Low Readability Research Articles

Artificial Intelligence-Generated Writing in the ERAS Personal Statement: An Emerging Quandary for Post-graduate Medical Education.

This study was designed to investigate if artificial intelligence (AI) detection software can determine the use of AI in personal statements for residency applications. Previously written personal statements were collected from physicians who had already matched to residency through the Electronic Residency Application System. Physicians were recruited for the study through collegial relationships and were given study information via email. The study team constructed five parallel statements from the shared personal statements to prompt AI to create a personal statement of similar content. An online AI detection tool, GPTZero, was used to assess all the personal statements. Statistical analyses were conducted using R. Descriptive statistics, t-tests, and Pearson correlations were used to assess the data. Eight physicians' statements were compared to eight AI-generated statements. GPTZero was able to correctly identify AI-generated writing, assigning them significantly higher AI probability scores compared to human-authored essays. Human-generated statements were considered more readable, used shorter words with fewer syllables, and had more sentences compared to AI-generated essays. Longer average sentence length, low readability scores, and high SAT word percentages were strongly associated with AI-generated essays. This study shows the capacity of GPTZero to distinguish human-created versus AI-generated writing. Use of AI can pose significant ethical challenges and carries a risk of inadvertent harm to certain applicants and erosion of trust in the application process. Authors suggest standardization of protocol regarding the use of AI prior to its integration in post-graduate medical education.

Accuracy of natural language processors for patients seeking inguinal hernia information.

NLPs such as ChatGPT are novel sources of online healthcare information that are readily accessible and integrated into internet search tools. The accuracy of NLP-generated responses to health information questions is unknown. We queried four NLPs (ChatGPT 3.5 and 4, Bard, and Claude 2.0) for responses to simulated patient questions about inguinal hernias and their management. Responses were graded on a Likert scale (1 poor to 5 excellent) for relevance, completeness, and accuracy. Responses were compiled and scored collectively for readability using the Flesch-Kincaid score and for educational quality using the DISCERN instrument, a validated tool for evaluating patient information materials. Responses were also compared to two gold-standard educational materials provided by SAGES and the ACS. Evaluations were performed by six hernia surgeons. The average NLP response scores for relevance, completeness, and accuracy were 4.76 (95% CI 4.70-4.80), 4.11 (95% CI 4.02-4.20), and 4.14 (95% CI 4.03-4.24), respectively. ChatGPT4 received higher accuracy scores (mean 4.43 [95% CI 4.37-4.50]) than Bard (mean 4.06 [95% CI 3.88-4.26]) and Claude 2.0 (mean 3.85 [95% CI 3.63-4.08]). The ACS document received the best scores for reading ease (55.2) and grade level (9.2); however, none of the documents achieved the readibility thresholds recommended by the American Medical Association. The ACS document also received the highest DISCERN score of 63.5 (57.0-70.1), and this was significantly higher compared to ChatGPT 4 (50.8 [95% CI 46.2-55.4]) and Claude 2.0 (48 [95% CI 41.6-54.4]). The evaluated NLPs provided relevant responses of reasonable accuracy to questions about inguinal hernia. Compiled NLP responses received relatively low readability and DISCERN scores, although results may improve as NLPs evolve or with adjustments in question wording. As surgical patients expand their use of NLPs for healthcare information, surgeons should be aware of the benefits and limitations of NLPs as patient education tools.

Assessing the readability and quality of online written information on epistaxis.

The objective of this study was to assess the readability and quality of online written information on epistaxis. The terms 'epistaxis' and 'nosebleed' were entered into Google. The first six webpages generated for each search term were screened. Readability was assessed using the Flesch-Kincaid Reading Ease Score (FRES), Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG) Index and Gunning Fog Index (GFOG). Quality was assessed using the DISCERN instrument. Spearman's correlation between quality and readability was calculated. A total of 37 websites met the inclusion criteria. The mean and 95% confidence intervals for FRES, FKGL, SMOG and GFOG were 58.9 (55.3-62.5), 9.65 (8.74-10.6), 9.18 (8.57-9.8) and 12.5 (11.5-13.5), respectively. The DISCERN score was 34.3 (32.0-36.5). Weak negative correlation was noted between DISCERN and FRES (rs = -0.15, p = 0.36). Online information on epistaxis is generally of poor quality and low readability.

