Tag: nevin manimala

PLoS One. 2022 Jun 22;17(6):e0270254. doi: 10.1371/journal.pone.0270254. eCollection 2022.

ABSTRACT

This study aims to investigate the supply chain challenges of public sector agriculture development projects in Bangladesh using the modified Delphi, Best Worst Method (BWM), and Interpretive Structural Modelling (ISM) methods. Based on these three widely acclaimed statistical techniques, the study identified, ranked, and identified interrelationships among the challenges. The study is unique not only in terms of research findings, but also in terms of methodology, as it is the first to use the three MCDM (Multicriteria Decision Making) tools to examine supply chain issues in public sector agriculture development projects in a developing country context. A literature review and two modified Delphi rounds with 15 industry experts’ opinions were applied to identify and validate a list of 11 key supply chain challenges. To determine the priority of the challenges, a panel of eight industry experts was consulted, and their responses were analysed using the BWM. Then, another group of 10 experts was consulted using ISM to investigate the contextual relationships among the challenges, resulting in a five-layered Interpretive Structural Model (ISM) and MICMAC (cross-impact matrix multiplication applied to classification) analysis of the challenges. According to relative importance (global weights), “improper procurement planning (0.213), “delay in project initiation (0.177), “demand forecasting error (0.146)”, “lack of contract monitoring mechanism (0.097)”, and “lack of competent staff (0.095)” are the top five ranked key challenges that have a significant impact on the project supply chain. Regarding contextual relationships, the ISM model and ISM-MICMAC analysis identified the “political influence” challenge as the most influential, and also independent of the other challenges. The findings are critical for project managers in managing challenges because understanding both relative importance and contextual relationships are required to address the challenges holistically. Additionally, these findings will benefit policymakers, academics, and future researchers.

PMID:35731792 | DOI:10.1371/journal.pone.0270254

PLoS One. 2022 Jun 22;17(6):e0269569. doi: 10.1371/journal.pone.0269569. eCollection 2022.

ABSTRACT

BACKGROUND: The prevalence of obstructive sleep apnea is higher in women after menopause. This is suggested to be a result of an altered sex hormone balance but has so far not been confirmed in a population-based study.

OBJECTIVE: To investigate whether serum concentration of estrogens and progesterone are associated with the prevalence of sleep apnea symptoms in middle-aged women of the general population.

METHODS: We analyzed data from 774 women (40-67 years) from 15 study centers in seven countries participating in the second follow-up of the European Community Respiratory Health Survey (2010-2012). Multiple logistic regression models were fitted with self-reported symptoms of sleep apnea as outcomes and serum concentrations of various estrogens and progesterone as predictors. All analyses were adjusted for relevant covariates including age, BMI, education, study center, smoking habits, and reproductive age.

RESULTS: Among all included women, a doubling of serum concentrations of estrone and progesterone was associated with 19% respectively 9% decreased odds of snoring. Among snorers, a doubling of the concentrations of 17β-estradiol, estrone and estrone 3-sulfate was associated with 18%, 23% and 17% decreased odds of breathing irregularly, and a doubling of the progesterone concentration was further associated with 12% decreased odds of waking up suddenly with a chocking sensation. Other evaluated associations were not statistically significant.

CONCLUSIONS: Middle-aged women with low serum estrogen and progesterone levels are more likely to snore and report symptoms of obstructive sleep apnea.

PMID:35731786 | DOI:10.1371/journal.pone.0269569

PLoS One. 2022 Jun 22;17(6):e0268409. doi: 10.1371/journal.pone.0268409. eCollection 2022.

ABSTRACT

INTRODUCTION: The use of social media during the COVID-19 pandemic has led to an “infodemic” of mis- and disinformation with potentially grave consequences. To explore means of counteracting disinformation, we analyzed tweets containing the hashtags #Scamdemic and #Plandemic.

