Adolescents with depression have distinct affective reactions to daily events, but current research is controversial. The emotional context insensitivity theory suggests blunted reactivity in depression, whereas the hypotheses of negative potentiation and mood brightening effect suggest otherwise. While nonlinear associations between depression severity and affective reactivity have been observed, studies with a separate subclinical group remain rare. Subthreshold depression (SD), defined by two to four symptoms lasting for two weeks or more, provides a dimensional view to the underpinnings of affective reactivity. In this study, we compared positive affect (PA) and negative affect (NA) reactivity to positive and negative daily events (uplifts and stress) among adolescents with Major Depressive Disorder (MDD), SD and healthy controls (HC) using experience sampling methods (ESM).

We hypothesized a stepped difference in affective reactivity along the depression spectrum: the MDD group will have the strongest reactivity of PA and NA to uplifts and stress, followed by SD and HC.

Three groups (MDD, SD, and HC) of adolescents were recruited from an epidemiologic sample entitled ‘Hong Kong Child and Adolescent Psychiatric Epidemiologic Survey: Age 6 to 17’. Group status was determined by the Diagnostic Interview Schedule for Children Version 5. They completed an experience sampling diary on smartphone for 14 consecutive days, with 5-10 entries per day. Momentary levels of PA (happy, relaxed, contented), NA (irritated, low, nervous), uplifts and stress experienced before the entry were measured on a 1-7 Likert scale.

The sample consisted of 19 adolescents with MDD, 30 with SD, and 59 HC. The M:F ratio was 17:19. The age range was 12-18 with a mean of 14.8. The overall ESM completion rate was 46%. The MDD group had the highest levels of stress and NA, and the lowest levels of uplifts and PA, followed by the SD and HC groups respectively (p<0.01). Across groups, levels of PA were positively associated with uplifts and negatively associated with stress, whereas levels of NA were positively associated with stress and negatively associated with uplifts. The Group x Uplift interaction effect on PA was significant, with greater PA reactivity in SD (p<0.01) and MDD (p=0.07) when compared with HC. The Group x Uplift interaction effect on NA was significant, with greater NA reactivity in SD than HC (p<0.01). The Group x Stress interaction effect on PA was significant, with greater PA reactivity in SD than HC (p<0.01) and MDD (p<0.01). The Group x Stress interaction effect with NA is non-significant.

Contrary to our hypothesis, adolescents with SD experienced strongest PA and NA reactivity in uplifts and PA reactivity in stress. It provides evidence towards a nonlinear relationship between severity of depression and affective reactivity.

None Declared

In response to the Omicron surge in early 2022, the HTA Philippines evaluated the acceptability of Filipinos in using self-administered antigen tests (SAAgTs) as part of COVID-19 HTAs in the Philippines.

Scoping review from literature databases was initially conducted to identify preset codes in the use of SAAgT. Preset codes were used to establish the questions for focus group discussions (FGDs). Semi-structured questionnaires were created through Delphi technique. FGDs with four stakeholder groups (i.e., nine healthcare workers [HCWs], seven representatives of at-risk groups, six economic frontliners, and seven representatives of micro–small–medium-sized enterprises) were conducted.

Discomfort in being a target of stigma and being prescribed an “illness identity” when suspected or confirmed COVID-19-positive, along with lack of confidence to perform self-test, caused hesitancy in self-testing among participants. The need for subsidies for test kits from the government or employers was emphasized to increase its accessibility. Having a designated access point and reporting system for SAAgT was highlighted to avoid nepotism (padrino system attributed to debt of gratitude), inequitable distribution, and lapses in reporting. A participatory approach to education was perceived as crucial to reduce any misconceptions associated with the use of SAAgT.

All FGD groups expressed favorable reviews on the implementation of SAAgT because it can potentially reduce the burden of health facility-administered tests. These findings were considered by the HTA Council in the recommendation of SAAgT as part of the overarching national strategies for the diagnosis and screening of COVID-19.

