bims-librar Biomed News on Biomedical librarianship
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Issue of 2021‒06‒20 │
sixteen papers selected by │
Thomas Krichel (Open Library │
Society) │
http://e.biomed.news/librar │
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1. Search Engine Gender Bias.
2. Online Interactive Platform for COVID-19 Literature Visual Analytics.
3. Quality of web-based information at the beginning of a global
pandemic: a cross-sectional infodemiology study investigating preventive
measures and self care methods of the coronavirus disease 2019.
4. Automation of Article Selection Process in Systematic Reviews Through
Artificial Neural Network Modeling and Machine Learning: Protocol for an
Article Selection Model.
5. Structured critical analysis correction of a systematic review.
6. Enhancing Knowledge Graph Extraction and Validation From Scholarly
Publications Using Bibliographic Metadata.
7. ONLINE INFORMATION ABOUT THE EFFECTIVENESS OF SHOULDER SURGERY IS NOT
EVIDENCE-BASED: A CONTENT ANALYSIS.
8. Evaluation of clustering and topic modeling methods over
health-related tweets and emails.
9. Factors Associated with Cancer Message Believability: a Mixed Methods
Study on Simulated Facebook Posts.
10. Febrile seizure: What information can caregivers access through
YouTube?
11. Readability of the Most Commonly Accessed Online Patient Education
Materials Pertaining to Surgical Treatments of the Spine.
12. Dietary and herbal supplements for fatigue: A quality assessment of
online consumer health information.
13. Quality of Online Information Regarding High-Risk Pregnancies.
14. A Quality Assessment of YouTube Content on Shoulder Instability.
15. Effect of a Consumer-Focused Website for Low Back Pain on Health
Literacy, Treatment Choices, and Clinical Outcomes: Randomized Controlled
Trial.
16. Food for thought: A natural language processing analysis of the 2020
Dietary Guidelines publice comments.
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Front Big Data. 2021 ;4 622106
1. Search Engine Gender Bias.
Wijnhoven F, van Haren J
This article discusses possible search engine page rank biases as a
consequence of search engine profile information. After describing search
engine biases, their causes, and their ethical implications, we present data
about the Google search engine (GSE) and DuckDuckGo (DDG) for which only the
first uses profile data for the production of page ranks. We analyze 408
search engine screen prints of 102 volunteers (53 male and 49 female) on
queries for job search and political participation. For job searches via
GSE, we find a bias toward stereotypically "female" jobs for women but also
for men, although the bias is significantly stronger for women. For
political participation, the bias of GSE is toward more powerful positions.
Contrary to our hypothesis, this bias is even stronger for women than for
men. Our analysis of DDG does not give statistically significant page rank
differences for male and female users. We, therefore, conclude that GSE's
personal profiling is not reinforcing a gender stereotype. Although no
gender differences in page ranks was found for DDG, DDG usage in general
gave a bias toward "male-dominant" vacancies for both men and women. We,
therefore, believe that search engine page ranks are not biased by profile
ranking algorithms, but that page rank biases may be caused by many other
factors in the search engine's value chain. We propose ten search engine
bias factors with virtue ethical implications for further research.
Keywords: DuckDuckGo; Google; filter bubble; gender bias; job search;
personalization; political participation search
DOI: https://doi.org/10.3389/fdata.2021.622106
URL: http://pubmed.ncbi.nlm.nih.gov/34124651
J Med Internet Res. 2021 Jun 12.
2. Online Interactive Platform for COVID-19 Literature Visual Analytics.
Moran A, Hampton S, Dowson S, Dagdelen J, Trewartha A, Ceder G, Persson K,
Saxon E, Barker A, Charles L, Webb-Robertson BJ
BACKGROUND: The rate of publication of COVID-19 literature is astonishing
and the research is extremely varied. Innovative tools are needed to aid
researchers to find patterns in this vast amount of literature to identify
subsets of interest in an automated fashion.
