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Abstract

Lifestyle of an individual is distinguished from that of others by its reflection of individual values and subjectivity. Therefore, this study attempted to explore recognition type by focusing on individual subjectivity using the Q methodology for health-related lifestyles. Q-Methodology was divided into five stages. Step 1-Q sample collected statements about representative lifestyle behavior; Step 2-P sample recruited 34 study participants to express subjectivity about lifestyle; Step 3-Q sort classified statements according to subjective perspective; Step 4-Q-factor analysis examined the correlation between participants’ responses; and Step 5-factor analysis could be interpreted as a lifestyle factor. Health-related lifestyles were divided into four recognition types that focused on (A) interpersonal and emotional well-being, (B) happiness and daily management, (C) emotional well-being and cultivation, and (D) regular life practice. Individual subjectivity was reflected in all factors, and preferred behavior was interpreted in relation to health. The limitations and directions addressed in previous studies to promote healthy lifestyles were clarified. Lifestyle diversity reflects individual values and subjectivity. Considering the multidimensional nature of health lifestyle perception types emphasizes the need for a tailored approach. This study offers valuable insights for developing community health management strategies and public health policies aimed at improving health and quality of life.

Keywords

behavior healthy lifestyle subjectivity Q-methodology

Introduction

In the field of public health, lifestyle has been highlighted as an essential factor for maintaining and improving health for people of all age groups (Bryndin & Bryndina, 2017). Unhealthy lifestyle behaviors, regardless of demographic factors such as age and gender, contribute to the rising incidence of non-communicable diseases (World Health Organization, 2017; Kibria et al., 2019). Such lifestyles have increasingly been recognized as key determinants of individual health and quality of life (Nari et al., 2021). The lifestyle choices made in adulthood are pivotal in determining health and quality of life in old age, underscoring the importance of understanding adult lifestyles for effective health promotion (World Health Organization, 2022a, 2022b).

The concept and definition of lifestyle remain diverse and are interpreted variably across disciplines. From a psychological perspective, lifestyle encompasses an individual’s personality, values, and beliefs (Adler & Porter, 1931; Diener & Biswas-Diener, 2011), whereas from a sociological perspective, it is shaped by social status, class, and cultural capital (Lazer, 1963; Weber, 1978). Recent studies in the field of public health propose that lifestyle is formed by habitual activities based on personal needs and values, influenced by the given environmental context (J. H. Park et al., 2023).

Key lifestyle factors that determine health include physical activity, dietary habits, alcohol consumption, smoking, and social relationships, as well as engagement in work (J. H. Park et al., 2023; Wu, 2021). These factors are subject to change depending on individual identity, value systems, and the choices made in response to opportunities provided by society, community groups, and cultural contexts (Cockerham, 2017; World Health Organization, 2021). Given the ability to address health issues through lifestyle, it is essential to have an in-depth understanding of the context in which different behaviors and habits are chosen (Balwan & Kour, 2021).

To comprehensively understand the multidimensional aspects of lifestyle within the public health domain, standardized assessment tools have been developed and utilized. These include the Health-Promoting Lifestyle Profile II (Walker et al., 1995), Yonsei Lifestyle Profile (K. H. Park & Park, 2020), and the International Physical Activity Questionnaire (IPAQ; Craig et al., 2003). Such tools quantitatively measure the frequency, intensity, and exposure to risk factors associated with lifestyle behaviors that affect health (Lim & Park, 2022). Although these tools allow for an understanding of characteristic behavioral patterns, they are limited in their ability to capture the personality traits that influence behavior, cognitive processes, and properties (W. T. Anderson & Golden, 1984; Garcia et al., 2015; Piksa et al., 2022).

Existing studies have rarely attempted an exploratory analysis of the subjectivity behind decisions regarding personal health lifestyles, which are shaped by core values rather than just individualized behavioral patterns. Therefore, this study is necessary due to the lack of research exploring and understanding healthy lifestyles formed by daily activities and habits based on personal core values. In the absence of foundational academic information, an exploratory study aimed at identifying individual subjectivity and the perception structure of healthy lifestyle activities and patterns is considered appropriate (Rubin & Babbie, 2016). Q-methodology, which objectively analyzes subjective views and attitudes, is well-suited for exploring the perspectives and opinions that shape individual lifestyles (Stephenson, 1935). Such exploratory research is expected to contribute academically to promoting health and improving the quality of life by understanding the subjective perspectives on healthy lifestyles among individuals from diverse sociocultural contexts.

Therefore, to explore the subjective differences and diverse lifestyles formed by daily activities and patterns, Q-methodology was applied to explore the perspective of their subjectivity and to examine the characteristics of lifestyles types.

