Development and Psychometric Properties of a Lifestyle-Related Behaviors &amp; Barriers Scale (LBBS) among Young Adults

doi:10.21203/rs.3.rs-3771052/v1

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Development and Psychometric Properties of a Lifestyle-Related Behaviors & Barriers Scale (LBBS) among Young Adults

https://doi.org/10.21203/rs.3.rs-3771052/v1

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Background & Aim: The management of obesity has unique characteristics and challenges in different age groups. Effective redressal requires the recognition of unhealthy lifestyles through reliable and valid assessments targeting young adults (YAs). The present study is dedicated to formulating and evaluating the psychometric attributes of an all-encompassing questionnaire to assess lifestyle-related behavior and associated barriers.

Methods: The tool was formulated through a mixed-method study design, including item generation, assessment of content validity by experts, face validity through pre-testing, and construct validity through exploratory factor analysis (EFA). The dimensionality and discriminant validity were tested through structural equation modeling (SEM) by confirmatory factor analysis (CFA). Reliability, stability, and internal consistency were also confirmed by conducting a test-retest assessment using Cronbach’s alpha and Intraclass correlation (ICC).

Result: A tool with four latent factors and 17 items was found a good fit after EFA and subsequent CFA. A total of 302 participants were recruited for EFA, and 152 participants were subjected to SEM through CFA. Additional data from 102 participants was taken after one week for test-retest reliability. The tool demonstrated good reliability, stability, internal consistency (Cronbach’s alpha: .72, ICC= 0.960, CI= 0.952 to 0.971).

Conclusion: This study has successfully developed a concise and reliable questionnaire for assessing obesity-related factors in YAs, addressing the limitations of prior tools. The questionnaire holds promise for widespread use in clinical, research, and public health settings, facilitating assessments and interventions.

Health sciences/Health care/Nutrition

Health sciences/Risk factors

Obesity

Overweight

Young Adult

Lifestyle

Questionnaire

Tool

Instrument

Scale

Obesity has become a major global health issue, impacting people of various age groups and socioeconomic status. Over the past few years, there has been a concerning increase in the prevalence of obesity and its related complications among young adults (YA)(1, 2). This rise can be attributed to the unique challenges faced by individuals in this age group, including changes in eating patterns, decreased levels of physical activity, social influences, and psychological stress(3, 4). The effective redressal of these issues requires the recognition of unhealthy lifestyles through reliable and valid assessments. Such assessment would provide crucial insights into their individual risk factors, enabling the development of tailored interventions to target unhealthy lifestyle-related behaviours (5, 6).

Existing questionnaires such as the Eating Attitude Test (EAT), Three-Factor Eating Questionnaire (TFEQ), Yale Food Addiction Scale (YFAS), Binge Eating Scale (BES), Healthy Eating Index (HEI), and International Physical Activity Questionnaire (IPAQ) are predominantly centred around specific facets of lifestyle for the general population(7–12). Apart from this, various lifestyle questionnaires have also been developed and validated for different age groups and life stages(13, 14). Yet, there is a significant gap for a specific focus on young adults, necessitating the development of a comprehensive and streamlined questionnaire for assessing the multifaceted nature of their lifestyle. The questionnaire development requires a broad spectrum of pertinent lifestyle dimensions, balancing comprehensive assessment and participant ease while avoiding undue resource demands for administration and analysis. Thus, the present study is dedicated to formulating and evaluating the psychometric attributes of an all-encompassing questionnaire for the assessment of lifestyle-related behavior and associated barriers.

Research Design

The questionnaire has been developed through a mixed-method approach with the development team comprising a multi-disciplinary team of nutritionists, general physicians, psychiatrists, psychologists, and statisticians to enrich the process. The team was involved in all phases of the questionnaire and participated actively in discussions and decisions of the questionnaire development.

Ethical Clearance and Informed Consent

The Institute ethics committee approved the study procedures with reference no. IEC-798/07.10.2022. The participants involved at all stages provided written informed consent before their participation.

