Introducing a new measure for assessing self-efficacy in response to air pollution hazards for pregnant women

  • Marzieh Araban1,

    Affiliated with

    • Seddigheh Sadat Tavafian1Email author,

      Affiliated with

      • Saeid Motesaddi Zarandi2,

        Affiliated with

        • Ali Reza Hidarnia1,

          Affiliated with

          • Mahmood Reza Gohari3,

            Affiliated with

            • Janice M Prochaska4,

              Affiliated with

              • Afsaneh Laluie5 and

                Affiliated with

                • Ali Montazeri6Email author

                  Affiliated with

                  Journal of Environmental Health Science and Engineering201311:16

                  DOI: 10.1186/2052-336X-11-16

                  Received: 13 January 2013

                  Accepted: 6 July 2013

                  Published: 8 July 2013


                  A self-efficacy instrument should be condition-specific. There are several instruments for measuring self-efficacy, but none are air pollution-specific. This study aimed to develop a self-efficacy measure for assessing pregnant women’s responses to air pollution hazards. A random sample of pregnant women aged between 18 and 35 years attending three prenatal care centers were entered into the study. Prenatal care centers randomly selected from a list of centers located in different geographical regions of Tehran, Iran. After careful consideration and performing content and face validity, a 4-item measure was developed and participants completed the questionnaire. Reliability was estimated using internal consistency and validity was assessed by performing confirmatory factor analysis (CFA) and known group comparison. In all 200 eligible pregnant women were studied. The mean age of participants was 26.9 (SD = 4.8) years and it was 27.9 (SD = 9.1) weeks for gestational age. The findings showed almost perfect results for both content validity ratio (CVR = 1) and content validity index (CVI = 1). The confirmatory factor analysis indicated a good fit to the data, and known group comparison revealed satisfying results. Internal consistency as measured by the Cronbach’s alpha coefficient was found to be 0.74. In general, the findings suggest that this new generated scale is a reliable and valid specific measure of self-efficacy in response to air pollution hazards for pregnant women. However, further studies are needed to establish stronger psychometric properties for the questionnaire.


                  Air polltion Confirmatory factor analysis Iran Pregnant women Reliability Self-efficacy Validity


                  Globally, it has been estimated that 24% of all disease burden (healthy life years lost) and 23% of all premature deaths were attributable to environmental issues of which air pollution was the most important contributing factor [1]. It is argued that air pollution could cause 3% of mortality due to cardiopulmonary diseases and 5% of mortality due to respiratory system cancers, leading to 800000 premature deaths and 6400000 years of life lost [2]. This feature of air pollution consequences occurs predominantly in developing countries among them Asia is more vulnerable [2].

                  Tehran, the capital city of Iran, is one of the most polluted cities in the world [3]. Despite applying some policies and regulations in Iran, existed evidence has revealed that the current level of air pollutants in Tehran is above healthy levels. Although, air pollution is very harmful for population health, this hazard could be more severe for higher risk groups such as pregnant women [4, 5]. Some adverse outcomes of air pollution for pregnant women include low birth weight, preterm labor, and intrauterine growth retardation that in turn could be leaded to a range of childhood and adulthood morbidity and mortality later [68] imposing extra costs to the health system [9]. However, there is a strong believe that we could prevent pregnant women from being exposed to air pollution [3]. As such, the most suggested preventive strategy is to reduce exposure to air pollution by reducing time spent outdoors [1012].

                  It is well documented that effective preventive strategies and interventions should be theory-driven or at least should have constructs that might increase the likelihood of behavioral changes toward desired outcomes [1315]. For instance, self-efficacy is a key construct in many health education theories and models [16]. Those interventions that contained self-efficacy as a basic element showed more satisfying results [17, 18]. Self-efficacy is defined as people’s beliefs in their own abilities to perform a given behavior [19]. These perceptions contribute to individuals’ judgments in their own abilities to perform a specific behavior and greatly influence their choice of or maintaining in doing that behavior [20]. As indicated above, it has been consistently shown that self-efficacy is one of the most important predictors of health behaviors [2124]. Thus we thought it would be important to focus on self-efficacy in order to change exposure behavior among pregnant women.