OBJECTIVE: We present a new online software resource with a friendly user
interface that allow users to query and interact with visual representations
of relationships between publications.
METHODS: We publicly released an application called PLATIPUS (Publication
Literature Analysis and Text Interaction Platform for User Studies) that
allows researchers to interact with literature supplied by COVIDScholar via
a visual analytics platform. This tool contains standard filtering
capabilities based on authors, journals, high-level categories, and various
research-specific details via natural language processing and dozens of
customizable visualizations that dynamically update from a researcher's
query.
RESULTS: PLATIPUS is available at https://vcs.pnnl.gov/ and currently links
to over hundreds of thousands of publications and still growing. This
application has the potential to transform how COVID-19 researchers utilize
public literature to enable their research.
CONCLUSIONS: The PLATIPUS application provides the end-user with a variety
of ways to search, filter and visualize over one hundred thousand COVID-19
publications.
CLINICALTRIAL:
DOI: https://doi.org/10.2196/26995
URL: http://pubmed.ncbi.nlm.nih.gov/34138726
BMC Public Health. 2021 06 14. 21(1): 1141
3. Quality of web-based information at the beginning of a global
pandemic: a cross-sectional infodemiology study investigating preventive
measures and self care methods of the coronavirus disease 2019.
Stern J, Georgsson S, Carlsson T
BACKGROUND: reducing the spread and impact epidemics and pandemics requires
that members of the general population change their behaviors according to
the recommendations, restrictions and laws provided by leading authorities.
When a new epidemic or pandemic emerges, people are faced with the challenge
of sorting through a great volume of varied information. Therefore, the
dissemination of high-quality web-based information is essential during this
time period. The overarching aim was to investigate the quality of web-based
information about preventive measures and self care methods at the beginning
of the COVID-19 pandemic.
METHODS: in May 2020, consumer-oriented websites written in Swedish were
identified via systematic searches in Google (n = 76). Websites were
assessed with inductive content analysis, the JAMA benchmarks, the QUEST
tool and the DISCERN instrument.
RESULTS: seven categories and 33 subcategories were identified concerning
preventive measures (md = 6.0 subcategories), with few specifying a method
for washing hands (n = 4), when to sanitize the hands (n = 4), and a method
for sanitizing the hands (n = 1). Eight categories and 30 subcategories were
identified concerning self care methods (md = 3.0 subcategories), with few
referring to the national number for telephone-based counseling (n = 20) and
an online symptom assessment tool (n = 16). Overall, the median total
quality scores were low (JAMA = 0/4, QUEST =13/28, DISCERN = 29/80).
CONCLUSIONS: at the beginning of the pandemic, substantial quality deficits
of websites about COVID-19 may have counteracted the public recommendations
for preventive measures. This illustrates a critical need for standardized
and systematic routines on how to achieve dissemination of high-quality
web-based information when new epidemics and pandemics emerge.
Keywords: COVID-19; Consumer health information; Primary prevention; Self
care; Severe acute respiratory syndrome coronavirus 2; World wide web
DOI: https://doi.org/10.1186/s12889-021-11141-9
URL: http://pubmed.ncbi.nlm.nih.gov/34126962
JMIR Res Protoc. 2021 Jun 15. 10(6): e26448
4. Automation of Article Selection Process in Systematic Reviews Through
Artificial Neural Network Modeling and Machine Learning: Protocol for an
Article Selection Model.
Ferreira GF, Quiles MG, Nazaré TS, Rezende SO, Demarzo M
BACKGROUND: A systematic review can be defined as a summary of the evidence
found in the literature via a systematic search in the available scientific
databases. One of the steps involved is article selection, which is
typically a laborious task. Machine learning and artificial intelligence can
be important tools in automating this step, thus aiding researchers.
OBJECTIVE: The aim of this study is to create models based on an artificial
neural network system to automate the article selection process in
systematic reviews related to "Mindfulness and Health Promotion."