Methods

Study Design

This was an exploratory study that applied the Q-methodology of a mixed method research design to analyze the perception structure and types of subjective opinions and attitudes toward healthy lifestyles in adults.

Q-Methodology

Q-methodology can analyze the different subjectivities of humans (Stephenson, 1935). This methodology combines quantitative and qualitative approaches and can scientifically analyze subjectivity, reflecting individual opinions, attitudes, and values, by focusing on intraindividual significance rather than interindividual differences (Kim, 2008). The R-method, a quantitative research methodology, identifies population characteristics and analyzes differences through correlation analysis between variables, while the Q-method examines differences in the meanings of human subjectivity related to specific phenomena (Watts & Stenner, 2012). Therefore, Q-method is the most effective approach to grasp the perception structure and type characteristics of subjectivity among the healthy lifestyles of adults, reflecting different personal values and attitudes.

Steps in Q-Methodology

In this study, data collection (Q-sample, P-sample) was done from adults aged 19 or older living in the community. All participants in the study included those who voluntarily consented after understanding the purpose of the study, scope of collection, and privacy guidelines. This research has been reviewed and approved by the Institutional Review Board of University (Approval No .1041849-202201-SB-011-01, 1041849-202205-SB-091-01).

Q-Sample (Development of the Statement)

Q-sampling is a process of collecting subjective subjectivities about adults healthy lifestyles in the form of statements. For this study, data were collected online from approximately 1.6 million panelists registered with Macroville Embrain using non-probability sampling. Panelists voluntarily responded to open-ended questions about “healthy lifestyles that are important in daily life” between March 30 and April 4, 2022. Before participation, an online information sheet outlined the study’s purpose, procedures, data protection, anonymity, and the right to withdraw. Informed consent was obtained via an online agreement checkbox. All data were anonymized by Macroville Embrain prior to being provided to the researcher, ensuring that no identifiable or sensitive information was accessible. Panelists were compensated through Macroville Embrain’s point system; no additional incentives were provided by the researcher (Approval No. 1041849-202201-SB-011-01).

Among the 237 statements expressed, sentences with duplicate meanings and insincere answers were excluded and the expression method was reviewed and modified into sentences with appropriate content. The statements were classified based on lifestyle factors such as physical activity, eating habits, activity participation, social activity, and mental health (Sowa et al., 2016). Thereafter, 48 statements were selected through consensus among the experiences in lifestyle research for the statements that were representative and meaningful. The final number of Q-samples was found to satisfy 40 to 80 suitable statements in the Q-methodology study (Watts & Stenner, 2012).

For the preliminary survey, three adults were selected as a purposive sample, and the reliability was confirmed by setting the time difference between the sort and re-sort processes at 5-day intervals. Consequently, the reliability of the Q-sample was found to have a correlation coefficient of r .747, which confirmed the high reliability level of the Q-sample (r .7–.8; Kim, 2008; Table 1).

Table 1.

Reliability of the Q-sample.

Respondents	Correlation coefficient (r)
Soter 1	.666***
Soter 2	.803***
Soter 3	.773***
Average	.747

***

p < .001.

P-Sample (Recruitment of Participants)

In the Q-methodology, P-sample follows the small-sample doctrine because it is sufficient to objectify the subjectivity of the research topic, unlike the R-method, which aims to generalize through the collection of many samples (Brown, 1993). The selection criteria for P-sample included non-disabled adults (aged over 19 years), those who could read and understand the text, and those who agreed to participate. A total of 34 P-samples were recruited, which satisfied the appropriate number of P-samples from 30 to 50 people in the Q-methodology (Brown, 1996).

P-sample was conducted through snowball sampling targeting adults living in the community. Data were collected from July 1 to September 29, 2022, using FLASHQ Offline v.1.0, which supports remote data collection in Q methodology research. The software was distributed and returned via email and included an information page detailing the study’s purpose, procedures, data protection, and the right to withdraw. Participants provided informed consent by checking an agreement box before proceeding. The task was completed individually on participants’ personal computers, allowing them to participate at their convenience and withdraw at any time. Data were anonymized, and no identifiable information was collected. No additional incentives were offered, and the task took approximately 15 to 20 min to complete (Approval No. 1041849-202205-SB-091-01).

The age range of the P-sample was 21 to 61 years, with an average age of 39.88 years. The proportion of women was higher than that of men and most participants had university education. Furthermore, 82.3% had paid jobs, and 67.3% managed their living expenses through earned income (Table 2).

Table 2.