                  There are several instruments for measuring self-efficacy [2132]. Examples of these instruments are presented in Table 1. None of these instruments were air pollution specific. Hence, the aim of this study was to develop a self-efficacy measure for assessing the prevention of air pollution hazards. It was hoped this might help to fill the gaps and perhaps contribute to the existing literature on the topic.
                  Table 1

                  Examples of Self-efficacy measures used in the literature

                  Author(s) [ref.]



                  Number of items

                  Response format

                  Schwarzer [21]


                  General Self Efficacy


                  Definitely not to exactly true

                  Barkley & Burns [22]


                  Condom Use Self-Efficacy


                  Strongly disagree to strongly agree

                  Schwarzer & Renner [23]


                  The Nutrition Self-Efficacy


                  Very uncertain to very certain

                  Schwarzer & Renner [23]


                  The physical exercise Self-Efficacy


                  Very uncertain to very certain

                  Schwarzer & Renner [23]


                  The Alcohol Resistance Self-Efficacy


                  Very uncertain to very certain

                  Mohr et al. [24]


                  Adherence (self injection) self-efficacy


                  I will not have any problems injecting myself to I will not be able to tolerate it at all.

                  Ma et al. [25]


                  Consumption of fruit and vegetables Self-Efficacy


                  Not at all confident to very confident

                  Dennis [26]


                  Breastfeeding Self-Efficacy Scale-Short Form


                  Not at all confident to 5 always confident

                  Luszczynska & Schwarzer [27]


                  Preaction BSE Self-Efficacy Scale:


                  Definitely not to exactly true

                  Luszczynska & Schwarzer [27]


                  Maintenance BSE

                  Self-Efficacy Scale


                  Definitely not to exactly true

                  Kerr et al. [28]


                  Adherence to therapy self-efficacy


                  Not reported

                  Kerr et al. [28]


                  Adherence to therapy regulatory self-efficacy


                  Not reported

                  Kronborg et al. [29]


                  Health visitor’s Self-efficacy


                  Five-point Likert scale

                  Clayman et al. [30]


                  Patient Communication Self-Efficacy (AURA)


                  A lot disagree to a lot agree

                  Latimer et al. [31]


                  Self-efficacy for weight loss (nutrition and exercise)


                  Not at all confident to completely confident

                  Schwarzer & Luszczynska [32]


                  Smoking cessation Try Self-Efficacy


                  ‘Not at all sure I am able to, to ‘very sure I am able to’

                  Materials and methods

                  The questionnaire

                  Self-efficacy provided the theoretical concept for the instrument development. Albert Bandura has defined self-efficacy as one’s belief in his/her ability to succeed behavior changes in specific situations [19]. Thus as indicated earlier (Table 1) and considering several different self-efficacy measures, we produced a set of specific items for this study as recommended by Bandura. His main recommendation relies on the fact that a self-efficacy measure should be condition-specific. In this study the time spent outdoors by pregnant women was defined as a specific situation. Accordingly, decreasing this time was considered as a desired behavior to be adopted by pregnant women. In fact the desired behavior (prevention of air pollution hazards) was defined as any activities resulting in decreased exposure time to air pollution. To be more specific we asked environmental health experts to indicate necessary recommendations for pregnant women. Then the idea of ability to perform the recommended behaviors was set to develop the concept and generate items to provide a measure for self-efficacy. Overall 16 items resulted from the above mentioned approaches. After careful examination and recombination of similar items or items very close in meanings, the following 5 items remained:

                  1). I can stay indoors in the peak hours of the air pollution - from 7.00 o’clock to 9.00 o’clock in the morning 2). I can stay indoors in the peak hours of the air pollution - from 6.00 o’clock to 9.00 o’clock in the evening; 3). I can stay home in the days that air quality is in the crisis situation; 4). I can avoid entering into the high traffic area of the city. 5). I can wear an air filtering face mask during my walks through the city center. Each item is rated on a 4-point Likert scale ranging from ‘not at all sure’ to ‘completely sure’ giving a possible score of 1 to 4 for each item and 4 to 16 for the total items.


                  A multi stage cluster sampling was applied. First Tehran was divided into 3 regions: north, center and south. Among all prenatal health care centers located in these three regions, one center was randomly selected. Then from pregnant women attending to the center, a random sample was selected through random numbers. The sample size was estimated on the basis of our planned procedure for confirmatory factor analysis. It has been suggested that a sample size of 100 to 200 individuals is an acceptable sample size if the model is not complex in the confirmatory factor analysis. Thus a sample of 200 women was thought for this study [33]. The inclusion criteria were: being aged 18 to 35 years old, having the history of pregnancy without adverse outcomes, not suffering from chronic diseases during the present pregnancy and not having the history of fertility problems. Demographic characteristics of the pregnant women included recoding of age, education of pregnant women and their husbands, gestational age, and family monthly income.

