Validation and Reliability Testing of the Yonsei Lifestyle Profile for Assessing Multifaceted Health Lifestyles
ABSTRACT
Background
In this study, we aimed to validate and test the reliability of the Yonsei lifestyle profile (YLP) in assessing multifaceted health lifestyle levels in a study population from the United States.
Methods
The YLP-English version and health-promoting lifestyle profile II were administered to 100 individuals living in the United States. Concurrent validity was analyzed using Pearson's correlation coefficient, and discriminant validity was examined by comparing sex and age differences through t-tests and multiple variance analysis. Internal consistency was assessed using Cronbach's α for each sub-factor.
Results
The YLP-English Version demonstrated concurrent validity with the Health-Promoting Lifestyle Profile II, showing consistent correlations for the total score (0.3, p < 0.01) and frequency sub-factors (0.25–0.69, p < 0.01). Among the satisfaction sub-factors, only nutrition showed a weak negative correlation (−0.19, p < 0.01); all others were nonsignificant. Discriminant validity revealed no significant sex differences, but physical activity frequency varied across age groups. Internal consistency was high (Cronbach's α = 0.80–0.86).
Conclusion
In this study, we validated the YLP-English version as a reliable instrument for assessing health-related lifestyle behaviors. The YLP uniquely captures both lifestyle frequency and satisfaction, offering a comprehensive perspective on health behaviors. Although this tool is currently most applicable in population-level studies, future research should establish clinical thresholds to enhance its utility in individualized health assessments and interventions.
Abbreviations
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- HPLP-II
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- health-promoting lifestyle profile II
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- MANOVA
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- multivariate analysis of variance
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- YLP
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- Yonsei lifestyle profile
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- USA
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- the United States of America
1 Introduction
In the context of biological aging, maintaining health and quality of life is recognized as a critical issue as humans experience aging [1]. With rapid aging of the global population, public health concerns and strategies are increasingly focused on sustaining and improving health and quality of life [2]. Consequently, lifestyle factors are being emphasized, such as diet, physical activity, and abstinence from alcohol and smoking, as these can be helpful in preventing non-communicable diseases and reducing risk factors [3].
Lifestyle factors that determine health include habitual behaviors such as physical activity, diet, alcohol consumption, smoking, sleep, and social participation [4]. Methods for assessing an individual's lifestyle aim to objectively and quantitatively capture the presence and frequency of health-related behaviors and factors [5]. These lifestyle assessments focus on interpreting behaviors and factors as being healthy or unhealthy.
In the field of health sciences, there is a recognized need for precise measurement of the complex characteristics of lifestyle factors [6-8]. Studies measuring lifestyle use self-developed questionnaires or standardized tools that include health-related factors [5]. However, because lifestyle factors involve deliberate patterns of behavior rather than random actions, comprehensive tools that are capable of measuring and understanding multifaceted lifestyles are limited [9].
The Yonsei Lifestyle Profile (YLP) is an assessment tool used to measure multifaceted health lifestyles [10]. Developed by a panel of health care professionals in Korea using a modified Delphi method, this tool comprises 60 items categorized into three domains: physical activity, participation in activities, and diet. The YLP has been content-validated by health care experts with a sociocultural background in the United States, yielding values of 0.86 for the construct validity ratio, 0.17 for stability, 0.38 for convergence, and 0.80 for consensus [11]. However, considering the cultural, environmental, and behavioral differences that influence lifestyle assessment, further validation of the psychometric properties of the YLP-English Version is needed to ensure its accuracy in capturing multidimensional lifestyle patterns. Additionally, further research is required to evaluate the effectiveness of this tool in measuring lifestyle factors within the United States of America (USA) population and to confirm its consistency with existing assessment tools across different demographic groups.
In this study, we aimed to validate and verify the reliability of the English version of the YLP in assessing healthy lifestyles in a USA population. By confirming the validity and stability of the tool, this study can provide valuable information for health-related research and clinical applications.
