Quality Of Information Research Articles

How evidence-based is the "hashtag ADHD test" (#adhdtest). A cross-sectional content analysis of TikTok videos on attention-deficit/hyperactivity disorder (ADHD) screening.

TikTok is being increasingly used as an easily accessible source of information on Attention-Deficit/Hyperactivity Disorder (ADHD). This study aimed to find the quality of information on ADHD screening or self-test in TikTok videos with the hashtag #adhdtest and the engagement of these videos with their viewers. The content of the top 50 TikTok videos with the "hashtag #ADHDtest" was analyzed cross-sectionally and categorized as "useful" or "misleading" after comparison of its content with the "Adult ADHD Self-Report Scale" (ASRS-v1.1). The videos were categorized as "useful" if its contents had at least 4 out of the 6 questions on the ASRS-v1.1 screener. Its level of engagement was quantified by measuring the number of times the video was liked, commented on, or added to favorites. Descriptive statistics were used for analysis. Out of the 50 included #adhdtest videos, 92% (n = 46) were misleading. Furthermore, useful videos had minimal engagement, with only 4% of the total likes, 1% of the total comments, and 7% of the total favorites. There is misleading information related to adult ADHD screening and testing on TikTok. There is a need to address this misinformation.

Breaking down the impenetrable wall: What are the barriers to good corporate governance practices above all?

Good corporate governance practices are essential in every organisation to ensure accountability and due diligence enhancing corporate value. However, some countries face barriers to good corporate governance practices such as poor regulatory frameworks, perceived constraints, and threats from external factors, etc. Therefore, the organisations will face consequences such as eroding shareholder confidence, declining market value and the organisation integrity. Hence, the study’s main objective is to systematically review the barriers to good corporate governance practice in the global context. This study uses a systematic literature review whereby the authors analyse 24 selected articles. Therefore, the main findings indicated ten barriers to good corporate governance practices. The ten barriers are weak regulatory framework, perceived constraints, poor quality of information, external business factors, lack of awareness, confusion of authority, lack of monitoring, board diversity, transparency and investor protection. These findings provide significant contributions in theoretical development for potential scholars and practical implications for organisations, stakeholders, investors, and corporate leaders who aim to strengthen the governance framework, improve organisational resilience and promote sustainable value creation to understand these barriers comprehensively.

The Holistic Intelligent Healthcare Theory (HIHT): Integrating AI for Ethical, Transparent, and Human-Centered Healthcare Innovation

The rise of artificial intelligence (AI) in healthcare has the potential to significantly increase the efficiency, personalization, and overall efficacy of medical care delivery. However, its integration needs to be improved regarding ethical norms, data quality, openness, and human-centered care. This study proposes the Holistic Intelligent Healthcare Theory (HIHT), a comprehensive theory for guiding AI's ethical and practical use in healthcare. It draws on insights from theories such as the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), Socio-Technical Systems Theory (STS), Ethics of Care, Data Governance and Information Quality Theory, and Augmented Intelligence Theory. The HIHT highlights the importance of centralized governance, strong data quality, transparent AI methods, human-AI collaboration, and a reimagined role for healthcare practitioners—the "Intelligent Doctor." The study presents the theory's structures and investigates their implications for AI integration in healthcare, offering a road map for responsible and practical AI applications.

Performance-based budgeting reform and evolution of performance information quality: empirical analysis of Indonesia

Performance-based budgeting reform and evolution of performance information quality: empirical analysis of Indonesia

Government affiliation, analyst behavior and the economic consequences

AbstractA significant number of regional brokerage firms in China are owned by their respective local governments. We use this context to examine how local government affiliation affects brokerage firms’ research activities. Using a sample of analyst reports from 2013 to 2021, we find that analysts working at local government‐affiliated brokerage firms are more likely to cover firms within the local government's jurisdiction than non‐affiliated analysts. Local government‐affiliated analysts enjoy an information advantage, as evidenced by the issuance of more accurate earnings forecasts for local firms, compared to those of non‐affiliated analysts. The effect is stronger for local firms with lower information quality. Additionally, local government‐affiliated analysts show more optimism in stock recommendations, but not in earnings forecasts, for local firms, compared to non‐affiliated analysts. The effect is more pronounced for local firms that receive more local government subsidies, operate in regions with greater local government intervention or during the COVID‐19 pandemic and the National Congress conferences, and require more capital market support. The results of this study advance our understanding of the key determinants of analyst performance and provide new evidence in the debate on the role of government intervention in financial institutions.

