While tuberculosis (TB) is associated with increased depressive symptoms, the long-term mental health trajectory post-diagnosis in low-resource settings remains poorly understood. This study investigated the longitudinal progression of depressive symptoms among individuals diagnosed with TB and evaluated whether symptom severity persisted or attenuated over time.
Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa. Population-based cohort study.
Rural Agincourt subdistrict, Mpumalanga province, South Africa, a high-TB-burden, resource-constrained region.
Adults aged 40 years and older who were permanent residents of the Agincourt subdistrict (N=5059 at baseline).
Depressive symptoms were assessed using the Centre for Epidemiologic Studies Depression Scale (CES-D) 8 (Wave 1) and CES-D 20 (Wave 2), with standardised scores enabling cross-wave comparisons. TB diagnosis status (self-reported) was categorised as recently diagnosed, previously diagnosed or never diagnosed.
At baseline, HIV prevalence was significantly higher (p
A recent TB diagnosis is strongly associated with depressive symptoms at baseline, and with the persistence of severe depressive symptoms 4 years later. These results were robust to a number of sensitivity tests and do not seem to be driven by differences in healthcare utilisation. Integrating mental health support into TB care programmes at all phases of diagnosis and treatment, particularly in low-resource settings, may have significant benefits.
To assess the prevalence of depression or depressive symptoms among engineering students.
Systematic review and meta-analysis of prevalence surveys using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.
PubMed, Index Medicus Global, EMBASE, Web of Science, Scopus and PsycINFO were searched from 1 January 2003 to 28 June 2024.
Studies were included if they: (1) reported the prevalence of depression or depressive symptoms among engineering students, (2) used a validated instrument with defined cut-off points to assess depression or depressive symptoms and (3) were published in a peer-reviewed journal.
Two researchers independently extracted data using a standardised spreadsheet, collecting information on country of data collection, survey years, year of training, sample size, mean age of participants, number and percentage of male participants, assessment instrument, cut-off points and prevalence estimates. Discrepancies were resolved by a third researcher. Risk of bias was assessed with the Risk of Bias for Studies of the Prevalence of Mental Health Disorders tool. Prevalence estimates were synthesised using random-effects meta-analysis. Between-study heterogeneity was assessed with ² tests and the I² statistic. Subgroup analyses were conducted according to severity cut-off points, and meta-regression was used to explore the influence of study-level characteristics on prevalence estimates.
23 studies involving 12 758 students across 11 countries were analysed. All studies used validated scales with cut-off points to assess depression or depressive symptoms. The overall pooled prevalence was 42.6% (95% CI 32.7 to 53.1) for studies using symptom severity cut-off points at mild or above, and 33.1% (95% CI 25.2 to 42.0) for studies using symptom severity cut-off points at moderate or above. Meta-regression indicated a progressive annual increase in prevalence (OR 1.14, 95% CI 1.01 to 1.28, p=0.034) across studies conducted from 2014 to 2024.
Prevalence of depression and depressive symptoms is high among engineering students, at levels comparable to medical students. Given the substantial impact, further research should investigate risk factors and evaluate preventive, early detection and treatment strategies tailored to engineering students.
CRD42024571131.
The study focused on nurses' familiarity with, beliefs about, and attitudes towards artificial intelligence, aiming to identify configurations of necessary and sufficient conditions associated with strong intentions to use artificial intelligence-based health technologies in their clinical practice.
Cross-sectional survey conducted online from mid-October 2023 through early February 2024.
The fuzzy set qualitative comparative analysis method was employed to analyse the survey data.
307 members of the professional order of nurses in Québec province, Canada.
Findings from the qualitative comparative analysis show that strong intentions to use artificial intelligence are only observed when nurses perceive artificial intelligence to have a high impactfulness on their future clinical practice (necessary condition). Moreover, we observe three configurations of sufficient conditions, that is, three combinations (artificial intelligence profiles) of familiarity with, belief about, trust in, and perceived impactfulness of artificial intelligence.