2 Methods
2.1 Study Design
This cross-sectional survey was designed to validate the concurrent validity and reliability of the English version of the YLP for measuring healthy lifestyles in the USA population. The overall study procedure is summarized in Graphical Abstract.
2.2 Participants
To ensure ethical compliance, this study was conducted with approval from the Institutional Review Board of a regional Yonsei University (Approval Numbers: 1041849-202404-SB-090-02 and 1041849-202406-SB-136-01). Participants were selected using non-probability sampling from a panel registered with the online professional research organization Macromill Embrain (https://embrain.com/). The criteria for participation in the online survey included the following: (i) USA citizen (nationwide); (ii) adults aged 18 and 69 years and above; (iii) individuals capable of using online/Internet services; (iv) individuals capable of reading and writing; (v) individuals who consented to participate in this study. The online survey was conducted from June 10 to 15, 2024, with data collected from 100 participants. The minimum sample size was determined through statistical power analysis to meet the analytical requirements. We found that 10–20 participants per group were needed in multiple variance analysis (MANOVA) [12], and 85–100 participants were needed in correlation analysis for a moderate effect size with 80% power at α = 0.05 [13]. Additionally, a minimum sample size of 100 was deemed appropriate for Cronbach's α analysis [14]. Thus, 100 participants were recruited to satisfy both criteria and ensure analytical robustness.
2.3 Data Collection
2.3.1 Yonsei Lifestyle Profile—English Version
The YLP was developed to assess the health lifestyles of older adults in a regional community [10]. The YLP evaluates health-related daily behaviors across three sub-domains: physical activity, participation in social activities, and dietary habits. Participants were selected using non-probability sampling from a panel registered. For the subfactors, physical activity and participation in activities include responses on frequency, duration, and satisfaction with each element; dietary habits are structured around the five major nutrients. The assessment comprises 60 items: 18 items across six concepts for physical activity, 17 items across six concepts for participation in activities, and 25 items for dietary habits. Responses are given on a 5-point Likert scale ranging from 5=Very often (much more than desired) to 1=Very seldom (much less than desired). Higher scores on all sub-factors indicate a healthier lifestyle. This study used the YLP-English Version, which has been validated for content relevance by reflecting the linguistic and cultural characteristics of USA society, to expand application of the YLP to the USA population. The YLP-English Version is confirmed to have a construct validity ratio of 0.86, stability of 0.17, convergence of 0.38, and consensus of 0.80 [11] (Supporting Information S1).
2.3.2 Health-Promoting Lifestyle Profile II
The health-promoting lifestyle profile II (HPLP-II) is a self-reported assessment tool used to measure the extent of health-promoting behaviors in adults [15]. As a standardized instrument, it has been extensively applied in public health and epidemiological research, particularly in chronic disease prevention and health behavior studies [16, 17]. Given its established validity in assessing lifestyle factors [18, 19], we used the HPLP-II as a comparative tool to evaluate the concurrent validity of the YLP-English Version. The HPLP-II categorizes health-promoting behaviors into six subdomains: nutrition, physical activity, health responsibility, stress management, spiritual growth, and interpersonal relationships. The assessment comprises 52 items, with responses measured on a 4-point Likert scale ranging from “routinely” (4 points) to “never” (1 point). Higher scores indicate a greater degree of engagement in health-promoting lifestyles. The HPLP-II has demonstrated convergent validity with the Personal Lifestyle Questionnaire (r = 0.678) and has a high internal consistency, with a Cronbach's α value of 0.94 [15].
2.4 Data Analysis
The collected data were analyzed using SAS version 7.4 (SAS Institute Inc., Cary, North Carolina, USA) to determine the general characteristics and descriptive statistics of each assessment tool and evaluate concurrent validity and reliability. The concurrent validity of the YLP and HPLP-II was assessed using Pearson's correlation coefficients in correlation analysis. Interpretation of the correlation coefficients for concurrent validity was based on the following scale: very weak (0.0–0.10), weak (0.10–0.39), moderate (0.40–0.69), strong (0.70–0.89), and very strong (0.90–1.0) [20]. Discriminant validity was examined by comparing raw scores by sex and age group [21]. Sex differences were analyzed using t-tests whereas age group comparisons were conducted using MANOVA, followed by post-hoc tests (Scheffé). Internal consistency for reliability was assessed by calculating Cronbach's α, with values above 0.08 indicating very good reliability and values between 0.07 and 0.08 indicating good reliability [22].