Analysis of Cement properties using Hyperspectral Remote Sensing methods

Abstract. Understanding building material properties can play a key role in analyzing the health of structural elements in buildings. However, the field and laboratory tests can be laborious, time-consuming, and cost-intensive. Generally, the standard tests employed for characterizing the material properties are destructive in nature, but in the recent past, non-destructive testing (NDT) has given us the ease of understanding the material properties. Hyperspectral remote sensing technology has been exploited as one of the NDT methods for assessing the properties of building components. This study aims to investigate the quality information about cement using the hyperspectral remote sensing method and correlate it with the results of traditional quality testing methods. The materials used in the experiments included Ordinary Portland Cement (OPC), Portland Pozzolana Cement (PPC), and White Portland Cement (WPC). The cement samples were studied and experimented with for the identification of their types, and their temporal variability and changes in their spectral properties on which the strength of the samples depended were further checked. The study concluded that for OPC, PPC, and WPC, the absorption range is 1970 nm to 2020 nm, which is mainly due to the presence of different chemical compounds in cement. Also, the spectral reflectance decreases with time, and it can be concluded that in the present work, the strength of cement decreases with the decrease in spectral reflectance. Hence, Cement properties can be found using hyperspectral remote sensing data.

The Effectiveness of Tiktok in Increasing Brand Awareness Among Users

Technological advancements have revolutionized marketing strategies, particularly in the realm of social media. As businesses recognize the importance of brand awareness in consumer decision-making, platforms like TikTok have emerged as powerful tools for enhancing brand visibility. Despite its rapid rise in popularity, TikTok's effectiveness in increasing brand awareness remains underexplored. This study investigates "The Effectiveness of TikTok in Increasing Brand Awareness Among Users" with three primary objectives: (RO1) to identify the effect of Mobile Application Values, Information Quality, System Quality, and Influencer Trust on Brand Awareness; (RO2) to identify the effect between Brand Awareness and Word of Mouth; and (RO3) to analyze the effect between Brand Awareness on Purchase Intention. The research adopts a quantitative approach, utilizing a questionnaire distributed to B2C TikTok users. A sample size of 343 respondents was determined using stratified sampling. Descriptive and regression analyses were conducted to interpret the data. The results indicate that Mobile Application Value, System Quality, and Influencer Trust significantly influence Brand Awareness on TikTok, while Information Quality does not exhibit a significant effect. Moreover, Brand Awareness positively impacts both Word of Mouth and Purchase Intention, underscoring its pivotal role in consumer behavior. This study contributes to a deeper understanding of TikTok's potential as a branding tool and offers practical insights for marketers seeking to leverage the platform effectively. Despite limitations in sample size and survey biases, the findings provide a foundation for future research and the refinement of marketing strategies in the dynamic landscape of social media.

Incertidumbre, Estrés, Ansiedad, Depresión e Información en Personas con Esclerosis Múltiple

Theoretical Framework. Multiple sclerosis (MS) is associated with increased depression and anxiety, which in turn are related to stress and uncertainty. The amount and quality of information, relevant due to their association with uncertainty in different populations, have not been investigated in people with MS. Method. Through MS associations, a questionnaire was distributed that collected demographic data, information (attendance at informational talks, internet searches, etc.), stress, uncertainty, anxiety, and depression. A total of 119 people with MS participated, mostly Spanish women belonging to an association with an average age of 46 years and Relapsing-Remitting MS. Results. 57% and 39% of the sample might have anxiety and depression problems, respectively. There were differences in anxiety and stress according to the type of MS. Uncertainty showed correlations of .21-.26 with stress, anxiety, and depression. The sample was generally satisfied with the information they had, especially with that provided by healthcare professionals, and the latter was the only information source that showed a significant inverse correlation with uncertainty (r = -.22). Depression was correlated with the amount of information searched on the internet (r = .17). There were no differences in uncertainty, stress, anxiety, or depression according to membership in associations or attendance at informational talks. Conclusions. Providing people with MS with reliable, clear, and tailored information is crucial to fostering their understanding of the disease and their psychological well-being, with healthcare professionals playing a key role in this.