Descriptive Statistics of the P-Sample (n = 34).

Demographic characteristics		Mean ± SD or n (%)
Age (years)		39.88 ± 11.54
Sex	Male	13 (38.2%)
Sex	Female	21 (61.8%)
Education level	≤Middle school	1 (2.9%)
	High school	4 (11.8%)
	University	22 (64.7%)
	≥Graduate school	7 (20.6%)
Job	Yes	28 (82.3%)
Job	No	7 (20.5%)
Sources of income	Earned income	23 (67.3%)
	Pensions and savings	2 (5.8%)
	Other	9 (26.5%)

Q-Sort (Data Collection)

Q-sort is a process in which participants of the P-sample classify the statements of the Q-sample according to their subjective opinions and viewpoints. The Q-distribution charts were set on an 11-point Likert-type scale (+5 to −5) in the form of a normal distribution, and forced distribution, which forcibly sorted Q-samples as much as a given number, was applied (Brown, 1980).

In Q-sort, after the P-sample participants read and understood the statement of the Q-sample, each statement was classified into three categories: agreed, neutral, and disagreed. Then, it was classified as both extremes of agreed (+5 points) and disagreed (−5 points) of the distribution chart, followed by a sequential classification as neutral (0 points; Figure 1).

Figure 1.

An example of a Q-sort for the data collection (FLASHQ offline).

Data Processing and Analysis Methods

The Q-sort data sorted from the P sample were analyzed using the PQMethod (ver. 2.35) program. Q-factor analysis was performed using a principal component analysis (PCA). Factor extraction was conducted based on the following criteria: a factor with an eigenvalue of 1.0 or higher (Guttman, 1954; Kaiser, 1970, that satisfies the significance level of factor loading (0.01), and loaded with two or more significant samples (=2.58 × [1/√n]; n = number of Q-samples; Brown, 1980). According to Humphrey’s rule, the factor in which the cross-product of the two items with the highest loading in each factor exceeded twice the standard error was selected (=2 × [1/√n]; n = number of Q-samples; Fruchter, 1954).

The varimax rotation method was applied to increase the variance difference and the explanatory power of the major factors (Brown, 1980). Recognition type characteristics were analyzed based on significant factor loadings and z-scores among the extracted factors.

Results

Formation of Perception Factors for Lifestyle

Four factors suitable for the extraction criteria were selected after analyzing the subjectivity of 34 people on healthy lifestyle. The four selected factors were included in the final factor as they were judged to be suitable for interpreting the meaning of the subject of this study. The cumulative variance of the final four factors had an explanatory power of 45.36%. In Q-methodology, if the level of explanatory power is 35% to 40%, it is judged to be at an appropriate level (Kline, 1994; Table 3).

Table 3.

Eigenvalue and Valiance by Each Factor.

Factor characteristics	Factor A	Factor B	Factor C	Factor D
Eigenvalue	7.0748	3.0463	2.7833	2.5274
% of variance	0.2080	0.0895	0.0818	0.0743
Cumulative variance	0.2080	0.2975	0.3793	0.4536

Factor A (variance = 20.80%, n = 9) was 31 to 40 years old, and the proportion of men with educational background above university and with paid or unpaid jobs was high. Factor B (variance = 8.95%, n = 9) was a high proportion of women aged 31 to 40, women with an educational background above university, and those with paid or unpaid jobs. Factor C (variance = 8.18%, n = 3) had a high ratio of 41 to 50 years of age. In addition, all women had paid or unpaid jobs, and the proportion of those with an educational background above university was high. Factor D (variance = 7.43%, n = 7) had a high proportion of women under the age of 30, and the level of education in middle and high schools was distributed. The ratio of paid to unpaid jobs was the same (Supplemental 2).

Interpreting Healthy Lifestyle Factors

The subjective perception type of lifestyle was interpreted with name, focusing on three statements, top and bottom, and based on the Z-score. The values of the statements at the top and bottom of each factor are presented in Table 4 (see Supplemental 3).

Table 4.

Top and Bottom Statements of Each Type and Z-score.