                  Statistical analysis

                  In this study face, content and construct validity of the designed instrument was performed as follows:

                  Face validity

                  Both qualitative and quantitative methods were applied for face validity. For the purpose of qualitative approach, 20 pregnant women were asked to assess each item for ambiguity and difficulty. In general, there were no problems in reading and understanding the items by pregnant women. The quantitative face validity was evaluated through impact score. The impact score for each item was calculated as multiplying the importance of an item with its frequency. The impact scores of greater than 1.5 were considered suitable [34].

                  Content validity

                  An expert panel including 15 health education, environmental health, obstetrics and maternal child health specialists examined the content validity. The expert panel was asked to comment on the necessity and relevance of the items in order to calculate the Content Validity Ratio (CVR) and the Content Validity Index (CVI), respectively. The necessity of an item was assessed using a three-point rating scale: (i) not essential, (ii) useful, but not essential, (iii) essential. Following the experts’ assessments, the CVR for total scale was computed. According to Lawshe, if more than half of the panelists indicate that an item is essential, then that item has the least content validity [35]. Here, the CVR for the scale equal or greater than 0.59 was considered satisfactory. The CVI was estimated by experts’ ratings of items relevancy, simplicity, and clarity on a 4-point Likert scale. The CVI of each statement was calculated and as recommended values of equal or greater than 0.80 were considered acceptable [36].

                  Factor structure

                  Confirmatory Factor Analysis (CFA) was carried out to test whether the data fit the hypothesized measurement model. Usually for the confirmatory factor analysis 2 to 3 items are enough to carry out the analysis and there are several fit indices for evaluating model fit [33]. We will report on some of the most important fit indexes with their cut of points as follows: Chi-Squared Test Values closer to zero indicate a better fit, For Root Mean Square Error of Approximation, a value of .06 or less is indicative of acceptable model fit. GFI and CFI value of .90 or larger is generally considered to indicate acceptable model fit [33, 37].

                  Discriminant validity

                  Discriminant validity of the instrument was assessed using known groups comparison. Known groups comparison was performed to test how well the questionnaire discriminates between women in different stages of behavior change (pre-action stage and action stage).


                  Internal consistency of the instrument was assessed by using Cronbach’s alpha coefficient. Alpha values of equal or greater than 0.70 was thought satisfactory [38].


                  The ethics committee of Tarbiat Modares University approved the study. Informed consent was obtained from participants.


                  In total, 200 pregnant women completed the questionnaire. The mean age of women was 26.9 (SD = 8.4) years and the mean gestational age was 27.9 (SD = 9.1) weeks. The characteristics of participants and self-efficacy scores by demographic characteristics are shown in Table 2.
                  Table 2

                  The characteristics of the study sample and self-efficacy scores by demographic status (n = 200)


                  Number (%)

                  Self-efficacy *

                  Age (years)



                  61 (30.5)

                  13.3 (2.3)



                  85 (42.5)

                  12.6 (2.1)



                  54 (27)

                  12.3 (3.3)

                  Test result (P-value)



                  Gestational age (weeks)


                  < 12

                  20 (10)

                  12.75 (2.6)



                  64 (32)

                  12.76 (2.1)



                  116 (58)

                  12.79 (2.8)

                  Test result (P-value)






                  97 (48.5)

                  12.7 (2.9)



                  103 (51.5)

                  12.8 (2.9)

                  Test result (P-value)






                  192 (96)

                  12.9 (2.7)



                  8 (4)

                  8.3 (3.11)

                  Test result (P-value)






                  51 (25.5)

                  13.2 (3.1)



                  125 (62.5)

                  13.5 (2.9)



                  24 (12)

                  12.5 (2.8)

                  Test result (P-value)



                  Husband Education



                  53 (26.5)

                  13.3 (3.1)



                  126 (63)

                  13.2 (3.1)



                  21 (10.5)

                  12.5 (2.9)

                  Test result (P-value)



                  Family income per month



                  41 (20.5)

                  13.6 (3.1)



                  116 (58)

                  13 (2.8)



                  43 (21.5)

                  12.2 (2.9)

                  Test result (P-value)



                  * Mean (SD). Higher values indicate better self-efficacy.

