Yoxas/statistical_literacy huggingface dataset:
Anxiety and depression are the most prevalent mental disorders associated with aging. Positive thinking training is a way to help older adults cope with anxiety and depression and increase their happiness. This study aimed to determine the effect of positive thinking training on anxiety and happiness among older adults. This quasi-experimental study was conducted with 48 older adults referred to two comprehensive health service facilities in the southeastern Iranian province of Kerman. The intervention (n = 24) and control (n = 24) groups were randomly assigned from a convenience sample of older adults. The intervention group attended eight two-hour training sessions on positive thinking. Data were collected before and one month after the positive thinking training using Beck Anxiety Inventory and Oxford Happiness Inventory. All statistical procedures were performed in SPSS software (version 22), with the significance level set to P = 0.05. Before the positive thinking program was delivered, the mean anxiety scores in the intervention and control groups were 13.98 ± 8.61 and 19.25 ± 11.67, respectively. After the intervention was completed, the mean scores for the intervention and control groups were 4.50 ± 4.07 and 15.54 ± 9.04, indicating a significant reduction in anxiety among intervention group participants (t = -5.45, P < 0.001). The mean baseline happiness scores in the intervention and control groups were 26.58 ± 12.40 and 37.91 ± 5.57, respectively, which changed to 62.91 ± 4.66 and 35.62 ± 10.62 at the post-test. Positive thinking training improved happiness in a significant manner (t = -4.08, P < 0.001). Results revealed that positive thinking training decreased anxiety and enhanced happiness among older adults. Given the growing elderly population, clinical managers, clinical specialists, nurses in health care centers, and those involved in elderly care facilities can benefit from this non-pharmacological treatment program for older adults suffering from anxiety and depression. It is suggested that preventive programs based on positive psychology be developed to aid in the prevention of people's declining happiness and increasing anxiety as they age.
Anxiety and depressive disorders are characterized with frequent co-occurance. Depression comorbid to anxiety disorder increases severity of main disorder, aggravates it`s clinical course, worsens social functioning of the patients and decreases life quality, results resistance to therapy and increases the probability of suicidal attempts. In patients with depressive disorders onset of anxiety disorder results increased severity of disorder and decrease in quality of remission. There are different opinions on nature and phenomenology of comorbidity of anxiety and depressive disorders. There are biological and psychological factors of risk of comorbidity. Some scientists consider comorbid disorders to be independent and not to effect each other; others pay attention at common anatomic basis of comorbid disorders, which explains manifestation of comorbid disorder. Hierarchical analysis of clinical features of comorbid disorders favors nosological approach to understanding of comorbidity, and implicates the need for inclusion of transdiagnostic elements. Some authors consider comorbid disorders to be separate type of disorder, characterized with special dynamics of syndromes which reveals transformation of one disorder into another. Phenomenon of comorbidity can be described as part of concept of disease spread which estimates important role of bridge psychic states. Considering clinical features of comorbid disorders, difficulties of their therapy based on concepts of phenomenology of comorbid depressive and anxiety disorders recommendations on prevention, early diagnosing and managing of comorbid disorders were elaborated. Psychotherapy (including CBT, which demonstrated high efficiency) is an essential element of treatment of comorbid depressive and anxiety disorders. Psychotherapy is supposed to be correcting personality traits, cognitive mistakes and maladaptive strategies of coping with disorder, which support the comorbidity.
Anxiety disorder is one of the most common mental disorders. This cross-sectional research aimed to determine anxiety literacy (A-Lit) psychometric properties among the Iranian population in 2022. This research was conducted on 690 people in Iran in 2022. In this study, people were selected by proportional stratified sampling, and the validity and reliability of the A-Lit designed by Griffiths were assessed. Validity of A-Lit was assessed by face validity, content validity, and confirmatory factor analysis. Reliability of A-Lit was evaluated by the McDonald's omega coefficient, Cronbach's alpha coefficient, and test- retest. In analytical sections, the tests of One-way ANOVA, Chi-squared test, and independent samples t-test were used. The rates of S-CVI/Ave and CVR for A-Lit were 0.922 and 0.774, respectively. In confirmatory factor analysis, three items were deleted because the factor loading was less than 0.4, and goodness-of-fit indexes (Some of goodness-of-fit indexes: χ2/df = 4.175, GFI: 0.909, RMSEA = 0.068, PCFI = 0.745, AGFI = 0.883) were confirmed as the final model with 19 items. For all items, the Cronbach's alpha coefficient was 0.832, the McDonald's omega coefficient was 0.835, and the intraclass correlation coefficient was 0.874. According to the results of this study, 1.3% (n = 9) did not answer any questions correctly and 8.4% (n = 58) were able to answer 1-6 questions correctly. Approximately 72% (n = 495) were able to answer 7-12 questions, and eventually only 18.6% (n = 128) were able to answer 13 questions and more. There was a significant relationship between sex, age group, occupation status, marital status, and get information related to mental illness with A-Lit level (p < 0.05). The Persian version of A-Lit was confirmed with 19 items, and this scale is a reliable tool for measuring A-Lit in the general population. The results also showed that a few people have a higher level of anxiety literacy and that educational and intervention programs need to be designed and implemented for the public population.
