Results

The sociodemographic and health information are summarized and presented in Table 1. There were 836 participants in this study. The mean age of participants was 26.6±12.2 years (range = 18–87). Age was categorized into 17–30 (63.3%), 31–45 (13.4%), 46–60 (9.6%), and > 61 (12.6%) year groups. Over half (51.9%) of participants were females; 64.0% were single, 30.4% (n = 254) were married, and 5.6% (n = 47) were others who were widowed, divorced, or separated. Twenty (2.4%) participants never attended school, 75 (9.0%) completed primary school, 101 (12.1%) completed a university degree or diploma. The majority (69.9%) were pursuing a bachelors/diploma program. The majority (64.6%) were still pursuing education, 20.3% were employed, and 15.1% were pensioners or dependants. Over half of (51.9%) participants reported to be in good health, and 24.5% in excellent health. Most (62.1%) participants had no long-term sickness. In terms of the time since last visit to the GP, 15.6% had visited within the last week, 32.9% within the last month, 28.8% within the last six months, 9.8% within the last year, and 12.9% more than a year ago. Voluntary participation in the survey by the young and educated was prominent. This could be due to good general literacy of the educated young than others who shied away from the survey. Fifteen percent of the sample reported having long-term sickness, and that mirrored the response of their last visit to the GP within the last week.

The overall Cronbach’s alpha value for the survey tool was 0.74, which is considered satisfactory. Our results of Cronbach’s alpha for the three sub-scales were 0.84 (good) for FUN items; 0.77 (acceptable) for the COM items; and 0.66 (questionable) for the CR items. Similarly, the overall McDonald’s omega coefficients of the factors was 0.81, for the three
sub-scales were 0.79 (acceptable) for FUN items, 0.82 (good) for the COM items, and 0.77 (acceptable) for CR items. The overall ICC for the factors were good with a value of 0.89 (95% CI: 0.77–0.97;
p = 0.001).

The AAHLS tool measured a comprehensive range of HL elements for each domain of HL assessed. Scores on the different items are presented in Table 2. Although the AAHLS tool does not provide the scoring mechanism to categorize the participants as having low, medium, or high HL, we have described mean scores on each of the AAHLS items of the responders. In general, responses to the AAHLS domains were significantly different. We found that the mean item scores were higher for EMP, followed by COM HL, suggesting confidence in these areas compared to CR and FUN HL which had lower scores. The highest mean score (1.8) was observed for the EMP item: “Do you think that there are plenty of ways to have a say about health?” The lowest mean score (0.1) was observed for the FUN HL item: “When you need help, can you easily get hold of someone to assist you?”

The association between important sociodemographic and health information variables with each AAHLS item was determined by a series of Pearson’s chi-square tests. By HL domain specificity, the responses of the participants significant to the AAHLS items were 12 for CR HL, 10 for FUN HL, six for COM HL, and five for EMP. Notably, five significant responses to the items in the FUN HL “how often do you need someone to help you when you are given information to read by your doctor, nurse, or pharmacist?” as well as in the CR HL “how often do you try to work out whether information about your health can be trusted?” were distinguishable. On the contrary, the responses to the item in the FUN HL “when you need help, can you easily get hold of someone to assist you?” was fairly distributed, and none was found significant. To reiterate, this item had the lowest mean score. Furthermore, by category specificity of the sociodemographics, more diverse responses to the AAHLS items were noted under the “education and employment” category. Of that, responses to seven items were significant. Likewise, among the categorized health information variables, the participants’ responses under the “self-rating of health” were diverse, and responses to eight items were significant.

For each participant, we also computed overall score and domain level score by summing up the responses recorded [Table 3], and investigated their relationship with the important sociodemographic and health information variables using the t-test and ANOVA. Participants aged < 30 years old, female, married, pursuing/completed master’s program, employed, and whose self-rating of health was excellent had significantly higher total HL scores. The participants’ scores were significantly higher in FUN HL for those aged < 30 years old; in CR HL for married participants; in FUN HL and CR HL for pursuing or completed master’s program and current employment categories. Self-rating of health as excellent was associated with higher scores in FUN and COM HLs, and this association did not reflect in CR HL. Participants who had not visited their GP in the past year had significantly higher CR HL scores. On the other hand, respondents aged > 30, less educated, unemployed, and who rated their self-rating as poor were associated with low HL scores, and visited the GP more frequently.

Discussion

We believe that assessing HL in the Bahraini community will be a critical step towards providing access to healthcare and utilization of health services by all. To the best of our knowledge, this study is the first of its kind in the Bahraini community to measure HL and its associated factors using a validated AAHLS tool. Various tools to measure the levels of HL exist, including the Newest Vital Sign, the Rapid Estimate of Adult Literacy in Medicine (REALM), Test of Functional HL in Adults (TOFHLA), Wide Range Achievement Test, and the Short Assessment of HL for Spanish Adults. Although the use of REALM and TOFHLA are not uncommon, the measurement methods are not sensitive and comprehensive, as they measure a single dimension in general.22 Therefore, we chose the AAHLS survey tool, as it was reliable, had a validated Arabic version, was sensitive, quick, easy to use in the community, and encompasses a range of competencies of FUN, COM, and CR HL.16,17,19 Our results on factor analysis further strengthened our assumptions to carry out the survey using the AAHLS tool. The overall Cronbach’s alpha value for the survey tool was 0.74, and the overall McDonald’s omega coefficients of the factors was 0.81.

