Aid Of Information Research Articles

Suggested Calibration Estimators of Finite Population Total for Cluster Sample - (I)

In survey sampling, the use of auxiliary information can greatly improve the precision of estimates of population total and/or means. Calibration estimation has developed into an important field of research in survey sampling where the auxiliary information plays an important role. In this paper, calibration estimator for cluster sampling with equal clusters have been introduced to improve variance estimator with the aid of auxiliary information and proposed the estimator of variance of calibration estimator. Six distances measures, presented the estimator of the variance of calibration approach estimators are introduced and a simulation study has been conducted to compare between the performance of calibration estimators against Horvitz-Thompson estimator using R statistical package.

TBT Stipulations and Stakeholder Responses: Repercussions in the Sea Food Sector of India and the Tuning up Process in the State of Kerala

Sea food is a globally traded product. The trading is mostly from the developing to the developed countries. The very basic factor beholding this is the income elasticity driven demand from the affluent consumers of the developed world. The rich fishery resource availability of the developing countries has helped to become the major beneficiaries of this trade process. The rich resource of India and Kerala have indeed helped in reaping this benefit. However, the post WTO period also witnessed big transformation in the fishery trade with more stringent restrictions, regulations and quality assurance practices mostly imposed by the importers of seafood. These include strict quality standards stipulations, technical barriers and non-tariff barriers imposed by the developed economies towards seafood exports. In these, TBT measures and SPS standards have differently been treated by different importers in the EU, Japan and the US and this is stipulated mostly for the prime export item of Kerala the shrimp. Though it has affected every seafood exporter globally, its repercussion in India and Kerala is also big as these measures have been detrimental to the progress of the export sector. India could soon try to galvanize these issues. The result is that India has come out from the shackles of TBT conundrums. But the fact is that when one of the issues is settled, the EU and the US are coming with newer stipulations. The paper tries to addresses the fisheries trade with the existing theoretical framework. It also gives an overview of various agreements prevailing in the seafood export sector with the aid of secondary information. Keywords: Fishery Trade, Technical Barriers to Trade (TBT), Non-Tariff Barriers (NTB), Trade agreements, Sanitary and Phytosanitary, Codex, WTO. DOI: 10.7176/JESD/13-10-07 Publication date: May 31 st 2022

Parents' Experience with Infant Safety Accidents and Needs of Safety Education: Content Analysis

Purpose: This study investigated the experiences of parents with infant safety accidents. In addition, this study analyzed the safety education required by the parents.Methods: A total of 21 parents with 6- to 12-month-old infants participated in the study. Data were gathered by one-on-one interviews with the parents using a semi-structured interview guide that included experiences with safety accidents and safety education. Content analysis was used.Results: Most safety accidents involving infants occurred at home, and the most common type of accident was falls. Because infant safety accidents occurred suddenly, it was difficult for parents to predict them. Parents reported a lack of first aid information or the ability to deal with safety accidents. They felt guilty for the safety accidents. The safety education contents they requested were first aid practice and home environment management. Home visits, group education, and mobile applications were the preferred methods for providing the safety education.Conclusion: To reduce the difficulties that parents face in safety accidents, infant safety education for parents is needed that provides a parental education program about first aid practices and home environment management. Additionally, to meet the needs of the parents, various modes of delivery for the safety education course should be developed.

Advanced Health Control Consultation Application at Clinic B White C Based on Android

Health information is a very important part of everyday life, where health information is obtained through direct consultation with doctors. However, in the midst of the Covid-19 pandemic that hit, we are required to continue to follow the health protocols recommended by the government by keeping a distance from each other or social distancing. Consultations are carried out face-to-face with doctors and conventional consultation methods prolong the meeting time between doctors and patients. Based on interviews conducted with several patients in several clinics, patients obtain health information by visiting the clinic and consulting directly with doctors. The purpose of this research is to build an Android-based Health Control Consultation application with an Information Technology approach, which is a form of service application. This application was built so that patients can find out health information through questions and answers via e-consul. Patients enter questions about health problems or health problems in text form, then the e-consul will respond to patient questions. So that it can facilitate someone in health consultations and obtain information on health problems and provide first aid information when a symptom or disease occurs. The E-consul application is also equipped with articles so that doctors can also share information from their knowledge with patients. This application is built by utilizing mobile-based application technology.