Sampling

The sample size for Exploratory Factor Analysis (EFA) was calculated through subject-to-item ratio, assuming the ratio to be 5–10 participants per item, the estimated sample size was between 190–380(15). Participants with age of 18–30 years were recruited with body mass index (BMI) > 23.5kg/m2. After data collection, entry, and cleaning, a total of n = 302 participants were subjected to initial data analysis. Additional data from 255 participants was taken to check the dimensionality and discriminant validity of the questionnaire. Apart from this n = 102 participants were contacted after one week to assess test-retest reliability. Participants were selected through a purposive sampling frame and the principle of maximum diversity was used to ensure heterogeneous responses.

A detailed description of the phase-wise process of development and validation of the questionnaire is given below:

Step 1: Generation of items and Development of construct

The questionnaire's construct was developed through inductive and deductive approaches to generate the items. For the deduction approach, a comprehensive and exhaustive literature review was done by using PubMed and Wiley to identify the existing questionnaires; eight existing validated questionnaires were identified for the generation of items for the construct. Research experts from nutrition, psychology, and medicine conducted focus group discussions with an inductive approach with young adults to generate additional items. A total of 30 participants from diverse backgrounds were enrolled. The content was saturated after six focus group discussions. Codes and themes were generated through qualitative statistical analysis, and another 27 items were added to the questionnaire. The construct of the questionnaire was developed by combining all the items (n = 68) and was divided into domains; dietary practices and behaviors, physical activity-related behavior, sleep assessment, and the barriers associated with these domains. The questionnaire was devised on a five-point Likert scale. The focus was given to keep the questionnaire concise and in simple language. The flow of the questions was kept from general to specific to avoid complexity. Double negative and leading questions were avoided while framing the questions.

Step 2: Content validity

The developed construct of the questionnaire was thoroughly reviewed by a panel of 10 experts from various fields of academia (medicine, nutrition, clinical psychology, and metabolic experts). The validation process aimed to assess the questions' critical appraisal and content validity.

To establish content validity, both qualitative and quantitative approaches were employed. The experts provided their comments on each question, evaluating its necessity, relevance, clarity, and simplicity. A quantitative measure was also used to calculate the Content Validity Index (CVI) and Content Validity Ratio (CVR). For CVR, the experts independently rated the necessity of each question on a three-point scale (-1 to + 1), indicating whether it was not necessary, useful but not essential, or essential. The CVR formula is as follows: CVR = (Ne - N/2)/(N/2), where Ne represents the number of panelists indicating "essential," and N is the total number of panelists. The acceptable cut-off values were determined based on Lawshe scores(16).

For CVI calculation, the experts rated the relevance, clarity, and simplicity of each question on a four-point Likert scale: (1) not relevant/clear/simple, (2) slightly relevant/clear/simple, (3) relevant/clear/simple, and (4) very relevant/clear/simple. The proportion of experts who rated the question as relevant/clear/simple (rating 3 or 4) was used to calculate the CVI. A cut-off value of 0.70 was applied, indicating that questions scoring below this threshold would be considered for elimination, while those scoring between 0.70 and 0.79 would require modification based on expert opinion.

Step 3: Assessment of face validity

The face validity of the questionnaire was assessed by pretesting the questionnaire on 30 young adults with different ages, sex, and educational levels. They were asked to rate the items for clarity and to give any additional comments on the language, appropriateness, and applicability. The participants were recruited through purposive sampling and based on the recommendation in the literature of 20–60 participants for pre-testing. The assessment was done after written informed consent and the items were removed and reworded as per the suggestions.

Step 4: Questionnaire administration

The questionnaire was administered to n = 302 participants with written and informed consent. Efforts were made to use the principle of maximum diversity in the collection of data. The responses were collected in both paper surveys and computer-assisted surveys.

