Health-Seeking Behavior and Its Determinants Among Older Adults with Mild Cognitive Impairment: From Symptom Recognition to Self-Care

Health-Seeking Behavior and Its Determinants Among Older Adults with Mild Cognitive Impairment: From Symptom Recognition to Self-Care | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Health-Seeking Behavior and Its Determinants Among Older Adults with Mild Cognitive Impairment: From Symptom Recognition to Self-Care Dongmei Zhong, Yingren Mai, Rui Song, Yifan Ye, Lifeng Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8220732/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Mild cognitive impairment (MCI) is a transitional stage between normal aging and dementia, where timely recognition and appropriate health-seeking behavior may help delay cognitive decline. Although both pharmacological and non-pharmacological interventions show potential benefits, the utilization of healthcare services among older adults with MCI remains inadequate. This study examined health-seeking behavior-including symptom recognition, medical treatment, standardized treatment, and self-care at home-its determinants, and potential strategies to promote proactive care-seeking. Methods A cross-sectional survey was conducted among community-dwelling older adults diagnosed with MCI. Health-seeking behavior was assessed using a structured questionnaire based on Andersen’s Behavioral Model. Data on MCI-related knowledge, social support, activities of daily living (ADL), and sociodemographic and health characteristics were also collected. Descriptive statistics summarized participant characteristics and behavioral patterns. Independent-samples t tests and chi-square tests examined group differences, and variables significant at P < 0.05 were entered into multivariate logistic regression models to identify determinants of each behavior type. Results A total of 244 older adults with MCI were included. Only 13.1% actively sought medical treatment, while most were diagnosed passively during clinical visits or community screening. Standardized treatment was reported in 12.7%, and 25.4% engaged in self-care at home. Urban residence, medical payment method, diagnosing institution, and MoCA scores were significantly associated with medical treatment behavior. Urban residents were more likely to seek care ( OR = 7.45, P = 0.01), while individuals using medical insurance were less likely to do so compared with self-paying participants ( OR = 0.26, P = 0.04). Participants diagnosed in tertiary hospitals were more likely to seek treatment ( OR = 11.07, P = 0.02), whereas higher MoCA scores were negatively associated with medical consultation ( P = 0.001). Similar patterns were observed for standardized treatment. For self-care behavior, gender, education level, and transportation mode were key predictors. Conclusions Health-seeking behavior among older adults with MCI remains suboptimal, with very low rates of active care-seeking and standardized treatment adherence. Urban-rural disparities, cognitive status, healthcare accessibility, and socioeconomic characteristics significantly influence behavioral patterns. Targeted health education, community-based cognitive screening, and supportive healthcare policies are urgently needed to improve early recognition, diagnosis, and long-term management of MCI, potentially delaying its progression to dementia. older adults mild cognitive impairment health-seeking behavior Figures Figure 1 Figure 2 Figure 3 1 Background Mild cognitive impairment (MCI) is a clinical diagnosis based on subjective cognitive decline, objective cognitive impairment, and relative preservation of activities of daily living(Bradfield, 2023). It may be established via clinical interview, collateral history from an informant, and psychometric examination(Bradfield, 2023). The number of people with dementia and MCI has rapidly increased in recent decades and related challenges have become a globe burden(Collaborators, 2022; Organization, 2025). In China, MCI affects over one-fourth of rural older adults(Cong et al., 2023). Evidence suggests that within a 5–10 years period following a diagnosis of MCI due to Alzheimer’s disease, approximately 30% to 50% of individuals progress to Alzheimer’s dementia(2024). Specifically, up to 15% of people with amnestic MCI are estimated to develop Alzheimer’s dementia that period, with research suggesting that this subtype of MCI due to Alzheimer’s disease may increase the likelihood of progression to dementia(Dementia, 2021). The number of people with dementia reached 57 million worldwide in 2021, over 60% of whom live in low-and middle-income countries(Organization, 2025). Every year, there are nearly 10 million new cases(Organization, 2025). Caregivers of old people with dementia often report emotional, financial and physical difficulties. A total of eight drugs are available for the treatment of Alzheimer’s disease, and early health seeking shows promise in reducing the progression of MCI to dementia(2024). Health or care seeking behavior has been defined as any action undertaken by individuals who perceive themselves to have a health problem or to be ill in order to find an appropriate remedy(Ward et al., 1997). In this study, health-seeking behavior refers to all actions taken by older adults after the onset of disease symptoms, including symptom recognition, medical treatment, standardized treatment, and self-care at home. At present, there is no standardized instrument for measuring health-seeking behavior. Researchers typically determine the measurement dimensions based on the conceptual definition of health-seeking behavior and their specific research focus. Existing studies on health-seeking behavior have primarily examined delays in seeking care and their influencing factors, the care-seeking process, and the potential overuse of healthcare services after diagnosis(Du QH et al., 2024; Sun et al., 2021; Taghikhah et al., 2025). To address this gap, the present study developed a self-designed questionnaire to assess health-seeking behavior among older adults with MCI, covering four dimensions: symptom recognition behavior, medical treatment behavior, standardized treatment behavior, and self-care behavior at home. Health-seeking behavior is generally regarded as key to delay progression of MCI to dementia(Bradfield, 2023; Erickson et al., 2022). Pharmacological and non-pharmacological behavior are two approaches for improving cognitive function(2024). However, health-seeking behavior among older adults with MCI are generally suboptimal. Studies have shown that over 50% of people with cognitive impairment fail to receive medical evaluations for memory problems, and cannot make use of community resources when seeking help for memory problems (Ishiwata et al., 2014; Maslow & Fortinsky, 2018; Ross et al., 1997). Approximately 80% of Chinese diagnosed with dementia remain untreated by any medication(Jia et al., 2016). Only a small proportion of individuals with MCI actively seek medical evaluation or standardized treatment, while many are diagnosed incidentally through routine screening or during visits for other health problems(Wang et al., 2025). Several factors may contribute to this low rate of active health-seeking, including poor symptom recognition, limited awareness of MCI as a clinical condition, and the belief that memory decline is a normal part of aging(Hill et al., 2021; Jiao et al., 2023). In addition, barriers such as financial constraints, insufficient access to specialized medical services, and stigma related to cognitive decline further discourage older adults and their families from pursuing timely diagnosis and treatment(Hill et al., 2021; Jiao et al., 2023). As a result, many MCI individuals miss the critical window for early intervention, which may accelerate their progression to dementia. Timely health-seeking behavior is essential to delay the progression of MCI to dementia. This study aims to investigate health-seeking behavior for older adults with MCI, encompassing symptom recognition, medical treatment, standardized treatment, and self-care at home. Additionally, it seeks to identify potential determinants, including sociodemographic and behavioral characteristics, knowledge of MCI, social support, and activities of daily living. Theoretical framework Andersen’s Behavioral Model of Health Service Utilization is one of the most widely applied theoretical frameworks for understanding and predicting health-seeking behavior (Anderson, 1973). According to this model, healthcare utilization is determined by three major categories of factors: predisposing factors, enabling factors, and need factors(Anderson, 1973). In the present study, health-seeking behavior encompasses four dimensions: symptom recognition behavior, medical treatment behavior, standardized treatment behavior, and self-care behavior at home. Predisposing factors refer to the individual characteristics that influence the likelihood of seeking healthcare before the onset of illness. These include gender, age, education level, marital status, caregiving responsibilities for grandchildren under 18 years, and MCI-related knowledge. Enabling factors represent the resources that facilitate or impede access to healthcare services, such as monthly income and perceived social support. Need factors reflect both the perceived and evaluated need for medical care and include monthly medical expenses, body mass index (BMI), comorbid chronic conditions, disease duration, cognitive function scores, and activities of daily living (ADL). This theoretical framework guided the identification and classification of variables in the study and provided a conceptual basis for analyzing the determinants of health-seeking behavior among older adults with MCI (Fig. 1 ). 2 Methods 2.1 Study design and participants This study employed a cross-sectional design and a questionnaire-based survey to collect and evaluate data. The required sample size was estimated to be 5–10 times the number of independent variables. Given that 15 predictors were included (Tables 1 and 2 ), a minimum of 75–150 participants was required(Kline, 1991). A convenience sample of 253 older adults was recruited from two communities in Guangzhou, China, between September 2021 and March 2024. A total of 244 valid questionnaires were returned, yielding a completion rate of 96.4%. Inclusion criteria were: (1) a clinical diagnosis of MCI confirmed using standardized cognitive screening tools administered by trained professionals, ( 2 ) age ≥ 60 years, and ( 3 ) education level of primary school or above. Exclusion criteria were: (1) communication barriers; and ( 2 ) severe psychiatric disorders (e.g., major depression or bipolar disorder). Diagnostic information was obtained from participants’ medical records. 2.2 Measurements 2.2.1 Sociodemographic and health characteristics A self-developed demographic and health questionnaire was used to collect information on gender, age, education level, working status, marital status, dwelling status, caregiving for grandchildren under 18 years, perceived main symptoms, chances for diagnosis with MCI, the course of MCI, comorbid conditions etc (see Supplementary Material 1). 