Tag: pubmed

Elife. 2024 May 16;12:RP88616. doi: 10.7554/eLife.88616.

ABSTRACT

Zoonotic disease dynamics in wildlife hosts are rarely quantified at macroecological scales due to the lack of systematic surveys. Non-human primates (NHPs) host Plasmodium knowlesi, a zoonotic malaria of public health concern and the main barrier to malaria elimination in Southeast Asia. Understanding of regional P. knowlesi infection dynamics in wildlife is limited. Here, we systematically assemble reports of NHP P. knowlesi and investigate geographic determinants of prevalence in reservoir species. Meta-analysis of 6322 NHPs from 148 sites reveals that prevalence is heterogeneous across Southeast Asia, with low overall prevalence and high estimates for Malaysian Borneo. We find that regions exhibiting higher prevalence in NHPs overlap with human infection hotspots. In wildlife and humans, parasite transmission is linked to land conversion and fragmentation. By assembling remote sensing data and fitting statistical models to prevalence at multiple spatial scales, we identify novel relationships between P. knowlesi in NHPs and forest fragmentation. This suggests that higher prevalence may be contingent on habitat complexity, which would begin to explain observed geographic variation in parasite burden. These findings address critical gaps in understanding regional P. knowlesi epidemiology and indicate that prevalence in simian reservoirs may be a key spatial driver of human spillover risk.

PMID:38753426 | DOI:10.7554/eLife.88616

J Dent Educ. 2024 May 16. doi: 10.1002/jdd.13570. Online ahead of print.

ABSTRACT

INTRODUCTION: Effective pain control is crucial in dental practice; thus, local anesthetic techniques have been extensively taught. The Halstead technique is the most commonly used inferior alveolar nerve block despite its relatively high failure rate. On the other hand, the Vazirani‒Akinosi technique (VAT) is less commonly taught. This study evaluated changes in final-year students’ perceptions of VAT after a period of active learning.

METHODS: This prospective randomized study was performed in 2022 and included fifth-year dental students (n = 91). The study group (n = 49) received practical VAT training during oral surgery internships, whereas the control group (n = 42) did not. A Likert-scale questionnaire assessed students’ perceptions, theoretical knowledge, and difficulty levels. An independent sample t-test was used for comparison and the statistical significance level was set at p < 0.05.

RESULTS: The survey response rate was 100%. Statistical analysis revealed significant differences between the groups for seven of the 12 questionnaire statements (p < 0.05). Overall, perception scores favored the study group, indicating a more positive response. The statements related to theoretical knowledge, except for one statement, showed no significant differences (p > 0.05).

CONCLUSION: Practical training significantly improved students’ perceptions of VAT, demonstrating the importance of active learning in dental education. Faculties should integrate active learning methods to enhance students’ clinical skills and prepare them for professional practice.

PMID:38753425 | DOI:10.1002/jdd.13570

JMIR Hum Factors. 2024 May 16;11:e50098. doi: 10.2196/50098.

ABSTRACT

BACKGROUND: Digital interventions are gaining increasing interest due to their structured nature, ready availability, and self-administered capabilities. Perinatal women have expressed a desire for such interventions. In this regard, behavioral activation interventions may be particularly suitable for digital administration.

OBJECTIVE: This study aims to exploratorily investigate and compare the feasibility of the internet-based self-help guided versus unguided version of the Brief Behavioral Activation Treatment for Depression-Revised, an empirically supported in-person behavioral activation protocol, targeting pregnant women with subclinical depression symptoms. A user-centered design is used, whereby data are collected with the intent of evaluating how to adjust the intervention in line with pregnant women’s needs. Usability and user engagement were evaluated.

METHODS: A total of 11 Italian pregnant women with subclinical depressive symptoms based on the Patient Health Questionnaire-9 (scoring<15) participated in this study; of them, 6 (55%) women were randomly assigned to the guided group (age: mean 32.17, SD 4.36 years) and 5 (45%) to the unguided group (age: mean 31, SD 4.95 years). The Moodle platform was used to deliver the interventions in an e-learning format. It consisted of 6 core modules and 3 optional modules; the latter aimed at revising the content of the former. In the guided group, each woman had weekly chats with their assigned human guide to support them in the homework revisions. The intervention content included text, pictures, and videos. Semistructured interviews were conducted, and descriptive statistics were analyzed.