Machine learning studies of PTSD show promise for identifying neurobiological signatures of this disorder, but studies to date have largely excluded Black American women, who experience disproportionately greater trauma and have relatively higher rates of PTSD. PTSD is characterized by four symptom clusters: trauma reexperiencing, trauma avoidance, hyperarousal, and anhedonia. A prior machine learning study reported successful PTSD symptom cluster severity prediction using functional MRI data but did not examine white matter predictors. White matter microstructural integrity has been related to PTSD presence and symptoms, and unexplored metrics such as estimates of tract shape may provide unique predictive utility. Therefore, this study examines the relationship between white matter tract shape and PTSD symptom cluster severity amongst trauma-exposed Black American women using multiple machine learning models.

Participants included 45 Black American women with PTSD (Mage=40.4(12.9)) and 89 trauma-exposed controls (Mage=39.8(11.6)). Shape and diffusion metrics for the cingulum, corpus callosum, fornix, inferior longitudinal fasciculus, superior longitudinal fasciculus, and uncinate fasciculus were calculated using deterministic tractography. Current symptom severity was calculated using the PTSD Symptom Scales. Input features included tract metrics, questionnaire responses, and age. The following regression models were generated: least absolute shrinkage and selection operator (LASSO), ridge, elastic net, and gaussian process (GPR). Additionally, two forms of latent-scale GPR, one without (lsGPR) and with (sp-lsGPR) node selection via spike and slab priors, were calculated. The performance of regression models was estimated using mean square error (MSE) and R2.

sp-lsGPR performed at or above other models across all symptom clusters. LASSO models were comparable to sp-lsGPR for avoidance and hyperarousal clusters. Ridge regression and GPR had the weakest performance across clusters. Scores for sp-lsGPR by cluster are as follows: reexperiencing Mmse =0.70(0.17), Mr2=0.56(0.13); avoidance Mmse =0.75(0.17), Mr2= 0.51(0.13); hyperarousal Mmse =0.57(0.18), Mr2=0.66(0.12); anhedonia Mmse =0.74(0.27), Mr2=0.57(0.13). The top three ranked posterior inclusion probabilities for white matter tracts across sp-lsGPR models include four sections of the cingulum, three sections of the corpus callosum, the right fornix, the left inferior longitudinal fasciculus, the first segment of the right superior longitudinal fasciculus, and the right uncincate fasciculus. The greatest posterior inclusion probability value for the sp-lsGPR models was the left frontal parahippocampal cingulum for the hyperarousal cluster.

Results support the combined predictive utility of white matter metrics for brain imaging regression models of PTSD. Results also support the use of sp-lsGPR models, which are designed to balance interpretable linear models and highly-flexible non-linear models. The sp-lsGPR model performance was similar across clusters but was relatively better for the hyperarousal cluster. This finding contrasts with prior machine learning work using functional data which was unable to predict hyperarousal scores above chance (MR2=0.06). These diverging findings highlight the importance of examining both functional and structural data in PTSD populations. Differing findings may also be related to sample characteristics as the prior study was conducted in China. Black American women and Chinese individuals have unique lived experiences that may differentially impact brain structure and function. Future work should continue to include diverse research samples to account for such experiences.

Convergent evidence has suggested atypical relationships between brain structure and function in major psychiatric disorders, yet how the abnormal patterns coincide and/or differ across different disorders remains largely unknown. Here, we aim to investigate the common and/or unique dynamic structure–function coupling patterns across major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ).

We quantified the dynamic structure–function coupling in 452 patients with psychiatric disorders (MDD/BD/SZ = 166/168/118) and 205 unaffected controls at three distinct brain network levels, such as global, meso-, and local levels. We also correlated dynamic structure–function coupling with the topological features of functional networks to examine how the structure–function relationship facilitates brain information communication over time.

The dynamic structure–function coupling is preserved for the three disorders at the global network level. Similar abnormalities in the rich-club organization are found in two distinct functional configuration states at the meso-level and are associated with the disease severity of MDD, BD, and SZ. At the local level, shared and unique alterations are observed in the brain regions involving the visual, cognitive control, and default mode networks. In addition, the relationships between structure–function coupling and the topological features of functional networks are altered in a manner indicative of state specificity.

These findings suggest both transdiagnostic and illness-specific alterations in the dynamic structure–function relationship of large-scale brain networks across MDD, BD, and SZ, providing new insights and potential biomarkers into the neurodevelopmental basis underlying the behavioral and cognitive deficits observed in these disorders.