METHODS: Using a Twitter scraping tool called twint, we collected 419,269 English-language tweets that contained “#Scamdemic” or “#Plandemic” posted in 2020. Using the Twitter application-programming interface, we extracted the same tweets (by tweet ID) with additional user metadata. We explored descriptive statistics of tweets including their content and user profiles, analyzed sentiments and emotions, performed topic modeling, and determined tweet availability in both datasets.

RESULTS: After removal of retweets, replies, non-English tweets, or duplicate tweets, 40,081 users tweeted 227,067 times using our selected hashtags. The mean weekly sentiment was overall negative for both hashtags. One in five users who used these hashtags were suspended by Twitter by January 2021. Suspended accounts had an average of 610 followers and an average of 6.7 tweets per user, while active users had an average of 472 followers and an average of 5.4 tweets per user. The most frequent tweet topic was “Complaints against mandates introduced during the pandemic” (79,670 tweets), which included complaints against masks, social distancing, and closures.

DISCUSSION: While social media has democratized speech, it also permits users to disseminate potentially unverified or misleading information that endangers people’s lives and public health interventions. Characterizing tweets and users that use hashtags associated with COVID-19 pandemic denial allowed us to understand the extent of misinformation. With the preponderance of inaccessible original tweets, we concluded that posters were in denial of the COVID-19 pandemic and sought to disperse related mis- or disinformation resulting in suspension.

CONCLUSION: Leveraging 227,067 tweets with the hashtags #scamdemic and #plandemic in 2020, we were able to elucidate important trends in public disinformation about the COVID-19 vaccine.

PMID:35731785 | DOI:10.1371/journal.pone.0268409

IEEE Trans Ultrason Ferroelectr Freq Control. 2022 Jun 22;PP. doi: 10.1109/TUFFC.2022.3185528. Online ahead of print.

ABSTRACT

This article addresses the measurement of the power spectrum of red noise processes at the lowest frequencies, where the minimum acquisition time is so long that it is impossible to average on a sequence of data record. Therefore, averaging is possible only on simultaneous observation of multiple instruments. This is the case of radio astronomy, which we take as the paradigm, but examples may be found in other fields such as climatology and geodesy. We compare the Bayesian confidence interval of the red noise parameter using two estimators, the spectrum average and the cross-spectrum. While the spectrum average is widely used, the cross-spectrum using multiple instruments is rather uncommon. With two instruments, the cross-spectrum estimator leads to the Variance-Gamma distribution. A generalization to q devices based on the Fourier transform of characteristic functions is provided, with the example of the observation of millisecond pulsars with 5 radio telescopes. The simulations show that the spectrum average is by a small amount more efficient than the cross-spectrum, chiefly when the background exceeds the signal. However some notable differences between their upper limit indicate that it should be wiser to compute both estimators.

PMID:35731776 | DOI:10.1109/TUFFC.2022.3185528

Pediatr Blood Cancer. 2022 Jun 22:e29867. doi: 10.1002/pbc.29867. Online ahead of print.

ABSTRACT

BACKGROUND: Burkitt lymphoma (BL) accounts for 90% of pediatric lymphomas in sub-saharan Africa. Plasmodium falciparum (Pf) malaria is considered an etiological factor of BL. We describe the geographic distribution of pediatric BL in Malawi and association with malaria prevalence (PfPR).

METHODS: We enrolled 220 pathologically confirmed incident pediatric BL cases (2013-2018) into an observational clinical cohort at Kamuzu Central Hospital (KCH) in Lilongwe district. KCH is the main tertiary cancer referral center serving the central and northern region of Malawi. Using an ecological study design, we calculated district-level annual BL incidence rate using census population estimates. District-level PfPR was extracted from the National Malaria Control Program 2010 report. BL incidence and PfPR maps were constructed in QGIS. Moran’s I was used to identify BL spatial clusters. Pearson’s correlation and multiple linear regression was used to statistically examine the relationship between PfPR and BL.

