Development and psychometric evaluation of the physical activity and nutritional behavior questionnaire based on social cognitive theory (PANBQ-SCT) in the middle aged at risk of coronary artery disease

doi:10.21203/rs.3.rs-4208712/v1

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Research Article

Development and psychometric evaluation of the physical activity and nutritional behavior questionnaire based on social cognitive theory (PANBQ-SCT) in the middle aged at risk of coronary artery disease

https://doi.org/10.21203/rs.3.rs-4208712/v1

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Background

Coronary artery disease (CAD) is the most common cardiovascular disease and the main cause of mortality in developed and developing countries. Physical activity and nutrition behaviors are modifiable factors in people at risk of CAD and the related risk factors. There is evidence to suggest that socio-cognitive factors play a crucial role in adopting physical activity and nutritional behaviors. The present study aimed to develop and evaluate the psychometric properties of the physical activity and nutritional behavior Questionnaire based on the social cognitive theory (PANBQ-SCT).

Methods

A questionnaire was developed based on the constructs of Bandura’s Social Cognitive Theory, knowledge, self-efficacy, collective efficiency, outcome expectations, observational learning, normative beliefs, social support, barriers and opportunities, reinforcement and punishment, behavioral skills, behavioral intention and nutritional behaviors. The questionnaire was administered as a two-week test-retest among the middle aged at risk of CAD. Confirmatory factor analysis was run to test the model fit of each scale using multiple indices including chi-square test, comparative-fit index (CFI), goodness-of-fit index (GFI), and the root mean square error of approximation (RMSEA). Reliability indices were also tested (ICC and Cronbach’s alpha).

Results

The reliability and factorial validity of each subscale were substantiated. Fit indices suggested that each model was an adequate-to-exact fit to data (CFI = .928, IFI = .894, GFI = .943, TLI = .969, RMSEA = .046). The internal consistency of the test was good, as Cronbach’s alpha coefficient for the entire scale was 0.913, and for the subscales ranged between 0.768 and 0.899. Also, the ICC ranged between 0.643 and 0.918.

Conclusions

The results substantiated the reliability and factorial validity of the socio-cognitive constructs related to physical activity and nutrition behaviors among the middle aged at risk of CAD. Thus, the suggested scale can be used to identify potential socio-cognitive correlates of middle age physical activity and nutrition behaviors, the mediators and validation of theoretical models based on SCT.

Factor analysis

SCT

Psychometric

Coronary artery disease

Nutrition behavior

Physical activity

Middle-aged

CAD is the most common type of heart disease and remains the leading cause of mortality worldwide, accounting for more than 350,000 mortalities on an annual scale (1, 2). CAD is a multi-caused disease in which increased cholesterol, high blood pressure, diabetes and insufficient physical activity are the main risk factors(3).

Coronary artery disease (CAD) is the leading cause of mortality in developed and developing countries. The prevalence of risk factors among the healthy population increases the possible occurrence of CAD in near future (4).

High blood pressure, high blood cholesterol level, cigarette smoking, diabetes, overweight or obesity, insufficient physical activity and improper nutrition are the main risk factors of CAD (4, 5). Unhealthy eating behaviors and insufficient physical activity are important risk factors of CAD.

Improper nutritional behaviors are on the rise in Iran, especially among children and women. The dietary pattern of Iranian people is limited when people are more inclined to consume fast food, made up of a limited range of food stuff with the least variety (6). In Hormozgan province, the type of residents’ nutrition is associated with high consumption of sugary and fatty materials (7).

Research has shown that unhealthy eating habits increase in middle age (8).

Insufficient physical activity has been recognized as an independent risk factor of CAD (9, 10). About 30% of the middle-aged are physically inactive (11, 12), and the current objective of WHO is to reduce the global prevalence of insufficient PA by 15% by 2030 (13). This problem is very common in Iran as it has often been observed that nutrition in Iran is limited to the consumption of certain foods with almost no variety in pattern (6). Theory-based research provides a framework for designing, implementing, and evaluating interventions (14). It aims to facilitate the understanding of factors influencing behavior change (15, 16). The socio-cognitive theory (SCT) is a promising theory for use in behavior change interventions (17).

