Introduktion: I dagens digitala tidsålder vänder sig många individer till internet som sin första källa till hälsoinformation. Forskning har dock visat att majoriteten av digital hälsoinformation är av låg kvalitet och har bristfällig korrekthet. En stor del av denna information består sannolikt av både desinformation och missinformation. Syfte: Syftet med denna studie var att sammanställa resultaten från peer-review granskade studier som utvärderar korrektheten hos digital hälsoinformation, med särskilt fokus på studier som använder expertgranskade texter utvärderade mot etablerade riktlinjer. Metod: Den 7 april 2024 genomsöktes tre databaser – MEDLINE EBSCO, Scopus och PubMed. Totalt 21 artiklar inkluderades. Resultaten från dessa artiklar kategoriserades och analyserades induktivt utifrån Narro och Tudges neo-ekologiska teori. Resultat: Fyra huvudkategorier skapades gällande informationens korrekthet: god, måttlig, bristfällig och varierande. Av de inkluderade artiklarna bedömdes 3 (14%) ha god korrekthet, 4 (19%) artiklar måttlig korrekthet, 13 (62%) bristfällig korrekthet och 1 (5%) hade varierande. Därtill ansågs 76% av det inkluderade materialet från trovärdiga källor ha bristfällig korrekthet. Slutsats: Majoriteten av de inkluderade studierna och det trovärdiga materialet har bristfällig korrekthet. Dessutom, tenderar studier som uppvisar en högre grad av korrekthet, ha sämre läsbarhet och den övergripande kvaliteten är ofta bristfällig, vilket även gör det svårt för konsumenter att förstå informationen. / Introduction: In today's digital age, many individuals turn to the internet as their initial source of health information. However, research has shown that the majority of online health information is of poor quality and low accuracy. A significant portion of this information likely includes both misinformation and disinformation. Aim: The aim of this study was to synthesize findings from peer-reviewed research assessing the accuracy of online health information, with a particular emphasis on studies that utilize expert-reviewed content evaluated against established guidelines. Method: On 7 April 2024, three databases—MEDLINE EBSCO, Scopus, and PubMed—were searched. A total of 21 articles were included in the systematic review. The results from these articles were categorized and inductively examined through the lens of Narro and Tudge’s neo-ecological theory. Results: Four primary categories were created concerning the accuracy of the information: good, moderate, poor, and varied. Among the included articles, 3 (14%) were deemed to have good accuracy, 4 (19%) articles exhibited moderate accuracy, 13 (62%) demonstrated poor accuracy, and 1 (5%) had varied accuracy. Additionally, 76% of the included material from trustworthy sources were categorized as having poor accuracy. Conclusion: The majority of the included studies and trustworthy material were found to have poor accuracy. Furthermore, even when studies exhibited a higher degree of accuracy, the readability and overall quality were often deficient, making it difficult for consumers to understand.

Yes / This study explored healthcare quality issues affecting the reporting and investigation levels of digital incident reporting systems. Methods: A total of 38 health information technology-related incident reports (free-text narratives) were collected from one of Sweden’s national incident reporting repositories. The incidents were analysed using an existing framework, i.e., the Health Information Technology Classification System, to identify the types of issues and consequences. The framework was applied in two fields, ‘event description’ by the reporters and ‘manufacturer’s measures’, to assess the quality of reporting incidents by the reporters. Additionally, the contributing factors, i.e., either human or technical factors for both fields, were identified to evaluate the quality of the reported incidents. Results: Five types of issues were identified and changes made between before-and-after investigations: Machine to software- related issues (n = 8), machine to use-related issues (n = 5), software to software-related issues (n = 5), use to software- related issues (n = 4) and use to use-related issues (n = 1). Over two-thirds (n = 15) of the incidents demonstrated a change in the contributing factors after the investigation. Only four incidents were identified as altering the consequences after the investigation. Conclusion: This study shed some light on the issues of incident reporting and the gap between the reporting and investigation levels. Facilitating sufficient staff training sessions, agreeing on common terms for health information technology systems, refining the existing classifications systems, enforcing mini-root cause analysis, and ensuring unit-based local reporting and standard national reporting may help bridge the gap between reporting and investigation levels in digital incident reporting.

Little is known regarding registered nurse (RN) information management practice in long-term care (LTC) settings. This study identifies LTC RNs’ information management practice and needs, which are important for designing and implementing health information technology (HIT) in LTC settings. Methods: This descriptive qualitative study combines direct observations and semi-structured interviews, conducted at Alberta’s LTC facilities between May 2014 and August 2015. The constant comparative method of joint coding was used for data analysis. Results: Nine RNs from six nursing homes participated in the study. Based on the RNs’ existing information management system requirements, a graphic information flow model was constructed. Conclusion: This baseline study identified key components of LTC RNs’ information management system. The information flow model may assist HIT developers with future design and development of HIT solutions for LTCs, serve as a communication tool between RNs and developers to refine requirements and support further LTC HIT research. / Graduate

