosis exhibited more severe impairments. Social cognition and motor functioning were less affected in both groups.

Key deficits in learning, memory, and general intelligence highlight the potential for these cognitive domains to serve as markers of vulnerability to psychosis. While both groups of offsrping show impairments, the more pronounced deficits in the non-affective group indicate a distinct cognitive risk profile. These insights may inform early interventions tailored to the specific cognitive challenges faced by high-risk populations.

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Accumulating evidence supports the mental health benefits of self-compassion. However, longitudinal research unravelling how self-compassion affects mental health outcomes is scarce.

This study aimed to clarify whether mindsets of negative emotions serve as a mechanism of how self-compassion exerts impacts on youth mental health.

The longitudinal school-based survey was conducted annually across three years among 719 secondary school students (mean age: 14.65, SD: 0.72). Mediation models were examined with self-compassion at T1 as the independent variable, negative emotion mindsets at T2 as the mediator variable, and depression, anxiety, and life satisfaction at T3 as the dependent variables. Alternative mediation models with negative emotion mindsets at T1 as the independent variable and self-compassion at T2 as the mediator variable were also tested to corroborate the hypothesized direction of the mediation effects. The mediation models all controlled for age, sex, socioeconomic status (SES), and respective measurements of mediator and dependent variables at baseline.

Negative emotion mindsets at T2 significantly and fully mediated the effects of self-compassion at T1 on mental health (indexed by depression, anxiety, and life satisfaction levels) at T3 (see Fig. 1, Fig. 2, and Fig. 3, respectively). The alternative mediation models were all insignificant, corroborating that negative emotion mindsets serve as the pathway through which self-compassion impacts mental health, rather than the reverse.

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This study highlights the belief-in-change of negative emotions as a key mechanism underlying the impact of self-compassion, and has important implications for research and interventions aimed at promoting youth mental health.

None Declared

Mental health reform represents one of the most transformative changes in the field of healthcare, as it not only changes the forms of services, but also the nature of services offered. While many countries have successfully implemented such reforms, others, including Georgia, have struggled with a protracted and inconsistent process. Despite decades of advocacy by professionals for deinstitutionalization psychiatric hospital treatment continues to dominate in Georgia’s mental healthcare system.

The purpose of the review is to explore the concept of deinstitutionalization within the mental health landscape and assess its status in the context of Georgia. It aims to study the lessons learned from successful deinstitutionalization and illuminate achievements and challenges surrounding deinstitutionalization in Georgia’s reality.

A qualitative analysis including desk review, in-depth interviews and focus group discussions was conducted. Proceeding from the research objectives we analyzed the existing legislation, strategic documents and clinical practices concerning individuals with mental disorders; Interviews were also conducted with key informants on the shortcomings and problems in deinstitutionalization practices

The review findings reveal, that despite recent progress such as the development of community mobile teams and increased funding allocated for community services within mental health budget, a number of issues still remain a problem: there is no agreement among stakeholders on how to restructure existing hospital beds and financial provisions remains unresolved. The field of mental health in Georgia suffers from a lack of human resources. Attracting new personnel, ensuring regional distribution, and enhancing qualifications are necessary components of deinstitutionalization that require the involvement of all stakeholders, coordinated and time-planned action. The current mental healthcare system in Georgia is characterized by a lack of coordination and collaboration among its various components. Establishing patient care pathways between services with clear referral criteria is crucial for improving the efficiency of mental health services.

This research highlights that successful deinstitutionalization requires additional funds, time, and trained people. Institutions should have a long-term (3-5) year development plan, detailing the source of funding, activities to be implemented, and expected outcomes. In the absence of such a plan, progress remains sporadic, intermittent, uncoordinated, and less effective.

By addressing identified challenges and promoting coordination among mental health components, Georgia can guide a more effective course toward a community-based, patient-centered mental healthcare system.

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Myoclonus-dystonia syndrome (MDS) is a rare childhood-onset movement disorder characterized by the combination of myoclonus and dystonia. It is caused by loss of function of the epsilon-sarcoglycan gene (SGCE) due to mutations, although the pathogenic mechanism is not fully understood. Deep brain stimulation is used in patients that are refractory to pharmacological treatment. A higher prevalence of psychiatric disorders has been observed in MDS patients, especially obsessive-compulsive disorder (OCD) (Timmers et al. Parkinsonism Relat Disord. 2019; 69 85-90). A dysfunction of cortico-basal ganglia-thalamo-cortical (CBGTC) loops is present in both conditions, but the mechanism by which they display high comorbidity is unknown.

To determine the presence of OCD comorbidity in pediatric and young adult patients that are candidates for DBS treatment for motor disorders, and the effects that the treatment may have on OCD symptoms.

This study is part of an ongoing cohort (n = 34) of children and adolescents (at the time of diagnosis) receiving internal globus pallidus DBS as treatment for motor disorders in Vall d’Hebron Hospital. The candidates go through a psychiatric evaluation before the procedure, including the diagnostic interview K-SADS, to diagnose psychiatric comorbidity. Long-term evaluation is performed by subsequent visits to the specialist.

