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The validity and reliability of the Healthy Lifestyle Screening Tool
Physical Therapy Rehabilitation Science 2019;8:99-111
Published online June 30, 2019
© 2019 Korean Academy of Physical Therapy Rehabilitation Science.

Cheong Hoon Kima, Kyung-Ah Kangb

aDepartment of Physical Therapy, Collage of Health Science and Social Welfare, Sahmyook University, Seoul, Republic of Korea
bCollege of Nursing, Sahmyook University, Seoul, Republic of Korea
Correspondence to: Kyung-Ah Kang (ORCID, College of Nursing, Sahmyook University, 815 Hwarang-ro, Nowon-gu, Seoul 01795, Republic of Korea, Tel: 82-2-3399-1585 Fax: 82-2-3399-1594 E-mail:
Received May 16, 2019; Revised June 12, 2019; Accepted June 12, 2019.
cc This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.


The aim of the present study was to develop a valid and reliable scale that measures the healthy life styles among young adults.


A methodological study design was employed to develop and validate the Healthy Lifestyle Screening Tool (HLST).


The validity and reliability of the HLST were established in accordance with DeVellis’ 8 steps guideline for tool development. The question items were generated based on literature reviews and interviews, which were then classified into 12 categories. The HLST was administered to 272 students attending a Korean university. The reliability was tested using Cronbach’s alpha. The validity of the scale was examined with the mean inter-item correlations (MIIC) and factor analysis, and was also examined for content validity by experts.


The reliability of the HLST was found to be acceptable, as indicated by a Cronbach’s alpha of 0.71. In the validity test, items with less than 80% “agreement” ratings on the content validity index by experts were revised. The MIIC values were greater than 0.25. A factor analysis of 36 items extracted 9 factors (i.e., four items per factor), which together explained 50.4% of the variance. The HLST consists of 36 items that measure 9 factors based on a 4-point Likert rating scale, with 4 items per factor, as follows: sunlight, water, air, rest, exercise, nutrition, temperance, trust, and general physical condition. High scores on the HLST are indicative of a healthy lifestyle (HL).


The HLST is a valid and reliable scale that can be used to measure HL among young adults. Identification of HL by using the HLST can provide guidance to integrated therapeutic approaches along with conventional physical therapy.

Keywords : Adults, Health, Life style, Reliability, Validity

Individuals differ in their lifestyle behaviors. Studies have found that a healthy lifestyle (HL) is significantly correlated with health maintenance and disease prevention [1-3]. Lifestyle can be defined as a person or group’s way of living, such as specific behaviors or habits [4]. The World Health Organization’s guidelines suggest that a HL can reduce the risk of preventable health problems and improve one’s quality of life (QoL) [5]. A HL entails conscious efforts on part of the individual to effectively protect one’s health and the health of others [6]. Healthcare professionals advise patients about the importance of a HL and its role in disease prevention and recovery. Moreover, various health-related articles have also posited that a HL plays a crucial role in averting the development of lifestyle diseases [7-10].

Physical therapists can effectively counsel patients about the importance of a HL, either individually or as a part of a health professional team. Most patients believe that it is necessary for them to have a therapeutic relationship with physical therapists and to speak to them about a HL. Moreover, they consider physical therapists to be their role models since they promote the health and wellbeing of their patients through exercise prescription [11]. Patients also believe that physical therapists should advise them about various personal health-related behaviors. Therefore, physical therapists require a broad array of knowledge and skills that extend beyond traditional notions of physical therapy [12].

In order to ensure that physical therapy yields effective outcomes, first-line interventions must not only adopt the traditional approaches (e.g., exercise prescription) but should also promote a HL [12]. Individual physical activity levels, which comprise of the patient’s dietary status and other unhealthy behaviors, should be assessed during the first and follow-up visits. However, HL related factors have not been assessed primarily due to the following reasons: lack of time, limited knowledge and expertise, traditional beliefs about the physical therapist’s role (i.e., that assessing HR-related factors is not a physical therapist’s responsibility), and patients’ lack of interest in changing their unhealthy lifestyles [11]. Additionally, whereas physical therapists in the community rely heavily on their tacit and professional subject-matter knowledge, they often ironically believe that these skills do not pertain to physical therapy [9].

There is sufficient evidence to show that HL changes are needed to prevent injury or improve functional limitations. However, previous assessment tools have primarily dealt with only limited aspects of a HL, such as nutrition, exercise, and mindfulness [7-10]. There is lack of a lifestyle tool that includes information about a broad aspect of healthy lifestyle choices that could be completed in a relatively short period of time. The purpose of a screening tool is to guide and provide effective lifestyle advice based on the result of a HL in a timely manner. Therefore, the purpose of this study was to develop a valid and reliable screening tool to measure HL among adults.


Research design

This study employed a methodological design to develop the Healthy Lifestyle Screening Tool (HLST), which evaluates HL among young adults. The validity and reliability of the HLST were established in accordance with DeVellis’ guidelines [13] for tool development (Figure 1).