RESULTS: Collectively, the data suggest that the guided intervention was better accepted than the unguided one. However, the high rates of dropout (at T6: guided group: 3/6, 50%; unguided: 4/5, 80%) suggest that a digital replica of Behavioral Activation Treatment for Depression-Revised may not be feasible in an e-learning format. The reduced usability of the platform used was reported, and homework was perceived as too time-consuming and effort-intensive. Moreover, the 6 core modules were deemed sufficient for the intervention’s goals, suggesting that the 3 optional modules could be eliminated. Nevertheless, participants from both groups expressed satisfaction with the content and found it relevant to their pregnancy experiences.

CONCLUSIONS: Overall, the findings have emphasized both the intervention’s merits and shortcomings. Results highlight the unsuitability of replicating an in-person protocol digitally as well as of the use of nonprofessional tools for the implementation of self-help interventions, ultimately making the intervention not feasible. Pregnant women have nonetheless expressed a desire to receive psychological support and commented on the possibilities of digital psychosocial supports, particularly those that are app-based. The information collected and the issues identified here are important to guide the development and co-design of a more refined platform for the intervention deployment and to tailor the intervention’s content to pregnant women’s needs.

PMID:38753421 | DOI:10.2196/50098

JMIR Ment Health. 2024 May 16;11:e49916. doi: 10.2196/49916.

ABSTRACT

BACKGROUND: The care environment significantly influences the experiences of patients with severe mental illness and the quality of their care. While a welcoming and stimulating environment enhances patient satisfaction and health outcomes, psychiatric facilities often prioritize staff workflow over patient needs. Addressing these challenges is crucial to improving patient experiences and outcomes in mental health care.

OBJECTIVE: This study is part of the Patient-Reported Experience Measure for Improving Quality of Care in Mental Health (PREMIUM) project and aims to establish an item bank (PREMIUM-CE) and to develop computerized adaptive tests (CATs) to measure the experience of the care environment of adult patients with schizophrenia, bipolar disorder, or major depressive disorder.

METHODS: We performed psychometric analyses including assessments of item response theory (IRT) model assumptions, IRT model fit, differential item functioning (DIF), item bank validity, and CAT simulations.

RESULTS: In this multicenter cross-sectional study, 498 patients were recruited from outpatient and inpatient settings. The final PREMIUM-CE 13-item bank was sufficiently unidimensional (root mean square error of approximation=0.082, 95% CI 0.067-0.097; comparative fit index=0.974; Tucker-Lewis index=0.968) and showed an adequate fit to the IRT model (infit mean square statistic ranging between 0.7 and 1.0). DIF analysis revealed no item biases according to gender, health care settings, diagnosis, or mode of study participation. PREMIUM-CE scores correlated strongly with satisfaction measures (r=0.69-0.78; P<.001) and weakly with quality-of-life measures (r=0.11-0.21; P<.001). CAT simulations showed a strong correlation (r=0.98) between CAT scores and those of the full item bank, and around 79.5% (396/498) of the participants obtained a reliable score with the administration of an average of 7 items.

CONCLUSIONS: The PREMIUM-CE item bank and its CAT version have shown excellent psychometric properties, making them reliable measures for evaluating the patient experience of the care environment among adults with severe mental illness in both outpatient and inpatient settings. These measures are a valuable addition to the existing landscape of patient experience assessment, capturing what truly matters to patients and enhancing the understanding of their care experiences.

TRIAL REGISTRATION: ClinicalTrials.gov NCT02491866; https://clinicaltrials.gov/study/NCT02491866.

PMID:38753416 | DOI:10.2196/49916

Psychol Aging. 2024 May 16. doi: 10.1037/pag0000807. Online ahead of print.

ABSTRACT

The present study aimed to characterize profiles of cognitive aging and how these can be predicted from interindividual differences in demographic, lifestyle, health, and genetic factors. The participants were 1,966 older adults (mean baseline age = 71.6 years; 62.9% female), free from dementia at baseline and with at least two cognitive assessments over the 15-year follow-up, from the population-based Swedish National Study on Aging and Care in Kungsholmen. The cognitive assessment comprised tests of semantic and episodic memory, letter and category fluency, perceptual speed, and executive function. First, we estimated the level and change within each of the cognitive domains with linear mixed effect models, based on which we grouped our sample into participants with “maintained high cognition,” “moderate cognitive decline,” or “accelerated cognitive decline.” Second, we analyzed determinants of group membership within each cognitive domain with multinomial logistic regression. Third, group memberships within each cognitive domain were used to derive general cognitive aging profiles with latent class analysis. Fourth, the determinants of these profile memberships were analyzed with multinomial logistic regression. Follow-up analyses targeted profiles and predictors specifically related to the rate of cognitive change. We identified three latent profiles of overall cognitive performance during the follow-up period with 31.6% of the sample having maintained high cognition, 50.6% having moderate cognitive decline, and 17.8% having accelerated cognitive decline. In multiadjusted analyses, maintained high cognition was predicted by female sex, higher education, and faster walking speed. Smoking, loneliness, and being an ε4 carrier were associated with a lower likelihood of maintained high cognition. Higher age, diagnosis of diabetes, depression, and carrying the apolipoprotein E ε4 allele increased the likelihood of accelerated cognitive decline. Factors at baseline that could significantly predict profile membership within the specific cognitive domains included age, sex, years of education, walking speed, diabetes, and the ε4 allele. Of note, these factors differed across cognitive domains. In sum, we identified demographic, lifestyle, health, and genetic factors of interindividual differences in domain-specific and general cognitive aging profiles, some of which are modifiable. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

