Determinants of Intention Toward Dementia-Preventive Behaviors Among Middle-Aged Korean Adults

Abstract

This study aims to determine the influence of the constructs of the health belief model and fear of dementia on the behavioral intention to prevent middle-aged Korean adults’ dementia. Applying a descriptive design, 163 middle-aged adults were recruited. Structured questionnaires were used to collect data regarding fear of dementia, behavioral intention to prevent dementia, the expanded health belief model’s variables (i.e., perceived susceptibility, perceived severity, perceived benefit, perceived barrier, cues to action, general health motivation, and self-efficacy), and other general characteristics between August and September 2019. The determinants of the behavioral intention for dementia prevention were identified through hierarchical regression analysis. The significant factors influencing the behavioral intention for dementia prevention were general health motivation and self-efficacy, accounting for 34.2% of the variance. The results revealed key factors that should be considered in future interventions to enhance adherence concerning dementia-preventive behaviors.

Keywords

behavioral intention fear dementia health belief model middle-aged

Dementia is a disease indicated by memory impairment along with one or more cognitive disorders, such as aphasia, apraxia, agnosia, and executive dysfunction, which eventually lead to social and occupational disabilities (Jeong & Han, 2013). Dementia is associated with decreased quality of life for patients and increased burden and stress for families caring for dementia patients (Kim et al., 2015; Nam et al., 2018). In Korea, the number of patients with dementia rose from 650,000 in 2015 to 750,488 in 2018 and is expected to exceed 3 million by 2050 (Nam et al., 2018). Due to this rapid growth, the direct and indirect costs of dementia, including treatment cost, caregiving expenses, and loss of labor, are predicted to rise. The total annual management cost for dementia patients was 13.2 trillion Korean Republic Won (KRW) in 2015 but is anticipated to rise to 106.5 trillion KRW by 2050 (Nam et al., 2018). Therefore, dementia has surfaced as an important public health issue in Korea.

Unfortunately, the exact pathogenesis and etiology of dementia remain undetermined, and an optimal treatment thus is yet to be developed. Hence, preventing the progression and ensuring early detection of dementia are core objectives for any healthcare management (Jang & Lee, 2016). In this context, previous studies have attempted to categorize the factors that elevate the risk of dementia and reported various modifiable lifestyle risk factors for dementia (Alzheimer’s Disease International, 2014). Thus, the Korean government has launched “the dementia prevention rule 3.3.3,” which involves maintaining “3 recommendations” (exercising, eating, reading), “3 prohibitions” (moderation in drink, no smoking, prevent head injury), and “3 do’s” (health check-ups, communication, early dementia detection; Ministry of Health and Welfare & National Institute of Dementia, 2014). However, dementia-related studies in Korea indicated that the degree of compliance with the mandatory rules is low, at about 56%–60.8% (Cho, 2019; Lee & Kim, 2018). In particular, middle-aged adults in Korea perceived that dementia is a normal and unavoidable part of the aging process, so they were more passive toward dementia-preventive behaviors, including lowering dementia risk factors or adopting a healthy lifestyle (Cho, 2019). Consequently, to ensure successful dementia management in Korea, the focus should be shifted toward a potential dementia group, that is, middle-aged adults (Jang & Lee, 2016), and it is necessary to develop strategies to facilitate their compliance with dementia-preventive rules.

The health belief model (HBM) is utilized in predicting preventive health behaviors or behavioral intentions (Lee et al., 2014). This framework suggests that behavior is induced by perceived threats (i.e., perceived susceptibility, perceived severity), and the anticipation of the development of an illness, as well as expected outcomes (i.e., perceived benefits and perceived barriers) of engaging in healthy behaviors (Rosenstock, 1974). Since the model’s introduction, researchers who utilized the HBM as a theoretical framework have expanded the model and enhanced its explanatory power by adding the concepts of cues to action, general health motivation, and self-efficacy as other critical predictors of preventive behaviors, or behavioral intention (Choi et al., 2019; Jang & Ahn, 2015; Rosenstock et al., 1994). Therefore, the components of an expanded HBM (EHBM; that is, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, general health motivation, and self-efficacy) are likely to be associated with dementia-preventive behaviors (Kim et al., 2014).