In order to test the reliability and validity of a developed tool, a survey was administered to 272 university students. The sample size was based on Yang’s rationale [14] that at least 100 cases are required to conduct a factor analysis. The inclusion criteria were as follows: university students without any cognitive impairments, communication problems, and psychiatric problems. Moreover, it was essential that students who fulfill the inclusion criteria understand the purpose of the study and provide written informed consent to participate in this study. The exclusion criterion was as follows: university students who do not agree to participate in the study.

Study procedure

Tool development
Step 1: Identification of the dimensions of HL

A review of literature that was retrieved from scientific databases was conducted to identify factors that affect the HL of adults. We interviewed five medical professionals (i.e., 3 doctors, 1 nurse, 1 public-health educator), 30 terminally ill patients, and 50 healthy adults regarding the factors that they considered to be important in maintaining a healthy lifestyle.

Step 2: Item pool generation

An initial pool of 36 items was generated based on content that was identified by means of literature reviews and interviews. These items were classified into 12 categories, namely, sunlight, water, air, rest, exercise, meal, temperance, family history, physical condition, love, stress, and emotion.

An easy-to-use dichotomous scale (i.e., yes-no; yes=2, no=1) was employed to record the participant responses to each of the 36 items. The initial questionnaire was developed in the Korean language, and the first pilot study was conducted on 159 Korean adults to determine if respondents could accurately understand the meaning of the items.

Step 3: Determination of the measurement scale

In the first pilot study, participant responses were recorded on a 4-point Likert rating scale, which is more likely to produce predictable and controllable results than a dichotomous scale. The scores that were assigned to each response anchor of the Likert rating scale were as follows: 4=strongly agree, 3=agree, 2=disagree, and 1=strongly disagree.

Step 4: Expert review of the initial item pool

In order to examine content validity, 5 professors who were experts in tool development, reviewed the initial pool of 36 items. The validity of each item was assessed and a content validity index was computed [15]. Items with less than 80% “agreement” ratings between the five experts were reviewed and revised. Further, the revised items were rearranged by assigning them to appropriate categories. Accordingly, the 12 categories of the HLST (i.e., 3 items per category) were reclassified into 9 categories (i.e., 4 items per category).

Step 5: Revision and inclusion of items

After establishing the content validity of the item pool, the revised tool was translated into English for international use. The first author of this paper is Korean-American who translated the tool into English. He participated in all of the tool development processes as well as the selection process of the questions. Subsequently, the translated English questions were reviewed by English-speaking Americans. The second pilot study was conducted to determine the time that is required to respond to the questionnaire and examine the placement, composition, and comprehensibility of the items. To this end, we administered the HLST to 24 university students from a city in the Philippines. Mean and standard deviation values, and item analyses were used to test the normality of the data.

Tool validation

Step 6: Administration of the items to a development sample

The final instrument consisted of 36 items that were selected through literature review, content validation by experts, and two pilot studies. The Korean and English versions of the HLST were developed simultaneously in order to prevent any bias related to nationality and race.

Step 7: Evaluation of the items

The validity and reliability of the questionnaire were tested by administering the final pool of 36 items to 272 college students who attended a Sahmyook University in Seoul, Korea. Data were collected using the Google’s online survey platform. The online survey Uniform Resource Locator was shared only with those who agreed to participate in the research study by means of informed consent.

Following the completion of the survey, participants were compensated with drink coupons. Data was collected from June 5, 2018 to June 17, 2018; and there were no missing responses in any of the questionnaires.

Step 8: Optimization of the tool length

The final instrument, which consisted of items that the tool development procedure yielded according to the DeVellis’ guidelines [13], was tested for validity and reliability.

Ethical considerations

Ethical approval for this study was granted by Sahmyook University Institutional Review Board (IRB no. 2018031HR).

Data analyses

All statistical analyses were conducted using the IBM SPSS Statistics ver. 22.0 software (IBM Co., Armonk, NY, USA).

Sample characteristics were examined using descriptive statistics (i.e., percentage, frequency, mean, standard deviation).

1. The validity of the HLST were conducted with content validity by an expert reviewer, mean inter-item correlation (MIIC), and a factor analysis using VarimaxRrotation to determine the dimensionality of the HLST [16]. Content validity involves a process of evidence building and an adequate conceptualization of the construct [17]. Whereas the MIIC is a straightforward indicator of internal consistency, the number of items is not meaningfully related to the internal consistency of a construct. MICC>0.25 was considered as being a sufficient level of internal consistency or reliability [18,19].

2. The reliability of the total scale as well as each dimension that it subsumes were examined using Cronbach’s alpha. Cronbach’s alpha is the most widely used index relating to scale reliability for multi-item reflective scales in the health and social sciences [17].


Step 2: Generation of an item pool

The first pilot study was conducted with a sample of 159 Korean adults. Out of the 159 subjects, 61 (38.4%) were male and 98 (61.6%) were female. The mean age of the sample was 58 years (±10.05); the age of the sample ranged from 30 to 81 years. Results of the item analysis of the initial pool of 36 items are presented in Table 1.

There were 10 items (i.e., items 5, 15, and 20-27) with item-sum correlation coefficients that were less than 0.20. These 10 items were found to be double-barreled questions (i.e., items that simultaneously tap on two different issues); therefore, the content of each of these items was revised to ensure that it assesses only one aspect of the dimension that it measures.