The lack of standardized tests is a major barrier to health-related research and, if removed, can pave the way for productive research. The existence of measurement instruments, if of acceptable psychometric properties, enables timely diagnosis and screening. These instruments can be used in epidemiological studies to provide a basis for planning to prevent disorders and ultimately improve public health (18). Considering the importance of using standard instruments, Leung contends in his study that having valid and reliable instruments is inevitable for more effective interventions and for the design and evaluation of theory-based health promotion programs (19). The pre-existing physical activity and nutritional behavior questionnaires were not designed for the middle aged and for those at risk of diseases. Some of these instruments only addressed a few constructs of the theory (20, 21).

As the review of literature showed, no study had been conducted on the development and psychometric evaluation of the nutritional behavior and physical activity questionnaire based on SCT in middle-aged population at risk of CAD in Iran; thus, it was essential to design a theory-based instrument with strong psychometric properties to measure physical activity and nutritional behaviors. To this aim, the present study aimed to design and psychometrically evaluate a nutritional behavior and physical activity questionnaire based on SCT for the middle-aged at risk of CAD.

Research design and population

The present methodological research was carried out in qualitative and quantitative phases, approved by the Ethics Committee of Hormozgan University of Medical Sciences [#IR.HUMS.REC.1401.065]. written Informed consent was obtained from all participants and, for illiterate participants, from close relatives.

The present study was part of a larger research project (22) conducted from June 2022 to May 2023 in four health centers in Bandar Abbas, in the south of Iran. The coastal city of Bandar Abbas is the capital of Hormozgan province, located in the south of Iran, with an area of nearly 70 square kilometers and a population of 680,000 (23). The research population included all middle-aged people between 35 and 55 years who enrolled in the National Integrated Health System (known as Seeb). There are 21 urban health centers in Bandar Abbas. All centers were used in the sampling. A simple random sampling method was used to recruit the middle-aged at risk of CAD from comprehensive health centers of Bandar Abbas, Hormozgan, Iran. In the first phase, the items were constructed through a qualitative method, and then in the second phase, the psychometric properties of the scale were evaluated in a cross-sectional study. The psychometric evaluation was done through a confirmatory factor analysis (CFA) to check the \ validity. The reliability of the instrument was also measured.

Inclusion and Exclusion criteria

The inclusion criteria were:(1) the age of 35 to 55 years, (2) having at least one risk factor of CAD (hyperlipidemia, hypertension, diabetes, overweight and obesity as diagnosed by a physician and approved by a health care provider), (3) willingness to participate in the study, 4) residence in Bandar Abbas.

The exclusion criteria were: (1) chronic diseases such as cardiovascular diseases, kidney, cancer, mental diseases, (2) incomplete questionnaires.

Phase 1: Design and item generation

Initially, semi-structured interviews were held for a qualitative directed content analysis approach based on SCT with 20 middle-aged participants at risk of CAD in Bandar Abbas.

Participants

The research population was middle-aged people visiting health centers with less than 150 minutes of weekly physical activity and at least one CAD risk factor. These people entered the study through a purposive sampling with maximum variety (age, sex, education, marital status, employment status, risk factors).

Data collection

The data collection technique in this phase was in-depth one-on-one interviews (40–60 minutes) which continued until data saturation. At the beginning of each interview, after introducing himself and explaining the purpose of study, the researcher gained the participant’s consent for interview. All interviews were conducted by the first author who was fluent in Persian and local languages. The time and place of the interview was decided on as the participants preferred. Permission was gained from the participants to audio-record the interview. The interview guide was developed based on the SCT.