However, recently published dementia-related studies in Korea focused on concepts such as awareness, knowledge, anxiety, and attitude and their relationships with dementia-preventive behaviors (Cho, 2019; Kim & Yang, 2016; Lee & Kim, 2018). Previous studies in Korea that applied the HBM as a framework to explain dementia-preventive behavior yielded insufficient results. A limited number of studies applied only some of the concepts and dealt with older adult populations (Choi et al., 2019; Yoo & Kim, 2017). Thus, it was limited in its ability to fully elucidate the influencing factors of dementia-preventive behaviors using an HBM in middle-aged adults in Korea.

People’s behavioral decisions are influenced by emotional factors (Bagozzi & Moore, 1994), including fear, which is a response to recognizing something being serious and dangerous and was identified as a major emotional factor that predicts behavioral changes (Floyd et al., 2000). When people identify a health threat, they develop fear and adhere to standard practices to eliminate such an emotion (Cha, 2005). Indeed, in the focus group study, fear of developing dementia was identified as the major motivator toward adopting a healthy lifestyle (Kim et al., 2015). Therefore, we believe that a study considering emotional factors such as fear of dementia in the HBM are needed to promote desirable dementia-preventive behaviors among middle-aged adults in Korea. Furthermore, Ajzen (1991) argued that intention, which indicates an individual’s readiness to perform a given behavior, is a strong determinant of behavior. For example, the level of actual compliance with dementia-preventive behaviors can be predicted based on an individual’s intention to follow the recommended and relevant behaviors (Harada et al., 2017).

Thus, this study aimed to identify the factors that influence the intention toward dementia-preventive behaviors among middle-aged adults in Korea by utilizing the components of an EHBM with fear of dementia as the conceptual framework. Specifically, the study investigated the differences in the intention toward dementia-preventive behaviors based on the participants’ general characteristics. Additionally, the relationship between EHBM variables, fear of dementia, and the intention toward dementia-preventive behaviors is analyzed. Further, these mechanisms identified the factors that influence participants’ behavioral intention toward dementia prevention and could help structure strategies that encourage dementia-preventive behaviors among middle-aged adults in Korea and even ultimately contribute to expediting dementia prevention in the region.

Methods

Study Design and Participants

This cross-sectional retrospective correlative study used a questionnaire survey on factors affecting the intention toward dementia-preventive behaviors in middle-aged Korean adults.

The target population aged between 50 and 64 years, were recruited from companies, cultural centers, and lifelong education institutes in B metropolitan city and G province in Korea. The inclusion criteria were (a) adults aged 50–64 years, (b) people capable of verbal communication and text comprehension in the Korean language, and (c) those who provided written informed consent. The exclusion criteria were (a) people who were diagnosed with a cognitive disorder by a physician, such as dementia, and (b) individuals with a history of diagnosed mental illness or use of psychiatric medication (e.g., antipsychotic drugs, antidepressants, antianxiety drugs).

The sample size was computed using the G*power 3.1 program. For a linear regression with an α of 0.05, power of 0.95, effect size of 0.15, and eight independent variables, the minimum required sample size was calculated to be 160. Considering a 15.0% withdrawal rate, 184 participants were recruited, but 21 were excluded due to incomplete responses or withdrawal, resulting in a final sample of 163 participants.

Among the 163 participants, 60.1% were women, and the largest number of participants were aged 50–54 years (39.9%). The majority were married (89.0%), identified as having a religion (68.1%), graduated high school or lower (68.7%), were employed (73.6%), had no family history of dementia (82.2%), had never smoked (69.3%), indicated that they consumed alcohol (60.7%), and did not exercise regularly (67.5%). Fifty-four percent of participants had an underlying condition, such as hypertension or diabetes. Table 1 details the demographic characteristics.