Two systematic reviews23,24 have shown that comparing results from HL studies has been difficult due to different approaches and measures used for HL; likewise, we too experienced difficulties comparing. In addition, considering the cultural and linguistic similarity within the Arab region, a comparison of HL was difficult due to the scarcity of regional studies. Obtaining health information is reckoned as a functional skill; however, functional skill alone is not enough to make good health decisions. Our study findings imply that exerting control over one’s health is dependent on the complimentary types of functional, interactive, and critical components of HL, and this agrees with the report of van der Heide et al.25 Predominantly, educational attainment can be regarded to be associated with HL. Two-thirds of the participants were younger and attending university; therefore, their good general literacy propelled them to participate in our survey voluntarily, and they reported better health status than others. Our results reflected previous reports from Europe26–28 that participants who had completed higher education scored high in the three domains of HL relating to finding, understanding, and appraising health information compared with their less-educated contemporaries. Equivalently, the employment status of the respondents mimicked the association of HL to that of education. It is discernable that education and employment are similar in attaining higher levels of HL and that is further expressed in the “self-rating of health” in our study.

The study population was considerably heterogenic concerning several sociodemographic and health-related characteristics [Table 1]. Health information access and health system utilization may be particularly challenging for those with low HL. Of particular note, a high proportion of participants lacked FUN HL- a domain of access to support for comprehending written health information that is considered diverse with ‘distributed’ and ‘individual’ competence. To illustrate [Table 2], the lowest mean score (0.1) obtained by the respondents to the item “when you need help, can you easily get hold of someone to assist you?” explains that people sought the help often. In deviance, the highest mean score (1.8) was recorded in the EMP capability domain, echoing EMP at the level of community and social engagement for the item “do you think that there are plenty of ways to have a say about health?” This suggests that people assumed to have various ways talk about their health. Bearing in mind that HL is a complex phenomenon, analogous paradoxes have been found in documented reports,29,30 where a high percentage of participants had low FUN HL while they simultaneously reported that they did not have any challenges with other health information. Our findings demonstrated that assumptions should not be made that those having limited FUN HL have limited HL or converse. From a public health perspective, it is necessary to be aware of the multifarious dimensions of HL and that HL competencies vary in the populations.

There were several significant univariate associations among sociodemographics and health information variables with HL. On examining the significant associations between important variables to AAHLS items [Table 2], the responses to the item in the FUN HL “how often do you need someone to help you when you are given information to read by your doctor, nurse, or pharmacist?” emerged as significant to the most number of variables. Thus, suggesting people sought the help of the doctor, nurse, or pharmacist often, and significant variations were found among age, gender, marital status, education, employment, and self- rating on health. Besides, the responses to the item in the CR HL “how often do you try to work out whether information about your health can be trusted?” was also prominent suggesting people often tried to work out on the veracity of health information provided, and significant variations were found among age, marital status, education, employment, and self- rating on health.

Overall, participants who were < 30 years of age, female, married, pursuing/completed Master’s program, employed, and whose self-rating of health was excellent had significantly higher total HL scores and in certain domain-specific scores [Table 3]. A partial explanation could be that our sample was heterogenic; therefore, young, educated participants who volunteered to participate have scored high to our AAHLS items. Conversely, older, less-educated respondents, not employed, who self-rated their health as poor were associated with low HL scores, and they visited the GP more frequently. Further, the significant associations between inadequate FUN HL and education, and long-term illness and age, and the significant associations between inadequate COM HL and long-term illness in this study have been identified similar to the report of HL among diabetic patients.31

The methodological strengths of this study included a validated AAHLS tool and a larger sample size spread across the four governorates of Bahrain. It is known that individuals with a high burden of symptoms are less likely to attend surveys, and that is reflected in our study.32 However, our study had a few limitations. Foremost, we relied on self-reported data that may differ from actual behavior, because respondents might have given socially desirable answers during the interview. In reality, owing to stress or fear, people may have more difficulty with HL to exert control over healthcare than their responses in the survey. Second, the non-probability convenience sampling used in our study may not have adequately represented all members of the Bahraini population; our student surveyors had better access to other students of the university hence resulting in more student participants in our survey. Additionally, due to the paucity of time, we chose convenience sampling as the study had to be completed within a semester. Third, no inferences could be made about the directionality of the causal associations that were found owing to the cross-sectional design of the study.

Despite these limitations, we believe HL screening is expected to assist in efficiently managing healthcare resources for good returns on health. HL is a feature of interactions involving an individual’s HL and social environments,33 thereby, improved HL could motivate individuals to solve personal and public health problems. Furthermore, good HL enables efficient health policies with lower health care costs, and builds healthy environments and successful health promotions with better health
care outcomes.34

Conclusion

Older, less-educated respondents with a poor self-rating of health had low HL scores. Regionally HL studies are scarce, therefore, we recommend further studies to identify the gaps to improve the usability of health information and health services, build knowledge to improve decision making, and advocate for HL to address the relative importance of FUN, COM, and CR HL in community ability to fulfill an active role in their care in order to promote health outcomes and strengthen health systems.

Disclosure

The authors declared no conflicts of interest. No funding was received for this study. A poster presentation was made during the Second International Research Conference held at Royal College of Surgeons of Ireland, Bahrain in 2018.

Acknowledgements

We thank the Dean, College of Health Sciences, University of Bahrain, Bahrain for the support and encouragement to carry out the study.

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