<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v2.0 20040830//EN" "journalpublishing.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="2.0" xml:lang="en" article-type="research-article"><front><journal-meta><journal-id journal-id-type="nlm-ta">J Med Internet Res</journal-id><journal-id journal-id-type="publisher-id">jmir</journal-id><journal-id journal-id-type="index">1</journal-id><journal-title>Journal of Medical Internet Research</journal-title><abbrev-journal-title>J Med Internet Res</abbrev-journal-title><issn pub-type="epub">1438-8871</issn><publisher><publisher-name>JMIR Publications</publisher-name><publisher-loc>Toronto, Canada</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">v27i1e72661</article-id><article-id pub-id-type="doi">10.2196/72661</article-id><article-categories><subj-group subj-group-type="heading"><subject>Original Paper</subject></subj-group></article-categories><title-group><article-title>Developing an Evaluation System for Quality of Health Educational Short Videos on Social Media (LassVQ) Using Nominal Group Technique and Analytic Hierarchy Process: Qualitative Study</article-title></title-group><contrib-group><contrib contrib-type="author"><name name-style="western"><surname>Hu</surname><given-names>Yang</given-names></name><degrees>MSc</degrees><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Yang</surname><given-names>Yiran</given-names></name><degrees>MSc</degrees><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Li</surname><given-names>Wei</given-names></name><degrees>PhD</degrees><xref ref-type="aff" rid="aff3">3</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Zhou</surname><given-names>Yan</given-names></name><degrees>BS</degrees><xref ref-type="aff" rid="aff4">4</xref><xref ref-type="aff" rid="aff5">5</xref></contrib><contrib contrib-type="author" corresp="yes"><name name-style="western"><surname>Sun</surname><given-names>Jing</given-names></name><degrees>PhD</degrees><xref ref-type="aff" rid="aff2">2</xref></contrib></contrib-group><aff id="aff1"><institution>Peking University Third Hospital</institution><addr-line>Beijing</addr-line><country>China</country></aff><aff id="aff2"><institution>School of Nursing, Peking University</institution><addr-line>38 Xueyuan Rd, Haidian District</addr-line><addr-line>Beijing</addr-line><country>China</country></aff><aff id="aff3"><institution>HSSE Technical Support Center, China National Oil and Gas Exploration and Development Company Ltd</institution><addr-line>Beijing</addr-line><country>China</country></aff><aff id="aff4"><institution>Clinical Laboratory, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University</institution><addr-line>Taiyuan</addr-line><country>China</country></aff><aff id="aff5"><institution>Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology</institution><addr-line>Wuhan</addr-line><country>China</country></aff><contrib-group><contrib contrib-type="editor"><name name-style="western"><surname>Sarvestan</surname><given-names>Javad</given-names></name></contrib></contrib-group><contrib-group><contrib contrib-type="reviewer"><name name-style="western"><surname>Polat</surname><given-names>Meryem Betul</given-names></name></contrib><contrib contrib-type="reviewer"><name name-style="western"><surname>Jiang</surname><given-names>Zhehan</given-names></name></contrib></contrib-group><author-notes><corresp>Correspondence to Jing Sun, PhD, School of Nursing, Peking University, 38 Xueyuan Rd, Haidian District, Beijing, China, 86 13520238688; <email>sunjing99@bjmu.edu.cn</email></corresp></author-notes><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>18</day><month>9</month><year>2025</year></pub-date><volume>27</volume><elocation-id>e72661</elocation-id><history><date date-type="received"><day>14</day><month>02</month><year>2025</year></date><date date-type="rev-recd"><day>18</day><month>07</month><year>2025</year></date><date date-type="accepted"><day>21</day><month>07</month><year>2025</year></date></history><copyright-statement>&#x00A9; Yang Hu, Yiran Yang, Wei Li, Yan Zhou, Jing Sun. Originally published in the Journal of Medical Internet Research (<ext-link ext-link-type="uri" xlink:href="https://www.jmir.org">https://www.jmir.org</ext-link>), 18.9.2025. </copyright-statement><copyright-year>2025</copyright-year><license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on <ext-link ext-link-type="uri" xlink:href="https://www.jmir.org/">https://www.jmir.org/</ext-link>, as well as this copyright and license information must be included.</p></license><self-uri xlink:type="simple" xlink:href="https://www.jmir.org/2025/1/e72661"/><abstract><sec><title>Background</title><p>With the increasing use of social media platforms for health communication, the quality of health educational short videos (HESVs) has become a key concern. However, no standardized framework exists to evaluate the quality of health videos on social media, highlighting the need for a comprehensive evaluation system.</p></sec><sec><title>Objective</title><p>This study aimed to develop a valid and structured evaluation tool for assessing the quality of HESVs on social media.</p></sec><sec sec-type="methods"><title>Methods</title><p>The initial evaluation indicators obtained from the literature review and brainstorming undertaken in the study group were provided to the nominal group reference Lasswell&#x2019;s 5W communication model, and 2 rounds of nominal group technique (NGT) were carried out to screen, add, revise, and adjust indicators, and reach a consensus of evaluation system. The indicators were then ranked based on their significance, as scored by the experts using the analytic hierarchy process. The content validity was assessed by experts who rated the relevance of each indicator on a 4-point Likert scale.</p></sec><sec sec-type="results"><title>Results</title><p>The primary indicators include communicator, communication content, communication channel, and communication effect, along with 13 secondary indicators and 34 tertiary indicators. In total, 11 experts were enrolled in the NGT, 45% (5/11) of experts had a doctoral degree, and 80% (9/11) of them were ranked as an associate professor or professor. The average values of the expert judgment coefficient and authority coefficient were 0.93 (SD 0.08) and 0.85 (SD 0.10), respectively. In round 1 of NGT, the &#x201C;communication target&#x201D; of 5 primary indicators, 7 of 20 secondary indicators, and 66 of 94 tertiary indicators did not reach a consensus, and therefore, they were not deleted and proceeded to the next round of NGT. In round 2 of NGT, 1 primary indicator, 7 secondary indicators, and 59 tertiary indicators were deleted based on the consensus criteria. Among primary indicators, communication content was found to be the most influential, accounting for 45.68%. Among secondary indicators, credibility, scientificity, availability, and social attention were the most influential indicators, with priorities of 56.67%, 24.26%, 74.62%, and 39.89% in their respective categories. Among tertiary indicators, &#x201C;become a hot search recommended by the platform&#x201D; was the most influential indicator with a weight of 0.07. The content validity of all the evaluation indicators was 0.73-1.0, and the scale-level content validity index (average) was 0.87 (SD 0.15), which was indicated as acceptable.</p></sec><sec sec-type="conclusions"><title>Conclusions</title><p>The evaluation system for the quality of HESVs on social media (LassVQ; the Lasswell&#x2019;s Video Quality scale) was developed, and its validity was acceptable. The proposed evaluation system can be used in conjunction with qualitative methods to gain a holistic perspective on the multidimensional quality of HESVs on social media.</p></sec></abstract><kwd-group><kwd>Lasswell&#x2019;s 5W communication model</kwd><kwd>LassVQ</kwd><kwd>health educational short videos</kwd><kwd>HESV</kwd><kwd>social media</kwd><kwd>video quality</kwd></kwd-group></article-meta></front><body><sec id="s1" sec-type="intro"><title>Introduction</title><p>Social media provides useful forums for health care providers and consumers to exchange health information; the boom of short video platforms also offers new potential for health-related information dissemination [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref2">2</xref>]. A total of 83% of American adults [<xref ref-type="bibr" rid="ref3">3</xref>] and 74.2% of the total Chinese population [<xref ref-type="bibr" rid="ref4">4</xref>] are active social media users. Furthermore, 87.6% of YouTube users watched health-related content, with 84.7% noted some influence on their health decisions [<xref ref-type="bibr" rid="ref5">5</xref>]. On social media channels, posts with videos had 3 times greater chance of receiving likes, almost 4 times greater chance of receiving comments, and 2.5 times greater chance of being shared [<xref ref-type="bibr" rid="ref6">6</xref>]. Social media&#x2013;based interventions have been associated with reduction in weight, BMI, and waist circumference by meta-analyses [<xref ref-type="bibr" rid="ref7">7</xref>]. Around 50% of people act on physical activity and diet videos shared on social media during the COVID-19 lockdown [<xref ref-type="bibr" rid="ref8">8</xref>].</p><p>Videos can capture visual information, facilitate self-paced learning, and engage learners, making them a valuable tool for learning procedures and complex skills that may be difficult to acquire through reading or description alone [<xref ref-type="bibr" rid="ref9">9</xref>]. Social media permits video submissions from all users; it can be subjective or inaccurate, which dilutes its overall quality [<xref ref-type="bibr" rid="ref2">2</xref>]. In total, 30% to 87% of health information on social media is false, misleading, or causing harm [<xref ref-type="bibr" rid="ref10">10</xref>]. False news spreads 3 to 20 times faster and deeper than the truth on social media [<xref ref-type="bibr" rid="ref11">11</xref>]. Repeated exposure to such news tends to increase agreement [<xref ref-type="bibr" rid="ref12">12</xref>], which is linked to potential harmful health decisions, poor medical compliance, discontinuation of medication, heightened anxiety, and so on [<xref ref-type="bibr" rid="ref13">13</xref>].</p><p>A potential solution would be to use a standardized rating system to evaluate the quality of posted videos and display the score on the page alongside the videos [<xref ref-type="bibr" rid="ref14">14</xref>]. In a review of 2113 videos, fewer than 1 in 10 of the studies used an externally validated quality scoring tool to evaluate the quality of medical educational videos, while the majority relied on tools or limited questions developed by authors [<xref ref-type="bibr" rid="ref14">14</xref>]. The currently most commonly used tools are the DISCERN instrument [<xref ref-type="bibr" rid="ref15">15</xref>], <italic>Journal of the American Medical Association</italic> (<italic>JAMA</italic>) benchmarks [<xref ref-type="bibr" rid="ref16">16</xref>], and the Health on the Net principles [<xref ref-type="bibr" rid="ref17">17</xref>]. These tools were originally developed for written health materials or websites in the 1990s, which may limit their suitability for assessing health educational short videos (HESVs) on social media [<xref ref-type="bibr" rid="ref18">18</xref>]. HESVs require high-quality images and visuals, well-written scripts, and clear sound with minimal background noise; however, these features are not currently covered by existing evaluation tools [<xref ref-type="bibr" rid="ref15">15</xref>,<xref ref-type="bibr" rid="ref17">17</xref>-<xref ref-type="bibr" rid="ref19">19</xref>].</p><p>In dynamic social media environments, both video content and engagement metrics are supposed to be in the HESVs quality assessment [<xref ref-type="bibr" rid="ref20">20</xref>]. The quality of social media HESVs encompasses several dimensions, including content accuracy, reliability, understandability, interactivity, technical quality, and others [<xref ref-type="bibr" rid="ref21">21</xref>-<xref ref-type="bibr" rid="ref23">23</xref>]. A comprehensive and targeted quality evaluation system may contribute to the effective assessment of health educational short videos on social media, which remains an area of ongoing concern. Lasswell&#x2019;s 5W communication model (the 5W model) is considered a foundational communication model and has been applied in certain new media contexts [<xref ref-type="bibr" rid="ref24">24</xref>,<xref ref-type="bibr" rid="ref25">25</xref>]. The analytic hierarchy process (AHP) is a widely used multiattribute weighting method for addressing complex decision-making problems in health care [<xref ref-type="bibr" rid="ref26">26</xref>]. This study aims to develop a comprehensive evaluation system (LassVQ: the Lasswell&#x2019;s Video Quality scale) for HESVs on social media, with preliminary evidence of validity, to facilitate more structured evaluation and understanding of video quality.