Anxiety disorders represent the single largest mental health problem in the United States [Greenberg et al., 1999. J Clin Psychiatry 60:427-435; Rice and Miller, 1998. Br J Psychiatry 173:4-9]. However most individuals with anxiety disorders never seek treatment [Henderson et al., 2002. Can J Psychiatry 47:819-824; Mojtabai et al., 2002. Arch Gen Psychiatry 59:77-84; Roness et al., 2005. Acta Psychiatr Scand 111:51-58]. Deficits in the ability to recognize anxiety disorders and beliefs about them, (i.e., "mental health literacy") may contribute to low levels of help seeking. Survey data assessing mental health literacy for multiple anxiety disorders and for depression were collected from 284 undergraduate students enrolled in psychology courses at a public university in the United States. Specifically, respondents were presented with vignettes portraying individuals experiencing various forms of mental illness and were asked to label the disorder, its cause and whether or not they would recommend treatment. Findings showed that social phobia and obsessive compulsive disorder (OCD) were associated with recognition rates that were generally high and similar to depression (approximately 80%). In contrast, less than half of the respondents labeled panic disorder or generalized anxiety disorder (GAD) correctly. Symptoms of OCD were attributed to mental illness by approximately 50% of respondents, but such attributions were rare for the other anxiety disorders studied (<12%). Finally, data on help-seeking recommendations suggested that such recommendations are far from universal and varied between different anxiety disorders and according to perceptions of the causes of symptoms. Given that the current sample was well-educated young adults, mental health literacy of the general public may be even lower.
Aphasia is among the most debilitating of symptoms affecting stroke survivors. Speech and language therapy (SLT) is effective, but many hours of practice are required to make clinically meaningful gains. One solution to this 'dosage' problem is to automate therapeutic approaches via self-supporting apps so people with aphasia (PWA) can amass practice as it suits them. However, response to therapy is variable and no clinical trial has yet identified the key brain regions required to engage with word-retrieval therapy. Between Sep 7, 2020 and Mar 1, 2022 at University College London in the UK, we carried out a phase II, item-randomised clinical trial in 27 PWA using a novel, self-led app, 'iTalkBetter', which utilises confrontation naming therapy. Unlike previously reported apps, it has a real-time utterance verification system that drives its adaptive therapy algorithm. Therapy items were individually randomised to provide balanced lists of 'trained' and 'untrained' items matched on key psycholinguistic variables and baseline performance. PWA practised with iTalkBetter over a 6-week therapy block. Structural and functional MRI data were collected to identify therapy-related changes in brain states. A repeated-measures design was employed. The trial was registered at ClinicalTrials.gov (NCT04566081). iTalkBetter significantly improved naming ability by 13% for trained items compared with no change for untrained items, an average increase of 29 words (SD = 26) per person; beneficial effects persisted at three months. PWA's propositional speech also significantly improved. iTalkBetter use was associated with brain volume increases in right auditory and left anterior prefrontal cortices. Task-based fMRI identified dose-related activity in the right temporoparietal junction. Our findings suggested that iTalkBetter significantly improves PWAs' naming ability on trained items. The effect size is similar to a previous RCT of computerised therapy, but this is the first study to show transfer to a naturalistic speaking task. iTalkBetter usage and dose caused observable changes in brain structure and function to key parts of the surviving language perception, production and control networks. iTalkBetter is being rolled-out as an app for all PWA and anomia: https://www.ucl.ac.uk/icn/research/research-groups/neurotherapeutics/projects/digital-interventions-neuro-rehabilitation-0 so that they can increase their dosage of practice-based SLT. National Institute for Health and Care Research, Wellcome Centre for Human Neuroimaging.
Application of knowledge is shown to improve student comprehension, but with dwindling hands-on clinical opportunities in nursing programs, active learning strategies need to be incorporated into classroom learning. Nursing faculty in an undergraduate nursing program transitioned from a lecture format to a flipped classroom format, thereby incorporating active learning. Quantitative and qualitative data on student performance were collected over three semesters. The Assessment Technologies Institute (ATI) maternal-newborn content mastery exam, used as the final examination for the course, was used to assess student academic performance. End-of-course student feedback was collected from the Campuslabs IDEA Student Rating of Instruction (SRI) evaluation to assess students' perceptions of their ability to understand and apply knowledge, as well as perceptions of the flipped classroom format in general. The ATI exam scores for the course did not change significantly, but the SRI showed a statistically significant increase in the percentage of students who felt they gained a "deeper understanding" and could "apply the knowledge and skills." Although students resisted the flipped classroom format change initially, subsequent cohorts came to accept the change. Implications for educators are that although student dissatisfaction increased initially, the inclusion of the flipped classroom format within a course improved students' confidence in their ability to perform.
