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PubMed2026

Data-centric, robust, and explainable multimodal deep learning for clinical decision support: A systematic review.

PURPOSE: Multimodal deep learning is increasingly proposed for clinical decision support (CDS) under a "data-centric" framing that prioritizes label quality, missing-modality robustness, distribution shift, calibration, and explainability. Prior reviews have examined multimodal medical AI, CDS, and data-centric methods separately, but none address their intersection. We mapped the modalities, fusion strategies, and data-centric and explainability techniques used in this recent literature, quantified how often each is implemented rather than merely mentioned, assessed deployment-relevant evidence (external validation, clinical-outcome measurement, equity), and formally appraised study-level risk of bias. METHODS: Following the PRISMA 2020 statement (PROSPERO CRD420261427815; registered retrospectively), we screened 150 records and included primary, clinical, multimodal studies that applied machine or deep learning to a decision-support task and reported at least one quantitative result. Two reviewers screened and extracted data with consensus adjudication. Each study was coded against pre-specified operational definitions, separating implemented or empirically evaluated techniques from those only mentioned. Study-level risk of bias was assessed with PROBAST + AI. Synthesis was narrative. RESULTS: Thirty-one studies met inclusion; 30 (97%) were published between 2024 and 2026, with a median of three modalities (range 2-6), most commonly structured EHR (71%) and imaging (39%). Data-centric techniques were frequently reported (74-84% across label-noise, distribution-shift, calibration, missing-modality and class-imbalance handling; equity 61%). However, external validation was reported in only 4/31 studies (13%), a clinical or provider outcome in 3/31 (10%), and no study reported routine deployment. Overall risk of bias was high in 27/31 studies (87%), driven by the analysis domain. CONCLUSION: Within this recent, self-selected slice of the field, technical robustness and explainability techniques are widely reported but rarely validated out-of-distribution or against clinical outcomes, and the underlying evidence is at high risk of bias. Progress requires external multi-site validation, clinical-outcome measurement, formal bias appraisal, and adherence to AI reporting standards (e.g., TRIPOD + AI) before deployment can be justified.

Deep Learning↗

PubMed2026

Introgression shapes the genomic conflict landscape of Malus, providing evidence for a reticulate backbone in a woody crop lineage.

Phylogenomic discordance is widespread across plants, but its evolutionary significance is often obscured when conflict is treated primarily as analytical noise rather than as evidence of underlying processes. In woody lineages in particular, incomplete lineage sorting, introgression, and genome duplication can interact over long timescales to produce complex genomic histories that are not adequately summarized by a strictly bifurcating tree. Here, we use Malus as a model woody genus to investigate how these processes structure conflict across a genus-scale, accession-based phylogenomic framework. Using broad taxon sampling, hundreds of nuclear loci, plastid genomes, and genome-wide SNP summaries, we reconstruct a robust nuclear backbone for sampled Malus lineages and evaluate where discordance is concentrated and which processes best explain it. Nuclear analyses resolve eight major clades, whereas conflict is non-random and localized to recurrent hotspots rather than evenly distributed across the tree. Cytonuclear discordance is similarly concentrated, especially around Clade H, represented by sampled accessions of M. tschonoskii, where localized plastid-nuclear disagreement is consistent with candidate plastid capture or organellar introgression. Multiple complementary analyses further indicate that the strongest conflict is not explained by ILS alone, but instead reflects lineage-structured introgression, while polyploid complexes represent additional localized sources of evolutionary complexity. Together, these results provide evidence for a reticulate genomic backbone in Malus and show how integrating nuclear, plastid, and genome-wide conflict analyses can help distinguish background discordance from process-specific signals in woody plant radiations. Several lineage-level reticulation hypotheses identified here should now be tested with broader population-level sampling and curated reference accessions.

Malus↗

PubMed2026

Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.

