14 research outputs found
Neurodevelopmental disorders in children aged 2-9 years: Population-based burden estimates across five regions in India.
BACKGROUND: Neurodevelopmental disorders (NDDs) compromise the development and attainment of full social and economic potential at individual, family, community, and country levels. Paucity of data on NDDs slows down policy and programmatic action in most developing countries despite perceived high burden. METHODS AND FINDINGS: We assessed 3,964 children (with almost equal number of boys and girls distributed in 2-<6 and 6-9 year age categories) identified from five geographically diverse populations in India using cluster sampling technique (probability proportionate to population size). These were from the North-Central, i.e., Palwal (N = 998; all rural, 16.4% non-Hindu, 25.3% from scheduled caste/tribe [SC-ST] [these are considered underserved communities who are eligible for affirmative action]); North, i.e., Kangra (N = 997; 91.6% rural, 3.7% non-Hindu, 25.3% SC-ST); East, i.e., Dhenkanal (N = 981; 89.8% rural, 1.2% non-Hindu, 38.0% SC-ST); South, i.e., Hyderabad (N = 495; all urban, 25.7% non-Hindu, 27.3% SC-ST) and West, i.e., North Goa (N = 493; 68.0% rural, 11.4% non-Hindu, 18.5% SC-ST). All children were assessed for vision impairment (VI), epilepsy (Epi), neuromotor impairments including cerebral palsy (NMI-CP), hearing impairment (HI), speech and language disorders, autism spectrum disorders (ASDs), and intellectual disability (ID). Furthermore, 6-9-year-old children were also assessed for attention deficit hyperactivity disorder (ADHD) and learning disorders (LDs). We standardized sample characteristics as per Census of India 2011 to arrive at district level and all-sites-pooled estimates. Site-specific prevalence of any of seven NDDs in 2-<6 year olds ranged from 2.9% (95% CI 1.6-5.5) to 18.7% (95% CI 14.7-23.6), and for any of nine NDDs in the 6-9-year-old children, from 6.5% (95% CI 4.6-9.1) to 18.5% (95% CI 15.3-22.3). Two or more NDDs were present in 0.4% (95% CI 0.1-1.7) to 4.3% (95% CI 2.2-8.2) in the younger age category and 0.7% (95% CI 0.2-2.0) to 5.3% (95% CI 3.3-8.2) in the older age category. All-site-pooled estimates for NDDs were 9.2% (95% CI 7.5-11.2) and 13.6% (95% CI 11.3-16.2) in children of 2-<6 and 6-9 year age categories, respectively, without significant difference according to gender, rural/urban residence, or religion; almost one-fifth of these children had more than one NDD. The pooled estimates for prevalence increased by up to three percentage points when these were adjusted for national rates of stunting or low birth weight (LBW). HI, ID, speech and language disorders, Epi, and LDs were the common NDDs across sites. Upon risk modelling, noninstitutional delivery, history of perinatal asphyxia, neonatal illness, postnatal neurological/brain infections, stunting, LBW/prematurity, and older age category (6-9 year) were significantly associated with NDDs. The study sample was underrepresentative of stunting and LBW and had a 15.6% refusal. These factors could be contributing to underestimation of the true NDD burden in our population. CONCLUSIONS: The study identifies NDDs in children aged 2-9 years as a significant public health burden for India. HI was higher than and ASD prevalence comparable to the published global literature. Most risk factors of NDDs were modifiable and amenable to public health interventions
Addressing mitochondrial dynamics in intercellular transfer to glioblastoma
reservedPerform biochemical analysis of morpho-functional remodeling of transferred mitochondria to glioblastoma using molecular and cellular techniques (cytometry, confocal microscopy, inhibitors, cell culture of primary neural cells and cell lines, etc.).Perform biochemical analysis of morpho-functional remodeling of transferred mitochondria to glioblastoma using molecular and cellular techniques (cytometry, confocal microscopy, inhibitors, cell culture of primary neural cells and cell lines, etc.)
Preliminary data on Planaria (Turbellaria) in Lithuania
Planarijos yra vienas iš pirmaujančių organizmo pavyzdžių daugeliui šiuolaikinių mokslinių eksperimentų, susijusių su regeneracija ir kamieninių ląstelių tyrimais. Tačiau šių gėlavandenių ir sausumos plokščiųjų kirmėlių paplitimas ir įvairovė Baltijos šalyse dar nėra nustatyta. Atsižvelgiant į planarijų ekonominę svarbą ir į tai, kad Lietuvoje nėra paplitę jų tyrimo šaltiniai, šiame darbe dėmesys sutelkiamas į skirtingus gėlo vandens ir sausumos planarijų mėginių ėmimo, surinkimo, fiksavimo ir identifikavimo metodus iš skirtingų mėginių ėmimo vietų visoje Lietuvoje.Planaria are one of the leading model organisms for many modern scientific experiments on regeneration and stem cell research. However, the distribution and diversity of these freshwater and terrestrial flatworms has not yet been established in the Baltic states. In consideration with the economic importance of planaria and the lack there of any sources on its distribution in Lithuania, this research paper focuses on different methods for sampling, collecting, fixation and identification of freshwater and terrestrial planaria from different sampling sites across LithuaniaGamtos mokslų fakultetasBiologijos katedr
Trainees\u27 perceptions of feedback: validity evidence for two FEEDME (feedback in medical education) instruments.