Table 1

Participant General Characteristics and Intention Toward Dementia-Preventive Behaviors (N = 163).

Variable	Number of participants [n (%)]	Intention score (Mean ± SD)	F or T	p
Gender
Male	65 (39.9)	5.03 ± 1.56	−0.316	.753
Female	98 (60.1)	5.11 ± 1.60	−0.316	.753
Age (years)
50–54^a	65 (39.9)	5.12 ± 1.42	3.864	.023*^†
55–59^b	55 (33.7)	4.67 ± 1.79
60–64^c	43 (26.4)	5.54 ± 1.41
Marital status
Alone	18 (11.0)	4.93 ± 1.38	−0.438	0.662
With spouse	145 (89.0)	5.01 ± 1.61	−0.438	0.662
Religion
No	52 (31.9)	4.72 ± 1.60	−1.976	.050
Yes	111 (68.1)	5.25 ± 1.55	−1.976	.050
Education level
≤High school	112 (68.7)	5.15 ± 1.62	0.891	.374
≥College	51 (31.3)	4.92 ± 1.50	0.891	.374
Householdincome (month)
<2 million won	46 (28.2)	5.30 ± 1.47	0.888	.449
2–3 million won	39 (23.9)	5.21 ± 2.02
3–4 million won	27 (16.6)	5.02 ± 1.37
≥4 million won	51 (31.3)	4.81 ± 1.39
Occupation
No	43 (26.4)	5.39 ± 1.28	1.492	.138
Yes	120 (73.6)	4.97 ± 1.67	1.492
Family history of dementia
No	134 (82.2)	4.98 ± 1.49	−0.375	.708
Yes	29 (17.8)	5.10 ± 1.60	−0.375	.708
Diseases
No	75 (46.0)	5.04 ± 1.69	−0.300	.765
Yes	88 (54.0)	5.11 ± 1.48	−0.300	.765
Smoking
Never	113 (69.3)	5.06 ± 1.53	0.291	.748
Ceased smoking	29 (17.8)	5.26 ± 1.53
Currently smoking	21 (12.9)	4.94 ± 1.95
Alcohol consumption
No	64 (39.3)	5.03 ± 1.55	−0.352	.726
Yes	99 (60.7)	5.12 ± 1.61	−0.352	.726
Regular exercise
No	110 (67.5)	5.03 ± 1.60	−0.616	.539
Yes	53 (32.5)	5.19 ± 1.55	−0.616	.539

Note. *p < .05 indicates statistical significance^{. †}c > b.

SD = standard deviation

Measures

Components of EHBM

The components of EHBM were assessed using the Motivation to Change Lifestyle and Health Behaviors for Dementia Risk Reduction scale (MCLHB-DRR), which was originally developed by Kim et al. (2014) and translated into Korean by Choi et al. (2019). The MCLHB-DRR comprises seven subscales: perceived susceptibility (i.e., perceiving oneself to be susceptible to dementia in one’s lifetime), perceived severity (i.e., perceived level of potential anxiety and stress after developing dementia), perceived benefits (i.e., perceived benefits from modifying lifestyle or health behaviors to reduce the risk of dementia), perceived barriers (i.e., perceived barriers that hinder the modification of lifestyle or practice of health behaviors to lower the risk of dementia), cues to action (i.e., perceived social influence that promotes oneself to modify lifestyle or practice health behaviors to reduce risk of dementia), general health motivation (i.e., value for general health and well-being), and self-efficacy (i.e., confidence to modify lifestyle or practice health behaviors to reduce risk of dementia). This 27-item tool is rated on a five-point Likert scale ranging from strongly disagree to strongly agree, with higher scores indicating higher levels of the respective subscales. The construct validity of the MCLHB-DRR was established at the time of its development (Kim et al., 2014), and the Cronbach’s α values for internal consistency were0.86 for perceived susceptibility, 0.72 for perceived severity, 0.69 for perceived benefits, 0.74 for perceived barriers, 0.68 for cues to action, 0.61 for general health motivation, and 0.66 for self-efficacy at the time of development. In our study, the values were 0.92 for perceived susceptibility, 0.84 for perceived severity, 0.85 for perceived benefits, 0.84 for perceived barriers, 0.72 for cues to action, 0.88 for general health motivation, and 0.81 for self-efficacy.