2.2.2 Healthcare-seeking behavior for older adults with mild cognitive impairment Based on Andersen’s Behavioral Model and and previous research on healthcare-seeking among older adults with MCI (Anderson, 1973; Kasper et al., 2020), a self-reported 8-item questionnaire was developed to assess healthcare-seeking behavior across four dimensions(Anderson, 1973) (see Supplementary Material 1): Symptom recognition behavior include whether older adults identify cognitive-related symptoms and their progression; medical treatment behavior refer to older adults’ actions regarding cognitive symptoms, including proactive visits to medical institutions due to cognitive symptoms and passive visits prompted by healthcare providers or community screenings; Standardized treatment behavior refer to standardized therapeutic actions taken by older adults for cognitive symptoms; self-care behavior at home encompass self-administered interventions for cognitive symptoms, including the use of health supplements and traditional Chinese medicine, the rationale behind such measures, and their perceived effectiveness. Content validity was evaluated by five experts (one neurologist specializing in Alzheimer’s disease, one neurology nurse, and three behavioral care researchers). After two rounds of expert consultation, the scale-level content validity index (S-CVI) of the measure was 1.0, indicating excellent content validity. 2.2.3 Global cognition function Global cognitive function was assessed using the Chinese versions of the Montreal Cognitive Assessment (MoCA). It has total scores ranging from 0–30, with higher scores indicating better cognition (Hughes et al., 2020). The MoCA evaluates naming, short-term memory, visuospatial ability, executive function, abstraction, attention, language, and orientation. It has a sensitivity of 90% for MCI and 100% for dementia(Nasreddine et al., 2005). A score < 26 indicates cognitive impairment, with one point added for participants with < 12 years of education(Nasreddine et al., 2005). 2.2.4 Knowledge about mild cognitive impairment Knowledge related to MCI was measured using the MCI Knowledge Questionnaire developed by Pan Huiying (Huiying, 2012). The questionnaire consisted of 20 items, divided into three parts: basic knowledge of cognitive impairment/MCI (4 items), knowledge of risk factors (8 items) and knowledge of disease prevention and treatment (8 items). Each item was scored 1 for correct and 0 for incorrect or missing responses. Total scores ranged from 0–20, with higher scores reflecting better knowledge. The questionnaire demonstrated good validity (CVI = 0.93) and reliability (Cronbach’s α = 0.85) in prior studies (Huiying, 2012), and Cronbach’s α = 0.71 in this study. 2.2.5 Social Support Rating Scale Social support was assessed using the Social Support Rating Scale (SSRS) developed by Xiao Shuiyuan(Shuiyuan, 1994), which is widely used to assess social support in the Chinese population(Lu et al., 2022; Yu et al., 2023; Zhou et al., 2023). The scale consists of 10 items, including objective support (3 items), subjective support (4 items) and utilization of social support (3 items). Higher total scores indicate stronger social support. The SSRS has demonstrated good reliability and validity in Chinese populations(Yu et al., 2015). The Cronbach’s α of the questionnaire was 0.689 in this pilot study. 2.2.6 Activities of daily living Activities of daily living (ADL) were measured using a 14-item ADL scale, consisting of 6 items on basic self-care and 8 items on instrumental activities(Qihao & Zhen, 2016). Each item was scored from 1 (“independent”) to 4 (“unable to perform”), with total scores ranging from 14 to 56. Higher scores indicate poorer functional ability. The ADL scale demonstrated good psychometric properties in the previous study (Yu et al., 2015). The Cronbach’s α of the questionnaire was 0.721 in this pilot study. 2.3 Data collection procedure Data were collected by four trained researchers. A clinical researcher provided additional explanations during data collection to ensure participant understanding and prevent item misinterpretation. 2.4 Statistical analysis Descriptive statistics were used to summarize sample characteristics and study variables. Continuous variables were expressed as mean ± standard deviation, and categorical variables as frequencies and percentages. Bivariate analyses (independent-sample t -tests and chi-square tests) were used to examine associations between health-seeking behavior and potential determinants. Binary logistic regression analyses were then conducted to identify independent predictors of each health-seeking behavior dimension (symptom recognition, medical treatment, standardized treatment, and self-care). All data analyses were performed using SPSS Version 25.0 (IBM Corp., Armonk, NY, USA). The significance level was set as a p value < 0.05. 3 Results 3.1 Sociodemographic and health characteristics Table 1 presents the sociodemographic and health characteristics of the participants. Among the 244 older adults with MCI, 59.4% were female, and 74.6% were married. Participants’ ages ranged from 60 to 93 years, with a mean age of 68.57 ± 6.30 years. Most participants lived with their spouse and children (62.3%) and engaged in regular physical exercise (83.6%). All participants had a clinical diagnosis of MCI, with a mean disease duration of 3.83 ± 3.09 years. The mean MoCA was18.95 ± 5.10. The majority of participants (80.3%) had at least one chronic disease, most commonly hypertension (52.0%) (Table 1 ). Table 1 Characteristics of the participants (n = 244) Items n ( % )/Mean ± SD/M (P25,75) Items n ( % )/Mean ± SD Sociodemographic characteristics Payment of medical expenses Gender Medical insurance 225(92.2) Male 99(40.6) Self-financed 19(7.8) Female 145(59.4) Monthly medical expenses (yuan) Age (years) (60–93 years) 68.57 ± 6.30 <1000 176(72.1) Educational level ≥ 1000 68(27.9) Primary school and below 81(33.2) The most frequently visited medical institution Secondary school 128(52.5) Community health center 67(27.5) Junior college 35(14.3) Level II or level III hospital 177(72.5) Working status Regular follow-up in medical institution Employed 26(10.7) No 147(60.2) Unemployed 218(89.3) Yes 97(39.8) Place of residence Smoking Urban 201(82.4) No 209(85.7) Rural 43(17.6) Yes 35(14.3) Marital status Drinking Married 182(74.6) No 216(88.5) Widowed, divorced or separated 62(25.4) Yes 28(11.5) Dwelling status Sleep disorders Living alone 24(9.8) No 130(53.3) Living with spouse 68(27.9) Yes 114(46.7) Living with spouse and kids 152(62.3) Exercise regularly Caring for grandchildren under 18 years No 40(16.4) No 151(61.9) Yes 204(83.6) Yes 93(38.1) Duration of prolonged sitting ③ (hours)/day 3.33 ± 2.15 Monthly income (yuan) 0 22(9.0) <2000 57(23.4) ~ 2.9 109(44.7) 2000~ 137(56.1) ~ 4.9 80(32.8) ≥ 6000 50(20.5) ~ 12 33(13.5) Time required to visit a medical institution ① (minutes) 22.5(10.0,30.0) Health characteristics 3~ 186(76.2) MoCA score 18.95 ± 5.10 40~ 20(8.2) Course of MCI (years) 3.83 ± 3.09 60 ~ 270 38(15.6) BMI(kg/m 2 ) (x ± s) 23.17 ± 3.32 The main transportation methods to medical institutions Other chronic diseases Public transportation vehicles ② 113(46.3) Hypertension 127(52.0) Driving 57(23.4) Cerebral infarction, cerebral hemorrhage 67(27.5) Walking 74(30.3) Diabetes mellitus 62(25.4) Is accompaniment required for medical treatment Coronary heart disease 36(14.8) No 159(65.2) Hyperlipidemia 21(8.6) Yes 85(34.8) None 48(19.7) Accompanying personnel Spouse 52(21.3) Children 36(14.8) Nanny 3(1.2) Note: ①The time required for older adults to reach their most frequently visited medical institution.②Including buses, subways and taxis. ③Including sitting quietly, watching TV, playing mahjong, and playing cards. ④Abbreviations: MCI, mild cognitive impairment; MoCA, Montreal Cognitive Assessment; BMI: body mass index. 3.2 Activities of daily living, mild cognitive impairment-related knowledge and social support Table 2 summarizes the results for activities of daily living (ADL), knowledge related to MCI, and social support. The mean ADL score was 14.87 ± 1.71, indicating relatively good functional ability. The mean MCI knowledge score was 11.77 ± 3.13, suggesting a moderate level of understanding regarding cognitive impairment. The mean social support score was 37.97 ± 6.59, reflecting generally good perceived social support (Table 2 ). Table 2 Health characteristics of the participants (n = 244) Items (Score range) n ( % )/Mean ± SD Items (Score range) n ( % )/Mean ± SD ADL score (14–56) 14.87 ± 1.71 Social support by SSRS (12 ~ 66) 37.97 ± 6.59 MCI-related knowledge (0–20) 11.77 ± 3.13 Objective support (1 ~ 22) 10.44 ± 2.08 Knowledge of symptoms (0–4) 2.50 ± 1.25 Subjective support (8 ~ 32) 21.32 ± 4.56 Knowledge of risk factors (0–8) 3.43 ± 1.78 Utilization of support (3 ~ 12) 6.20 ± 2.40 Knowledge of prevention and intervention (0–8) 5.84 ± 1.56 Note: ADL, activities of daily living scale. 3.3 Health-seeking behavior for older adults with mild cognitive impairment 3.3.1 Symptom recognition behavior Among 244 older adults with MCI, 100.00% reported memory impairment, 22.13% reported calculation impairment, and 8.61% reported orientation impairment (Table 3 ). Table 3 Symptom recognition behavior and utilization of healthcare services in older adults with mild cognitive impairment (n = 244) Items n ( % ) Duration of symptoms (years) M ( P 25, P 75) Perceived main symptoms Memory disorders 244(100.0) 3.00(2.00,5.13) Calculation barriers 54(22.1) 2.50(1.00,4.00) Orientation barriers 21(8.6) 1.92(0.79,3.00) Language barriers 7(2.9) 2.00(0.83,7.00) 3.3.2 Medical treatment behavior and standardized treatment behavior As illustrated in Fig. 2 , only 13.11% (n = 32) of participants sought medical attention proactively for cognitive impairment symptoms. More than half, 57.79% (n = 141), were diagnosed incidentally when healthcare providers identified cognitive decline during visits for other health conditions, while 29.10% (n = 71) were diagnosed through routine community-based screenings. In terms of diagnostic institutions, 70.08% (n = 171) were diagnosed in tertiary hospitals, whereas 29.92% (n = 73) were diagnosed at community health service centers. However, only 12.70% (n = 31) received standardized treatment from qualified medical personnel, primarily involving medication therapy (12.70%) and electrical stimulation or biofeedback therapy (4.10%). Notably, all participants who received standardized treatment (100.0%) reported a marked improvement in their self-rated health status. Note #This is a multiple-choice question. Ten older adults simultaneously underwent pharmacotherapy combined with electrical stimulation and biofeedback therapy. 3.3.3 Self-care behavior at home As shown in Fig. 3 , 25.41% (n = 62) of participants engaged in self-care behavior at home. The most common forms were self-administration of health supplements (n = 56) and traditional Chinese medicine (n = 6). Among these, 27.42% (n = 17) reported noticeable improvement in their self-perceived health status, while 1.61% (n = 1) reported a partial worsening. Note # Includes fish oil, omega-3, and vitamin D;*Includes Panax notoginseng, Codonopsis pilosula, Astragalus membranaceus, and Lycium chinensis. 