</p></sec><sec id="s2" sec-type="methods"><title>Methods</title><sec id="s2-1"><title>Overview</title><p>This methodological, multiphase study comprises 5 main stages to develop the LassVQ scale for assessing the HESVs on social media. This study was reported in accordance with COSMIN (Consensus-Based Standards for the Selection of Health Status Measurement Instruments) reporting guideline [<xref ref-type="bibr" rid="ref27">27</xref>]. A completed COSMIN checklist is provided in <xref ref-type="supplementary-material" rid="app2">Checklist 1</xref>.</p></sec><sec id="s2-2"><title>Ethical Considerations</title><p>This study was approved by the Biomedical Ethics Review Board of Peking University (IRB00001052-24115) and complied with the Declaration of Helsinki principles. All participants provided informed consent. Participants were assured that their privacy and confidentiality would be strictly protected, and all data were anonymized before analysis. No personal identifying information was collected or stored. No compensation was provided to participants.</p></sec><sec id="s2-3"><title>Stage 1: Generation of the Initial Evaluation Indicators</title><p>To develop an initial item pool of evaluation indicators, a literature review was conducted by predefined search terms, including &#x201C;video,&#x201D; &#x201C;social media,&#x201D; &#x201C;social networking,&#x201D; YouTube, TikTok, Douyin, quality, reliab*, understandability, actionab*, credib*, interactiv*, comprehensive*, accuracy, completeness, and clarity. Systematic searches were carried out across 5 major databases&#x2014;PubMed (n=1864), Web of Science (n=6191), Embase (n=2817), CNKI (n=3543), and WANFANG (n=411) databases, spanning from the inception of each database to May 2024. Eligible records were limited to those published in English or Chinese and included peer-reviewed journal articles, academic reports, and conference proceedings relevant to the development or application of evaluation indicators. After removing duplicates (n=5401), 9425 records were screened based on titles and abstracts. Records deemed irrelevant or inaccessible, or that did not meet the inclusion criteria (n=9119), were excluded. The full texts of the remaining 306 articles were reviewed in detail, resulting in 72 studies meeting the final inclusion criteria. The research was conducted by 2 researchers (YH, YY) who participated in the literature search and screening. The entire research process was supervised and guided by one professor (JS). The professor was engaged in health education research for many years. The complete list of included studies is provided in Appendix S1 in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>.</p><p>The study group summarized relevant research evidence, including preliminary research of literature review, brainstorming undertaken in the study group, literature reviews of the tools to assess printed health education materials. Then, a structured brainstorming session was subsequently organized with the study group, which included both senior experts and younger technical professionals. During the meeting, participants reviewed the draft framework and items, suggested additional items, identified potential overlaps, and proposed modifications. All inputs were recorded in real time by a designated notetaker (YY) to ensure completeness and accuracy. The resulting item pool integrated evidence from the literature (as the foundation) and expert opinions (to contextualize and refine items). Based on the 5W model, the initial version of the evaluation system comprised 5 primary indicators and a total of 119 indicators.</p></sec><sec id="s2-4"><title>Stage 2: Development of Consensus on Indicators</title><sec id="s2-4-1"><title>Composition of the Nominal Group</title><p>In May 2024, a sample of experts with experience in different aspects of health education was identified for the nominal group [<xref ref-type="bibr" rid="ref28">28</xref>]. To be eligible to participate in the nominal group, participants needed to have intermediate or above professional titles, published works in relevant professional fields, and more than 8 years of experience in the current field. No conflicts of interest among participants were noted. In total, 13 people were invited, and 11 agreed to participate in the study. The 2 who declined to take part did so due to time conflicts between their clinical work and meeting schedules. The 11 participants comprised 4 health education research facilitators, 1 health education researcher, 2 HESV practitioners, 3 clinical health education practitioners, and 1 library information science expert.</p></sec><sec id="s2-4-2"><title>Generation of the Nominal Group Questionnaire</title><p>Potential outcome domains and definitions are to be measured. In total, 5 primary indicators, 20 secondary indicators, and 94 tertiary indicators were listed, informed by Lasswell&#x2019;s communication framework, evidence synthesis, and relevant assessment skills.</p><p>Potential methods of assessment are used to measure the domains and items. The necessity of each domain and item was rated using a 9-point Likert scale (1&#x2010;3=not essential, 4&#x2010;6=neutral, 7&#x2010;9=essential) [<xref ref-type="bibr" rid="ref28">28</xref>]. Necessity was defined as &#x201C;how necessary is it that this domain of measurement is included in the future assessment of the quality of HESVs on social media.&#x201D;</p><p>The basis for measurement and scoring formed the references while measuring. One is the titles and sources of key references labeled after the indicators. Furthermore, 2 important resources, the printed full text of the original literature of the assessment tools, included the tools themselves.</p></sec><sec id="s2-4-3"><title>Postal Invitation of the Nominal Group Experts</title><p>A letter of invitation that includes meeting time and place, process, and participants was mailed to the remaining experts of the meeting 2 weeks in advance of the consensus meeting. The precoded questionnaire and evidence synthesis were sent to the experts one week before the meeting.</p></sec><sec id="s2-4-4"><title>Nominal Group Consensus Meeting</title><p>The 1-day NGT meeting was set up in a conference room on May 17, 2024, with a &#x201C;U&#x201D;-shaped table and a wide-screen monitor, including 4 sections. First, an introductory lecture was given to describe the meeting&#x2019;s goals, the formation of the group, and the NGT process, particularly what experts need to do. Second, the precoded group rating questionnaire and evidence synthesis were presented. Participants had around 15 minutes to complete their individual ratings. Participants were asked to explore core domains, rewrite and add potential domains and their associated definitions, investigate reasons for any differences in ratings, and consider candidate outcome measures. Completed questionnaires were extracted by the conference secretary (Xiaojing Zhong). Data statistics and analysis were performed by 2 trained research assistants (YY, Ziling Pang). Third, a semistructured group discussion was completed after the first round of individual rating. Participants were asked to make suggestions. As some were more vocal than others, facilitators asked each participant to speak in turn, in the order in which they were sitting, clockwise. To ensure that everyone has the opportunity to speak independently, the seating order is ranked from lowest to highest in terms of authority. Fourth, items that were not agreed upon (deleted or retained) were regenerated for the round 2 questionnaires.</p></sec><sec id="s2-4-5"><title>Data Analysis</title><p>The distribution of ratings for each domain and outcome measure was summarized, including the frequency, mean, SD, and IQR. The level of consensus reached by the group was set at 80% [<xref ref-type="bibr" rid="ref29">29</xref>]. Indicators that reached group consensus with strong support, 80% of the group rated the indicator between 7 and 9. The NGT method specifies agreement as 7 out of 9 members&#x2019; panel rating within a specific 3-point range. With 11 participants, consensus was established at 9 out of 11 participants, or 80% [<xref ref-type="bibr" rid="ref29">29</xref>].</p><p>The expert judgment coefficient (Ca) for each item was the sum score of each expert&#x2019;s judgment basis for each item, representing the experts&#x2019; judgment. The impact degree scores of each judgment basis are illustrated in Appendix S2 in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>. The familiarity coefficient (Cs) represents the familiarity of the expert, and the authority coefficient (Cr; Cr=[Ca+Cs]&#x00F7;2), with the results expressed as mean (SD). If Cr was above 0.7, it was generally considered a relatively high degree of an expert authority. The degree of coordination of expert opinions is Kendall&#x2019;s coordination coefficient W. Kendall&#x2019;s coordination coefficient W (statistical significance set at <italic>P</italic>&#x003C;.05) was used to assess whether the experts&#x2019; scoring of each item was consistent. The larger the value of the coordination coefficient W, the higher the degree of expert coordination.</p></sec></sec><sec id="s2-5"><title>Stage 3: Empowerment of Evaluation Indicators</title><sec id="s2-5-1"><title>Overview</title><p>We used the AHP to analyze and determine the weight of each indicator [<xref ref-type="bibr" rid="ref30">30</xref>]. Each respondent compares the relative importance of each pair of items using a specially designed questionnaire [<xref ref-type="bibr" rid="ref31">31</xref>].</p></sec><sec id="s2-5-2"><title>Data Analysis</title><p>This study uses Yaahp software (MetaDecision Software Technology Co, Ltd) to calculate the weights and verify the consistency of AHP. Yaahp is a kind of visual modeling and calculation software. According to the importance value assigned to each factor, we determined the Saaty scale, established the hierarchical model, constructed the judgment matrix, and conducted a hierarchical ranking and consistency test. The Saaty&#x2019;s 9-point intensity of relative importance weight scale is illustrated in Appendix S3 in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>. The consistency test was done by calculating the consistency index (CI) and the consistency ratio (CR). The consistency index is defined by the equation: <inline-formula><mml:math id="ieqn1"><mml:mi>C</mml:mi><mml:mi>I</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:mrow><mml:msub><mml:mrow><mml:mi>&#x03B3;</mml:mi></mml:mrow><mml:mrow><mml:mi>m</mml:mi><mml:mi>a</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub><mml:mo>-</mml:mo><mml:mi>n</mml:mi></mml:mrow><mml:mo>/</mml:mo><mml:mrow><mml:mi>n</mml:mi><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="ieqn2"><mml:mi>C</mml:mi><mml:mi>R</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:mrow><mml:mi>C</mml:mi><mml:mi>I</mml:mi></mml:mrow><mml:mo>/</mml:mo><mml:mrow><mml:mi>R</mml:mi><mml:mi>I</mml:mi></mml:mrow></mml:mrow></mml:math></inline-formula>, where <inline-formula><mml:math id="ieqn3"><mml:msub><mml:mrow><mml:mi>&#x03B3;</mml:mi></mml:mrow><mml:mrow><mml:mi>m</mml:mi><mml:mi>a</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:math></inline-formula> is the largest eigenvalue of a preference matrix, and n is the number of parameters. Random index (RI) values have been tabulated as a function of n, illustrated in Appendix S4 in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>. Consistency ratios higher than 0.1 suggest untrustworthy judgments, indicating that the comparisons and scores should be revised. When the AHP model is run through the consistency check, the weight of all factors at each level and ranking can be calculated. The combined weight of the 3-level items is multiplied by 100, and the integer value is taken according to the rounding principle.</p></sec></sec><sec id="s2-6"><title>Stage 4: Content Validity Test of the Evaluation System</title><sec id="s2-6-1"><title>Overview</title><p>The panel of experts assessed the relevance of the LassVQ evaluation system, and items were rated on a 4-point Likert scale, where 1 indicated &#x201C;not relevant,&#x201D; 2 indicated &#x201C;marginally relevant,&#x201D; 3 indicated &#x201C;quite relevant,&#x201D; and 4 indicated &#x201C;strongly relevant.