BACKGROUND: Predictive modelling for cancer risk, treatment-related complications, and survival is central to precision oncology. Conventional logistic regression (LR) and Cox proportional hazards (CoxPH) regression remain widely used but are limited when modelling nonlinear interactions, high-dimensional imaging features, and multimodal clinical-metabolic predictors. Artificial intelligence (AI) and machine learning (ML) methods offer expanded capability through automated feature extraction, ensemble learning, and flexible survival modelling, but the evidence on when AI/ML adds value over conventional models across cancer sites and predictive tasks remains fragmented. OBJECTIVE: To systematically evaluate the methodological performance, validation strategies, and translational limitations of AI/ML models compared with conventional statistical models in published predictive-modelling studies for breast, colorectal, or pancreatic cancer. METHODS: PubMed, Scopus, and Web of Science were searched for studies published between January 2019 and March 2025. Two reviewers independently conducted title-and-abstract screening, full-text eligibility assessment, and PROBAST risk-of-bias assessment. Sixty-five studies (n = 907,567 participants) were narratively synthesised by cancer site, predictive task, model family, comparator, validation strategy, predictor modality, and calibration or explainability reporting. RESULTS: The 65 studies comprised breast cancer (n = 35), colorectal cancer (n = 21), and pancreatic cancer (n = 9). AI/ML superiority over LR and CoxPH was task- and data-dependent. CNN- and U-Net-based models predominated in imaging and body-composition tasks, tree-based ensembles consistently outperformed LR for tabular perioperative complication prediction, and CoxPH remained competitive, and in the largest pancreatic risk study, superior to XGBoost (C-index 0.802 vs 0.723) in well-structured datasets. PROBAST analysis-domain risk was moderate in 54 of 65 studies (83%), driven by limited external validation, sparse calibration reporting (11/65), and few decision-curve analyses (7/65). CONCLUSION: AI/ML adds the most methodological value in imaging-derived feature extraction and nonlinear perioperative prediction, while conventional regression remains preferable in large, structured datasets with linear predictors. Clinical translation requires standardised body-composition definitions, external validation, calibration assessment, decision-curve analysis, and explainability, in line with TRIPOD+AI and CLAIM standards.

Humans↗

PubMed2026

Integrated analysis uncovers exogenous induction and molecular regulation of erinacine A accumulation in Hericium erinaceus.

Erinacine A, a cyathane-type diterpenoid mainly from Hericium erinaceus mycelia, exhibits prominent neurotrophic and neuroprotective activities, making it a promising candidate for managing neurodegenerative diseases. However, its low abundance and unclear genetic regulatory mechanisms hinder its application as a nutraceutical. This study aimed to decipher its regulatory mechanisms and enhance production. Four exogenous inducers were screened, with salicylic acid (SA) and ergosterol (ERG) significantly increasing erinacine A content by 62.21% and 146.70% at 20 days, respectively. Transcriptome and WGCNA of inducer-treated sample identified darkorange and magenta modules associated with erinacine A biosynthesis, with the eri gene cluster enriched in the darkorange module and eriG and eriF as hub genes. Forward genetic analysis via QTL mapping of the HeD127 dikaryon population revealed significant phenotypic variation in erinacine A content (0.341-13.085 mg/g) and identified two loci (erA-1 and erA-2) explaining 18.63% of phenotypic variation. Integrating these forward and reverse genetic analyses revealed that salicylic acid and ergosterol synergistically regulate core carbon metabolic pathways to augment acetyl-CoA supply for the mevalonate pathway, suppressed competitive metabolism, enhanced diterpene skeleton construction and structural modification. These results deepen our understanding of the genetic and molecular basis governing accumulation of erinacine A, and facilitate its application in neuroprotective pharmaceuticals.

Diterpenes↗

PubMed2026

Genome-wide SNP data support species boundaries in sympatric Polylepis Ruiz & Pav. (Rosaceae) species from Bolivia and Ecuador.

Species delimitation in the South American genus Polylepis is notoriously challenging due to high morphological similarity and phenotypic plasticity, likely driven by hybridization and gene flow. Previous phylogenetic studies suggested that genetic structure aligns more strongly with geography than with taxonomy, questioning existing species concepts and hampering conservation efforts. We used double-digest RAD sequencing (ddRADseq) to generate genome-wide SNP data for 11 Polylepis species sampled across multiple localities in Bolivia and Ecuador. Population genetic analyses, phylogenetic inference, and network approaches were combined to assess whether genetic structure aligns more closely with taxonomy or geography. Morphologically defined species formed largely cohesive genetic lineages across regions, with species identity explaining substantially more genetic variation than locality. While localized admixture and reticulation were detected among closely related taxa, widespread species showed strong genetic cohesion and clear separation from congeners. Our results indicate that the sampled Polylepis species from Bolivia and Ecuador maintain distinct genetic identities despite localized signals consistent with gene flow. This genome-wide support for current taxonomy highlights Polylepis as a valuable model for studying speciation under gene flow and indicates that multiple geographic sampling will be essential in reconstructing a robust phylogeny of the genus, with important implications for conservation planning in Andean montane forests.