3 Results
3.1 Sample Characteristics
The demographic characteristics of study participants are shown in Table 1. This study included 100 participants (50 men and 50 women). The average participant age was approximately 44.4 years (standard deviation [SD] = 13.84). The participants were evenly distributed across different age groups, each representing 20% of the total sample. Most participants resided in mid-sized cities (N = 39, 39%), had 15–16 years of education (N = 38, 38%), and were employed (N = 63, 63%).
Variable | N (%) | Variable | N (%) |
---|---|---|---|
Sex (male) | 50 (50) | Educational level | |
Age (years) | 44.4 (13.84)a | Less than 12 | 5 (5) |
18–29 | 20 (20) | 12 | 16 (16) |
30–39 | 20 (20) | 13–14 | 24 (24) |
40–49 | 20 (20) | 15–16 | 38 (38) |
50–59 | 20 (20) | 17–18 | 13 (13) |
60–69 | 20 (20) | 18 years or more | 4 (4) |
Residence | Employment status | ||
Metropolitan area | 37 (37) | Currently employed | 63 (63) |
Mid-sized city | 39 (39) | Unemployed | 6 (6) |
Small town | 11 (11) | Retired | 18 (18) |
Rural area | 13 (13) | Self-employed | 9 (9) |
Other | 4 (4) |
- a Variables are described using mean and standard deviation.
3.2 YLP Characteristics
The characteristics of the YLP are listed in Table 2. The mean total score was 3.17 (SD = 0.57). The mean score on the frequency domain of the YLP was 2.84 (SD = 0.54) and that of the satisfaction domain was 3.48 (SD = 0.97).
Mean ± SD | |
---|---|
Total | 3.17 ± 0.57 |
Frequency | 2.86 ± 0.54 |
Physical activity | 2.61 ± 0.81 |
Activity participation | 2.89 ± 0.73 |
Nutrition | 3.08 ± 0.55 |
Satisfaction | 3.48 ± 0.97 |
Physical activity | 3.41 ± 1.21 |
Activity participation | 3.38 ± 1.17 |
Nutrition | 3.64 ± 1.08 |
3.3 Concurrent Validity
Concurrent validity was evaluated through correlation analysis by comparing YLP and HPLP-II scores (Table 3). The YLP and HPLP-II total average scores were significantly and weakly correlated (0.30, p < 0.01). Most frequency domains of the YLP and factors of the frequency domain were significantly correlated with the HPLP-II, ranging from weak to moderate correlations. However, most satisfaction domains of the YLP were not significantly correlated with the HPLP-II.
Total average score of HPLP-II | Health responsibility domain of HPLP-II | Physical activity domain of HPLP-II | Nutrition domain of HPLP-II | Spiritual growth domain of HPLP-II | Interpersonal relations domain of HPLP-II | Stress management domain of HPLP-II | |
---|---|---|---|---|---|---|---|
YLP total | 0.30** | 0.10 | 0.29** | 0.25** | 0.31** | 0.30** | 0.33*** |
Frequency | 0.69*** | 0.53*** | 0.69*** | 0.59*** | 0.55*** | 0.59*** | 0.62*** |
Physical activity | 0.60*** | 0.51*** | 0.69*** | 0.59*** | 0.35*** | 0.43*** | 0.47*** |
Activity participation | 0.36*** | 0.15 | 0.32*** | 0.29** | 0.35*** | 0.4*** | 0.39*** |
Nutrition | 0.58*** | 0.53*** | 0.50*** | 0.45*** | 0.51*** | 0.47*** | 0.52*** |
Satisfaction | 0.02 | −0.14 | 0.02 | 0.01 | 0.10 | 0.06 | 0.08 |
Physical activity | 0.05 | −0.10 | 0.11 | 0.01 | 0.11 | 0.07 | 0.07 |
Activity participation | 0.08 | −0.06 | −0.01 | 0.04 | 0.16 | 0.11 | 0.16 |
Nutrition | −0.07 | −0.19* | −0.08 | −0.03 | 0.01 | −0.02 | 0.00 |
- Abbreviations: HPLP-II, health-promoting lifestyle profile II; YLP, Yonsei lifestyle profile.