&#x201D;</p></sec><sec id="s2-6-2"><title>Data Analysis</title><p>The I-CVI (Item-level Content Validity Index) was calculated from the expert&#x2019;s relevance rating for items 3 or 4, whereas the S-CVI/Ave (Scale-level Content Validity Index, Average) was derived by averaging the proportional relevance judgments of all experts. The number of experts in the relevance agreement was divided by the total number of experts. The interrater agreement among the experts was determined using the modified kappa statistic. The probability of chance agreement (Pc) for each item was determined using the formula: <inline-formula><mml:math id="ieqn4"><mml:mi>P</mml:mi><mml:mi>c</mml:mi><mml:mo>=</mml:mo><mml:mfenced open="[" close="]" separators="|"><mml:mrow><mml:mfenced separators="|"><mml:mrow><mml:mrow><mml:mrow><mml:mi>N</mml:mi><mml:mo>!</mml:mo></mml:mrow><mml:mo>/</mml:mo><mml:mrow><mml:mi>A</mml:mi><mml:mo>!</mml:mo></mml:mrow></mml:mrow></mml:mrow></mml:mfenced><mml:mfenced separators="|"><mml:mrow><mml:mi>N</mml:mi><mml:mo>-</mml:mo><mml:mi>A</mml:mi></mml:mrow></mml:mfenced><mml:mo>!</mml:mo></mml:mrow></mml:mfenced><mml:mi>*</mml:mi><mml:msup><mml:mrow><mml:mn>0.5</mml:mn></mml:mrow><mml:mrow><mml:mi>N</mml:mi></mml:mrow></mml:msup></mml:math></inline-formula>. <italic>N</italic> is the number of experts, and <italic>A</italic> is the number of experts who agree that the item was relevant [<xref ref-type="bibr" rid="ref32">32</xref>]. Kappa was determined using the following formula: <italic>k</italic>=(item-level content validity index<italic>&#x2212;Pc</italic>)/(1&#x2212;Pc). The kappa value above 0.74 was considered excellent, 0.60 to 0.74 as good, and 0.54 to 0.59 as fair [<xref ref-type="bibr" rid="ref32">32</xref>].</p></sec></sec><sec id="s2-7"><title>Stage 5: Pilot Testing</title><p>A pilot study with 15 participants (9 viewers and 6 producers of HESVs) was conducted to evaluate readability and comprehensibility of the draft scale, following the NGT. The main study did not include these participants. Data were collected through face-to-face interactions to ensure detailed feedback on the scale items during the pilot phase. Participants rated each item using a 5-point Likert scale (1=very poor, 5=excellent) for both readability and comprehensibility. Open-ended feedback was also solicited to identify potential ambiguities. The subsequent survey was conducted with the main participants after adjustments were made based on feedback received during the pilot test.</p></sec></sec><sec id="s3" sec-type="results"><title>Results</title><sec id="s3-1"><title>Overview</title><p>The overall process of LassVQ development and validation is summarized in <xref ref-type="fig" rid="figure1">Figure 1</xref>. This flowchart provides an overview of each step, which is described in detail in the following sections.</p><fig position="float" id="figure1"><label>Figure 1.</label><caption><p>The flowchart for establishing the evaluation system. I-CVI: Item-level Content Validity Index; S-CVI/Ave: Scale-level Content Validity Index, Average.</p></caption><graphic alt-version="no" mimetype="image" position="float" xlink:type="simple" xlink:href="jmir_v27i1e72661_fig01.png"/></fig></sec><sec id="s3-2"><title>Generation and Categorization of Indicators</title><p>Based on the preliminary literature review, a framework was established, including defined dimensions, operational definitions, and an initial item pool. The brainstorming session resulted in the generation of 2 new items and the modification of 3 overlapping items. The final initial version of LassVQ consisted of 5 primary indicators, 20 secondary indicators, and 94 tertiary indicators as illustrated in Appendix S5 in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>.</p></sec><sec id="s3-3"><title>Development of Consensus on Indicators</title><p>This study adopted 2 rounds of NGT meetings, enrolling a total of 11 experts. Demographic characteristics of the expert panel are outlined in <xref ref-type="table" rid="table1">Table 1</xref>. Among the selected experts, 2 were male and 9 were female, 45% (5/11) of experts had a doctoral degree. The panel represented a multidisciplinary background, comprising 2 health educational video practitioners, 5 health education researchers, 3 health education practitioners, and 1 library informatics researcher. Furthermore, 80% (9/11) of them ranked associate professor or professor, with 55% (6/11) having more than 20 years of research and work experience. All participating experts were from institutions located in Beijing. The Cs of each key indicator of the NGT was 0.77. The average value of the Ca and Cr was 0.93 and 0.85, respectively. The Kendall W of the revised indicator system is 0.216 (<italic>&#x03C7;</italic><sup>2</sup><sub>49</sub>=105.8, <italic>P</italic>&#x003C;.001), as presented in <xref ref-type="table" rid="table2">Table 2</xref>, while our predefined consensus threshold (&#x2265;80% experts agreement) was achieved, indicating that consensus could be reached among the experts.</p><table-wrap id="t1" position="float"><label>Table 1.</label><caption><p>Demographic characteristics of experts.</p></caption><table id="table1" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Characteristics</td><td align="left" valign="bottom">Value</td></tr></thead><tbody><tr><td align="left" valign="top">Age (y), mean (SD); minimum-maximum</td><td align="left" valign="top">44.82 (7.80); 31&#x2010;54</td></tr><tr><td align="left" valign="top">Sex, n (%)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Male</td><td align="left" valign="top">2 (0.18)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Female</td><td align="left" valign="top">9 (0.82)</td></tr><tr><td align="left" valign="top">Level of education, n (%)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Bachelor-graduated</td><td align="left" valign="top">3 (0.27)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Postgraduated</td><td align="left" valign="top">3 (0.27)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Doctoral degree</td><td align="left" valign="top">5 (0.45)</td></tr><tr><td align="left" valign="top">Professional background, n (%)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Health educational videos practitioners</td><td align="left" valign="top">2 (0.18)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Health education researcher</td><td align="left" valign="top">5 (0.45)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Health education practitioner</td><td align="left" valign="top">3 (0.27)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Library informatics researcher</td><td align="left" valign="top">1 (0.09)</td></tr><tr><td align="left" valign="top">Professional title, n (%)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Senior professor</td><td align="left" valign="top">3 (0.27)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Vice-senior professor</td><td align="left" valign="top">6 (0.55)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Middle title</td><td align="left" valign="top">2 (0.18)</td></tr><tr><td align="left" valign="top">Years of research or work experience, n (%)</td><td align="left" valign="top"/></tr><tr><td align="char" char="." valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>1&#x2010;10</td><td align="left" valign="top">2 (0.18)</td></tr><tr><td align="char" char="." valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>10&#x2010;20</td><td align="left" valign="top">3 (0.27)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x003E;20</td><td align="left" valign="top">6 (0.55)</td></tr><tr><td align="left" valign="top">Degree of authority of experts, mean (SD)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>The degree of familiarity (Cs)</td><td align="left" valign="top">0.77 (0.15)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>The coefficient of judgment (Ca)</td><td align="left" valign="top">0.93 (0.08)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>The degree of expert opinion authority (Cr)</td><td align="left" valign="top">0.85 (0.10)</td></tr></tbody></table></table-wrap><table-wrap id="t2" position="float"><label>Table 2.</label><caption><p>The degree of coordination of experts&#x2019; opinions.</p></caption><table id="table2" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Indicator level</td><td align="left" valign="bottom">W</td><td align="left" valign="bottom">Chi-square (<italic>df</italic>)</td><td align="left" valign="bottom"><italic>P</italic> value</td></tr></thead><tbody><tr><td align="left" valign="top">Primary indicators</td><td align="char" char="." valign="top">0.23</td><td align="left" valign="top">6.8 (3)</td><td align="left" valign="top">.08</td></tr><tr><td align="left" valign="top">Secondary indicators</td><td align="char" char="." valign="top">0.16</td><td align="left" valign="top">19.5 (12)</td><td align="left" valign="top">.08</td></tr><tr><td align="left" valign="top">Tertiary indicators</td><td align="char" char="." valign="top">0.23</td><td align="left" valign="top">74.3 (32)</td><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top">Evaluation system</td><td align="char" char="." valign="top">0.22</td><td align="left" valign="top">105.8 (49)</td><td align="left" valign="top">&#x003C;.001</td></tr></tbody></table></table-wrap><p>In round 1, 11 experts suggested amendments to some indicators. During the discussion, there were 5 primary indicators and 20 secondary indicators, with the number unchanged. The primary indicator, &#x201C;communication target,&#x201D; did not reach a consensus. For secondary indicators, 7 of 20 did not reach consensus, which will be addressed in round 2 of NGT. The &#x201C;reliability&#x201D; of the primary indicator &#x201C;communicator&#x201D; was changed to &#x201C;credibility.&#x201D; Tertiary indicators were screened as follows: (1) revised &#x201C;reasonable and clear navigation structure&#x201D; to &#x201C;reasonable navigation structure,&#x201D; and revised &#x201C;the comments are positive&#x201D; to &#x201C;the positive ratio of comments;&#x201D; (2) added &#x201C;views volume;&#x201D; (3) two indicators &#x201C;available and easy to use forwarding function&#x201D; and &#x201C;available and easy to use like function&#x201D; were merged into 1 indicator &#x201C;available and easy to use like and share functions,&#x201D; and &#x201C;available and easy to use comments and messages&#x201D; and &#x201C;available and easy to use messaging function&#x201D; were merged into 1 indicator &#x201C;available and easy to use comments and messages functions.&#x201D;</p><p>In round 2, the expert panel achieved consensus about the final indicator system, which then deleted 1 primary indicator, 7 secondary indicators, and 59 tertiary indicators based on the consensus criteria. The medication and consensus rate of indicators of the 2 rounds of NGT were presented in Appendices S6 and S7 in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>. After the 2 rounds of NGT, 4 primary indicators, 13 secondary indicators, and 34 tertiary indicators finally reached consensus, as presented in <xref ref-type="fig" rid="figure1">Figure 1</xref>.</p></sec><sec id="s3-4"><title>Empowerment of the Quality Evaluation System</title><p>According to the AHP, the quality evaluation system of HESVs on social media was divided into 4 layers. The 9-point intensity of relative weight of importance scale and random index is illustrated in Appendices S2 and S3 in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>. Matrix and weight analysis of the primary indicators (communicator, communication content, communication channel, and communication effect) are presented in <xref ref-type="table" rid="table3">Table 3</xref>. Among the 4 primary indicators of the evaluation system, &#x201C;communication content&#x201D; was perceived as the most influential variable and had a weight of 45.73%, more important than &#x201C;communicator,&#x201D; &#x201C;communication channel,&#x201D; and &#x201C;communication effect,&#x201D; with a relative contribution of 34.58%, 9.93%, and 9.81%, respectively.</p><table-wrap id="t3" position="float"><label>Table 3.</label><caption><p>Analysis of the matrix and weight of the primary indicators (consistency index 0.0608).