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Original Article
3 (
1
); 19-24
doi:
10.25259/SRJHS_38_2022

The pattern of online health information-seeking behavior before and during the COVID-19: An online cross-sectional survey among Nigerians

Department of Medical Laboratory Services, University of Osun State Teaching Hospital, Osogbo, Nigeria
Department of Physiotherapy, Nigeria Ports Authority Medical Centre, Lagos, Nigeria
Department of Physiotherapy, ATBUTH, Dutse, Jigawa State, Nigeria
Department of Physiotherapy, Dutse General Hospital, Dutse, Jigawa State, Nigeria
Corresponding author: Daha Garba Muhammad, Department of Physiotherapy, Dutse General Hospital, Dutse, Jigawa State, Nigeria. dahagarba@gmail.com
Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

How to cite this article: Jamiu MO, Ozoeze UN, Gbonjubola YT, Muhammad DG. The pattern of online health information-seeking behavior before and during the COVID-19: An online cross-sectional survey among Nigerians. Sri Ramachandra J Health Sci 2023;3:19-24.

Abstract

Objectives:

To evaluate alterations in the behavioral pattern of people looking for health information online in Nigeria.

Material and Methods:

Using a Google form that included a consent form and a data collection tool, 206 internet users participated in this online descriptive cross-sectional survey. From April 22 through May 31, 2022, the Google form’s link was shared on social media with all eligible participants. Descriptive statistics of frequency and percentage were used to summarize the data, which was represented as a bar chart.

Results:

Respondents within the age range of 20-29 years (82.5%) predominated in the study and were mostly Male (63.1%). The proportion of persons with internet access had gone up slightly from 98.5% to 99.5%, but internet usage remained the same (99% Vs 99%), however, a decrease in the frequency of using the internet always (56.3% Vs 48.5%) was observed. During COVID-19, there was a rise in the percentage of people obtaining health information online (87.4% vs. 96.6%).

Conclusion:

Albeit a slight decrease in using the internet during the COVID-19 era, however, there was an increase in online seeking behavior.

Keywords

Online health-seeking behavior
COVID-19
Nigeria

INTRODUCTION

Many people have died as a result of the COVID-19 infection, which has also impacted daily life. As of June 30, 2022, over 500 million people were infected, with death records totaling 6,357,058 globally. In Nigeria, 256,958 cases and approximately 3,144 deaths had been reported as of the same reference date.[1] Information sources assist individuals during a public health emergency by educating them, assisting them in taking preventative action, easing their anxiety, and assisting them in becoming more aware of the problem.[2] Because of the restrictions imposed by the World Health Organization and governments to curtail the spread, people had to rely heavily on media sources to get health information about the virus.

Any knowledge that can help a person make decisions about their health and maintain it is considered health information.[3] The process of looking for and utilizing any information in a way that satisfies an individual’s need is known as health information-seeking behavior, which is a type of personal health promotion. A variety of advantages come from seeking out health information, and it also contributes to closing the knowledge gap between social groups.[4] Seeking information can occur unconsciously, passively, or actively, but it is always purposeful to meet the desired goal or personal need.[5] From passive observation through passive searching to active searching and continuing searches, the extent of information-seeking behavior might vary.[6] Riordain and McCreary[7] showed that the reason individuals sought health information online was to improve knowledge about their condition, reduce fear and anxiety as well as find alternative remedies and treatment options.

In the past, people learnt about health issues by going to the library, talking to a doctor, or confiding in close friends. Since then, a new situation has arisen as a result of the rapid evolution and expansion of technology.[8] Online resources are becoming the method of choice for finding health information because of their comprehensiveness, easiness, accessibility, cost, and privacy.[9] Despite these increasing benefits, the internet’s information quality fluctuates, and the anonymity of content publishers alongside poor monitoring of the web content all contribute to a large pool of misleading and inaccurate information.[10] Although these factors pose a challenge in seeking health information online, there is however a shift in people becoming more knowledgeable and capable of managing their own health, which favors looking for health information online. Most people looking for health information online do so actively and passively,[3] to retrieve health information from the internet to gain knowledge to promote better personal health and facilitate decision-making. Among the most popular theoretical models in health promotion, Social Cognitive Theory,[11] establish a structure that can be used to interpret the results of individuals after getting information online. This theory explains that an individual’s self-efficacy in searching and finding quality health care information is connected to the anticipated outcomes after retrieval. In simple terms, self-efficacy is a powerful predictor of the outcomes you would anticipate seeing in regards to a person’s online health-seeking behavior. The model developed by Brown, Skelly, and Chew-Graham also shows that people’s online health retrieval is frequently influenced by their health attitudes, past experiences, and other background circumstances.[12]