METHODS: The study will be performed using Python programming software. The
system will consist of six main steps: (1) data import, (2) exclusion of
duplicates, (3) exclusion of non-articles, (4) article reading and model
creation using artificial neural network, (5) comparison of the models, and
(6) system sharing. We will choose the 10 most relevant systematic reviews
published in the fields of "Mindfulness and Health Promotion" and
"Orthopedics" (control group) to serve as a test of the effectiveness of the
article selection.
RESULTS: Data collection will begin in July 2021, with completion scheduled
for December 2021, and final publication available in March 2022.
CONCLUSIONS: An automated system with a modifiable sensitivity will be
created to select scientific articles in systematic review that can be
expanded to various fields. We will disseminate our results and models
through the "Observatory of Evidence" in public health, an open and online
platform that will assist researchers in systematic reviews.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/26448.
Keywords: deep learning; machine learning; mindfulness; systematic review
DOI: https://doi.org/10.2196/26448
URL: http://pubmed.ncbi.nlm.nih.gov/34128820
Cranio. 2021 Jun 16. 1-8
5. Structured critical analysis correction of a systematic review.
Solow R
OBJECTIVE: : Systematic reviews (SRs) are an increasingly important format
in the scientific literature. Commentaries on improvements to the SR format
have focused on methodological quality, but a greater concern is a frequent
lack of critical analysis. A structured critical analysis (SCA) was
described as a solution to this deficiency.
METHODS: : Recommendations and conclusions of a recent SR were analyzed with
a SCA to address common problems previously reported with the SR format.
RESULTS: : Errors in the component studies and their interpretation by the
SR that led to erroneous recommendations were presented. The 5-part SCA
provided comprehensive analysis that corrected the SR, which had accepted
the component study conclusions verbatim.
CONCLUSION: : The SCA is a logical approach to provide critical thinking in
SRs to ensure appropriate conclusions. This is especially important, as many
SRs report contradictory evidence. Also, the reader can use the SCA format
to better understand existing literature.
Keywords: Systematic review; component studies; meta-analysis;
methodological quality; occlusion; scientific merit; splints; structured
critical analysis
DOI: https://doi.org/10.1080/08869634.2021.1941541
URL: http://pubmed.ncbi.nlm.nih.gov/34132634
Front Res Metr Anal. 2021 ;6 694307
6. Enhancing Knowledge Graph Extraction and Validation From Scholarly
Publications Using Bibliographic Metadata.
Turki H, Hadj Taieb MA, Ben Aouicha M, Fraumann G, Hauschke C, Heller L
Keywords: bibliographic metadata; bibliometric-enhanced information
retrieval; data mining and knowledge discovery; information retrieval and
extraction; knowledge graph (ontologies)
DOI: https://doi.org/10.3389/frma.2021.694307
URL: http://pubmed.ncbi.nlm.nih.gov/34124535
Arch Phys Med Rehabil. 2021 Jun 12. pii: S0003-9993(21)00376-2.
7. ONLINE INFORMATION ABOUT THE EFFECTIVENESS OF SHOULDER SURGERY IS NOT
EVIDENCE-BASED: A CONTENT ANALYSIS.
Robertson A, Birch M, Harris IA, Buchbinder R, Ferreira G, O'Keeffe M,
Maher CG, Zadro JR
OBJECTIVE: To summarise the proportion of consumer webpages on subacromial
decompression and rotator cuff repair surgery that make an accurate
portrayal of the evidence for these surgeries (primary outcome), mention the
benefits and harms of surgery, outline alternatives to surgery, and make
various surgical recommendations.
DESIGN: Content analysis.
SETTING: Online consumer information about subacromial decompression and
rotator cuff repair surgery. Webpages were identified through (1) Google
searches using terms synonymous with 'shoulder pain' and 'shoulder surgery',
and searching 'orthopaedic surgeon' linked to each Australian capital city,
and (2) websites of relevant professional associations (e.g. Australian
Orthopaedic Association). Two reviewers independently identified webpages
and extracted data.