</p></caption><table id="table3" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Primary indicators</td><td align="left" valign="bottom">(Who) Communicator</td><td align="left" valign="bottom">(What) Communication content</td><td align="left" valign="bottom">(In which channel) Communication channel</td><td align="left" valign="bottom">(With what effect) Communication effect</td><td align="left" valign="bottom">W</td><td align="left" valign="bottom">Rank</td></tr></thead><tbody><tr><td align="left" valign="top">(Who) Communicator</td><td align="left" valign="top">1</td><td align="left" valign="top">0.21</td><td align="left" valign="top">0.99</td><td align="left" valign="top">0.28</td><td align="left" valign="top">0.10</td><td align="left" valign="top">4</td></tr><tr><td align="left" valign="top">(What) Communication content</td><td align="left" valign="top">4.66</td><td align="left" valign="top">1</td><td align="left" valign="top">4.60</td><td align="left" valign="top">1.32</td><td align="left" valign="top">0.46</td><td align="left" valign="top">1</td></tr><tr><td align="left" valign="top">(In which channel) Communication channel</td><td align="left" valign="top">1.01</td><td align="left" valign="top">0.22</td><td align="left" valign="top">1</td><td align="left" valign="top">0.29</td><td align="left" valign="top">0.10</td><td align="left" valign="top">3</td></tr><tr><td align="left" valign="top">(With what effect) Communication effect</td><td align="left" valign="top">3.52</td><td align="left" valign="top">0.76</td><td align="left" valign="top">3.48</td><td align="left" valign="top">1</td><td align="left" valign="top">0.35</td><td align="left" valign="top">2</td></tr></tbody></table></table-wrap><p>The relative weights of secondary indicators are presented in Appendix S8 in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>. The secondary indicators analysis showed that in the &#x201C;communicator,&#x201D; &#x201C;credibility&#x201D; was perceived as more important than &#x201C;authoritative&#x201D; (within-dimensional weight=56.67% and 43.33%, respectively). Among the &#x201C;communication content,&#x201D; the relative importance was &#x201C;scientific&#x201D; (24.26%), followed by &#x201C;understandability&#x201D; (18.59%), &#x201C;reliability&#x201D; (18%), &#x201C;actionability&#x201D; (14.64%), &#x201C;watchability&#x201D; (12.99%), and &#x201C;attractiveness&#x201D; (11.53%). In the &#x201C;communication channel&#x201D;, &#x201C;availability&#x201D; (74.62%) was viewed as more important than &#x201C;interactivity&#x201D; (25.38%). Among &#x201C;communication effect,&#x201D; the relative importance was &#x201C;social attention&#x201D; (39.89%), followed by &#x201C;perceived usefulness&#x201D; (36.15%) and &#x201C;communication engagement&#x201D; (23.96%).</p><p>The relative weights of tertiary indicators are presented in Appendix S8 in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>. The ten tertiary indicators with highest ranks were: (1) recommended as a trending video; (2) positive comments ratio, tied for (3) content&#x2019;s consistency with scientific common sense, and (4) content complies with ethical standards; (5) content contains necessary relevant information; (6) stable and effective video information source; (7) motivation to share; (8) behavioral guidance or operation techniques are presented with clear steps in logical order; (9) expression is understandable, avoiding medical terms; and (10) theme is clear. The top 1, 2, and 7 tertiary indicators fell into the &#x201C;communication effect&#x201D; dimension; numbers 3, 4, 5, 8, 9, and 10 into the &#x201C;communication content&#x201D; dimension.</p></sec><sec id="s3-5"><title>Content Validity Analysis of the LassVQ Evaluation System</title><p>The content validity index for the relevancy of the LassVQ evaluation system was calculated to be 0.87 (<xref ref-type="table" rid="table4">Table 4</xref>). The kappa designating agreement of relevance of the LassVQ evaluation system was all above 0.74 (&#x03BA;=0.80&#x2010;1.14).</p><table-wrap id="t4" position="float"><label>Table 4.</label><caption><p>Content validity index of indicator relevancy and modified kappa of the LassVQ<sup><xref ref-type="table-fn" rid="table4fn1">a</xref></sup> evaluation system.</p></caption><table id="table4" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Indicator</td><td align="left" valign="bottom">Experts in agreement</td><td align="left" valign="bottom">I-CVI<sup><xref ref-type="table-fn" rid="table4fn2">b</xref></sup></td><td align="left" valign="bottom">Probability of chance occurrence</td><td align="left" valign="bottom">Modified kappa</td></tr></thead><tbody><tr><td align="left" valign="top">(Who) Communicator</td><td align="left" valign="top">8</td><td align="left" valign="top">0.73</td><td align="left" valign="top">2.90</td><td align="left" valign="top">1.14</td></tr><tr><td align="left" valign="top">(What) Communication content</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1</td></tr><tr><td align="left" valign="top">(In which channel) Communication channel</td><td align="left" valign="top">8</td><td align="left" valign="top">0.73</td><td align="left" valign="top">2.90</td><td align="left" valign="top">1.14</td></tr><tr><td align="left" valign="top">(With what effect) Communication effect</td><td align="left" valign="top">10</td><td align="left" valign="top">0.91</td><td align="left" valign="top">0.01</td><td align="left" valign="top">0.91</td></tr><tr><td align="left" valign="top">Credibility</td><td align="left" valign="top">10</td><td align="left" valign="top">0.91</td><td align="left" valign="top">0.01</td><td align="left" valign="top">0.91</td></tr><tr><td align="left" valign="top">Authoritative</td><td align="left" valign="top">10</td><td align="left" valign="top">0.91</td><td align="left" valign="top">0.01</td><td align="left" valign="top">0.91</td></tr><tr><td align="left" valign="top">Scientific</td><td align="left" valign="top">10</td><td align="left" valign="top">0.91</td><td align="left" valign="top">0.01</td><td align="left" valign="top">0.91</td></tr><tr><td align="left" valign="top">Reliability</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Attractiveness</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Watchability</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Understandability</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Actionability</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Availability</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Interactivity</td><td align="left" valign="top">9</td><td align="left" valign="top">0.82</td><td align="left" valign="top">0.11</td><td align="left" valign="top">0.80</td></tr><tr><td align="left" valign="top">Perceived usefulness</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Communication engagement</td><td align="left" valign="top">10</td><td align="left" valign="top">0.91</td><td align="left" valign="top">0.01</td><td align="left" valign="top">0.91</td></tr><tr><td align="left" valign="top">Social attention</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Account&#x2019;s basic information is disclosed</td><td align="left" valign="top">8</td><td align="left" valign="top">0.73</td><td align="left" valign="top">2.90</td><td align="left" valign="top">1.14</td></tr><tr><td align="left" valign="top">Account&#x2019;s credibility is high</td><td align="left" valign="top">9</td><td align="left" valign="top">0.82</td><td align="left" valign="top">0.11</td><td align="left" valign="top">0.80</td></tr><tr><td align="left" valign="top">Account&#x2019;s holder is engaged in medical and health-related domain</td><td align="left" valign="top">10</td><td align="left" valign="top">0.91</td><td align="left" valign="top">0.01</td><td align="left" valign="top">0.91</td></tr><tr><td align="left" valign="top">Account&#x2019;s platform certification is authoritative</td><td align="left" valign="top">9</td><td align="left" valign="top">0.82</td><td align="left" valign="top">0.11</td><td align="left" valign="top">0.80</td></tr><tr><td align="left" valign="top">Account&#x2019;s holder has expertise with specialized academic background</td><td align="left" valign="top">9</td><td align="left" valign="top">0.82</td><td align="left" valign="top">0.11</td><td align="left" valign="top">0.80</td></tr><tr><td align="left" valign="top">Content&#x2019;s consistency with scientific common sense</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Content complies with ethical standards</td><td align="left" valign="top">10</td><td align="left" valign="top">0.91</td><td align="left" valign="top">0.01</td><td align="left" valign="top">0.91</td></tr><tr><td align="left" valign="top">Content contains visible reference information</td><td align="left" valign="top">7</td><td align="left" valign="top">0.64</td><td align="left" valign="top">92.81</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Content has info that&#x2019;s kind of needed and related stuff</td><td align="left" valign="top">9</td><td align="left" valign="top">0.82</td><td align="left" valign="top">0.11</td><td align="left" valign="top">0.80</td></tr><tr><td align="left" valign="top">Content aligns with people&#x2019;s health concerns</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Content focuses on popular health topics</td><td align="left" valign="top">9</td><td align="left" valign="top">0.82</td><td align="left" valign="top">0.11</td><td align="left" valign="top">0.80</td></tr><tr><td align="left" valign="top">Images, text, and other materials are used properly</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Image quality is clear</td><td align="left" valign="top">8</td><td align="left" valign="top">0.73</td><td align="left" valign="top">2.90</td><td align="left" valign="top">1.14</td></tr><tr><td align="left" valign="top">Dubbing is clear, louder than background music</td><td align="left" valign="top">7</td><td align="left" valign="top">0.64</td><td align="left" valign="top">92.81</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Dubbing is smooth, without any lag or ambiguity</td><td align="left" valign="top">8</td><td align="left" valign="top">0.73</td><td align="left" valign="top">2.90</td><td align="left" valign="top">1.14</td></tr><tr><td align="left" valign="top">Theme is clear</td><td align="left" valign="top">9</td><td align="left" valign="top">0.82</td><td align="left" valign="top">0.11</td><td align="left" valign="top">0.80</td></tr><tr><td align="left" valign="top">Expression is clear and consistent</td><td align="left" valign="top">10</td><td align="left" valign="top">0.91</td><td align="left" valign="top">0.01</td><td align="left" valign="top">0.91</td></tr><tr><td align="left" valign="top">Expression uses unclear or confusing language</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Behavioral guidance or operation techniques are presented with clear steps in logical order</td><td align="left" valign="top">9</td><td align="left" valign="top">0.82</td><td align="left" valign="top">0.11</td><td align="left" valign="top">0.80</td></tr><tr><td align="left" valign="top">Photos, graphics, tables, or models are used to explain how to take action clearly</td><td align="left" valign="top">9</td><td align="left" valign="top">0.82</td><td align="left" valign="top">0.11</td><td align="left" valign="top">0.80</td></tr><tr><td align="left" valign="top">Reasonable and clear navigation structure</td><td align="left" valign="top">8</td><td align="left" valign="top">0.73</td><td align="left" valign="top">2.90</td><td align="left" valign="top">1.14</td></tr><tr><td align="left" valign="top">Stable and effective video information source</td><td align="left" valign="top">9</td><td align="left" valign="top">0.82</td><td align="left" valign="top">0.11</td><td align="left" valign="top">0.80</td></tr><tr><td align="left" valign="top">Available and easy to use like and share functions</td><td align="left" valign="top">8</td><td align="left" valign="top">0.73</td><td align="left" valign="top">2.90</td><td align="left" valign="top">1.14</td></tr><tr><td align="left" valign="top">Available and easy to use comments and messages functions</td><td align="left" valign="top">8</td><td align="left" valign="top">0.73</td><td align="left" valign="top">2.90</td><td align="left" valign="top">1.14</td></tr><tr><td align="left" valign="top">Perception of knowledge acquisition</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Perception of action necessity</td><td align="left" valign="top">10</td><td align="left" valign="top">0.91</td><td align="left" valign="top">0.01</td><td align="left" valign="top">0.91</td></tr><tr><td align="left" valign="top">Intention of behavioral modification</td><td align="left" valign="top">10</td><td align="left" valign="top">0.91</td><td align="left" valign="top">0.01</td><td align="left" valign="top">0.91</td></tr><tr><td align="left" valign="top">Motivation to share</td><td align="left" valign="top">9</td><td align="left" valign="top">0.82</td><td align="left" valign="top">0.11</td><td align="left" valign="top">0.80</td></tr><tr><td align="left" valign="top">Views volume</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Likes volume</td><td align="left" valign="top">9</td><td align="left" valign="top">0.82</td><td align="left" valign="top">0.11</td><td align="left" valign="top">0.80</td></tr><tr><td align="left" valign="top">Collection volume</td><td align="left" valign="top">8</td><td align="left" valign="top">0.73</td><td align="left" valign="top">2.90</td><td align="left" valign="top">1.14</td></tr><tr><td align="left" valign="top">Repost volume</td><td align="left" valign="top">9</td><td align="left" valign="top">0.82</td><td align="left" valign="top">0.11</td><td align="left" valign="top">0.80</td></tr><tr><td align="left" valign="top">Recommended as a trending video</td><td align="left" valign="top">9</td><td align="left" valign="top">0.82</td><td align="left" valign="top">0.11</td><td align="left" valign="top">0.80</td></tr><tr><td align="left" valign="top">Positive comments ratio</td><td align="left" valign="top">11</td><td align="left" valign="top">1.00</td><td align="left" valign="top">0.00</td><td align="left" valign="top">1.00</td></tr><tr><td align="left" valign="top">Average S-CVI<sup><xref ref-type="table-fn" rid="table4fn3">c</xref></sup></td><td align="left" valign="top">0.87</td><td align="left" valign="top">&#x2014;<sup><xref ref-type="table-fn" rid="table4fn4">d</xref></sup></td><td align="left" valign="top">&#x2014;</td><td align="left" valign="top">&#x2014;</td></tr></tbody></table><table-wrap-foot><fn id="table4fn1"><p><sup>a</sup>LassVQ: Lasswell&#x2019;s Video Quality scale</p></fn><fn id="table4fn2"><p><sup>b</sup> I-CVI: Item-level Content Validity Index.