Step 4: Expert review of the initial Item pool

Validity: identification of the content validity by experts

On the basis of expert feedback, a few modifications were made to the initial version of the HLST to establish its content validity. Table 2 shows the modified items that were corrected in accordance with the process of content validation.

Step 5: Revision of items with low item-sum correlations

The second pilot study was conducted with 24 university students. There were 8 items (i.e., items 3, 7, 11-12, 25-26, and 35-36) with item-sum correlation coefficients that were less than 0.20. In total, 10 items, which included the aforementioned 8 items, were revised (Table 2).

Step 7: Evaluation of the items

The demographic details of those who had participated in the final survey (n=272) are as follows: 89 students (32.7%) were in the first grade, 58 students (21.3%) were in the second grade, 59 students (21.7%) were in the third grade, 54 students (19.9%) were in the fourth grade, and 12 students (4.4%) were in the fifth grade. With the exception of 1 individual, all participants were unmarried.

Validity: examination of internal consistency using item analysis

Item analysis of the final pool of the HLST (Table 2) items showed that each item’s mean value was neither too high nor too low. All the HLST items were subjected to further analysis the skewness (−1.25 to 1.26) and kurtosis (−0.01 to 1.65) did not exceed a standard deviation (SD) of ±2.

According to Briggs and Cheek’s guidelines [20], the MIIC should not be less than 0.15; therefore, emergent MIIC values, which were either equal to or greater than 0.25, were acceptable.

There were 8 items (i.e., items 2, 6-8, 12, 20, 25, and 28) that were tested for inter-sum correlations. Additionally, four items (i.e., items 6-7, 12, and 28) were newly added to the existing pool of items. Across all 8 items, the degree of skewness and kurtosis did not exceed a SD of ±2.

Validity: identification of the hypothesized factors using factor analysis
• The appropriateness for factor analysis

The Kaiser-Meyer-Olkin (KMO) test was conducted to determine the appropriateness of the HLST and yielded a value of 0.81. In other words, given that the KMO value was equal to or above 0.80, it was appropriate to factor analyze the data [21]. In addition, according to the results of Bartlett’s test [22] of sphericity, the χ2 value was 2,128.49 (p<0.00); therefore, the items were found to be appropriate for factor analysis.

•Factor extraction and rotation

Varimax rotation was conducted with specifications that the 9 factors were to be extracted. The eigenvalue of all the 9 factors were above 1.00; these nine factors together accounted for 50.4% of the total variance.

The first factor evidenced acceptable loadings from7 items (range, 0.35-0.75) and accounted for 13.3% of the variance; the eigenvalue of this factor was 4.78. The second factor evidenced acceptable loadings from 4 items (range, 0.38-0.77) and accounted for 7.2% of the variance; the eigenvalue of this factor was 2.58. The third factor evidenced acceptable loadings from 5 items (range, 0.34-0.76) and accounted for 5.7% of the variance; the eigenvalue of this factor was 2.05.

The fourth factor evidenced acceptable loadings from 4 items (range, 0.34-0.73) and explained 5.2% of the variance; the eigenvalue of this factor was 1.86. The fifth factor evidenced acceptable loadings from 3 items (range, 0.32-0.78) and explained 4.22% of the variance; the eigenvalue of this factor was 1.52. The sixth factor evidenced acceptable loadings from 4 items (range, 0.35-0.66) and accounted for 4.1% of the variance; the eigenvalue of this factor was 1.48. The seventh factor evidenced acceptable loadings from 3 items (range, 0.37-0.60) and accounted for 3.9% of the variance; the eigenvalue of this factor was 1.39. The eighth factor evidenced acceptable loadings from 4 items (range, 0.40-0.56) and accounted for 3.5% of the variance; the eigenvalue of this factor 1.27. The ninth factor evidenced acceptable loadings from 2 items (range, 0.48-0.79) and accounted for 3.3% of the variance; the eigenvalue of this factor was 1.20 (Table 3).

Reliability: examination of internal consistency using Cronbach’s alpha

The reliability of the HLST was determined using Cronbach’s alpha and was found to be acceptable (α=0.71).

Step 8. Optimization of scale length

The HLST, which screens the HL among young adults, consists of 36 items that measure 9 factors (i.e., 4 items per factor). The 9 factors, each of which consist of 4 items, are as follows: sunlight (items 1 to 4), water (items 5 to 8), air (items 9 to 12), rest (items 13 to 16), exercise (items 17 to 20), nutrition (items 21 to 24), temperance (items 25 to 28), trust (items 29 to 32), and general physical condition (items 33 to 36). Scores are computed using responses recorded on the following 4-point Likert rating scale: 4=strongly agree, 3=agree, 2=disagree, and 1=strongly disagree.

Scores on the HLST can range from 36 to 144; moreover, factor-wise scores can each range from 4 to 16. High scores on the HLST are indicative of a HL; high factor-specific scores are indicative of higher adherence to the respective dimension of a HL (Appendix).


The HLST measures 9 independent dimensions of a HL but it does not measure psychosocial characteristics. The discussion regarding the validity of the HLST was described based on the content validity and the MIIC.