Data analysis

The recorded interviews were transcribed verbatim and typed. For a deep understanding of the interview, each interview was read several times and then divided into the smallest meaningful units (codes). The analysis of research data was done through a directed qualitative content analysis approach based on the socio-cognitive theory in Max-QDA 10. These items were reviewed and finally approved by the research team to ensure no overlap and no repetition in multiple sessions. The duplicates were removed and the items that could be integrated were merged with each other. The items were also modified, then the instrument entered the psychometric phase with 159 items, 147 of which were about 11 constructs of the socio-cognitive theory extracted from qualitative phase interviews. Also, 12 questions were related to nutritional behaviors extracted from the Mediterranean diet questionnaire. Studies have shown that the Mediterranean diet has a protective effect against cardiovascular diseases. These studies especially showed its protective role in primary and secondary prevention of cardiovascular diseases (33–35). Mediterranean diet questions were about the consumption of olive oil, fruits and vegetables, red meat, butter and cream, carbonated drinks, legumes, seafood, sweets, nuts, chicken and turkey, and rice. The initial Mediterranean diet questionnaire contained 13 items, and the item related to wine consumption was removed as it is considered a taboo in Islam. The items related to the consumption of pork and rabbit meat were reworded and the answers on a 5-point Likert scale were modified to always to never. The 12 items entered the psychometric phase.

Phase 2: Validity and reliability evaluation of the instrument

Content validity

Content validity provides evidence about the degree to which elements of a measurement instrument are relevant to and representative of a given construct for a particular assessment purpose (24).

Quantitative content validity was checked through content validity ratio (CVR) and content validity index (CVI). In this phase, the proposed instrument was provided to 10 health education and health promotion specialists, cardiology and nutrition specialists. This panel of experts were supposed to evaluate the grammar, phrasing, division of items and scaling indicators.

To calculate the CVR, the aforementioned experts were asked to evaluate the necessity of each item using a 3-point rating scale (‘The item is essential”, “The item is useful but not essential”, and “The item is not essential”). CVR was calculated through the following formula:

$$\varvec{C}\varvec{V}\varvec{R}=\frac{{\varvec{n}}_{\varvec{e}}- \frac{\varvec{N}}{2}}{\frac{\varvec{N}}{2}}$$

ne is the number of experts evaluating an item as “essential”
N is the total number of experts
Based on Lawshe table and the number of experts (n = 10), the value of 0.62 was considered as the minimum acceptable value for the content validity ratio. Based on Lawshe table and the number of experts (n = 10), the value of 0.62 was considered as the minimum acceptable value for the content validity ratio.

To estimate CVI, three criteria of simplicity, relevance and clarity on a 5-point Likert scale for each item were evaluated by relevant experts and calculated through the following formula:

A score of 0.79 and above for each item led to the acceptance and maintenance of that item.

Face validity

Both quantitative and qualitative methods were used to test the face validity. In the qualitative phase, the questionnaire was administered to 10 middle-aged subjects who met the inclusion criteria to check the ambiguity, relevance and difficulty of each item. In the next phase, a quantitative method was used to discard inappropriate items and determine the relative importance of each item. In this phase, a 5-point Likert scale was used for each item in the questionnaire, ranging from very important (5 points), somehow important (4 points), relatively important (3 points), slightly unimportant (2 points) and not important at all (1 point). Then, 10 participants were asked to review all items and rate the importance of each item on a 5-point Likert scale. Then the score of each item was calculated separately based on the following formula:

Impact Score = Frequency(%)∗importance

If the impact score was 1.5 or higher, the item was retained for further analysis.

Construct validity

The construct validity of the questionnaire was tested using confirmatory factor analysis (CFA).

Confirmatory factor analysis was run to investigate a special factor structure. The number of factors, the number of items and the pattern of placement of items in each factor were clearly stated as a hypothesis and the fit of the factor structure in the hypothesis with the structure of the measured covariances was tested (25).

The minimum sample size required to run the confirmatory factor analysis is 5 people per item (26). In the present study, the sample size was estimated at 490 according to the number of items.

Among the comprehensive health service centers in Bandar Abbas, four centers were randomly selected. According to the sample size, 122 patients from two centers and 123 from two other centers were randomly selected based on the list of the middle-aged registered in Seeb to enter the study.