</p></fn><fn id="table4fn3"><p><sup>c</sup>S-CVI: Scale-level Content Validity Index.</p></fn><fn id="table4fn4"><p><sup>d</sup>Not applicable.</p></fn></table-wrap-foot></table-wrap></sec><sec id="s3-6"><title>Pilot Testing</title><p>A total of 15 participants completed the pilot questionnaire, including 9 viewers (aged 19&#x2010;46 years) and 6 producers (aged 33&#x2010;54 years). Participant characteristics are detailed in Appendix S9 in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>.</p><p>The mean readability score across all items was 4.87 (SD 0.26), and the mean comprehensibility score was 4.92 (SD 0.18), indicating that the items were generally clear and understandable. Qualitative feedback highlighted minor issues in wording and phrasing, which were addressed through targeted revisions. For example, vague or informal phrases such as &#x201C;content has info that&#x2019;s kind of needed and related stuff&#x201D; were replaced with clearer wording like &#x201C;content contains necessary relevant information.&#x201D; Similarly, ambiguous expressions like &#x201C;expression uses unclear or confusing language&#x201D; were revised to &#x201C;expression is understandable, avoiding medical terms.&#x201D; These refinements improved the clarity, professionalism, and user-centeredness of the final scale.</p></sec></sec><sec id="s4" sec-type="discussion"><title>Discussion</title><sec id="s4-1"><title>Principal Findings</title><p>This study developed LassVQ, an HESVs evaluation system, focusing on 4 key dimensions: communicator, content, channel, and effect, with credibility, scientific rigor, accessibility, and social engagement as core quality indicators. The indicators showed preliminary evidence of acceptable content validity. LassVQ is a preliminary tool that requires further empirical validation. It may, in the future, contribute to supporting researchers in assessing HESVs on social media, aid platforms in video screening, and assist policymakers in developing video production standards.</p><p>Valid and reliable measurement tools play an important role in supporting quantitative research and are also frequently used in communication studies [<xref ref-type="bibr" rid="ref33">33</xref>]. With the emergence and popularity of HESVs on social media and concerns about their quality, it is of both theoretical and practical meaning to explore a quality evaluation system [<xref ref-type="bibr" rid="ref34">34</xref>]. Based on the 5W model, this research developed the LassVQ evaluation system using the nominal group technique and the analytic hierarchy process. Overall, results of Cs, Ca, and Cr suggested that experts are familiar with the topic, with judgments influenced by practical experience and theoretical analysis and demonstrated a relatively high authority. The result of the modified kappa suggested that the LassVQ evaluation system possesses acceptable content validity [<xref ref-type="bibr" rid="ref32">32</xref>].</p></sec><sec id="s4-2"><title>Comparison With Previous Work</title><p>Shawahna [<xref ref-type="bibr" rid="ref35">35</xref>] and Hong et al [<xref ref-type="bibr" rid="ref36">36</xref>] used to combine NGT and AHP and facilitated decision-making and quantitatively observe and reviewed in health care dilemmas and streams&#x2019; quality, respectively. The NGT calls for methods to include every expert&#x2019;s opinion. As would be expected, some experts were more vocal than others, and so sessions would include a &#x201C;round-robin,&#x201D; which means asking each participant to speak in turn in the order in which they are sitting to ensure each had suggested discussion. The anonymous voting process was intended to encourage participant engagement. The participating experts included both health education researchers and practitioners, along with HESV practitioners and a library informatics researcher. All experts were involved in aspects of HESV production and communication. This combination with AHP allows for analyzing an expert&#x2019;s subjective judgment with mathematical form and conducting multiobjective decision-making analysis of the scientific treatment to ensure the scientific result [<xref ref-type="bibr" rid="ref37">37</xref>]. Experts adopt judgment matrices to determine the importance value of each indicator, and the result shows that the consistency of the pairwise comparison matrices at all levels met the consistency test criterion, with CR&#x003C;0.10 [<xref ref-type="bibr" rid="ref37">37</xref>], suggesting acceptable logical consistency and supporting scientific rigor and reliability. The weighted value of the primary indicator was in the following order: communication content (0.46), communication effect (0.34), communication channel (0.10), and communicator (0.10). Existing tools were designed for printed materials, developed many years ago, and may not be fully applicable to the social media context. Furthermore, DISCERN consists of 6 questions focusing on diseases and treatment, while the JAMA benchmarks take advertisement into consideration.</p><p>The Lasswell&#x2019;s 5W communication model, a classic theory in information communication, offers a theoretical framework for understanding the dissemination process of HESVs on social media [<xref ref-type="bibr" rid="ref25">25</xref>]. It was put forward in 1948 and still has its applicability to this day, which divides the communication process into 5 parts, including the communicator, information, channel, audience, and effect. Critics argue that the 5W model&#x2019;s linear approach is outdated and insufficient for adapting to the dynamic environment of the internet [<xref ref-type="bibr" rid="ref38">38</xref>]. However, consistent with the point by Sapienza et al [<xref ref-type="bibr" rid="ref39">39</xref>], this study holds that the 5W model is flexible and we should dialectically explore new applications of it. For instance, Wei et al [<xref ref-type="bibr" rid="ref24">24</xref>] expanded the 5W model into an 8-element communication framework for internet health rumors, while Xu et al [<xref ref-type="bibr" rid="ref40">40</xref>] designed a questionnaire based on the 5W model to investigate caregivers&#x2019; needs regarding medication content and dissemination channels. In the 2 rounds of NGT discussions and indicator evaluations, this study removed the audience dimension from the original 5W model and restructured the dimensions into 4 categories: communicator, communication content, communication channel, and communication effect. Experts concurred that within the social media context, the roles of communicator and audience often overlap, with individuals potentially fulfilling both roles simultaneously [<xref ref-type="bibr" rid="ref25">25</xref>]. Since audience research typically examines viewer characteristics and responses, while our study focuses on the quality of HESVs, including this dimension was considered outside our methodological scope.</p><p>Following the NGT discussions, the study excluded the communicator&#x2019;s influence, originally measured by tertiary indicators such as the communicator&#x2019;s total number of followers, total number of received likes, and total number of posted videos. Bengi et al [<xref ref-type="bibr" rid="ref41">41</xref>] advised focusing on the communicator&#x2019;s credibility and professional background rather than metrics like follower count or video quantity. The elaboration likelihood model indicated that professional titles may serve as signals of expertise, potentially enhancing viewer engagement [<xref ref-type="bibr" rid="ref42">42</xref>,<xref ref-type="bibr" rid="ref43">43</xref>]. The influence of the communication channel was also removed, including metrics such as &#x201C;number of platform users,&#x201D; &#x201C;frequency of platform being forwarded by mainstream media,&#x201D; and &#x201C;the proportion of health popularization videos on the platform.&#x201D; While platforms like TikTok (ByteDance) garner significantly more views and likes than YouTube, they have comparatively fewer high-quality videos [<xref ref-type="bibr" rid="ref41">41</xref>]. The model also eliminated breadth-of-spread metrics, such as &#x201C;balanced gender of users,&#x201D; &#x201C;balanced age distribution of users,&#x201D; &#x201C;wide distribution of users,&#x201D; and &#x201C;balanced classification of the user&#x2019;s city.&#x201D; The NGT experts argued that these indicators were considered of limited significance and that data availability was relatively low. When producing or evaluating HESVs, priority should be given to the content&#x2019;s theme and target audience [<xref ref-type="bibr" rid="ref15">15</xref>,<xref ref-type="bibr" rid="ref44">44</xref>]. For example, videos about menstruation inherently tend to attract an audience with an imbalanced gender and age distribution. For &#x201C;communication recognition&#x201D; and &#x201C;communication participation,&#x201D; NGT experts emphasized the significance of views as a direct communication metric. They also suggested combining views, likes, collections, and reposts as a single metric, which aligns with the research by Erdem and Karaca [<xref ref-type="bibr" rid="ref45">45</xref>] on the video power index used for evaluating YouTube content.</p><p>For the tertiary indicators of the understandability of communication content, the NGT removed some indicators deemed less relevant. Among those addressing the consistency between theme and title, only &#x201C;theme is clear&#x201D; was retained as the most representative indicator [<xref ref-type="bibr" rid="ref46">46</xref>]. Indicators like informative subtitles, clear summaries, 3 to 5 core points, and highlighting of core information were also removed, as they were deemed unsuitable in the context of short social media videos [<xref ref-type="bibr" rid="ref18">18</xref>]. This study refined the tertiary indicators for content attractiveness by focusing on the &#x201C;three Vs&#x201D; of communication&#x2014;verbal, vocal, and visual [<xref ref-type="bibr" rid="ref16">16</xref>], a model recommended for enhancing educational outcomes in HESVs [<xref ref-type="bibr" rid="ref18">18</xref>]. Experts noted that the indicator &#x201C;subtitles are consistent with dubs&#x201D; was inappropriate since subtitles might be autogenerated text. Indicators of actionability were narrowed down to emphasize logical presentation and clear guidance on how to take action, consistent with the study by Sui and Zhang [<xref ref-type="bibr" rid="ref47">47</xref>] on the role of logical coherence in changing attitudes. All indicators related to perceived cultural appropriateness were excluded, as experts argued that evaluating HESVs based on target audience and linguistic preferences might lead to conflicting conclusions.