Factor		Q-statement		Z-scores
A	Top	31.	I try to maintain good relationships with people (family, friends, colleagues, etc.).	2.064
		41.	I try to have positive thoughts and minds in daily life.	1.945
		40.	I try to lower stress.	1.526
	Bottom	35.	I try to participate in religious activities regularly.	−1.939
		11.	I try to plan my diet based on raw vegan food.	−1.699
		8.	I am going to enjoy regular hiking during the weekends.	−1.622
B	Top	33.	I try to be happy by traveling or hobby activities.	1.712
		20.	Take nutritional supplements such as vitamins, proteins, and lactic acid bacteria.	1.643
		2.	I try to walk the distance I can walk in daily life.	1.573
	Bottom	35.	I try to participate in religious activities regularly.	−2.315
		8.	I am going to enjoy regular hiking during the weekends.	−2.208
		45.	I try to live a balanced life at work, self-development, rest, home role, etc.	−2.043
C	Top	35.	I try to participate in religious activities regularly.	2.647
		41.	I try to have positive thoughts and minds in daily life.	1.558
		30.	I try to enjoy private group activities (volunteer activities, socializing, etc.) with people.	1.511
	Bottom	3.	I am trying to use the stairs rather than the elevator.	−1.630
		25.	It is feared that smoking or drinking habits will harm health.	−1.483
		9.	I try to do aerobic exercise regularly (running, jump rope, and cycling).	−1.418
D	Top	37.	I try to spend my daily life regularly.	1.485
		17.	I try to keep the time and amount of meals constant at every meal.	1.459
		1.	I try to do it regularly even if it is light exercise.	1.444
	Bottom	25.	It is feared that smoking or drinking habits will harm health.	−2.202
		27.	I try to drink less or not consume alcohol.	−2.002
		15.	I try to stop smoking or reduce the frequency of smoking.	−1.846

Factor A; Interpersonal and Emotional Well-Being

Factor A showed a clear perspective on forming and maintaining positive interpersonal relationships by focusing on relationships with others in their daily lives (Q-Statement 31, Z-Scores: 2.064). In addition, they had positive thoughts and minds and sought emotional well-being by minimizing stress (Q-Statements 41, Z-Scores: 1.945; Q-Statements 40, Z-Scores: 1.526). On the other hand, religious people (Q-Statement 35, Z-Scores: −1.939) achieved spiritual well-being and they did not prefer a raw vegetarian-oriented diet known as a healthy method and regular physical activity (Q-Statement 11, Z-Scores: −1.699; Q-Statement 8, Z-Scores: −1.622).

Therefore, Factor A emphasizes social exchanges with people in social networks, values relationships, and aims to stabilize emotions.

Factor B; Happiness and Daily Management

Factor B focused on leisure and hobbies and pursued happiness in daily life (Q-Statement 33, Z-Scores: 1.712). In addition, to achieve a basic health balance, nutritional supplement intake and walking and physical activity were important in daily life (Q-Statement 20, Z-Scores: 1.643; Q-Statement 2, Z-Scores: 1.573). On the contrary, religion and regular physical activity for spiritual stability were not preferred (Q-Statements 35, Z-Scores: −2.315; Q-Statements 8, Z-Scores: −2.208). Furthermore, it was not a priority to achieve a balance in human life with a multidimensional role (Q-Statement 45, Z-Scores: −2.043).

Therefore, Factor B focuses on the enjoyment and mental and life satisfaction gained from leisure and hobbies in daily life and prefers nutritional supplements and walking activities for incidental health effects.

Factor C; Emotional Well-Being and Cultivation

Factor C was found to value religious activities and pursue spiritual well-being (Q-Statement 35; Z-Scores: 2.647). In addition, social gathering activities that focused on positive thinking and emotional well-being in daily life as well as socializing and interacting with others were important (Q-Statements 41, Z-Scores: 1.558; Q-Statements 30, Z-Scores: 1.511). In contrast, the practice of improving and habituating behaviors that could have a positive or negative effect on health was not preferred (Q-Statement 3, Z-Scores: −1.630; Q-Statements 25, Z-Scores: −1.483; Q-Statements 9, Z-Scores: −1.418).

Therefore, Factor C was found to prefer spiritual and emotional well-being through religious activities and prefer interaction through social gatherings that fit with others.

Factor D; Regular Life Practice

Factor D pursued regularity in daily life (Q-Statement 37, Z-Scores: 1.485) and habituated and practiced eating habits and physical activities directly related to health in a certain pattern (Q-Statement 17, Z-Scores: 1.459; Q-Statement 1, Z-Scores: 1.444). However, they were passive in managing risk factors for smoking and drinking that could negatively affect health (Q-Statements 25, Z-Scores: −2.202; Q-Statement 27, Z-Scores: −2.002; Q-Statement 15, Z-Scores: −1.846).

Therefore, factor D emphasizes the regularity of daily life along with eating habits and physical activity, whereas risk factor management is not preferred.