How loud is consumer voice in product deletion decisions? Retail analytic insights

This study examines the role of online consumer reviews in product deletion decisions. Building upon product portfolio management theory and the signaling theory, we integrate consumer voice, represented by online consumer review behavior into organizational voice—strategic product deletion decision-making. We empirically evaluated the relationship between online consumer reviews and organizational product deletion decisions using text mining and logistic regression models. The results indicate consumer online review characteristics are significant factors for product deletion decisions. Findings suggest that products with lower review attribute ratings, or those with textual review content less pertinent to the core performance attributes, are more likely to be deleted. The linguistic retail analytic characteristics of online reviews also provide insights for product deletion decisions. Products with reviews having higher subjectivity, shorter length, and lower readability are more likely to be deleted. Pre-purchase consumer voice—the perceived helpfulness or unhelpfulness of online reviews also impacts product deletion decisions. A general conclusion is that online reviews can provide important retail analytics for smarter retail operations planning at the strategic and tactical levels when it comes to product planning and portfolio management through product deletion.

Do investor reactions to merger announcements shape the writing of SEC filings?

The way filings of mergers and acquisitions (M&A) with the Security Exchange Commission (SEC) are written might depend on investor reactions to initial public announcements of the deal. We examine this investor feedback hypothesis by focusing on the readability and timing of a large sample of SEC documents. We show that acquirers write documents with lower readability and file them faster when investors react negatively to the deal announcement, a finding consistent with strategic obfuscation efforts. The results are robust to alternative empirical choices, such as controlling for deal complexity or the firm's writing style. They are also confirmed using an instrumental variables approach.

In the Belly of Text Complexity: Unravelling the Nexus between Lexical Density and Readability

This study set out to explore the link between lexical density (LD) as a tool for determining text complexity and the general readability of texts (in this study, texts assigned to Senior High School learners in Ghana). To clearly establish this link, the levels of LD of assigned texts have to be first determined, and then, compared with their corresponding readability values. To that end, Ure’s (1971) LD formula and Halliday’s (1985b) LD formula have been used to determine the LD values of the sampled texts. Gunning’s (1952) and Flesch’s (1948) readability indices have been used to determine the readability values of same assigned texts. LD values for the sampled texts were found to be generally very high (above the widely agreed minimum of 40%); as their corresponding readability values were low. The correlation between LD and readability is therefore adequately revealed: high LD translates directly into low readability while low LD translates directly into high readability. Implicatively, low readability of texts definitely affects learner progress negatively. Keywords: lexical density, readability, Senior High School learners in Ghana, Ure’s (1971) LD formula, Halliday’s (1985) LD formula, Gunning’s (1952) readability index, Flesch’s (1948) readability index

Readability and Information Quality in Cancer Information From a Free vs Paid Chatbot

The mainstream use of chatbots requires a thorough investigation of their readability and quality of information. To identify readability and quality differences in information between a free and paywalled chatbot cancer-related responses, and to explore if more precise prompting can mitigate any observed differences. This cross-sectional study compared readability and information quality of a chatbot's free vs paywalled responses with Google Trends' top 5 search queries associated with breast, lung, prostate, colorectal, and skin cancers from January 1, 2021, to January 1, 2023. Data were extracted from the search tracker, and responses were produced by free and paywalled ChatGPT. Data were analyzed from December 20, 2023, to January 15, 2024. Free vs paywalled chatbot outputs with and without prompt: "Explain the following at a sixth grade reading level: [nonprompted input]." The primary outcome measured the readability of a chatbot's responses using Flesch Reading Ease scores (0 [graduate reading level] to 100 [easy fifth grade reading level]). Secondary outcomes included assessing consumer health information quality with the validated DISCERN instrument (overall score from 1 [low quality] to 5 [high quality]) for each response. Scores were compared between the 2 chatbot models with and without prompting. This study evaluated 100 chatbot responses. Nonprompted free chatbot responses had lower readability (median [IQR] Flesh Reading ease scores, 52.60 [44.54-61.46]) than nonprompted paywalled chatbot responses (62.48 [54.83-68.40]) (P < .05). However, prompting the free chatbot to reword responses at a sixth grade reading level was associated with increased reading ease scores than the paywalled chatbot nonprompted responses (median [IQR], 71.55 [68.20-78.99]) (P < .001). Prompting was associated with increases in reading ease in both free (median [IQR], 71.55 [68.20-78.99]; P < .001)and paywalled versions (median [IQR], 75.64 [70.53-81.12]; P < .001). There was no significant difference in overall DISCERN scores between the chatbot models, with and without prompting. In this cross-sectional study, paying for the chatbot was found to provide easier-to-read responses, but prompting the free version of the chatbot was associated with increased response readability without changing information quality. Educating the public on how to prompt chatbots may help promote equitable access to health information.

