Supplementary Source Of Information Research Articles

An Effective Method for Estimating the Population Mean That Utilizes Dual Auxiliary Information

To improve the effectiveness of population estimators, researchers have recently implemented dual supplementary information. They employed traditional rankings, the empirical cumulative distribution function, and indicator functions as supplementary sources of information in their analysis. An improved family of population mean estimators is introduced in this article, which utilizes the relative ranks of the auxiliary information’s configurations to incorporate the relevant information. A first-order approximation is employed to derive the mathematical expressions for the bias and the mean-squared error (MSE) of the proposed family of estimators. The empirical analysis is investigated to demonstrate the practicality of the proposed estimators in real-world scenarios. Additionally, the theoretical conclusions are effectively validated by the Monte Carlo simulation integration. Our results unequivocally indicate that the proposed family of estimators surpasses their current counterparts.

Development of a model for assessing the technical condition of Baghdad bridges

The research aims to develop a significant model for assessing the condition of bridges. This model may serve as a supplementary source of information in determining bridge condition ratings not only in Baghdad, but also in other regions with similar operating conditions. The authors also used the methods of mathematical statistics, probability theory, and mathematical theory of planning to conduct an experiment using the results of bridge survey. Currently, the Commission on Audit uses financial depreciation models to determine the service life of structures, with no alternative formulas available for predicting this parameter in the country. Therefore, the authors consider a new approach on the basis of available research on depreciation models. This approach is based on assessment of the condition of 30 structural elements of a bridge, as well as the results of inspections conducted by the Department of Public Works and Highway Bridges. The purpose was to determine the applicability of available data as meaningful variables in identifying a regression model to predict the condition of such bridges in Baghdad. Statistical data for determining the coefficients and dependent variables provided a relevant model for bridge condition assessment, which can be applied to identify the technical state of bridge structures.

In the future I will use corpora in my classroom: is it really applicable?

The aim of this study was to assess in-service teachers’ pedagogical skills that enable them to exploit corpora successfully in their daily teaching. The teachers attended an intensive training course and were then asked to submit end-of-course projects. The projects involved designing lesson plans based on the teaching contexts and implementing corpora into these plans according to their contexts. The project outcomes revealed that the submitted plans were preliminary and basic in terms of using corpus resources and activities. However, the teachers were genuinely keen to implement corpora into their daily teaching. The teachers applied corpora as an additional teaching methodology and in supplementary activities after explaining the learning units’ aims, periods, foci, and so on. They used corpora as hands-on supplementary sources of information, which was understandable for early application. The teachers seemed willing to implement corpora in their classrooms and needed no further training, but they might still need more guidance and feedback on the first-time application, which could lead to successful implementation.

Can ChatGPT provide health information as physicians do? Preliminary findings from a cross-sectional study of online medical consultation

Introduction. ChatGPT has shown promise in medical consultation. This paper presents the preliminary findings of evaluating the capability of ChatGPT in responding to real-world patient questions from a patient point of view, using physician responses as a benchmark. Method. 24 patient questions and physician responses were collected from a Chinese professional medical consultation platform. The corresponding ChatGPT responses were also collected. Five evaluators without medical background were given the patient questions and responses from both sources in random order. Evaluations were made in terms of the quality and presented empathy of collected responses. Analysis. Evaluation scores were analysed using descriptive statistical method. Results. Preliminary findings demonstrated that ChatGPT could be considered as a dependable source for acquiring useful health information. However, it was not able to present the feeling of empathy to patients compared with human physicians. Conclusion. We recommend that physicians consider utilizing ChatGPT as a supplementary information source when addressing general medical consultations to improve the experience of seeking medical information for patients.

