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Jonathan P Evans,1 Alexander Smith,2 Chris Gibbons,3 Jordi Alonso,4–6 Jose M Valderas1 1Health Services and Policy Research Group, University of Exeter Medical School, Exeter, UK; 2Aneurin Bevan University Health Board, Clinical Research and Innovation Centre, St Woolos Hospital, Newport, UK; 3Patient-Reported Outcomes, Value and Experience (PROVE) Center Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA; 4IMIM-Hospital del Mar Medical Research Institute, Barcelona, Spain; 5Pompeu Fabra University (UPF), Barcelona, Spain; 6CIBER en Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain Abstract: The interest in patient-reported outcome measures (PROMs) continues to increase as recognition of their potential utility rises in an effort to make health systems more patient-centered. The US National Institutes of Health (NIH) Patient-Reported Outcomes Measurement Information System® (PROMIS®) has used state of the art psychometric and statistical techniques to create a universal PROMs language, with potential application across the whole spectrum of health conditions, languages, and geographic locations. PROMIS offers a versatile platform where specific health domains are assessed using both standardized short forms and computerized adaptive tests, which are automatically tailored to individual patients. The scores of each health domain or a standardized profile of multiple domains are all scored on a common metric scale. PROMIS is increasingly recognized as the international gold standard for patient-centered assessment, although the use of these tools in the UK is limited. In this review, the developmental methodology of the PROMIS is described with discussion of its relevant strengths and limitations for use in the UK. We provide a case study of the largest application of the PROMIS tools in the UK as an example of straightforward integration into health-care research. Barriers to the uptake of PROMIS in the UK include the technology requirement, measurement tradition, and lack of a clear understanding of its benefits, and although potential stakeholders should cautiously consider its use, its impressive potential and increasing international utilization should be recognized. Keywords: outcomes, patient reported outcomes, quality of life, health-related quality of life, PROMIS

Comorbidity is associated with worse health outcomes, more complex clinical management, and increased health care costs. There is no agreement, however, on the meaning of the term, and related constructs, such as multimorbidity, morbidity burden, and patient complexity, are not well conceptualized. In this article, we review definitions of comorbidity and their relationship to related constructs. We show that the value of a given construct lies in its ability to explain a particular phenomenon of interest within the domains of (1) clinical care, (2) epidemiology, or (3) health services planning and financing. Mechanisms that may underlie the coexistence of 2 or more conditions in a patient (direct causation, associated risk factors, heterogeneity, independence) are examined, and the implications for clinical care considered. We conclude that the more precise use of constructs, as proposed in this article, would lead to improved research into the phenomenon of ill health in clinical care, epidemiology, and health services. [ABSTRACT FROM AUTHOR]

Background: Specialist physicians provide a large share of outpatient health care for children and adolescents in the United States, but little is known about the nature and content of these services in the ambulatory setting. Our objective was to quantify and characterize routine and co-managed pediatric healthcare as provided by specialists in community settings.Methods: Nationally representative data were obtained from the National Ambulatory Medical Care Survey for the years 2002-2006. We included office based physicians (excluding family physicians, general internists and general pediatricians), and a representative sample of their patients aged 18 or less. Visits were classified into mutually exclusive categories based on the major reason for the visit, previous knowledge of the health problem, and whether the visit was the result of a referral. Primary diagnoses were classified using Expanded Diagnostic Clusters. Physician report of sharing care for the patient with another physician and frequency of reappointments were also collected.Results: Overall, 41.3% out of about 174 million visits were for routine follow up and preventive care of patients already known to the specialist. Psychiatry, immunology and allergy, and dermatology accounted for 54.5% of all routine and preventive care visits. Attention deficit disorder, allergic rhinitis and disorders of the sebaceous glands accounted for about a third of these visits. Overall, 73.2% of all visits resulted in a return appointment with the same physician, in half of all cases as a result of a routine or preventive care visit.Conclusion: Ambulatory office-based pediatric care provided by specialists includes a large share of non referred routine and preventive care for common problems for patients already known to the physician. It is likely that many of these services could be managed in primary care settings, lessening demand for specialists and improving coordination of care. [ABSTRACT FROM AUTHOR]

Quality-of-life (QOL) instruments used in clinical research can provide important evidence to inform decisions about alternative treatments. This is particularly true when patients, such as those with cancer who are contemplating toxic chemotherapy, face tradeoffs between quantity of life and QOL or when the primary goal of therapy is to improve how patients feel. Surrogate measures (cardiac function, exercise capacity, bone density, tumor size) are inadequate substitutes for direct measurement of QOL. Quality-of-life measures will be most valuable when they comprehensively measure aspects of QOL that are both important to patients and likely to be influenced by therapy, when the QOL measurement instruments are valid (measuring what is intended) and responsive (able to detect all important changes, even if small), and when the results are readily interpretable (determining whether treatment-related changes are trivial, small but important, or large). Researchers are finding new, imaginative ways to help clinicians understand the magnitude of treatment impact on QOL. Additionally, QOL measures may be useful in clinical practice. Recent results from well-designed randomized controlled trials suggest that information on patient QOL provided to clinicians might, in some circumstances, result in benefits for these patients. Further investigation is warranted to confirm these observations and to define the particular combination of methods and settings most likely to yield important benefits. [ABSTRACT FROM AUTHOR]