Probabilistic Prediction of Nonadherence to Psychiatric Disorder Medication from Mental Health Forum Data: Developing and Validating Bayesian Machine Learning Classifiers.

Background Medication nonadherence represents a major burden on national health systems. According to the World Health Organization, increasing medication adherence may have a greater impact on public health than any improvement in specific medical treatments. More research is needed to better predict populations at risk of medication nonadherence. Objective To develop clinically informative, easy-to-interpret machine learning classifiers to predict people with psychiatric disorders at risk of medication nonadherence based on the syntactic and structural features of written posts on health forums. Methods All data were collected from posts between 2016 and 2021 on mental health forum, administered by Together 4 Change, a long-running not-for-profit organisation based in Oxford, UK. The original social media data were annotated using the Tool for the Automatic Analysis of Syntactic Sophistication and Complexity (TAASSC) system. Through applying multiple feature optimisation techniques, we developed a best-performing model using relevance vector machine (RVM) for the probabilistic prediction of medication nonadherence among online mental health forum discussants. Results The best-performing RVM model reached a mean AUC of 0.762, accuracy of 0.763, sensitivity of 0.779, and specificity of 0.742 on the testing dataset. It outperformed competing classifiers with more complex feature sets with statistically significant improvement in sensitivity and specificity, after adjusting the alpha levels with Benjamini–Hochberg correction procedure. Discussion. We used the forest plot of multiple logistic regression to explore the association between written post features in the best-performing RVM model and the binary outcome of medication adherence among online post contributors with psychiatric disorders. We found that increased quantities of 3 syntactic complexity features were negatively associated with psychiatric medication adherence: “dobj_stdev” (standard deviation of dependents per direct object of nonpronouns) (OR, 1.486, 95% CI, 1.202–1.838, P < 0.001), “cl_av_deps” (dependents per clause) (OR, 1.597, 95% CI, 1.202–2.122, P, 0.001), and “VP_T” (verb phrases per T-unit) (OR, 2.23, 95% CI, 1.211–4.104, P, 0.010). Finally, we illustrated the clinical use of the classifier with Bayes' monograph which gives the posterior odds and their 95% CI of positive (nonadherence) versus negative (adherence) cases as predicted by the best-performing classifier. The odds ratio of the posterior probability of positive cases was 3.9, which means that around 10 in every 13 psychiatric patients with a positive result as predicted by our model were following their medication regime. The odds ratio of the posterior probability of true negative cases was 0.4, meaning that around 10 in every 14 psychiatric patients with a negative test result after screening by our classifier were not adhering to their medications. Conclusion Psychiatric medication nonadherence is a large and increasing burden on national health systems. Using Bayesian machine learning techniques and publicly accessible online health forum data, our study illustrates the viability of developing cost-effective, informative decision aids to support the monitoring and prediction of patients at risk of medication nonadherence.

Public awareness of first aid treatment in acute burns

Background/Aim: Burn injury is a global public health concern. First aid in burns can reduce morbidity and mortality by stopping the burning process and reducing the size and ultimate depth of the burn injury. The aim of this study is to assess the knowledge about first aid for burns in an urban population in Malaysia. Methods: We conducted a cross-sectional study using questionnaires to assess the knowledge about first aid for acute burns in our single tertiary main national referral unit for burn injuries. A total of 100 respondents were interviewed. Respondents were voluntary outpatients in the surgical outpatient department. Results: Twenty-two percent of the respondents complied with World Health Organization (WHO) recommendations. Other methods used were toothpaste (5.6%), soy sauce (4.4%), traditional oils (3.3%), aloe vera gels (2.2%), and a variety of creams (3.3%). Twenty-five percent agreed that the best information in first aid is through a first aid course; 15% chose a phone application, 14% chose a website, and 12% chose a television advertisement. The recommended first aid treatment (running tap water for ≥ 20 minutes) has proven beneficial in reducing tissue temperature and severity of injury. Conclusion: In 2019, 91% of the Malaysia population had access to the internet, which offers fast and reliable information on first aid for acute burn injuries. The majority of our population still lacks knowledge about first aid treatment for acute burns. Implementation of education regarding burn first aid should target all populations in Malaysia through different community health campaigns, with collaboration between government and non-governmental agencies.