Consumers of online health information can be of sick persons, their families or even people who want to pursue a good health lifestyle.[13] Online health resources can provide information on various diseases’ symptoms, diagnosis, and treatments, as well as general diet, weight-loss, and wellness advice.[14] This is why seeking information online has become a global trend. Studies were been conducted globally on individuals’ online health information-seeking behavior. According to a survey in 2020, there had been a 21% rise between 2010 in the proportion of Europeans between the ages of 16 and 74 who used the Internet to search information.[15] According to a research conducted in the USA, 61.2% of people looked for health information online in 2008; and by 2017, that number had risen to 74.4%.[16]

In Nigeria, several studies have been conducted across different groups on the frequency of information-seeking behavior for health online. A study among university undergraduate students in Nigeria showed a positive result for more than half of the participants.[17] Furthermore, Latunji and Akinyemi[18] studied the determinants of health-seeking behavior among civil servants in Ibadan in the South-Western part of Nigeria, with an appropriate high result among the targeted population. Another health-seeking behavior that targeted the pregnant women at the University College Hospital Ibadan also discovered increased online health-seeking behavior.[19] However, all these studies mentioned above were conducted before the COVID-19 hit. Very few studies reported the nature of online health information-seeking behavior during the pandemic. A study in India revealed that the pandemic increased the online health-seeking behavior for certain diseases such as hypertension, lung disease, and cardiovascular diseases.[20]

There is currently a shortage of information on whether the COVID-19 pandemic has changed how people seek information online. Therefore, this study sets to check if there is a change in the behavioral habit when looking for health information online among Nigerians.

MATERIAL AND METHODS

Design and population of the study

The study was a descriptive, cross-sectional survey aimed at determining the trends in health information seeking behavior online among Nigerians during and after COVID-19 lockdown.

Sample size calculation and sampling procedure

The sample size was calculated using the Cochran’s formula[21] where P was set at 83.2% as estimated by the previous study.[22] Therefore, a minimum of 240 (10% non-response rate added) respondents are required. Convenient and snowball sampling techniques were used to recruit the participants.

Instrument

We used a self-administered questionnaire, which comprises two sections and takes approximately 10 min to complete. The first part collects socio-demographic data such as age, gender, suffering from chronic condition, having a relative or friend with chronic condition. The second section assessed the pattern of online health information seeking behavior before and during COVID-19 lockdown using an adapted questionnaire. We adapted the instrument from AdegbileroIwari et al.[22] and Esmaeilzadeh et al.[23] Test retest reliability of 0.93 was obtained using a 2 weeks intervals pilot testing. The instrument was piloted among 15 potential participants to respond without informing them that they will retake the survey in order to avoid recall bias, however only 11 responded. Two weeks later, the same link was shared to the 11 people that responded but only 9 people retook the survey. We didn’t include these 11 responses in the main analysis and the respondents were also excluded in the main study.

Method of data collection

We obtained an ethical approval from University of Osun Teaching Hospital research ethics review committee with protocol number UTH/EC/2022/03/579. Data collection commenced April 22 and ended May 31, 2022. An online questionnaire was utilized for this study since the study cut across every part of the country. We sought for the participant’s informed consent via the google form link sent and the purpose of the study was explained to them. The link to the online questionnaire (Google form) was shared through a social media platform (Whatsapp).

Analysis of data

SPSS version 20 was used to summarize the data using a descriptive statistic of bar chart, frequency and percentage.