Step 5: Item Reduction & Extraction of Factors for Construct Validity

The responses were coded and analyzed through Exploratory Factor Analysis (EFA) with varimax rotation to ensure the inclusion of only functional, precise, and internally consistent items in the questionnaire. The items with factor loading or slope coefficient < 0.30 were considered inadequate due to their low contribution to the latent construct and were thus removed. Additionally, items with < .30 difference in factor loading were removed in the cross-loading. The sampling adequacy was confirmed through the Kaiser-Meyer-Olkin (KMO) values of > 0.8 and a significant Bartlett Sphericity Test with a p-value of < 0.05.

Step 6: Assessment of Dimensionality and Discriminant Validity

The questionnaire's dimensionality and discriminant validity were assessed using confirmatory factor analysis (CFA), employing Structural Equation Modelling (SEM) to delineate the relationships between latent constructs and observed variables and to gauge the model's goodness of fit. This evaluation encompassed several fit indices, including the Chi-Square test for overall model fit, Comparative Fit Indices (CFI), Tucker-Lewis Index (TLI), as well as error-based metrics such as the Root Mean Square Error of Approximation (RMSEA) and Standardised Root Mean Square Residual (SRMR). Attainment of values near or exceeding 0.95 for CFI and TLI indicated a good model fit, while RMSEA values below 0.08 suggested a reasonable fit, with values under 0.05 signifying a close fit. Additionally, SRMR values approximating or falling below 0.08 indicated a favorable model fit.

Step 7: Test of Reliability

The reliability of the questionnaire was measured through Cronbach’s alpha and the stability was assessed through the calculation of the correlation coefficient through test-retest and measurement of the intraclass correlation coefficient (ICC).

Internal Consistency Assessment

Cronbach's α was employed to evaluate internal consistency, which refers to how well the items within the instrument align in measuring the same construct. A Cronbach's α coefficient of 0.7 or higher indicates good internal consistency.

Stability

The stability of the questionnaire was confirmed through test-retest reliability. The questionnaire was re-administered on a sub-sample (n = 102) of the same participant’s data set. This was done on two different occasions, one week apart by comparing participant data from both time points.

All the statistical analysis were done using IBM® SPSS® Statistics version 29.0.

Scoring

The scoring methodology involved collaboration among seven subject matter experts, encompassing Nutritionists, Psychiatrist, and metabolic experts. The unadjusted odds ratio, was calculated for the development dataset, where the participants responses were considered as a categorical variable and BMI as a continuous variable, yielding a range from 0.9 to 1.1. Based on this, the weightage of each item is established as 1, and items are organized in ascending order.

Ratings are assigned using a five-point Likert scale. For dietary behavior responses, ranging from 'Daily' to 'Rarely/Never,' in the scale is defined as follows: Daily (0), three to four times/week (1), one to two times/week (2), Sometimes (3), Rarely/Never (4). Physical activity's duration and intensity are similarly assigned on a five-point scale. Barriers associated with a healthy lifestyle are rated from 'strongly agree' to 'strongly disagree': Strongly agree (0), agree (1), neither agree nor disagree (2), disagree (3), strongly disagree (4). The total score ranges from 0 to 68, and a higher score suggests a healthier lifestyle. It considers diet, physical activity, and barriers towards a healthy lifestyle

The summary of the questionnaire development and validation activities and the socio-demographics of the participants are reported in Tables 1 and 2.

The findings of the development and validation of the questionnaire are reported in two parts:

1. Construct of the Questionnaire

The final questionnaire comprised 17 items and was divided into four domains. The first domain (n=5) is focused on the dietary assessment that includes food-related behavior, and frequency of consumption of food. The second domain (n=5) consists of barriers associated with healthy dietary behavior, including attitudes related to eating patterns, food choices, and influence of appetite and satiety. Additionally, items related to the mediators of eating behavior such as stress, media, social support, and social and other environmental triggers are also added. The third domain (n=2) assesses the physical activity of YA in which the level of physical activity is assessed. The fourth domain (n=5) comprises barriers associated with optimum physical activity.