3.4 Factors to health-seeking behavior for older adults with mild cognitive impairment The results of the t -tests and chi-square tests are presented in Table S1 , and the results of multivariate logistic regression analyses are summarized in Table 4 . For medical treatment behavior, older adults living in urban areas were more likely to actively seek medical treatment than those living in rural areas ( OR = 7.450, P = 0.010). In contrast, those whose medical expenses were covered by medical insurance were less likely to seek care compared with self-paying individuals ( OR = 0.260, P = 0.040). Participants diagnosed in tertiary hospitals were significantly more likely to seek medical treatment than those diagnosed in community health centers ( OR = 11.070, P = 0.020). However, higher recent MoCA scores-indicating better cognitive function-were associated with a lower likelihood of active medical consultation ( P = 0.001). For standardized treatment behavior, urban residents were more likely to receive standardized treatment than rural counterparts ( OR = 6.320, P = 0.020), and those diagnosed in tertiary hospitals were more likely to receive standardized treatment than those diagnosed in community facilities ( OR = 4.530, P = 0.050). Similarly, higher MoCA scores were negatively associated with the likelihood of receiving standardized treatment ( P < 0.001). For self-care behavior at home, male were less likely to engage in self-care behavior than female ( OR = 0.530, P = 0.050). Older adults with an education level of primary school or below were less likely to adopt self-care behavior compared with those with college or higher education ( OR = 0.350, P = 0.040). In addition, older adults who drove to medical institutions were less likely to perform self-care behavior than those who walked ( OR = 0.310, P = 0.010). Table 4 Multivariate analysis of the factors associated with health-seeking behavior of the participants (n = 244) Variables Reference \(\:\text{β}\) P OR 95% CI Medical treatment behavior Intercept -2.21 0.12 0.11 Place of residence Urban Rural 2.01 0.01 * 7.45 (1.52, 36.57) Payment of medical expenses Medical insurance Self-financed -1.34 0.04 * 0.26 (0.07, 0.94) Institutions of initial diagnosis of MCI Level III hospital Community health center 2.40 0.02 * 11.07 (1.42, 86.07) MoCA score -0.13 0.001 ** 0.88 (0.81, 0.95) Standardized treatment behavior Intercept -2.07 0.09 0.13 Place of residence Urban Rural 1.84 0.02 * 6.32 (1.36, 29.41) Institutions of initial diagnosis of MCI Level III hospital Community health center 1.51 0.05 * 4.53 (1.00, 20.45) MoCA score -0.16 < 0.001 *** 0.86 (0.79, 0.92) Self-care behavior at home Intercept -0.11 0.81 0.90 Gender Male Female -0.64 0.05 * 0.53 (0.28, 1.00) Educational level Primary school and below Junior college -1.04 0.04 * 0.35 (0.13, 0.94) Secondary school 0.03 0.94 1.03 (0.45, 2.36) The main transportation methods to medical institutions Public transportation vehicles Walking -0.52 0.12 0.59 (0.31, 1.15) Driving -1.19 0.01 * 0.31 (0.12, 0.79) Note: \(\:\beta\:\) : Partial regression coefficient; * P < 0.05, ** P < 0.01, *** P < 0.001; . OR : Odds Ratio; CI : Confidence Interval. Abbreviations: MCI, mild cognitive impairment. 4 Discussion This study examined health-seeking behavior among older adults with mild cognitive impairment (MCI), all of whom exhibited memory impairment. The findings revealed that proactive health-seeking behavior were relatively limited in this population: only 13.11% of participants sought medical consultation on their own initiative, 12.70% received standardized treatment, and 25.41% engaged in self-care behavior at home. Urban residence and diagnosis in tertiary hospitals were positively associated with both medical treatment behavior and standardized treatment behavior, suggesting that better healthcare accessibility and institutional capacity may facilitate medical engagement among MCI individuals. In contrast, higher MoCA scores were negatively associated with active consultation and standardized treatment, possibly reflecting a reduced perceived need for care among older adults with MCI. For self-care behavior, male gender, lower educational level, and driving as the main transportation meithod were associated with lower likelihood of engagement, indicating that self-management capacity may be constrained by both sociodemographic and behavioral factors. Although MCI-related knowledge, social support, and activities of daily living (ADL) were included in the analysis, none entered the final models, suggesting that their influence may be indirect or mediated by cognitive and contextual factors. The limited rates of proactive medical treatment and standardized treatment observed in this study are consistent with previous research showing that early-stage cognitive impairment often leads to under-recognition of symptoms and delayed medical contact(Jia et al., 2016; Jiao et al., 2023). Studies conducted in community populations have reported that most individuals with early cognitive decline are identified through passive screening rather than self-initiated consultation, largely due to limited awareness of MCI as a medical condition and the social normalization of mild forgetfulness among older adults(Jeyagurunathan et al., 2024; Mukadam et al., 2015). The strong influence of residence and healthcare institution type found here underscores the role of structural accessibility in shaping medical behavior(Kramer et al., 2025; Wiese et al., 2023). Urban residents benefit from higher medical literacy and closer proximity to specialized care, while tertiary hospitals are more likely to provide accurate diagnosis, follow-up guidance, and referral pathways, facilitating further medical engagement. The negative association between higher cognitive function and both consultation and standardized treatment behavior is noteworthy. Similar findings have been reported in studies suggesting that individuals with milder impairment may underestimate their symptoms or deny disease progression, thereby reducing their motivation to seek medical evaluation or adhere to prescribed treatment(Jeyagurunathan et al., 2024; Jiao et al., 2023). This highlights the importance of early education and cognitive screening programs targeting older adults with subjective memory complaints, to promote symptom recognition and timely intervention before cognitive decline advances. Moreover, the association between lower education level and reduced self-care behavior aligns with evidence that health literacy strongly influences self-management capacity, particularly in chronic and cognitive conditions(Chow et al., 2024; Mohammad et al., 2024). Gender differences observed in home-based self-intervention behavior may reflect disparities in health awareness and help-seeking tendencies, with women typically showing greater engagement in preventive health behavior. Although MCI-related knowledge, social support, and ADL did not independently predict healthcare behavior in this study, their potential indirect effects should not be overlooked. Previous studies have suggested that adequate social support can facilitate healthcare access and adherence by reducing psychological barriers and enhancing family involvement(Bartley et al., 2024; Jiao et al., 2023). Similarly, functional independence may affect the ability to comply with treatment recommendations or perform self-care tasks, particularly in older adults living alone(Silva et al., 2023). The nonsignificant results in this analysis may be due to limited variability in these factors or potential mediation through cognitive status and socioeconomic conditions. Future studies employing structural equation modeling or longitudinal designs could further clarify these pathways. Taken together, these findings highlight the need for targeted interventions to improve healthcare engagement among older adults with MCI. Enhancing public awareness of MCI, integrating cognitive screening into primary care, and establishing referral and follow-up systems across healthcare levels may help reduce diagnostic delays and improve treatment adherence. Tailored health education programs addressing cognitive awareness, gender differences, and health literacy should be developed to strengthen self-management behavior, particularly in rural populations and those with lower education levels. Several limitations of this study should be acknowledged. First, its cross-sectional design precludes causal inference regarding the relationships between cognitive status, contextual factors, and healthcare-related behavior. Longitudinal studies are needed to explore how these behavior evolve as cognitive decline progresses. Second, the sample was recruited from a limited geographic area, which may restrict generalizability to broader populations with different healthcare systems or cultural backgrounds. Third, all data on health behavior were self-reported, potentially introducing recall or social desirability bias, especially among participants with memory impairment. Fourth, some potentially relevant psychological factors, such as health beliefs, were not included and may further explain individual variations in healthcare engagement. Future research should incorporate longitudinal and mixed-method designs to examine behavioral trajectories, explore mediating mechanisms-such as health literacy-and evaluate the effectiveness of targeted interventions designed to enhance proactive healthcare-seeking and self-management among older adults with MCI. 5 Conclusions This study revealed that health-seeking behavior (including symptom recognition behavior, medical treatment behavior, standardized treatment behavior, and self-care behavior at home) among older adults with mild cognitive impairment (MCI) remain suboptimal. Only a small proportion of participants actively sought medical treatment, received standardized treatment, or engaged in self-care at home, indicating substantial gaps in symptom recognition and disease management. Both individual and contextual factors significantly influenced these behavior. Urban residence and diagnosis in tertiary hospitals were strong facilitators of medical treatment and standardized treatment engagement, whereas higher cognitive scores were negatively associated with such behavior. Additionally, gender, education level, and transportation methods affected self-care behavior at home, reflecting the role of socioeconomic and behavioral determinants. Although MCI-related knowledge, social support, and daily living ability did not independently predict health-seeking behavior, they may exert indirect or mediating effects. These findings underscore the urgent need for tailored interventions to improve early symptom recognition, strengthen health literacy, and promote accessible and continuous care for older adults with MCI, particularly in rural and low-education populations. Future studies should further explore behavioral trajectories and test targeted strategies to enhance proactive healthcare and self-management in this vulnerable group. Declarations Ethics approval and consent to participate This study was performed in accordance with the Declaration of Helsinki and have been approved by the Ethics Committee of the Sun Yat-sen Memorial Hospital (Ethical approval number: SYSEC-KY-KS-2020-009). Participation was voluntary, and the participants were informed of the research objectives and voluntary participation. In addition, informed consent was requested at the start of the questionnaire. Consent for publication Not applicable Availability of data and materials The datasets used and analysed during the current study are available from the corresponding author on reasonable request. Competing interests No conflict of interest has been declared by the authors. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors’ contributions ZDM: Research Design, Conceptualization, Project administration, Data curation, Writing-original draft, Writing-review & editing. MYR: Project administration, Data collection, Formal analysis, Writing-original draft. SR: Project administration, Data collection, Formal analysis. YYF: Data collection, Formal analysis. ZLF: Research Design, Conceptualization, Project administration, Data collection and curation, Formal analysis, Writing-original draft, Writing-review & editing. Acknowledgement We acknowledge all the participated the elderly for their cooperation in this study. We acknowledge AJE (https://secure.aje.com/login) for its linguistic assistance during the preparation of this manuscript. Clinical trial number Not applicable. References 2024). 2024 Alzheimer's disease facts and figures [Journal Article]. 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How does social support interact with intrinsic capacity to affect the trajectory of functional ability among older adults? Findings of a population-based longitudinal study [Journal Article]. Maturitas , 171, 33-39. http://doi.org/10.1016/j.maturitas.2023.03.005 Zhou, E., Ma, S., Kang, L., Zhang, N., Wang, P., Wang, W., Nie, Z., Chen, M., Xu, J., Sun, S., Yao, L., Xiang, D., & Liu, Z. (2023). Psychosocial factors associated with anxious depression [Journal Article; Research Support, Non-U.S. Gov't]. J Affect Disord , 322, 39-45. http://doi.org/10.1016/j.jad.2022.11.028 Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial1.docx SupplementaryMaterial2OnewayANOVA202503zlf1127.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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1","display":"","copyAsset":false,"role":"figure","size":242227,"visible":true,"origin":"","legend":"\u003cp\u003eTheoretical framework\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8220732/v1/67bab9a02ce7832f13f3861e.png"},{"id":98429233,"identity":"2f445645-8254-4dc8-af98-d84429cd666b","added_by":"auto","created_at":"2025-12-17 16:43:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":256165,"visible":true,"origin":"","legend":"\u003cp\u003eMedical treatment behavior and standardized treatment behavior among older adults with mild cognitive impairment (\u003cem\u003eN\u003c/em\u003e=244)\u003c/p\u003e\n\u003cp\u003eNote: #This is a multiple-choice question. Ten older adults simultaneously underwent pharmacotherapy combined with electrical stimulation and biofeedback therapy.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8220732/v1/f31b50ef8f582a070a37e8ed.png"},{"id":98428859,"identity":"2b7cf64a-a87d-4adb-99a9-88cdb491551e","added_by":"auto","created_at":"2025-12-17 16:42:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":229280,"visible":true,"origin":"","legend":"\u003cp\u003eSelf-care behavior at home among older adults with mild cognitive impairment (\u003cem\u003eN\u003c/em\u003e=244)\u003c/p\u003e\n\u003cp\u003eNote: # Includes fish oil, omega-3, and vitamin D；*Includes Panax notoginseng, Codonopsis pilosula, Astragalus membranaceus, and Lycium chinensis.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8220732/v1/71063c80718ebafc5819d395.png"},{"id":100687747,"identity":"1668195e-61e9-4d40-9ff9-cf0e19452c69","added_by":"auto","created_at":"2026-01-20 13:20:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2426604,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8220732/v1/fc05fa36-1fb5-45e0-b713-3c9b47fcdbf7.pdf"},{"id":98074682,"identity":"e4783206-3844-47b5-943c-bfc7ef9acb7f","added_by":"auto","created_at":"2025-12-12 13:28:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":39672,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8220732/v1/91fecb730dbea6a79bd3eecf.docx"},{"id":98427451,"identity":"2abd3a77-0859-41e0-910a-75d3b47c57ca","added_by":"auto","created_at":"2025-12-17 16:40:27","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":34100,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial2OnewayANOVA202503zlf1127.docx","url":"https://assets-eu.researchsquare.com/files/rs-8220732/v1/3016ca07cb539434e1799935.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Health-Seeking Behavior and Its Determinants Among Older Adults with Mild Cognitive Impairment: From Symptom Recognition to Self-Care","fulltext":[{"header":"1 Background","content":"\u003cp\u003eMild cognitive impairment (MCI) is a clinical diagnosis based on subjective cognitive decline, objective cognitive impairment, and relative preservation of activities of daily living(Bradfield, 2023). It may be established via clinical interview, collateral history from an informant, and psychometric examination(Bradfield, 2023). The number of people with dementia and MCI has rapidly increased in recent decades and related challenges have become a globe burden(Collaborators, 2022; Organization, 2025). In China, MCI affects over one-fourth of rural older adults(Cong et al., 2023). Evidence suggests that within a 5\u0026ndash;10 years period following a diagnosis of MCI due to Alzheimer\u0026rsquo;s disease, approximately 30% to 50% of individuals progress to Alzheimer\u0026rsquo;s dementia(2024). Specifically, up to 15% of people with amnestic MCI are estimated to develop Alzheimer\u0026rsquo;s dementia that period, with research suggesting that this subtype of MCI due to Alzheimer\u0026rsquo;s disease may increase the likelihood of progression to dementia(Dementia, 2021). The number of people with dementia reached 57\u0026nbsp;million worldwide in 2021, over 60% of whom live in low-and middle-income countries(Organization, 2025). Every year, there are nearly 10\u0026nbsp;million new cases(Organization, 2025). Caregivers of old people with dementia often report emotional, financial and physical difficulties. A total of eight drugs are available for the treatment of Alzheimer\u0026rsquo;s disease, and early health seeking shows promise in reducing the progression of MCI to dementia(2024).\u003c/p\u003e\u003cp\u003eHealth or care seeking behavior has been defined as any action undertaken by individuals who perceive themselves to have a health problem or to be ill in order to find an appropriate remedy(Ward et al., 1997). In this study, health-seeking behavior refers to all actions taken by older adults after the onset of disease symptoms, including symptom recognition, medical treatment, standardized treatment, and self-care at home. At present, there is no standardized instrument for measuring health-seeking behavior. Researchers typically determine the measurement dimensions based on the conceptual definition of health-seeking behavior and their specific research focus. Existing studies on health-seeking behavior have primarily examined delays in seeking care and their influencing factors, the care-seeking process, and the potential overuse of healthcare services after diagnosis(Du QH et al., 2024; Sun et al., 2021; Taghikhah et al., 2025). To address this gap, the present study developed a self-designed questionnaire to assess health-seeking behavior among older adults with MCI, covering four dimensions: symptom recognition behavior, medical treatment behavior, standardized treatment behavior, and self-care behavior at home.\u003c/p\u003e\u003cp\u003eHealth-seeking behavior is generally regarded as key to delay progression of MCI to dementia(Bradfield, 2023; Erickson et al., 2022). Pharmacological and non-pharmacological behavior are two approaches for improving cognitive function(2024). However, health-seeking behavior among older adults with MCI are generally suboptimal. Studies have shown that over 50% of people with cognitive impairment fail to receive medical evaluations for memory problems, and cannot make use of community resources when seeking help for memory problems (Ishiwata et al., 2014; Maslow \u0026amp; Fortinsky, 2018; Ross et al., 1997). Approximately 80% of Chinese diagnosed with dementia remain untreated by any medication(Jia et al., 2016). Only a small proportion of individuals with MCI actively seek medical evaluation or standardized treatment, while many are diagnosed incidentally through routine screening or during visits for other health problems(Wang et al., 2025). Several factors may contribute to this low rate of active health-seeking, including poor symptom recognition, limited awareness of MCI as a clinical condition, and the belief that memory decline is a normal part of aging(Hill et al., 2021; Jiao et al., 2023). In addition, barriers such as financial constraints, insufficient access to specialized medical services, and stigma related to cognitive decline further discourage older adults and their families from pursuing timely diagnosis and treatment(Hill et al., 2021; Jiao et al., 2023). As a result, many MCI individuals miss the critical window for early intervention, which may accelerate their progression to dementia.\u003c/p\u003e\u003cp\u003eTimely health-seeking behavior is essential to delay the progression of MCI to dementia. This study aims to investigate health-seeking behavior for older adults with MCI, encompassing symptom recognition, medical treatment, standardized treatment, and self-care at home. Additionally, it seeks to identify potential determinants, including sociodemographic and behavioral characteristics, knowledge of MCI, social support, and activities of daily living.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTheoretical framework\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAndersen\u0026rsquo;s Behavioral Model of Health Service Utilization is one of the most widely applied theoretical frameworks for understanding and predicting health-seeking behavior (Anderson, 1973). According to this model, healthcare utilization is determined by three major categories of factors: predisposing factors, enabling factors, and need factors(Anderson, 1973). In the present study, health-seeking behavior encompasses four dimensions: symptom recognition behavior, medical treatment behavior, standardized treatment behavior, and self-care behavior at home.\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003ePredisposing factors refer to the individual characteristics that influence the likelihood of seeking healthcare before the onset of illness. These include gender, age, education level, marital status, caregiving responsibilities for grandchildren under 18 years, and MCI-related knowledge.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eEnabling factors represent the resources that facilitate or impede access to healthcare services, such as monthly income and perceived social support.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eNeed factors reflect both the perceived and evaluated need for medical care and include monthly medical expenses, body mass index (BMI), comorbid chronic conditions, disease duration, cognitive function scores, and activities of daily living (ADL).