</p></sec><sec id="s4-3"><title>Strengths and Limitations</title><p>This study is the first to develop a comprehensive evaluation system for HESVs on social media (LassVQ). Some limitations of this study should be noted. The NGT itself is less commonly used than the Delphi process in health communication, with disadvantages including limited rounds of voting [<xref ref-type="bibr" rid="ref48">48</xref>]. However, this is outweighed by allowing face-to-face discussions and anonymous voting, which yield higher response rates than would have been achieved with mailed questionnaires [<xref ref-type="bibr" rid="ref49">49</xref>]. Further research is required to confirm the validity of the findings obtained here on this evaluation system by applying it to HESVs on social media platforms. For the pilot study, the small sample size limits the generalizability of the findings related to readability and comprehensibility. As an exploratory step, the pilot was primarily intended to guide item refinement, and its results should be interpreted with caution. The expert selection process, constrained by the authors&#x2019; available resources, may introduce certain limitations and potential biases. The other limitation of the study lies in its focus on short-form video content, which may limit the applicability of the findings to other types of media, such as long-form videos or text-based health information. Although short videos are highly popular on social media, the evaluation criteria developed may not fully capture the nuances of different content formats. Future research could explore how the evaluation system might need to be adapted or expanded for other forms of health communication content across various platforms. The LassVQ evaluation system may offer a useful framework for analyzing the current circumstance of HESVs on social media, although further application and validation are needed to confirm its broader utility.</p></sec><sec id="s4-4"><title>Further Directions</title><p>A more detailed investigation into the key factors for the quality improvement of HESVs on social media is needed to clarify. To support external validation, several health video producers and viewers will apply the LassVQ to a representative sample of high-view HESVs from major social media platforms. Intraclass correlation coefficients will be used to evaluate interrater reliability. Videos will also be rated using DISCERN and Global Quality Score, enabling correlation analyses to examine LassVQ&#x2019;s predictive accuracy.</p></sec><sec id="s4-5"><title>Conclusions</title><p>In summary, the quality evaluation system for HESVs on social media (LassVQ) developed in this study offers a structured approach to enhancing the quality of health communication throughout the entire video production and dissemination process. The system equips health care professionals with a research-based tool for the design, production, and evaluation of HESVs, with an emphasis on critical quality indicators. Future research could expand on these findings by refining the evaluation criteria, integrating additional perspectives from health care professionals, or tailoring the system to address specific health topics. The application of the LassVQ enables researchers and practitioners to continually enhance the effectiveness and impact of health education content disseminated on social media platforms.</p></sec></sec></body><back><ack><p>The authors gratefully acknowledge the experts who contributed to this study through valuable discussions and insights. Special thanks are also extended to Ziling Pang and Xiaojing Zhong for their assistance in coordinating the expert meetings.</p></ack><fn-group><fn fn-type="con"><p>YH wrote the draft of manuscript, led the literature review, data analysis, and interpretation. YY and WL provided critical feedback and assisted in refining the methodology and data analysis. YZ contributed to manuscript writing. JS supervised the research and interpreted the results.</p></fn><fn fn-type="conflict"><p>None declared.</p></fn></fn-group><glossary><title>Abbreviations</title><def-list><def-item><term id="abb1">5W</term><def><p>Lasswell&#x2019;s 5W communication model</p></def></def-item><def-item><term id="abb2">AHP</term><def><p>analytic hierarchy process</p></def></def-item><def-item><term id="abb3">COSMIN</term><def><p>Consensus-Based Standards for the Selection of Health Status Measurement Instruments</p></def></def-item><def-item><term id="abb4">HESV</term><def><p>health educational short video</p></def></def-item><def-item><term id="abb5">I-CVI</term><def><p>Item-level Content Validity Index</p></def></def-item><def-item><term id="abb6"><italic>JAMA</italic></term><def><p><italic>Journal of the American Medical Association</italic></p></def></def-item><def-item><term id="abb7">LassVQ</term><def><p>Lasswell&#x2019;s Video Quality scale</p></def></def-item><def-item><term id="abb8">NGT</term><def><p>nominal group technique</p></def></def-item><def-item><term id="abb9">S-CVI/Ave</term><def><p>Scale-level Content Validity Index, Average</p></def></def-item></def-list></glossary><ref-list><title>References</title><ref id="ref1"><label>1</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Xiao</surname><given-names>L</given-names> </name><name name-style="western"><surname>Min</surname><given-names>H</given-names> </name><name name-style="western"><surname>Wu</surname><given-names>Y</given-names> </name><etal/></person-group><article-title>Public&#x2019;s preferences for health science popularization short videos in China: a discrete choice experiment</article-title><source>Front Public Health</source><year>2023</year><volume>11</volume><fpage>1160629</fpage><pub-id pub-id-type="doi">10.3389/fpubh.2023.1160629</pub-id><pub-id pub-id-type="medline">37601206</pub-id></nlm-citation></ref><ref id="ref2"><label>2</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Moorhead</surname><given-names>SA</given-names> </name><name name-style="western"><surname>Hazlett</surname><given-names>DE</given-names> </name><name name-style="western"><surname>Harrison</surname><given-names>L</given-names> </name><name name-style="western"><surname>Carroll</surname><given-names>JK</given-names> </name><name name-style="western"><surname>Irwin</surname><given-names>A</given-names> </name><name name-style="western"><surname>Hoving</surname><given-names>C</given-names> </name></person-group><article-title>A new dimension of health care: systematic review of the uses, benefits, and limitations of social media for health communication</article-title><source>J Med Internet Res</source><year>2013</year><month>04</month><day>23</day><volume>15</volume><issue>4</issue><fpage>e85</fpage><pub-id pub-id-type="doi">10.2196/jmir.1933</pub-id><pub-id pub-id-type="medline">23615206</pub-id></nlm-citation></ref><ref id="ref3"><label>3</label><nlm-citation citation-type="web"><person-group person-group-type="author"><name name-style="western"><surname>Gottfried</surname><given-names>J</given-names> </name></person-group><article-title>Americans&#x2019; social media use</article-title><source>Pew Research Center</source><year>2024</year><access-date>2025-09-11</access-date><comment><ext-link ext-link-type="uri" xlink:href="https://www.pewresearch.org/internet/2024/01/31/americans-social-media-use">https://www.pewresearch.org/internet/2024/01/31/americans-social-media-use</ext-link></comment></nlm-citation></ref><ref id="ref4"><label>4</label><nlm-citation citation-type="web"><person-group person-group-type="author"><name name-style="western"><surname>Kemp</surname><given-names>S</given-names> </name></person-group><article-title>Digital 2024: China</article-title><source>DataReportal</source><access-date>2025-09-11</access-date><comment><ext-link ext-link-type="uri" xlink:href="https://datareportal.com/reports/digital-2024-china">https://datareportal.com/reports/digital-2024-china</ext-link></comment></nlm-citation></ref><ref id="ref5"><label>5</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Mohamed</surname><given-names>F</given-names> </name><name name-style="western"><surname>Shoufan</surname><given-names>A</given-names> </name></person-group><article-title>Users&#x2019; experience with health-related content on YouTube: an exploratory study</article-title><source>BMC Public Health</source><year>2024</year><month>01</month><day>3</day><volume>24</volume><issue>1</issue><fpage>86</fpage><pub-id pub-id-type="doi">10.1186/s12889-023-17585-5</pub-id><pub-id pub-id-type="medline">38172765</pub-id></nlm-citation></ref><ref id="ref6"><label>6</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Gabarron</surname><given-names>E</given-names> </name><name name-style="western"><surname>Larbi</surname><given-names>D</given-names> </name><name name-style="western"><surname>Dorronzoro</surname><given-names>E</given-names> </name><name name-style="western"><surname>Hasvold</surname><given-names>PE</given-names> </name><name name-style="western"><surname>Wynn</surname><given-names>R</given-names> </name><name name-style="western"><surname>&#x00C5;rsand</surname><given-names>E</given-names> </name></person-group><article-title>Factors engaging users of diabetes social media channels on Facebook, Twitter, and Instagram: observational study</article-title><source>J Med Internet Res</source><year>2020</year><month>09</month><day>29</day><volume>22</volume><issue>9</issue><fpage>e21204</fpage><pub-id pub-id-type="doi">10.2196/21204</pub-id><pub-id pub-id-type="medline">32990632</pub-id></nlm-citation></ref><ref id="ref7"><label>7</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Loh</surname><given-names>YL</given-names> </name><name name-style="western"><surname>Yaw</surname><given-names>QP</given-names> </name><name name-style="western"><surname>Lau</surname><given-names>Y</given-names> </name></person-group><article-title>Social media-based interventions for adults with obesity and overweight: a meta-analysis and meta-regression</article-title><source>Int J Obes</source><year>2023</year><month>07</month><volume>47</volume><issue>7</issue><fpage>606</fpage><lpage>621</lpage><pub-id pub-id-type="doi">10.1038/s41366-023-01304-6</pub-id></nlm-citation></ref><ref id="ref8"><label>8</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Goodyear</surname><given-names>VA</given-names> </name><name name-style="western"><surname>Boardley</surname><given-names>I</given-names> </name><name name-style="western"><surname>Chiou</surname><given-names>SY</given-names> </name><etal/></person-group><article-title>Social media use informing behaviours related to physical activity, diet and quality of life during COVID-19: a mixed methods study</article-title><source>BMC Public Health</source><year>2021</year><month>07</month><day>6</day><volume>21</volume><issue>1</issue><fpage>1333</fpage><pub-id pub-id-type="doi">10.1186/s12889-021-11398-0</pub-id><pub-id pub-id-type="medline">34229651</pub-id></nlm-citation></ref><ref id="ref9"><label>9</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Noetel</surname><given-names>M</given-names> </name><name name-style="western"><surname>Griffith</surname><given-names>S</given-names> </name><name name-style="western"><surname>Delaney</surname><given-names>O</given-names> </name><etal/></person-group><article-title>Video improves learning in higher education: a systematic review</article-title><source>Rev Educ Res</source><year>2021</year><month>04</month><volume>91</volume><issue>2</issue><fpage>204</fpage><lpage>236</lpage><pub-id pub-id-type="doi">10.3102/0034654321990713</pub-id></nlm-citation></ref><ref id="ref10"><label>10</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Suarez-Lledo</surname><given-names>V</given-names> </name><name name-style="western"><surname>Alvarez-Galvez</surname><given-names>J</given-names> </name></person-group><article-title>Prevalence of health misinformation on social media: systematic review</article-title><source>J Med Internet Res</source><year>2021</year><month>01</month><day>20</day><volume>23</volume><issue>1</issue><fpage>e17187</fpage><pub-id pub-id-type="doi">10.2196/17187</pub-id><pub-id pub-id-type="medline">33470931</pub-id></nlm-citation></ref><ref id="ref11"><label>11</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Vosoughi</surname><given-names>S</given-names> </name><name name-style="western"><surname>Roy</surname><given-names>D</given-names> </name><name name-style="western"><surname>Aral</surname><given-names>S</given-names> </name></person-group><article-title>The spread of true and false news online</article-title><source>Science</source><year>2018</year><month>03</month><day>9</day><volume>359</volume><issue>6380</issue><fpage>1146</fpage><lpage>1151</lpage><pub-id pub-id-type="doi">10.1126/science.aap9559</pub-id><pub-id pub-id-type="medline">29590045</pub-id></nlm-citation></ref><ref id="ref12"><label>12</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Bizzotto</surname><given-names>N</given-names> </name><name name-style="western"><surname>de Bruijn</surname><given-names>GJ</given-names> </name><name name-style="western"><surname>Schulz</surname><given-names>PJ</given-names> </name></person-group><article-title>Buffering against exposure to mental health misinformation in online communities on Facebook: the interplay of depression literacy and expert moderation</article-title><source>BMC