Bolivia↗

PubMed2026

Cytonuclear conflict and reticulate evolution in the Morelloid clade (Solanum, Solanaceae): Insights from genome skimming and network Phylogenomics.

The Morelloid clade (black nightshades) is one of the most strongly supported clades within the megadiverse Solanum genus. It comprises 76 globally distributed, non-spiny herbaceous and suffrutescent species. While often erroneously considered poisonous weeds, several species are economically important as orphan crops. The clade is closely related to tomato and potato but, due to a lack of focused breeding efforts, remains a putative reservoir of genetic diversity for crop improvement. Despite this potential, we lack fundamental knowledge on the evolution of the Morelloid clade. The group includes polyploid species with unknown parental origins-likely reflecting reticulate processes such as hybridization, introgression, and associated backcrossing events. Prior analyses have been unable to disentangle these processes, leaving the mechanisms underlying reticulate evolution in the Morelloid clade poorly understood. Here, we use genome skimming to produce a well-supported maximum likelihood plastid phylogeny from complete circularized plastomes and a coalescent-based species tree from combined Angiosperms353 and conserved ortholog set nuclear markers. Our dataset, composed of previously published data and deep genome skimming from herbarium samples, spans 26 Morelloid species. To investigate phylogenetic discordance, we used a nuclear phylogenetic network, multispecies coalescent simulations, a fused rooted nuclear chloroplast tree, and quantification of nuclear gene tree concordance. We show that incongruence between nuclear and plastid trees is pervasive and cannot be explained by incomplete lineage sorting alone. Instead, our results demonstrate that events consistent with repeated chloroplast capture have shaped the reticulate evolutionary history of the clade, especially among African polyploid and Pan-American diploid lineages.

Phylogeny↗

PubMed2026

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans↗

PubMed2026

Beyond antigen matching: compatibility intelligence theory for transfusion as an emergent biological system.

BACKGROUND: Despite major advances in serologic testing, extended phenotyping, and blood group genomics, clinically similar transfusion exposures may result in markedly different immune and clinical outcomes. Existing compatibility strategies do not fully explain this biological variability. OBJECTIVES: To examine transfusion compatibility as an emergent donor-recipient biological state and propose a systems-level conceptual framework that integrates established biological determinants into a testable model for future precision transfusion medicine. METHODS: This narrative review critically synthesizes current evidence from blood group genomics, recipient immunobiology, inflammation, disease-specific biology, transfusion medicine, and computational prediction. The proposed framework distinguishes Compatibility Intelligence Theory (CIT) as a biological interpretation from Precision Transfusion Intelligence (PTI) as its potential clinician-supervised translational application. RESULTS: The review argues that transfusion compatibility is shaped by interactions among donor genetics, recipient immune biology, inflammatory physiology, disease context, transfusion history, and longitudinal adaptation rather than by antigen matching alone. CIT provides an organizational framework for integrating these determinants, whereas PTI describes a possible clinician-supervised translation. To address current feasibility, the revised framework separates variables into routinely measurable, contextually available but incompletely standardized, and research-stage domains, and proposes a staged strategy for deriving rather than assuming their quantitative weights. Any clinical implementation would require comparative validation against current serologic, phenotypic, and genotype-based practice. CONCLUSIONS: Compatibility Intelligence Theory offers a testable systems-level framework for understanding transfusion compatibility without replacing established transfusion practices. The framework is not presented as a ready-to-use score: currently measurable variables can be organized for structured risk review, whereas inflammatory, immunogenetic, and multi-omic inputs require prospective standardization and validation. If future studies demonstrate incremental predictive and patient-centered benefit, CIT-informed PTI could support an adaptive, evidence-based extension of current precision transfusion practice.

Humans↗

PubMed2026

Climate and soil shape Daqu wheat quality and seed microbiome via rhizosphere taxa and microbial assembly.