Fear of Dementia

Fear of dementia was measured using the Korean Version of the Fear of Alzheimer’s Disease Scale (K-FADS), which was originally developed by French et al. (2012) and adapted into Korean by Moon et al. (2014). The K-FADS consists of three subscales for general fear, physical symptoms, and catastrophic attitudes. The 30-item scale is rated on a five-point Likert scale with answers ranging from never to always, and a higher total score indicates greater fear of dementia. The construct validity and reliability of the K-FADS for addressing anticipatory dementia among Koreans were established in a previous study (Moon et al., 2014). In the previous study (Moon et al., 2014), Cronbach’s α for the reliability of the total score was 0.96, and the reliability values of the three subscales were 0.94–0.96. In the present study, the Cronbach’s α for the reliability of the total score was 0.92, and the reliability values of the three subscales were 0.84–0.96.

Behavioral Intention Toward Dementia Prevention

The intention toward dementia-preventive behaviors was measured using an instrument developed by Choi et al. (2019),which was operationalized according to the instrument development guidelines provided by Ajzen (2002) and the behavioral intention measurement of Sohn and Lee (2012).The instrument included information about the dementia prevention rules (exercising, eating, reading, moderation in drink, no smoking, preventing head injury, health check-ups, communication, and early dementia detection) and items to investigate the behavioral intention toward dementia prevention. The instrument consists of the following three items: (a) “To prevent dementia, I plan to regularly perform the dementia-preventive rules in everyday life from next week,” (b) “To prevent dementia, I expect to regularly perform the dementia-preventive rules in everyday life from next week,” and (c) “To prevent dementia, I intend to regularly perform the dementia-preventive rules in everyday life from next week.” Each item is rated on a seven-point Likert scale ranging from strongly disagree to strongly agree, and a higher score indicates a greater inclination toward dementia-preventive behaviors. The validity and reliability of the instrument to measure the intention toward dementia-preventive behaviors were established at the time of development (Choi et al., 2019). The Cronbach’s α for reliability was 0.97 at the time of development (Choi et al., 2019) and 0.96 in our study.

Data Collection and Ethical Considerations

This study was approved by the institutional review board at the author’s affiliated institution (KSU-19-06-001-0708), and informed permission was obtained from companies, culture centers, and lifelong education institutes in B metropolitan city and G province to recruit participants. The researchers and two research assistants selected 163 middle-aged adults and collected data from August 19, 2019, to September 20, 2019. As for the sampling, it was difficult to select middle-aged adults based on the region, so a convenience sampling method was used. Among the administrative areas in Korea, B metropolitan city, the third largest in terms of population, and G province, the fourth largest in terms of population (Statistics Korea, 2019), were selected. Further, efforts have been made to balance the scale of the investigation site and the number of participants so that the sample is not localized to a specific area. The research assistants were nursing graduate students who were trained by experienced researchers before data collection regarding survey methods, contents of the survey instruments, and effective interviewing techniques. After informing eligible participants about the purpose of this study and the ability to withdraw from it at any time, those who expressed consent signed a written consent form. Participants received the structured questionnaire and were asked to complete it. Those with visual impairments or who experienced difficulty in interpreting the questions were assisted by the researchers and research assistants. It took approximately 15–20 min to complete the questionnaire, and the completed questionnaires were retrieved on site. Participants who completed the questionnaires received a gift worth US$4. Thereafter, the collected questionnaires were processed using IDs before being entered and analyzed quantitatively on a password-protected computer to maintain the confidentiality of personal information.