Discussion

Human lifestyles are shaped by behaviors and habits that reflect individual values and subjectivity, which in turn influence health. An exploratory approach is needed to understand how these lifestyles are formed and reflected in daily life. Therefore, this study aimed to explore the types of perceptions of healthy adults by focusing on individual subjectivity in various behaviors and patterns of lifestyle with a core value on health care.

Factor A emphasizes interpersonal relationships formed through social networks and the pursuit of emotional stability. Relationships, stress, and emotions in this factor are known to affect mental health (Cain et al., 2012; Martínez et al., 2019). Neuroscience research has shown that social connections are closely linked to mental and brain health (Krueger & Meyer-Lindenberg, 2019). Improving the mental health of individuals in this group can be achieved through interventions like social support (Lindfors et al., 2014), physical activity (Tamminen et al., 2020), and leisure activities with mediating effects (Belo et al., 2020).

Factor B emphasized the pursuit of happiness and a meaningful daily life, with basic health maintenance through nutritional supplements and physical activities. Happiness positively impacts a healthy lifestyle and helps prevent illness (Bagheri & Gharehbaghi, 2019). Generally, people who seek pleasure are proactive in their healthcare and engage in activities and social networks to improve their health (Veenhoven, 2008). While happiness can be associated with behaviors like smoking and drinking, this study highlights the importance of healthier hobbies and leisure activities that mediate the relationship between happiness and health (Steptoe, 2019).

Factor C emphasizes religious activities, focusing on emotional well-being and personal growth through social interactions. These interactions among individuals with shared beliefs enhance social participation, internal satisfaction, and collective identity. From a spiritual healing perspective, they positively affect feelings of defensiveness, hopelessness, and happiness, contributing to mental health (Schroder, 2003). However, conflicting findings exist (Bakhtiari et al., 2019), indicating that misguided values in some religious communities can lead to unhealthy lifestyles (Anshel, 2010). Religion, therefore, can be both a motivator for healthy living and a potential source of unhealthy habits (Anshel, 2003). This study suggests the need for further exploration into the dual impact of religious activities on health and quality of life.

Factor D focused on actively practicing health management through regular life patterns, physical activity, and eating habits, highlighting these as modifiable behaviors (Sakaniwa et al., 2022). These practices are effective in managing chronic diseases and obesity-related conditions (E. Anderson & Durstine, 2019; Barbaresko et al., 2018; Lambrinou et al., 2019). However, continuous lifestyle improvement is needed, as individual values and subjectivity influence the importance of healthy behaviors (World Health Organization, 2022a, 2022b). Transforming unhealthy habits requires professional knowledge and expert guidance (Riekert et al., 2013). Thus, professional support is essential for promoting and maintaining effective health management practices.

The recognition types of healthy lifestyles identified in this study appear to be influenced by the contexts to which the participants were exposed. Lifestyles that emphasize health have been shaped by the expansion of regulations related to public health guidelines and community initiatives, which focus on physical activity, emotional well-being, and dietary habits (WHO, 2022). Public health programs that highlight lifestyle factors in various national and regional contexts likely contributed to the relative importance or prioritization of these factors among individuals. Additionally, subjective preferences toward daily health management may have been shaped by health promotion programs offered through educational curricula and workplaces, influencing participants’ attitudes. This suggests that aligning personal values and subjective priorities with public health and health promotion strategies is a critical aspect of successfully fostering healthy lifestyles (Steptoe, 2019; Veenhoven, 2008).

This study focused on understanding lifestyle subjectivity in the context of individual situations, rather than from a medical perspective. This approach helps to interpret diverse lifestyle behaviors, beyond merely verifying their health impacts. In today’s context, where health programs and policies are increasingly important (Williams & Fullagar, 2019), the findings can inform personalized health strategies and public health policy development. By categorizing health lifestyles based on subjectivity, we gain deeper insights into individual and group behaviors, which can guide the creation of tailored health policies. Approaches based on subjective perceptions consider both psychological and social factors, enabling the development of comprehensive health promotion strategies. This method respects individual differences while enhancing the effectiveness of public health interventions and driving meaningful change.

However, the purpose and methodology of this study are limited in generalization because they focus on exploratory research. The P-sample included only 34 healthy adults, a relatively small group. To improve generalizability, future research should include individuals with disabilities, chronic illnesses, and the elderly, reflecting the multidimensional aspects of human health. It should also consider social, cultural, and environmental factors affecting health (Furman et al., 2019; Ladak et al., 2020). Expanding the sample will provide a deeper understanding of diverse health behaviors and needs, forming a stronger foundation for developing effective, broadly applicable health interventions and policies.