- * p < 0.05
- ** p < 0.01
- *** p < 0.001.
3.4 Discriminant Validity
Regarding discriminant validity by sex, there were no significant differences in the total score, domains, or factors of the YLP (Table 4). Before analyzing discriminant validity by age group, we conducted Box's M test and Levene's test to confirm variances across all age groups. The results of Box's M test indicated unequal covariance matrices (Box's M = 147.20, F = 1.50; p < 0.01); however, Levene's test confirmed equal variances across all age groups (p > 0.05).
Male | Female | t | p | |
---|---|---|---|---|
Total | 3.17 ± 0.56 | 3.16 ± 0.59 | 0.12 | 0.90 |
Frequency | 2.88 ± 0.46 | 2.84 ± 0.60 | 0.38 | 0.70 |
Physical activity | 2.70 ± 0.65 | 2.51 ± 0.93 | 1.15 | 0.25 |
Activity participation | 2.87 ± 0.70 | 2.92 ± 0.76 | −0.32 | 0.75 |
Nutrition | 3.07 ± 0.55 | 3.08 ± 0.55 | −0.13 | 0.89 |
Satisfaction | 3.47 ± 0.1.02 | 3.48 ± 0.94 | −0.07 | 0.95 |
Physical activity | 3.57 ± 1.08 | 3.25 ± 1.31 | 1.30 | 0.19 |
Activity participation | 3.34 ± 1.19 | 3.41 ± 1.15 | −0.31 | 0.76 |
Nutrition | 3.50 ± 1.17 | 3.78 ± 0.96 | −1.30 | 0.20 |
- Abbreviation: YLP, Yonsei lifestyle profile.
Subsequently, the results of MANOVA indicated significant differences among age groups (18–20s, 30s, 40s, 50s, 60s, and above) in YLP scores (Wilks' lambda value = 0.62; F value = 1.94; p < 0.01; Table 5). Specifically, the frequency domain (F = 2.56, p < 0.05) and physical activity factor of the frequency subdomain (F = 4.45, p < 0.01) showed significant age differences; none of the satisfaction domains and factors exhibited significant differences. Post-hoc analysis revealed that individuals in their 30s scored significantly higher than those in their 60s and older on the physical activity subfactors of the frequency domain.
Age group | F | ηp2 | Post-hoc | |||||
---|---|---|---|---|---|---|---|---|
10–20 s | 30 s | 40 s | 50 s | 60 s | ||||
Total | 3.21 ± 0.66 | 3.16 ± 0.38 | 3.17 ± 0.61 | 2.98 ± 0.59 | 3.31 ± 0.6 | 0.86 | 0.04 | |
Frequency | 2.89 ± 0.48 | 3.15 ± 0.52 | 2.85 ± 0.59 | 2.75 ± 0.45 | 2.65 ± 0.54 | 2.56* | 0.1 | |
Physical activity | 2.73 ± 0.46 | 3.05 ± 0.68 | 2.73 ± 0.89 | 2.4 ± 0.84 | 2.12 ± 0.82 | 4.45** | 0.16 | 30 s > 60 s*** |
Activity participation | 2.84 ± 0.69 | 3.16 ± 0.66 | 2.68 ± 0.74 | 2.78 ± 0.74 | 3.02 ± 0.78 | 1.42 | 0.06 | |
Nutrition | 3.11 ± 0.64 | 3.23 ± 0.45 | 3.16 ± 0.61 | 3.08 ± 0.48 | 2.82 ± 0.5 | 1.68 | 0.07 | |
Satisfaction | 3.53 ± 1.09 | 3.18 ± 0.85 | 3.48 ± 0.86 | 3.21 ± 0.9 | 3.97 ± 1.03 | 2.24 | 0.09 | |
Physical activity | 3.45 ± 1.33 | 3.12 ± 0.8 | 3.67 ± 1.11 | 3.05 ± 1.37 | 3.77 ± 1.28 | 1.43 | 0.06 | |
Activity participation | 3.57 ± 1.18 | 3.05 ± 1.03 | 3.3 ± 1.06 | 3.03 ± 1.16 | 3.93 ± 1.25 | 2.22 | 0.09 | |
Nutrition | 3.58 ± 1.01 | 3.38 ± 1.15 | 3.47 ± 0.95 | 3.55 ± 1.19 | 4.22 ± 0.96 | 1.97 | 0.08 |
- Note: Wilks' lambda = 0.62; F = 1.94; p = 0.01. ηp2, partial eta squared.