The Fight Against Hailstorms in Italy, 1950–70: A Long History of Confirmation Bias

This article analyzes the experiments for hail suppression by means of exploding rockets in Italy, where a remarkable national program of active defense was undertaken in the period 1950–70. The history of the trials of this technique is reconstructed in view of highlighting the methodological flaws of the entire experimental approach. A supplementary source of information is offered by about 1,600 “storm postcards”: reports sent back by farmers after single weather events. An archive of these postcards, recently collected, digitized, and analyzed for the Trentino region (northern Italy), offers an interesting glimpse into the scientific and pseudoscientific approaches to a difficult to predict and volatile phenomenon, both for farmers and for appointed experts.

Artificial intelligence in practice: measuring its medical accuracy in oculoplastics consultations

Purpose: The aim of this study was to investigate the medical accuracy of responses produced by Chat Generative Pretrained Transformer 4 (Chat GPT-4) and DALLE-2 in relation to common questions encountered during oculoplastic consultations. Methods: The 5 most frequently discussed oculoplastic procedures on social media were selected for evaluation using Chat GPT-4 and DALLE-2. Questions were formulated from common patient concerns and inputted into Chat GPT-4, and responses were assessed on a 3-point scale. For procedure imagery, descriptions were submitted to DALLE-2, and the resulted images were graded for anatomical and surgical accuracy. Grading was completed by 5 oculoplastic surgeons through a 110-question survey. Results: Overall, 87.3% of Chat GPT-4’s responses achieved a score of 2 or 3 points, denoting a good to high level of accuracy. Across all procedures, questions about pain, bruising, procedure risk, and adverse events garnered high scores. Conversely, responses regarding specific case scenarios, procedure longevity, and proceduredefinitions were less accurate. Images produced by DALLE-2-were notably subpar, often failing to accurately depict surgical outcomes and realistic details. Conclusions: Chat GPT-4 demonstrated a creditable level of accuracy in addressing common oculoplastic procedure concerns. However, its limitations in handling case-based scenarios suggests that it is best suited as a supplementary source of information rather than a primary diagnostic or consultative tool. The current state of medical imagery generated by means of artificial intelligence lacks anatomical accuracy. Significant technological advancements are necessary before such imagery can complement oculoplastic consultations effectively.

Development of a topic‐specific bibliographic database supporting the updates of SPIRIT 2013 and CONSORT 2010

AbstractIntroductionAn important mechanism of research waste is inadequate incorporation of, and references to, previous relevant research. Identifying references for a research manuscript can be challenging, in part due to the exponential rise in potentially relevant literature to consider. For large research projects, such as developing or updating reporting guidelines, it may be helpful to construct a supportive topic‐specific bibliographic database.MethodsIn support of updating the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) 2013 and the CONsolidated Standards Of Reporting Trials (CONSORT) 2010, we developed the SPIRIT‐CONSORT Evidence Bibliographic database (SCEBdb): a freely available topic‐specific bibliographic database of publications providing an evidence foundation for the updates. We searched multiple sources of potential publications and tagged included ones with database‐specific keywords. For context, we also formulated 10 core considerations for constructing topic‐specific bibliographic databases and identified and described 5 illustrative other databases.ResultsAs of April 2024, the SCEBdb included 846 publications. The database proved useful as a supplementary information source for our scoping review of published comments on SPIRIT 2013 and CONSORT 2010, for a supplementary Delphi process, and in the writing phase of the guidance documents. We expect that the database will be useful for future projects within the fields of clinical research methodology, bias, evidence synthesis, and randomized trials.ConclusionThe methods involved in constructing the SCEBdb, and our suggested core considerations for topic‐specific bibliographic databases, could be helpful for researchers reflecting on whether, and how, to develop a topic‐specific bibliographic database.