Conclusion

This study aimed to understand the characteristics of reflecting individual values and subjectivity using Q-methodology for health-related lifestyles. Healthy lifestyle perceptions were categorized into interpersonal and emotional well-being, happiness and daily management, emotional well-being and cultivation, and regular life practices. These findings offer valuable insights into the prioritization of different healthy lifestyles, which can guide the development of targeted programs and policies aimed at improving health and quality of life. The results provide subjective perspectives, reflecting diverse individual contexts and expanding the scope of services. This study highlights the need for expert approaches to understanding individual characteristics and fostering behavioral change. However, due to the study’s sample size and characteristics, future research should include a more diverse population in terms of health, cultural, social, and environmental factors to validate these findings. Such research would offer a broader perspective and contribute to resolving public health issues by guiding policy and program development.

Supplemental Material

sj-docx-1-sgo-10.1177_21582440251376752 – Supplemental material for Subjective Factors of Healthy Lifestyle: Q-Methodology

Supplemental material, sj-docx-1-sgo-10.1177_21582440251376752 for Subjective Factors of Healthy Lifestyle: Q-Methodology by Young-Myoung Lim and Ji-Hyuk Park in SAGE Open

Footnotes

ORCID iDs

Young-Myoung Lim

Ji-Hyuk Park

Funding

The authors disclosed receipt of the following financial support for the research,authorship,and/or publication of this article: This research was supported by the BK21 FOUR (Fostering Outstanding Universities for Research) funded by the Ministry of Education (MOE) of the Republic of Korea and National Research Foundation of Korea (NRF) (Big data specialized education and research team for cognitive health and social integration of community-dwelling older adults).

Declaration of Conflicting Interests

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

Data Availability Statement

Due to privacy and ethical restrictions,the Q-sort raw data are not publicly available. However,summary data are available from the corresponding author upon reasonable request.

Supplemental Material

Supplemental material for this article is available online.

References

Adler

Porter

(1931). What life should mean to you (pp. 22–23). Grosset & Dunlap.

Anderson

Durstine

J. L.

(2019). Physical activity, exercise, and chronic diseases: A brief review. Sports Medicine and Health Science, 1(1), 3–10.

Anderson

W. T.

Jr Golden

L. L.

(1984). Lifestyle and psychographics: A critical review and recommendation. Advances in Consumer Research, 11(1), 405–411.

Anshel

M. H.

(Ed.). (2003). Sport psychology: From theory to practice (4th ed.). Benjamin-Cummings.

Anshel

M. H.

(2010). The disconnected values (intervention) model for promoting healthy habits in religious institutions. Journal of Religion and Health, 49(1), 32–49.

Bagheri

Gharehbaghi

(2019). The relationship between mindfulness, happiness and healthy lifestyle. Caspian Journal of Health Research, 4(2), 44–48. https://doi.org/10.29252/cjhr.4.2.44

Bakhtiari

Yadollahpur

Omidvar

Ghorbannejad

Bakouei

(2019). Does religion predict health-promoting behaviors in community-dwelling elderly people? Journal of Religion and Health, 58(2), 452–464.

Balwan

W. K.

Kour

(2021). Lifestyle diseases: The link between modern lifestyle and threat to public health. Saudi Journal of Medical and Pharmaceutical Sciences, 7(4), 179–184. https://doi.org/10.36348/sjmps.2021.v07i04.003

Barbaresko

Rienks

Nöthlings

(2018). Lifestyle indices and cardiovascular disease risk: A meta-analysis. American Journal of Preventive Medicine, 55(4), 555–564. https://doi.org/10.1016/j.amepre.2018.04.046

10.

Belo

Navarro-Pardo

Pocinho

Carrana

Margarido

(2020). Relationship between mental health and the education level in elderly people: Mediation of leisure attitude. Frontiers in Psychology, 11, 573.

11.

Brown

S. R.

(1980). Political subjectivity: Applications of Q methodology in political science. Yale University.

12.

Brown

S. R.

(1993). A primer on Q methodology. Operant Subjectivity, 16(3/4), 91–138.

13.

Brown

S. R.

(1996). Q methodology and qualitative research. Qualitative Health Research, 6(4), 561–567.

14.

Bryndin

Bryndina

I. E.

(2017). Formation of public health care on basis of healthy lifestyle. International Journal of Psychological and Brain Sciences, 2(3), 63–68. https://doi.org/10.11648/j.ijpbs.20170203.11

15.

Cain

N. M.

Ansell

E. B.

Wright

A. G.

Hopwood

C. J.

Thomas

K. M.

Pinto

Markowitz

J. C.

Sanislow

C. A.

Zanarini

M. C.

Shea

M. T.

Morey

L. C.

McGlashan

T. H.

Skodol

A. E.

Grilo

C. M.

(2012). Interpersonal pathoplasticity in the course of major depression. Journal of Consulting and Clinical Psychology, 80(1), 78–86.