Current curriculum efforts have centred on defining artificial intelligence competencies, yet competency alone does not guarantee a willingness to adopt artificial intelligence tools. Our findings indicate that a positive attitude towards artificial intelligence's potential impact is crucial, with various profiles supporting intentions to adopt artificial intelligence.
These findings suggest that nurses' preparation should go beyond developing artificial intelligence competencies and that nursing educators and trainers need to account for the different profiles associated with strong intentions to use artificial intelligence technologies. Training programmes and nursing curricula should prioritise shaping nurses' beliefs and attitudes about artificial intelligence rather than focusing solely on technical skills.
We contribute to nursing research by showing that a positive attitude towards artificial intelligence's impactfulness on nurses' future clinical practice is a necessary condition for having high intentions to use artificial intelligence technologies.
Relevant guidelines have been adhered to by employing recommended qualitative comparative analysis reporting methods.
No patient or public contribution.
The aim of this study is to identify and analyse research priorities across the osteopathic profession internationally, to determine how different interested parties conceptualise research importance and to examine how contextual factors influence research prioritisation.
A mixed methods sequential exploratory design combining an umbrella review, a thematic analysis, an expert consensus agreement and an international cross-sectional survey was used to define, validate and evaluate research priorities.
An international online survey, available in nine languages, was distributed through professional osteopathic organisations and network worldwide, a patient representative organisation and social media.
2229 respondents including patients (7.4%), practitioners (42.1%), students (17.4%), educators (13.5%), researchers (5.0%) and policy makers (4.3%) from across 42 countries.
Primary outcomes were interested party’s conceptualisation of research importance and validation of the priorities in Research for Osteopathic Care (PROCare) framework. Secondary outcomes included current research priorities across interested parties groups and influence of contextual factors on prioritisation.
Three distinct approaches to priority-setting emerged: conservative (42.9%), sceptic (20.2%) and enthusiast (36.9%). Organising research priorities as a construct built from domains and subdomains was shown to be internally valid (Cronbach’s α=0.911). ‘Patient safety’ (nominated by 82% of relevant countries) and ‘physical activities and mobility’ (51.0%) were the most prioritised subdomains. ‘Digital health’ ranked lowest (28th of 28 subdomains). Significant geographic variations were observed mainly for the overall importance to most research domains. Strong consensus emerged around core priorities including patient safety, physical activity promotion and understanding treatment mechanisms.
The PROCare framework provides a validated structure for evaluating osteopathic research priorities across diverse interested parties. While geographic variations exist in priority emphasis, fundamental agreement on key research domains suggests potential for internationally coordinated research strategies. Future work should focus on developing mechanisms to ensure balanced representation of conservative, sceptic and enthusiast perspectives in research planning.
To investigate the occurrence of depression and mental health disorders other than depression among Brazilian people with intellectual disabilities, analysing data from a national household survey.
Cross-sectional epidemiological study using data from the 2019 National Health Survey (PNS).
Brazil, nationwide data collection in urban and rural private households.
272 499 individuals, among whom 1.2% (n=3198) reported intellectual disabilities.
Self-reported depression and mental health disorders other than depression (anxiety, panic, schizophrenia, bipolar disorder, psychosis or obsessive–compulsive disorder (OCD)), either isolated or comorbid.
Among people with intellectual disabilities, 43.2% reported at least one mental health disorder versus 13.7% without disabilities. In adults aged 0–59 years, intellectual disability was associated with higher odds of depression (adjusted OR (aOR) 3.25, 95% CI 1.76 to 6.00), mental health disorders other than depression (aOR 12.23, 95% CI 7.52 to 19.90) and depression associated with other mental health disorders (aOR 14.34, 95% CI 7.92 to 25.96). In older adults (≥60 years), risks also remained elevated: depression (aOR 1.71, 95% CI 1.04 to 2.79), mental health disorders other than depression (aOR 4.33, 95% CI 2.09 to 8.94) and depression associated with other mental health disorders (aOR 2.98, 95% CI 1.49 to 5.95). Women with intellectual disabilities were more likely to report depression and multimorbidity, while men more often reported non-depressive disorders. Poorer self-perceived health was consistently linked to worse outcomes across age groups.