The fitness of the proposed models for the questionnaire was checked using the chi-square index, Goodness of Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), the index of the ratio of the chi-square statistic to the degree of freedom. Bentler's Comparative Fit Index (CFI), Akaike Information Criterion (AIC) and Root Mean Square Error of Approximation (RMSEA). Since each index only indicates a certain aspect of the model fit, several indices are usually used to check the adequacy of the model fit (27). It should be noted that GFI and AGFI are between zero and one, and values greater than 0.9 indicate a good fit of the model. The CFI index is also between zero and one, and the closer it is to one, the better fit the model has. Values greater than 0.9 for this index indicate a good fit of the model (28, 29). RMSEA value less than 0.05 shows a good fit, values around 0.08 indicate average fit, and values greater than 0.1 indicate poor fit of the model (30). Regarding the chi-square value, its lower values and its non-significance with respect to the degree of freedom indicate a good fit of the model, but since it is difficult to achieve such a criterion in questionnaires with a large number of questions(31), instead, it is suggested to use the ratio of the chi-square statistic to the degree of freedom as an index of the goodness of fit, and values less than 3 of this index represent a good model fit (32, 33).

Reliability

To test the reliability of the instrument, test-retest method and Cronbach's alpha were used for each sub-scale of the questionnaire and the whole questionnaire as well. To this aim, 30 middle-aged subjects were asked to complete the questionnaire twice with an interval of 2 weeks. The scores of the two phases of instrument use were calculated and their intra-cluster correlation coefficient (ICC) was estimated using SPSS. ICC values less than 0.5, between 0.5 and 0.75, between 0.75 and 0.9 and more than 0.9 indicate poor, moderate, good and excellent reliability (34).

Statistical analysis

To measure the validity of the instrument designed for factors affecting nutritional behaviors and physical activity based on the SCT constructs, content validity, face validity, construct validity and confirmatory factor analysis were used. To test the reliability of instrument, Cronbach's alpha test of internal consistency was used as well as the test-retest method in SPSS21 and Amos21.

Qualitative findings

The average age of the participants was 45.85 years. High blood pressure was the most common risk factor. Most participants were married, employed and had university degrees.

Content validity

To increase the qualitative content validity, some items were modified according to experts' opinions. In the quantitative stage, according to Lawshe table, 49 items with scores less than 0.62 were removed and the rest were retained.

In testing the CVI, as the Waltz & Bausell's index showed, all items scored higher than 0.79.

Face validity

To test the qualitative face validity, 6 items whose legibility/comprehensibility was low were modified. In the quantitative face validity, 12 items that scored below 1.5 were removed and finally 98 items were retained for the next step.

Reliability

In evaluating the results of face validity, content validity ratio and content validity index showed that the instrument with 98 items was acceptable and ready to be checked for other validity indices. Thus, the instrument entered the next phase to check the validity of the construct.

Construct validity

A total number of 490 subjects completed the 98-item questionnaire, and their demographic information is summarized in Table 1.

Table 1

Research participants’ demographic characteristics
Demographic variable	Level	f.	%
Age	35–45 46–55	284 206	58 42
Sex	Female Male	308 182	62.9 37.1
Marital status	Single Married Divorced/Widowed	62 399 29	12.7 81.4 5.9
Occupation	Employee Retired Housewife Unemployed Student Self-employed	159 39 155 6 28 103	32.4 8 31.6 1.2 5.7 21
Education level	Illiterate Elementary High school Diploma University degree	23 58 89 107 213	4.7 11.8 18.2 21.8 43.5
Socio-economic status	High Moderate Low	131 318 41	26.7 64.9 8.4
BMI	>18.5 18.5–24.9 25–30 < 30	10 213 166 101	2 43.5 33.9 20.6
Smoking	No cigarettes hookah Other	416 21 49 4	84.9 4.3 10 0.8
Hypertension	Yes no	263 227	53.7 46.3
Hyperlipidemia	Yes no	183 307	37.3 62.7
Diabetes	Yes no	235 255	48 52
Family history of CAD	Yes no	152 338	31 69

The model examined in the CFA phase was a 98-item model with 12 sub-scales, knowledge, self-efficacy, collective efficacy, outcome expectations, observational learning, normative beliefs, social support, barriers and opportunities, reinforcement and punishment, behavioral skills, behavioral intention and nutritional behaviors. Table 2 shows the results of testing the structural model of subscales with the correlation of structures assumed.

