The concept of total suffering is widely recognized in palliative care (PC), encompassing a range of interconnected and complex factors that collectively shape the evolving and individualized experience of a patient’s illness journey. Studies on will to live (WtL) in terminally ill patients have demonstrated its variability over time and various factors that influence these changes.

To objectively investigate the concept of total suffering and WtL; including their fluctuation over time and associations with sociodemographic, clinical, physical, and psychological symptoms in a sample of individuals with life-limiting conditions receiving PC. This multicenter Iberian study involved 3 centers in Portugal and 1 in Spain. A total of 107 individuals with life-limiting conditions consented to participate. To capture the dynamic and multifaceted components of total suffering, we had each participant completed the Edmonton Symptom Assessment Scale (ESAS) along an additional WtL visual analogue once daily over a 30-day period.

WtL demonstrated various patterns over time. While some patterns reflected relative stability, other demonstrated substantive fluctuation during the course of illness. Significant correlations were observed between WtL and all other ESAS items. Moderate positive correlations were found between WtL and total ESAS score and its physical and psychological sub-scores. Spearman’s correlation coefficients between all physical and psychosocial items on the ESAS were statistically significant across all 45 correlations performed, with only 5 showing moderate strength; the remaining correlations were weaker.

Evidence-based understanding of WtL is critical to improving care for patients who experience suffering toward end-of-life and their families. Further research is needed to inform and refine interventions targeting total suffering.

Cognitive deficits and immune system dysregulation are core features of psychotic disorders. Among inflammatory markers, interleukin-6 (IL-6) and tumour necrosis factor-alpha (TNF-α) have been linked to both psychosis pathophysiology and related cognitive impairments.

We investigated associations among IL-6, TNF-α, and neurocognitive performance in 107 participants: individuals at clinical high risk for psychosis (CHR-P, n = 35), first-episode psychosis (FEP, n = 39), and healthy controls (HC, n = 33). Assessments included memory, processing speed, executive function, and social cognition. Cytokines were measured from fasting serum samples. Analyses included ANOVA, correlations, and multivariate regressions controlling for age, sex, IQ, group, and symptom severity.

TNF-α levels were significantly elevated in FEP compared to CHR-P (p = 0.0251); IL-6 differences were non-significant. FEP showed poorer performance in multiple cognitive domains, especially social cognition. CHR-P individuals exhibited intermediate profiles between FEP and HC in cognition. In adjusted regression models, IL-6 was significantly associated with undermentalization on the MASC task (β = 0.28, p = 0.0337) and showed a trend-level association with slower processing speed (β = 0.98, p = 0.075). TNF-α levels predicted poorer facial emotion recognition (β = −1.37, p = 0.0022). IQ and group were significant covariates in most models.

Our findings suggest that peripheral inflammation, particularly IL-6 and TNF-α, may selectively impact social cognitive functioning in early psychosis. Though modest, these associations highlight potential inflammatory contributions to functional impairment and support further investigation of immunological targets in early intervention.

Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), but initial outcomes can be modest.

To compare SSRI dose optimisation with four alternative second-line strategies in MDD patients unresponsive to an SSRI.

Of 257 participants, 51 were randomised to SSRI dose optimisation (SSRI-Opt), 46 to lithium augmentation (SSRI+Li), 48 to nortriptyline combination (SSRI+NTP), 55 to switch to venlafaxine (VEN) and 57 to problem-solving therapy (SSRI+PST). Primary outcomes were week-6 response/remission rates, assessed by blinded evaluators using the 17-item Hamilton Depression Rating Scale (HDRS-17). Changes in HDRS-17 scores, global improvement and safety outcomes were also explored. EudraCT No. 2007-002130-11.

Alternative second-line strategies led to higher response (28.2% v. 14.3%, odds ratio = 2.36 [95% CI 1.0–5.6], p = 0.05) and remission (16.9% v. 12.2%, odds ratio = 1.46, [95% CI 0.57–3.71], p = 0.27) rates, with greater HDRS-17 score reductions (−2.6 [95% CI −4.9 to −0.4], p = 0.021]) than SSRI-Opt. Significant/marginally significant effects were only observed in both response rates and HDRS-17 decreases for VEN (odds ratio = 2.53 [95% CI 0.94–6.80], p = 0.067; HDRS-17 difference: −2.7 [95% CI −5.5 to 0.0], p = 0.054) and for SSRI+PST (odds ratio = 2.46 [95% CI 0.92 to 6.62], p = 0.074; HDRS-17 difference: −3.1 [95% CI −5.8 to −0.3], p = 0.032). The SSRI+PST group reported the fewest adverse effects, while SSRI+NTP experienced the most (28.1% v. 75%; p < 0.01), largely mild.