16.

Cockerham

W. C.

(2017). Health lifestyle theory. In Turner

B. S.

(Ed.), The Wiley-Blackwell encyclopedia of social theory. (pp. 1–3). Wiley-Blackwell.

17.

Craig

C. L.

Marshall

A. L.

Sjöström

Bauman

A. E.

Booth

M. L.

Ainsworth

B. E.

Pratt

Ekelund

Yngve

Sallis

J. F.

Oja

(2003). International physical activity questionnaire: 12-country reliability and validity. Medicine and Science in Sports and Exercise, 35(8), 1381–1395. https://doi.org/10.1249/01.MSS.0000078924.61453.FB

18.

Diener

Biswas-Diener

(2011). Happiness: Unlocking the mysteries of psychological wealth. John Wiley & Sons.

19.

Fruchter

(1954). Introduction to factor analysis. Van Nostrand.

20.

Furman

Campisi

Verdin

Carrera-Bastos

Targ

Franceschi

Ferrucci

Gilroy

D. W.

Fasano

Miller

G. W.

Miller

A. H.

Mantovani

Weyand

C. M.

Barzilai

Goronzy

J. J.

Rando

T. A.

Effros

R. B.

Lucia

Kleinstreuer

… Slavich

G. M.

(2019). Chronic inflammation in the etiology of disease across the life span. Natural Medicines, 25(12), 1822–1832. https://doi.org/10.1038/s41591-019-0675-0

21.

Garcia

Andersson Arntén

A. C.

Archer

(2015). Editorial: Character, responsibility, and well-being: Influences on mental health and constructive behavior patterns. Frontiers in Psychology, 6, 1079. https://doi.org/10.3389/fpsyg.2015.01079

22.

Guttman

(1954). Some necessary conditions for common-factor analysis. Psychometrika, 19(2), 149–161. https://doi.org/10.1007/BF02289162

23.

Kaiser

H. F.

(1970). A second generation little jiffy. Psychometrika, 35(4), 401–415. https://doi.org/10.1007/BF02291817

24.

Kibria

G. M. A.

Swasey

Das Gupta

Choudhury

Nayeem

Sharmeen

Burrowes

(2019). Differences in prevalence and determinants of hypertension according to rural-urban place of residence among adults in Bangladesh. Journal of Biosocial Science, 51(4), 578–590. https://doi.org/10.1017/S0021932018000366

25.

Kim

H. K.

(2008). Q Methodology: Philosophy, thoeries, analysis, and application. CommunicationBooks.

26.

Kline

(1994). An easy guide to factor analysis (pp. 1–12). Routledge.

27.

Krueger

Meyer-Lindenberg

(2019). Toward a model of interpersonal trust drawn from neuroscience, psychology, and economics. Trends in Neurosciences, 42(2), 92–101.

28.

Ladak

L. A.

Gallagher

Hasan

B. S.

Awais

Abdullah

Gullick

(2020). Exploring the influence of socio-cultural factors and environmental resources on the health related quality of life of children and adolescents after congenital heart disease surgery: parental perspectives from a low middle income country. Journal of Patient-Reported Outcomes, 4, 72. https://doi.org/10.1186/s41687-020-00239-0

29.

Lambrinou

Hansen

T. B.

Beulens

J. W.

(2019). Lifestyle factors, self-management and patient empowerment in diabetes care. European Journal of Preventive Cardiology, 26(2_suppl), 55–63.

30.

Lazer

(1963). Life style concepts and marketing. Toward Scientific Marketing, 15(4), 130–139.

31.

Lim

Y. M.

Park

J. H.

(2022). A systematic review on lifestyle assessment tools for middle-aged and aged. Journal of the Korean Gerontological Society, 42(1), 137–148. https://doi.org/10.31888/jkgs.2022.42.1.137

32.

Lindfors

Ojanen

Jääskeläinen

Knekt

(2014). Social support as a predictor of the outcome of depressive and anxiety disorder in short-term and long-term psychotherapy. Psychiatry Research, 216(1), 44–51.

33.

Martínez

L. M.

Estrada

Prada

S. I.

(2019). Mental health, interpersonal trust and subjective well-being in a high violence context. SSM - Population Health, 8, 100423.

34.

Nari

Jeong

Jang

B. N.

Lee

H. J.

Park

E. C.

(2021). Association between healthy lifestyle score changes and quality of life and health-related quality of life: A longitudinal analysis of South Korean panel data. BMJ Open, 11(10), e047933. https://doi.org/10.1136/bmjopen-2020-047933

35.