The 4 items that are subsumed by this factor assess appropriate skin exposure to sunlight (i.e., approximately 10 minutes per day). Items that belong to this dimension pertain to the positive effects (i.e., a rich source of vitamin D for the body, prevention of autoimmune diseases, reduction of melanoma risk, improved immunologic tolerance, and endorphin-related effects) of skin exposure to moderate amounts of sunlight, as well as its negative effects (i.e., cataracts) [23,24]. Item analysis showed that 3 items had MIIC values that were 0.20 or greater. The item, “I use sun protection (sunscreen) properly,” evidenced a value of 0.11. However, this item was retained because it tapped on strategies that are used to prevent the negative effects of sunburn that result from overexposure to sunlight.


Sufficient daily water intake is important for the maintenance of good health; conversely, insufficient water intake has been known to cause thirst, reduce exercise performance, and adversely affect working memory and mood [25, 26]. The 4 items that belong to this factor assess water ingestion, thirst, caffeine ingestion, and water intake during meals. The MIIC of one item (i.e., “I drink 8 glasses of water daily”) was found to be 0.24; however, the other 3 items evidenced low correlation coefficients (i.e., 0.10). Therefore, further refinement and validation of these three items through literature review and further research is necessary.


This factor, which is comprised of 4 items, assesses deep breathing and clean atmospheric environments. Brunt et al.’s study [27] showed that air pollution is significantly and positively correlated with respiratory health. Therefore, they recommended that it is important to obtain an air quality index to assess the health status of vulnerable individuals. Further, they also asserted that air pollution-related risks should be considered as determinants of health [28]. To achieve this, greater integration of public health and policy, collaboration with local air quality management [27], and efforts to clean air and maintain a HL have been suggested. The MIIC of the 3 items ranged from 0.20 to 0.40. One item that was related to breathing exercises evidenced a low correlation coefficient (i.e., 0.04); however, this item was not deleted because its effect on the reliability of total items was low.


The 4 items that belong to this factor assess the presence of sufficient hours of sleep and the habit of going to sleep early. Given that lifestyle has been associated with sleep habits, fatigue, and positive and negative self-efficacy, it has been emphasized that increasing individuals’ sleep- and lifestyle-related self-efficacy can contribute to the promotion of positive health outcomes [29]. Further, a study of health problems among footwear factory workers found significant correlations between sleep quality, nicotine and alcohol dependence, and work-related musculoskeletal discomfort [30]. These results were the basis upon which we considered it necessary to measure sleep habits within this factor.


Exercise has been reported as a very important factor in the maintenance of good health [31-33]. Todde et al. [33] has suggested that high-intensity exercise and functional exercises can improve functional mobility and muscle endurance among those who are above the age of 65.

The 4 items that belong to this factor assess endurance exercises that last for over 30 minutes per day. The MIIC of 3 out of the four items ranged from 0.20 to 0.40; the item “that assesses the keeping same position over a long period of time” evidenced a low correlation coefficient (r<0.10). Wisse et al. [34] has suggested that people must be encouraged to change their sedentary lifestyles; this is especially necessary for those who require long-term physical therapy.


The 4 items of this factor assess individual intake of regular and balanced meals. The MIIC of the 4 items evidenced correlation coefficients that ranged from 0.25 to .53 or more. Fleig et al.’s findings [35] suggest that habit strength and transfer cognitions are important factors that underlie the relationship between exercise and nutrition. Moreover, an optimal level of nutrition and healthy lifestyle play a vital role in healing and maintaining a healthy thyroid function [36]. Indeed, recent studies have presented regular and balanced meals as effective guidelines for nutrition maintenance.


Self-control is related to several positive outcomes, such as mental health, interpersonal success, academic success, and health-related behaviors. Moreover, self-regulation has been linked to improved health outcomes and functional limitations among older Americans [37]. The temperance factor of the HLST assesses unhealthy coping strategies, control of food intake, alcohol, smoking, and work-life balance. Two items that measure smoking and overeating were found to have MIIC values that were less than 0.10. Low level of physical activity was the most common risk factor that emerged during the initial and follow-up visits. However, O’Donoghue et al. [11] have posited that physical therapists should also consider dietary status, smoking, and alcohol consumption as possible risk factors.


The 4 items that belong to this factor assess purpose in life, hope, positive social relations, and regular mind training. Social desirability response sets can bias self-reported psychological well-being in late adulthood. Moreover, lifestyle and perceived physical health are related and influence the perceived QoL of older adults [38]. Campos-Matos et al. [39] have suggested that contextual trust plays a complex role in explaining health inequalities and self-reported health. In addition, spiritual-mind-body beliefs, which may serve either as barriers or motivators to obtaining and adhering to treatment, are important factors that affect the survival and QoL of patients with advanced or terminal illnesses [40]. Consistent with past findings, the MIIC values of all the items in this factor were found to have correlation coefficients that were 0.30 or higher.

General Physical condition

The, 4 items that belong to this factor measure one’s general physical condition (i.e., body weight, blood pressure, blood sugar, and bowel habits); in other words, it is an indicator of overall health status. Past studies that have been conducted across many countries have linked obesity, smoking, heavy drinking, poor diet, and a lack of physical activity to morbidity and mortality [41,42]. Indeed, weight, blood pressure, blood sugar, and bowel habits are useful indicators of overall physical health.