PARTICIPANTS: N/A INTERVENTION: N/A MAIN OUTCOME MEASURE: Whether the
webpage made an accurate portrayal of the evidence for subacromial
decompression or rotator cuff repair surgery (primary outcome), mentioned
benefits and harms of surgery, outlined alternatives to surgery, and made
various surgical recommendations (e.g. delay surgery). Outcome data were
summarised using counts and percentages.
RESULTS: 155 webpages were analysed (n=89 on subacromial decompression, n=90
on rotator cuff repair, n=24 on both). Only 18% (n=16) and 4% (n=4) of
webpages made an accurate portrayal of the evidence for subacromial
decompression and rotator cuff repair surgery, respectively. For subacromial
decompression and rotator cuff repair, respectively, 85% (n=76) and 80%
(n=72) of webpages mentioned benefits, 38% (n=34) and 47% (n=42) mentioned
harms, 94% (n=84) and 92% (n=83) provided alternatives to surgery, and 63%
(n=56) and 62% (n=56) recommended delayed surgery (the most common
recommendation).
CONCLUSION: Most online information about subacromial decompression and
rotator cuff repair surgery does not accurately portray the best available
evidence for surgery and may be inadequate to inform patient decision-making.
Keywords: Consumer resources; Rotator cuff repair; Shoulder surgery;
Subacromial decompression
DOI: https://doi.org/10.1016/j.apmr.2021.03.041
URL: http://pubmed.ncbi.nlm.nih.gov/34129832
Artif Intell Med. 2021 Jul;pii: S0933-3657(21)00089-0.
8. Evaluation of clustering and topic modeling methods over
health-related tweets and emails.
Lossio-Ventura JA, Gonzales S, Morzan J, Alatrista-Salas H,
Hernandez-Boussard T, Bian J
BACKGROUND: Internet provides different tools for communicating with
patients, such as social media (e.g., Twitter) and email platforms. These
platforms provided new data sources to shed lights on patient experiences
with health care and improve our understanding of patient-provider
communication. Several existing topic modeling and document clustering
methods have been adapted to analyze these new free-text data automatically.
However, both tweets and emails are often composed of short texts; and
existing topic modeling and clustering approaches have suboptimal
performance on these short texts. Moreover, research over health-related
short texts using these methods has become difficult to reproduce and
benchmark, partially due to the absence of a detailed comparison of
state-of-the-art topic modeling and clustering methods on these short texts.
METHODS: We trained eight state-of- the-art topic modeling and clustering
algorithms on short texts from two health-related datasets (tweets and
emails): Latent Semantic Indexing (LSI), Latent Dirichlet Allocation (LDA),
LDA with Gibbs Sampling (GibbsLDA), Online LDA, Biterm Model (BTM), Online
Twitter LDA, and Gibbs Sampling for Dirichlet Multinomial Mixture (GSDMM),
as well as the k-means clustering algorithm with two different feature
representations: TF-IDF and Doc2Vec. We used cluster validity indices to
evaluate the performance of topic modeling and clustering: two internal
indices (i.e. assessing the goodness of a clustering structure without
external information) and five external indices (i.e. comparing the results
of a cluster analysis to an externally known provided class labels).
RESULTS: In overall, for number of clusters (k) from 2 to 50, Online Twitter
LDA and GSDMM achieved the best performance in terms of internal indices,
while LSI and k-means with TF-IDF had the highest external indices. Also, of
all tweets (N = 286, 971; HPV represents 94.6% of tweets and lynch syndrome
represents 5.4%), for k = 2, most of the methods could respect this initial
clustering distribution. However, we found model performance varies with the
source of data and hyper-parameters such as the number of topics and the
number of iterations used to train the models. We also conducted an error
analysis using the Hamming loss metric, for which the poorest value was
obtained by GSDMM on both datasets.
