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.

The course of depression is heterogeneous. The employed treatment is a key element in the impact of the course of depression over the time. However, there is currently a gap of knowledge about the trajectories per treatment and related baseline factors. We aimed to identify trajectories of depressive symptoms and associated baseline characteristics for two treatment arms in a randomized clinical trial: treatment as usual (TAU) or TAU plus transdiagnostic group cognitive behavioral therapy (TAU + TDG-CBT).

Growth mixture modeling (GMM) was used to identify trajectories of depressive symptoms over 12 months post-treatment. Logistic regression models were used to examine associations between baseline characteristics and trajectory class membership in 483 patients (TAU: 231; TAU + TDG-CBT: 251).

We identified different patterns of symptom change in the randomized groups: two trajectories in TAU (‘improvement’ (71.4%) and ‘no improvement’ (28.6%)), and four trajectories in TAU + TDG-CBT (‘recovery’ (69.8%), ‘late recovery’ (5.95%), ‘chronicity’ (4.77%), and ‘relapse’ (19.44%)). Higher baseline symptom severity and comorbidity were associated with poorer treatment outcomes in both treatment groups and worse emotional regulation strategies were linked to the ‘no improvement trajectory’ in TAU. The TAU + TDG-CBT group demonstrated greater symptom reduction compared to TAU alone.

There is heterogeneity in treatment outcomes. Integration of TDG-CBT with TAU significantly improves symptom reduction compared to TAU alone. Patients with higher baseline severity and comorbidities show poorer outcomes. Identification of trajectories and related factors could assist clinicians in tailoring treatment strategies to optimize outcomes, particularly for patients with a worse prognosis.

One obstacle to the development of clinical practice guidelines (CPGs) for rare diseases (RDs) is the lack of scientific evidence. This can be partially overcome by involving patients in the development of CPGs. Our aim was to develop a process for involving patients with RDs in all stages of CPG development to ensure that their needs and expectations are addressed.

A literature search was conducted in the MEDLINE, Cochrane Library, and Embase databases and the websites of the European Organization for Rare Diseases, the National Organization for Rare Disorders, and INAHTA. Eligible articles reported methods for involving patients in CPGs, other clinical decision support tools, and research studies. A fit-for-purpose data extraction template was created to capture the following data: author, year, country, type of study, characteristics of the target population, and strategies for participation, engagement, and involvement of patients. Data were synthesized according to methods for recruiting, involving, or engaging patients and obtaining information from them. The entire process was performed by pairs of researchers.

A total of 1,113 records were identified once duplicates were deleted. Of these, 55 were included. The review collected data on types of patients (patient representatives or patient experts) and their recruitment, which could be classified as open or nominated. The various involvement strategies included consultation, participation, and communication. Differences between involving and engaging patients in the CPGs development process were noted. Procedures for obtaining the opinion of patients included surveys, interviews, workshops, and focus groups, among others. The review also provided information on the importance of involving patients in the dissemination and implementation stages of CPG development and the methods for doing so.

When patients with RDs are actively involved in all phases of CPG development, they can contribute to the identification, prioritization, and inclusion of topics pertinent to RDs as questions to be addressed in the CPGs. These aspects might otherwise be overlooked by clinical experts and researchers. Therefore, involving patients with RDs is a promising approach to addressing gaps in the management of these diseases.

Mass Casualty Incidents (MCIs) pose significant challenges to health care systems, especially regarding emergency preparedness and response. This study aims to analyze the epidemiological characteristics and burden of MCIs in Spain from 2014 to 2022, focusing on the type, frequency, and impact of these incidents on public health and emergency services.

A population-based retrospective observational study examined MCIs in Spain between January 2014 and December 2022. Data were collected from various emergency services. Incidents involving 4 or more victims requiring medical assistance and ambulance mobilization were included. The study categorized MCIs into 5 types: road traffic accidents, fires and explosions, chemical poisonings, maritime accidents, and others.

A total of 1618 MCIs resulting in 8556 victims were identified, averaging 15 (95% CI, 11-19) incidents per month, with 79% due to road traffic accidents and 13% to fires and explosions, which also had the highest average of 7.6 victims per incident. Despite maritime accidents comprising only 1.9% of incidents, they had the highest fatality rate. MCIs were more frequent on weekends, in January and July, and between 3:00 PM and 9:00 PM. The average response time was 38 minutes, with 35% of victims sustaining severe injuries.