                  ** Results derived from one-way analysis of variance.

                  *** Results derived from t-test.

                  The results obtained from validity analysis showed good levels of the CVR (equal to 1), CVI (equal to 1) and impact score (IS = 5) for four first items. Item 5 was not found as necessary by panelists and it was omitted from further analysis.

                  The results from confirmatory factor analysis are shown in Figure 1. Overall all fit indices were found to be satisfactory. The root mean square error of approximation (RMSEA) showed an acceptable value model fit (< 0.0001). The goodness of fit index (GFI) and Adjucted goodness of fit index (AGFI) were acceptable (GFI = 0.97 and AGFI = 0.96).
                  Figure 1

                  Factor structure of the self-efficacy measure for prevention of air pollution hazards among pregnant women derived from confirmatory factor analysis.

                  Validity of the scale as assessed by known groups comparison indicated that the questionnaire discriminated well between sub-groups of women who differed in the stage of behavior change. As expected, those who scored higher on the scale were more likely to be in the action stage (Table 3).
                  Table 3

                  The descriptive statistics for the self-efficacy measure* (n = 200)


                  Mean (SD)

                  Possible range

                  I can stay indoors in the peak hours of the air pollution - from 7.00 o’clock to 9.00 o’clock in the morning.

                  3.02 (1.04)


                  I can stay indoors in the peak hours of the air pollution - from 6.00 o’clock to 9.00 o’clock in the evening.

                  3.41 (1.09)


                  I can stay home in the days that air quality is in the crisis situation.

                  2.84 (0.82)


                  I can avoid entering into the high traffic area of the city.

                  3.46 (1.04)


                  Total score

                  12.73 (2.92)


                  Cronbach’s alpha coefficient



                  * Higher values indicate better self-efficacy.

                  The result obtained from reliability analysis indicated that alpha coefficient for the scale was 0.74, well above the threshold lending support to its acceptable internal consistency. The results are shown in Table 4.
                  Table 4

                  Known groups comparison by stages of change*





                  Mean (SD)

                  Mean (SD)


                  I can stay indoors in the peak hours of the air pollution - from 7.00 o’clock to 9.00 o’clock in the morning.

                  2.79 (1.07)

                  3.52 (0.75)


                  I can stay indoors in the peak hours of the air pollution - from 6.00 o’clock to 9.00 o’clock in the evening.

                  3.24 (0.99)

                  3.7 (0.48)


                  I can stay home in the days that air quality is in the crisis situation.

                  2.60 (1.1)

                  3.38 (0.85)


                  I can avoid entering into the high traffic area of the city.

                  3.33 (0.86)

                  3.74 (0.62)


                  Total score

                  11.97 (2.97)

                  14.44 (1.92)


                  * Higher values indicate better self-efficacy.


                  The findings demonstrated that the air pollution self efficacy measure developed by this study obtained good validity values. In addition we found that the pattern of observed level of self efficacy across the stages of change was consistent with health education theory’s prediction [39]. Self-efficacy was lower among participants who were in pre action stages and was higher among those who were in the action stages. The findings from current study were consistent with previous findings on the topic [16, 4043] indicating that targeting interventions that focus on self-efficacy as a theoretical framework for a desirable behavior (that was reduced time spent outdoors) might lead to acceptance of a behavior (that was prevention of air pollution hazards).

                  Few studies have investigated the validity of self-efficacy scales using confirmatory factor analysis. In line with our study, Latimer et al. [31] reported a unidimensional scale for weight loss among women with a sedentary lifestyle while Barkley and Burnes [22] reported a three-dimensional tool for condom use self-efficacy. One possible explanation for such differences in construct of these questionnaires is the fact that these tools were used for different types of behaviors. For instance while weight loss is a matter of personal attempt, condom use self-efficacy is a unique behavior that requires interaction between two partners.

                  As Bandura [19] advocated a behavior-specific approach to the study of self-efficacy, he argues that a measure of general self-efficacy in overall ability for tapping an individual’s efficacy in managing tasks associated with a specific behavior would be inadequate. Thus, to assess air pollution exposure self-efficacy, an instrument specific to tasks could lead to more concise values of self-efficacy as compared to using a general self-efficacy measure as reported by Schwarzer [21].