RESULTS

Two hundred and forty participants were proposed to fill the questionnaire however, 206 filled the instrument and were all considered for analysis giving rise to a response rate of 86%.

Demography of the participant

[Table 1] showed that, majority of the participants 170 (82.5%) were within 20–29 years of age. With regards to gender, Male participants 130 (63.1%) predominate in the study. Of ethnic origin of the participants, Yoruba 105 (51%) were the dominant followed by Hausa 57 (27.7%). Almost all of the participants 189 (91.7%) possessed a tertiary level of education and are mostly single 171 (83%). With regards to the occupation of the participants, majority were unemployed 57 (27.7%), followed by civil servants (health workers) 46 (22.3%) and self-employed 42 (20.4%). Almost all of the participants were in middle 169 (82%) socio-economic class. Only 7, (3.4%) were having chronic condition and about one-third 56 (27.2%) of the participants were having relatives with chronic disease. Fourteen (6.8%) of the participants tested positive to COVID-19.

Table 1: Participant’s details.
Variables Frequency Percentage
Age (years)
  Below 20 1 0.5
  20–29 170 82.5
  30–39 27 13.1
  40–49 7 3.4
  Above 50 1 0.5
Sex
  Male 130 63.1
  Female 76 36.9
Ethnicity
  Yoruba 105 51.0
  Igbo 21 10.2
  Hausa 57 27.7
  Others 23 11.2
Educational level
  Secondary school 2 1.0
  Tertiary 189 91.7
  Others 6 2.9
Marital status
  Married 29 14.1
  Single 171 83.0
  Engaged 6 2.9
Occupation
  Civil servant (health worker) 46 22.3
  Civil servant (non-health worker) 9 4.4
  Self-employed 42 20.4
  Unemployed 57 27.7
  Employed in a private organization 33 16
Socio-economic status
  Low 36 17.5
  Middle 169 82.0
  High 1 0.5
Presence of a chronic health
condition
  Yes 7 3.4
  No 199 96.6
Friends/Relatives with
chronic condition
  Yes 56 27.2
  No 150 72.8
Tested positive to COVID-19
  Yes 192 93.2
  No 14 6.8

Pattern of use of internet for health information seeking before and during COVID-19

Though there was slight increase in access to internet before and during COVID-19 (98.5% vs. (99.5%), the internet usage remain the same (99% vs. 99%). However, there was decrease in the frequency of usage of the internet always before and during COVID_19 (56.3% vs. 48.5%) as can be seen in [Table 2].

Table 2: Pattern of Internet use for health information seeking before and during COVID-19.
Variables Before COVID-19 n (%) During COVID-19 n (%)
Access to the Internet
  Yes 203 (98.5) 205 (99.5)
  No 3 (1.5) 1 (0.5)
Utilization of the Internet
  Yes 204 (99.0) 204 (99.0)
  No 2 (1.0) 2 (1.0)
Frequency of use
  Never 1 (0.5) 2 (1.0)
  Occasionally 12 (5.8) 20 (9.7)
  Sometimes 18 (8.7) 23 (11.2)
  Often 59 (28.6) 61 (29.6)
  Always 116 (56.3) 100 (48.5)
Use the Internet for
health information
  Yes 180 (87.4) 199 (96.6)
  No 26 (12.6) 7 (3.4)
Frequency of seeking health
information online
  Never 12 (5.8) 10 (4.9)
  Once a year 7 (3.4) 4 (1.9)
  Once a month 21 (10.2) 15 (7.3)
  Once a week 29 (14.1) 14 (6.8)
  Several times a month 32 (15.5) 21 (10.2)
  Several times a week 64 (31.1) 73 (35.4)
  Everyday 41 (19.9) 69 (33.5)
Average time spent on health
information web pages (hour/week)
  <2 h 117 (56.8) 104 (50.5)
  2–5 h 35 (17) 57 (27.7)
  More than 5 h 22 (10.7) 26 (12.6)
  Not applicable 32 (15.5) 10 (4.9)
Online health information
is sought for
  Self 69 (33.5) 59 (28.6)
  Someone else 16 (7.8) 13 (7.3)
  Both 101 (49.0) 119 (57.8)
  Not applicable 20 (9.8) 15 (7.3)
Sources of Online
Health Information*
  Google 179 (86) 181 (87.9)
  Journal 71 (34.5) 76 (36.9)
  Youtube 63 (30.6) 73 (35.4)
  Facebook, Whatsapp 60 (29.1) 74 (35.9)
  Others 28 (13.6) 35 (17)
Impact of the sourced information
  Not applicable 5 (2.4) 5 (2.4)
  Not at all 2 (1.0) 0
  Only a little 13 (6.3) 14 (6.8)
  Somehow 29 (14.1) 16 (7.8)
  A lot 157 (76.2) 169 (82)
Multiple response, n: Frequency