Patients with MDD and insufficient response to SSRIs would benefit from any other second-line strategy aside from dose optimisation. With limited statistical power, switching to venlafaxine and adding psychotherapy yielded the most consistent results in the DEPRE'5 study.

Studies conducted during the COVID-19 pandemic found high occurrence of suicidal thoughts and behaviours (STBs) among healthcare workers (HCWs). The current study aimed to (1) develop a machine learning-based prediction model for future STBs using data from a large prospective cohort of Spanish HCWs and (2) identify the most important variables in terms of contribution to the model’s predictive accuracy.

This is a prospective, multicentre cohort study of Spanish HCWs active during the COVID-19 pandemic. A total of 8,996 HCWs participated in the web-based baseline survey (May–July 2020) and 4,809 in the 4-month follow-up survey. A total of 219 predictor variables were derived from the baseline survey. The outcome variable was any STB at the 4-month follow-up. Variable selection was done using an L1 regularized linear Support Vector Classifier (SVC). A random forest model with 5-fold cross-validation was developed, in which the Synthetic Minority Oversampling Technique (SMOTE) and undersampling of the majority class balancing techniques were tested. The model was evaluated by the area under the Receiver Operating Characteristic (AUROC) curve and the area under the precision–recall curve. Shapley’s additive explanatory values (SHAP values) were used to evaluate the overall contribution of each variable to the prediction of future STBs. Results were obtained separately by gender.

The prevalence of STBs in HCWs at the 4-month follow-up was 7.9% (women = 7.8%, men = 8.2%). Thirty-four variables were selected by the L1 regularized linear SVC. The best results were obtained without data balancing techniques: AUROC = 0.87 (0.86 for women and 0.87 for men) and area under the precision–recall curve = 0.50 (0.55 for women and 0.45 for men). Based on SHAP values, the most important baseline predictors for any STB at the 4-month follow-up were the presence of passive suicidal ideation, the number of days in the past 30 days with passive or active suicidal ideation, the number of days in the past 30 days with binge eating episodes, the number of panic attacks (women only) and the frequency of intrusive thoughts (men only).

Machine learning-based prediction models for STBs in HCWs during the COVID-19 pandemic trained on web-based survey data present high discrimination and classification capacity. Future clinical implementations of this model could enable the early detection of HCWs at the highest risk for developing adverse mental health outcomes.

NCT04556565

Many factors can impact survey completion rates, including survey length, sensitivity of the topics addressed, and clarity of wording. This study used cognitive interviews (CIs), a methodological tool that can aid in developing and refining elements for multi-faceted assessments, and previous survey response patterns to refine, streamline, and increase response rates of RADx-UP Common Data Elements (CDEs) for survey/questionnaire use.

Ten previously enrolled CO-CREATE study participants were interviewed between May–June 2023. Interviewees identified CDEs that were “confusing, uncomfortable, and/or not applicable,” along with their reasoning. Interview data were analyzed using a rapid qualitative analytic approach, resulting in a summary matrix categorized by language. For further contextualization, CDE response rates were calculated for the 9147 surveys administered during the CO-CREATE study (May 2021–March 2023) and compared against their survey position.

Of the 94 CDEs evaluated in the CIs, 20 (21.3%) were flagged by one or more interviewees. Nine (9.6%) English while fourteen (14.9%) Spanish CDEs were flagged by interviewees, with some overlap. Also, CDE response rates differed according to position in the survey, with lower response rates for questions positioned later in the survey. Following review by the research team and the RADx-UP program, 10 English and 15 Spanish were revised, and seven were removed in both languages in the final survey.

Our findings underscore the importance of integrating community member perspectives to enhance the relevance and clarity of assessment instruments, optimizing the impact of public health research among underrepresented populations.