Assessing parental comprehension of online resources on childhood pain.

We aimed to examine the patient education materials (PEMs) on the internet about "Child Pain" in terms of readability, reliability, quality and content. For our observational study, a search was made on February 28, 2024, using the keywords "Child Pain," "Pediatric Pain," and "Children Pain" in the Google search engine. The readability of PEMs was assessed using computer-based readability formulas (Flesch Reading Ease Score [FRES], Flesch-Kincaid Grade Level [FKGL], Automated readability index (ARI), Gunning Fog [GFOG], Coleman-Liau score [CL], Linsear Write [LW], Simple Measure of Gobbledygook [SMOG]). The reliability and quality of websites were determined using the Journal of American Medical Association (JAMA) score, Global Quality Score (GQS), and DISCERN score. 96 PEM websites included in our study. We determined that the FRES was 64 (32-84), the FKGL was 8.24 (4.01-15.19), ARI was 8.95 (4.67-17.38), GFOG was 11 (7.1-19.2), CL was 10.1 (6.95-15.64), LW was 8.08 (3.94-19.0) and SMOG was 8.1 (4.98-13.93). The scores of readability formulas showed that, the readability level of PEMs was statistically higher than sixth-grade level with all formulas (P = .011 for FRES, P < .001 for GFOG, P < .001 for ARI, P < .001 for FKGL, P < .001 for CL and P < .001 for SMOG), except LW formula (P = .112). The websites had moderate-to-low reliability and quality. Health-related websites had the highest quality with JAMA score. We found a weak negative correlation between Blexb score and JAMA score (P = .013). Compared to the sixth-grade level recommended by the American Medical Association and the National Institutes of Health, the readability grade level of child pain-related internet-based PEMs is quite high. On the other hand, the reliability and quality of PEMs were determined as moderate-to-low. The low readability and quality of PEMs could cause an anxious parent and unnecessary hospital admissions. PEMs on issues threatening public health should be prepared with attention to the recommendations on readability.

Quality and Readability of Online Educational Mohs Micrographic Surgery Resources.

As internet access continues to expand, online health care information is increasingly influencing patient decisions. Mohs micrographic surgery (MMS) is commonly used in the field of dermatology but may be unfamiliar to many patients. The purpose of this study was to identify and analyze online educational resources regarding MMS and learn how to optimize the understanding and informational content of MMS for patients and their families. Thirty-two websites were evaluated for authorship, quality, and readability using DISCERN, JAMA Benchmark Criteria, and Flesch-Kincaid tests. Physician-authored content showed a trend toward higher quality ( p = .058). Google scored higher in specific DISCERN questions when overlapping websites were excluded. Bing scored higher in JAMA criteria ( p = .03) in criteria such as authorship and currency. Higher DISCERN scores correlated with lower readability. Physician involvement improves content quality, raising questions about physicians' responsibility in online resource creation. Correlations between content quality and readability highlight potential challenges for certain demographics. Balancing medical accuracy with comprehensibility is crucial for equitable patient education. This study underscores the need to refine online resources, ensuring accurate, transparent, and accessible health care information.

Readability and Comprehension of Anesthesia Informed Consent Forms in a Spanish County Hospital: An Observational Study.

(1) Background: The wording of informed consent forms could hinder their comprehension and hinder patients' autonomous choice. The objective of this study was to analyze the readability and comprehension of anesthesia informed consent forms in a Spanish county hospital. (2) Methods: Descriptive and cross-sectional study carried out on patients who were going to undergo anesthetic techniques. The readability of the forms was analyzed using the INFLESZ tool and their subjective comprehension using an ad hoc questionnaire. (3) Results: The analyzed forms presented a "somewhat difficult" legibility. A total of 44.2% of the patients decided not to read the form, mainly because they had previously undergone surgery with the same anesthetic technique. The language used in the forms was considered inadequate by 49.5% of the patients and 53.3% did not comprehend it in its entirety. A statistically significant negative correlation of age and INFLESZ readability score with the overall questionnaire score was found. A statistically significant association was observed as a function of age and educational level with the different criteria of the questionnaire. (4) Conclusions: The anesthesia informed consent forms presented low readability with limited comprehension. It would be necessary to improve their wording to favor comprehension and to guarantee patients' freedom of choice.