Kepuasan Mahasiswa terhadap Biro Administrasi dan Registrasi Akademik di Universitas Stella Maris Sumba

This research aims to analyze the level of student satisfaction with the services provided by the Academic Administration and Registration Bureau at Stella Maris University, Sumba. The method used in this research is a survey with a quantitative approach, where data is collected through questionnaires distributed to students from various study programs. Data analysis was carried out using descriptive statistical techniques to describe the characteristics of respondents and their level of satisfaction with various aspects of service, including speed of service, quality of information, and the attitude of bureau officers. The research results show that the majority of students are satisfied with the services provided, although there are several aspects that need to be improved, such as response time to questions and completeness of the information provided. This research provides recommendations for service improvements, including increased training for bureau staff and the development of more efficient information systems. It is hoped that these findings can contribute to improving the quality of academic administration services at Stella Maris University, Sumba.

The Effects of Electronic Health Records on Medical Error Reduction: Extension of the DeLone and McLean Information System Success Model.

Medical errors are becoming a major problem for health care providers and those who design health policies. These errors cause patients' illnesses to worsen over time and can make recovery impossible. For the benefit of patients and the welfare of health care providers, a decrease in these errors is required to maintain safe, high-quality patient care. This study aimed to improve the ability of health care professionals to diagnose diseases and reduce medical errors. Data collection was performed at Dr George Mukhari Academic Hospital using convenience sampling. In total, 300 health care professionals were given a self-administered questionnaire, including doctors, dentists, pharmacists, physiologists, and nurses. To test the study hypotheses, multiple linear regression was used to evaluate empirical data. In the sample of 300 health care professionals, no significant correlation was found between medical error reduction (MER) and knowledge quality (KQ) (β=.043, P=.48). A nonsignificant negative relationship existed between MER and information quality (IQ) (β=-.080, P=.19). However, a significant positive relationship was observed between MER and electronic health records (EHR; β=.125, 95% CI 0.005-0.245, P=.042). Increasing patient access to medical records for health care professionals may significantly improve patient health and well-being. The effectiveness of health care organizations' operations can also be increased through better health information systems. To lower medical errors and enhance patient outcomes, policy makers should provide financing and support for EHR adoption as a top priority. Health care administrators should also concentrate on providing staff with the training they need to operate these systems efficiently. Empirical surveys in other public and private hospitals can be used to further test the validated survey instrument.

The utility of ChatGPT in gender-affirming mastectomy education

IntroductionThe integration of AI such as ChatGPT in medicine has been showing promise in enhancing patient education. Gender-affirming mastectomy (GAM) is a surgical procedure designed to help individuals transition to their self-identified gender, playing a crucial role in mitigating psychological distress for many transmasculine and non-binary (TNB) patients. With increased demand and attention towards GAM, plastic and reconstructive surgeons may rely on AI-driven chatbots as an accessible, accurate, and patient-driven model for relevant details on this procedure. Specific Aim(s)This study aimed to assess the quality and readability of information provided by ChatGPT in response to frequently asked questions (FAQs) related to GAM. MethodsInspired by online forums and physician websites, 10 frequently asked questions (FAQs) about pre- and postoperative topics were submitted to ChatGPT and assessed using validated readability score measures and expert interpretation. ResultsThe average readability score was 16.0 ± 1, indicating a college or graduate reading level. Mean accuracy, comprehensiveness, and danger scores were 8.8 ± 0.5, 7.8 ± 0.7, and 2.2 ± 0.4, respectively. Although physicians appreciated ChatGPT's tone, patient autonomy, and advice to seek professional medical and mental help, they also cited instance of generic information, misinformation, support of debated techniques, and pathologization of gender dysphoria. ConclusionEven with its promise in providing accurate and comprehensive information on GAM, ChatGPT’s current limitations suggest caution as a supplementary tool to physician consultation.