This research presents a framework for enhancing and analyzing time-sequenced mammographic images for detection of cancerous tissue, specifically designed to assist radiologists and physicians with the detection of breast cancer. By using computer aided diagnosis (CAD) systems as a tool to help in the detection of breast cancer in computed tomography (CT) mammography images, previous CT mammography images will enhance the interpretation of the next series of images. The first stage of this dissertation applies image subtraction to images from the same patient over time. Image types are defined as temporal subtraction, dual-energy subtraction, and Digital Database for Screening Mammography (DDSM). Image enhancement begins by applying image registration and subtraction using Matlab 2012a registration for temporal images and dual-energy subtraction for dual-energy images. DDSM images require no registration or subtraction as they are used for baseline analysis. The image data are from three different sources and all images had been annotated by radiologists for each image type using an image mask to identify malignant and benign. The second stage involved the examination of four different thresholding techniques. The amplitude thresholding method manipulates objects and backgrounds in such a way that object and background pixels have grey levels grouped into two dominant and different modes. In these cases, it was possible to extract the objects from the background using a threshold that separates the modes. The local thresholding introduced posed no restrictions on region shape or size, because it maximized edge features by thresholding local regions separately. The overall histogram analysis showed minima and maxima of the image and provided four feature types--mean, variance, skewness, and kurtosis. K-means clustering provided sequential splitting, initially performing dynamic splits. These dynamic splits were then further split into smaller, more variant regions until the regions of interest were isolated. Regional-growing methods used recursive splitting to partition the image top-down by using the average brightness of a region. Each thresholding method was applied to each of the three image types. In the final stage, the training set and test set were derived by applying the four thresholding methods on each of the three image types. This was accomplished by running Matlab 2012a grey-level, co-occurrence matrix (GLCM) and utilizing 21 target feature types, which were obtained from the Matlab function texture features. An additional four feature types were obtained from the state of the histogram-based features types. These 25 feature types were applied to each of the two classifications malignant and benign. WEKA 3.6.10 was used along with classifier J48 and cross-validation 10 fold to find the precision, recall, and f-measure values. Best results were obtained from these two combinations: temporal subtraction with amplitude thresholding, and temporal subtraction with regional-growing thresholding. To summarize, the researcher's contribution was to assess the effectiveness of various thresholding methods in the context of a three-stage approach, to help radiologists find cancerous tissue lesions in CT and MRI mammography images.

When face-to-face physical medical exams are not possible, virtual physical exams, in the form of a pictorial medical exam/history, can be substituted, and telemedicine can be the means to deliver these virtual exams. The goal of this work was to determine if presence in the form of a visual and/or pictorial medical history can be of benefit to clinicians in the diagnosis of medical conditions of individuals with developmental disabilities (DDs) and/or intellectual disabilities (IDs), in particular those who cannot, because of their cognitive and/or physical disabilities, verbally relate their illness to a clinician. Virtual exams can also be useful in cases where clinicians may need additional advice from fellow experts, especially if those experts are not physically present. A web-based telemedicine application used for treating persons with DD/IDs was developed. This application includes a visual medical history component incorporated into an electronic medical records application. The purpose is to allow the clinician to use an environment that integrates a written and visual representation of a patient’s medical history and physical findings to aid the clinician in determining a medical diagnosis. Twenty-two clinicians and five direct service aids of a New York State Developmental Disabilities Services Office facility, who deliver healthcare to DD/ID patients on a daily basis, accessed the telemedicine application instead of their traditional hardcopy/paper medical history when examining patients. A comprehensive survey was distributed to the clinicians to determine the effectiveness of the application as well as help answer the primary questions proposed by this research. The results of this study showed that presence in the form of a video medical history is preferred by clinicians rather than having just a written medical history of the patient. Clinicians felt the visual medical history component of the telemedicine application was useful and informative for delivering healthcare to individuals with DD/ID and enabled them in diagnosing a patient as well as lessened the need to transfer patients to the emergency room, resulting in a significant cost savings.

Diabetes is the seventh leading cause of death in the United States. With the population rapidly aging, it is expected that 1 out of 3 Americans will have diabetes by 2050. Mobile devices and mobile applications have the potential to contribute to diabetes self-care by allowing users to manage their diabetes by keeping track of their blood glucose levels. Usability is important for systems that help people self-manage conditions such as diabetes. Age and diabetes-related cognitive decline might intensify the impact of usability issues for the users who need these mobile applications the most. As highlighted by usability researchers, the context of use (i.e. environment, user, task, and technology) has a significant impact on usability. The environment (lighting, temperature, audio and visual distractions, etc.) is of special interest to the mobile usability arena since in the case of mobile devices, is always changing. This dissertation aims to support the claim that context and more specifically environmental distraction such as semantic auditory distractions impact the usability of mobile applications. In doing so, it attempts to answer the following research questions: 1) Does semantic auditory distractions reduce the effectiveness of a blood glucose tracking mobile application? 2) Does semantic auditory distractions reduce the efficiency of a blood glucose tracking mobile application? 3) Does semantic auditory distractions reduce the user satisfaction of a blood glucose tracking mobile application? To answer the study research questions, a true experimental design was performed involving 30 adults with type 2 diabetes. Participants were paired based on their age and experience with smartphones and randomly assigned to the control (no semantic auditory distractions) or experimental (semantic auditory distractions) group. Research questions were tested using the general linear model. The results of this study confirmed that semantic auditory distractions have a significant effect on efficiency and effectiveness, and hence they need to be taken into account when evaluating mobile usability. This study also showed that semantic auditory distractions have no significant effect on user satisfaction. This dissertation enhances the current knowledge about the impact of semantic auditory distractions on the usability of mobile applications within the diabetic senior population.

