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Precisionen av digital hälsoinformation: en systematisk översikt
University of Skövde, School of Health Sciences.
University of Skövde, School of Health Sciences.
2024 (Swedish)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesisAlternative title
The accuracy of online health information : a systematic review (English)
Abstract [sv]

Introduktion: I dagens digitala tidsålder vänder sig många individer till internet som sin första källa till hälsoinformation. Forskning har dock visat att majoriteten av digital hälsoinformation är av låg kvalitet och har bristfällig korrekthet. En stor del av denna information består sannolikt av både desinformation och missinformation. Syfte: Syftet med denna studie var att sammanställa resultaten från peer-review granskade studier som utvärderar korrektheten hos digital hälsoinformation, med särskilt fokus på studier som använder expertgranskade texter utvärderade mot etablerade riktlinjer. Metod: Den 7 april 2024 genomsöktes tre databaser – MEDLINE EBSCO, Scopus och PubMed. Totalt 21 artiklar inkluderades. Resultaten från dessa artiklar kategoriserades och analyserades induktivt utifrån Narro och Tudges neo-ekologiska teori. Resultat: Fyra huvudkategorier skapades gällande informationens korrekthet: god, måttlig, bristfällig och varierande. Av de inkluderade artiklarna bedömdes 3 (14%) ha god korrekthet, 4 (19%) artiklar måttlig korrekthet, 13 (62%) bristfällig korrekthet och 1 (5%) hade varierande. Därtill ansågs 76% av det inkluderade materialet från trovärdiga källor ha bristfällig korrekthet. Slutsats: Majoriteten av de inkluderade studierna och det trovärdiga materialet har bristfällig korrekthet. Dessutom, tenderar studier som uppvisar en högre grad av korrekthet, ha sämre läsbarhet och den övergripande kvaliteten är ofta bristfällig, vilket även gör det svårt för konsumenter att förstå informationen.

Abstract [en]

Introduction: In today's digital age, many individuals turn to the internet as their initial source of health information. However, research has shown that the majority of online health information is of poor quality and low accuracy. A significant portion of this information likely includes both misinformation and disinformation. Aim: The aim of this study was to synthesize findings from peer-reviewed research assessing the accuracy of online health information, with a particular emphasis on studies that utilize expert-reviewed content evaluated against established guidelines. Method: On 7 April 2024, three databases—MEDLINE EBSCO, Scopus, and PubMed—were searched. A total of 21 articles were included in the systematic review. The results from these articles were categorized and inductively examined through the lens of Narro and Tudge’s neo-ecological theory. Results: Four primary categories were created concerning the accuracy of the information: good, moderate, poor, and varied. Among the included articles, 3 (14%) were deemed to have good accuracy, 4 (19%) articles exhibited moderate accuracy, 13 (62%) demonstrated poor accuracy, and 1 (5%) had varied accuracy. Additionally, 76% of the included material from trustworthy sources were categorized as having poor accuracy. Conclusion: The majority of the included studies and trustworthy material were found to have poor accuracy. Furthermore, even when studies exhibited a higher degree of accuracy, the readability and overall quality were often deficient, making it difficult for consumers to understand.

Place, publisher, year, edition, pages
2024. , p. 29
Keywords [en]
Online health information, accuracy, guidelines, misinformation
National Category
Public Health, Global Health and Social Medicine
Identifiers
URN: urn:nbn:se:his:diva-23908OAI: oai:DiVA.org:his-23908DiVA, id: diva2:1865865
Subject / course
Public Health Science
Educational program
Folkhälsovetenskap: Digital hälsa och kommunikation
Supervisors
Examiners
Available from: 2024-06-05 Created: 2024-06-05 Last updated: 2025-02-20Bibliographically approved

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Citation style
  • apa
  • apa-cv
  • ieee
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  • en-GB
  • en-US
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  • nn-NO
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  • sv-SE
  • Other locale
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Output format
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  • text
  • asciidoc
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