Human-AI collaboration patterns in AI-assisted academic writing

ABSTRACT Artificial Intelligence (AI) has increasingly influenced higher education, notably in academic writing where AI-powered assisting tools offer both opportunities and challenges. Recently, the rapid growth of generative AI (GAI) has brought its impacts into sharper focus, yet the dynamics of its utilisation in academic writing remain largely unexplored. This paper focuses on examining the nature of human-AI interactions in academic writing, specifically investigating the strategies doctoral students employ when collaborating with a GAI-powered assisting tool. This study involves 626 recorded activities on how ten doctoral students interact with GAI-powered assisting tool during academic writing. AI-driven learning analytics approach was adopted for three layered analyses: (1) data pre-processing and analysis with quantitative content analysis, (2) sequence analysis with Hidden Markov Model (HMM) and hierarchical sequence clustering, and (3) pattern analysis with process mining. Findings indicate that doctoral students engaging in iterative, highly interactive processes with the GAI-powered assisting tool generally achieve better performance in the writing task. In contrast, those who use GAI merely as a supplementary information source, maintaining a linear writing approach, tend to get lower writing performance. This study points to the need for further investigations into human-AI collaboration in learning in higher education, with implications for tailored educational strategies and solutions.

Women’s Participation in Training on The Processing of Economic Value Rubber Seeds and Local Wisdom Based in Curahtakir Village, Jember

Curahtakir Village, located in Jember, is affiliated with PTPN XII and serves as a prominent rubber-producing community. A significant proportion of the village's population comprises women who are actively engaged in rubber-related labor. A significant quantity of rubber seeds is discarded and commercially traded at a price range of IDR 2000-3000 per kilogram. The absence of sufficient knowledge regarding the local potential necessitates the provision of training programs focused on the conversion of rubber seeds into high-value food products. The rubber seed chip products have the potential to enhance the local wisdom of Curahtakir Village. This research explains women's participation, empowerment through training for women, and training based on local wisdom. The study involved conducting interviews with female rubber workers, trainees, and members of the local community. The village chiefs serve as supplementary sources of information to obtain insights on the involvement of women in training programs. The findings indicated a significant level of active participation among women. During the pre-planning, the activities aimed at promoting women's participation persist in their planning and evaluation, despite encountering various obstacles, such as the challenges posed by their existing work commitments. The implementation continued to run well, the participants continued to follow the activity process to completion.

Snakebite Advice and Counseling From Artificial Intelligence: An Acute Venomous Snakebite Consultation With ChatGPT.

Snakebites, particularly from venomous species, present a significant global public health challenge. Access to accurate and timely information regarding snakebite prevention, recognition, and management is crucial for minimizing morbidity and mortality. Artificial intelligence (AI) language models, such asChatGPT (Chat Generative Pre-trained Transformer), have the potential to revolutionize the dissemination of medical information and improve patient education and satisfaction. This study aimed to explore the utility of ChatGPT, an advanced language model, in simulating acute venomous snakebite consultations. Nine hypothetical questions based on comprehensive snakebite management guidelines were posed to ChatGPT, and the responses were evaluated by clinical toxicologists and emergency medicine physicians. ChatGPT provided accurate and informative responses related to the immediate management of snakebites, the urgency of seeking medical attention, symptoms, and health issues following venomous snakebites, the role of antivenom, misconceptions about snakebites, recovery, pain management, and prevention strategies. The model highlighted the importance of seeking professional medical care and adhering to healthcare practitioners' advice. However, some limitations were identified, including outdated knowledge, lack of personalization, and inability to consider regional variations and individual characteristics. ChatGPT demonstrated proficiency in generating intelligible and well-informed responses related to venomous snakebites. It offers accessible and real-time advice, making it a valuable resource for preliminary information, education, and triage support in remote or underserved areas. While acknowledging its limitations, such as the need for up-to-date information and personalized advice, ChatGPT can serve as a supplementary source of information to complement professional medical consultation and enhance patient education. Future research should focus on addressing the identified limitations and establishing region-specific guidelines for snakebite management.