Designing Caring and Informative Decision Aids to Increase Trust and Enhance the Interaction Atmosphere

Decision aids have enjoyed extensive use in various domains. While decision aid research and practice have largely focused on making these aids more functional and utilitarian, we propose that one should also purposefully design them as effective interaction partners, especially when one deploys them in contexts that require a “human touch”, such as finance or healthcare. In this paper, we report on the results from an experiment we conducted on the effects that designing caring and informative decision aids have on how users evaluate them and, subsequently, their satisfaction with them. Our results show that using explanations and expressive speech acts can enhance the extent to which users perceive decision aids as informative and caring. These strengthened beliefs subsequently enhance the extent to which users view decision aids as competent and as having integrity and improve the interaction atmosphere, which, in turn, increases users’ satisfaction with their overall interaction with the decision aid. We discuss the study’s contributions to theory and practice.

Adolescent Reproductive Health Service in Accessing HIV and AIDS Information

Adolescent reproductive health problems are very complex, one of them is HIV and AIDS. Adolescent Reproductive Health Service (PKPR) in Public Health Center the aims to increase adolescent knowledge about adolescent healthy behavior including reproductive health. The research aimed to identify utilization of Adolescent Reproductive Health Service in acces HIV and AIDS information in Kulon Progo. The research used a quantitative design, The population in the research is senior high school students. The sampling technique was simple random sampling with a sample of 125 respondents. The data collection instrument in this quantitative study was a questionnaire using google form, the data was processed using the steps of editing, coding, tabulating and analysis. The results showed that 73% of respondents had good knowledge, 60% of respondents had poor knowledge of PKPR Puskesmas and 56% of respondents used PKPR services for adolescents. The provision of adolescent reproductive health services is in accordance with the needs of adolescents and it is necessary to increase the promotion of adolescent reproductive health services so that they are more familiar with and can access services.

Optimization-based self-alignment method for stationary SINS with geographical latitude uncertainty

To solve the self-alignment problem of strapdown inertial navigation system (SINS) with geographical latitude uncertainty, an optimization-based self-alignment (OSA) method and its improvement for stationary SINS without using the latitude information are proposed. We use only the accelerometer and gyroscope measurements, without the aid of the external latitude information, to determine the Earth rate in the navigation frame. Then we formulate the SINS self-alignment process as a Wahba problem to overcome the disturbances of random noise, and use the estimated Earth rate vector and multiple measurements from the accelerometer and gyroscope to formulate the nonlinear objective function. Moreover, the alignment errors of the OSA method are also presented, based on which we propose a two-position OSA to estimate and compensate the horizontal accelerometer biases to further improve the alignment accuracy. The results of simulation and experiments demonstrate that the proposed OSA method and its improvement perform robust to the noise disturbances and achieve better alignment accuracy than conventional self-alignment methods.

Feasibility of a primary care patient decision aid for smoking cessation with information about e-cigarettes

Decision aids can promote shared decision making and behavior change and may be effective in helping patients quit smoking. Patients are increasingly using e-cigarettes for smoking cessation; however, little is known about the impact of including e-cigarette information in smoking cessation decision aids. Our objective was to assess the feasibility and acceptability of a smoking cessation decision aid including e-cigarette information. This study was conducted at one family medicine clinic in the United States. We used a pre-post design. In Phase I, the decision aid presented information about approved cessation methods. In Phase II, current e-cigarette users and patients with no intention of quitting received additional information on switching to e-cigarettes. We assessed the impact of the decision aids on quit attempts and abstinence, confidence and readiness to quit, confidence and readiness to switch to e-cigarettes, and patient satisfaction. We enrolled 60 patients in each phase (N = 120). Patients reported higher confidence and readiness to quit after viewing the decision aids and consulting with their physician (p < 0.01). Patients reported the decision aid helped prepare them to make a decision about quitting smoking and expressed satisfaction with the decision aid and clinician consultation. We did not observe an impact of including e-cigarette information. Smoking cessation decision aids are acceptable to patients and may promote behavior change. Future studies should explore the impact of providing patients e-cigarette information using larger sample sizes and rigorous designs. Further research is needed to identify strategies to promote shared decision-making regarding e-cigarettes.