CONCLUSIONS: Researchers hoping to group or classify health related
short-text data can expect to select the most suitable topic modeling and
clustering methods for their specific research questions. Therefore, we
presented a comparison of the most common used topic modeling and clustering
algorithms over two health-related, short-text datasets using both internal
and external clustering validation indices. Internal indices suggested
Online Twitter LDA and GSDMM as the best, while external indices suggested
LSI and k-means with TF-IDF as the best. In summary, our work suggested
researchers can improve their analysis of model performance by using a
variety of metrics, since there is not a single best metric.
Keywords: Clustering; External cluster indices; Internal cluster indices;
Natural language processing; Topic modeling
DOI: https://doi.org/10.1016/j.artmed.2021.102096
URL: http://pubmed.ncbi.nlm.nih.gov/34127235
J Cancer Educ. 2021 Jun 19.
9. Factors Associated with Cancer Message Believability: a Mixed Methods
Study on Simulated Facebook Posts.
Trivedi N, Lowry M, Gaysynsky A, Chou WS
The ability to share and obtain health information on social media (SM)
places higher burden on individuals to evaluate the believability of such
health messages given the growing nature of misinformation circulating on
SM. Message features (i.e., format, veracity), message source, and an
individual's health literacy all play significant roles in how a person
evaluates health messages on SM. This study assesses how message features
and SM users' health literacy predict assessment of message believability
and time spent looking at simulated Facebook messages. SM users (N = 53)
participated in a mixed methods experimental study, using eye-tracking
technology, to measure relative time and message believability. Measures
included individual health literacy, message format
(narrative/non-narrative), and information veracity
(evidence-based/non-evidence-based). Results showed individuals with
adequate health literacy rated evidence-based posts as more believable than
non-evidence-based posts. Additionally, individuals with limited health
literacy spent more relative time on the source compared to individuals with
adequate health literacy. Public health and health communication efforts
should focus on addressing myths and misinformation found on SM.
Additionally, the source of message may be equally important when evaluating
messages on SM, and strategies should identify reliable sources to prevent
limited health literate individuals from falling prey to misinformation.
Keywords: Eye-tracking; Health literacy; Social media
DOI: https://doi.org/10.1007/s13187-021-02054-7
URL: http://pubmed.ncbi.nlm.nih.gov/34145508
Seizure. 2021 Jun 01. pii: S1059-1311(21)00172-2.
10. Febrile seizure: What information can caregivers access through
YouTube?
Oh J, You SY
INTRODUCTION: To analyze the content of Korean YouTube videos related to
febrile seizures and examine the general characteristics, reliability, and
quality of the videos.
METHOD: A search of YouTube was performed using three Korean keywords
meaning "febrile seizure", and a total of 1,641 videos were identified.
Among them, 73 eligible videos were analyzed for their characteristics,
quality, and reliability. The quality and reliability were rated using
global quality (GQS) on a scale of 1-5 and the DISCERN instrument.
RESULTS: The mean reliability and quality scores were 2.37±1.16 and
3.11±1.17 out of 5, respectively. Fifty-one of the 73 (69.8%) videos are
related to febrile seizure management. Longer videos (13.94±20.06 vs
6.68±7.34) and videos with physicians (82.61% vs 32.00%) as the main speaker
were higher quality.
DISCUSSION: Both the quality and reliability of YouTube videos on febrile
seizures were relatively low, and approximately only 30% of all videos were
classified as high quality. Healthcare professionals should be aware that
there is misinformation and low-quality information on social media and warn
parents of this issue.
Keywords: Caregivers; Febrile seizure; Online information; Parents; Social
media
DOI: https://doi.org/10.1016/j.seizure.2021.05.020
URL: http://pubmed.ncbi.nlm.nih.gov/34130196
World Neurosurg. 2021 Jun 14. pii: S1878-8750(21)00835-4.