Statistical Analysis

The collected data were evaluated using the SPSS/WIN 21.0 software. Participants’ characteristics and study variables were analyzed using descriptive statistics, and the differences in the intention toward dementia-preventive behaviors according to participants’ general characteristics were examined using t-tests and ANOVA with Scheffe’s test as post-hoc analysis. The correlations among perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, general health motivation, self-efficacy, fear of dementia, and intention toward dementia-preventive behaviors were studied using Pearson’s correlation coefficients, and the factors that influence the intention toward dementia-preventive behaviors were inspected through a hierarchical regression analysis.

Results

Participants’ General Characteristics and Differences in the Behavioral Intention of Dementia Prevention

The general characteristic that varied according to the intention toward dementia-preventive behaviors was age (F (2,160) = 3.86, p = .023). In other words, people aged 60–64 years exhibited a significantly greater intent to engage in dementia-preventive behaviors (Table 1).

Levels of Study Variables and Their Association With Intention Toward Dementia-Preventive Behaviors

The highest mean score out of the EHBM variables was recorded for general health motivation (4.05 ± 0.76 out of 5), followed by perceived benefits (3.70 ± 0.81), self-efficacy (3.69 ± 0.90), cues to action (3.48 ± 0.74), perceived severity (2.50 ± 0.93), perceived barriers (2.49 ± 0.87), and perceived susceptibility (2.14 ± 0.56). The mean score for fear of dementia was 1.49 ± 0.89 out of 4, and the score for the intention toward dementia-preventive behaviors was 5.08 ± 1.58 out of 7. (Table 2).

Table 2

Levels of Study Variables and Their Association With Intention Toward Dementia-Preventive Behaviors (N = 163).

Variable	M	SD	Score range	Intention toward dementia-preventive behaviors
Variable	M	SD	Score range	r	p
HBM variables
Perceived susceptibility	2.14	0.56	1–5	.19	.015
Perceived severity	2.50	0.93	1–5	.29	<.001
Perceived benefits	3.70	0.81	1–5	.25	<.001
Perceived barrier	2.49	0.87	1–5	.15	<.049
Cues to action	3.48	0.74	1–5	.35	<.001
General health motivation	4.05	0.76	1–5	.49	<.001
Self-efficacy	3.69	0.90	1–5	.42	<.001
Fear of dementia	1.49	0.89	0–4	.28	<.001
Intention toward dementia-preventive behaviors	5.08	1.58	1–7

Abbreviation: HBM = health belief model.

A significant correlation was observed between intention toward dementia-preventive behaviors and perceived susceptibility (r = .19, p = .015), severity (r = .29, p < .001), benefit (r = .25, p < .001), barriers (r = .15, p = .049), cues to action (r = .35, p < .001), general health motivation (r = .49, p < .001), self-efficacy (r = .42, p < .001), and fear of dementia (r = .28, p < .001; Table 2).

The Determinants Influencing the Behavioral Intention Toward Dementia Prevention

To detect the determinants that influence the intention toward dementia-preventive behaviors, we performed a hierarchical regression analysis by processing the variables that were significantly correlated, such as age, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, general health motivation, self-efficacy, and fear of dementia.

Before the regression analysis, we validated that the dependent variables were not auto-correlated with a Durbin-Watson statistic of 1.97 and that there was no problem of multicollinearity among independent variables, with a variance inflation factor (VIF) below 10 (1.27–2.76) and tolerance of above 0.10 (0.36–0.79). The conditions for normality of the error matrix and assumption of equal variance were fulfilled; thus, the data were suitable for regression.