                  The validity of the scale was strengthened further by estimates of how well the observed indicators (each item on the measure) served as a measurement tool for the construct of self-efficacy related to the prevention of air pollution hazards behaviors. These estimates all were suitable, providing strong evidence that each item reflected self-efficacy. The Cronbach’s alpha coefficient was 0.74 and seems very satisfying for a 4-item scale. It is argued that using large scales are not necessary for predicting a health behavior and rather using rigorous theory-based item wording is more important than the number of statements of an scale [29]. Thus, one might conclude that our short scale could be useful to measure self-efficacy. Self-efficacy scores are very important for setting priorities when developing an specific intervention. One goal of developing a scale is to construct parsimonious measures that can be integrated into a more comprehensive questionnaire [24]. As such we feel our new scale could be integrated into interventions based on many health education and promotion theories and models such as: TransTheoretical Model, Social Cognitive Theory, Theory of Planned Behavior and Health Belief Model; where all have the construct of self-efficacy and are among the most used theories for health behavior change [16].

                  In summary, one of the most important millennium development goals is to improve maternal health. Also millennium goal 7 and 8 state that the study of air pollution and its potential public health impact on the general population and highly susceptible groups such as pregnant women should be a priority [44]. In addition it is recommended that one goal of any program is to be measured correctly [45]. Yet, we thought developing a measure of self-efficacy for prevention of air pollution hazards for pregnant women might cover these goals in particular and help to improve women’s health in general.

                  The current study, however, had some limitations. Almost all participants (96%) were housewives. Perhaps further testing of the measure is needed with employed pregnant women. In addition since our analysis was not based on the maximum required sample size, its replication in a larger sample is warranted to confirm the factor structure of the measure.


                  In general, the findings suggest that this new generated scale is a reliable and valid specific measure of self-efficacy in response to air pollution hazards for pregnant women. However, further studies are needed to establish stronger psychometric properties for the questionnaire.



                  The authors wish to express their deepest appreciation to those pregnant women who participated in this study. The authors also thank Professor Fazlollah Ahmadi for his admirable guidance on the process of tool validation and also for his valuable comments on the earlier version of the paper. This article is written based on the first author’s PhD dissertation at the Department of Health Education of Tarbiat Modarres University, and the official support from the university is also acknowledged.

                  Authors’ Affiliations

                  Department of Health Education, Faculty of Medical Sciences, Tarbiat Modares University
                  Department of Environmental Health Engineering, Faculty of Health, Shaheed Beheshti University of Medical Sciences
                  Department of Biostatistics, Hospital Management Research Center, School of Health Management and Information Sciences, Iran University of Medical Sciences
                  Prochange Behavior System
                  Department of Gynecology, Faculty of Medical Sciences, Baqiyatallah University of Medical Sciences
                  Mental Health Research Group, Health Metrics Research Center, Iranian Institute for Health Sciences Research, ACECR