Forecasting of the efficiency of monoclonal therapy in the treatment of CoViD-19 induced by the Omicron variant of SARS-CoV2

On November 26, 2021, the World Health Organization (WHO) announced a new variant of concern of SARS-CoV2 called Omicron. This variant has biological–functional characteristics such as to make it much faster in the infectious process so as to show an even more intense spread. Although many data are currently incomplete, it is possible to identify, based on the viral biochemical characteristics, a possible therapy consisting of a monoclonal antibody called Sotrovimab. The model proposed here is based on the mathematical analysis of the dynamics of action of this monoclonal antibody and two cell populations: the immune memory cells and the infected cells. Indeed, a delay exists during the physiological immune response and the response induced by administration of Sotrovimab. This manuscript presents that delay in a novel manner. The model is developed with the aid of information based on the chemical kinetics. The machine learning tools have been used to satisfy the criteria designed by the dynamical analysis. Regression learner tools of Python are used as the reverse engineering tools for the understanding of the balance in the mathematical model, maintained by the parameters and their corresponding intervals and thresholds set by the dynamical analysis.

Unveiling music genre structure through common-interest communities

Using a dataset of more than 90,000 metal music reviews written by over 9,000 users in a period of 15 years, we analyse the genre structure of metal music with the aid of review text information. We model the relationships between genres using a user-oriented network, based on the written reviews. We then perform community detection and employ a network "averaging" method to obtain stable genre clusters, in order to analyse the structures of clusters both locally within each cluster and globally over the entire network. In addition to identifying the clusters, we use Dependency Parsing and modified Term Frequency - Inverse Document Frequency to extract significant and unique features of each cluster. These structures and review text information can allow us to understand how music audience (fans) perceive similar and different genres, and also assist in classifying different genres which share common-interest user communities, offering a more objective way in grouping music genres. Furthermore, the classification can also help recommendation engines provide more targeted suggestions of music, and potentially help musicians to select genre labels for their music, and design music to better cater to preferences of their audiences based on previous reviews.

Barriers and facilitators for parents in end-of-life decision-making for neonates at the Neonatal Intensive Care Unit: A qualitative study

Background: Mortality and end-of-life decision-making can occur in newborns, especially within the Neonatal Intensive Care Unit. For parents, participating in end-of-life decision-making is taxing. Knowledge is lacking on what support is helpful to parents during decision-making. Aim: To identify barriers and facilitators experienced by parents in making an end-of-life decision for their infant. Design: Qualitative study using face-to-face semi-structured interviews. Setting/participants: We interviewed 23 parents with a child that died after an end-of-life decision at a Neonatal Intensive Care Unit between April and September 2018. Results: Parents stated barriers and facilitators within 4 themes: 1. Clinical knowledge and prognosis; 2. Quality of information provision; 3. Emotion regulation; and 4. Psychosocial environment. Facilitators include knowing whether the prognosis includes long-term negative quality of life, knowing all treatment options, receiving information according to health literacy level, being able to process intense emotions, having experienced counseling and practical help. Barriers include a lack of general medical knowledge, being unprepared for a poor prognosis, having an uninformed psychologist. Conclusions: We found that clinical information and psychosocial support aid parents in decision-making. Information is best tailored to health literacy. Psychosocial support can be provided by experienced, informed counselors, social services and sibling support, distinguishing between verbal and non-verbal coping preferences, and calm, familiar architecture. Intense emotions may hinder absorption of clinical information, therefore interventions to aid emotion regulation and reduce cognitive load may be looked at in further research. Adjustment of the Situations, Opinions and Options, Parents, Information, Emotions framework based on our results can be evaluated.

A Formal Representation of the Semantics of Structural Geological Models

A structural geological model describes the structure of subsurface and plays an important role in the exploration of mineral and petroleum resources. Despite the widespread use of three-dimensional geological models, the theoretical research of informatics in the field of structural geology is still very limited. We have noticed a lack of methods for integrating explicit semantics of field observation data and geophysical data into geological models. The existing model representation methods focus on accurately representing the geometric morphological information of underground structures, ignoring the high-level semantics implied in the model. The formal representation of the semantic information is necessary to promote the development of intelligent methods in geomodeling and geophysical inversion. In this paper, we propose a new framework to formally represent the semantics of structural geological models with a clear distinction of geometric and geological semantics. For the geometric semantics, based on the extension of the 9-intersection model, we mathematically define the spatial topological relations between geometric objects that make up the geological model. For the geological semantics, we define the geological contact and compositional relations between geological bodies and geological surfaces and reveal the temporal implications of these geological relationships. We design a multilayer heterogeneous network as a computer characterization of the semantics of the geological model. A better representation of semantic information aids in the creation and validation of geological models, as well as management, queries, and analyses of geological knowledge.

