Health Literacy and Critical Lecture as Key Elements to Detect and Reply to Nutrition Misinformation on Social Media: Analysis between Spanish Healthcare Professionals
Abstract
:1. Introduction
2. Materials and Methods
2.1. Procedure and Participants
2.2. Data Collection
2.3. Procedure and Ethical Considerations
2.4. Data Analysis
3. Results
3.1. Health Information on Social Media
3.2. Analysis of Critical Lecture of Health Information Linked to Scientific/Technical Documents
3.3. Reply to Health Misinformation
3.4. Relationship of Critical Reading Skills with the Response to Health Misinformation
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Categories | Subcategories | |
---|---|---|
Filter strategies of health misinformation | Origin of health information | Authentication of users |
Check the internal reliability | ||
Elements to check the external reliability | Tone of messages Presence or absence of data to support the affirmation about health. Presence of links to scientific or technical documents | |
Check the reliability of scientific papers linked to health information messages | Health literacy competence | Auto perception of high or low competence on health literacy |
Critical lecture competence | Analyzed the methodology and data analysis used Check reliability using, exclusively, clinical experience (no application of methodology research or data analysis competencies) | |
Reply to health misinformation messages | Frequency of reply | |
Tone and (kind of) language used | Technical/non-technical | |
Rebuttal misinformation | Publicly or privately | |
Inclusion of scientific references in the replies |
Competence on Health Literacy | Critical Lecture of Articles Linked to Health Messages | ||||||
---|---|---|---|---|---|---|---|
Yes | No | (χ2; p-value) | R.M. | C.E. | (χ2; p-value) | ||
Gender | Female | 33 | 25 | (2.019;0.121) | 37 | 21 | (0.0154; 0.558) |
Male | 17 | 6 | 15 | 8 | |||
Age (years) | <35 | 12 | 13 | (2.901; 0.234) | 14 | 11 | (3.821; 0.148) |
36–50 | 26 | 12 | 23 | 15 | |||
>50 | 12 | 6 | 15 | 3 | |||
Social media use | Personal | 9 | 6 | (0.31; 0.856) | 9 | 5 | (0.275; 0.871) |
Professional | 5 | 2 | 5 | 2 | |||
Mixed | 36 | 23 | 38 | 21 | |||
Followers | <1000 | 23 | 12 | (0.424; 0.809) | 22 | 13 | (0.200; 0.905) |
1000–5000 | 21 | 15 | 24 | 12 | |||
>5000 | 6 | 4 | 6 | 4 |
Reply to Health Misinformation Messages | Tone of the Replies | Language Used in the Replies | Rebuttal of Misinformation | Included Appropriate Scientific References in the Replies | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Yes | No | (χ2) | Conciliatory | Critical | Neutral | (χ2; p) | Scientific and Technical | Non-Scientific | (χ2; p) | Publicly | Privately. | (χ2; p) | Yes | No | (χ2; p) | ||
Gender (n; %) | Female | 33 | 25 | (0.001; 0.584) | 13 | 2 | 17 | (1.817; 0.611) | 15 | 19 | (0.054; 0.974) | 28 | 5 | (0.013; 0.994) | 22 | 10 | (0.230; 0.891) |
Male | 13 | 10 | 4 | 2 | 8 | 6 | 7 | 11 | 2 | 11 | 3 | ||||||
Age (years)(n; %) | <35 | 14 | 11 | (0.036; 0.982) | 5 | 4 | 5 | (11.978; 0.062) | 7 | 7 | (5.472; 0.242) | 15 | 2 | (0.450; 0.978) | 6 | 8 | (9.763; 0.045 *) |
36–50 | 22 | 16 | 9 | 0 | 13 | 6 | 16 | 18 | 4 | 18 | 3 | ||||||
>50 | 10 | 8 | 2 | 0 | 8 | 8 | 3 | 10 | 1 | 8 | 3 | ||||||
Social media use | Personal | 9 | 6 | (7.228; 0.300) | 4 | 1 | 3 | (7.228; 0.300) | 5 | 2 | (0.936; 0.919) | 9 | 0 | (3.667; 0.453) | 5 | 4 | (8.480; 0.075) |
Professional | 4 | 3 | 2 | 2 | 1 | 2 | 4 | 4 | 0 | 1 | 3 | ||||||
Mixed | 33 | 26 | 11 | 1 | 21 | 13 | 20 | 25 | 8 | 26 | 7 | ||||||
Followers | <1000 | 20 | 15 | (5.943; 0.430) | 7 | 0 | 13 | (5.943; 0.430) | 9 | 11 | (0.269; 0.992) | 17 | 3 | (0.238; 0.993) | 13 | 6 | (2.077; 0.722) |
1000–5000 | 21 | 15 | 8 | 4 | 9 | 9 | 12 | 18 | 3 | 15 | 7 | ||||||
>5000 | 5 | 5 | 2 | 0 | 3 | 2 | 3 | 4 | 1 | 5 | 0 |
A | B | C | D | E | F | G | |
---|---|---|---|---|---|---|---|
A | |||||||
B | 0.11; (n.s.) | ||||||
C | 0.25; * | 0.53; *** | |||||
D | 0.21; (n.s.) | 0.38; *** | 0.53; *** | ||||
E | 0.21; (n.s.) | 0.41; ** | 0.53; *** | 0.71; *** | |||
F | 0.22; (n.s.) | 0.42; *** | 0.55; *** | 0.70; *** | 0.74; *** | ||
G | 0.21; (n.s.) | 0.43; *** | 0.55; *** | 0.70; *** | 0.13; (n.s.) | 0.25; (n.s.) |
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Segado-Fernández, S.; Lozano-Estevan, M.d.C.; Jiménez-Gómez, B.; Ruiz-Núñez, C.; Jiménez Hidalgo, P.J.; Fernández-Quijano, I.; González-Rodríguez, L.; Santillán-García, A.; Herrera-Peco, I. Health Literacy and Critical Lecture as Key Elements to Detect and Reply to Nutrition Misinformation on Social Media: Analysis between Spanish Healthcare Professionals. Int. J. Environ. Res. Public Health 2023, 20, 23. https://doi.org/10.3390/ijerph20010023
Segado-Fernández S, Lozano-Estevan MdC, Jiménez-Gómez B, Ruiz-Núñez C, Jiménez Hidalgo PJ, Fernández-Quijano I, González-Rodríguez L, Santillán-García A, Herrera-Peco I. Health Literacy and Critical Lecture as Key Elements to Detect and Reply to Nutrition Misinformation on Social Media: Analysis between Spanish Healthcare Professionals. International Journal of Environmental Research and Public Health. 2023; 20(1):23. https://doi.org/10.3390/ijerph20010023
Chicago/Turabian StyleSegado-Fernández, Sergio, María del Carmen Lozano-Estevan, Beatriz Jiménez-Gómez, Carlos Ruiz-Núñez, Pedro Jesús Jiménez Hidalgo, Invención Fernández-Quijano, Liliana González-Rodríguez, Azucena Santillán-García, and Ivan Herrera-Peco. 2023. "Health Literacy and Critical Lecture as Key Elements to Detect and Reply to Nutrition Misinformation on Social Media: Analysis between Spanish Healthcare Professionals" International Journal of Environmental Research and Public Health 20, no. 1: 23. https://doi.org/10.3390/ijerph20010023