\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThis theoretical framework guided the identification and classification of variables in the study and provided a conceptual basis for analyzing the determinants of health-seeking behavior among older adults with MCI (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"2 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study design and participants\u003c/h2\u003e\u003cp\u003eThis study employed a cross-sectional design and a questionnaire-based survey to collect and evaluate data. The required sample size was estimated to be 5\u0026ndash;10 times the number of independent variables. Given that 15 predictors were included (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), a minimum of 75\u0026ndash;150 participants was required(Kline, 1991). A convenience sample of 253 older adults was recruited from two communities in Guangzhou, China, between September 2021 and March 2024. A total of 244 valid questionnaires were returned, yielding a completion rate of 96.4%. Inclusion criteria were: (1) a clinical diagnosis of MCI confirmed using standardized cognitive screening tools administered by trained professionals, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) age\u0026thinsp;\u0026ge;\u0026thinsp;60 years, and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) education level of primary school or above. Exclusion criteria were: (1) communication barriers; and (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) severe psychiatric disorders (e.g., major depression or bipolar disorder). Diagnostic information was obtained from participants\u0026rsquo; medical records.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Measurements\u003c/h2\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.2.1 Sociodemographic and health characteristics\u003c/h2\u003e\u003cp\u003eA self-developed demographic and health questionnaire was used to collect information on gender, age, education level, working status, marital status, dwelling status, caregiving for grandchildren under 18 years, perceived main symptoms, chances for diagnosis with MCI, the course of MCI, comorbid conditions etc (see Supplementary Material 1).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2 Healthcare-seeking behavior for older adults with mild cognitive impairment\u003c/h2\u003e\u003cp\u003eBased on Andersen\u0026rsquo;s Behavioral Model and and previous research on healthcare-seeking among older adults with MCI (Anderson, 1973; Kasper et al., 2020), a self-reported 8-item questionnaire was developed to assess healthcare-seeking behavior across four dimensions(Anderson, 1973) (see Supplementary Material 1): Symptom recognition behavior include whether older adults identify cognitive-related symptoms and their progression; medical treatment behavior refer to older adults\u0026rsquo; actions regarding cognitive symptoms, including proactive visits to medical institutions due to cognitive symptoms and passive visits prompted by healthcare providers or community screenings; Standardized treatment behavior refer to standardized therapeutic actions taken by older adults for cognitive symptoms; self-care behavior at home encompass self-administered interventions for cognitive symptoms, including the use of health supplements and traditional Chinese medicine, the rationale behind such measures, and their perceived effectiveness. Content validity was evaluated by five experts (one neurologist specializing in Alzheimer\u0026rsquo;s disease, one neurology nurse, and three behavioral care researchers). After two rounds of expert consultation, the scale-level content validity index (S-CVI) of the measure was 1.0, indicating excellent content validity.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.2.3 Global cognition function\u003c/h2\u003e\u003cp\u003eGlobal cognitive function was assessed using the Chinese versions of the Montreal Cognitive Assessment (MoCA). It has total scores ranging from 0\u0026ndash;30, with higher scores indicating better cognition (Hughes et al., 2020). The MoCA evaluates naming, short-term memory, visuospatial ability, executive function, abstraction, attention, language, and orientation. It has a sensitivity of 90% for MCI and 100% for dementia(Nasreddine et al., 2005). A score\u0026thinsp;\u0026lt;\u0026thinsp;26 indicates cognitive impairment, with one point added for participants with \u0026lt;\u0026thinsp;12 years of education(Nasreddine et al., 2005).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.2.4 Knowledge about mild cognitive impairment\u003c/h2\u003e\u003cp\u003eKnowledge related to MCI was measured using the MCI Knowledge Questionnaire developed by Pan Huiying (Huiying, 2012). The questionnaire consisted of 20 items, divided into three parts: basic knowledge of cognitive impairment/MCI (4 items), knowledge of risk factors (8 items) and knowledge of disease prevention and treatment (8 items). Each item was scored 1 for correct and 0 for incorrect or missing responses. Total scores ranged from 0\u0026ndash;20, with higher scores reflecting better knowledge. The questionnaire demonstrated good validity (CVI\u0026thinsp;=\u0026thinsp;0.93) and reliability (Cronbach\u0026rsquo;s \u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.85) in prior studies (Huiying, 2012), and Cronbach\u0026rsquo;s \u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.71 in this study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.2.5 Social Support Rating Scale\u003c/h2\u003e\u003cp\u003eSocial support was assessed using the Social Support Rating Scale (SSRS) developed by Xiao Shuiyuan(Shuiyuan, 1994), which is widely used to assess social support in the Chinese population(Lu et al., 2022; Yu et al., 2023; Zhou et al., 2023). The scale consists of 10 items, including objective support (3 items), subjective support (4 items) and utilization of social support (3 items). Higher total scores indicate stronger social support. The SSRS has demonstrated good reliability and validity in Chinese populations(Yu et al., 2015). The Cronbach\u0026rsquo;s α of the questionnaire was 0.689 in this pilot study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.2.6 Activities of daily living\u003c/h2\u003e\u003cp\u003eActivities of daily living (ADL) were measured using a 14-item ADL scale, consisting of 6 items on basic self-care and 8 items on instrumental activities(Qihao \u0026amp; Zhen, 2016). Each item was scored from 1 (\u0026ldquo;independent\u0026rdquo;) to 4 (\u0026ldquo;unable to perform\u0026rdquo;), with total scores ranging from 14 to 56. Higher scores indicate poorer functional ability. The ADL scale demonstrated good psychometric properties in the previous study (Yu et al., 2015). The Cronbach\u0026rsquo;s α of the questionnaire was 0.721 in this pilot study.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Data collection procedure\u003c/h2\u003e\u003cp\u003eData were collected by four trained researchers. A clinical researcher provided additional explanations during data collection to ensure participant understanding and prevent item misinterpretation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistics were used to summarize sample characteristics and study variables. Continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, and categorical variables as frequencies and percentages. Bivariate analyses (independent-sample \u003cem\u003et\u003c/em\u003e-tests and chi-square tests) were used to examine associations between health-seeking behavior and potential determinants. Binary logistic regression analyses were then conducted to identify independent predictors of each health-seeking behavior dimension (symptom recognition, medical treatment, standardized treatment, and self-care). All data analyses were performed using SPSS Version 25.0 (IBM Corp., Armonk, NY, USA). The significance level was set as a \u003cem\u003ep\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Sociodemographic and health characteristics\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the sociodemographic and health characteristics of the participants. Among the 244 older adults with MCI, 59.4% were female, and 74.6% were married. Participants\u0026rsquo; ages ranged from 60 to 93 years, with a mean age of 68.57\u0026thinsp;\u0026plusmn;\u0026thinsp;6.30 years. Most participants lived with their spouse and children (62.3%) and engaged in regular physical exercise (83.6%). All participants had a clinical diagnosis of MCI, with a mean disease duration of 3.83\u0026thinsp;\u0026plusmn;\u0026thinsp;3.09 years. The mean MoCA was18.95\u0026thinsp;\u0026plusmn;\u0026thinsp;5.10. The majority of participants (80.3%) had at least one chronic disease, most commonly hypertension (52.0%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of the participants (n\u0026thinsp;=\u0026thinsp;244)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e(\u003cem\u003e%\u003c/em\u003e)/Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD/M\u003c/p\u003e\u003cp\u003e(P25,75)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e(\u003cem\u003e%\u003c/em\u003e)/Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSociodemographic characteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePayment of medical expenses\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMedical insurance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e225(92.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e99(40.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSelf-financed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19(7.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e145(59.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eMonthly medical expenses (yuan)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge (years) (60\u0026ndash;93 years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e68.57\u0026thinsp;\u0026plusmn;\u0026thinsp;6.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;1000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e176(72.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducational level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;1000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e68(27.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary school and below\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e81(33.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eThe most frequently visited medical institution\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e128(52.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCommunity health center\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e67(27.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJunior college\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35(14.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLevel II or level III hospital\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e177(72.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWorking status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eRegular follow-up in medical institution\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26(10.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e147(60.