Of the seven patients with SGCE+ MDS that underwent DBS treatment, four of them presented OCD symptoms before the procedure, two did not, and one did not receive an evaluation. Of the patients with OCD symptoms, all four of them showed significant improvement in motor function after DBS but had worsening of OCD symptoms. Some of the patients also had a worsening of other psychiatric symptoms, such as anxiety, mood and behavioral symptoms.

OCD symptoms are present in a significant proportion of our patients with SGCE+ MDS. OCD and other psychiatric symptoms worsened during follow-up in our patients, although it is not clear if this is due to DBS treatment or due to the natural course of the disorder. Further studies are needed to explore this observation.

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Binge-eating disorder (BED) is a significant global health challenge associated with obesity and psychological issues. The combination of Naltrexone-Bupropion (NB) has emerged as a promising pharmacological approach for managing eating behaviors.

This meta-analysis aims to evaluate the efficacy and safety of Naltrexone-Bupropion compared to placebo in managing eating behaviors, focusing on weight loss, binge-eating frequency, eating disorder psychopathology, quality of life, and adverse effects.

PubMed, Embase and Cochrane databases were searched for randomized controlled trials (RCT) comparing NB versus placebo for BED. Primary endpoints were weight loss and binge-eating frequency. Secondary endpoints included eating disorder psychopathology, depression, quality of life, food cravings, and adverse effects.The mean differences (MD) were applied with their 95% confidence intervals (95%CIs) for continuous outcomes, using a random-effects model. We used RevMan 5.4.1 for statistical analyses. Heterogeneity was assessed using the I² statistic.

Five RCTs with 2,466 adult participants (mean age 46.5 years, BMI 21.5-50 kg/m²) were included. NB was associated with a statistically significant reduction in weight loss percentage compared to placebo (MD -3.67%, 95% CI [-4.30; -3.03], I²=98%; Figure 1). However, no significant differences were found between NB and placebo in reducing binge-eating episodes(SMD 0.02, 95% CI [-0.30; 0.34], I2 =0%, Figure 2) , improving eating disorder psychopathology, alleviating depression, or decreasing food cravings. Although NB showed some benefits in improving the quality of life, the results were not statistically significant. NB was associated with a higher risk of adverse effects, including nausea, headache, constipation, dizziness, vomiting, insomnia, and dry mouth. The certainty of the evidences is in the Summary of findings (SOF) of GRADE evaluation (Figure 3). After leave-one-out sensitivity analysis, no single study was found to influence the effect estimate or drive heterogeneity excessively.

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NB demonstrated efficacy for weight loss in individuals with eating behavior issues but showed no significant benefits for core eating disorder symptoms. The higher risk of adverse effects necessitates careful consideration in clinical decision-making. Further research is needed to determine optimal patient populations, treatment duration, and strategies to mitigate adverse effects.

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Eating disorders are a group of mental illnesses determining general health consequences. Several studies suggest that social media influence body image concerns, considered the core of eating disorder pathology. Thin idealization has become an increasing cultural focus, leading young people to pursue body image as a symbol of success.

Aim of this study is to assess the quality and quantity of Social Network (SN) use and their influence on body uneasiness in individuals with Disordered Eating Behaviours (DEB) or Eating Disorders(ED)

69 individuals suffering from Disordered Eating Behaviours (Grazing, Sweeteating, Food Addiction) or Eating Disorders (Night Eating Syndrome, Anorexia nervosa, Bulimia nervosa or Binge eating disorder) were enrolled. Mean age was 34 (SD ±11,33), mean BMI 28,68 (SD ±12,23). 93% of individuals were females. 20,29% (14) of the sample suffered from ED and 79,71% (55) from DEB. A social network self-administered questionnaire was used to investigate which SN was most used and what contents were most shown in users’ feed; domains investigated by the questionnaire are reported in fig. 1

Questionnaire analysis allowed to investigate individuals preferences about social media use and the kind of contents they consumed the most. The data showed the most frequently used social network are Facebook (42%), Instagram (33%) and Tiktok (22%). Healthy and/or fit contents were frequently displayed on SN feed 57.9% (40), but only 26,08% (18) of users were influenced in their lifestyle and food habits. 39,13% (27) of the individuals also felt like this kind of contents increased their sense of body uneasiness.

The study emphasize that 42,85% of the individuals diagnosed with an ED answered that SN content influenced their lifestyle and 71,42% that it increased their feeling of body uneasiness. In individuals with DEB only 21,8% were influenced in their lifestyle and 30,9% describe a worsening of their body uneasiness, as is shown in Tab.1.Tab 1

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Social media contents about health, diet and sport impact on individuals body image, diet and body uneasiness, mostly in individuals diagnosed with ED. This evidence stresses the importance to take into account every component of ED and DEB for a global approach to individuals including an assessment on interests, hobbies and use of social media.

None Declared