PMID:38753406 | DOI:10.1037/pag0000807

Stat Appl Genet Mol Biol. 2024 May 16;23(1). doi: 10.1515/sagmb-2023-0034. eCollection 2024 Jan 1.

ABSTRACT

Somatic mutations in cancer can be viewed as a mixture distribution of several mutational signatures, which can be inferred using non-negative matrix factorization (NMF). Mutational signatures have previously been parametrized using either simple mono-nucleotide interaction models or general tri-nucleotide interaction models. We describe a flexible and novel framework for identifying biologically plausible parametrizations of mutational signatures, and in particular for estimating di-nucleotide interaction models. Our novel estimation procedure is based on the expectation-maximization (EM) algorithm and regression in the log-linear quasi-Poisson model. We show that di-nucleotide interaction signatures are statistically stable and sufficiently complex to fit the mutational patterns. Di-nucleotide interaction signatures often strike the right balance between appropriately fitting the data and avoiding over-fitting. They provide a better fit to data and are biologically more plausible than mono-nucleotide interaction signatures, and the parametrization is more stable than the parameter-rich tri-nucleotide interaction signatures. We illustrate our framework in a large simulation study where we compare to state of the art methods, and show results for three data sets of somatic mutation counts from patients with cancer in the breast, Liver and urinary tract.

PMID:38753402 | DOI:10.1515/sagmb-2023-0034

Sch Psychol. 2024 May 16. doi: 10.1037/spq0000628. Online ahead of print.

ABSTRACT

Initially excluded from many evaluations of education research, single-case designs have recently received wider acceptance within and beyond special education. The growing approval of single-case design has coincided with an increasing departure from convention, such as the visual analysis of results, and the emphasis on effect sizes comparable with those associated with group designs. The use of design-comparable effect sizes by the What Works Clearinghouse has potential implications for the experimental literature in special education, which is largely composed of single-case designs that may not meet the assumptions required for statistical analysis. This study examined the compatibility of single-case design studies appearing in 33 special education journals with the design-comparable effect sizes and related assumptions described by the What Works Clearinghouse. Of the 1,425 randomly selected single-case design articles published from 1999 to 2021, 59.88% did not satisfy assumptions related to design, number of participants, or treatment replications. The rejection rate varied based on journal emphasis, with publications dedicated to students with developmental disabilities losing the largest proportion of articles. A description of the results follows a discussion of the implications for the interpretation of the evidence base. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

PMID:38753395 | DOI:10.1037/spq0000628

Psychol Methods. 2024 May 16. doi: 10.1037/met0000664. Online ahead of print.

ABSTRACT

Latent change score (LCS) models within a continuous-time state-space modeling framework provide a convenient statistical approach for analyzing developmental data. In this study, we evaluate the robustness of such an approach in the context of accelerated longitudinal designs (ALDs). ALDs are especially interesting because they imply a very high rate of planned data missingness. Additionally, most longitudinal studies present unexpected participant attrition leading to unplanned missing data. Therefore, in ALDs, both sources of data missingness are combined. Previous research has shown that ALDs for developmental research allow recovering the population generating process. However, it is unknown how participant attrition impacts the model estimates. We have three goals: (a) to evaluate the robustness of the group-level parameter estimates in scenarios with empirically plausible unplanned data missingness; (b) to evaluate the performance of Kalman scores (KS) imputations for individual data points that were expected but unobserved; and (c) to evaluate the performance of KS imputations for individual data points that were outside the age ranged observed for each case (i.e., to estimate the individual trajectories for the complete age range under study). In general, results showed lack of bias in the simulated conditions. The variability of the estimates increased with lower sample sizes and higher missingness severity. Similarly, we found very accurate estimates of individual scores for both planned and unplanned missing data points. These results are very important for applied practitioners in terms of forecasting and making individual-level decisions. R code is provided to facilitate its implementation by applied researchers. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

PMID:38753382 | DOI:10.1037/met0000664

JCO Clin Cancer Inform. 2024 May;8:e2300186. doi: 10.1200/CCI.23.00186.