Public Health</source><year>2023</year><month>08</month><day>18</day><volume>23</volume><issue>1</issue><fpage>1577</fpage><pub-id pub-id-type="doi">10.1186/s12889-023-16404-1</pub-id><pub-id pub-id-type="medline">37596592</pub-id></nlm-citation></ref><ref id="ref13"><label>13</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Thapa</surname><given-names>DK</given-names> </name><name name-style="western"><surname>Visentin</surname><given-names>DC</given-names> </name><name name-style="western"><surname>Kornhaber</surname><given-names>R</given-names> </name><name name-style="western"><surname>West</surname><given-names>S</given-names> </name><name name-style="western"><surname>Cleary</surname><given-names>M</given-names> </name></person-group><article-title>The influence of online health information on health decisions: a systematic review</article-title><source>Patient Educ Couns</source><year>2021</year><month>04</month><volume>104</volume><issue>4</issue><fpage>770</fpage><lpage>784</lpage><pub-id pub-id-type="doi">10.1016/j.pec.2020.11.016</pub-id><pub-id pub-id-type="medline">33358253</pub-id></nlm-citation></ref><ref id="ref14"><label>14</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Helming</surname><given-names>AG</given-names> </name><name name-style="western"><surname>Adler</surname><given-names>DS</given-names> </name><name name-style="western"><surname>Keltner</surname><given-names>C</given-names> </name><name name-style="western"><surname>Igelman</surname><given-names>AD</given-names> </name><name name-style="western"><surname>Woodworth</surname><given-names>GE</given-names> </name></person-group><article-title>The content quality of YouTube videos for professional medical education: a systematic review</article-title><source>Acad Med</source><year>2021</year><month>10</month><day>1</day><volume>96</volume><issue>10</issue><fpage>1484</fpage><lpage>1493</lpage><pub-id pub-id-type="doi">10.1097/ACM.0000000000004121</pub-id><pub-id pub-id-type="medline">33856363</pub-id></nlm-citation></ref><ref id="ref15"><label>15</label><nlm-citation citation-type="book"><person-group person-group-type="author"><name name-style="western"><surname>Charnock</surname><given-names>D</given-names> </name></person-group><source>The DISCERN Handbook: Quality Criteria for Consumer Health Information on Treatment Choices</source><year>1998</year><publisher-name>Radcliffe Medical</publisher-name><pub-id pub-id-type="other">1857753100</pub-id></nlm-citation></ref><ref id="ref16"><label>16</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Silberg</surname><given-names>WM</given-names> </name><name name-style="western"><surname>Lundberg</surname><given-names>GD</given-names> </name><name name-style="western"><surname>Musacchio</surname><given-names>RA</given-names> </name></person-group><article-title>Assessing, controlling, and assuring the quality of medical information on the internet: Caveant lector et viewor--let the reader and viewer beware</article-title><source>JAMA</source><year>1997</year><month>04</month><day>16</day><volume>277</volume><issue>15</issue><fpage>1244</fpage><lpage>1245</lpage><pub-id pub-id-type="medline">9103351</pub-id></nlm-citation></ref><ref id="ref17"><label>17</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Boyer</surname><given-names>C</given-names> </name><name name-style="western"><surname>Selby</surname><given-names>M</given-names> </name><name name-style="western"><surname>Appel</surname><given-names>RD</given-names> </name></person-group><article-title>The Health On the Net Code of Conduct for medical and health web sites</article-title><source>Stud Health Technol Inform</source><year>1998</year><volume>52 Pt 2</volume><fpage>1163</fpage><lpage>1166</lpage><pub-id pub-id-type="medline">10384641</pub-id></nlm-citation></ref><ref id="ref18"><label>18</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Azer</surname><given-names>SA</given-names> </name></person-group><article-title>Are DISCERN and JAMA suitable instruments for assessing YouTube videos on thyroid cancer? Methodological concerns</article-title><source>J Cancer Educ</source><year>2020</year><month>12</month><volume>35</volume><issue>6</issue><fpage>1267</fpage><lpage>1277</lpage><pub-id pub-id-type="doi">10.1007/s13187-020-01763-9</pub-id><pub-id pub-id-type="medline">32472374</pub-id></nlm-citation></ref><ref id="ref19"><label>19</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Shoemaker</surname><given-names>SJ</given-names> </name><name name-style="western"><surname>Wolf</surname><given-names>MS</given-names> </name><name name-style="western"><surname>Brach</surname><given-names>C</given-names> </name></person-group><article-title>Development of the Patient Education Materials Assessment Tool (PEMAT): a new measure of understandability and actionability for print and audiovisual patient information</article-title><source>Patient Educ Couns</source><year>2014</year><month>09</month><volume>96</volume><issue>3</issue><fpage>395</fpage><lpage>403</lpage><pub-id pub-id-type="doi">10.1016/j.pec.2014.05.027</pub-id><pub-id pub-id-type="medline">24973195</pub-id></nlm-citation></ref><ref id="ref20"><label>20</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Huang</surname><given-names>MM</given-names> </name><name name-style="western"><surname>Winoker</surname><given-names>JS</given-names> </name><name name-style="western"><surname>Allaf</surname><given-names>ME</given-names> </name><name name-style="western"><surname>Matlaga</surname><given-names>BR</given-names> </name><name name-style="western"><surname>Koo</surname><given-names>K</given-names> </name></person-group><article-title>Evidence-based quality and accuracy of YouTube videos about nephrolithiasis</article-title><source>BJU Int</source><year>2021</year><month>02</month><volume>127</volume><issue>2</issue><fpage>247</fpage><lpage>253</lpage><pub-id pub-id-type="doi">10.1111/bju.15213</pub-id><pub-id pub-id-type="medline">32805761</pub-id></nlm-citation></ref><ref id="ref21"><label>21</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Charnock</surname><given-names>D</given-names> </name><name name-style="western"><surname>Shepperd</surname><given-names>S</given-names> </name><name name-style="western"><surname>Needham</surname><given-names>G</given-names> </name><name name-style="western"><surname>Gann</surname><given-names>R</given-names> </name></person-group><article-title>DISCERN: an instrument for judging the quality of written consumer health information on treatment choices</article-title><source>J Epidemiol Community Health</source><year>1999</year><month>02</month><volume>53</volume><issue>2</issue><fpage>105</fpage><lpage>111</lpage><pub-id pub-id-type="doi">10.1136/jech.53.2.105</pub-id><pub-id pub-id-type="medline">10396471</pub-id></nlm-citation></ref><ref id="ref22"><label>22</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Cortes Cavalcante</surname><given-names>J</given-names> </name><name name-style="western"><surname>Faria Sales</surname><given-names>M</given-names> </name><name name-style="western"><surname>Sousa Junior</surname><given-names>R de</given-names> </name><etal/></person-group><article-title>Analysis of the Brazilian-Portuguese content on autism spectrum disorder available on YouTube videos</article-title><source>Phys Occup Ther Pediatr</source><year>2024</year><volume>44</volume><issue>1</issue><fpage>128</fpage><lpage>142</lpage><pub-id pub-id-type="doi">10.1080/01942638.2023.2199843</pub-id><pub-id pub-id-type="medline">37069791</pub-id></nlm-citation></ref><ref id="ref23"><label>23</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Fat</surname><given-names>MJL</given-names> </name><name name-style="western"><surname>Doja</surname><given-names>A</given-names> </name><name name-style="western"><surname>Barrowman</surname><given-names>N</given-names> </name><name name-style="western"><surname>Sell</surname><given-names>E</given-names> </name></person-group><article-title>YouTube videos as a teaching tool and patient resource for infantile spasms</article-title><source>J Child Neurol</source><year>2011</year><month>07</month><volume>26</volume><issue>7</issue><fpage>804</fpage><lpage>809</lpage><pub-id pub-id-type="doi">10.1177/0883073811402345</pub-id><pub-id pub-id-type="medline">21551373</pub-id></nlm-citation></ref><ref id="ref24"><label>24</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Wei</surname><given-names>H</given-names> </name><name name-style="western"><surname>Chen</surname><given-names>J</given-names> </name><name name-style="western"><surname>Gan</surname><given-names>X</given-names> </name><name name-style="western"><surname>Liang</surname><given-names>Z</given-names> </name></person-group><article-title>Eight-element communication model for internet health rumors: a new exploration of Lasswell&#x2019;s &#x201C;5W communication model&#x201D;</article-title><source>Healthcare (Basel)</source><year>2022</year><month>12</month><day>11</day><volume>10</volume><issue>12</issue><fpage>2507</fpage><pub-id pub-id-type="doi">10.3390/healthcare10122507</pub-id><pub-id pub-id-type="medline">36554031</pub-id></nlm-citation></ref><ref id="ref25"><label>25</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Peng</surname><given-names>W</given-names> </name></person-group><article-title>Analysis of new media communication based on Lasswell&#x2019;s &#x201C;5W&#x201D; model</article-title><source>Model Journal of Educational and Social Research</source><year>2015</year><access-date>2025-09-11</access-date><volume>5</volume><fpage>245</fpage><comment><ext-link ext-link-type="uri" xlink:href="https://www.richtmann.org/journal/index.php/jesr/article/view/7723">https://www.richtmann.org/journal/index.php/jesr/article/view/7723</ext-link></comment></nlm-citation></ref><ref id="ref26"><label>26</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Liberatore</surname><given-names>MJ</given-names> </name><name name-style="western"><surname>Nydick</surname><given-names>RL</given-names> </name></person-group><article-title>The analytic hierarchy process in medical and health care decision making: a literature review</article-title><source>Eur J Oper Res</source><year>2008</year><month>08</month><volume>189</volume><issue>1</issue><fpage>194</fpage><lpage>207</lpage><pub-id pub-id-type="doi">10.1016/j.ejor.2007.05.001</pub-id></nlm-citation></ref><ref id="ref27"><label>27</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Gagnier</surname><given-names>JJ</given-names> </name><name name-style="western"><surname>de Arruda</surname><given-names>GT</given-names> </name><name name-style="western"><surname>Terwee</surname><given-names>CB</given-names> </name><name name-style="western"><surname>Mokkink</surname><given-names>LB</given-names> </name><collab>Consensus group</collab></person-group><article-title>COSMIN reporting guideline for studies on measurement properties of patient&#x2011;reported outcome measures: version 2.0</article-title><source>Qual Life Res</source><year>2025</year><month>07</month><volume>34</volume><issue>7</issue><fpage>1901</fpage><lpage>1911</lpage><pub-id pub-id-type="doi">10.1007/s11136-025-03950-x</pub-id><pub-id pub-id-type="medline">40153128</pub-id></nlm-citation></ref><ref id="ref28"><label>28</label><nlm-citation citation-type="journal"><article-title>Consensus development methods, and their use in clinical guideline development</article-title><source>Health Technol Assess</source><year>1998</year><volume>2</volume><issue>3</issue><fpage>1</fpage><lpage>88</lpage><pub-id pub-id-type="doi">10.3310/hta2030</pub-id></nlm-citation></ref><ref id="ref29"><label>29</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Nair</surname><given-names>R</given-names> </name><name name-style="western"><surname>Aggarwal</surname><given-names>R</given-names> </name><name name-style="western"><surname>Khanna</surname><given-names>D</given-names> </name></person-group><article-title>Methods of formal consensus in classification/diagnostic criteria and guideline development</article-title><source>Semin Arthritis Rheum</source><year>2011</year><month>10</month><volume>41</volume><issue>2</issue><fpage>95</fpage><lpage>105</lpage><pub-id pub-id-type="doi">10.1016/j.semarthrit.2010.12.001</pub-id><pub-id pub-id-type="medline">21420149</pub-id></nlm-citation></ref><ref id="ref30"><label>30</label><nlm-citation citation-type="book"><person-group person-group-type="editor"><name name-style="western"><surname>Saaty</surname><given-names>TL</given-names> </name></person-group><source>Theory and Applications of the Analytic Network Process: Decision Making With Benefits, Opportunities, Costs, and Risks</source><year>2005</year><publisher-name>RWS Publications</publisher-name></nlm-citation></ref><ref