Consumers’ Knowledge and Use of Nutritional Labelling Information in Lagos, Nigeria

Nutrition labelling is a topical issue, being a vital aid that shapes consumers’ food choices and could be an efficient tool for the prevention of consumer vulnerability to diet-related diseases such as cancer, high blood pressure, hypertension, and obesity. However, data on the public use of nutritional labels as an information source on nutritional properties of foods and health claims, especially as it relates to Nigeria, are not popular in the literature. This study seeks to examine consumers’ use of labelling information: knowledge; attitude, and practice. A cross-sectional study with the aid of a survey elicited information from 374 randomly selected shoppers in five shopping malls in Lagos State. Data were analysed using the T-test method. Findings show that while the majority of the respondents (70.6%) read the nutritional information, only 64.9% understand the information presented on food labels. The study also reveals that the majority of the respondents (57.5%) do not know that information on food labels should be presented in the English language before any other language as recommended by the National Agency Food and Drug Administration and Control (NAFDAC). While 57.9% of consumers have a positive attitude towards using food labels, 58% of the respondents’ buying decisions are influenced by food labels. The study concludes that consequent upon the importance of nutritional knowledge and wellbeing, consumers of Fast Moving Goods in Nigeria are beginning to consciously pay attention to nutritional labels. The study recommends that producers of Fast Moving Consumer Goods (FMCG) products in Nigeria should adopt the total disclosure of ingredients and nutritional content of their products. Also, regulatory bodies in charge of pre-packaged food products in Nigeria (NAFDAC) should go the whole way and make nutritional labelling mandatory.

The Next Generation of eHealth: A Multidisciplinary Survey

Over the past two years, the spread of COVID-19 has spurred the use of information and communication technologies (ICT) in aid of healthcare. The need to guarantee continuity to care has promoted research and industry activities aimed at developing solutions for the digitalization of the procedures to be performed to provide health services, even in emergency scenarios. Digital collection, transmission, and processing of health data represent the starting point for fulfilling this innovation process but also bring heterogeneous challenges. These motivations led to the elaboration of this work, which analyzes innovative and technological tools for the development of digital health (eHealth) through the collection of multisectoral literature, produced thanks to the cooperation of varied research groups, thus providing a multidisciplinary survey. Since digital health is expected to be one of the leading applications of the sixth-generation (6G) wireless cellular networks, this paper covers the related telecommunications aspects. Furthermore, the exploitation of artificial intelligence paradigms to elaborate massive amounts of biological data is examined. Given the extreme sensitivity of health data, this paper also investigates security and privacy issues. In particular, the main techniques and approaches to guarantee security properties (i.e., anonymity, responsibility, authentication, confidentiality, integrity, non-repudiation, and revocability) are studied. Applications involving innovative electromagnetic systems for healthcare and assisted living services are described to provide an example of an eHealth scenario leveraging ICT. Finally, the telemedicine-related regulations of the European Commission are analyzed, with particular reference to the General Data Protection Regulation (GDPR).

Separable Coupled Dictionary Learning for Large-Scene Precise Classification of Multispectral Images

Large-scene precise classification of multispectral images (MSIs) has become one of the hot topics in remote sensing field. MSIs usually have wide swath and a meter or even submeter level of spatial resolution, which make large-scene observation possible. However, the limited number of spectral bands leads to the confusion of land covers in classification, especially for the large-scene conditions with abundant land cover types. Therefore, overlapped hyperspectral images (HSIs) can be used to improve the precision degree of classification. To achieve this purpose, coupled dictionary learning has been proposed as a major means. Aiming at separating the class-specific characteristics and mutual patterns among different land covers, this paper proposed a separable coupled dictionary learning (SCDL) method, which converts the separation of mutual features into the construction of separable coupled dictionaries and learns both class-specific coupled dictionaries and mutual coupled dictionaries simultaneously with the aid of label information. More specifically, the proposed method uses the labels of training samples to construct class-specific reconstruction error constraint, class-specificity constraint and separable dictionary incoherence constraint as regularization terms, to make sure that the learned coupled dictionaries to be both compact and discriminative. The learned separable coupled dictionaries facilitate pixels belong to the same category to be represented by the mutual dictionary and the class-specific sub-dictionary of corresponding class. The experiments compared with several state-of-the-art methods on three pairs of HSI and MSI have shown better classification performance.