Criteria2Query 3.0: Leveraging generative large language models for clinical trial eligibility query generation

ObjectiveAutomated identification of eligible patients is a bottleneck of clinical research. We propose Criteria2Query (C2Q) 3.0, a system that leverages GPT-4 for the semi-automatic transformation of clinical trial eligibility criteria text into executable clinical database queries. Materials and MethodsC2Q 3.0 integrated three GPT-4 prompts for concept extraction, SQL query generation, and reasoning. Each prompt was designed and evaluated separately. The concept extraction prompt was benchmarked against manual annotations from 20 clinical trials by two evaluators, who later also measured SQL generation accuracy and identified errors in GPT-generated SQL queries from 5 clinical trials. The reasoning prompt was assessed by three evaluators on four metrics: readability, correctness, coherence, and usefulness, using corrected SQL queries and an open-ended feedback questionnaire. ResultsOut of 518 concepts from 20 clinical trials, GPT-4 achieved an F1-score of 0.891 in concept extraction. For SQL generation, 29 errors spanning seven categories were detected, with logic errors being the most common (n = 10; 34.48 %). Reasoning evaluations yielded a high coherence rating, with the mean score being 4.70 but relatively lower readability, with a mean of 3.95. Mean scores of correctness and usefulness were identified as 3.97 and 4.37, respectively. ConclusionGPT-4 significantly improves the accuracy of extracting clinical trial eligibility criteria concepts in C2Q 3.0. Continued research is warranted to ensure the reliability of large language models.

Dialogue for Prompting: A Policy-Gradient-Based Discrete Prompt Generation for Few-Shot Learning

Prompt-based pre-trained language models (PLMs) paradigm has succeeded substantially in few-shot natural language processing (NLP) tasks. However, prior discrete prompt optimization methods require expert knowledge to design the base prompt set and identify high-quality prompts, which is costly, inefficient, and subjective. Meanwhile, existing continuous prompt optimization methods improve the performance by learning the ideal prompts through the gradient information of PLMs, whose high computational cost, and low readability and generalizability are often concerning. To address the research gap, we propose a Dialogue-comprised Policy-gradient-based Discrete Prompt Optimization (DP_2O) method. We first design a multi-round dialogue alignment strategy for readability prompt set generation based on GPT-4. Furthermore, we propose an efficient prompt screening metric to identify high-quality prompts with linear complexity. Finally, we construct a reinforcement learning (RL) framework based on policy gradients to match the prompts to inputs optimally. By training a policy network with only 0.62M parameters on the tasks in the few-shot setting, DP_2O outperforms the state-of-the-art (SOTA) method by 1.52% in accuracy on average on four open-source datasets. Moreover, subsequent experiments also demonstrate that DP_2O has good universality, robustness and generalization ability.

Nominalization in Arabic translations of patient information leaflets

Patient information leaflets (PILs) inserted in medicine packages constitute a genre written by experts for an audience of laymen, but studies of PILs in Arabic report low readability. According to the lay friendliness framework developed by Jensen (2013) for translated PILs, nominalization is one of the linguistic factors that contribute to PILs’ low readability. Although nominalization has been extensively studied in scientific texts including medical papers, no studies examine its use and effect on lay friendliness in PILs translated into Arabic. This study analyzes a parallel corpus of English PILs and their Arabic translations to examine the frequency and forms of nominalization introduced into the Arabic translations. Considering Givon’s (1993) definition of nominalization, all instances of finite verb phrases in the Source Texts (ST) that are fully or partially nominalized in the Target Texts (TT) were examined. Examples are discussed in terms of the level and function of nominalization in the target language.

Readability of Patient Electronic Materials for Atopic Dermatitis in 23 Languages: Analysis and Implications for Dermatologists.