On the Effectiveness of Images in Multi-modal Text Classification: An Annotation Study

Combining different input modalities beyond text is a key challenge for natural language processing. Previous work has been inconclusive as to the true utility of images as a supplementary information source for text classification tasks, motivating this large-scale human study of labelling performance given text-only, images-only, or both text and images. To this end, we create a new dataset accompanied with a novel annotation method—Japanese Entity Labeling with Dynamic Annotation—to deepen our understanding of the effectiveness of images for multi-modal text classification. By performing careful comparative analysis of human performance and the performance of state-of-the-art multi-modal text classification models, we gain valuable insights into differences between human and model performance, and the conditions under which images are beneficial for text classification.

Should Inflammatory Bowel Disease Clinicians Provide Their Patients with e-Health Resources? Patients' and Professionals' Perspectives.

Introduction: The internet is emerging as a source of information for patients with inflammatory bowel disease (IBD). However, it is not always reliable and may cause anxiety. We aim to assess patients' information habits and patients' and professionals' perceptions of a national website integrated as an educational resource for the IBD unit. Methods: Patients aged 18-65 years, comfortable with the internet, and attending follow-ups at participating IBD units (March-June 2019) and their professionals were invited to evaluate a recommended website through an online survey. Results: Three hundred eighty-nine patients and 95 professionals completed the survey. The internet (n = 109; 27.4%) was the second preferred source of information after the health care team (n = 229; 57.5%). Eighty percent of patients searched the internet for information on their disease and 28.6% did so at least once a week (n = 114), especially newly diagnosed ones (<2 years). Patients valued a website recommended by their professional (n = 379; 95.2%) and endorsed by the National Working Group (n = 377; 94.7%). They would attend online educational initiatives on the website (n = 279; 70.1%) and complete periodical surveys to improve its usefulness (n = 338; 84.9%). According to IBD professionals, this type of website is the best patient source of supplementary information (n = 76; 80%) and they "prescribe" it to most patients (67.0 ± 25.2%), especially the newly diagnosed patients (52.7 ± 26.5%). It effectively integrates routine face-to-face education (n = 95; 100%). Conclusions: Patients of IBD units, especially newly diagnosed ones, appreciate a trusted e-Health resource to back up professional information. The favorable opinion of patients and professionals will allow its use in training interventions.

MyGuide: Perceptions and Acceptance of an Online Concussion Self-Management Tool

<h3>Research Objectives</h3> To investigate the perceptions and acceptance of clinicians and people with concussion using an online concussion self-management tool. <h3>Design</h3> Using a mixed-methods content analysis approach, we interviewed and analyzed responses from clients and clinicians who used the online self-management tool within the past 2 years. We also asked participants about their acceptability of the tool using the Health Information Technology Usability Evaluation Scale (Health-ITUES). <h3>Setting</h3> Participants were living in the community setting. All participants (clinicians and people with history of concussion) completed an online survey. Representative clinicians and people with concussion participated in a semi-structured interview via Zoom. <h3>Participants</h3> A total of 16 participants were included in this study, comprising of 8 people with concussion and 8 healthcare providers. <h3>Interventions</h3> N/A. <h3>Main Outcome Measures</h3> Qualitative data (semi-structured interviews) and quantitative questionnaire (Health Information Technology Usability Evaluation Scale (Health-ITUES)) was used to understand acceptance and perception of the MyGuide Tool for concussion management. <h3>Results</h3> Participants reported two key benefits of using the online self-management tool, namely, the tool's emphasis on the interconnectedness of physical and psychological symptoms, and the ability to provide reassurance that symptoms being experienced were a normal part of the concussion experience. Clinicians described the tool as being useful as a supplementary source of information for clients in addition to clinical sessions, and believed the content was useful for increasing clients' independence in managing their own recovery. People with concussion indicated that the using the tool early in their recovery was important as knowledge and information was most needed at that point. Some people with concussion described that the tool had reduced benefit as it was used too late in their concussion management. Rather than using the site regularly as a management tool, several people with concussion reported that they worked through the material once and didn't refer to it afterwards. <h3>Conclusions</h3> Findings will provide insight into the acceptability and potential benefit of an online self-management tool in concussion rehabilitation and may provide important design considerations in this population. <h3>Author(s) Disclosures</h3> N/A.