This study demonstrates that hybrid methods can be used for measuring the risk severity of technology-induced errors (TIE) that result from use of health information technology (HIT). The objectives of this research study include: 1. Developing an integrated conceptual risk assessment model to measure the risk severity of technology-induced errors. 2. Analyzing the criticality and risk thresholds associated with TIE’s contributing factors. 3. Developing a computer-based simulation model that could be used to undertake various simulations of TIE’s problems and validate the results. Using data from published papers describing three sample problems related to usability and technology-induced errors, hybrid methods were developed for assessing the risk severity and thresholds under various simulated conditions. A risk assessment model (RAM) and its corresponding steps were developed. A computer-based simulation of risk assessment using the model was also developed, and several runs of the simulation were carried out. The model was tested and found to be valid. Based on assumptions and published statistics obtained by publically available databases, we measured the risk severity and analyzed its criticality to classify risks of contributing factors into four different classes. The simulation results validated the efficiency and efficacy of the proposed methods with the sample problems. / Graduate / 0723 / 0680 / 0769 / tschio2011@gmail.com

Thesis (MScMedSc (Rehabilitation))--University of Stellenbosch, 2008. / Stroke is the second commonest cause of mortality worldwide and remains a leading cause of adult physical disability. It is estimated that sixty percent of South African stroke survivors require assistance with at least one activity of daily living. This burden is predominantly on the shoulders of mostly untrained caregivers. The process of enabling caregivers to make choices conducive to their own health as well as the health of the stroke survivors is multidimensional. One of the cornerstones of this process is the provision of information. In 1995, the Centre for Rehabilitation Studies of the University of Stellenbosch started to develop a training package for stroke care at home. The training takes the form of an interactive workshop and a booklet with practical information. The aim of this study was to refine and pilot this booklet for implementation with the training. The study found that existing guidelines to evaluate the appropriateness of written material for developing communities (measured by Hugo’s grading model), were inadequate. Consequently, a new checklist, based on twenty existing checklists, was compiled. This list, as well as the Suitability Assessment of Material (SAM), was used to evaluate the booklet and make recommendations for a pre-pilot refinement. Even though this checklist has not been validated, it revealed similar results to the SAM when applied to the booklet. After cosultation with the authors, improvements were effected to the booklet The booklet was tested with four samples of the target audience. The functional literacy of the participants was determined using a standardised literacy test. A fifth sample completed a questionnaire on their preference between the pre- and postrefined booklet. Experts in the field of rehabilitation and graphic design also commented on the booklet. This study confirmed the need of stroke survivors and their caregivers for written health information. The refined booklet was found to be an appropriate tool to address the needs of the target audience. The participants perceived the booklet as useful and comprehensible and the readability level was shown to correspond with the tested literacy level of the samples. However, there is a need for printed material on topics related to stroke not currently covered in the booklet, e.g. spasticity. This study showed that the checklist could be used to tailor written health information that is preferred by the target audience. It confirmed that the testing of printed material with stakeholders could expose additional gaps after applying the checklist. Recommendations for further improvements were made based on the comments of the participants. It is foreseen that the new checklist could be a valuable tool for developing future written health material. Finally, it is recommended that an interdisciplinary team that includes a graphic designer be involvement from the planning stages.

A new hospital in United Arab Emirates (UAE) plans to adopt health information technology (HIT) and become fully digitalized once operational. The hospital has identified a need to assess basic computer literacy of new employees prior to offering them training on various HIT applications. Lack of research in identifying an accurate assessment method for basic computer literacy among health care professionals led to this explanatory correlational research study, which compared self-assessment scores and a simulated actual computer skills test to find an appropriate tool for assessing computer literacy. The theoretical framework of the study was based on constructivist learning theory and self-efficacy theory. Two sets of data from 182 hospital employees were collected and analyzed. A t test revealed that scores of self-assessment were significantly higher than they were on the actual test, which indicated that hospital employees tend to score higher on self-assessment when compared to actual skills test. A Pearson product moment correlation revealed a statistically weak correlation between the scores, which implied that self-assessment scores were not a reliable indicator of how an individual would perform on the actual test. An actual skill test was found to be the more reliable tool to assess basic computer skills when compared to self-assessment test. The findings of the study also identified areas where employees at the local hospital lacked basic computer skills, which led to the development of the project to fill these gaps by providing training on basic computer skills prior to them getting trained on various HIT applications. The findings of the study will be useful for hospitals in UAE who are in the process of adopting HIT and for health information educators to design appropriate training curricula based on assessment of basic computer literacy.

No abstract available.