Despite a slight decrease in annual MCIs from 2014 to 2022 in Spain, the trend is not statistically significant. The study highlights the need for a national registry and standardized data collection to enhance emergency preparedness and response planning and facilitate the reduction of the MCI burden.

The relevance of family relationships in the outcome of various disorders has been highlighted from different domains. Specifically, empirical studies on the relationship between the outcome of schizophrenia and various affective dimensions of family relationships have allowed the identification of particularly relevant aspects: criticism, hostility, and over-protection.

The present study aims to adapt and validate an abbreviated Spanish version of the Influential Relationship Questionnaire (IRQ), an instrument that measures the patient’s own perception of the affective dimensions of family relationships.

Participants were 188 patients (63.8% male) of the Public Health Service in Andalusia (Spain) with a diagnosis of schizophrenia or a related disorder. One hundred and thirty-six participants provided data related to both father and mother, and 52 only related to mother or father, so the analyses were carried out with a total of 324 questionnaires. Simultaneously, in 130 participants, the Perceived Criticism Scale was applied, and in 50 cases, relatives were asked to complete the Family Attitudes Scale.

Principal component analysis allowed for the identification of four factors that explained 61.53% of the total variance (criticism, over-protection, restriction, and care). The values of Cronbach’s alpha coefficient, as well as the omega coefficient, showed high consistency. The temporal reliability for an interval of 3 months was high. The correlations between the IRQ dimensions and the other variables included in the study were significant and in the expected direction.

The results support the reliability and validity of the abbreviated version of the IRQ.

There is heterogeneity in the long-term trajectories of depressive symptoms among patients. To date, there has been little effort to inform the long-term trajectory of symptom change and the factors associated with different trajectories. Such knowledge is key to treatment decision-making in primary care, where depression is a common reason for consultation. We aimed to identify distinct long-term trajectories of depressive symptoms and explore pre-treatment characteristics associated with them.

A total of 483 patients from the PsicAP clinical trial were included. Growth mixture modeling was used to identify long-term distinct trajectories of depressive symptoms, and multinomial logistic regression models to explore associations between pre-treatment characteristics and trajectories.

Four trajectories were identified that best explained the observed response patterns: “recovery” (64.18%), “late recovery” (10.15%), “relapse” (13.67%), and “chronicity” (12%). There was a higher likelihood of following the recovery trajectory for patients who had received psychological treatment in addition to the treatment as usual. Chronicity was associated with higher depressive severity, comorbidity (generalized anxiety, panic, and somatic symptoms), taking antidepressants, higher emotional suppression, lower levels on life quality, and being older. Relapse was associated with higher depressive severity, somatic symptoms, and having basic education, and late recovery was associated with higher depressive severity, generalized anxiety symptoms, greater disability, and rumination.

There were different trajectories of depressive course and related prognostic factors among the patients. However, further research is needed before these findings can significantly influence care decisions.

Polygenic risk scores for educational attainment (PRSEA), cognitive reserve (CR), and clinical symptoms are associated with functioning in first-episode psychosis (FEP). Nevertheless, the mechanisms underlying their complex interaction are yet to be explored. This study assessed the mediating role of CR and clinical symptoms, both negative (NS) and positive (PS), on the interrelationship between PRSEA and functionality, one year after a FEP.

A total of 162 FEP patients underwent clinical, functional, and genetic assessments. Using genome-wide association study summary results, PRSEA were constructed for each individual. Two mediation models were performed. The parallel mediation model explored the relationship of PRSEA with functionality through CR and clinical symptoms. The serial mediation model tested a causal chain of the three mediators: CR, NS, and PS. Mediation analysis was performed using the PROCESS function V.4.1 in SPSS V.22.

A serial mediation model revealed a causal chain for PRSEA > CR > NS > Functionality (β = −0.35, 95%CI [−0.85, −0.04], p < 0.05). The model fit the data satisfactorily (CFI = 1.00; RMSEA = 0.00; SRMR = 7.2 × 10−7). Conversely, no parallel mediation was found between the three mediators, PRSEA and functionality and the model poorly fit the data (CFI = 0.30; RMSEA = 0.25; SRMR = 0.11).

Both CR and NS mediate the relationship between PRSEA and functionality at one-year follow-up, using serial mediation analysis. This may be relevant for prevention and personalized early intervention to reduce illness impact and improve functional outcomes in FEP patients.