Background: Multimorbidity, the presence of two or more conditions in one person, is common but studies are often limited to observational data and single datasets. We address this gap by integrating large-scale primary-care and genetic data from multiple studies to interrogate multimorbidity patterns and producing digital resources to support future research., Methods: We defined chronic, common, and heritable conditions in individuals aged ≥65 years, using two large primary-care databases [CPRD (UK) N = 2,425,014 and SIDIAP (Spain) N = 1,053,640], and estimated heritability using the same definitions in UK Biobank (N = 451,197). We used logistic regression to estimate the co-occurrence of pairs of conditions in the primary care data. Linkage disequilibrium score regression was used to estimate genetic similarity between pairs of conditions. Meta-analyses were conducted across databases, and up to three sources of genetic data, for each pair of conditions. We classified pairs of conditions as across or within-domain based on the international classification of disease., Findings: We identified 72 chronic conditions, with 43.6% of 2546 pairs showing higher co-occurrence than chance in primary care and evidence of shared genetics. Many across-domain pairs exhibited substantial shared genetics (e.g., iron deficiency anaemia and peripheral arterial disease: genetic correlation R g  = 0.45 [95% Confidence Intervals 0.27:0.64]). 33 pairs displayed negative genetic correlations, such as skin cancer and rheumatoid arthritis (R g  = -0.14 [-0.21:-0.06]), due to potential adverse drug effects. Discordance between genetic and primary care data was also observed, e.g., abdominal aortic aneurysm and bladder cancer co-occurred in primary care but were not genetically correlated (Odds-Ratio = 2.23 [2.09:2.37], R g  = 0.04 [-0.20:0.28]) and schizophrenia and fibromyalgia were less likely to co-occur together in primary care but were positively genetically correlated (OR = 0.84 [0.75:0.94], R g  = 0.20 [0.11:0.29])., Interpretation: Most pairs of chronic conditions show evidence of shared genetics, and co-occurrence in primary care, suggesting shared mechanisms. The identified patterns of shared genetics, negative correlations and discordance between genetic and observational data provide a foundation for future multimorbidity research., Funding: UK Medical Research Council [MR/W014548/1]., Competing Interests: Declaration of interests ARL is now an employee of AstraZeneca and has interests in the company. The work undertaken here was prior to his appointment. SK's group has received funding support from Amgen BioPharma outside of this work. JB is a part time employee of Novo Nordisk Research Centre Oxford, limited, unrelated to this work. TF has consulted for several pharmaceutical companies. All other authors have no disclosures to declare., (Copyright © 2025. Published by Elsevier B.V.)

Introduction: The effective management of depression, anxiety, and other forms of psychological distress depends on individuals' readiness to seek and accept help for their mental suffering. Understanding which personality traits relate to help-seeking can help better tailor mental healthcare to individual needs. However, findings regarding associations of personality traits with help-seeking have been inconsistent., Methods: This systematic review and meta-analysis focused on English-language research studies on the association of personality (encompassing personality disorders, Five Factor -Big Five- dimensions, and other measures of personality) with depression, anxiety, or unspecified psychological distress in adults aged 18 years and older. Procedures followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The search strategy included two concepts: personality and help-seeking and was carried out on PubMed, Embase, Web of Science, and PsycINFO. Reference tracking and searches on Google Scholar were additionally performed. Sufficiently homogeneous subsections were analyzed by meta-analysis., Results: A total of 48 studies described in 47 records reported on the association between personality and help-seeking. Nine assessed personality disorders, 29 Five Factor dimensions, and 13 other personality constructs. Twenty-three studies investigated attitudes towards help-seeking while 25 studies investigated help-seeking behaviors. Of the studies investigating behavior, three used external observations, the rest relied on self-reports/clinician-administered questionnaires. Evidence highlighted a dissociation between attitudes and behavior for schizotypal and borderline personality disorders, and neuroticism, which displayed negative help-seeking attitudes but more help-seeking behavior. By contrast, paranoid, schizoid and obsessive-compulsive personality disorders related to both negative help-seeking attitudes and behavior across studies. Limited evidence linked extraversion to social support seeking and conscientiousness to care seeking behaviors. Meta-analyses on the Five Factor dimensions and help-seeking attitudes supported robust negative associations with neuroticism, as well as positive associations with agreeableness, albeit less reliably. Other personality traits mostly corroborated the above relationships, while also contributing new perspectives, such as help-seeking behavior's negative associations with reality weakness and cynicism, and positive associations with abasement and rigidity., Discussion: Future research should investigate help-seeking behavior using external observations and longitudinal designs. Assessing personality in clinical settings can help identify populations at risk of keeping to themselves when mentally distressed., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors AM and JV declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2025 Szücs, Lam, Tang, Zhou, Lazarus, Maier and Valderas.)