2. Psychometric properties of the questionnaire

Content validity

The calculated S-CVI and S-CVR for the items were 0.92 and 0.96 respectively. 12 items were deleted based on the qualitative assessment, and 08 items were removed due to low CVI (<0.7).

Face validity

A total of 10 items were reworded and reframed based on the rating of unclarity, additional comments on appropriateness, ambiguity, and language were also considered in their modification.

Construct Validity

Supplementary Table 1 presents the inter-correlation matrix, which was utilised to examine the relationships and similarities between pairs of variables in the distribution of questionnaire items. The obtained correlation matrix demonstrated satisfactory results, indicating that while the items exhibit a certain level of similarity, they also possess enough distinctiveness to avoid being excessively similar to one another. This suggests that the items are relatively homogeneous while retaining sufficient unique variability. Additionally, the factorial validity of all the subscales was satisfactory and the KMO and Bartlett test of sphericity (p <0.01) were also adequate (Table 3).

Reliability

All three parts of the questionnaire had good reliability (0.72) excellent internal consistency and test-retest reliability (Table 4)

Dimensionality and Discriminant Validity

The Confirmatory Factor Analysis (CFA) model was illustrated through the utilization of a Structural Equation Modeling (SEM) diagram (figure 1). In this representation, each latent factor was depicted within a circular shape, while all indicator items were encapsulated within rectangular shapes. The unidirectional arrows in the diagram symbolize the standardised loadings of observed variables onto their respective latent factors. Consistent with the recommendations of Exploratory Factor Analysis (EFA), a four-factor model was employed and it underwent refinement based on the loadings of the indicator items. Notably, during the CFA procedure, it was established that the 17 items played a statistically significant role in measuring crucial aspects of the latent factors within their respective domains. Consequently, these factors were retained in the final model.

The goodness of fit indices (Table 5) for the final model was as follows: Tucker-Lewis Index (TLI) of " 0.92," a Comparative Fit Index (CFI) of "0.90," a Standardised Root Mean Square Residual (SRMR) of "0.054," and a Root Mean Square Error of Approximation (RMSEA) of "0.049." These values collectively indicate that the model achieved a commendable fit, affirming the robustness of the questionnaire in terms of its construct and discriminant validity.

The current study yielded a concise and structured tool for the efficient and dependable assessment of lifestyle and behavioural factors for weight management in YAs, with potential for application in both clinical and research settings. This questionnaire comprises a four-factor, 17-item instrument designed to evaluate lifestyle-related behaviours and barriers associated with maintaining a healthy lifestyle among YAs (Table 6). The questionnaire has exhibited satisfactory levels of internal consistency and test-retest reliability.

Previous studies on different age groups have taken diet, physical activity, and sleep as the main components to develop lifestyle-related questionnaires. Similarly, the present study has encompassed items related to these domains with an emphasis on the unique challenges of YAs. However, during the course of the study and subsequent EFA, it was observed that items pertaining to the sleep domain did not load significantly in the factor analysis. Consequently, these sleep-related items were excluded to facilitate confirmatory factor analysis (CFA). This outcome suggests that, in the context of weight management among young adults, sleep may not play a significant role(17). Furthermore, within the physical activity domain, an item assessing the time spent in sedentary activities did not load in the final model due to the ‘flooring effect’. This phenomenon occurred because a substantial majority of participants reported spending more than eight hours engaged in sedentary activities(3,18,19). This finding is concerning, as it underscores the prevalence of sedentary behaviour among the target population. It highlights the need for immediate interventions in educational institutions, workplaces, and communities, emphasising the importance of increasing non-exercise-related activity thermogenesis for maintaining a healthy weight(20).