Table 3 presents the results of the three-step hierarchical regression analysis. Age was entered in the first step, and the first model explained 4.6% of the variance in the behavioral intention toward dementia prevention. Perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, general health motivation, and self-efficacy were added in the second step, and the resulting model explained 33.8% of the variance in the behavioral intention toward dementia prevention. This result depicts a statistically significant improvement due to the explanation of a 29.2% increase in the variance and significant predictors, specifically general health motivation and self-efficacy. Finally, when fear was entered in the last step, general health motivation (β = 0.32, p < .001) and self-efficacy (β = 0.22, p = .012) were significant predictors of the behavioral intention toward dementia prevention. Notably, the variables in step 3 contribute to the behavioral intention toward dementia prevention 0.4% more than the variables in step 2. Moreover, the total explanatory adequacy of these factors was 34.2% (F = 7.89, p < .001; Table 3).

Table 3

Variables Predicting the Behavioral Intention Toward Dementia Prevention (N = 163).

Variable	Step 1		Step 2		Step 3
Variable	B	β (p)	B	β (p)	B	β (p)
Age 55–59^†	−0.46	−0.14 (.112)	−0.37	−0.11 (.137)	−0.35	−0.11 (.156)
Age 60–64^†	0.42	0.12 (.171)	0.41	0.11 (.128)	0.44	0.12 (.103)
Perceived susceptibility			0.23	0.13 (.181)	0.21	0.11 (.240)
Perceived severity			0.15	0.09 (.373)	0.08	0.05 (.559)
Perceived benefits			−0.15	−0.08 (.340)	−0.14	−0.07 (.368)
Perceived barriers			−0.18	−0.10 (.211)	−0.20	−0.11 (.172)
Cues to action			0.14	0.07 (.434)	0.12	0.06 (.524)
General health motivation			0.71	0.34 (<.001)	0.70	0.34 (<.001)
Self-efficacy			0.40	0.22 (.012)	0.40	0.22 (.012)
Fear					0.15	0.09 (.377)
R² (R² change)	0.046		0.338 (0.292)		0.342 (0.004)
Adjusted R²	0.034		0.299		0.299
F (p)	3.86(.023)		8.69 (<.001)		7.89 (<.001)

Note. Dummy code ^†= (Ref. 50–54).

Discussion

In our study, the mean score of intention toward dementia-preventive behaviors was 5.08 out of 7. This outcome is similar to studies that reported that participants’ intention toward dementia-preventive behaviors was not enough, with a score of 5.1 out of 7 (Choi et al., 2019). However, our study, which examined the association between intention toward dementia-preventive behaviors and general characteristics, resulted in findings that were different from those of previous studies (Choi et al., 2019; Werner, 2003). In this study, the intention toward dementia-preventive behaviors was only significantly higher among those of advanced age. However, in the study by Choi et al. (2019), intention toward dementia-preventive behaviors was higher among females, those without a spouse, those with a higher educational background, and those who did not drink alcohol, but such behavioral intention was unrelated to age. Other studies reported that general characteristics were unrelated to intention toward dementia-preventive behaviors (Werner, 2003).The inconsistency among findings may be attributed to the differences in participant age and other demographic variables included in the models. Therefore, it may call for replication studies to accumulate relevant research data.

Hierarchical regression analysis, performed to identify factors that impact behavioral intention toward dementia prevention among middle-aged Korean adults, indicated that general health motivation and self-efficacy were variables that significantly predicted behavioral intention toward dementia prevention. General health motivation and self-efficacy accounted for 30% of variance observed for behavioral intention toward dementia prevention. Interestingly, the explanatory power of the intention toward dementia prevention behaviors increased from 3% to 30% when the constructs of HBM were entered in step 2, but there was no change in the explanatory power of the intention toward dementia prevention behaviors when fear was entered in the last step. Because of a lack of comparable data from previous studies related to dementia, no direct comparisons could be made regarding the significance of explanatory power. However, our results are contrary to previous findings (Jo et al., 2012) that showed fear as a major predictor that directly affects tuberculosis preventive behavior intention, and the fit of model was good as a result of applying the HBM and fear as a theoretical basis. Considering that participants with a high fear of dementia are adopting healthier lifestyles and healthier behaviors than those with a low fear of dementia (Kim et al., 2015), it is believed that the inconsistency of the results is due to the difference in the participants’ fear level. Although the target diseases are different, the previous study showed that most participants had moderate to strong fears, averaging 2.08 on a four-point scale, and the participants in this study scored low, with an average of 1.49. Therefore, in future studies, to understand the impact of emotional factors such as fear, it would be necessary to compare the results by dividing the group into low and high fear groups.