The HLST, which comprises 9 factors that assess HL, was found to have an acceptable Cronbach’s alpha of 0.71; an alpha that is between 0.70 and 0.90 is indicative of a reliability that is acceptable [43].

Patients who receive physical therapy prefer therapeutic interventions that are based on their health problems. In order to provide medical services that address unique patient needs, it is necessary to evaluate not only conventional approaches to physical therapy but also the patient’s lifestyle-related limitations, when conducting physical activities or prescribing exercise routines. The tool that has been developed in this study is a holistic assessment of a HL. Thus, the HLST can serve as a useful assessment in integrated therapeutic approaches that are cognizant of the role that lifestyle behaviors play in a HL.

The validity and reliability of the final 36 items were tested on one university students. They did not represent the total population of university students across all cultural groups in Korean society. This limitation indicates that further research is required into the HLST to eliminate the effects of selection, information bias to strengthen the validity and reliability obtained thus far.

Conflict of Interest

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

Fig. 1. Tool development process. Cited from the DeVellis. Scale development: Theory and applications: Sage publications; 2016 [].

Table 1

Internal consistency of 1st pilot study (N=159)

Category1st pilot study (dichotomous scale: no 1, yes 2)
ItemsMean (SD)Corrected item-total correlationAlpha if item deleted
SunlightI go outside for 30 min in the sunny day1.55 (0.49)0.3640.780
I like sunshine and enjoy sunbathing.1.57 (0.49)0.3570.781
I use sunlight for my health promotion and care.1.44 (0.49)0.2470.785
WaterI drink 8 glasses of water a day.1.60 (0.49)0.3090.783
I do not feel thirsty normally.1.67 (0.47)0.2590.785
I choose water without mineral.1.51 (0.50)0.1300.790
AirI do deep breathing in a good posture everyday.1.35 (0.47)0.3200.782
I live in an area with no pollution and clean area.1.43 (0.49)0.2490.785
I do deep breathing with stomach movement.1.22 (0.41)0.2540.785
RestI sleep for 7 to 8 h every day.1.52 (0.50)0.2260.786
I go to bed early and wake up early.1.42 (0.49)0.3450.781
I did not have sleeping issues last 6 mo.1.53 (0.50)0.2820.784
ExerciseI exercise for 30 min or more every day.1.53 (0.50)0.3650.780
I do not overwork or over-exercise.1.62 (0.48)0.3150.782
I do not have weight changes and I am not obese.1.68 (0.46)0.1920.787
DietI eat a vegetarian diet with lots of fibers.1.61 (0.48)0.4330.777
My breakfast is the best meal of the day.1.58 (0.49)0.2300.786
I do not binge eating and eat meals regularly.1.49 (0.50)0.3810.780
TemperanceI do not overeat or eat fast.1.54 (0.50)0.3160.782
I do not drink alcohol or smoke.1.81 (0.39)0.0860.790
I do not use coffee or drugs.1.59 (0.49)0.1880.787
Family HistoryMy family and I do not have cancer, diabetes, or high blood pressure.1.17 (0.37)0.1310.789
My family and I rarely catch a cold or flu.1.62 (0.48)0.1720.788
My family and I do not use medication and maintain health.1.54 (0.50)0.1910.787
Physical ConditionMy blood pressure and blood sugar are in the normal range (blood pressure 140/90, blood sugar below 140).1.72 (0.44)0.0680.792
My hand and feet are always warm1.45 (0.49)−0.0430.797
I bowel movements at least once a day.1.82 (0.38)0.1830.787
LoveI am living with true love.1.63 (0.48)0.2290.786
I’m not afraid of death and I am hopeful about the future.1.70 (0.46)0.4770.776
I forgive others easily.1.64 (0.48)0.3110.783
StressI usually overcome stress well.1.58 (0.49)0.3590.781
I always have peace and stability in my mind.1.55 (0.49)0.3570.781
When in a crisis, I do not panic and solve it well.1.69 (0.46)0.3880.780
EmotionI am optimistic and positive for everything1.60 (0.49)0.2970.783
I do not get angry and generous to everything1.48 (0.50)0.3570.781
I am happy at home and work1.62 (0.48)0.4180.778

Table 2

Results of internal consistency and Cronbach’s alpha (N=296)