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e218(89.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e97(39.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePlace of residence\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e201(82.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e209(85.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43(17.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e35(14.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eDrinking\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e182(74.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e216(88.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWidowed, divorced or separated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e62(25.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28(11.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDwelling status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eSleep disorders\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiving alone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e24(9.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e130(53.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiving with spouse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e68(27.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e114(46.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiving with spouse and kids\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e152(62.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eExercise regularly\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCaring for grandchildren under 18 years\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40(16.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e151(61.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e204(83.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e93(38.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eDuration of prolonged sitting\u003c/b\u003e \u003csup\u003e\u003cb\u003e③\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e(hours)/day\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMonthly income (yuan)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22(9.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;2000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e57(23.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e~\u0026thinsp;2.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e109(44.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2000~\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e137(56.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e~\u0026thinsp;4.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e80(32.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;6000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e50(20.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e~\u0026thinsp;12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e33(13.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTime required to visit a medical institution\u003c/b\u003e\u003csup\u003e\u003cb\u003e①\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e(minutes)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22.5(10.0,30.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eHealth characteristics\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3~\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e186(76.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eMoCA score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.95\u0026thinsp;\u0026plusmn;\u0026thinsp;5.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e40~\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20(8.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eCourse of MCI (years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.83\u0026thinsp;\u0026plusmn;\u0026thinsp;3.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e60\u0026thinsp;~\u0026thinsp;270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e38(15.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eBMI(kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e) (x\u0026thinsp;\u0026plusmn;\u0026thinsp;s)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e23.17\u0026thinsp;\u0026plusmn;\u0026thinsp;3.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eThe main transportation methods to medical institutions\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eOther chronic diseases\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePublic transportation vehicles\u003csup\u003e②\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e113(46.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e127(52.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDriving\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e57(23.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCerebral infarction, cerebral hemorrhage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e67(27.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWalking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e74(30.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDiabetes mellitus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e62(25.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIs accompaniment required for medical treatment\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCoronary heart disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e36(14.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e159(65.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHyperlipidemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21(8.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e85(34.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e48(19.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAccompanying personnel\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpouse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e52(21.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChildren\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36(14.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNanny\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3(1.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: ①The time required for older adults to reach their most frequently visited medical institution.②Including buses, subways and taxis. ③Including sitting quietly, watching TV, playing mahjong, and playing cards. ④Abbreviations: MCI, mild cognitive impairment; MoCA, Montreal Cognitive Assessment; BMI: body mass index.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Activities of daily living, mild cognitive impairment-related knowledge and social support\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the results for activities of daily living (ADL), knowledge related to MCI, and social support. The mean ADL score was 14.87\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71, indicating relatively good functional ability. The mean MCI knowledge score was 11.77\u0026thinsp;\u0026plusmn;\u0026thinsp;3.13, suggesting a moderate level of understanding regarding cognitive impairment. The mean social support score was 37.97\u0026thinsp;\u0026plusmn;\u0026thinsp;6.59, reflecting generally good perceived social support (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHealth characteristics of the participants (n\u0026thinsp;=\u0026thinsp;244)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItems (Score range)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e(\u003cem\u003e%\u003c/em\u003e)/Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eItems (Score range)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e(\u003cem\u003e%\u003c/em\u003e)/Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eADL score (14\u0026ndash;56)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e14.87\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eSocial support by SSRS (12\u0026thinsp;~\u0026thinsp;66)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e37.97\u0026thinsp;\u0026plusmn;\u0026thinsp;6.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMCI-related knowledge (0\u0026ndash;20)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e11.77\u0026thinsp;\u0026plusmn;\u0026thinsp;3.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eObjective support (1\u0026thinsp;~\u0026thinsp;22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e10.44\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKnowledge of symptoms (0\u0026ndash;4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e2.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSubjective support (8\u0026thinsp;~\u0026thinsp;32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e21.32\u0026thinsp;\u0026plusmn;\u0026thinsp;4.56\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKnowledge of risk factors (0\u0026ndash;8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e3.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUtilization of support (3\u0026thinsp;~\u0026thinsp;12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e6.20\u0026thinsp;\u0026plusmn;\u0026thinsp;2.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKnowledge of prevention and intervention (0\u0026ndash;8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e5.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: ADL, activities of daily living scale.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Health-seeking behavior for older adults with mild cognitive impairment\u003c/h2\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003ch2\u003e3.3.1 Symptom recognition behavior\u003c/h2\u003e\u003cp\u003eAmong 244 older adults with MCI, 100.00% reported memory impairment, 22.13% reported calculation impairment, and 8.61% reported orientation impairment (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSymptom recognition behavior and utilization of healthcare services in older adults with mild cognitive impairment (n\u0026thinsp;=\u0026thinsp;244)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e(\u003cem\u003e%\u003c/em\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDuration of symptoms (years) \u003cem\u003eM\u003c/em\u003e(\u003cem\u003eP\u003c/em\u003e25,\u003cem\u003eP\u003c/em\u003e75)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerceived main symptoms\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMemory disorders\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e244(100.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.00(2.00,5.13)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCalculation barriers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e54(22.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.50(1.00,4.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrientation barriers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e21(8.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.92(0.79,3.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLanguage barriers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7(2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.00(0.83,7.