Construct: Medical educators consider feedback a core component of the educational process. Effective feedback allows learners to acquire new skills, knowledge, and attitudes. Learners\u27 perceptions of feedback are an important aspect to assess with valid methods in order to improve the feedback skills of educators and the feedback culture.
BACKGROUND: Although guidelines for delivering effective feedback have existed for several decades, medical students and residents often indicate that they receive little feedback. A recent scoping review on feedback in medical education did not reveal any validity evidence on instruments to assess learner\u27s perceptions of feedback. The purpose of our study was to gather validity evidence on two novel FEEDME (Feedback in Medical Education) instruments to assess medical students\u27 and residents\u27 perceptions of the feedback that they receive.
APPROACH: After the authors developed an initial instrument with 54 items, cognitive interviews with medical students and residents suggested that 2 separate instruments were needed, one focused on the feedback culture (FEEDME-Culture) and the other on the provider of feedback (FEEDME-Provider). A Delphi study with 17 medical education experts and faculty members assessed content validity. The response process was explored involving 31 medical students and residents at 2 academic institutions. Exploratory factor analysis and reliability analyses were performed on completed instruments.
RESULTS: Two Delphi consultation rounds refined the wording of items and eliminated several items. Learners found both instruments easy and quick to answer; it took them less than 5 minutes to complete. Learners preferred an electronic format of the instruments over paper. Factor analysis revealed a two- and three-factor solution for the FEEDME-Culture and FEEDME-Provider instruments, respectively. Cronbach\u27s alpha was greater than 0.80 for all factors. Items on both instruments were moderately to highly correlated (range, r = .3-.7).
CONCLUSIONS: Our results provide preliminary validity evidence of 2 novel feedback instruments. After further validation of both FEEDME instruments, sharing the results of the FEEDME-Culture instrument with educational leaders and faculty may improve the culture of feedback on specific educational rotations and at the institutional level. The FEEDME-Provider instrument could be useful for faculty development targeting feedback skills. Additional research studies could assess whether both instruments may be used to help learners receive feedback and prompt reflective learning
The interplay between residency program culture and feedback culture: a cross-sectional study exploring perceptions of residents at three institutions.
BACKGROUND: Giving and receiving feedback that changes performance is influenced significantly by the clinical learning environment. This environment is multi-dimensional but includes both organizational and feedback specific dimensions.
OBJECTIVE: The objectives of this research were to investigate the relationship between residents\u27 perceptions of residency program culture and feedback culture; and whether there were differences in resident perceptions of their programs\u27 and feedback cultures based on their disciplines and institution. We hypothesized that residents preferred certain program culture types and that certain aspects of a residency program\u27s culture were related to the feedback culture.
DESIGN: Residents from six specialties at three institutions voluntarily completed two validated survey instruments (Organizational Culture Assessment Instrument [OCAI] and Feedback in Medical Education [FEEDME]-Culture survey) to assess the residency program and feedback cultures, respectively. Descriptive statistics were calculated and non-parametric tests were used to analyze the data.
RESULTS: The overall response rate was 37.9% (116/306 residents). \u27Clan\u27 culture was both the current and preferred culture by 49.3% and 56.8%, respectively, of the residents overall. There were differences across programs with more current \u27clan\u27 culture in pediatrics than in surgery (P = 0.01). Multiple regression analysis showed the Hierarchy Now culture type was significantly related to the feedback culture mean score (p =
CONCLUSIONS: The findings of this study add to the literature by describing residents\u27 preferences of their residency program\u27s culture, and providing insights into the interplay between the residency program and feedback cultures
The interplay between residency program culture and feedback culture: a cross-sectional study exploring perceptions of residents at three institutions
Background: Giving and receiving feedback that changes performance is influenced significantly by the clinical learning environment. This environment is multi-dimensional but includes both organizational and feedback specific dimensions. Objective: The objectives of this research were to investigate the relationship between residents’ perceptions of residency program culture and feedback culture; and whether there were differences in resident perceptions of their programs’ and feedback cultures based on their disciplines and institution. We hypothesized that residents preferred certain program culture types and that certain aspects of a residency program’s culture were related to the feedback culture. Design: Residents from six specialties at three institutions voluntarily completed two validated survey instruments (Organizational Culture Assessment Instrument [OCAI] and Feedback in Medical Education [FEEDME]-Culture survey) to assess the residency program and feedback cultures, respectively. Descriptive statistics were calculated and non-parametric tests were used to analyze the data. Results: The overall response rate was 37.9% (116/306 residents). ‘Clan’ culture was both the current and preferred culture by 49.3% and 56.8%, respectively, of the residents overall. There were differences across programs with more current ‘clan’ culture in pediatrics than in surgery (P = 0.01). Multiple regression analysis showed the Hierarchy Now culture type was significantly related to the feedback culture mean score (p = <.01). For every one unit increase in the Hierarchy Now culture type, the FEEDME-Culture mean score decreases by 0.023 units. Conclusions: The findings of this study add to the literature by describing residents’ preferences of their residency program’s culture, and providing insights into the interplay between the residency program and feedback cultures
Synthesis and characterization of tungsten and barium co-doped La2Mo2O9 by sol-gel process for solid oxide fuel cells
The interplay between residency program culture and feedback culture: a cross-sectional study exploring perceptions of residents at three institutions
Multivariable logistic regression analysis for risk factors for NDDs<sup>#</sup>.
<p>Multivariable logistic regression analysis for risk factors for NDDs<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002615#t005fn001" target="_blank"><sup>#</sup></a>.</p