- Abbreviation: YLP, Yonsei lifestyle profile.
- * p < 0.05
- ** p < 0.01
- *** p < 0.001.
3.5 Internal Consistency
The total YLP score had a Cronbach's alpha value of 0.77, indicating good reliability. The mean scores of the domains and factors had Cronbach's alpha values ranging from 0.80 to 0.86, reflecting very good reliability (Table 6).
Cronbach's α | Cronbach's α | ||
---|---|---|---|
Total | 0.77 | ||
Frequency | 0.82 | Satisfaction | 0.80 |
Physical activity | 0.83 | Physical activity | 0.81 |
Activity participation | 0.83 | Activity participation | 0.81 |
Nutrition | 0.86 | Nutrition | 0.84 |
- Abbreviation: YLP, Yonsei lifestyle profile.
4 Discussion
In this study, we evaluated the validity and reliability of the English version of the YLP in measuring the healthy lifestyles of a USA population. The results confirmed that the YLP is a valid and reliable tool for assessing healthy lifestyles within this demographic group. These findings are discussed and compared with those of previous studies.
Concurrent validity analysis revealed a weak correlation between the YLP total score and HPLP-II total average score. This weak correlation may be owing to the YLP assessing lifestyle frequency and satisfaction whereas the HPLP-II focuses on health-promoting behaviors. This finding is consistent with the weak correlation observed using similar questionnaire tools reported by Kallings et al. [23]. Specifically, there was a significant weak-to-intermediate correlation between the frequency domain of the YLP and certain subregions of the HPLP-II. This result aligns with the findings of Kim et al. [24], who reported a similar correlation between lifestyle evaluation tools. Nevertheless, the satisfaction domain of the YLP did not show a significant correlation with the HPLP-II, likely owing to the subjective nature of satisfaction, which may not directly align with the behavioral measures captured by the HPLP-II. This observation is consistent with the study by Hensel et al. [25], who demonstrated a low correlation between subjective satisfaction and other objective indicators. Including both objective behaviors and subjective satisfaction in lifestyle assessment provides unique insights into subjective well-being, which can complement traditional behavior-focused evaluations.
In the analysis of discriminant validity by sex, no significant differences were found in the total score, domains, or YLP factors. This finding aligns with the results of Oksuzyan et al. [26], who indicated that sex did not have a significant effect on lifestyle scores. This suggests that lifestyle assessment tools should focus on personalized interventions rather than generalized sex-based strategies. Conversely, discriminant validity analysis by age group revealed significant differences in the frequency domain and physical activity factors. Specifically, individuals in their 30s recorded higher scores for frequency of physical activity than those in their 60s or older. This result is consistent with the findings of Spartano et al. [27], who demonstrated different PA patterns of physical activity across age groups. The significant difference in physical activity frequency between younger and older adults may reflect age-related changes in mobility, occupational engagement, and social activity levels. This finding highlights the potential use of the YLP in designing age-specific health promotion programs.