Background: Little is known about the practices and resources employed by general practitioners (GPs) in Singapore to manage late-life depression. As the country is stepping up its efforts to promote collaborative care across community mental health and geriatric care, understanding GPs' current practices when managing late-life depression appears timely., Methods: This qualitative descriptive study explored the perspectives on late-life depression of 28 private GPs practicing in Singapore through online semi-structured group and individual interviews. GPs were purposively sampled across age, gender, and ethnicity. Analysis followed a reflexive thematic approach and focused on physician- and system-related factors., Findings: Clinical instinct, experience, and knowledge of appropriate resources for specific patients played an important role for GPs during late-life depression care. GPs paid particular attention to communicating with patients tactfully during initial assessments and diagnosis, although some GPs chose to be upfront with patients with whom they had already established rapport. Using non-English languages when communicating about depression could mitigate stigma in some cases but added confusion in others. GPs relied primarily on their own professional support network to manage late-life depression. Although GPs acknowledged the usefulness of public care services, they felt that collaborative care was hindered by a lack of efficient communication channels between providers and appropriate financial coverage to coordinate the frequently complex care of depressed older adults., Interpretation: Current resources and practices to manage late-life depression vary greatly between private GPs in Singapore. This needs to be considered during ongoing reforms to achieve effective collaborative care., Funding: This work was funded by the Division of Family Medicine Research Capabilities Building Budget under the project "Technology and Compassion: Improving Patient Outcomes Through Data Analytics and Patients' Voice in Primary Care" [NUHSRO/2022/049/NUSMed/DFM]., Competing Interests: The authors have no conflicting interests to declare., (© 2024 The Author(s).)

Objectives: Health state utility (HSU) instruments for calculating quality-adjusted life years, such as the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Utility - Core 10 Dimensions (QLU-C10D), derived from the EORTC QLQ-30 questionnaire, the Patient-Reported Outcome Measurement Information System (PROMIS) preference score (PROPr), and the EuroQoL-5-Dimensions-5-Levels (EQ-5D-5L), yield different HSU values due to different modeling and different underlying descriptive scales. For example the QLU-C10D includes cancer-relevant dimensions such as nausea. This study aimed to investigate how these differences in descriptive scales contribute to differences in HSU scores by comparing scores of cancer patients receiving chemotherapy to those of the general population., Study Design and Setting: EORTC QLU-C10D, PROPr, and EQ-5D-5L scores were obtained for a convenience sample of 484 outpatients of the Department of Oncology, Charité - Universitätsmedizin Berlin, Germany. Convergent and known group's validity were assessed using Pearson's correlation and intraclass correlation coefficients (ICC). We assessed each descriptive dimension score's discriminatory power and compared them to those of the general population (n > 1000) using effect size (ES; Cohen's d) and area under the curve (AUC)., Results: The mean scores of QLU-C10D (0.64; 95% CI 0.62-0.67), PROPr (0.38; 95% CI 0.36-0.40), and EQ-5D-5L (0.72; 95% CI 0.70-0.75) differed significantly, irrespective of sociodemographic factors, condition, or treatment. Conceptually similar descriptive scores as obtained from the HSU instruments showed varying degrees of discrimination in terms of ES and AUC between patients and the general population. The QLU-C10D and its dimensions showed the largest ES and AUC., Conclusion: The QLU-C10D and its domains distinguished best between health states of the two populations, compared to the PROPr and EQ-5D-5L. As the EORTC Core Quality of Life Questionnaire (QLQ-C30) is widely used in clinical practice, its data are available for economic evaluation., Plain Language Summary: The assessment of dimensions of health-related quality of life (HRQoL), such as physical functioning or depression, is important to cancer patients and physicians for treatment and side effect monitoring. Descriptive HRQoL is measured by patient-reported outcomes measures (PROM). The European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 questionnaire and the Patient-Reported Outcome Measurement Information System (PROMIS) are the most common PROM in the clinical HRQoL assessment. In recent years, multidimensional preference-based HRQoL measures were developed using these PROM as dimensions. These preference-based measures, also referred to as health state utility (HSU) scores, are needed for economic evaluations of treatments. The QLQ-C30's corresponding HSU score is the Quality of Life Utility measure-Core 10 Dimensions (QLU-C10D), and PROMIS' HSU score is the PROMIS preference score (PROPr). Both new HSU scores are frequently compared to the well-established EuroQoL-5-dimensions-5-levels (EQ-5D-5L). They all conceptualize HSU differently, as they assess different dimensions of HRQoL und use different models. Both the QLU-C10D and the PROPr have thus shown systematic differences to the EQ-5D-5L but these were largely consistent across the subgroups. Convergent and known groups validity can therefore be considered established. However, as HSU is a multidimensional construct, it remains unclear how differences in its dimensions, for example, its descriptive scales, contribute to differences in HSU scores. This is of importance as it is the descriptive scales that measure clinical HRQoL. We investigated this question by assessing each dimension's ability to distinguish between a sample of 484 cancer patients and the German general population. We could show that the ability to distinguish depended on the domain: for example, for depression, the QLU-C10D and EQ-5D-5L distinguished clearer, while for physical function, PROMIS did. Overall, the QLU-C10D and its dimensions distinguish best between cancer patients and general population., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Competing Interests: The authors have no conflicting interests to declare.