Mental health disorders and their comorbidities are significantly more prevalent among people with intellectual disabilities in Brazil. These findings highlight the urgent need for inclusive, equitable and specialised mental healthcare policies.
Nurses confront substantial daily workloads. Coping mechanisms, including resilient behaviours at both individual and team levels, are pivotal in managing these challenges. Factors like work experience can significantly influence individual resilience. Yet, team resilience among nurses remains relatively unexplored.
Our study examined perceptions of both individual and team resilience among Dutch hospital nurses. Furthermore, we investigated the impacts of hospital type, ward type and work experience.
The Employee Resilience Scale was used to evaluate individual resilience and adapted for team contexts to assess team resilience. This study was one of three conducted under a governmental research program aimed at improving patient safety in the Netherlands. A paired t-test and correlation analysis were conducted to compare individual resilience with team resilience. A separate t-test assessed the impact of ward type on perceived individual and team resilience. Finally, post hoc analyses were used to examine the effects of hospital type and work experience.
In total, 344 nurses from 25 different wards of 17 Dutch hospitals completed the survey. In general, nurses indicated to act more resilient on the individual level (mean = 3.77, SD = 0.61) compared to the team level (mean = 3.53, SD = 0.65; t = 7.25, p = 0.00). A correlation was found between perceived individual and team resilience (r = 0.53, p = 0.00). No effects of hospital- and ward type were found on both individual or team resilience. Years of work experience did not affect individual resilience but showed a significant effect on team resilience.
Dutch hospital nurses indicated they often act resilient on both individual and team levels. However, with increasing workloads in healthcare, being able to remain resilient will become increasingly challenging and important. Organisations should therefore support employees to maintain resilience by adapting their work environment to meet more employees' needs.
To investigate whether quantitative retinal markers, derived from multimodal retinal imaging, are associated with increased risk of mortality among individuals with proliferative diabetic retinopathy (PDR), the most severe form of diabetic retinopathy.
Longitudinal retrospective cohort analysis.
This study was nested within the AlzEye cohort, which links longitudinal multimodal retinal imaging data routinely collected from a large tertiary ophthalmic institution in London, UK, with nationally held hospital admissions data across England.
A total of 675 individuals (1129 eyes) with PDR were included from the AlzEye cohort. Participants were aged ≥40 years (mean age 57.3 years, SD 10.3), and 410 (60.7%) were male.
The primary outcome was all-cause mortality. Quantitative retinal markers were derived from fundus photographs and optical coherence tomography using AutoMorph and Topcon Advanced Boundary Segmentation, respectively. We used unadjusted and adjusted Cox-proportional hazards models to estimate hazard ratios (HR) for the association between retinal features and time to death.
After adjusting for sociodemographic factors, each 1-SD decrease in arterial fractal dimension (HR: 1.54, 95% CI: 1.18 to 2.04), arterial vessel density (HR: 1.59, 95% CI: 1.15 to 2.17), arterial average width (HR: 1.35, 95% CI: 1.02 to 1.79), central retinal arteriolar equivalent (HR: 1.39, 95% CI: 1.05 to 1.82) and ganglion cell-inner plexiform layer (GC-IPL) thickness (HR: 1.61, 95% CI: 1.03 to 2.50) was associated with increased mortality risk. When also adjusting for hypertension, arterial fractal dimension (HR: 1.45, 95% CI: 1.08 to 1.92), arterial vessel density (HR: 1.47, 95% CI: 1.05 to 2.08) and GC-IPL thickness (HR: 1.56, 95% CI: 1.03 to 2.38) remained significantly associated with mortality.
Several quantitative retinal markers, relating to both microvascular morphology and retinal neural thickness, are associated with increased mortality among individuals with PDR. The role of retinal imaging in identifying those individuals with PDR most at risk of imminent life-threatening sequelae warrants further investigation.