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003e3.3.2 Medical treatment behavior and standardized treatment behavior\u003c/h2\u003e\u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, only 13.11% (n\u0026thinsp;=\u0026thinsp;32) of participants sought medical attention proactively for cognitive impairment symptoms. More than half, 57.79% (n\u0026thinsp;=\u0026thinsp;141), were diagnosed incidentally when healthcare providers identified cognitive decline during visits for other health conditions, while 29.10% (n\u0026thinsp;=\u0026thinsp;71) were diagnosed through routine community-based screenings. In terms of diagnostic institutions, 70.08% (n\u0026thinsp;=\u0026thinsp;171) were diagnosed in tertiary hospitals, whereas 29.92% (n\u0026thinsp;=\u0026thinsp;73) were diagnosed at community health service centers. However, only 12.70% (n\u0026thinsp;=\u0026thinsp;31) received standardized treatment from qualified medical personnel, primarily involving medication therapy (12.70%) and electrical stimulation or biofeedback therapy (4.10%). Notably, all participants who received standardized treatment (100.0%) reported a marked improvement in their self-rated health status.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003cp\u003e#This is a multiple-choice question. Ten older adults simultaneously underwent pharmacotherapy combined with electrical stimulation and biofeedback therapy.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\u003ch2\u003e3.3.3 Self-care behavior at home\u003c/h2\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, 25.41% (n\u0026thinsp;=\u0026thinsp;62) of participants engaged in self-care behavior at home. The most common forms were self-administration of health supplements (n\u0026thinsp;=\u0026thinsp;56) and traditional Chinese medicine (n\u0026thinsp;=\u0026thinsp;6). Among these, 27.42% (n\u0026thinsp;=\u0026thinsp;17) reported noticeable improvement in their self-perceived health status, while 1.61% (n\u0026thinsp;=\u0026thinsp;1) reported a partial worsening.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003cp\u003e# Includes fish oil, omega-3, and vitamin D;*Includes Panax notoginseng, Codonopsis pilosula, Astragalus membranaceus, and Lycium chinensis.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Factors to health-seeking behavior for older adults with mild cognitive impairment\u003c/h2\u003e\u003cp\u003eThe results of the \u003cem\u003et\u003c/em\u003e-tests and chi-square tests are presented in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, and the results of multivariate logistic regression analyses are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eFor medical treatment behavior, older adults living in urban areas were more likely to actively seek medical treatment than those living in rural areas (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7.450, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010). In contrast, those whose medical expenses were covered by medical insurance were less likely to seek care compared with self-paying individuals (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.260, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.040). Participants diagnosed in tertiary hospitals were significantly more likely to seek medical treatment than those diagnosed in community health centers (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;11.070, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020). However, higher recent MoCA scores-indicating better cognitive function-were associated with a lower likelihood of active medical consultation (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eFor standardized treatment behavior, urban residents were more likely to receive standardized treatment than rural counterparts (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.320, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020), and those diagnosed in tertiary hospitals were more likely to receive standardized treatment than those diagnosed in community facilities (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.530, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.050). Similarly, higher MoCA scores were negatively associated with the likelihood of receiving standardized treatment (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eFor self-care behavior at home, male were less likely to engage in self-care behavior than female (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.530, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.050). Older adults with an education level of primary school or below were less likely to adopt self-care behavior compared with those with college or higher education (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.350, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.040). In addition, older adults who drove to medical institutions were less likely to perform self-care behavior than those who walked (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.310, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultivariate analysis of the factors associated with health-seeking behavior of the participants (n\u0026thinsp;=\u0026thinsp;244)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026beta;}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMedical treatment behavior\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntercept\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePlace of residence\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.01\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e(1.52, 36.57)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePayment of medical expenses\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedical insurance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSelf-financed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.04\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e(0.07, 0.94)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eInstitutions of initial diagnosis of MCI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLevel III hospital\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCommunity health center\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e(1.42, 86.07)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMoCA score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e(0.81, 0.95)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eStandardized treatment behavior\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntercept\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePlace of residence\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e(1.36, 29.41)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eInstitutions of initial diagnosis of MCI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLevel III hospital\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCommunity health center\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.05\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e(1.00, 20.45)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMoCA score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e(0.79, 0.92)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSelf-care behavior at home\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntercept\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.05\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e(0.28, 1.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducational level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary school and below\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJunior college\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.04\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e(0.13, 0.94)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e(0.45, 2.36)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eThe main transportation methods to medical institutions\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePublic transportation vehicles\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWalking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e(0.31, 1.15)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDriving\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.01\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e(0.12, 0.79)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\beta\\:\\)\u003c/span\u003e\u003c/span\u003e: Partial regression coefficient; *\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; .\u003cem\u003eOR\u003c/em\u003e: Odds Ratio; \u003cem\u003eCI\u003c/em\u003e: Confidence Interval. Abbreviations: MCI, mild cognitive impairment.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThis study examined health-seeking behavior among older adults with mild cognitive impairment (MCI), all of whom exhibited memory impairment. The findings revealed that proactive health-seeking behavior were relatively limited in this population: only 13.11% of participants sought medical consultation on their own initiative, 12.70% received standardized treatment, and 25.41% engaged in self-care behavior at home. Urban residence and diagnosis in tertiary hospitals were positively associated with both medical treatment behavior and standardized treatment behavior, suggesting that better healthcare accessibility and institutional capacity may facilitate medical engagement among MCI individuals. In contrast, higher MoCA scores were negatively associated with active consultation and standardized treatment, possibly reflecting a reduced perceived need for care among older adults with MCI. For self-care behavior, male gender, lower educational level, and driving as the main transportation meithod were associated with lower likelihood of engagement, indicating that self-management capacity may be constrained by both sociodemographic and behavioral factors. Although MCI-related knowledge, social support, and activities of daily living (ADL) were included in the analysis, none entered the final models, suggesting that their influence may be indirect or mediated by cognitive and contextual factors.\u003c/p\u003e\u003cp\u003eThe limited rates of proactive medical treatment and standardized treatment observed in this study are consistent with previous research showing that early-stage cognitive impairment often leads to under-recognition of symptoms and delayed medical contact(Jia et al., 2016; Jiao et al., 2023). Studies conducted in community populations have reported that most individuals with early cognitive decline are identified through passive screening rather than self-initiated consultation, largely due to limited awareness of MCI as a medical condition and the social normalization of mild forgetfulness among older adults(Jeyagurunathan et al., 2024; Mukadam et al., 2015). The strong influence of residence and healthcare institution type found here underscores the role of structural accessibility in shaping medical behavior(Kramer et al., 2025; Wiese et al., 2023). Urban residents benefit from higher medical literacy and closer proximity to specialized care, while tertiary hospitals are more likely to provide accurate diagnosis, follow-up guidance, and referral pathways, facilitating further medical engagement.