[Table 2] showed that an increase in online health seeking behavior during COVID-19 (87.4% vs. 96.6%). The frequency of seeking online health information everyday also increase during COVID-19 (19.9% vs. 33.5%). Spending more time on health information websites has also increased; either in the range of 2–5 h (17% vs. 27.7%) and >5 h (10.7% vs. 12.6%). The information is mostly sought for self and someone else both before and during COVID-19 (49% vs. 57.8%). Utilization of sources of online health information has also increased; Google (86% vs. 87.9%), Journal (34.5% vs. 36.9%), YouTube (30.6% vs. 35.9%). The impact of the sought information (a lot) has also increased during the pandemic (76.2% vs. 82%).

Reason for seeking an online health information before and during COVID-19

[Figure 1] showed that the motives for diagnosing a health problem, and getting general health information through seeking online health information has virtually remain the same (31.6% vs. 31.1%) and (64.1 vs. 66%) respectively. While seeking information on available treatment options has reduced (43.7% vs. 38.8%), searching to gain information about infection/COVID-19 has increased (60.7% vs. 65.5%).

Figure 1:
Reason for seeking an online health information before and during COVID-19

DISCUSSION

This study aimed at investigating the changes in the trends in the use of internet as a means of seeking health information amongst Nigerians. The rate of using internet sources to look up health information has allegedly been increasing due to the spread of information and advances in communication technologies.[24] Online sources for health information are increasingly popular due to a variety of factors, including their accessibility and scope, ease of search, accessibility that is affordable, interaction, and anonymity, among many others.[25] Getting information about health has many advantages, including closing knowledge gaps and teaching others outside of the medical field. It is worthy of note that, demographics of individuals such as age, gender, disability status, employment status and other determinants of health such as education had been found to have correlation with healthier populations.[14]

This study also established some discrepancies between the health information-seeking behavior and risk perceptions across age differences as youth are predominant in online health information seeking behavior when compared with the elderly population. Gender discrepancy as a factor that discriminates the quality of e-health information perception was also found in our study as male participants were more than females. This discrepancy in the gender distribution was in contrary to the earlier study which revealed that female gender perceived e-health information quality higher than the male[26] and by another study from Bidmon and Terlutter[27] who found higher frequency of using health forums and blogs for women in comparison with men. Also, notable is that, internet was an important source of information. However, the discrepancies highlighted in our study, were similar both before and during the pandemic.

Although, high income individuals are more prone to be online health information seekers,[24] the outcome of our study also reiterates the fact that the majority of the participants fall within the middle-class socio-economic status. This is understandable when we consider the proliferation of hand-held devices in addition to the cost implication of buying mobile data to gain access to the internet which are widely available and affordable to people falling into this socio-economic status.