Applied artificial intelligence, particularly large language models, in biomedical research is accelerating, but effective discovery and validation requires a toolset without limitations or bias. On January 30, 2023, the National Academies of Sciences, Engineering, and Medicine (NAS) appointed an ad hoc committee to identify needs and opportunities to advance the mathematical, statistical, and computational foundations of digital twins in applications across science, medicine, engineering, and society. On December 15, 2023, the NAS released a 164-page report, "Foundational Research Gaps and Future Directions for Digital Twins." This report described the importance of using digital twins in biomedical research. We developed an innovative method that incorporated phenotype-ranking algorithms with knowledge engineering via a biomimetic digital twin ecosystem. This ecosystem applied real-world reasoning principles to nonnormalized, raw data to identify hidden or dark data. We performed a clinical exome sequencing study on patients with endometriosis and were able to identify four variants of unknown clinical significance potentially associated with endometriosis-related disorders in nearly all patients analyzed. One variant of unknown clinical significance was identified in all patient samples and could be a biomarker for diagnostics. To the best of our knowledge, this is the first study to incorporate the recomandations of the NAS to biomedical research. This method can be used to understand the mechanisms of any disease, for virtual clinical trials, and to identify effective new therapies.
Applying constant tensile stress to a piece of amorphous solid results in a slow extension, followed by an eventual rapid mechanical collapse. This "creep" process is of paramount engineering concern, and as such was the subject of study in a variety of materials, for more than a century. Predictive theories for τ_{w}, the expected time of collapse, are incomplete, mainly due to its dependence on a bewildering variety of parameters, including temperature, system size, tensile force, but also the detailed microscopic interactions between constituents. The complex dependence of the collapse time on all the parameters is discussed below, using simulations of strip of amorphous material. Different scenarios are observed for ductile and brittle materials, resulting in serious difficulties in creating an all-encompassing theory that could offer safety measures for given conditions. A central aim of this paper is to employ scaling concepts, to achieve data collapse for the probability distribution function (pdf) of lnτ_{w}. The scaling ideas result in a universal function which provides a prediction of the pdf of lnτ_{w} for out-of-sample systems, from measurements at other values of these parameters. The predictive power of the scaling theory is demonstrated for both ductile and brittle systems. Finally, we present a derivation of universal scaling function for brittle materials. The ductile case appears to be due to a plastic necking instability and is left for future research.
Applying new technologies in teaching has led to the phenomenon of blended learning (BL), which is currently flourishing as a specific requirement for higher self-efficacy and success in increasingly complex healthcare environments. Although various forms of novel education are on the rise worldwide, the effects of electronic learning (EL), combined with collaborative learning (CL) and lecture-based teaching (LBT) approaches, have not yet been validated on academic self-efficacy among undergraduate nursing students. Utilizing a pre-/post-test comparison-group design, this quasi-experimental study was conducted on 70 undergraduate nursing students of Urmia University of Medical Sciences, Urmia, Iran, selected by the census sampling technique in 2020. The eligible participants were allocated to intervention groups, viz., the EL+LBT group (n=34) and the EL+CL group (n=36). A learning management system (LMS) was used for both intervention groups along with the LBT approach, and then 10 steps were integrated into the CL approach during 14 sessions, lasting 150 minutes. Afterward, a demographic information form and the College Academic Self-Efficacy Scale (CASES) were administered to collect the data. The data were analyzed using descriptive statistics, Chi-square test, independent-samples t-test, and analysis of covariance (ANCOVA). No significant difference was observed in the CASE scores between the students were taught using the EL+LBT (113.76±16.98) and the EL+CL approaches (107.66±16.70) before the interventions (P=0.136). However, the CL+EL approaches resulted in the highest changes in the CASE scores at the pre- (107.66±16.70) and post-test (119.08±25.49) stages (P=0.019). Moreover, the female students attending the CL+EL classrooms experienced significantly positive differences in their CASE scores (127.12±30.34), compared to the males (112.65±19.30) (P=0.011). Blending the EL and CL approaches significantly promoted CASE among the undergraduate nursing students in this study by providing sufficient collaboration, essential educational equipment, and better technical support.