The total score of the YLP and Cronbach's alpha values in the sub-areas ranged between 0.77 and 0.86. According to the criteria established by Cronbach and Meehl [22], this indicated good reliability. Additionally, these values were comparable to the internal consistency metrics of the lifestyle evaluation tools used by Zambrano et al. [28]. This demonstrated that YLP is a reliable tool for consistently evaluating lifestyle. Given its high internal consistency, the YLP-English Version can be reliably used in public health research and clinical settings to assess lifestyle patterns and inform health interventions tailored to different demographic groups.
This study confirmed that the English version of the YLP is a valid and reliable tool for the USA population. This extends the findings of Park et al. [29], who demonstrated the effectiveness and reliability of the YLP for the Korean population. Given its ability to evaluate both lifestyle frequency and satisfaction, this tool can be particularly useful in longitudinal studies examining behavioral changes over time and their impact on health outcomes. Additionally, the YLP can support personalized health counseling, helping health care providers identify at-risk individuals and design interventions tailored to their specific lifestyle patterns. Future studies should explore the potential of the YLP in predicting long-term health risks, integrating it into digital health platforms, and assessing its effectiveness in behavior modification programs.
This study has several limitations. First, because participants were recruited via an online panel, generalizability of the findings may be limited. Holtom et al. [30] highlighted the limitations of online sample recruitment. Second, the use of self-reported questionnaires introduces the possibility of subjective bias. To address these limitations, future studies should include more diverse samples and should use more objective measurement tools. Finally, the internal consistency of the YLP-English Version was confirmed to be good, with Cronbach's α ranging from 0.80 to 0.86. However, its long-term stability was not assessed. To comprehensively validate the reliability of this tool, test–retest reliability analysis using the intraclass correlation coefficient is necessary to determine its temporal stability and ensure consistent results over repeated measurements.
5 Conclusion
In this study, we aimed to validate the reliability of the YLP-English version, a tool for measuring multifaceted health-related lifestyles within a USA population. The findings confirmed the concurrent validity of this tool through strong correlations with the total and subscale scores of the HPLP II, which is widely used in USA sociocultural contexts. Discriminant validity was established, indicating that the YLP-English Version can be used regardless of sex and is partially applicable to individuals in their 30s and 60s. Additionally, the high internal consistency observed across total and subdomain scores supports the reliability of this adaptation. High internal consistency was observed across the total score and subdomains of the YLP-English Version, demonstrating reliable measurements. Consequently, this study established the English version of the YLP as a valid and reliable instrument through cultural adaptation and validation, supporting its use in clinical settings and public health research. Furthermore, the YLP-English Version can be used to develop personalized health management strategies aimed at promoting balanced lifestyle patterns within the US sociocultural context and detecting behavioral changes over time. The YLP-English Version is currently suited for population-level studies, providing insights into general lifestyle trends. Future research should focus on defining evidence-based thresholds to identify high-risk individuals and develop targeted interventions for personalized health management.
Author Contributions
Young-Myoung Lim: conceptualization (lead), formal analysis (equal), writing – original draft (lead); Ah-Ram Kim: methodology (lead), project administration (lead), writing – review & editing (equal); Seung-Ju Lim: formal analysis (lead), software (lead), writing – review & editing (equal); Ji-Hyuk Park: funding acquisition (lead), project administration (lead), resources (lead), supervision (lead).
Acknowledgements
The authors have nothing to report.
Ethics Statement
This study was approved by the Institutional Review Board of Yonsei University (Approval Numbers: 1041849-202404-SB-090-02 and 1041849-202406-SB-136-01).
Consent
Given the minimal risk involved, the requirement for written informed consent was waived, and all participants provided informed consent online before participation. The study was conducted in accordance with the ethical standards of the Declaration of Helsinki. Data were collected anonymously and treated confidentially.
Conflicts of Interest
The authors declare no conflicts of interest.
Open Research
Data Availability Statement
The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.