Investigating 10 Yr of Volcanoacoustic Activity at Tungurahua Volcano, Ecuador, Aided by Machine Learning

Abstract Here, we present the results of applying diverse data processing and machine learning tools to investigate a very large dataset obtained from single station infrasonic recordings from the last 10 yr of the most recent period of explosive activity at Tungurahua volcano, Ecuador. To increase the quality and quantity of information extracted from the large data set and enhance pattern recognition, we combined traditional techniques with more recent ones. We divided the investigation into sequential steps: detection, discrimination, cleaning, and clustering. For the detection step, we tested the classical short-term average/long-term average algorithm and an algorithm specific for explosions detection called “Volcanic INfrasound Explosions Detector Algorithm (VINEDA)” and detected 118,516 events. To clean the detected signals from potential false positives, we used supervised classification that reduced the events to 75,483, and a catalog cleaning procedure using shallow learners including support vector machines, random forests, and a single layer neural network, trained using data from a manual catalog, to a final number of 36,359 events. This led to a sixfold increase in detected explosions compared to the manual catalog. Then, we applied hierarchical clustering to a well-studied time window of activity using two independent difference metrics: dynamic time warping and waveform cross correlation and showed the insights and drawbacks from this approach. We showed that the different techniques were able to reveal repeating and striving events between selected different eruptive phases and associated them to possible changes in eruptive dynamics. Finally, to analyze the whole dataset at once we used a convolutional autoencoder network and obtained similar results to the classical clustering in a fraction of the time. We identified different families of explosions that appeared, sometimes intermittently, and revealed various potentially competing eruptive processes during the whole time period.

Определение литологического состава осадочных пород для построения объемной модели по данным ГИС

The features of the lithological composition of productive sediments and their consideration in the petrophysical modeling of a volumetric model based on a GIS complex are considered. It is noted that on the basis of X-ray spectral and granulometric analysis, it is possible to obtain reliable information about the structure, texture, component and mineral composition in order to clarify the petrophysical characteristics of the rocks under study. Using the example of two hydrocarbon deposits “K” and “N” the results of determining the lithological composition of sedimentary rocks from core from different age terrigenous deposits are discussed in order to build a petrophysical model of the entire well section, taking into account the areas of lack of information from direct studies (sludge and core). Electron microscopy and X-ray diffraction analysis are used to study finely dispersed (clay, siliceous, carbonate, etc.) rocks, which are especially important for accurate diagnosis of the mineral composition of rocks. In addition to the features of the geological structure of the deposit, the quantity and quality of the initial information largely determine the methods of constructing the model and the results obtained. The results of X-ray spectral analysis made it possible to determine the composition of chemical elements and the amount of each element in the sample. Information about the mineral composition of rocks and the lithological differences identified at the first stage are distributed to the part of the section where there is no or insufficient information on the core or sludge. The information obtained on the lithological composition of sediments gives the most complete picture of the geological structure of the section opened by the well and is further used as the basis of a volumetric model based on the data of geophysical surveys of GIS wells.

Customer perceptions about traceable meat: research from Northern China

Food traceability and food safety, including quality assurance processes, are essential for ensuring the health of members of society and can prevent food-supply-related problems. Meat-related food safety issues are significant, especially in developing countries like China. The main aim of this paper was to explore customer perceptions and purchase behavior, including willingness to pay, related to traceable meat. A qualitative exploratory approach was applied. Five focus groups were implemented with interviewees from Northern China, and grounded theory methodology was used in their analysis. The results showed that participants were influenced by product characteristics, sales-related factors, and subjective norms when purchasing meat. Their level of trust in traceability information was variable; respondents preferred independent quality assurance associations and information obtainable by scanning QR codes. The findings of this study may contribute to the introduction and development of food traceability systems in the meat industry, reinvigorating consumer trust.