ABSTRACT

PURPOSE: Real-world evidence (RWE)-derived from analysis of real-world data (RWD)-has the potential to guide personalized treatment decisions. However, because of potential confounding, generating valid RWE is challenging. This study demonstrates how to responsibly generate RWE for treatment decisions. We validate our approach by demonstrating that we can uncover an existing adjuvant chemotherapy (ACT) guideline for stage II and III colon cancer (CC)-which came about using both data from randomized controlled trials and expert consensus-solely using RWD.

METHODS: Data from the population-based Netherlands Cancer Registry from a total of 27,056 patients with stage II and III CC who underwent curative surgery were analyzed to estimate the overall survival (OS) benefit of ACT. Focusing on 5-year OS, the benefit of ACT was estimated for each patient using G-computation methods by adjusting for patient and tumor characteristics and estimated propensity score. Subsequently, on the basis of these estimates, an ACT decision tree was constructed.

RESULTS: The constructed decision tree corresponds to the current Dutch guideline: patients with stage III or stage II with T stage 4 should receive surgery and ACT, whereas patients with stage II with T stage 3 should only receive surgery. Interestingly, we do not find sufficient RWE to conclude against ACT for stage II with T stage 4 and microsatellite instability-high (MSI-H), a recent addition to the current guideline.

CONCLUSION: RWE, if used carefully, can provide a valuable addition to our construction of evidence on clinical decision making and therefore ultimately affect treatment guidelines. Next to validating the ACT decisions advised in the current Dutch guideline, this paper suggests additional attention should be paid to MSI-H in future iterations of the guideline.

PMID:38753347 | DOI:10.1200/CCI.23.00186

JAMA Oncol. 2024 May 16. doi: 10.1001/jamaoncol.2024.1129. Online ahead of print.

ABSTRACT

IMPORTANCE: Two prominent organizations, the American Society of Clinical Oncology and the National Quality Forum (NQF), have developed a cancer quality metric aimed at reducing systemic anticancer therapy administration at the end of life. This metric, NQF 0210 (patients receiving chemotherapy in the last 14 days of life), has been critiqued for focusing only on care for decedents and not including the broader population of patients who may benefit from treatment.

OBJECTIVE: To evaluate whether the overall population of patients with metastatic cancer receiving care at practices with higher rates of oncologic therapy for very advanced disease experience longer survival.

DESIGN, SETTING, AND PARTICIPANTS: This nationwide population-based cohort study used Flatiron Health, a deidentified electronic health record database of patients diagnosed with metastatic or advanced disease, to identify adult patients (aged ≥18 years) with 1 of 6 common cancers (breast cancer, colorectal cancer, non-small cell lung cancer [NSCLC], pancreatic cancer, renal cell carcinoma, and urothelial cancer) treated at health care practices from 2015 to 2019. Practices were stratified into quintiles based on retrospectively measured rates of NQF 0210, and overall survival was compared by disease type among all patients treated in each practice quintile from time of metastatic diagnosis using multivariable Cox proportional hazard models with a Bonferroni correction for multiple comparisons. Data were analyzed from July 2021 to July 2023.

EXPOSURE: Practice-level NQF 0210 quintiles.

MAIN OUTCOME AND MEASURE: Overall survival.

RESULTS: Of 78 446 patients (mean [SD] age, 67.3 [11.1] years; 52.2% female) across 144 practices, the most common cancer types were NSCLC (34 201 patients [43.6%]) and colorectal cancer (15 804 patients [20.1%]). Practice-level NQF 0210 rates varied from 10.9% (quintile 1) to 32.3% (quintile 5) for NSCLC and 6.8% (quintile 1) to 28.4% (quintile 5) for colorectal cancer. No statistically significant differences in survival were observed between patients treated at the highest and the lowest NQF 0210 quintiles. Compared with patients seen at practices in the lowest NQF 0210 quintiles, the hazard ratio for death among patients seen at the highest quintiles varied from 0.74 (95% CI, 0.55-0.99) for those with renal cell carcinoma to 1.41 (95% CI, 0.98-2.02) for those with urothelial cancer. These differences were not statistically significant after applying the Bonferroni-adjusted critical P = .008.

CONCLUSIONS AND RELEVANCE: In this cohort study, patients with metastatic or advanced cancer treated at practices with higher NQF 0210 rates did not have improved survival. Future efforts should focus on helping oncologists identify when additional therapy is futile, developing goals of care communication skills, and aligning payment incentives with improved end-of-life care.

PMID:38753341 | DOI:10.1001/jamaoncol.2024.1129