Park

J. H.

Park

H. Y.

Hong

Han

D. S.

Lim

Y. M.

Kim

A. R.

Jin

(2023). Conceptual model of establishing lifestyle (Lifestyle-DEPER [Decision, execution, personal factor, environment, resources]) and lifestyle intervention strategies. Therapeutic Science for Rehabilitation, 12(4), 9–22. https://doi.org/10.22683/tsnr.2023.12.4.009

36.

Park

K. H.

Park

J. H.

(2020). Development of an elderly lifestyle profile: A Delphi survey of multidisciplinary health-care experts. PLoS One, 15(6), e0233565. https://doi.org/10.1371/journal.pone.0233565

37.

Piksa

Noworyta

Piasecki

Gwiazdzinski

Gundersen

A. B.

Kunst

Rygula

(2022). Cognitive processes and personality traits underlying four phenotypes of susceptibility to (mis)information. Frontiers in Psychiatry, 13, 912397. https://doi.org/10.3389/fpsyt.2022.912397

38.

Riekert

K. A.

Ockene

J. K.

Pbert

(eds) (2013). The handbook of health behavior change. Springer Publishing Company.

39.

Rubin

Babbie

E. R.

(2016). Empowerment series: Research methods for social work. Cengage Learning.

40.

Sakaniwa

Noguchi

Imano

Shirai

Tamakoshi

Iso

(2022). Impact of modifiable healthy lifestyle adoption on lifetime gain from middle to older age. Age and Ageing, 51(5), afac080.

41.

Schroder

P. J.

(2003). Spirituality and mental health care. Journal of Psychosocial Nursing and Mental Health Services, 41(9), 57.

42.

Sowa

Tobiasz-Adamczyk

Topór-Mądry

Poscia

la Milia

D. I.

(2016). Predictors of healthy ageing: Public health policy targets. BMC Health Services Research, 16 (Suppl 5), 289–453.

43.

Stephenson

(1935). Technique of factor analysis. Nature, 136(3434), 297–297. https://doi.org/10.1038/136297b0

44.

Steptoe

(2019). Happiness and health. Annual Review of Public Health, 40(1), 339–359. https://doi.org/10.1146/annurev-publhealth-040218-044150

45.

Tamminen

Reinikainen

Appelqvist-Schmidlechner

Borodulin

Mäki-Opas

Solin

(2020). Associations of physical activity with positive mental health: A population-based study. Mental Health and Physical Activity, 18, 100319.

46.

Veenhoven

(2008). Healthy happiness: Effects of happiness on physical health and the consequences for preventive health care. Journal of Happiness Studies, 9(3), 449–469. https://doi.org/10.1007/s10902-006-9042-1

47.

Walker

S. N.

Sechrist

Pender

(1995). Health-promoting lifestyle profile II. University of Nebraska Medical Center, College of Nursing.

48.

Watts

Stenner

(2012). Doing Q methodological research: Theory, method & interpretation. Sage Publications Asia-Pacific Pte Ltd.

49.

Weber

(1978). Economy and society: An outline of interpretive sociology (Vol. 1). University of California press.

50.

Williams

Fullagar

(2019). Lifestyle drift and the phenomenon of ‘citizen shift’ in contemporary UK health policy. Sociology of Health & Illness, 41(1), 20–35. https://doi.org/10.1111/1467-9566.12783

51.

World Health Organization. (2017). Noncommunicable diseases. Fact sheet. World Health Organization. Retrieved September 23, 2022, from http://www.who.int/mediacentre/factsheets/fs355/en/

52.

World Health Organization. (2021). Health and well-being and the 2030 agenda for sustainable development in the WHO European region: An analysis of policy development and implementation. Report of the first survey to assess member states’ activities in relation to the WHO European region roadmap to implement the 2030 agenda for sustainable development. Report no. WHO/EURO: 2021-1878-41629-56873. World Health Organization. Regional Office for Europe.

53.

World Health Organization. (2022a). Global status report on physical activity 2022. World Health Organization. https://www.who.int/publications/i/item/9789240061665.

54.

World Health Organization. (2022b). Non-communicable diseases. Retrieved September 16, 2022 from https://www.who.int/en/news-room/fact-sheets/detail/noncommunicable-diseases

55.

D. M.

(2021). Lifestyle-related health promotion. In Fong

B. Y. F.

Wong

M. C. S.

(Eds.), The Routledge handbook of public health and the community (pp. 77–89). Routledge.

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