Evidence map›Paper›PMID 36502490›Full record

ArticleJournal of community genetics2023

Lost in print: difficulty in reading online information pertaining to phenylketonuria.

Lalitha Samuel, Joseph Fera, Corey H Basch

Abstract read
In one paragraph

Article in Journal of community genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Lalitha SamuelDepartment of Health Promotion and Nutrition Sciences, Lehman College, The City University of New York, Bronx, NY, 10468, USA. Lalitha.Samuel@lehman.cuny.edu.
Joseph FeraDepartment of Mathematics, Lehman College, The City University of New York, Bronx, NY, 10468, USA.
Corey H BaschDepartment of Public Health, William Paterson University, Wayne, NJ, 07470, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Phenylketonuria (PKU) is the most prevalent inborn error of amino acid metabolism, necessitating patients to strictly restrict dietary phenylalanine. As this can be a confusing and concerning diagnosis, patients and loved ones will likely be drawn to learn more. A critical factor for citizens to harness the health-related digital information is to ensure that it is easy to read. This study assessed the readability of 100 digital articles related to PKU and explored the effect of the source of online information on the readability of these articles. For each article, 5 readability tests were conducted using on-line readability software. From the 100 assessed websites, 34% were commercially sourced. Of the remaining 66 sites, 40% had.org and 17% had.gov extensions. All 5 tests confirm that a large majority of the sample was written at an unacceptable reading level. In fact, over two-thirds of the sample received a readability score within the difficult range for three of the tests, while the remaining two deemed 49% and 45% of the sample as difficult to read, respectively. Commercially sourced websites were deemed to be more difficult to read than the other sites with respect to the two of the five measures. Despite the large amount of PKU information online, most of it may be incomprehensible to the average person and thus miss the mark in helping patients and caregivers manage their condition. Opportunities exist for authors of digital health promotional information to effectively achieve their goal by using comprehensible, easy-to-read language.

Indexed as

Online resourcesPhenylketonuria (PKU)Readability

Identifiers

PMID36502490
PMCPMC10104971

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.