Table 2

Fit indices of confirmatory factor analysis for different models
Model		Df		GFI	AGFI	CFI	RMSEA (90% CI)	AIC
Initial 98-item model	10059	3857	2.60	0.856	0.807	0.816	0.063[0.061–0.065]	1978
Final 87-item model	7106	3524	2.01	0.943	0.931	0.928	0.046[0.044–0.048]	1218

As the GFI, AGFI and CFI indices show in Table 2, the initial model did not adequately fit the data. Also, the value with the corresponding degree of freedom and P < 0.0001 showed a poor model fit. Thus, this index was not used for the goodness of fit, but and RMSEA showed acceptable fit of the model. According to these values, in general, the model could not be considered a good model. Therefore, the original 98-item model was revised after testing the factor loadings and the correlation between items and sub-scales. Finally, 11 items were excluded from the model as their factor loading was less than 0.3. These included 4 items for knowledge, 2 for normative beliefs, 2 for barriers and opportunities, 1 for reinforcement and punishment and 2 for nutritional behaviors (27). An 87-item model was introduced whose fit indices were: GFI = 0.943, AGFI = 0.931, CFI = 0.928 and RMSEA = 0.046 at a confidence interval of 95 percent (0.044–0.048), and 7106 = 3524 degrees of freedom (P < 0.0001). As the relevant values showed, this model had a good fit to the data. Moreover, considering that the AIC value for this model is equal to 1218 and lower than the value of the same index for the previous model, this 87-question model was the best fitting model (Table 2).

Factor loadings of the revised model of 87 items are shown in Table 3. As the tabulated findings shows, all estimated standardized factor loadings were significant at the 0.05 level.