\u003c/p\u003e\u003cp\u003eThe negative association between higher cognitive function and both consultation and standardized treatment behavior is noteworthy. Similar findings have been reported in studies suggesting that individuals with milder impairment may underestimate their symptoms or deny disease progression, thereby reducing their motivation to seek medical evaluation or adhere to prescribed treatment(Jeyagurunathan et al., 2024; Jiao et al., 2023). This highlights the importance of early education and cognitive screening programs targeting older adults with subjective memory complaints, to promote symptom recognition and timely intervention before cognitive decline advances. Moreover, the association between lower education level and reduced self-care behavior aligns with evidence that health literacy strongly influences self-management capacity, particularly in chronic and cognitive conditions(Chow et al., 2024; Mohammad et al., 2024). Gender differences observed in home-based self-intervention behavior may reflect disparities in health awareness and help-seeking tendencies, with women typically showing greater engagement in preventive health behavior.\u003c/p\u003e\u003cp\u003eAlthough MCI-related knowledge, social support, and ADL did not independently predict healthcare behavior in this study, their potential indirect effects should not be overlooked. Previous studies have suggested that adequate social support can facilitate healthcare access and adherence by reducing psychological barriers and enhancing family involvement(Bartley et al., 2024; Jiao et al., 2023). Similarly, functional independence may affect the ability to comply with treatment recommendations or perform self-care tasks, particularly in older adults living alone(Silva et al., 2023). The nonsignificant results in this analysis may be due to limited variability in these factors or potential mediation through cognitive status and socioeconomic conditions. Future studies employing structural equation modeling or longitudinal designs could further clarify these pathways.\u003c/p\u003e\u003cp\u003eTaken together, these findings highlight the need for targeted interventions to improve healthcare engagement among older adults with MCI. Enhancing public awareness of MCI, integrating cognitive screening into primary care, and establishing referral and follow-up systems across healthcare levels may help reduce diagnostic delays and improve treatment adherence. Tailored health education programs addressing cognitive awareness, gender differences, and health literacy should be developed to strengthen self-management behavior, particularly in rural populations and those with lower education levels.\u003c/p\u003e\u003cp\u003eSeveral limitations of this study should be acknowledged. First, its cross-sectional design precludes causal inference regarding the relationships between cognitive status, contextual factors, and healthcare-related behavior. Longitudinal studies are needed to explore how these behavior evolve as cognitive decline progresses. Second, the sample was recruited from a limited geographic area, which may restrict generalizability to broader populations with different healthcare systems or cultural backgrounds. Third, all data on health behavior were self-reported, potentially introducing recall or social desirability bias, especially among participants with memory impairment. Fourth, some potentially relevant psychological factors, such as health beliefs, were not included and may further explain individual variations in healthcare engagement. Future research should incorporate longitudinal and mixed-method designs to examine behavioral trajectories, explore mediating mechanisms-such as health literacy-and evaluate the effectiveness of targeted interventions designed to enhance proactive healthcare-seeking and self-management among older adults with MCI.\u003c/p\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eThis study revealed that health-seeking behavior (including symptom recognition behavior, medical treatment behavior, standardized treatment behavior, and self-care behavior at home) among older adults with mild cognitive impairment (MCI) remain suboptimal. Only a small proportion of participants actively sought medical treatment, received standardized treatment, or engaged in self-care at home, indicating substantial gaps in symptom recognition and disease management. Both individual and contextual factors significantly influenced these behavior. Urban residence and diagnosis in tertiary hospitals were strong facilitators of medical treatment and standardized treatment engagement, whereas higher cognitive scores were negatively associated with such behavior. Additionally, gender, education level, and transportation methods affected self-care behavior at home, reflecting the role of socioeconomic and behavioral determinants. Although MCI-related knowledge, social support, and daily living ability did not independently predict health-seeking behavior, they may exert indirect or mediating effects. These findings underscore the urgent need for tailored interventions to improve early symptom recognition, strengthen health literacy, and promote accessible and continuous care for older adults with MCI, particularly in rural and low-education populations. Future studies should further explore behavioral trajectories and test targeted strategies to enhance proactive healthcare and self-management in this vulnerable group.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in accordance with the Declaration of Helsinki and have been approved by the Ethics Committee of the Sun Yat-sen Memorial Hospital (Ethical approval number: SYSEC-KY-KS-2020-009). Participation was voluntary, and the participants were informed of the research objectives and voluntary participation. In addition, informed consent was requested at the start of the questionnaire.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo conflict of interest has been declared by the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZDM: Research Design, Conceptualization, Project administration, Data curation, Writing-original draft, Writing-review \u0026amp; editing. MYR: Project administration, Data collection, Formal analysis, Writing-original draft. SR: Project administration, Data collection, Formal analysis. YYF:\u0026nbsp;Data collection, Formal analysis. ZLF: Research Design, Conceptualization, Project administration, Data collection and curation, Formal analysis, Writing-original draft, Writing-review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge all the participated the elderly for their cooperation in this study.\u003c/p\u003e\n\u003cp\u003eWe acknowledge AJE (https://secure.aje.com/login) for its linguistic assistance during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003e2024). 2024 Alzheimer's disease facts and figures [Journal Article]. \u003cem\u003eAlzheimers \u0026amp; Dementia\u003c/em\u003e, 20(5), 3708-3821. http://doi.org/10.1002/alz.13809\u003c/p\u003e\n\u003cp\u003eAnderson, J. G. (1973). 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Psychosocial factors associated with anxious depression [Journal Article; Research Support, Non-U.S. Gov't]. \u003cem\u003eJ Affect Disord\u003c/em\u003e, 322, 39-45. http://doi.org/10.1016/j.jad.2022.11.028\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"older adults, mild cognitive impairment, health-seeking behavior","lastPublishedDoi":"10.21203/rs.3.rs-8220732/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8220732/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eMild cognitive impairment (MCI) is a transitional stage between normal aging and dementia, where timely recognition and appropriate health-seeking behavior may help delay cognitive decline. Although both pharmacological and non-pharmacological interventions show potential benefits, the utilization of healthcare services among older adults with MCI remains inadequate. This study examined health-seeking behavior-including symptom recognition, medical treatment, standardized treatment, and self-care at home-its determinants, and potential strategies to promote proactive care-seeking.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA cross-sectional survey was conducted among community-dwelling older adults diagnosed with MCI. Health-seeking behavior was assessed using a structured questionnaire based on Andersen\u0026rsquo;s Behavioral Model. Data on MCI-related knowledge, social support, activities of daily living (ADL), and sociodemographic and health characteristics were also collected. Descriptive statistics summarized participant characteristics and behavioral patterns. Independent-samples \u003cem\u003et\u003c/em\u003e tests and chi-square tests examined group differences, and variables significant at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were entered into multivariate logistic regression models to identify determinants of each behavior type.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA total of 244 older adults with MCI were included. Only 13.1% actively sought medical treatment, while most were diagnosed passively during clinical visits or community screening. Standardized treatment was reported in 12.7%, and 25.4% engaged in self-care at home. Urban residence, medical payment method, diagnosing institution, and MoCA scores were significantly associated with medical treatment behavior. Urban residents were more likely to seek care (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7.45, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01), while individuals using medical insurance were less likely to do so compared with self-paying participants (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.26, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04). Participants diagnosed in tertiary hospitals were more likely to seek treatment (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;11.07, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02), whereas higher MoCA scores were negatively associated with medical consultation (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). Similar patterns were observed for standardized treatment. For self-care behavior, gender, education level, and transportation mode were key predictors.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eHealth-seeking behavior among older adults with MCI remains suboptimal, with very low rates of active care-seeking and standardized treatment adherence. Urban-rural disparities, cognitive status, healthcare accessibility, and socioeconomic characteristics significantly influence behavioral patterns. Targeted health education, community-based cognitive screening, and supportive healthcare policies are urgently needed to improve early recognition, diagnosis, and long-term management of MCI, potentially delaying its progression to dementia.\u003c/p\u003e","manuscriptTitle":"Health-Seeking Behavior and Its Determinants Among Older Adults with Mild Cognitive Impairment: From Symptom Recognition to Self-Care","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-12 13:28:18","doi":"10.21203/rs.3.rs-8220732/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"54439bf2-e8eb-4d88-8b7a-c07dda1f812d","owner":[],"postedDate":"December 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-20T11:12:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-12 13:28:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8220732","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8220732","identity":"rs-8220732","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}