Patients with a first episode of psychosis (FEP) display clinical, cognitive, and structural brain abnormalities at illness onset. Ventricular enlargement has been identified in schizophrenia since the initial development of neuroimaging techniques. Obstetric abnormalities have been associated with an increased risk of developing psychosis but also with cognitive impairment and brain structure abnormalities. Difficulties during delivery are associated with a higher risk of birth asphyxia leading to brain structural abnormalities, such as ventriculomegaly, which has been related to cognitive disturbances.

We examined differences in ventricular size between 142 FEP patients and 123 healthy control participants using magnetic resonance imaging. Obstetric complications were evaluated using the Lewis–Murray scale. We examined the impact of obstetric difficulties during delivery on ventricle size as well as the possible relationship between ventricle size and cognitive impairment in both groups.

FEP patients displayed significantly larger third ventricle size compared with healthy controls. Third ventricle enlargement was associated with diagnosis (higher volume in patients), with difficulties during delivery (higher volume in subjects with difficulties), and was highest in patients with difficulties during delivery. Verbal memory was significantly associated with third ventricle to brain ratio.

Our results suggest that difficulties during delivery might be significant contributors to the ventricular enlargement historically described in schizophrenia. Thus, obstetric complications may contribute to the development of psychosis through changes in brain architecture.

The coronavirus disease 2019 (COVID-19) has serious physiological and psychological consequences. The long-term (>12 weeks post-infection) impact of COVID-19 on mental health, specifically in older adults, is unclear. We longitudinally assessed the association of COVID-19 with depression symptomatology in community-dwelling older adults with metabolic syndrome within the framework of the PREDIMED-Plus cohort.

Participants (n = 5486) aged 55–75 years were included in this longitudinal cohort. COVID-19 status (positive/negative) determined by tests (e.g. polymerase chain reaction severe acute respiratory syndrome coronavirus 2, IgG) was confirmed via event adjudication (410 cases). Pre- and post-COVID-19 depressive symptomatology was ascertained from annual assessments conducted using a validated 21-item Spanish Beck Depression Inventory-II (BDI-II). Multivariable linear and logistic regression models assessed the association between COVID-19 and depression symptomatology.

COVID-19 in older adults was associated with higher post-COVID-19 BDI-II scores measured at a median (interquartile range) of 29 (15–40) weeks post-infection [fully adjusted β = 0.65 points, 95% confidence interval (CI) 0.15–1.15; p = 0.011]. This association was particularly prominent in women (β = 1.38 points, 95% CI 0.44–2.33, p = 0.004). COVID-19 was associated with 62% increased odds of elevated depression risk (BDI-II ≥ 14) post-COVID-19 when adjusted for confounders (odds ratio; 95% CI 1.13–2.30, p = 0.008).

COVID-19 was associated with long-term depression risk in older adults with overweight/obesity and metabolic syndrome, particularly in women. Thus, long-term evaluations of the impact of COVID-19 on mental health and preventive public health initiatives are warranted in older adults.

Peru’s health infrastructures, particularly hospitals, are exposed to disaster threats of different natures. Traditionally, earthquakes have been the main disaster in terms of physical and structural vulnerability, but the coronavirus disease 2019 (COVID-19) pandemic has also shown their functional vulnerability. Public hospitals in Lima are very different in terms of year constructed, type of construction, and number of floors, making them highly vulnerable to earthquakes. In addition, they are subject to a high demand for care daily. Therefore, if a major earthquake were to occur in Lima, the hospitals would not have the capacity to respond to the high demand.

The aim of this study was to analyze the Hospital Safety Index (HSI) in hospitals in Lima (Peru).

This was a cross-sectional observational study of 18 state-run hospitals that met the inclusion criteria; open access data were collected for the indicators proposed by the Pan American Health Organization (PAHO) Version 1. Associations between variables were calculated using the chi-square test, considering a confidence level of 95%. A P value less than .05 was considered to determine statistical significance.

The average bed occupancy rate was 90%, the average age was 70 years, on average had one bed per 25,126 inhabitants, and HSI average score was 0.36 with a vulnerability of 0.63. No association was found between HSI and hospital characteristics.

Most of the hospitals were considered Category C in earthquake and disaster safety, and only one hospital was Category A. The hospital situation needs to be clarified, and the specific deficiencies of each institution need to be identified and addressed according to their own characteristics and context.