Patients search on the Internet for information about various medical procedures and conditions. The main aim of this study was to evaluate the readability of online health information related to atopic dermatitis (AD). Online resources are becoming a standard in facilitating shared decision-making processes. With a pipeline of new therapeutic options like immunomodulators, understanding of the complexity of AD by the patients is crucial. The term "atopic dermatitis" translated into 23 official European Union languages was searched using the Google search engine. The first 50 records in each language were evaluated for suitability. Included materials were barrier-free, focused on patient education, and were not categorized as advertisements. Article sources were classified into four categories: non-profit, online shops, pharmaceutical companies, and dermatology clinic. Readability was assessed with Lix score. A total of 615 articles in Swedish, Spanish, Slovenian, Slovak, Romanian, Portuguese, Polish, Lithuanian, Latvian, Irish, Italian, Hungarian, Greek, German, French, Finnish, Estonian, English, Dutch, Danish, Czech, Croatian, and Bulgarian were evaluated. The overall mean Lix score was 56 ± 8, which classified articles as very hard to comprehend. Significant differences in mean Lix scores were observed across all included languages (all P < 0.001). Articles released by non-profit organizations and pharmaceutical companies had the highest readability (P < 0.001). Low readability level was correlated with high article prevalence (R2 = 0.189, P = 0.031). Although there was an abundance of online articles related to AD, the readability of the available information was low. As online health information has become essential in making shared decisions between patients and physicians, an improvement in AD-related materials is needed.

Climate‐related performance and stock price crash risk

AbstractWe examine how environmental performance affects future stock price crash risk. Previous literature shows that legitimacy threats, stemming from environmental risk, lead firms to be particularly sensitive about environmental disclosure and performance. However, we hypothesise and find that under specific conditions, relating to lower operating performance, firms that have higher environmental performance also have higher future stock price crash risk. Further analysis shows that such firms may also have lower readability and more confident tone in their 10‐K annual reports. We attribute these findings to impression management utilising environmental performance along with disclosure misdirection practices, where managers of firms with negative news, attempt in some cases to draw the attention of the users of financial reports by obfuscating annual reports for bad news hoarding purposes. Even though in the current year such practices may have a negative effect for stock price crash risk, future stock price crash risk increases due to the dissemination of the negative news in the market. Overall, our results show that environmental disclosure may be used, under certain conditions, as a tool for impression management, which along with financial reporting distraction practices, leads to higher future stock price crash risk.

Assessing the readability and quality of online information on benign paroxysmal positional vertigo.

Benign paroxysmal positional vertigo (BPPV) is the most common cause of peripheral vertigo. It can have a significant impact on quality of life, with individuals often seeking information online for reassurance and education. The aim of this study is to assess the readability and quality of online information on BPPV. The terms 'benign paroxysmal positional vertigo' and 'BPPV' were entered into Google. The first 50 websites generated for each search term were screened. Readability was assessed using the Flesch-Kincaid Reading Ease Score (FRES), Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG) Index and Gunning Fog Index (GFOG). Quality was assessed using the DISCERN instrument. Spearman's correlation between quality and readability was calculated. A total of 39 websites met the inclusion criteria. The mean and 95% confidence intervals for the FRES, FKGL, SMOG, GFOG and DISCERN scores were 50.2 (46.1-54.3), 10.6 (9.87-11.4), 10.1 (9.5-10.7), 13.6 (12.7-14.4) and 36.7 (34.6-38.7), respectively. Weak correlation was noted between DISCERN and FRES (rs = -0.23, p = 0.17). Online information on BPPV is generally of poor quality and low readability. It is essential that healthcare professionals inform their patients of this limitation and advocate for improved online patient education resources that are both high quality and easy to comprehend.

Readability of Sustainability Reports: A Bibliometric Analysis and Systematic Literature Review

This paper aims to investigate the latest scientific developments, map research networks and topics, and present a critical analysis of the gaps and future opportunities in the literature on the readability of sustainability reports. Through data collection and filtering processes, the final sample included 10 articles. Then, a bibliometric analysis was developed using Scopus metrics and AJG classification. VOSviewer software (Version 1.6.18) was used to develop bibliometric networks. Finally, we developed a systematic review analysis to answer our third objective. The results show that most studies on the readability of non-financial reports come from Europe and Oceania; the sample’s co-citations per author were classified into three clusters; most of the sample was linked to analyzing the quality and effectiveness of sustainability reports; and organizations tend to use low readability in sustainability reports. This study contributes to further scientific knowledge about the readability of sustainability reports and impression management techniques and to the research into the importance of sustainability reporting for managing stakeholder impressions. A wide range of implications for the academic community, regulatory bodies, organizations, and all users of the information disclosed through sustainability reports were identified. The main limitations may have been created by the sample’s size, exclusion criteria, and keywords selected.