Achieving sustainability on the ground poses a challenge in decoding globally defined goals, such as sustainable development goals, and aligning them with local perspectives and realities. This decoding necessitates the understanding of the multifaceted dimensions of the sustainability challenges in a given context, including their underlying causes. In case studies from Brazilian drylands, we illustrate how an enhanced multiscale participatory method, combined with systems thinking tools, can shed light on systemic structures that currently entrench unsustainable development trajectories. This method offers insights into co-designing potential pathways toward sustainable futures and unlocking transformative capacities of the local population.

Translating United Nations global sustainable development goals (SDGs) into actions that address local realities and aspirations is an urgent challenge. It requires new thinking and approaches that foster the discussion about the main challenges to implementing the SDGs at multiple levels. This paper presents a novel multiscale participatory approach that combines the popular Three Horizons diagram with the formalism of causal loop diagrams in systems thinking. We present results from six multi-stakeholder dialogues held across drylands in Brazil with a focus on desired futures aligned with SDGs. Focusing on identifying the root causes and systemic structures of unsustainability, participants identified lock-ins, leverage points, and interventions for how these could be changed. The core lock-ins are the discontinuity of public policies, and the historical land and power concentration reinforced by the current expansion of large-scale agricultural, mining, and energy projects. The proposed interventions are structural and – if implemented – would contribute to achieving SDGs in an integrated manner. The unique approach developed in this study can provide leverage as it bridges the inclusivity of participatory visioning with the change potential of systems thinking tools to tackle root causes and unleash societal transformations.

We are not achieving SDGs. Understanding root causes of unsustainability is critical to move toward sustainable and just futures.

One of the most relevant risk factors for suicide is the presence of previous attempts. The symptomatic profile of people who reattempt suicide deserves attention. Network analysis is a promising tool to study this field.

To analyze the symptomatic network of patients who have attempted suicide recently and compare networks of people with several attempts and people with just one at baseline.

1043 adult participants from the Spanish cohort “SURVIVE” were part of this study. Participants were classified into two groups: single attempt group (n = 390) and reattempt group (n = 653). Different network analyses were carried out to study the relationships between suicidal ideation, behavior, psychiatric symptoms, diagnoses, childhood trauma, and impulsivity. A general network and one for each subgroup were estimated.

People with several suicide attempts at baseline scored significantly higher across all clinical scales. The symptomatic networks were equivalent in both groups of patients (p > .05). Although there were no overall differences between the networks, some nodes were more relevant according to group belonging.

People with a history of previous attempts have greater psychiatric symptom severity but the relationships between risk factors show the same structure when compared with the single attempt group. All risk factors deserve attention regardless of the number of attempts, but assessments can be adjusted to better monitor the occurrence of reattempts.

Estimating the risk of developing bipolar disorder (BD) in children and adolescents (C&A) with depressive disorders is important to optimize prevention and early intervention efforts. We aimed to quantitatively examine the risk of developing BD from depressive disorders and identify factors which moderate this development.

In this systematic review and meta-analysis (PROSPERO:CRD42023431301), PubMed and Web-of-Science databases were searched for longitudinal studies reporting the percentage of C&A with ICD/DSM-defined depressive disorders who developed BD during follow-up. Data extraction, random-effects meta-analysis, between-study heterogeneity analysis, quality assessment, sub-group analyses, and meta-regressions were conducted.

Thirty-nine studies were included, including 72,371 individuals (mean age=13.9 years, 57.1% females); 14.7% of C&A with a depressive disorder developed BD after 20.4–288 months: 9.5% developed BD-I (95% CI=4.7 to 18.1); 7.7% developed BD-II (95% CI=3.2% to 17.3%); 19.8% (95% CI=9.9% to 35.6%) of C&A admitted into the hospital with a depressive disorder developed BD. Studies using the DSM (21.6%, 95% CI=20.2% to 23.1%) and studies evaluating C&A with a major depressive disorder only (19.8%, 95% CI=16.8% to 23.1%) found higher rates of development of BD. Younger age at baseline, a history of hospitalization and recruitment from specialized clinics were associated with an increased risk of developing BD at follow-up. Quality of included studies was good in 76.9% of studies.

There is a substantial risk of developing BD in C&A with depressive disorders. This is particularly the case for C&A with MDD, DSM-diagnosed depressive disorders, and C&A admitted into the hospital. Research exploring additional predictors and preventive interventions is crucial.