Confirming our result, earlier studies have shown the popularity of online health seeking behavior. For instance, the internet was one of the primary information sources in 2004 and is expected to have a big impact on healthcare communication in the future.[28] Also, the internet was deemed to be the second-most popular source for finding health-related information.[29] Similar to our results, earlier studies reported that most of the health information seekers believed that, the information they get online influence their health.[21,25] About three-quarter of users of health information thought that the information they had acquired online had either a minor or major impact on them in terms of the decisions they made regarding their medical care, their approach to maintaining their overall health, and the way they perceived health-related issues.[24] Also, considering the pattern of internet use before and during COVID-19, there is no any significant difference in questions that has to do with their use of internet, a slight difference in their access to internet, beneficiary of the information sought. However, there was a rise in the frequency of seeking health information and the number of hours in a week spent while accessing health information online. This finding was in consonance with the result of Maon et al.[24] reported that over more than half of the information seekers search at least once in a weekly with more than who search several times in a day.[24]

In our study, Google was the predominant source of online health information both before and during COVID-19 and Facebook/WhatsApp being the least source. More so, the impact of the sought information stepped up during the pandemic. This finding supports a study conducted in the US on the habits of US individuals seeking health information, which discovered that a higher proportion of US adults turn to the Internet as their first resource.[30] Another study found that while 15% of online users tended to search on specialist health information websites, 83% of health information consumers used general search engines such as Google and Yahoo to look up health information.[24]

Participants in this study seek health information online mainly for general health information before and during COVID-19. The second reason was to gain information about COVID-19/infectious disease while the least reason for seeking information online was for the diagnosis following other reasons not captured in this study. However, when comparing the reason for online health-seeking information before and during the COVID-19, diagnosing health problem and getting general health information had almost the same result as (31.6% vs. 31.1%) and (64.1 vs. 66%), respectively.

In spite of the important findings in this study, few limitations were observed. Methodologically, this was a survey study and thus indicated that causality cannot be assumed and was self-reported. Self-reported data may not accurately reflect the circumstances, viewpoints, or actions of all consumers of health information. Although a wide range of populations were studied, certain important and specific populations were covered.

CONCLUSION

Conclusively, during COVID-19, there was an increase in the behavior of seeking health information online to about 10%. It was noted that the participants’ responses were based on how well they understood the investigators’ queries. Even though questions were posed in simple terms and language participants understand, their understanding may influence responses, especially those who are not formally educated. Although participants may favor the extreme or moderate response style, particularly on a questionnaire’s rating scale, response distortion can also be a limitation of this finding.

It is recommended that future research should carefully plan and investigate how people seek out health information online from a different angle. Although the study sample size was considerably high, however, a larger sample is also recommended, as this would have given a more certain estimation of the health information-seeking behavior among Nigerians. It is important to explore other ways to improve skill and health literacy to reduce information access disparities, especially for people from lower socioeconomic classes who cannot afford internet-enabled gadgets.

Governments should work to put effective health information management into place to support the positive expansion of online platforms for accessing health information and to ensure its security and accuracy.

Declaration of patient consent

The authors certify that they have obtained all appropriate patient consent.

Conflicts of interest

There are no conflicts of interest.

Financial support and sponsorship

Nil.