Saying the Unseen: Video Descriptions via Dialog Agents.

Current vision and language tasks usually take complete visual data (e.g., raw images or videos) as input, however, practical scenarios may often consist the situations where part of the visual information becomes inaccessible due to various reasons e.g., restricted view with fixed camera or intentional vision block for security concerns. As a step towards the more practical application scenarios, we introduce a novel task that aims to describe a video using the natural language dialog between two agents as a supplementary information source given incomplete visual data. Different from most existing vision-language tasks where AI systems have full access to images or video clips, which may reveal sensitive information such as recognizable human faces or voices, we intentionally limit the visual input for AI systems and seek a more secure and transparent information medium, i.e., the natural language dialog, to supplement the missing visual information. Specifically, one of the intelligent agents - Q-BOT - is given two semantic segmented frames from the beginning and the end of the video, as well as a finite number of opportunities to ask relevant natural language questions before describing the unseen video. A-BOT, the other agent who has access to the entire video, assists Q-BOT to accomplish the goal by answering the asked questions. We introduce two different experimental settings with either a generative (i.e., agents generate questions and answers freely) or a discriminative (i.e., agents select the questions and answers from candidates) internal dialog generation process. With the proposed unified QA-Cooperative networks, we experimentally demonstrate the knowledge transfer process between the two dialog agents and the effectiveness of using the natural language dialog as a supplement for incomplete implicit visions.

Monitoring public engagement with nature using Google Trends

Abstract How humans interact with nature affects the health of both people and ecosystems. Yet, long‐term data on nature engagement are scarce because traditional survey methods are expensive, time consuming and require commitment over multiple years. Digital data sources (e.g. aggregated data from online searches) have major potential as a supplementary source of information and, in the absence of available data, as a proxy for more direct measurement of nature engagement. Using Google Trends, we created a list of refined and relevant search terms relating to diverse outdoor spaces and activities. We then compared trends in Google search volumes in England across both a 1‐year and 10‐year period to those from Google Community Mobility Reports, and from nationally representative survey data (Natural England's People and Nature Survey and the Monitor of Engagement with the Natural Environment). Search, survey and mobility data all support a general increase in public engagement with nature since 2009, and a more substantial increase during, or following, the initial national ‘lockdown’ period of the COVID‐19 pandemic in England. Search volumes increased for many urban and rural outdoor green spaces (e.g. woodlands), blue spaces (e.g. reservoirs), exercise activities (e.g. walking, running and hiking) and explicitly nature‐based activities (e.g. fishing, wild swimming and encouraging wildlife). Overall, volumes of Google searches were more closely related with longer‐term (10‐year) trends from survey data, than shorter‐term changes during the COVID‐19 pandemic. There were statistically significant relationships between search volumes, survey data (self‐reported past behaviour) and mobility data (movement trends) for around half of comparisons. Of these, an average of 13–44% of variation in the data was explained. The findings show that Google Trends provides valuable information about public engagement with nature, which can help to supplement existing survey data by providing new insights about behavioural trends. The paper also provides a proof of concept for using Google Trends to understand changes in public engagement with nature, which could be applied to the many countries that lack long‐term survey monitoring. Read the free Plain Language Summary for this article on the Journal blog.