id="ref31"><label>31</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Forman</surname><given-names>EH</given-names> </name><name name-style="western"><surname>Gass</surname><given-names>SI</given-names> </name></person-group><article-title>The analytic hierarchy process&#x2014;an exposition</article-title><source>Oper Res</source><year>2001</year><month>08</month><volume>49</volume><issue>4</issue><fpage>469</fpage><lpage>486</lpage><pub-id pub-id-type="doi">10.1287/opre.49.4.469.11231</pub-id></nlm-citation></ref><ref id="ref32"><label>32</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Polit</surname><given-names>DF</given-names> </name><name name-style="western"><surname>Beck</surname><given-names>CT</given-names> </name><name name-style="western"><surname>Owen</surname><given-names>SV</given-names> </name></person-group><article-title>Is the CVI an acceptable indicator of content validity? Appraisal and recommendations</article-title><source>Res Nurs Health</source><year>2007</year><month>08</month><volume>30</volume><issue>4</issue><fpage>459</fpage><lpage>467</lpage><pub-id pub-id-type="doi">10.1002/nur.20199</pub-id><pub-id pub-id-type="medline">17654487</pub-id></nlm-citation></ref><ref id="ref33"><label>33</label><nlm-citation citation-type="book"><person-group person-group-type="author"><name name-style="western"><surname>Rubin</surname><given-names>RB</given-names> </name><name name-style="western"><surname>Palmgreen</surname><given-names>P</given-names> </name><name name-style="western"><surname>Sypher</surname><given-names>HE</given-names> </name></person-group><source>Communication Research Measures</source><year>2020</year><publisher-name>Routledge</publisher-name><pub-id pub-id-type="doi">10.4324/9781003064343</pub-id></nlm-citation></ref><ref id="ref34"><label>34</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Zhao</surname><given-names>SS</given-names> </name><name name-style="western"><surname>Zhang</surname><given-names>BQ</given-names> </name><name name-style="western"><surname>Chang</surname><given-names>XH</given-names> </name></person-group><article-title>iQiYi video as a source of information on COVID-19 vaccine: content analysis</article-title><source>Disaster Med Public Health Prep</source><year>2023</year><volume>17</volume><pub-id pub-id-type="doi">10.1017/dmp.2022.57</pub-id></nlm-citation></ref><ref id="ref35"><label>35</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Shawahna</surname><given-names>R</given-names> </name></person-group><article-title>Facilitating ethical, legal, and professional deliberations to resolve dilemmas in daily healthcare practice: a case of driver with breakthrough seizures</article-title><source>Epilepsy Behav</source><year>2020</year><month>01</month><volume>102</volume><fpage>106703</fpage><pub-id pub-id-type="doi">10.1016/j.yebeh.2019.106703</pub-id></nlm-citation></ref><ref id="ref36"><label>36</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Hong</surname><given-names>CY</given-names> </name><name name-style="western"><surname>Chung</surname><given-names>ES</given-names> </name><name name-style="western"><surname>Chang</surname><given-names>H</given-names> </name></person-group><article-title>The right to urban streams: quantitative comparisons of stakeholder perceptions in defining adaptive stream restoration</article-title><source>Sustainability</source><year>2020</year><volume>12</volume><issue>22</issue><fpage>9500</fpage><pub-id pub-id-type="doi">10.3390/su12229500</pub-id></nlm-citation></ref><ref id="ref37"><label>37</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Saaty</surname><given-names>RW</given-names> </name></person-group><article-title>The analytic hierarchy process&#x2014;what it is and how it is used</article-title><source>Mathematical Modelling</source><year>1987</year><volume>9</volume><issue>3-5</issue><fpage>161</fpage><lpage>176</lpage><pub-id pub-id-type="doi">10.1016/0270-0255(87)90473-8</pub-id></nlm-citation></ref><ref id="ref38"><label>38</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>McQuail</surname><given-names>D</given-names> </name></person-group><article-title>Sociology of Mass Communication</article-title><source>Annu Rev Sociol</source><year>1985</year><month>01</month><day>1</day><volume>11</volume><issue>1</issue><fpage>93</fpage><lpage>111</lpage><pub-id pub-id-type="doi">10.1146/annurev.soc.11.1.93</pub-id></nlm-citation></ref><ref id="ref39"><label>39</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Sapienza</surname><given-names>ZS</given-names> </name><name name-style="western"><surname>Iyer</surname><given-names>N</given-names> </name><name name-style="western"><surname>Veenstra</surname><given-names>AS</given-names> </name></person-group><article-title>Reading Lasswell&#x2019;s model of communication backward: three scholarly misconceptions</article-title><source>Mass Communication and Society</source><year>2015</year><month>09</month><day>3</day><volume>18</volume><issue>5</issue><fpage>599</fpage><lpage>622</lpage><pub-id pub-id-type="doi">10.1080/15205436.2015.1063666</pub-id></nlm-citation></ref><ref id="ref40"><label>40</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Xu</surname><given-names>X</given-names> </name><name name-style="western"><surname>Wang</surname><given-names>Z</given-names> </name><name name-style="western"><surname>Li</surname><given-names>X</given-names> </name><etal/></person-group><article-title>Acceptance and needs of medication literacy education among children by their caregivers: a multicenter study in mainland China</article-title><source>Front Pharmacol</source><year>2022</year><volume>13</volume><fpage>963251</fpage><pub-id pub-id-type="doi">10.3389/fphar.2022.963251</pub-id><pub-id pub-id-type="medline">36176431</pub-id></nlm-citation></ref><ref id="ref41"><label>41</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Bengi</surname><given-names>VU</given-names> </name><name name-style="western"><surname>Sara&#x00E7; Atag&#x00FC;n</surname><given-names>&#x00D6;</given-names> </name><name name-style="western"><surname>Ceylan &#x015E;en</surname><given-names>S</given-names> </name><name name-style="western"><surname>&#x00D6;zcan</surname><given-names>E</given-names> </name><name name-style="western"><surname>Paksoy</surname><given-names>T</given-names> </name><name name-style="western"><surname>G&#x00FC;ler</surname><given-names>&#x00D6;&#x015E;</given-names> </name></person-group><article-title>How much information regarding gingival enlargement can we get from TikTok and YouTube?</article-title><source>Spec Care Dentist</source><year>2024</year><volume>44</volume><issue>4</issue><fpage>1115</fpage><lpage>1125</lpage><pub-id pub-id-type="doi">10.1111/scd.12957</pub-id><pub-id pub-id-type="medline">38177079</pub-id></nlm-citation></ref><ref id="ref42"><label>42</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Tan</surname><given-names>Y</given-names> </name><name name-style="western"><surname>Geng</surname><given-names>S</given-names> </name><name name-style="western"><surname>Chen</surname><given-names>L</given-names> </name><name name-style="western"><surname>Wu</surname><given-names>L</given-names> </name></person-group><article-title>How doctor image features engage health science short video viewers? Investigating the age and gender bias</article-title><source>IMDS</source><year>2023</year><month>08</month><day>29</day><volume>123</volume><issue>9</issue><fpage>2319</fpage><lpage>2348</lpage><pub-id pub-id-type="doi">10.1108/IMDS-08-2022-0510</pub-id></nlm-citation></ref><ref id="ref43"><label>43</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Zha</surname><given-names>X</given-names> </name><name name-style="western"><surname>Yang</surname><given-names>H</given-names> </name><name name-style="western"><surname>Yan</surname><given-names>Y</given-names> </name><name name-style="western"><surname>Liu</surname><given-names>K</given-names> </name><name name-style="western"><surname>Huang</surname><given-names>C</given-names> </name></person-group><article-title>Exploring the effect of social media information quality, source credibility and reputation on informational fit-to-task: Moderating role of focused immersion</article-title><source>Comput Human Behav</source><year>2018</year><month>02</month><volume>79</volume><fpage>227</fpage><lpage>237</lpage><pub-id pub-id-type="doi">10.1016/j.chb.2017.10.038</pub-id></nlm-citation></ref><ref id="ref44"><label>44</label><nlm-citation citation-type="web"><article-title>CDC Clear Communication Index: a tool for developing and assessing CDC public communication products</article-title><source>Centers for Disease Control and Prevention</source><year>2019</year><access-date>2025-09-12</access-date><comment><ext-link ext-link-type="uri" xlink:href="https://www.cdc.gov/ccindex/index.html">https://www.cdc.gov/ccindex/index.html</ext-link></comment></nlm-citation></ref><ref id="ref45"><label>45</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Erdem</surname><given-names>MN</given-names> </name><name name-style="western"><surname>Karaca</surname><given-names>S</given-names> </name></person-group><article-title>Evaluating the accuracy and quality of the information in kyphosis videos shared on YouTube</article-title><source>Spine (Phila Pa 1976)</source><year>2018</year><month>11</month><day>15</day><volume>43</volume><issue>22</issue><fpage>E1334</fpage><lpage>E1339</lpage><pub-id pub-id-type="doi">10.1097/BRS.0000000000002691</pub-id><pub-id pub-id-type="medline">29664816</pub-id></nlm-citation></ref><ref id="ref46"><label>46</label><nlm-citation citation-type="report"><article-title>How to develop products for adults with intellectual developmental disabilities and extreme low literacy: a product development tool</article-title><year>2023</year><access-date>2025-09-11</access-date><publisher-name>Centers for Disease Control and Prevention</publisher-name><comment><ext-link ext-link-type="uri" xlink:href="https://www.cdc.gov/ccindex/pdf/idd-ell-product-development-tool-508.pdf">https://www.cdc.gov/ccindex/pdf/idd-ell-product-development-tool-508.pdf</ext-link></comment></nlm-citation></ref><ref id="ref47"><label>47</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Sui</surname><given-names>Y</given-names> </name><name name-style="western"><surname>Zhang</surname><given-names>B</given-names> </name></person-group><article-title>Determinants of the perceived credibility of rebuttals concerning health misinformation</article-title><source>Int J Environ Res Public Health</source><year>2021</year><month>02</month><day>2</day><volume>18</volume><issue>3</issue><fpage>1345</fpage><pub-id pub-id-type="doi">10.3390/ijerph18031345</pub-id><pub-id pub-id-type="medline">33540869</pub-id></nlm-citation></ref><ref id="ref48"><label>48</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Humphrey-Murto</surname><given-names>S</given-names> </name><name name-style="western"><surname>Varpio</surname><given-names>L</given-names> </name><name name-style="western"><surname>Wood</surname><given-names>TJ</given-names> </name><etal/></person-group><article-title>The use of the Delphi and other consensus group methods in medical education research: a review</article-title><source>Acad Med</source><year>2017</year><month>10</month><volume>92</volume><issue>10</issue><fpage>1491</fpage><lpage>1498</lpage><pub-id pub-id-type="doi">10.1097/ACM.0000000000001812</pub-id><pub-id pub-id-type="medline">28678098</pub-id></nlm-citation></ref><ref id="ref49"><label>49</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Black</surname><given-names>N</given-names> </name><name name-style="western"><surname>Murphy</surname><given-names>M</given-names> </name><name name-style="western"><surname>Lamping</surname><given-names>D</given-names> </name><etal/></person-group><article-title>Consensus development methods: a review of best practice in creating clinical guidelines</article-title><source>J Health Serv Res Policy</source><year>1999</year><month>10</month><volume>4</volume><issue>4</issue><fpage>236</fpage><lpage>248</lpage><pub-id pub-id-type="doi">10.1177/135581969900400410</pub-id><pub-id pub-id-type="medline">10623041</pub-id></nlm-citation></ref></ref-list><app-group><supplementary-material id="app1"><label>Multimedia Appendix 1</label><p>Materials related to the development and validation of the Lasswell&#x2019;s Video Quality scale (LassVQ) evaluation system.</p><media xlink:href="jmir_v27i1e72661_app1.docx" xlink:title="DOCX File, 277 KB"/></supplementary-material><supplementary-material id="app2"><label>Checklist 1</label><p>COSMIN checklist.</p><media xlink:href="jmir_v27i1e72661_app2.docx" xlink:title="DOCX File, 21 KB"/></supplementary-material></app-group></back></article>