Table 3

Factor loadings of questionnaire items in the subscales estimated via confirmatory factor analysis
Construct/subscale	item	factor loading	mean
Knowledge	Physical activity at a moderate intensity at least 5 days a week and at least 30 minutes a day is useful to prevent coronary artery disease.	0.39	0.76
	Activities such as walking and cycling are useful to prevent coronary artery disease.	0.334	0.77
	The minimum time for effective physical activity is 10 minutes nonstop.	0.452	0.59
	Physical activity affects the control of sugar, blood pressure and blood fat.	0.382	0.77
	Daily consumption of at least 4 tablespoons of olive oil is useful to prevent coronary artery disease.	0.63	0.56
	Daily consumption of at least one glass of vegetables is useful to prevent coronary artery disease.	0.642	0.74
	Daily consumption of at least 3 fruits is useful to prevent coronary artery disease.	0.559	0.73
	The weekly consumption of at least one and a half glass of beans is to prevent heart disease.	0.614	0.61
	Weekly consumption of three pieces of fish or seafood is useful to prevent coronary artery disease.	0.537	0.75
	Weekly consumption of at least 2 tablespoons of nuts is useful to prevent coronary artery disease.	0.556	0.66
Self-efficacy	I can eat healthy food in any situation.	0.575	3.39
	I can do physical activity at least 5 days a week for 30 minutes every day.	0.607	3.27
	I can acquire the right information about how to do physical activity.	0.377	3.6
	I can acquire the right information about healthy nutrition.	0.467	3.99
	I can do regular physical activity despite household chores.	0.616	3.65
	I can have a healthy diet despite the high cost of healthy food.	0.529	3.01
	I can maintain regular physical activity despite my busy schedule.	0.715	3.23
	I can continue regular physical activity despite adverse weather conditions.	0.643	3.1
	I can continue to eat healthy food in any situation.	0.605	3.26
	I can constantly be physically active.	0.629	3.41
Collective efficacy	I can have regular physical activity if supported by people around me.	0.312	3.72
	I can have healthy nutrition if supported by people around me.	0.337	3.6
	I can be physically active with my friends feeling safer	0.485	3.89
	I can use the experiences of people in online groups to improve physical activity.	0.783	3.71
	I can use the experiences of people in online groups to have healthy nutrition.	0.827	3.69
	I can be physically active with the help of information and new ideas shared in online groups.	0.704	3.56
	I can be physically active with the help of information and new ideas shared in online groups.	0.703	3.53
Outcome expectations	I will live longer if I do regular physical activity.	0.331	3.71
	I will live longer if I eat healthy food.	0.657	3.46
	I will have less stress with regular physical activity.	0.7	4.22
	By eating healthy food, I will have lower medical expenses.	0.67	4.21
	With regular physical activity, I will have lower medical costs.	0.727	4.31
	I will be in a better mood by doing regular physical activity.	0.72	4.32
	If I fail to have a healthy diet, my body gets weak.	0.619	4.07
	If I fail to do regular physical activity, my body gets weak.	0.614	3.95
	If I fail to have a healthy diet, I will gain weight.	0.635	4.04
	If I fail to have regular physical activity, I get overweight.	0.565	4.06
Observational learning	I learn how to cook healthy food in online social networks.	0.486	3.73
	I learn appropriate physical activity online.	0.621	3.32
	I learn regular physical activity from people I know.	0.601	3.57
	I learn healthy nutrition from people I know.	0.509	3.59
	I tend to eat healthy food when I see people eating healthy food and are in a good shape.	0.624	4.11
	I tend to do regular physical activity when I see people who do regular physical activity and have a fit body.	0.615	4.1
Normative beliefs	People around me believe that homemade food is much healthier and better than eating out.	0.416	3.71
	People around me believe that I don't need physical activity because I do housework.	0.324	3.46
	If I do regular physical activity, I will be accepted by those around me.	0.809	3.18
	If I eat healthy food, I will be accepted by those around me.	0.756	3.22
Social support	Those around me encourage me to do physical activity.	0.564	3.72
	Those around me encourage me to have a healthy diet.	0.56	3.77
	I acquire the right information about healthy diet from social networks.	0.8	3.6
	I acquire the right information about physical activity from social networks.	0.792	3.6
	I acquire the right information about healthy diet from health specialists or providers.	0.47	3.72
	I acquire the right information about physical activity from health specialists or providers.	0.415	3.68
Barriers and opportunities	My passion for physical activity paves the way for me to do it.	0.527	2.81
	Membership in social networks paves the way for me to do physical activity.	0.613	3.09
	Membership in social networks paves the way for me to learn healthy eating.	0.819	2.58
	Having a suitable place in the neighborhood has become an opportunity for me to do physical activity.	0.516	2.25
	Weather conditions have prevented me from doing physical activity.	0.502	2.19
	For the long distance from the gym, I cannot do regular physical activity.	0.726	2.65
	I use sports equipment in parks to do physical activity.	0.68	2.73
	I cannot have a healthy diet because of the high cost of healthy food.	0.659	2.62
Reinforcement and punishment	Hope for future encourages me to eat healthy.	0.429	3.85
	Fear of disability in old age motivates me to do physical activity.	0.602	3.82
	Being responsible for my family encourages me to eat healthy food.	0.787	3.95
	Being responsible for my family encourages me to be physically active.	0.844	3.97
	Fatigue from physical activity discourages me from doing regular physical activity.	0.448	3.89
	Having a regular healthy diet especially for a long time is boring.	0.408	3.89
	Fear of coronary artery disease encourages me to do regular physical activity.	0.565	3.87
Behavioral skills	If I have stress control skills, I can do physical activity.	0.574	3.59
	If I have the skill to say no, I can avoid eating unhealthy foods.	0.512	3.52
	If I have planning skills, I can engage in physical activity.	0.677	4.01
	I can have a healthy diet if I have the skills to cook with healthy food available.	0.687	3.86
	I can do physical activity if I have the skills to do physical activity suitable for my individual conditions.	0.763	3.9
Behavioral intention	I intend to have regular physical activity.	0.46	3.96
	I plan to have regular physical activity.	0.784	3.67
	I intend to have a healthy diet.	0.664	4.04
	I plan to have a healthy diet.	0.799	3.85
Nutrition behaviors	I consume at least 4 tablespoons of olive oil daily.	0.416	2.12
	I consume at least two glasses of raw vegetables or one glass of cooked vegetables every day.	0.5	2.79
	I eat at least 3 fruits on average every day.	0.398	3
	I eat less than 100–150 g meat, hamburger and so on (at the size of 3–5 boxes of match) every day.	0.432	2.43
	I consume less than one tablespoon of butter, margarine or cream every day.	0.57	2.4
	I consume less than one glass of sweet carbonated drinks every day.	0.583	3.26
	I consume at least one and a half glass of beans every week.	0.452	2.88
	I eat at least 3 pieces of fish or seafood every week.	0.346	2.62
	I eat less than 3 sweets per week.	0.38	2.66
	I eat at least 2 tablespoons of nuts per week.	0.748	2.65