The purpose of the research project is to analyze the long-term evolution of obsessive-compulsive disorder (OCD) from of a study of a cohort of patients prospectively followed over a period ranging from 5 to 20 years, treated for according to therapeutic guidelines mediating serotonin reuptake inhibitors (IRS) and drug enhancers (antipsychotics) and cognitive behavioral therapy and evaluated in a standardized manner.

To assess the long-term course of Obsessive-Compulsive Disorder (OCD) in a cohort of patients treated according to current clinical guidelines; to analyse possible prognostic factors associated with the long-term course of the disorder including clinical and sociodemographic variables, as well as genetic and neuroimaging biomarkers, and their interaction, and finally to study neuroanatomical and functional cerebral connectivity changes after 15 years of treatment in a subsample of patients.

Prospective, descriptive, and observational study of a cohort of OCD patients, receiving treatment at the Department of Psychiatry of Hospital de Bellvitge since 1998, according to a standardized protocol. Follow-up period ranges from 5 (n=423), to 10 (n= 247) and 15 years (123). Baseline clinical and sociodemographic assessment, long-term evolution and information on treatments provided are available for the whole sample. Data on whole exome sequencing is available for 300 of the patients included in the cohort and baseline structural neuroimaging and cerebral functional connectivity has been analysed in 168 subjects. To expand the analysis of genetic biomarkers, we propose the study of de novo variants through exome analysis of 50 trios (patient and both parents) selected among those subjects that have reached 15 years of follow-up (25 trios with patients within the “long-term remission” group and 25 trios with patients with chronic OCD). De novo variants detected in the trio analysis will be replicated in the rest of the sample. A structural and resting state MRI will be obtained in a subsample of 100 patients recruited among those who have completed a minimum follow-up period of 15 years, to assess cerebral changes associated with the long-term course of the disorder.

in the current moment the recruitment period of the study has ended and all the data is being statistically analysed in order to provide solid results in a short period of time.

The identification of those factors associated with an increased risk of chronic disease is an element essential to offer personalized treatment to our patients and improve their prognosis, emphasizing the intensive use of those therapeutic strategies for which we can predict a better response and modifying to the extent of, if possible, environmental factors or factors of access to treatment that contribute to perpetuate obsessive symptoms.

None Declared

A significant proportion of people attending Primary Care (PC) have anxiety-depressive symptoms and work-related burnout and there is a lack of resources to attend them. The COVID-19 pandemic has worsened this problem, particularly affecting healthcare workers, and digital tools have been proposed as a workaround.

We present the development, feasibility and effectiveness studies of chatbot (Vickybot) aimed at screening, monitoring, and reducing anxiety-depressive symptoms and work-related burnout in PC patients and healthcare workers.

User-centered development strategies were adopted. Main functions included self-assessments, psychological modules, and emergency alerts. (1) Simulation: HCs used Vickybot for 2 weeks to simulate different possible clinical situations and evaluated their experience. (3) Feasibility and effectiveness study: People consulting PC or healthcare workers with mental health problems were offered to use Vickybot for one month. Self-assessments for anxiety (GAD-7) and depression (PHQ-9) symptoms, and work-related burnout (based on the Maslach Burnout Inventory) were administered at baseline and every two weeks. Feasibility was determined based on the combination of both subjective and objective user-engagement Indicators (UEIs). Effectiveness was measured using paired t-tests as the change in self-assessment scores.

(1) Simulation: 17 HCs (73% female; mean age=36.5±9.7) simulated different clinical situations. 98.8% of the expected modules were recommended according to each simulation. Suicidal alerts were correctly activated and received by the research team. (2) Feasibility and effectiveness study: 34 patients (15 from PC and 19 healthcare workers; 77% female; mean age=35.3±10.1) completed the first self-assessments, with 34 (100%) presenting anxiety symptoms, 32 (94%) depressive symptoms, and 22 (64.7%) work-related burnout. Nine (26.5%) patients completed the second self-assessments after 2-weeks of use. No significant differences were found for anxiety [t(8) = 1.000, p = 0.347] or depressive [t(8) = 0.400, p = 0.700] symptoms, but work-related burnout was significantly reduced [t(8) = 2.874, p = 0.021] between the means of the first and second self-assessments. Vickybot showed high subjective-UEIs, but low objective-UEIs (completion, adherence, compliance, and engagement).