YouTube™ as an information source for regenerative endodontic treatment procedures: Quality and content analysis

BackgroundRegenerative endodontic procedures (REPs) are one of the most important developments in dental practice, and in the era of Covid 19 pandemic, audio-visual contents of YouTube™ could be an information source for dental students, practitioners and patients. The aim of this study was to evaluate the quality, content and the demographics of YouTube™ videos about REPs. MethodsA search on YouTube™ was performed for REPs using “endodontic regeneration”, “pulp regeneration”, “regenerative endodontics”, “regenerative endodontic procedures”, “revascularization” and “revitalization” keywords. Totally 531 videos were found and 60 videos met the inclusion criteria. Following the assessment of the demographic features of the videos and the viewing rate of the videos were calculated. The content of the videos was evaluated based on the selected headings. The quality of the videos was assessed using the video information, quality index (VIQI), Global Quality Score (GQS) and DISCERN. The statistical analysis was performed using Spearman Correlation and linear regression analysis. ResultsMajority of the videos about REPs were created by dental professionals (91.7%). The most commonly covered topic was “clinical application” (76.7%). Total content score showed a positive correlation with total VIQI (r = 0.795; p < 0.001) and GQS (r = 0.952; p < 0.001). There were significant relationships between total content score, duration, GQS, total VIQI score and DISCERN. ConclusionThe findings revealed that YouTube™ videos about REPs provide predominantly clinical information about patient chairside practice of REPs and they could be considered as a supplementary information source for dental students and practitioners.

Energy Efficient, Highly Precise Cascade Dryness Control for Fibrous Tape by Induction-Based Surface Heating of a Rotating Steel Cylinder with Moving Inductors

Drying various materials constitutes an essential component of several industrial processes, e.g., paper production. Typically, rotating cylinders heated internally by water steam are used for drying tape-shaped material in paper-making machines. Such an approach remains very energy-consuming, while the whole process is expensive and in conflict with the global policy of reducing energy consumption in heavy industry. One promising alternative method of drying fibrous tapes is the induction heating of drying cylinders. In this paper, we propose a drying system based on a set of inductors (electromagnetic field sources) that generate energy in the mantle of the cylinder and dry the running tape. By enabling the movement of the inductors, the system provides a high level of flexibility in terms of reacting to the varying humidity of the tape. Additionally, imaging the temperature field on the cylinder surface provides a supplementary source of information, enabling the temperature profile to be controlled. Two types of humidity control systems, a one-loop feedback control and a cascade control, were designed and analyzed. Simulation analysis and experimental verification performed using a semi-industrial setup proves that using the proposed cascade control ensures more than 30% faster response of the whole dryness control system.

Analyzing Citizens' and Health Care Professionals' Searches for Smell/Taste Disorders and Coronavirus in Finland During the COVID-19 Pandemic: Infodemiological Approach Using Database Logs.

BackgroundThe COVID-19 pandemic has prevailed over a year, and log and register data on coronavirus have been utilized to establish models for detecting the pandemic. However, many sources contain unreliable health information on COVID-19 and its symptoms, and platforms cannot characterize the users performing searches. Prior studies have assessed symptom searches from general search engines (Google/Google Trends). Little is known about how modeling log data on smell/taste disorders and coronavirus from the dedicated internet databases used by citizens and health care professionals (HCPs) could enhance disease surveillance. Our material and method provide a novel approach to analyze web-based information seeking to detect infectious disease outbreaks.ObjectiveThe aim of this study was (1) to assess whether citizens’ and professionals’ searches for smell/taste disorders and coronavirus relate to epidemiological data on COVID-19 cases, and (2) to test our negative binomial regression modeling (ie, whether the inclusion of the case count could improve the model).MethodsWe collected weekly log data on searches related to COVID-19 (smell/taste disorders, coronavirus) between December 30, 2019, and November 30, 2020 (49 weeks). Two major medical internet databases in Finland were used: Health Library (HL), a free portal aimed at citizens, and Physician’s Database (PD), a database widely used among HCPs. Log data from databases were combined with register data on the numbers of COVID-19 cases reported in the Finnish National Infectious Diseases Register. We used negative binomial regression modeling to assess whether the case numbers could explain some of the dynamics of searches when plotting database logs.ResultsWe found that coronavirus searches drastically increased in HL (0 to 744,113) and PD (4 to 5375) prior to the first wave of COVID-19 cases between December 2019 and March 2020. Searches for smell disorders in HL doubled from the end of December 2019 to the end of March 2020 (2148 to 4195), and searches for taste disorders in HL increased from mid-May to the end of November (0 to 1980). Case numbers were significantly associated with smell disorders (P<.001) and taste disorders (P<.001) in HL, and with coronavirus searches (P<.001) in PD. We could not identify any other associations between case numbers and searches in either database.ConclusionsNovel infodemiological approaches could be used in analyzing database logs. Modeling log data from web-based sources was seen to improve the model only occasionally. However, search behaviors among citizens and professionals could be used as a supplementary source of information for infectious disease surveillance. Further research is needed to apply statistical models to log data of the dedicated medical databases.