Table 4 summarizes the results of the reliability test of questionnaire through Cronbach's alpha test. As the results show, the estimated coefficients for the subscales range between 0.768 and .899 indicating good values. Cronbach's alpha coefficient of the entire questionnaire is 0.913, indicating the acceptable reliability of the questionnaire. The scale score is the result of dividing the mean and standard deviation of each dimension by the number of items.

Table 4

Reliability of the physical activity and nutritional behavior questionnaire based on the social cognitive theory (PANBQ-SCT) in middle-aged population at risk of CAD
Construct/Subscale	Cronbach’s alpha	Number of items	Total score		Scaled score
Construct/Subscale	Cronbach’s alpha	Number of items	mean	Std. Deviation	mean s	Std. Deviation s
Knowledge	0.86	10	6.92	3.02	0.69	0.30
Self-efficacy	0.859	10	34	6.34	3.4	0.63
Collective efficacy	0.899	7	25.7	4.85	3.67	0.69
Outcome expectations	0.894	10	41.68	4.92	4.16	0.49
Observational learning	0.768	6	22.42	3.36	3.73	0.56
Normative beliefs	0.868	4	13.56	3.53	3.39	0.88
Social support	0.897	6	22.08	4.62	3.68	0.77
Barriers and opportunities	0.875	8	20.92	5.67	2.61	0.70
Reinforcement and punishment	0.847	7	27.25	4.29	3.89	0.61
Behavioral skills	0.793	5	18.86	2.94	3.77	0.58
Behavioral intention	0.793	4	15.52	2.18	3.88	0.54
Nutrition behaviors	0.837	10	26.82	7.38	2.68	0.73
Entire questionnaire	0.913	87	22.97	4.42	0.26	0.0

As the present findings showed, after removing 11 items from the initial 98-item questionnaire, the final version had acceptable reliability and validity and could be used as a valid questionnaire in future research. Having removed 11 items from the original 98-item questionnaire, the final version of the questionnaire was developed with 87 items, a very good reliability and construct validity to be used as a valid questionnaire in future research.

The present research aimed to develop and evaluate the psychometric properties of the PANBQ-SCT in middle-aged population at risk of CAD. The initial draft of the current questionnaire was developed during a qualitative study. After removing a number of items, the evaluation of the questionnaire continued. The results confirmed the reliability and validity of the questionnaire. Eventually, 87 items were confirmed after examining the face validity, content validity and construct validity. The items were divided into 12 subscales of knowledge, self-efficacy, collective efficacy, outcome expectations, observational learning, normative beliefs, social support, barriers and opportunities, reinforcement and punishment, behavioral skills, behavioral intention and nutritional behaviors. The results of this study showed that the current instrument enjoyed high reliability and validity. The SCT model proved to be an effective framework for physical activity and nutritional behaviors in the middle-aged population, and the present questionnaire can be used to measure the effect of interventions on physical activity and nutritional behaviors in the middle-aged.

In the present study, the estimated Cronbach's alpha for each subscale was between 0.768 and 0.899, and total alpha coefficient of the entire questionnaire was 0.913. The test-retest results for each construct ranged between 0.918 and 0.643. In the study of Nematollahi et al., the internal consistency of the questionnaire was estimated at 0.90 for women in the city of Isfahan(20). In another study, Ardestani et al. evaluated the physical activity behavior of Iranian female teenagers. The estimated Cronbach's α coefficient ranged between 0.78 and 0.85 and the intraclass correlation coefficient ranged between 0.73 and 0.90 (21). Nematollahi also evaluated the psychometrics of a calcium intake questionnaire based on the SCT, and reported a Cronbach's alpha of 0.901 for the scale (35). In a study of homeless Australians (age range 17–78 years, 79% male) regarding an oral health questionnaire, Cronbach's alpha of the instrument was estimated for the three subscales of oral health-related self-efficacy, oral health-related knowledge and oral health-related fatalism. The estimated values were, respectively, 0.95, 0.85 and 0.69 (36).