RESULTS: BL incidence was higher in central region districts (8.2 cases per million) than northern districts (2.9 cases per million) and was elevated in lakeshore districts. Districts with elevated PfPR tended to have elevated BL incidence. A low-risk BL cluster was detected in the north. Statistically, BL incidence was positively correlated with PfPR (r = 0.77, p<0.01). A 1% increase in PfPR predicted an increase in BL incidence of 0.2 cases per million (p = 0.03) when controlling for travel time from referral district hospital to KCH.

CONCLUSION: Our study supports evidence for an association between Pf and BL and highlights a need to improve geographic accessibility to tertiary cancer services in Malawi’s northern region. This article is protected by copyright. All rights reserved.

PMID:35731580 | DOI:10.1002/pbc.29867

JMIR Form Res. 2022 Jun 22;6(6):e28013. doi: 10.2196/28013.

ABSTRACT

BACKGROUND: Clinical decision support systems often adopt and operationalize existing clinical practice guidelines leading to higher guideline availability, increased guideline adherence, and data integration. Most of these systems use an internal state-based model of a clinical practice guideline to derive recommendations but do not provide the user with comprehensive insight into the model.

OBJECTIVE: Here we present a novel approach based on dynamic guideline visualization that incorporates the individual patient’s current treatment context.

METHODS: We derived multiple requirements to be fulfilled by such an enhanced guideline visualization. Using business process and model notation as the representation format for computer-interpretable guidelines, a combination of graph-based representation and logical inferences is adopted for guideline processing. A context-specific guideline visualization is inferred using a business rules engine.

RESULTS: We implemented and piloted an algorithmic approach for guideline interpretation and processing. As a result of this interpretation, a context-specific guideline is derived and visualized. Our implementation can be used as a software library but also provides a representational state transfer interface. Spring, Camunda, and Drools served as the main frameworks for implementation. A formative usability evaluation of a demonstrator tool that uses the visualization yielded high acceptance among clinicians.

CONCLUSIONS: The novel guideline processing and visualization concept proved to be technically feasible. The approach addresses known problems of guideline-based clinical decision support systems. Further research is necessary to evaluate the applicability of the approach in specific medical use cases.

PMID:35731571 | DOI:10.2196/28013

JMIR Form Res. 2022 Jun 22;6(6):e35961. doi: 10.2196/35961.

ABSTRACT

BACKGROUND: Age-related diseases such as dementia are playing an increasingly important role in global population development. Thus, prevention, diagnostics, and interventions require more accessibility, which can be realized through digital health apps. With the app on prescription, Germany made history by being the first country worldwide to offer physicians the possibility to prescribe and reimburse digital health apps as of the end of the year 2020.

OBJECTIVE: Considering the lack of knowledge about correlations with the likelihood of use among physicians, this study aimed to address the question of what makes the use of a digital health app by physicians more likely.

METHODS: We developed and validated a novel measurement tool-the Digital Health Compliance Questionnaire (DHCQ)-in an interdisciplinary collaboration of experts to assess the role of proposed factors in the likelihood of using a health app. Therefore, a web-based survey was conducted to evaluate the likelihood of using a digital app called DemPredict to screen for Alzheimer dementia. Within this survey, 5 latent dimensions (acceptance, attitude toward technology, technology experience, payment for time of use, and effort of collection), the dependent variable likelihood of use, and answers to exploratory questions were recorded and tested within directed correlations. Following a non-probability-sampling strategy, the study was completed by 331 physicians from Germany in the German language, of whom 301 (90.9%) fulfilled the study criteria (eg, being in regular contact with patients with dementia). These data were analyzed using a range of statistical methods to validate the dimensions of the DHCQ.

RESULTS: The DHCQ revealed good test theoretical measures-it showed excellent fit indexes (Tucker-Lewis index=0.98; comparative fit index=0.982; standardized root mean square residual=0.073; root mean square error of approximation=0.037), good internal consistency (Cronbach α=.83), and signs of moderate to large correlations between the DHCQ dimensions and the dependent variable. The correlations between the variables acceptance, attitude toward technology, technology experience, and payment for the time of use and the dependent variable likelihood of use ranged from 0.29 to 0.79, and the correlation between effort of the collection and likelihood of use was -0.80. In addition, we found high levels of skepticism regarding data protection, and the age of the participants was found to be negatively related to their technical experience and attitude toward technology.