Suicide poses a severe public health challenge worldwide, impacting individuals, families, work, and society. The multifaceted nature of suicide demands a complex approach involving psychological, biological, social, cultural, and environmental factors. Recognizing suicide’s status as the leading external cause of death in Spain, prevention increasingly incorporates technology, specifically mobile and software applications.

A systematic review of the effectiveness and safety of mobile and software applications was conducted (MEDLINE, Embase, CINAHL, and PsycINFO databases). Outcome variables included: suicide; suicidal behavior; suicidal intent; suicidal ideation/thinking; self-perceived suicide risk; using/seeking mental health services; associated mental symptoms; mental health-related quality of life; satisfaction of the user and the health professional; adverse events related to the app, as defined in the included studies. Studies that do not include suicidal behavior, intention, or ideation were excluded. Where available data allowed, a meta-analysis was conducted for each outcome variable.

One systematic review and 13 randomized controlled trials (n=2,952) were analyzed. No significant differences were found in deaths by suicide or suicide attempts. At post-intervention, small but significant reductions were observed in suicidal ideation, hopelessness, depression, and worry, with anxiety reduction slightly above statistical significance. At follow-up (8 to 52 weeks), these variables also obtained significant results, except depression and suicidal ideation. Regarding safety, there was no significant difference in safety phone calls for participants with suicidal ideation.

The evidence on suicide prevention app effectiveness is of low quality, precluding conclusive findings. Attempt reduction is suggested at 21 percent, but the confidence interval includes a potential 60 percent increase. Evidence on suicide-related psychological variables (suicide ideation, depression, hopelessness, and anxiety) is of higher quality (low–moderate), but effects are small and clinically uncertain. Safety findings are uncertain, impacting risk/benefit balance.

Suicidal behavior constitutes a multi-cause phenomenon that may also be present in people without a mental disorder. This study aims to analyze suicidal behavior outcomes in a sample of attempters, from a symptom-based approach.

The sample comprised 673 patients (72% female; M = 40.9 years) who attended a hospital emergency department due to a suicide attempt. A wide range of clinical factors (e.g., psychopathology symptoms, psychiatric diagnoses, impulsivity, acquired capability), was administered within 15 days after the index attempt. Nine psychopathology domains were explored to identify the profile of symptoms, using latent profile analysis. The relationship between the profile membership and suicide outcome (i.e., intensity of suicidal ideation, number of suicide behaviors, and medical injury derived from index attempt) was also studied, using linear and logistic regression.

Three psychopathology profiles were identified: high-symptom profile (45.02% of participants), moderate-symptom profile (42.50%), and low-symptom profile (12.48%). High-symptom profile members were more likely to show higher risk of non-suicidal self-injury, acquired capability for suicide, and more severe suicide behavior and ideation. On the other hand, a more severe physical injury was associated with low-symptom profile membership in comparison to membership from the other profiles (OR < 0.45, p < .05).

A symptom-based approach may be useful to monitor patients and determine the risk of attempt repetition in the future and potential medical injury, and to optimize prevention and intervention strategies.

Suicide is one of the main external causes of death worldwide. People who have already attempted suicide are at high risk of new suicidal behavior. However, there is a lack of information on the risk factors that facilitate the appearance of reattempts. The aim of this study was to calculate the risk of suicide reattempt in the presence of suicidal history and psychosocial risk factors and to estimate the effect of each individual risk factor.

This systematic review and meta-analysis were conducted following the PRISMA-2020 guidelines. Studies on suicide reattempt that measured risk factors were searched from inception to 2022. The risk factors studied were those directly related to suicide history: history of suicide prior to the index attempt, and those that mediate the transition from suicidal ideation to attempt (alcohol or drug misuse, impulsivity, trauma, and non-suicidal self-injury).

The initial search resulted in 11 905 articles. Of these, 34 articles were selected for this meta-analysis, jointly presenting 52 different effect sizes. The pooled effect size across the risk factors was significant (OR 2.16). Reattempt risk may be increased in presence of any of the following risk factors: previous history, active suicidal ideation, trauma, alcohol misuse, and drug misuse. However, impulsivity, and non-suicidal self-injury did not show a significant effect on reattempt.

Most of the risk factors traditionally associated with suicide are also relevant when talking about suicide reattempts. Knowing the traits that define reattempters can help develop better preventive and intervention plans.