The items that successfully loaded in the final construct demonstrated alignment with the latent construct and provided support for the theoretical framework, which posits that lifestyle plays a pivotal role in weight management(15). Within the dietary assessment, the questions encompassed regular meal patterns, dietary diversity, consumption of high-fat, high-sugar, and high-salt (HFSS) foods, as well as aspects of emotional and mindful eating(21). In the physical activity domain, the questionnaire assessed levels of physical activity and the role of mediators such as stress, media exposure, social support, and various environmental triggers in poor dietary and physical activity-related behaviour (3,21,22). The final items included in the four-factor model were confirmed through multiple rounds of analysis, incorporating both EFA and CFA. This robust validation process reinforces the questionnaire's validity, reliability, and theoretical underpinnings.

The study has several notable strengths as it overcomes the shortcomings of previously developed, unstructured, unvalidated questionnaires or checklists and the limitations of using multiple validated tools. It is also designed explicitly for YAs with a solid methodological foundation. Additionally, the questionnaire has the potential for wide applicability in clinical, public health, and research settings and to reduce the need for rigorously trained personnel for assessment and analysis. The questionnaires can also be longitudinally administered during follow-up visits to assess the effectiveness of interventions. Furthermore, it can contribute to generating consistent sets of predictors that contribute to the increasing trend of obesity and related lifestyle disorders in young adults thereby informing policy responses for obesity prevention. Additionally, researchers can utilise the consistent dataset to develop predictive models that explain the interaction between different factors and accurately predict the weight loss or weight gain trajectory in various population groups. However, there are a few noteworthy limitations of the study as well: the sample was selected based on convenience sampling, and despite the best effort, there was a lower contribution of a lower socio-economic population and university students. Despite the promising psychometric properties, further validation can be done by examining predictive and concurrent validity.

In conclusion, this study has successfully developed a concise and reliable questionnaire for assessing obesity-related factors in young adults, addressing the limitations of prior unstructured tools and the challenges of using multiple validated instruments. The questionnaire, with its solid methodology, holds promise for widespread use in clinical, research, and public health settings, facilitating assessments and interventions. Its longitudinal applicability can inform obesity prevention strategies and predictive models.

Acknowledgement: None

Author contribution: WA was responsible for conceptualisation, data collection, cleaning, analysis, writing the original draft, and tabulating the findings.
PR was responsible for funding acquisition, supervision, development of methodology, review of manuscript. AM was responsible for writing and editing the manuscript, conceptualising and supervising. ADU was responsible for data analysis and model development. GK and MV was responsible for data collection and screening the participants. AS and BP was responsible for resources and visualisation. KSD was responsible for validating the scores, writing-review and editing. NKV was responsible for project administration and funding acquisition.

Funding: This study has been funded by the Indian Council for Medical Research, with reference no. I-1466.

Ethical Approval: The study has been ethically approved by the Ethics Committee with reference no. IEC-798/07.10.2022

Competing Interests: None declared.

Data Availability Statement: The data has been made available in the supplementary files for the reference.

Source(s) of support: None

Conflicts of Interest: None declared

Statement: We, the authors, approve that the requirement for the authorship, as stated has been met and the manuscript represents honest work.

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Table 1: Socio-demographic profile of the participants (n=302)

Characteristics	Value
Gender
Male	133(44)
Female	169(56)
Socio-economic status
Upper	134(44.3)
Middle	112(37.08)
Lower	56(18.5)
Education
Postgraduate	77(25.5)
Graduate	137(45.4)
Intermediate	53(17.6)
Matriculate	27(8.9)
Middle-school certificate	08(2.6)
Marital Status
Married	34(11.25)
Single	268(88.75)
Place of Residence
Metropolitan	196(64.9)
Town	2(0.6)
City	104(34.5)
Anthropometric Parameters
Body Mass Index (BMI) Overweight (23.5 kg/m²-24.9 kg/m²) Obese I (25.0 kg/m²-27.9 kg/m²) Obese II (≥28.0 kg/m²)	116(38.4) 100(33.1) 86(28.5)
Values are presented as mean ± standard deviation or number (frequency%)