CategoryThe 2nd pilot study (n=24)
The final study (n=272)
ItemsMean (SD)The MIICAlpha if item deletedItemsMean (SD)SkewnessKurtosisThe MIICAlpha if item deleted
Sunlight1. I go outside for 10 min in the sun.3.50 (0.72)0.3060.7901. I go outside for the sun at least 10 min a day.3.18 (0.68)−0.390−0.2990.2590.698
2. I use a sun protection (hat, sunscreen) every time I go out.2.45 (1.02)0.2510.7932. I use a sun protection (sunscreen) properly.2.90 (1.02)−0.446−0.9800.1070.709
3. When sleeping at night, there is no light and it is quiet.3.25 (1.03)0.1650.7973. I expose skin properly when I go out for sunlight.2.81 (0.74)−0.287−0.0850.2090.701
4. I work in an office with no natural light.2.95 (0.90)0.3110.7904. I work (study) in a place where the amount of sunlight is good.2.05 (0.75)0.354−0.1250.2770.697
Water5. I drink 8 glasses of water a day.3.20 (0.72)0.4220.7865. I drink and glasses of water daily.2.48 (0.94)0.118−0.8730.2440.698
6. I drink other sweet beverages (sugar) besides water.3.91 (0.28)0.2180.7946. I often feel thirsty.2.38 (0.70)−0.031−0.2670.0700.708
7. I do not feel thirsty normally.1.08 (0.28)0.1660.7997. I drink water during the meals.2.26 (0.96)0.285−0.8790.0380.713
8. I take caffeinated drinks (coffee, tea, and energy drinks).2.58 (1.01)0.2330.8158. I drink caffeinated drinks (coffee, tea, supplements, energy drinks, etc.).2.29 (0.97)0.229−0.9360.0550.712
Air9. I do deep breathing throughout the day2.12 (0.74)0.2940.7919. I do deep breathing throughout the day.2.66 (0.76)−0.020−0.3890.2220.700
10. I breathe through my mouth when hiking or exercising.2.66 (1.20)0.4830.78110. I live in an area with clean air quality.2.38 (0.85)0.047−0.6150.1940.702
11. I live in an area with an unhealthy level of polluted air.2.12 (0.85)0.1310.80711. I keep indoor air quality clean.2.61 (0.71)−0.022−0.2470.4020.690
12. I smoke or exposed to second-hand smoking.3.29 (0.85)0.1880.79512. I breathe through my mouth when hiking or exercising2.69 (0.72)−0.3760.0760.0430.714
Rest13. I sleep for 7 to 8 h every day.2.75 (0.67)0.2910.79113. I sleep for 7 to 8 h.2.38 (0.84)0.062−0.5930.1960.702
14. I use electronic devices for more than 3 h in the evening.2.08 (1.01)0.6300.77414. I use electronic devices (TV, computer, or phone) for more than 3 h in the evening.1.70 (0.70)0.6900.0270.2240.700
15. I keep a balance between work/studies and rest.2.70 (0.85)0.5680.77915. I do not exercise right before bedtime1.68 (0.75)0.9810.6900.1500.704
16. I go to bed early and do not stay up late.2.66 (0.76)0.5510.78116. I go to bed early and wake up early.2.02 (0.88)0.462−0.6150.2820.696
Exercise17. I exercise for 30 min or more every day.1.95 (0.90)0.5220.78117. I exercise for more than 30 min every day.2.06 (0.86)0.536−0.2720.3480.692
18. I usually sweat when I exercise2.62 (0.87)0.2700.79218. I usually sweat when I exercise.2.91 (0.89)−0.428−0.5670.2210.700
19. I do enjoy physical activity whenever I have time2.79 (0.72)0.3640.78819. I enjoy physical activity whenever I have time.2.54 (0.85)−0.145−0.5920.4350.740
20. When I work, I stay in one position for long period time.2.20 (0.50)0.3440.79020. When I work, I stay in one position for long period time.2.63 (0.79)−0.077−0.4120.0890.708
Nutrition21. I eat a healthy breakfast regularly.2.70 (0.95)0.3860.78721. My breakfast is the best meal of the day1.72 (0.86)1.0550.3840.2590.698
22. I enjoy eating snacks between meals3.29 (0.80)0.2320.79322. I eat meals regularly.2.34 (0.85)0.202−0.5470.4740.683
23. I eat food slowly and chew it well2.95 (0.85)0.3390.78923. I eat food slowly and chew it well2.60 (0.83)0.063−0.5980.2760.697
24. I eat a vegetarian diet.2.58 (0.82)0.3570.78824. I eat nutritionally balanced diet.2.35 (0.80)0.248−0.3270.5340.681
Temperance25. I do not overeat.3.20 (0.72)0.0630.79825. When I feel blue, I often overeat.2.40 (0.92)0.167−0.7950.1060.708
26. I drink alcohol.3.00 (0.97)0.1100.79926. I did not drink alcohol for last 12 mo1.72 (1.02)1.2600.3230.2120.701
27. I get angry or annoyed more easily than before.3.04 (0.75)0.4880.78427. I keep a balance between work (study) and rest.2.66 (0.71)−0.5240.1910.4230.689
28. I am satisfied with my daily life.3.00 (0.88)0.2250.79328. I did not smoke within last 6 mo.3.63 (0.88)−1.2481.3460.1100.707
Trust29. I can trust most people.3.00 (0.65)0.2150.79329. I have a purpose of life.3.02 (0.73)−0.4950.2340.3530.693
30. I’m not afraid of death and I am hopeful about the future.3.37 (0.64)0.5170.78430. I am hopeful about the future.3.09 (0.72)−0.441−0.0100.4350.689
31. I feel loved by my family and friends.3.37 (0.64)0.4540.78631. I feel loved by my family and friends.3.32 (0.66)−0.6060.0250.3870.692
32. I pray or meditate on a regular basis.3.29 (0.62)0.4490.78632. I pray or meditate on a regular basis.1.98 (0.86)0.490−0.5430.2980.695
General physical condition33. There has been little change in my weight over the past year.3.08 (0.82)0.2650.79233. I maintain my weight properly.2.82 (0.81)−0.340−0.3050.3020.695
34. I did not catch a cold or flu for one year.1.91 (0.97)0.2890.79134. My blood pressure is in the normal range.3.24 (0.68)−0.7691.0200.1540.704
35. My blood pressure and blood sugar are in the normal range.3.50 (0.51)0.1170.79635. My blood sugar is in the normal range.3.25 (0.57)−0.3050.8100.2610.699
36. I have bowel movements at least once a day.3.37 (0.87)0.0550.80036. I have regular bowel movements.2.99 (0.79)−0.526−0.0430.2120.701