In Ardestani's investigation of the validity and reliability of a researcher-made questionnaire based on SCT to evaluate the physical activity behavior of Iranian female teenagers, the content validity index, content validity ratio and impact score were, respectively, 0.97-1.0, 0.91-1.0 and 4.6–4.9 (21).

The results of the psychometric evaluation of the present questionnaire (CFA = 7106, DF = 3524, CFI = 0.928, CFI = 0.046, RMSEA = 0.046) proved the appropriateness and acceptability of a questionnaire based on SCT. The four-factor model with a total variance of 80.9% was identified (P < 0.001). The CFA results (CMIN = 276.874, DF = 166, P < 0.001, CFI = 0.961, 061 RMSEA = 0) showed the appropriateness and acceptability of the model based on SCT (20). In the study of Nemaollahi, a four-factor model with a total variance of 72.3% and CFA results of 1.850 (CMIN/DF = 0.946) showed RMSEA = 0.938 and TLI = 0.938 (35). In the study of Mirzaei et al., principal component analysis with varimax rotation resulted in a four-factor construct. These four factors accounted for 65.9% of the whole variance (37). The results of the present research were consistent with studies that considered Cronbach's alpha reliability over 0.7 as a proof of scientific validity of a questionnaire (38, 39).

Strengths and limitations

One strength of the present study is the design of the instrument following a mixed approach and using participants’ perspective. Another strength is the use of SCT as the theoretical framework as well as the measurement of two preventive behaviors against CAD. One limitation is that the study was conducted in an urban area excluding any participants from rural areas which can limit the generalization of findings. Completing the questionnaire as self-reports and the large number of items are among the other limitations of study. Moreover, some participants were illiterate; thus, we faced problems in completing the questionnaires. For this purpose, we got help from a family member.

As the findings showed, the questionnaire enjoyed acceptable validity and reliability for measuring physical activity and nutritional behaviors based on SCT in middle-aged people at risk of CAD. This study developed a standard and comprehensive questionnaire. The proposed measurement instrument had good psychometric properties and can be used as a valid and useful instrument to measure factors related to physical activity and nutritional behaviors based on the social cognitive theory in middle-aged population at risk of coronary artery disease. Researchers can use this measurement instrument to evaluate the effectiveness of intervention programs to improve physical activity and nutritional behaviors in the middle-aged.

Acknowledgements

The authors would like to acknowledge the financial support of the Hormozgan University of Medical Sciences.

Authors' contributions

T.A and Z.H. conceptualized and designed the project, SH.M. analyzed data, R.ER. wrote and developed the manuscript, M.N. and M.M. performed the critical review. All authors have read and approved the manuscript.

Funding

This study received financial support from deputy of Research, Hormozgan University of Medical Sciences (grant no. 4010055). Study design, data collection and analysis processes were developed independently of the funder.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics approval and consent to participate

Ethical approval was received for this study from the Ethics Committee of the Hormozgan University of Medical Sciences (IR.HUMS.REC.1401.065). written Informed consent was obtained from all participants and, for illiterate participants, from close relatives. The authors confirm that all methods were performed in accordance with the relevant guidelines and regulations.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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No competing interests reported.

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Development and psychometric evaluation of the physical activity and nutritional behavior questionnaire based on social cognitive theory (PANBQ-SCT) in the middle aged at risk of coronary artery disease

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Abstract

Background

Methods

Results

Conclusions

Background

Methods

Research design and population

Inclusion and Exclusion criteria

Phase 1: Design and item generation

Participants

Data collection

Data analysis

Content validity

Face validity

Construct validity

Reliability

Statistical analysis

Results

Qualitative findings

Content validity

Face validity

Reliability

Construct validity

Discussion

Strengths and limitations

Conclusion

Declarations

References

Additional Declarations

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