11. Readability of the Most Commonly Accessed Online Patient Education
Materials Pertaining to Surgical Treatments of the Spine.
Phan A, Jubril A, Menga E, Mesfin A
OBJECTIVE: The American Medical Association (AMA) and National Institutes of
Health (NIH) recommend that patient education materials should be written at
the sixth-grade reading level to maximize patient comprehension. The
objective of this study was to evaluate the readability of internet
information for the 9 most common spinal surgeries.
METHODS: Ninety online patient educational materials were reviewed regarding
the nine most common spinal surgeries as reported by the North American
Spine Society. A Google search was performed on March 23, 2019 for each
surgery, and the top 10 most visited websites for each surgery were assessed
for reading level using the Flesch-Kincaid formula.
RESULTS: Using the Flesch-Kincaid formula, the average grade reading level
of the 90 websites included was 12.82 with a reading ease of 37.04
("difficult college"). There were only 6 websites that relayed information
to patients at or below the national average of aneighth-grade reading
level. BMP had the highest average grade reading level at 15.88 (standard
deviation: 2.6). Lumbar microscopic discectomy had the lowest average grade
reading level at 10.37 (standard deviation: 2.89). All surgical options
discussed had an average readability above the recommended sixth-grade
reading level.
CONCLUSIONS: The most accessed online materials for common spinal surgeries
not only exceed the readability limits recommended by both the AMA and NIH,
but they also exceed the average reading ability of most adults in the
United States. Patients, therefore, may not fully comprehend commonly
accessed websites with information regarding surgical spine treatment
options.
Keywords: Cervical Spine; Flesch-Kincaid; Health Literacy; Patient
Education; Readability; Reading Level
DOI: https://doi.org/10.1016/j.wneu.2021.06.010
URL: http://pubmed.ncbi.nlm.nih.gov/34139351
Integr Med Res. 2021 Dec;10(4): 100749
12. Dietary and herbal supplements for fatigue: A quality assessment of
online consumer health information.
Ng JY, Zhang CJ, Ahmed S
Background: The Internet is increasingly utilized by patients to acquire
information about dietary and herbal supplements (DHSs). Previously
published studies assessing the quality of websites providing consumer
health information about DHSs have been found to contain inaccuracies and
misinformation that may compromise patient safety.. The present study
assessed the quality of online DHSs consumer health information for fatigue.
Methods: Six unique search terms were searched on Google, each relating to
fatigue and DHSs, across four countries. Across 480 websites identified, 48
were deemed eligible and were quality assessed using the DISCERN instrument,
a standardized index of the quality of consumer health information.
Results: Across 48 eligible websites, the mean summed score was 47.64
(SD = 10.38) and the mean overall rating was 3.06 (SD = 0.90). Commercial
sites were the most numerous in quantity, but contained information of the
poorest quality. In general, websites lacked discussion surrounding
uncertainty of information, describing what would happen if no treatment was
used, and how treatment choices affect overall quality of life.
Conclusion: Physicians and other healthcare professionals should be aware of
the high variability in the quality of online information regarding the use
of DHSs for fatigue and facilitate open communication with patients to guide
them towards reliable online sources.
Keywords: Consumer health information; DISCERN; Dietary and herbal
supplements; Fatigue; Quality of information
DOI: https://doi.org/10.1016/j.imr.2021.100749
URL: http://pubmed.ncbi.nlm.nih.gov/34141579
Comput Inform Nurs. 2021 Jun 16.