                  1. Preventing disease through healthy environment [http://​www.​who.​int/​quantifying_​ehimpacts/​publications/​preventingdiseas​ebegin.​pdf]
                  2. Cohen AJ, Ross AH, Ostro B, Pandey KD, Krzyzanowski M, Kunzli N, Gutschmidt K, Pope A, Romieu I, Samet JM, Smith K: The global burden of disease due to outdoor air pollution. J Toxicol Environ Health A 2005, 68: 1301–1307. 10.1080/15287390590936166View Article
                  3. Araban M, Kariman N, Tavafian SS, Motesaddi S, Alavimajd H, Amin. Shokravi F: Air pollution and low birth weight, a historical cohort study from Tehran, Iran. East Mediterr Health J 2012, 18: 556–560.
                  4. Hackley B, Feinstein A, Dixon J: Air pollution: impact on maternal and perinatal health. J Midwifery Womens Health 2007, 52: 435–443. 10.1016/j.jmwh.2007.03.020View Article
                  5. Makri A, Stilianakis NI: Vulnerability to air pollution health effects. Int J Hyg Environmental Health 2008, 211: 326–336. 10.1016/j.ijheh.2007.06.005View Article
                  6. Bell ML, Ebisu K, Belanger K: Ambient air pollution and low birth weight in Connecticut and Massachusetts. Environ Health Perspect 2007, 115: 1118–1124. 10.1289/ehp.9759View Article
                  7. Rogers JF, Dunlop AL: Air pollution and very low birth weight infants: a target population? Pediatrics 2006, 118: 156–164. 10.1542/peds.2005-2432View Article
                  8. Dugandzic R, Dodds L, Stieb D, Smith-Doiron M: The association between low-level exposures to ambient air pollution and term low birth weight: a retrospective cohort study. Environ Health 2006, 5: 3. 10.1186/1476-069X-5-3View Article
                  9. Cunningham F, Leveno K, Bloom S, Hauth J, Rouse D, Spong C, Cunningham FG: Williams Obstetrics. 23rd edition. New York: MC Grawhill; 2005.
                  10. Barnes BR, Mathee A, Krieger L, Shafritz L, Favin M, Sherburne L: Testing selected behaviors to reduce indoor air pollution exposure in young children. Health Educ Res 2004, 19: 543–550. 10.1093/her/cyg075View Article
                  11. Dixon J, Hendrickson K, Ercolano E, Quackenbush R, Dixon P: The Environmental Health Engagement Profile: what people think and do about environmental health. Public Health Nurs 2009, 26: 460–473. 10.1111/j.1525-1446.2009.00804.xView Article
                  12. Mansfield C, Reed Johnson F, Van Houtven G: The missing piece: valuing averting behavior for children’s ozone exposures. Resour Energy Econ 2006, 28: 215–228. 10.1016/j.reseneeco.2006.02.002View Article
                  13. Noar SM: A health educator’s guide to theories of health behavior. Int Q Community Health Educ 2005, 24: 75–92. 10.2190/DALP-3F95-GCT3-M922View Article
                  14. Noar SM, Zimmerman RS: Health behavior theory and cumulative knowledge regarding health behaviors: are we moving in the right direction? Health Educ Res 2005, 20: 275–290. 10.1093/her/cyg113View Article
                  15. Painter J, Borba C, Hynes M, Mays D, Glanz K: The use of theory in health behavior research from 2000 to 2005: a systematic review. Ann Behav Med 2008, 35: 358–362. 10.1007/s12160-008-9042-yView Article
                  16. Glanz K, Rimer BK, Viswanath K: Health Behavior and Health Education: Theory, Research, and Practice. New York: Jossey-Bass; 2008.
                  17. Pearson N, Ball K, Crawford D: Parental influences on adolescent fruit consumption: the role of adolescent self-efficacy. Health Educ Res 2012, 27: 14–23. 10.1093/her/cyr051View Article
                  18. Williams SL, French DP: What are the most effective intervention techniques for changing physical activity self-efficacy and physical activity behaviour and are they the same? Health Educ Res 2011, 26: 308–322. 10.1093/her/cyr005View Article
                  19. Bandura A: Guide for constructing self-efficacy scales. In Bandura, Urdan T, Self-Efficacy Beliefs of Adolescents. North Carolina: Information Age Publishing Inc; 2006:307–337.
                  20. Dennis CL, Faux S: Development and psychometric testing of the Breastfeeding Self-Efficacy Scale. Res Nurs Health 1999, 22: 399–409. 10.1002/(SICI)1098-240X(199910)22:5<399::AID-NUR6>3.0.CO;2-4View Article
                  21. Schwarzer R: General perceived self-efficacy in 14 cultures. [http://​userpage.​fu-berlin.​de/​~gesund/​publicat/​ehps_​cd/​health/​world14.​htm]
                  22. Barkley TW Jr, Burns JL: Factor analysis of the condom use self-efficacy scale among multicultural college students. Health Educ Res 2000, 15: 485–489. 10.1093/her/15.4.485View Article