Table 3

Result of factor analysis on the Healthy Lifestyle Screening Tool

FactorEigenvalueVariance explained (%)Cumulative variance explained (%)

  1. Reynolds SL. Successful aging in spite of bad habits: introduction to the special section on ‘Life style and health expectancy’. Eur J Ageing 2008;5:275.
    Pubmed KoreaMed CrossRef
  2. Austin-McCain M. An examination of the association of social media use with the satisfaction with daily routines and healthy lifestyle habits for undergraduate and graduate students. Open J Occup Ther 2017.
  3. Cihangiroğlu Z, Deveci SE. Healthy life style behaviours and related influencing factors of the students of elazig high school of health sciences of Firat university. Firat Med J 2011;16:78-83.
  4. Cambridge Dictionary Cambridge advanced learner’s dictionary & thesaurus [Internet]. Cambridge University Press.
    Available from:
  5. Kockanat P, Bekar M. The relationship between sexual health be-haviors and healthy lifestyle behaviors of female students in Turkey. Int J Caring Sci 2018;11:1859-67.
  6. Aslan E, Bektas H, Basgol S, Demir SV. PI Level of information and patterns of behaviour of university students in relation to sexual health. J Contin Med Educ 2014;23:174-82.
  7. Addley K, McQuillan P, Ruddle M. Creating healthy workplaces in Northern Ireland: evaluation of a lifestyle and physical activity assessment programme. Occup Med (Lond) 2001;51:439-49.
    Pubmed CrossRef
  8. Darviri C, Alexopoulos EC, Artemiadis AK, Tigani X, Kraniotou C, Darvyri P, et al. The Healthy Lifestyle and Personal Control Questionnaire (HLPCQ): a novel tool for assessing self-empowerment through a constellation of daily activities. BMC Public Health 2014.
    Pubmed KoreaMed CrossRef
  9. Black B, Ingman M, Janes J. Physical therapists’ role in health promotion as perceived by the patient: descriptive survey. Phys Ther 2016;96:1588-96.
    Pubmed CrossRef
  10. Dean E, Söderlund A. What is the role of lifestyle behaviour change associated with non-communicable disease risk in managing musculoskeletal health conditions with special reference to chronic pain?. BMC Musculoskelet Disord 2015.
    Pubmed KoreaMed CrossRef
  11. O’Donoghue G, Cunningham C, Murphy F, Woods C, Aagaard-Hansen J. Assessment and management of risk factors for the prevention of lifestyle-related disease: a cross-sectional survey of current activities, barriers and perceived training needs of primary care physiotherapists in the Republic of Ireland. Physiotherapy 2014;100:116-22.
    Pubmed CrossRef
  12. Heckman KA, Cott CA. Home-based physiotherapy for the elderly: a different world. Physiother Can 2005;57:274-83.
  13. DeVellis RF. Scale development: theory and applications. SAGE Publications; 2016.
  14. Yang B. Multivariate data analysis and its applications. Seoul: Hakji Publishing Co.; 1998.
  15. Lynn MR. Determination and quantification of content validity. Nurs Res 1986;35:382-5.
    Pubmed CrossRef
  16. Taylor GJ, Bagby RM, Parker JD. The 20-Item Toronto Alexithymia Scale. IV. Reliability and factorial validity in different languages and cultures. J Psychosom Res 2003;55:277-83.
    Pubmed CrossRef
  17. Polit DF, Yang FM. Measurement and the measurement of change: a primer for the health professions. Philadelphia (PA): Wolters Kluwer; 2016.
  18. Clark LA, Watson D. Constructing validity: basic issues in objective scale development. Psychol Assess 1995;7:309-19.
  19. van Leeuwen R, Tiesinga LJ, Middel B, Post D, Jochemsen H. The validity and reliability of an instrument to assess nursing competencies in spiritual care. J Clin Nurs 2009;18:2857-69.
    Pubmed CrossRef
  20. Briggs SR, Cheek JM. The role of factor analysis in the development and evaluation of personality scales. J Personal 1986;54:106-48.
  21. Kaiser HF. An index of factorial simplicity. Psychom 1974;39:31-6.
  22. Bartlett MS. The effect of standardization on a χ2 approximation in factor analysis. Biom 1951;38:337-44.
  23. Mead MN. Benefits of sunlight: a bright spot for human health. National Institute of Environmental Health Sciences; 2008.
  24. Cullum A, Ellis S, Leng G, Richardson J, Sheppard L. NICE public health guidance update. J Public Health (Oxf) 2017;39:213-4.
    Pubmed CrossRef