13. Quality of Online Information Regarding High-Risk Pregnancies.
Lee SY, Lee S
Health information on the Internet can have a direct effect on healthcare
decision-making. However, the quality of information online has seldom been
evaluated. This study aimed to assess the quality of online information on
high-risk pregnancies provided by English and Korean Web sites. Through a
Google search, 30 English and 30 Korean Web sites were selected on January 2
and 3, 2020, respectively, and assessed using DISCERN, a Journal of the
American Medical Association, and Health On the Net Foundation code
questionnaires. The data assessed were analyzed using descriptive and
nonparametric statistical tests. Overall, the information provided by the
English Web sites presented higher-quality information than the Korean Web
sites. Most Web sites did not provide the sources of the information
presented on their Web sites, meet the Journal of the American Medical
Association criteria, or provide information on complementarity. Based on
our results, nurses need to be competent in assessing the quality of Web
sites and the health information presented there, and nursing students need
to be prepared to do so as well. Nurses are responsible for educating their
patients about the possibility of incorrect information provided by Internet
Web sites and informing their patients about reliable Web sites, thus
assisting them to make informed decisions regarding their health.
DOI: https://doi.org/10.1097/CIN.0000000000000768
URL: http://pubmed.ncbi.nlm.nih.gov/34145205
Phys Sportsmed. 2021 Jun 12.
14. A Quality Assessment of YouTube Content on Shoulder Instability.
Etzel CM, Bokshan SL, Forster TS, Owens BD
OBJECTIVES: The Internet is a widely used resource for patients seeking
health information, yet little editing or regulations are imposed on posted
material. We sought to assess the quality and accuracy of information
presented on shoulder instability on the online video platform YouTube. We
hypothesize that YouTube videos concerning shoulder instability will be of
little quality, accuracy, and reliability.
METHODS: The first 50 YouTube videos resulting from the keyword query
"shoulder instability" were analyzed. The Journal of American Medical
Association (JAMA) benchmark criteria (score range, 0-5) was used to assess
video accuracy and reliability, and the Global Quality Score (GQS; score
range, 0-4) was used to assess the quality of the video's educational
content along with a generated Shoulder-Specific Score (SSS).
RESULTS: The 50 videos observed collectively had 5,007,486 views, with the
mean number of views being 100,149.72 ± 227,218.04. Of all videos observed,
32% were from a medical source and 56% had content relating to pathology
information. The mean JAMA score was 2.84 ± 0.74, with the highest scores
coming from academic sources. The mean GQS and SSS scores were 2.68 ± 0.84
and 5.30 ± 3.78. The mean GQS score was highest in videos from medical
sources (3.3 ± 0.8) and videos about surgical technique/approach (3.2 ±
1.1). Advertisements were negative predictors of the JAMA score (β = -0.324,
P = 0.014), and academic (β = 0.322, P = 0.015) and physician sources (β =
0.356, P = 0.008) were positive predictors.
CONCLUSION: YouTube videos on shoulder instability are of low quality and
accuracy and are not reliable. Care providers should be aware of the overall
low quality of information available on YouTube regarding shoulder
instability.
Keywords: Glenohumeral Instability; Quality Assessment; Shoulder; Shoulder
Instability; YouTube
DOI: https://doi.org/10.1080/00913847.2021.1942286
URL: http://pubmed.ncbi.nlm.nih.gov/34121601
J Med Internet Res. 2021 Jun 15. 23(6): e27860
15. Effect of a Consumer-Focused Website for Low Back Pain on Health
Literacy, Treatment Choices, and Clinical Outcomes: Randomized Controlled
Trial.
Hodges PW, Hall L, Setchell J, French S, Kasza J, Bennell K, Hunter D,
Vicenzino B, Crofts S, Dickson C, Ferreira M
BACKGROUND: The internet is used for information related to health
conditions, including low back pain (LBP), but most LBP websites provide
inaccurate information. Few studies have investigated the effectiveness of
internet resources in changing health literacy or treatment choices.
OBJECTIVE: This study aims to evaluate the effectiveness of the MyBackPain
website compared with unguided internet use on health literacy, choice of
treatments, and clinical outcomes in people with LBP.
METHODS: This was a pragmatic, web-based, participant- and assessor-blinded
randomized trial of individuals with LBP stratified by duration.