MULTI-AGENCY DEVELOPMENT OF A NEW INFORMATION RESOURCE FOR PATIENTS WITH BRAIN METASTASES

Abstract AIMS Based in a large neuro-oncology centre which provides specialist care for hundreds of patients with BM per year, the authors identified a need for relevant, non-disease specific, technically accurate and holistically focussed patient information material. This project aimed to develop a comprehensive and patient-focussed information resource for patients with BM. METHOD A scoping exercise of twenty UK-based cancer charity websites was carried out. Generic cancer charity sites and sites of charities supporting the four main primary cancer groups which metastasize to the brain were targeted. Information pertaining to BM was collated and reviewed by a multidisciplinary group to assess for scope and quality of information provided. Particular attention was paid to identifying information which was technically accurate and specifically addressed the holistic needs of this patient group. RESULTS Information found was primary disease-specific, technically inaccurate and did not acknowledge the holistic needs of the patient. This exercise highlighted the need for comprehensive and relevant patient-focussed information material. A working group consisting of health professionals and BrainsTrust charity staff was formed to create an effective patient information resource. Existing BrainsTrust information templates were used to structure the new resource. Evidence-based clinical information was provided by the healthcare professionals involved and holistic information was created collaboratively with charity input. A patient reviewer was enlisted to provide feedback on draft versions. CONCLUSION This project resulted in production of a patient-focussed and comprehensive information resource on BM. Patient and healthcare professional feedback to date has been positive.

The double-edged sword of transparency: ESG disclosure's effect on competitive dynamics in manufacturing

This study explores the role and impact of Environmental, Social, and Governance (ESG) information on investor decision-making, focusing on the lack of standardized ESG reporting among companies. Although ESG disclosures can enhance a company’s legitimacy and attract investor interest, the voluntary nature of reporting has led to inconsistent practices and limited information quality. The research aims to develop a standardized ESG reporting model that meets investor needs while assessing the effects of ESG performance on corporate outcomes. Using a mixed-methods approach, the study combines qualitative research to formulate an ESG reporting model and quantitative methods to evaluate its impact on company performance. Data were collected from 167 manufacturing companies in Indonesia, selected based on their consistent publication of sustainability reports over four consecutive years. The findings reveal that ESG shows consistent high significance across all three models (Sig = 0.000 for Model-1, Model-2, and Model-3 regression). This uniform high significance underscores the growing importance of ESG factors in various aspects of corporate performance and perception. It suggests that ESG considerations are integral not only to stock returns and firm valuation but also to a company's competitive positioning. The study concludes that while ESG reporting is essential for corporate transparency, it may not always align with positive financial outcomes. This suggests the need for more comprehensive ESG frameworks to balance investor expectations and corporate performance.

Prototype Design IoT Based Air Quality Monitoring Tool for Urban Environment

In rapidly urban environments, air quality has become an important issue that affects public health and the environment. This research aims to design and implement a prototype of an IoT-based air quality monitoring device that can be used to monitor air conditions in urban environments. This prototype uses the DHT11 sensor for measuring temperature and humidity, the MQ135 sensor to detect the concentration of air pollutants such as CO, CO2, ALCOHOL, TOLUENE, NH4, and ACETONE, and an OLED LCD for displaying information. This system uses the NodeMCU ESP8266 as a microcontroller that connects devices to the internet and sends data to the Blynk application platform. The Blynk application serves as a user interface that allows for real-time monitoring of the device through a smartphone. With this system, users can obtain real-time air quality data to protect health and the environment in urban areas. The prototype evaluation shows that this system is effective in monitoring and displaying air quality information, as well as providing easy access to data through the Blynk application.

Optimizing fertilizer use by providing soil quality information: experimental evidence from Madagascar