The chatbot proved to be useful in screening the presence and severity of anxiety and depressive symptoms, in reducing work-related burnout, and in detecting suicidal risk. Subjective perceptions of use contrasted with low objective-use metrics. Our results are promising, but suggest the need to adapt and enhance the smartphone-based solution in order to improve engagement. Consensus on how to report UEIs and validate digital solutions, especially for chatbots, are required.

None Declared

Neuropsychiatric symptoms (NPS) are common during the course of neurocognitive disorders. NPS have been previously reported in early and late stages of Alzheimer’s Disease. However, our understanding of NPS in high-risk states for dementia such as mild cognitive impairment (MCI) and major depressive disorder (MDD) is poor.

To compare the frequency and factor structure of neuropsychiatric symptoms among individuals with Mild Cognitive Impairment (MCI), Major Depressive Disorder (MDD) in remission, and comorbid MCI and MDD (in remission) (MCI-D).

We used baseline data from the Prevention of Alzheimer’s Dementia with Cognitive Remediation Plus Transcranial Direct Current Stimulation in Mild Cognitive Impairment and Depression (PACt-MD) study, a multicenter trial across five academic sites in Toronto, Canada (clinical trial No. NCT0238667). We used ANOVA or χ2-test to compare frequency of NPS across groups. We used factor analysis of Neuropsychiatric Inventory Questionnaire (NPI-Q) items in the three groups.

We included 374 participants with a mean age of 72.0 years (SD = 6.3). In the overall sample, at least one NPS was present in 64.2% participants, and 36.1 % had at least moderate severity NPS (36.1%). Depression (54%, χ2 < 0.001) and apathy (28.7%, χ2=0.002) were more prevalent in the MCI-D group as compared to MCI and MDD groups. In factor analysis, NPS grouped differently in MCI, MDD, and MCI-D groups. A “psychotic” subgroup emerged among MCI and MCI-D, but not in MDD. Night-time behaviors and disinhibition grouped differently across all three groups.

Prevalence of NPS seems higher in persons with MCI-D as compared to those with only MCI or MDD. The factor structure of NPS differed between MCI, MDD, and MCI-D groups. Future studies should investigate the association of NPS factors with cognition, function, and illness biomarkers.

None Declared

No established guidelines exist regarding the role of oral antibiotic therapy (OAT) to treat bloodstream infections (BSIs), and practices may vary depending on clinician specialty and experience.

To assess practice patterns regarding oral antibiotic use for treatment of bacteremia in infectious diseases clinicians (IDCs, including physicians and pharmacists and trainees in these groups) and non–infectious diseases clinicians (NIDCs).

Open-access survey.

Clinicians caring for hospitalized patients receiving antibiotics.

An open-access, web-based survey was distributed to clinicians at a Midwestern academic medical center using e-mail and to clinicians outside the medical center using social media. Respondents answered questions regarding confidence prescribing OAT for BSI in different scenarios. We used χ2 analysis for categorical data evaluated association between responses and demographic groups.

Of 282 survey responses, 82.6% of respondents were physicians, 17.4% pharmacists, and IDCs represented 69.2% of all respondents. IDCs were more likely to select routine use of OAT for BSI due to gram-negative anaerobes (84.6% vs 59.8%; P < .0001), Klebsiella spp (84.5% vs 69.0%; P < .009), Proteus spp (83.6% vs 71.3%; P < .027), and other Enterobacterales (79.5% vs 60.9%; P < .004). Our survey results revealed significant differences in selected treatment of Staphylococcus aureus syndromes. Fewer IDCs than NIDCs selected OAT to complete treatment for methicillin-resistant S. aureus (MRSA) BSI due to gluteal abscess (11.9% vs 25.6%; P = .012) and methicillin-susceptible S. aureus (MSSA) BSI due to septic arthritis (13.9% vs 20.9%; P = .219).

Practice variation and discordance with evidence for the use of OAT for BSIs exists among IDCs versus NIDCs, highlighting opportunities for education in both clinician groups.