CONCLUSIONS: In the context of the results, increased communication between the medical and technology sectors and significantly more awareness raising are recommended to make the use of digital health apps more attractive to physicians as they can be adjusted to their everyday needs. Further research could explore the connection between areas such as adherence on the patient side and its impact on the likelihood of use by physicians.

PMID:35731567 | DOI:10.2196/35961

JMIR Res Protoc. 2022 Jun 22;11(6):e37334. doi: 10.2196/37334.

ABSTRACT

BACKGROUND: Up-to-date and accurate information about the health problems encountered by primary care doctors is essential to understanding the morbidity pattern of the community to better inform health care policy and practice. Morbidity surveys of doctors allow documentation of actual consultations, reflecting the patient’s reason for seeking care as well as the doctor’s diagnostic interpretation of the illness and management approach. Such surveys are particularly critical in the absence of a centralized primary care electronic medical record database.

OBJECTIVE: With the changing sociodemographic profile of the population and implementation of health care initiatives in the past 10 years, the aim of this study is to determine the morbidity and management patterns in Hong Kong primary care during a pandemic and compare the results with the last survey conducted in 2007-2008.

METHODS: This will be a prospective, practice-based survey of Hong Kong primary care doctors. Participants will be recruited by convenience and targeted sampling from both public and private sectors. Participating doctors will record the health problems and corresponding management activities for consecutive patient encounters during one designated week in each season of the year. Coding of health problems will follow the International Classification of Primary Care, Second Edition. Descriptive statistics will be used to calculate the prevalence of health problems and diseases as well as the rates of management activities (referral, investigation, prescription, preventive care). Nonlinear mixed effects models will assess the differences between the private and public sectors as well as factors associated with morbidity and management patterns in primary care.

RESULTS: The data collection will last from March 1, 2021, to August 31, 2022. As of April 2022, 176 doctor-weeks of data have been collected.

CONCLUSIONS: The results will provide information about the health of the community and inform the planning and allocation of health care resources.

TRIAL REGISTRATION: ClinicalTrials.gov NCT04736992; https://clinicaltrials.gov/ct2/show/NCT04736992.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/37334.

PMID:35731566 | DOI:10.2196/37334

JMIR Med Inform. 2022 Jun 22;10(6):e34753. doi: 10.2196/34753.

ABSTRACT

BACKGROUND: Cervical cancer has been recognized as a preventable type of cancer. As the assessment of all the risk factors of a disease is challenging for physicians, information technology and risk assessment models have been used to estimate the degree of risk.

OBJECTIVE: The aim of this study was to develop a clinical decision support system to assess the risk of cervical cancer.

METHODS: This study was conducted in 2 phases in 2021. In the first phase of the study, 20 gynecologists completed a questionnaire to determine the essential parameters for assessing the risk of cervical cancer, and the data were analyzed using descriptive statistics. In the second phase of the study, the prototype of the clinical decision support system was developed and evaluated.

RESULTS: The findings revealed that the most important parameters for assessing the risk of cervical cancer consisted of general and specific parameters. In total, the 8 parameters that had the greatest impact on the risk of cervical cancer were selected. After developing the clinical decision support system, it was evaluated and the mean values of sensitivity, specificity, and accuracy were 85.81%, 93.82%, and 91.39%, respectively.

CONCLUSIONS: The clinical decision support system developed in this study can facilitate the process of identifying people who are at risk of developing cervical cancer. In addition, it can help to increase the quality of health care and reduce the costs associated with the treatment of cervical cancer.

PMID:35731549 | DOI:10.2196/34753

JAMA Surg. 2022 Jun 22. doi: 10.1001/jamasurg.2022.2234. Online ahead of print.

NO ABSTRACT

PMID:35731543 | DOI:10.1001/jamasurg.2022.2234