Otosclerosis online: a critical analysis of quality, reliability, readability and content of otosclerosis information.

Several therapeutic options are usually discussed for otosclerosis management. Patients seek medical advice from an ENT specialist but are also increasingly using the internet for medical issues. This study intends to assess readability and quality of websites with information on otosclerosis. This is a cross-sectional study performed in a tertiary care centre. The results of the first two pages of a Google search with the keyword "otosclerosis" were reviewed by two independent investigators. Readability was assessed with the Flesch-Kincaid Grade Level (FKGL), Flesch Reading Ease Score (FRES) and Gunning Fog Index. For quality and reliability assessment, the 16-item DISCERN instrument was used. Spearman's coefficient was used for correlations, and multivariate analyses of variance were used to assess differences. Inter-rater agreement was evaluated with concordance correlation coefficient. 18 websites were included. Two websites (11.0%) were authored by academic institutions, 5/18 (28%) by government agencies, 6/18 (33%) by professional organisations and 5/18 (28%) were medical information websites. The mean DISCERN score of the 18 websites was 40.8 ± 6.7/80 (range 28.7-51.7), corresponding to "fair" quality. The mean FRES score was 43.27 ± 10.6, and the mean FKGL was 11.43 ± 2.30, corresponding to "difficult to read". The mean Gunning Fog index was 12.90 ± 2.19 (range 9.81-18.20), corresponding to a "college freshman" level. This study shows that internet information on otosclerosis has an overall low readability, while the quality is heterogeneous and varies from "poor" to "good". Efforts should be made to improve the readability of otosclerosis websites.

The Impact of Google Translate Syntactic Strategies on Translation Quality: Translating Journal Articles from Indonesian to English

The prevalent use of Google Translate as a tool for academic translations, despite concerns regarding its quality, frames the core issue of this research. This research aims to classify syntactic strategies used by Google Translate in translating from Indonesia to English. It also aims to analyze the quality of the translation produced and how the syntactic strategies affected the translation quality. The data were collected from a journal article entitled “Pengaruh Bahasa Indonesia dan Bahasa Inggris sebagai Bahasa Pengantar dalam Pendidikan Formal” which was presented using a descriptive qualitative method. The findings of this research reveal there are several types of different syntactic strategies used by Google Translate. The result of this research shows that, out of 273 data collected, there are 123 (45.05%) data of literal translation, 2 (0.73%) data of loan and calque, 53 (19.41%) of transposition, 17 (6.23%) data of unit shift, 45 (16.48%) data of phrase structure change, 1 (0.37%) data of clause structure change, 18 (6.59%) data of sentence structure change, 1 (0.37%) data of cohesion change, 13 (4.76%) data of level shift, and no data found for scheme change. In addition, there are several different classifications found for translation quality. Out of 194 data analyzed, the results show that 163 (84.02%) data are accurate, 30 (15.46%) data are less accurate, and 1 (0.52%) data is not accurate. For acceptability, there are 179 (92.27%) acceptable, 14 (7.22%) data are less accurate, and 2 (1.03%) data are not acceptable. Finally, there are 180 (92.78%) data with high readability, 15 (7.73%) data are medium readability, and no data found for low readability.

Using relevant headings in risk factor disclosures: What is the impact on information processing?

This paper empirically examines whether using relevant headings to categorize risk factors in Item 1A of Form 10-K can enhance its readability and thus facilitate investors’ understanding. Using a sample of S&P 1500 firms from 2017 to 2019, we find that post-filing abnormal returns and abnormal bid–ask spreads are lower for firms that use headings in Item 1A than for those that do not. We also find that these associations are stronger when filings have low readability, when the firm has higher financial risk, and when there is higher content concentration in risk factors under the same heading. Given that Regulation S-K was amended in 2020 to mandate categorizing risk factors under relevant headings, our findings provide policy implications by showing that such categorization helps investors to navigate risk factor disclosures and, thus, improves their process of comprehending information.