The grain quality and seed microbiome of Daqu wheat are fundamental determinants of Daqu fermentation performance; however, the mechanisms by which cultivation environments influence these traits via rhizosphere microbial communities remain unclear. Bacterial and fungal communities across the bulk soil-rhizosphere-seed continuum of three wheat cultivars grown in four ecoregions were characterized using absolute quantitative amplicon sequencing. The rhizosphere microbiome was treated as a central intermediary, while the response variables were seed microbial diversity and grain-quality traits, including starch content, protein content, and grain hardness. Twelve physicochemical properties of soil and 11 climatic factors were integrated into a multidimensional association framework. Environmental conditions exerted stronger influences on both seed quality traits and microbial diversity than cultivar identity. Distinct regional signatures were also evident in rhizosphere microbiomes, with environmental gradients explaining community variation more effectively than geographic distance. Bacterial communities exhibited greater sensitivity to environmental fluctuations than fungi. Mantel analyses identified available nitrogen, precipitation, and atmospheric pressure as significant drivers of core rhizosphere taxa (P < 0.05). iCAMP revealed that stochastic processes predominantly governed rhizosphere bacterial assembly, whereas stochastic and deterministic mechanisms jointly shaped fungal assembly. Partial least squares path modeling further uncovered a rhizosphere-mediated environment-seed cascade, wherein sunlight intensity and duration, atmospheric pressure, and soil nitrogen directly or indirectly affected seed wet gluten content, grain hardness, and seed microbial diversity through their influences on rhizosphere microbiota. Rhizosphere bacterial diversity was negatively associated with seed bacterial diversity (path coefficient = -0.118, P < 0.05), indicating that rhizosphere communities may shape seed endophytic bacterial assemblages via environmental filtering and competitive interactions. Collectively, these findings elucidate how environments shape the quality and seed microbiomes of Daqu wheat, providing scientific guidance for optimal site selection and the standardized production of high-quality brewing wheat for industrial Baijiu.

Triticum↗

PubMed2026

Nature-based meaning-focused photography intervention enhances subjective well-being: A three-arm randomized controlled study.

Gaining meaning from nature contact can promote subjective well-being. However, few studies have validated the effectiveness of nature-based meaning interventions in enhancing subjective well-being. This study consisted of a 7-day online intervention to examine the effects of nature-based meaning-focused photography on well-being by comparing a photo-only group, a photo + writing group, and a waiting list control group and how meaning in life mediates the relationship between nature contact and well-being. A pre-registered three-arm randomized controlled trial (groups: photo + writing group vs. photo-only group vs. control group) * (time: pre-test vs. post-test vs. 1-month follow-up) was conducted with 219 college students. In the photo + writing group, participants captured nature scenes and wrote 100-word reflections. The photo-only group only took nature photos. The primary outcomes were meaning in life and well-being, and the secondary outcome was life satisfaction. A conservative Bayesian causal forest analysis based on machine learning was used to detect both treatment and heterogeneous intervention effects. Compared with the control group, the photo + writing group showed positive effects on meaning in life, subjective well-being, and life satisfaction, with average treatment effects of 0.36, 0.27, and 0.66 standard deviations (SD), respectively. The photo-only group also showed generally positive effects on these outcomes, with average treatment effects of 0.27, 0.24, and 0.54 SD, respectively. However, these effects were not sustained after 1 month. The intervention was especially beneficial for participants from lower subjective socioeconomic status, with limited prior nature exposure, or lower baseline psychological well-being. Importantly, enhanced meaning in life helped explain how the intervention improved well-being and life satisfaction. This study also demonstrated that combining nature-based photography and reflective writing can improve well-being.

Humans↗

PubMed2026

Factors associated with successful integration of pharmacists into residential aged care teams: A qualitative study.

BACKGROUND: Australia's Aged Care Onsite Pharmacist program aims to support quality use of medicines in residential aged care homes. This is a novel role introduced into existing teams in a complex environment. Factors associated with successful integration since implementation are currently unknown. AIM: This study aims to explore the perspectives of pharmacists and other stakeholders within aged care homes regarding successful integration of the novel aged care pharmacist service into healthcare teams. METHODS: A qualitative approach, using interpretive descriptive methodology, was used to explore perspectives. Semi-structured focus groups and interviews with pharmacists, nursing and care staff, allied health professionals, general practitioners, residents, and family members were undertaken. Data were collected via Zoom™, audio- and video-recorded, and transcribed verbatim. Two researchers undertook inductive thematic analysis to identify key themes. RESULTS: 30 participants across focus groups, focus-group interviews, interviews, and member-checking processes contributed. An overarching theme of proactivity and showing a genuine interest in others underpinned three key themes. Theme 1: Pharmacists needed to be seen, through physical presence and availability, as well as developing a distinct identity. Theme 2: Pharmacists needed to build trust, through collaboration in real time and demonstrating value. Theme 3: Pharmacists needed to develop an understanding of the aged care home environment, including social and contextual norms, as well as procedures, routines and roles. DISCUSSION: This research complements existing understandings of interprofessional collaboration and teamwork amongst healthcare professionals. Themes were interlinked; we used a sensitising framework, social cognitive theory, to present and explain the findings and interactions that can support pharmacist integration into existing teams. Aged care services should structure onboarding to prioritise early visibility, clarify roles and organisational needs, and foster in-person collaboration. Pharmacists should demonstrate proactivity and an authentic interest in all staff, residents and families.