General health motivation was the most significant multivariate predictor of intention toward dementia prevention. Participants with high general health motivation had a higher level of intention toward dementia-preventive behaviors. This is similar to the result in a study that examined osteoporosis-preventive behaviors based on the HBM (Jang & Ahn, 2015) and found that general health motivation had the greatest impact on the regular physical exam and compliance with treatment instructions. These results suggest that people are likely to engage in preventive health behaviors against particular illnesses if they highly value health and well-being (Mairman & Becker, 1974). Therefore, the many health policy efforts made to manage dementia need to be guided by higher value placed on well-being, with positive reinforcement of the perspectives on health of the middle-aged in Korea. In addition, it is necessary for researchers to conduct research focusing on the development of strategies to improve the general health motivations of the middle-aged in Korea.

Additionally, self-efficacy emerged as a significant predictor of the behavioral intention toward dementia prevention. Similarly, in previous studies related to dementia (Choi et al., 2019; Yoo & Kim, 2017), which encompassed the components of HBM as independent variables, self-efficacy presented the strongest association with preventive behavior or preventive behavioral intention. These results suggest that self-efficacy is an integral determinant of whether persons will adopt such behaviors. Therefore, dementia prevention interventions targeting middle-aged adults in Korea should be developed based on the four sources of self-efficacy, as presented by Bandura (1998): performance accomplishments, vicarious experiences, social persuasion, and physiological and emotional states.

The current study has a few limitations. First, because of the sampling method, we may not have been able to recruit middle-aged adults who were not enrolled in programs or workers who were not working in white collar jobs. Additionally, participants volunteered to take part in the study, which may have resulted in a biased sample in which workers without a family history of dementia were overrepresented. The lack of diversity in the study sample limits the generalization of study results to people with different demographic characteristics. Therefore, in the future, it is necessary to recruit participants of more varied backgrounds. Furthermore, the fear of dementia may be different depending on the experience of caring for patients with dementia. A next step for this area of research would be to examine the relationship between a family history of dementia and fear of dementia and to determine whether there are differences in preventive behaviors according to the level of fear of dementia. Second, although the primary purpose of this study was to better understand dementia-preventive behavior in middle-aged people, the actual dependent variable used in our study was the intention toward dementia-preventive behaviors. However, this limitation is considered minor because intentions were confirmed as reliable and direct predictors of specific behaviors (Ajzen, 1991). Furthermore, the fact that the behavioral intention toward the dementia prevention factor was not assessed using each recommended behavioral item is a shortcoming of the study.

Still, this study is of significant value as it attempted to contribute to developing strategies for dementia, which is a nation-wide topic of interest in Korea, specifically among middle-aged adults, and it incorporated all of the components of EHBM to enable specific prediction of the intention toward dementia-preventive behaviors. Moreover, the fear of dementia is considered as an emotional determinant and is thus not dealt with in the HBM.

Based on our results, it is believed that further studies may provide more solutions for reducing the incidence of dementia in Korea.

Footnotes

Ethical Approval

This study was approved by the institutional review board of Kyungsung University (KSU-19-06-001-0708), and an informed permission was obtained from companies, culture centers, and lifelong education institutes to recruit participants.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the esearch, authorship, and/or publication of this article.

Author Biographies

Won-Hee Choi, PhD, Associate professor, Department of Nursing, Kyungsung University, Busan, Korea.

Yeong-Mi Seo, PhD, Associate professor, Department of Nursing, Gyeongnam National University of Science and Technology, Jinju, Korea.

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