The Use of Digital Media among China students in Belarusian State University during Covid-19 Pandemic

The purpose of this study is to understand the views of Chinese students studying in Belarus during the covid-19 pandemic and to reveal the extent to which they use online media. Through in-depth interviews, this study interviewed 10 Chinese students with different majors, genders, rental conditions and residence years in Belarus, hoping to objectively reflect the situation of Chinese students as much as possible. The interview results showed that during the epidemic period, online social media was the main contact information of these students, but Chinese media were more popular. Foreign media are the source of supplementary information for Chinese students during the epidemic. The diversity of media channels and the problems of Chinese social circles in Belarus also make Belarusian students experience information overload and information anxiety. In terms of media trust, Chinese students trust domestic mainstream media more than foreign media and social platform information.

The Online Patient Satisfaction Index for Patients With Low Back Pain: Development, Reliability, and Validation Study.

BackgroundLow back pain is highly prevalent, and most often, a specific causative factor cannot be identified. Therefore, for most patients, their low back pain is labeled as nonspecific. Patient education and information are recommended for all these patients. The internet is an accessible source of medical information on low back pain. Approximately 50% of patients with low back pain search the internet for health and medical advice. Patient satisfaction with education and information is important in relation to patients’ levels of inclination to use web-based information and their trust in the information they find. Although patients who are satisfied with the information they retrieve use the internet as a supplementary source of information, dissatisfied patients tend to avoid using the internet. Consumers’ loyalty to a product is often applied to evaluate their satisfaction. Consumers have been shown to be good ambassadors for a service when they are willing to recommend the service to a friend or colleague. When consumers are willing to recommend a service to a friend or colleague, they are also likely to be future users of the service. To the best of our knowledge, no multi-item instrument exists to specifically evaluate satisfaction with information delivered on the web for people with low back pain.ObjectiveThis study aims to report on the development, reliability testing, and construct validity testing of the Online Patient Satisfaction Index to measure patients’ satisfaction with web-based information for low back pain.MethodsThis is a cross-sectional validation study of the Online Patient Satisfaction Index. The index was developed with experts and assessed for face validity. It was subsequently administered to 150 adults with nonspecific low back pain. Of these, 46% (70/150) were randomly assigned to participate in a reliability test using an intraclass correlation coefficient of agreement. Construct validity was evaluated by hypothesis testing based on a web app (MyBack) and Wikipedia on low back pain.ResultsThe index includes 8 items. The median score (range 0-24) based on the MyBack website was 20 (IQR 18-22), and the median score for Wikipedia was 12 (IQR 8-15). The entire score range was used. Overall, 53 participants completed a retest, of which 39 (74%) were stable in their satisfaction with the home page and were included in the analysis for reliability. Intraclass correlation coefficient of agreement was estimated to be 0.82 (95% CI 0.68-0.90). Two hypothesized correlations for construct validity were confirmed through an analysis using complete data.ConclusionsThe index had good face validity, excellent reliability, and good construct validity and can be used to measure satisfaction with the provision of web-based information regarding nonspecific low back pain among people willing to access the internet to obtain health information.Trial RegistrationClinicalTrials.gov NCT03449004; https://clinicaltrials.gov/ct2/show/NCT03449004