Humans↗

PubMed2026

Educational interventions to improve medical students' bad news communication skills: A systematic review and meta-analysis.

OBJECTIVES: This systematic review aimed to both determine whether educational interventions improve medical students' ability and/or confidence in Bad News Communication (BNC), as well as assess the relative efficacy of instructional formats. METHODS: Performed according to the PRISMA guidelines, four databases were searched for articles describing education-based interventions to improve medical student's BNC ability and/or confidence, published in English between 2001 and 2024. Data on students' self-reported or observer-assessed level of competence/ability in BNC (primary outcome), and students' self-assessed confidence in BNC skills (secondary outcomes), were analysed. Meta regression explained the influence of several categorical moderators on heterogeneity in relation to intervention effects on competence/ability. RESULTS: 27 studies met the criteria for inclusion in the systematic review and 17 studies for the meta-analysis. Interventions described in controlled studies were associated with a moderate and significant increase in BNC ability (13 data sets; standardized mean difference [SMD] = 1.09, 95% CI = 0.52 - 1.66). Interventions detailed in pre-post design studies were associated with a significant increase in BNC ability (20 data sets; SMD = 0.92, 95% CI = 0.52 - 1.32), and student confidence/comfort in their BNC skills (12 data sets; SMD = 1.16, 95% CI = 0.57 - 1.75). Subgroup analysis demonstrated better skills/competence outcomes in studies that included simulation-based training (SBT). CONCLUSIONS: Educational interventions improve the BNC ability and confidence of medical students. Interventions should include an SBT element as this leads to greater improvements in BNC ability. Further research is needed to determine to what extent these interventions translate to positive patient outcomes. PRACTICE IMPLICATIONS: Diverse educational programme, especially those including simulation-based training, are effective in improving BNC skills, although the longetivity of these improvements is at present unclear. Therefore, we recommend that refresher courses or practice opportunities should be scheduled throughout students' medical education to ensure retention of BNC skills.

Humans↗

PubMed2028

Parental son preference in childhood and sex differences in the risk of cardiovascular disease in middle-aged and older adults.

INTRODUCTION: Sex differences in cardiovascular disease (CVD) risk are examined through biological and clinical factors, with less attention to early-life social exposures. This study examined associations of childhood parental son preference with CVD risk, sex differences, and mediation by modifiable risk factors. METHODS: This cohort analysis included China Health and Retirement Longitudinal Study participants aged ≥45 years without baseline CVD. Parental son preference was assessed retrospectively in 2014; incident CVD was self-reported physician-diagnosed heart disease or stroke through 2020. Sampling-weighted, community-clustered Cox models estimated adjusted hazard ratios (aHRs) and 95% CIs. Sex was prespecified as an effect modifier; mediation by 13 risk factors used inverse-odds-ratio weighting. Data were collected from 2011 to 2020 and analyzed from 2025 to 2026. RESULTS: Among 8,079 participants (mean age, 57.5 years; 4,216 women [52.2%]), 1,820 (22.5%) reported parental son preference. Son preference was associated with higher CVD risk overall (aHR 1.23 [95% CI 1.04, 1.46]) and among women (aHR 1.25 [95% CI 1.03, 1.53]); among men, the estimate was 1.16 (95% CI 0.87, 1.56), with limited heterogeneity by sex (ratio of aHRs 1.06 [95% CI 0.72, 1.58]). Among women, risk was concentrated in the highest paternal (aHR 1.47 [95% CI 1.14, 1.90]) and maternal (aHR 1.50 [95% CI 1.12, 1.99]) preference categories. Modifiable risk factors mediated 5.8% (95% CI 1.9%, 9.7%) of the association among women, mainly through socioeconomic and psychosocial factors. CVD risk was highest with both son preference and high risk-factor burden overall (aHR 1.97 [95% CI 1.43, 2.73]) and among women (aHR 2.23 [95% CI 1.61, 3.10]). CONCLUSIONS: Parental son preference was associated with higher incident CVD risk, with the largest estimates in the highest paternal or maternal categories among women. Modifiable risk factors explained a modest proportion, supporting life-course cardiovascular prevention that considers sex-differentiated childhood environments alongside risk-factor modification.

cardiovascular disease↗

PubMed2026

Critical insights on the application of the theory of planned behaviour to food handlers' food safety practices.