Well-Guided Multisource Elastic Full-Waveform Inversion

Full waveform inversion (FWI) has been considered one of the most promising approaches to estimating the high-resolution subsurface parameters, which takes advantage of the kinematics and dynamics information of seismic data. However, FWI is greatly dependent on the accuracy of the initial model and vulnerable to the issue of local minimum. Moreover, the multi-source and multi-parameter crosstalk artifacts make multi-source elastic FWI (MS-EFWI) more likely to trap into a suboptimal inversion result. To remedy this defect, this study proposes an efficient elastic FWI (EFWI) paradigm that combines the crosstalk-free MS-EFWI method and a well-guided initial model-building algorithm. Specifically, we apply a harmonic wavelet encoding technology to MS-EFWI, by which the multi-source wavefields can be completely deblended without crosstalk noise. The well-guided structure-oriented interpolation, with the aid of the dip information derived from the initial migration images, is designed to build a satisfactory initial model and therefore reduce the risk of cycle skipping. Numerical examples based on the 2D Overthrust model and Marmousi model further demonstrate the feasibility and robustness of the proposed method with a relatively little number of iterations.

Clinically Significant Incidental Findings on CT Imaging During TAVI Work-up: A Systematic Review and Meta-Analysis.

The transcatheter aortic valve implantation (TAVI) population is mostly elderly and frail. Clinically significant incidental findings (SIFs) are commonly encountered in the work-up of TAVI patients. This is a systematic review of current literature on the occurrence of SIFs on computed tomography (CT) imaging preceding TAVI and their association with mortality, delayed planning, and procedure cancellation. A systematic search on Medline, Embase, and Cochrane resulted in 19 retrospective studies (published from 2010-2020) reporting SIFs in the work-up for TAVI. A total of 6358 individuals from 19 studies were analyzed, with mean age of 80 years and sex equally divided. A random-effects meta-analysis was performed, with weighting based on study size. Pooled prevalence of patients with SIF was 22.2% (95% confidence interval [CI], 17.8-26.6) and most findings (48.3%) were found in the lungs. Pooled prevalence of new malignancies was 3.4% (95% CI, 2.5-4.4). Higher mortality in patients with SIF was only found in studies with a follow-up period >4 years (hazard ratio, 1.5-1.7). TAVI was more frequently cancelled in patients with SIF vs those with no SIF (ranges, 10.1%-47.1% vs 5.2%-37.0%, respectively). SIF did not delay time to TAVI (ranges, 6-91 days in SIF patients vs 4-81 days in non-SIF patients). SIFs are common in patients screened for TAVI. SIF is associated with a higher risk of TAVI cancellation and with increased mortality risk over the long term, which should be taken into consideration in decision making. These findings may help inform patients and aid patient selection.

#DomesticViolence During the COVID-19 Global Pandemic: An Analysis of Public Commentary via Twitter.

The current study sought to characterize commentary regarding intimate partner violence during the COVID-19 (SARS-CoV-2) pandemic via the Twitter hashtags #DomesticAbuse and #DomesticViolence. A sample of 481 original, English-language tweets containing the hashtag #DomesticAbuse or #DomesticViolence posted across five consecutive weekdays from March 22 to March 27, 2020—during which many places were enacting lockdown mandates—was examined using thematic content analyses. Overall, Twitter users commented on potential increased rates of IPV, while adding details about abuse tactics that could be employed by perpetrators during the pandemic. Additionally, Twitter users disclosed personal experiences of IPV victimization. Four themes were identified, including (1) type of domestic violence (i.e. whether the violence was COVID-specific or general domestic violence), (2) commentary about IPV (i.e. general reflections, decentralizing and centralizing survivorhood), (3) perpetrator tactic (i.e. abuse tactic used by the perpetrator), and (4) institutions responsible (i.e. institutions responsible for providing services to survivors). Overall, the commentary on Twitter reflected an effort to raise awareness and share informational aid for potential victims/survivors of IPV. Data highlight the potential of social media networks in conveniently facilitating the sharing and spreading of useful resources to other users. Future research should examine whether resources shared via Twitter reach individuals who need them and empower individuals to garner support.