References

  1. . Coronavirus Update (live): Cases and Deaths from COVID-19 Virus Pandemic. . Worldometers. Available from: https://www.worldometers.info/coronavirus [Last accessed on 2022 Jun 30]
    [Google Scholar]
  2. , , , , . Media use and acute psychological outcomes during COVID-19 outbreak in China. J Anxiety Disord. 2020;74:102248.
    [CrossRef] [PubMed] [Google Scholar]
  3. , , . A study of rural elderly's health information needs and seeking behaviour. J Libr Inf Stud. 2012;10:155-204.
    [Google Scholar]
  4. . Gaps in Knowledge: Tracking and explaining gender differences in health information seeking. Soc Sci Med. 2015;128:151-8.
    [CrossRef] [PubMed] [Google Scholar]
  5. . Looking for Information: A Survey of Research on Information Seeking, Needs and Behavior San Diego, CA, USA: Academic Press; . p. :284-8.
    [Google Scholar]
  6. . Human information behavior. Inf Sci. 2000;3:49-55.
    [CrossRef] [Google Scholar]
  7. , . Dental patients' use of the Internet. Br Dent J. 2009;207:583-6, 575
    [CrossRef] [PubMed] [Google Scholar]
  8. , , , . Sociodemographic and health-(care-) related characteristics of online health information seekers: A cross-sectional German study. BMC Public Health. 2015;15:31.
    [CrossRef] [PubMed] [Google Scholar]
  9. , , . Online health information seeking behavior: A systematic review. Healthcare (Basel). 2021;9:1740.
    [CrossRef] [PubMed] [Google Scholar]
  10. , , , , , . How, when and why people seek health information online: Qualitative study in Hong Kong. Interact J Med Res. 2017;6:e24.
    [CrossRef] [PubMed] [Google Scholar]
  11. . Self-Efficacy: The Exercise of Control New York, NY, USA: W.H. Freeman and Company; .
    [Google Scholar]
  12. , , . Online health research and health anxiety: A systematic review and conceptual integration. Clin Psychol. 2019;27:e12299.
    [CrossRef] [Google Scholar]
  13. , , . Health information seeking behaviors and source preferences between Chinese and U.S. populations. J Health Commun. 2020;25:490-500.
    [CrossRef] [PubMed] [Google Scholar]
  14. , . Impact of smartphones on quality of life: A health information behavior perspective. Inf Syst Front. 2020;22:1275-90.
    [CrossRef] [Google Scholar]
  15. . Citizens Look for Health Information Online. . Available from: https://ec.europa.eu/eurostat/web/products-eurostat-news/-/edn-20210406-1 [Last accessed on 2022 Jul 02]
    [Google Scholar]
  16. , , , , , . Online health information seeking among US adults: Measuring progress toward a healthy people 2020 objective. Public Health Rep. 2019;134:617-25.
    [CrossRef] [PubMed] [Google Scholar]
  17. , . Online Health Information Seeking Pattern Among Undergraduates in a Nigerian University United States: SAGE Open; . p. :1-9.
    [CrossRef] [Google Scholar]
  18. , . Factors influencing Health-Seeking Behavior among Civil Servants in Ibadan Nigeria. Ann Ib Postgrad Med. 2018;16:52-60.
    [Google Scholar]
  19. . Health Information Seeking Behavior among pregnant women at the University College Hospital (UCH) Ibadan, Nigeria. Afr J Med Med Sci. 2019;48:191-8.
    [Google Scholar]
  20. , , , . Online health information seeking behavior due to COVID-19 pandemic-induced health-related anxiety among the general population in India. J Assoc Physicians India. 2022;70:11-2.
    [Google Scholar]
  21. , . How to calculate sample size for different study design in medical research. Indian J Psychol Med. 2008;35:121-6.
    [CrossRef] [PubMed] [Google Scholar]
  22. , , . A cross-sectional survey of online health information seeking behavior pattern of undergraduate students in a Nigerian Private University. Libr Philos Pract (e-Journal). 2021;5787
    [Google Scholar]
  23. , , , . A survey on adolescent health information seeking behavior related to high-risk behaviors in a selected educational district in Isfahan. PLoS One. 2018;13:e0206647.
    [CrossRef] [PubMed] [Google Scholar]
  24. , , . Online health information seeking behavior pattern. Adv Sci Lett. 2017;23:10582-5.
    [CrossRef] [Google Scholar]
  25. , , . The internet use for health information seeking among Ghanaian University Students: A cross-sectional study. Int J Telemed Appl. 2017;2017:1756473.
    [CrossRef] [PubMed] [Google Scholar]
  26. , . Gender differences in the use internet for health information search. EGE Acad Rev. 2011;11:229-40.
    [CrossRef] [Google Scholar]
  27. , . Gender difference in searching for health information on the internet and the virtual patient-physician relationship in Germany: Exploratory result on hoe men and women differ and why. J Med Internet Res. 2015;17:e156.
    [CrossRef] [PubMed] [Google Scholar]
  28. , . Health information on the internet: Patient empowerment or patient deciet? Indian J Med Sci. 2004;58:321-6.
    [Google Scholar]
  29. , , . Health information sources accessed by college females: Difference between body image distorted and non-body-image distorted. Health Mark Q. 2008;25:241-53.
    [CrossRef] [PubMed] [Google Scholar]
  30. , . Health information-seeking in the digital age. J Am Coll Health. 2011;59:379-86.
    [CrossRef] [PubMed] [Google Scholar]
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