Foodborne diseases remain a significant public health concern, often linked to unsafe food-handling practices. The Theory of Planned Behaviour (TPB) is widely used to predict and explain food safety behaviours, yet its application in this field has not been systematically and in-depth evaluated. This review evaluated how the TPB has been applied to study food handlers' behaviour, focusing on methodological approaches, use of the TACT (Target, Action, Context, and Time) framework, validity, elicitation studies, and reliability. Seventeen studies were included following a systematic search of four databases (Scopus, Web of Science, Wiley Online Library, and Taylor & Francis Online). Data were extracted on behaviour definition, aim of study, main findings, use of indirect and direct TPB measures, use of elicitation studies, internal consistency, content validation, analytical methods used, and any extensions to the original TPB framework. Key elements related to adherence to core TPB principles and measurement practices were extracted using a Checklist. Most studies used direct measures of TPB constructs, and only a few reported procedures for content validation. Considerable variability was found in the reporting of key measurement and psychometric practices. Five studies fully applied the TACT framework, while nine incorporated additional factors such as knowledge and moral norms. Elicitation studies were conducted in five cases where indirect measures were employed. Analytical approaches were mainly based on multiple linear regression, with limited use of more advanced techniques such as structural equation modeling. Twelve studies reported internal consistency results. Overall, the review highlights opportunities to strengthen methodological practices in future TPB research on food safety. Greater attention to conducting and reporting content validation, full application of the TACT framework, reporting of internal consistency, and consistent inclusion of elicitation studies when using indirect measures may enhance transparency, reinforcing the credibility and trustworthiness of research findings. A major methodological limitation of this review was that screening and data extraction were conducted by a single reviewer and no formal quality or risk-of-bias assessment of the included studies was performed. Despite these limitations, the findings provide practical guidance for the development and validation of TPB-based questionnaires and may support more robust food safety research, interventions, and policy initiatives aimed at improving food handlers' practices.

Humans↗

PubMed2026

Extended Long-Term Effects of Cognitive and Aerobic Training on Cognitive Function in Patients With Stress-Related Exhaustion Disorder: A 4.5-Year Follow-Up of a Randomized Controlled Trial.

Stress-related conditions like clinical burnout and exhaustion disorder (ED) are associated with enduring cognitive problems. We have previously demonstrated that the addition of computerised cognitive training (CCT) and aerobic training (AT) to a multimodal rehabilitation programme (MMR) yielded greater improvements in cognitive function compared to MMR alone in patients with ED. These effects were maintained at the 1-year follow-up for CCT, but not for AT. Building on these findings, the present study examined the extended long-term effects of CCT and AT on cognitive function, psychological health, and work ability, 4.5 years after the interventions. Participants were recruited from a stress-rehabilitation clinic and 56 of the initial 132 participants returned for the 4.5-year follow-up. Assessments were conducted before (T1), immediately after (T2), 1-year after (T3) and 4.5-years after (T4) the interventions. Mixed model analyses assessed changes in the intervention groups relative to the control group from T1 to T4, with follow-up comparisons examining within-group stability of outcomes between T3 to T4. The primary outcome was cognitive performance on a global cognitive score. Secondary outcomes included domain-specific cognitive functioning, self-reported cognitive function, psychological health (burnout, depression, anxiety, and fatigue), and work ability. The analysis revealed sustained long-term effects on the global cognitive score, a trained updating task and episodic memory in the CCT group, with stable performance between one- and 4.5-year follow-up. The addition of AT did not yield any extended long-term effects on cognitive performance. Both groups showed extended long-term improvements in self-reported memory problems, although findings were mixed. Extended long-term improvements were observed on burnout for both groups, with additional effects on anxiety and work ability in the AT group. Notably, these effects were not present at the 1-year follow-up and are more plausibly explained by selective attrition rather than a delayed intervention effect. In conclusion, the result indicates that cognitive interventions such as CCT can have lasting positive effects on cognitive function in patients with ED, whereas the long-term psychological effects should be interpreted with caution. TRIAL REGISTRATION: ClinicalTrials.gov: NCT0073772.

Adult↗