Table 2: Summary of questionnaire revisions during various phases of validity and reliability

Phase Information	Content Validity (Phase 2)	Face Validity (Phase 3)	Construct Validity (Phase 4)	Test-Retest Reliability (Phase 5)	Test of Dimensionality & Discriminant Validity (Phase 6)
Study Activity	Subject Matter Experts (SME) review	Pilot Testing	Exploratory Factor Analysis (EFA) with varimax rotation	Reliability Testing	Confirmatory Factor Analysis
Participants	10	30	302	102	152
Summary	Two rounds of SME review, 12+8 items removed	10 items were reworded or reformed based on the ratings	19 items were removed following multiple rounds of EFA, four-factor domain emerged	Re-Administration of the questionnaire on the subset of the same participants, one week apart	2 additional items were removed to converge a final 17-item, 4-factor model
Locations/Sessions	Academic Block	Out-patient department	Out-patient department	Out-patient department	Out-patient department
Revised Questionnaire Version, items	V1 n=58	V2 n=58	V3 n=38	V3 n=38	V4 n=17

Table 3: Factor loadings and Exploratory Factor Analysis Findings

QUESTION	DOMAIN 1		DOMAIN 2	DOMAIN 3	DOMAIN 4
Q21	0.708
Q24	0.773
Q25	0.682
Q26	0.584
Q27	0.748
Q31				0.715
Q32				0.504
Q33				0.561
Q34				0.611
Q42				0.326
Q43					0.854
Q44					-0.844
Q47			0.505
Q48			0.519
Q49			0.731
Q50			0.73
Q51			0.711
*Scale Statistics*
Mean	Variance	Standard Deviation	Cronbach’s alpha	KMO (Kaiser-Meyer Olkin)	Bartlett’s Test of Sphericity
83.37	216.199	14.704	.72	0.723	Appx Chi-square: 2855.989 df: - 741 Sig.: .000

Table 4: Intraclass Correlation of the items after test-retest analysis

Questions	Intraclass Correlation	95% Confidence Interval
		Lower Bound	Upper Bound
How often do you make a conscious effort for regular meals (three major and two minor)	0.987	0.976	0.998
How often do you consume the three servings of whole grains (whole wheat, millet, whole pulses etc)	0.985	0.978	0.998
How often do you consume 1-2 serving of protein-rich foods (Dairy, Legumes, nuts, and chicken)	0.978	0.968	0.988
How often do you consume 2-3 servings of dairy and dairy-based products?	0.967	0.957	0.977
How often do you include 4-5 servings (400-500gm) of fruits and vegetables in your diet.?	0.956	0.945	0.966
How often do you eat when you're not hungry (e.g., when stressed, bored, or emotional)?	0.988	0.978	0.999
How often do you eat until you feel uncomfortably full?	0.945	0.934	0.955
Do you eat while distracted in leisure activities (e.g., watching TV, or scrolling on your phone)?	0.956	0.949	0.966
I often get tempted to eat food items high in fat, salt, and sugar (HFSS) after watching the advertisements of food on social media and apps	0.998	0.987	1.000
My friends and family often offer me foods rich in fat, sugar, and salt at social events and family gatherings	0.912	0.901	0.922
How often in a week do you engage in moderate-vigorous physical activity (brisk walking, dancing, jogging, cycling, swimming, playing outdoor sports etc)	0.945	0.934	0.955
How many minutes do you spend on moderate-vigorous physical activity per day	0.977	0.967	0.989
I don’t have enough time to indulge in physical activity due to my personal and professional commitments	0.978	0.968	0.988
I find it challenging to engage in physical activities due to joint pain/body pain/excessive tiredness.	0.965	0.955	0.976
My friends and family members show little interest in maintaining an active lifestyle	0.943	0.934	0.955
I don't have access to parks, fitness centres, and gyms	0.934	0.944	0.954
I find it challenging to engage in physical activity due to weather or outside temperature	0.912	0.901	0.922