Participants were randomly allocated to have access to the evidence-based
MyBackPain website, which was designed with input from consumers and expert
consensus or unguided internet use. The coprimary outcomes were two
dimensions of the Health Literacy Questionnaire (dimension 2: "having
sufficient information to manage my health;" dimension 3: "actively managing
my health;" converted to scores 1-100) at 3 months. Secondary outcomes
included additional Health Literacy Questionnaire dimensions, quality of
treatment choices, and clinical outcomes.
RESULTS: A total of 453 participants were recruited, and 321 (70.9%)
completed the primary outcomes. Access to MyBackPain was not superior to
unguided internet use on primary outcomes (dimension 2: mean difference
-0.87 units, 95% CI -3.56 to 1.82; dimension 3: mean difference -0.41 units,
95% CI -2.78 to 1.96). Between-group differences in other secondary outcomes
had inconsistent directions and were unlikely to be clinically important,
although a small improvement of unclear importance in the quality of stated
treatment choices at 1 month was found (mean difference 0.93 units, 95% CI
0.03 to 1.84).
CONCLUSIONS: MyBackPain was not superior to unguided internet use for health
literacy, but data suggest some short-term improvement in treatment choices.
Future research should investigate if greater interactivity and engagement
with the website may enhance its impact.
TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR)
ACTRN12617001292369; https://www.anzctr.org.au/Trial/Registr
ation/TrialReview.aspx?id=372926.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):
RR2-10.1136/bmjopen-2018-027516.
Keywords: health literacy; internet resources; low back pain; randomized
controlled trial
DOI: https://doi.org/10.2196/27860
URL: http://pubmed.ncbi.nlm.nih.gov/34128822
Am J Clin Nutr. 2021 Jun 16. pii: nqab119. [Epub ahead of print]
16. Food for thought: A natural language processing analysis of the 2020
Dietary Guidelines publice comments.
Lindquist J, Thomas DM, Turner D, Blankenship J, Kyle TK
BACKGROUND: The Administrative Procedure Act of 1946 guarantees the public
an opportunity to view and comment on the 2020 Dietary Guidelines as part of
the policymaking process. In the past, public comments were submitted by
postal mail or public hearings. The convenience of public comment through
the Internet has generated increased comment volume, making manual analysis
challenging.
OBJECTIVES: To apply natural language processing (NLP NLP is natural
language processing.) to identify sentiment, emotion, and themes in the 2020
Dietary Guidelines public comments.
METHODS: Written comments to the Scientific Report of the 2020 Dietary
Guidelines Advisory Committee that were uploaded and visible at
https://beta.regulations.gov/docket/FNS-2020-0015 were extracted using a
computer program and retained for analysis. All comments were filtered, and
duplicates were removed. A 2-round latent Dirichlet analysis (LDA) was used
to identify 3 overarching topics as well as subtopics addressed in the
comments. Sentiment analysis was applied to categorize emotion and overall
positive and negative sentiment within each topic.
RESULTS: Three different topics were identified by LDA. The first topic
involved negative sentiment surrounding removing dairy from the guidelines
because the commenters felt dairy is unnecessary. The second topic focused
on positive sentiment involved in restricting added sugars. The third topic
was too diverse to characterize under 1 theme. A second LDA within the third
topic had 3 subtopics containing positive sentiment. The first subtopic
valued the inclusion of dairy in the recommendations, the second involved
the health benefits of consuming beef, and the third indicated that the
recommendations lead to overall good health outcomes.
CONCLUSIONS: Public comments were diverse, held conflicting viewpoints, and
often did not base comments on personal anecdotes or opinions without citing
scientific evidence. Because the volume of public comments has grown
dramatically, NLP has promise to assist in objective analysis of public
comment input.
Keywords: 2020 Dietary Guidelines; emotion; latent Dirichlet allocation;
machine learning; natural language processing; public comments; sentiment;
topic modeling
DOI: https://doi.org/10.1093/ajcn/nqab119
URL: http://pubmed.ncbi.nlm.nih.gov/34134135
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