Applying the knowledge gained through implementation science can support the uptake of research evidence into practice; however, those doing and supporting implementation (implementation practitioners) may face barriers to applying implementation science in their work. One strategy to enhance individuals' and teams' ability to apply implementation science in practice is through training and professional development opportunities (capacity-building initiatives). Although there is an increasing demand for and offerings of implementation practice capacity-building initiatives, there is no universal agreement on what content should be included. In this study we aimed to explore what capacity-building developers and deliverers identify as essential training content for teaching implementation practice. We conducted a convergent mixed-methods study with participants who had developed and/or delivered a capacity-building initiative focused on teaching implementation practice. Participants completed an online questionnaire to provide details on their capacity-building initiatives; took part in an interview or focus group to explore their questionnaire responses in depth; and offered course materials for review. We analyzed a subset of data that focused on the capacity-building initiatives' content and curriculum. We used descriptive statistics for quantitative data and conventional content analysis for qualitative data, with the data sets merged during the analytic phase. We presented frequency counts for each category to highlight commonalities and differences across capacity-building initiatives. Thirty-three individuals representing 20 capacity-building initiatives participated. Study participants identified several core content areas included in their capacity-building initiatives: (1) taking a process approach to implementation; (2) identifying and applying implementation theories, models, frameworks, and approaches; (3) learning implementation steps and skills; (4) developing relational skills. In addition, study participants described offering applied and pragmatic content (e.g., tools and resources), and tailoring and evolving the capacity-building initiative content to address emerging trends in implementation science. Study participants highlighted some challenges learners face when acquiring and applying implementation practice knowledge and skills. This study synthesized what experienced capacity-building initiative developers and deliverers identify as essential content for teaching implementation practice. These findings can inform the development, refinement, and delivery of capacity-building initiatives, as well as future research directions, to enhance the translation of implementation science into practice.
Appraisal of treatment outcomes in integrative medicine is a challenge due to a gap between the concepts of Western medicine (WM) disease and traditional Chinese medicine (TCM) syndrome. This study presents an approach for the appraisal of integrative medicine that is based on targeted metabolomics. We use non-alcoholic fatty liver disease with spleen deficiency syndrome as a test case. A patient-reported outcome (PRO) scale was developed based on literature review, Delphi consensus survey, and reliability and validity test, to quantitatively evaluate spleen deficiency syndrome. Then, a metabonomic foundation for the treatment of non-alcoholic fatty liver disease with spleen deficiency syndrome was identified via a longitudinal interventional trial and targeted metabolomics. Finally, an integrated appraisal model was established by identifying metabolites that responded in the treatment of WM disease and TCM syndrome as positive outcomes and using other aspects of the metabonomic foundation as independent variables. Ten symptoms and signs were included in the spleen deficiency PRO scale. The internal reliability, content validity, discriminative validity and structural validity of the scale were all qualified. Based on treatment responses to treatments for WM disease (homeostasis model assessment of insulin resistance) or TCM syndrome (spleen deficiency PRO scale score) from a previous randomized controlled trial, two cohorts comprised of 30 participants each were established for targeted metabolomics detection. Twenty-five metabolites were found to be involved in successful treatment outcomes to both WM and TCM, following quantitative comparison and multivariate analysis. Finally, the model of the integrated appraisal system was exploratively established using binary logistic regression; it included 9 core metabolites and had the prediction probability of 83.3%. This study presented a new and comprehensive research route for integrative appraisal of treatment outcomes for WM disease and TCM syndrome. Critical research techniques used in this research included the development of a TCM syndrome assessment tool, a longitudinal interventional trial with verified TCM treatment, identification of homogeneous metabolites, and statistical modeling.
Appreciative inquiry harnesses an individual's strengths to realize positive change, and a flourishing-focused mindset emphasizes engagement, social connectivity, and seeking meaningful work. Though the impact of these models on physician well-being and career planning has been evaluated in graduate medical education, their integration into career development initiatives for faculty has been limited. We designed a workshop to nurture hospitalist career development, based on our CORE2 conceptual framework (character strengths, overall vision, role assessment, explicit goals, and evaluation). We presented the workshop at the 2022 and 2023 Society of Hospital Medicine (SHM) annual conferences. This 1.5-hour workshop comprised four modules and three small-group activities designed to help participants identify their signature character strengths, draft a professional vision statement, prioritize professional roles, and develop SMART goals aligned with these roles. At the 2023 SHM annual conference, 36 participants attended the workshop, and 32 (89%) completed pre- and postworkshop surveys. After workshop completion, participants' self-assessed familiarity with their signature character strengths, knowledge of evidence-based principles to develop SMART goals, and confidence in their ability to write a vision statement and SMART goals all increased significantly (p < .05). This workshop provides a valuable framework for self-directed longitudinal career development and reflection. We build on prior curricula on educator identity formation by guiding participants from identity definition to professional vision development to professional role evaluation to aligned goal creation and iterative evaluation. Our workshop's principles are readily generalizable to clinician-educators across medical disciplines.