  25. Altun İ, Çınar ND, Kaşıkçı MK. Self-reported quantity of daily water intake and urine output in healthy young. Int J Urol Nurs 2012;6:91-3.
  26. Nissensohn M, Castro-Quezada I, Serra-Majem L. Beverage and water intake of healthy adults in some European countries. Int J Food Sci Nutr 2013;64:801-5.
    Pubmed CrossRef
  27. Brunt H, Barnes J, Jones SJ, Longhurst JWS, Scally G, Hayes E. Air pollution, deprivation and health: understanding relationships to add value to local air quality management policy and practice in Wales, UK. J Public Health (Oxf) 2016;39:485-97.
    Pubmed CrossRef
  28. Spurr K, Pendergast N, MacDonald S. Assessing the use of the Air Quality Health Index by vulnerable populations in a ‘low-risk’ region: a pilot study. Can J Respir Ther 2014;50:45-9.
    Pubmed KoreaMed
  29. Johansson A, Windahl M, Svanborg E, Fredrichsen M, Swahn E, Uhlin PY, et al. Perceptions of how sleep is influenced by rest, activity and health in patients with coronary heart disease: a phenomenographical study. Scand J Caring Sci 2007;21:467-75.
    Pubmed CrossRef
  30. Sharma KS, Srivastava SP, Panchal PA, Kaur AM. The effect of shift work on lifestyle, mental health and physical health status of footwear factory workers: a comparison between night shifts and day shifts. Indian J Physiother Occup Ther 2017;11:34-9.
  31. Fujiki RB, Oliver AJ, Sivasankar MP, Craig BA, Malandraki GA. Secondary voice outcomes of a randomized clinical trial comparing two head/neck strengthening exercises in healthy older adults: a preliminary report. J Speech Lang Hear Res 2019;62:318-23.
    Pubmed KoreaMed CrossRef
  32. Cirer-Sastre R, Legaz-Arrese A, Corbi F, George K, Nie J, Carranza-García LE, et al. Cardiac biomarker release after exercise in healthy children and adolescents: a systematic review and meta-analysis. Pediatr Exerc Sci 2019;31:28-36.
    Pubmed CrossRef
  33. Todde F, Melis F, Mura R, Pau M, Fois F, Magnani S, et al. A 12-week vigorous exercise protocol in a healthy group of persons over 65: study of physical function by means of the Senior Fitness Test. Biomed Res Int 2016.
    Pubmed KoreaMed CrossRef
  34. Wisse W, Boer Rookhuizen M, de Kruif MD, van Rossum J, Jordans I, ten Cate H, et al. Prescription of physical activity is not sufficient to change sedentary behavior and improve glycemic control in type 2 diabetes patients. Diabetes Res Clin Pract 2010;88:e10-3.
    Pubmed CrossRef
  35. Fleig L, Kerschreiter R, Schwarzer R, Pomp S, Lippke S. ‘Sticking to a healthy diet is easier for me when I exercise regularly’: cognitive transfer between physical exercise and healthy nutrition. Psychol Health 2014;29:1361-72.
    Pubmed CrossRef
  36. Sonchar CL. Medications alone are not the answer for an optimally functioning thyroid, instead healthy nutrition & lifestyle choices are the keys!. J Counc Nutr 2016;39:11-4.
  37. Ward MM. Sense of control and self-reported health in a population-based sample of older Americans: assessment of potential confounding by affect, personality, and social support. Int J Behav Med 2013;20:140-7.
    Pubmed KoreaMed CrossRef
  38. Fastame MC, Hitchcott PK, Penna MP. Does social desirability influence psychological well-being: perceived physical health and religiosity of Italian elders? A developmental approach. Aging Ment Health 2017;21:348-53.
    Pubmed CrossRef
  39. Campos-Matos I, Subramanian SV, Kawachi I. The ‘dark side’ of social capital: trust and self-rated health in European countries. Eur J Public Health 2016;26:90-5.
    Pubmed CrossRef
  40. Kremer H, Ironson G, Porr M. Spiritual and mind-body beliefs as barriers and motivators to HIV-treatment decision-making and medication adherence? A qualitative study. AIDS Patient Care STDS 2009;23:127-34.
    Pubmed KoreaMed CrossRef
  41. Jensen MK, Chiuve SE, Rimm EB, Dethlefsen C, Tjønneland A, Joensen AM, et al. Obesity, behavioral lifestyle factors, and risk of acute coronary events. Circulation 2008;117:3062-9.
    Pubmed CrossRef
  42. Franco OH, de Laet C, Peeters A, Jonker J, Mackenbach J, Nusselder W. Effects of physical activity on life expectancy with cardiovascular disease. Arch Intern Med 2005;165:2355-60.
    Pubmed CrossRef
  43. Nunnally JC, Bernstein IH. Psychometric theory. 3rd ed. New York: McGraw-Hill; 1994.


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