Table 5: Model Fit Indices of Structure Equation Model through Confirmatory Factor Analysis

Model Fit Indices	RMSEA	P-CLOSE	CFI	TLI	SRMR	X2/df
	0.049	0.524	0.90	0.920	0.054	1.70

Table 6: Final questionnaire after confirmatory factor analysis

LIFESTYLE AND ASSOCIATED BARRIERS
This section aims to assess your general dietary habits that encompass your consistent food and drink consumption patterns
Statement	Daily	3-4times/week	1-2 times/week	Sometimes	Rarely/Never
How often do you make a conscious effort for regular meals (three major meals+ two snacks)
How often do you consume the 3 servings of whole grains (whole wheat, millet, whole pulses)
How often do you consume 1-2 servings of protein-rich foods (dairy, legumes, nuts, and chicken)?
How often do you consume 2-3 servings of dairy and dairy-based products?
How often do you include 4-5 servings (400- 500gm) of fruits and vegetables in your diet?
This section aims to assess your *barriers to healthy eating* by examining the actions, attitudes, and environment related to your food and eating pattern
Statement	Daily	3-4 times/week	1-2 times/week	Sometimes	Rarely/Never
How often do you eat when you're not hungry (e.g., when stressed, bored, or emotional)?
How often do you eat until you feel uncomfortably full?
Do you eat while distracted in leisure activities (e.g., watching TV, or scrolling on your phone)?
I often get tempted to eat food items high in fat, salt, and sugar (HFSS) after watching the advertisements of food on social media and apps
My friends and family often offer me foods rich in fat, sugar, and salt at social events and family gatherings
This section aims to assess your *general physical activity behavior* that encompasses your habitual patterns of movement and exercise that you engage in as part of your daily life
1D. How often in a week do you engage in moderate-vigorous physical activity (brisk walking, dancing, jogging, cycling, swimming, playing outdoor sports etc) (i) Daily (ii) 5-6 times per week (ii) 3-4 times per week (iii) Once in a fortnight (iv) Never 2D. How many minutes do you spend on moderate-vigorous physical activity per day (i) <30 minutes (ii) 30 minutes-60 minutes (iii) 60 minutes-90 minutes (iv) >90 minutes (v) Not Applicable
This section consists of statements that aim to assess the barriers to physical activity affecting your ability to engage in regular exercise or movement
Statement	Strongly Agree	Agree	Neither Agree nor Disagree	Disagree	Strongly Disagree
I don’t have enough time to indulge in physical activity due to my personal and professional commitments
I find it challenging to engage in physical activities due to joint pain/body pain/excessive tiredness.
My friends and family members show little interest in maintaining an active lifestyle
I don't have access to parks, fitness centres, and gyms
I find it challenging to engage in physical activity due to weather or outside temperature

There is NO conflict of interest to disclose.

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Editorial decision: revise
20 May, 2024
Review #1 received at journal
08 May, 2024
Reviewer #1 agreed at journal
15 Apr, 2024
Reviewers invited by journal
12 Jan, 2024
Editor assigned by journal
19 Dec, 2023
Submission checks completed at journal
19 Dec, 2023
First submitted to journal
18 Dec, 2023
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18 Dec, 2023

You are reading this latest preprint version

Development and Psychometric Properties of a Lifestyle-Related Behaviors & Barriers Scale (LBBS) among Young Adults

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Abstract

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Introduction

Methodology

Research Design

Ethical Clearance and Informed Consent

Sampling

Step 1: Generation of items and Development of construct

Step 2: Content validity

Step 3: Assessment of face validity

Step 4: Questionnaire administration

Step 5: Item Reduction & Extraction of Factors for Construct Validity

Step 6: Assessment of Dimensionality and Discriminant Validity

Step 7: Test of Reliability

Internal Consistency Assessment

Stability

Scoring

Results

Discussion

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1