BackgroundImproving food security in sub-Saharan Africa (SSA) requires increasing agricultural productivity. The increased and effective use of chemical fertilizers is widely recognized as one of the key strategies for achieving this goal. However, many smallholder farmers in SSA still grow crops without using fertilizer, and even when they do use fertilizer, the amount applied is often less than the recommended level. In addition to various constraints related to input markets and farmers’ socioeconomic characteristics, uncertainty about crop yield response is known to discourage fertilizer use. The purpose of this study was to investigate how site-specific information on soil characteristics can help farmers optimize their fertilizer application decisions by reducing uncertainty in yield response. Our unique approach uses simple binary information about the expected effectiveness of nitrogen fertilizer based on a single soil parameter.MethodologyThe simple binary information was generated for a focal rice plot of each 70 household. Based on the evaluation of oxalate-extractable phosphorus content in the soil composites collected from each of these plots, each plot was categorized into either high or low in terms of the expected effectiveness of nitrogen application. A randomized controlled trial was conducted to estimate the impact of providing this simple binary information primarily on nitrogen application rate and, consequently, on rice yield and income at plot-level and household-level.ResultsThe results showed that first, compared to those in the target plots of the control households, the nitrogen application rate was greater in the target plots of the treatment households who were informed of the high expected effectiveness. Second, information that the expected effectiveness was high increased the amount of nitrogen fertilizer in the target plot compared to that in other plots with no information about expected effectiveness within a household. Third, this change in fertilizer allocation led to higher rice yields and higher rice incomes at the household level.ConclusionsThese results highlight how the binary information about the expected effectiveness with a single soil parameter can improve fertilizer allocation among rice plots and its use efficiency to increase rice productivity and income.

Live Streaming Adoption for Small Medium Businesses to Support the Achievement Of SDG’s

Objective: The objective of this research is to analyze emerging digital technology and their impact on SDG’s innovation and digital economy. SME’s participation in live streaming will be explored to understand the impact on SME’s SDG’s Theoretical Framework: Social cognitive theory (SCT) is used as a theoretical base. The SCT can explain why individuals want to learn to observe others in social media/online shopping, Method: The variables studied were Product Information Quality (PIQ), Streamers’ Information Quality (SIQ), trust, and impulse buying. A quantitative approach by survey questionnaire distribution was conducted. The population is anyone who has experience with live streaming in Indonesia. Purposive sampling is chosen, and 325 valid data have been gathered for analysis using PLS-SEM. Results and Discussion: Product and streamers Information Quality positively influence trust but PIQ and SIQ do not positively influence impulse buying. Trust fully mediates between PIQ and SIQ to impulse buying. This confirms the role of trust as perceived by customers, as SMES have not yet gained market awareness thus trust is crucial to lead the decision to buy. Research Implications: The success of SMEs in the digital economy will help them access the market more effectively and efficiently. SMEs’ success means increasing community welfare more evenly as well as a more sustainable environment is achieved due to SMEs’ sense of belonging to their homeland. Originality/Value: The originality is the structural model and the observation of the model to SMES in adopting live streaming. The PIQ and SIQ were analyzed in the context of SME’s offerings.

The Influence of Personal Selling and Social Media Marketing on Purchase Behavior Mediated by Brand Awareness, Brand Association, Perceived Quality, and Brand Loyalty at PT. Asuransi Bangun Askrida Bandung Branch

The marketing landscape has shifted from traditional to digital approaches, requiring companies to adapt strategies to remain competitive. Askrida, using both personal selling and social media marketing, seeks to boost general insurance production and maintain market share. However, despite these efforts, Askrida lags behind its five main competitors in profit, and general insurance sales remain inadequate, with increasing customer complaints. This study aims to evaluate how personal selling and social media marketing influence consumer behavior at Askrida through brand awareness, brand association, perceived quality, and brand loyalty. Using a quantitative approach, this research collected primary and secondary data through Google Forms questionnaires distributed to 416 non-corporate customers of Askrida Bandung Branch. The sampling method employed was purposive sampling, and data analysis was conducted using SEM-PLS (Partial Least Squares) via SmartPLS software. The findings indicate that both personal selling and social media marketing significantly affect brand awareness, brand association, perceived quality, and brand loyalty. Personal selling impacts purchasing behavior through these mediating variables, though brand awareness itself does not directly influence purchasing behavior. Conversely, social media marketing affects purchasing behavior through brand awareness, brand association, perceived quality, and brand loyalty. Recommendations for Askrida's Marketing Team include enhancing personal selling by improving product information quality through additional training for sales staff and using interactive training materials. For social media marketing, it is advised to update content with relevant and engaging information. Increasing brand visibility and consistency in marketing campaigns, creatively strengthening brand associations, enhancing quality perception through customer testimonials and unique product features, and implementing loyalty programs are crucial strategies for Askrida to bolster market position and consumer loyalty. This study also notes that the findings may not be generalized to all digital marketing activities and suggests further research with additional variables and a more in-depth evaluation of effectiveness.