                  23. Schwarzer , Renner B: Social-cognitive predictors of health behavior: action self-efficacy and coping self-efficacy. Health Psychol 2000, 19: 487.View Article
                  24. Mohr D, Boudewyn A, Likosky W, Levine E, Goodkin D: Injectable medication for the treatment of multiple sclerosis: the influence of self-efficacy expectations and infection anxiety on adherence and ability to self-inject. Ann Behav Med 2001, 23: 125–132. 10.1207/S15324796ABM2302_7View Article
                  25. Ma J, Betts NM, Horacek T, Georgiou C, White A, Nitzke S: The importance of decisional balance and self-efficacy in relation to stages of change for fruit and vegetable intakes by young adults. Am J Health Promot 2002, 16: 157–166. 10.4278/0890-1171-16.3.157View Article
                  26. Dennis CL: The Breastfeeding Self-Efficacy Scale: psychometric assessment of the short form. J Obstet Gynecol Neonatal Nurs 2003, 32: 734–744. 10.1177/0884217503258459View Article
                  27. Luszczynska A, Schwarzer R: Planning and self-efficacy in the adoption and maintenance of breast self-examination: a longitudinal study on self-regulatory cognitions. Psychol Health 2003, 18: 93–108. 10.1080/0887044021000019358View Article
                  28. Kerr T, Palepu A, Barness G, Walsh J, Hogg R, Montaner J, Tyndall M, Wood E: Psychosocial determinants of adherence to highly active antiretroviral therapy among injection drug users in Vancouver. Antivir Ther 2004, 9: 407–414.
                  29. Kronborg H, Væth M, Olsen J, Harder I: Health visitors and breastfeeding support: influence of knowledge and self-efficacy. Eur J Public Health 2008, 18: 283–288. 10.1093/eurpub/ckm121View Article
                  30. Clayman ML, Pandit AU, Bergeron AR, Cameron KA, Ross E, Wolf MS: Ask, understand, remember: a brief measure of patient communication self-efficacy within clinical encounters. J Health Commun 2010,15(Suppl 2):72–79.View Article
                  31. Latimer L, Walker LO, Kim S, Pasch KE, Sterling BS: Self-efficacy Scale for Weight Loss among multi-ethnic women of lower income: a psychometric evaluation. J Nutr Educ Behav 2011, 43: 279–283. 10.1016/j.jneb.2010.09.007View Article
                  32. Schwarzer R, Luszczynska A: Self efficacy. [http://​dccps.​cancer.​gov/​brp/​constructs/​self-efficacy/​index.​html]
                  33. Harrington D: Confirmatory factor analysis. US: Oxford University Press; 2008.View Article
                  34. Broder HL, McGrath C, Cisneros GJ: Questionnaire development: face validity and item impact testing of the Child Oral Health Impact Profile. Community Dent Oral Epidemiol 2007, 35: 8–19. 10.1111/j.1600-0528.2007.00401.xView Article
                  35. Lawshe CH: A quantitative approach to content validity. Pers Psychol 1975, 28: 563–575. 10.1111/j.1744-6570.1975.tb01393.xView Article
                  36. Polit DF, Beck CT, Owen SV: Is the CVI an acceptable indicator of content validity? appraisal and recommendations. Res Nurs Health 2007, 30: 459–467. 10.1002/nur.20199View Article
                  37. Schumacker RE, Lomax RG: A Beginner’s Guide to Structural Equation Modeling. Volume 1. New Jersey: Lawrence Erlbaum; 2004.
                  38. Waltz CF, Strickland O, Lenz ER: Measurement in Nursing and Health Research. 4th edition. New York: Springer Publishing Company; 2010.
                  39. Bawadi HA, Banks AD, Ammari F, Tayyem RF, Jebreen S: Stage of change of 6 health-related behaviors among patients with type 2 diabetes. Prim Care Diabete in press
                  40. Transtheoretical Model [http://​www.​uri.​edu/​research/​cprc/​TTM/​detailedoverview​.​htm]
                  41. Norcross JC, Krebs PM, Prochaska JO: Stages of change. J Clin Psychol 2011, 67: 143–154. 10.1002/jclp.20758View Article
                  42. Sharma M, Romans JA: Theoretical Foundations of Health Education and Health Promotion. Massachusetts: Jones and Bartlett Learning; 2012.
                  43. Vincent-Onabajo GT, Lawan AK, Oyeyemi AY, Hamzat TK: Functional self-efficacy and its determinants in Nigerian stroke survivors. Top Stroke Rehabil 2012, 19: 411–416. 10.1310/tsr1905-411View Article
                  44. MDG5: improve maternal health [http://​www.​who.​int/​topics/​millennium_​development_​goals/​maternal_​health/​en/​index.​html]
                  45. Wartenberg D: Some considerations for the communication of results of air pollution health effects tracking. Air Qual Atmos Health 2009, 2: 207–221. 10.1007/s11869-009-0046-yView Article


                  © Araban et al.; licensee BioMed Central Ltd. 2013

                  This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​2.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.