Table of Contents
Abstract
The measurement of Cognitive distortions surrounding diet and nutrition is a critical endeavor in health psychology. The Irrational Food Belief Scale (IFBS) was originally developed to capture these maladaptive thought patterns, which often derail weight management and contribute to disordered eating. This adaptation focuses on translating and validating the IFBS for a Persian-speaking population, highlighting the profound impact that cultural context has on psychological constructs. By rigorously testing the tool within an Iranian demographic, researchers aimed to provide local clinicians with a reliable metric for assessing food-related cognitive vulnerabilities.
During the cross-cultural adaptation process, the original 57-item inventory underwent significant structural changes. Following translation and expert review, empirical testing revealed that many original items did not resonate or group together as expected in the new cultural setting. Consequently, the instrument was refined down to 27 items distributed across five distinct dimensions. This dramatic reduction underscores a vital psychometric lesson: psychological constructs, especially those tied to daily habits like eating, are rarely universal and require careful recalibration when crossing cultural boundaries.
Ultimately, while the Persian version of the IFBS demonstrates adequate internal consistency and temporal stability, its explanatory power remains somewhat limited. The retained factor structure accounts for a modest portion of the total variance in food beliefs. As a result, while the current adaptation serves as a useful interim tool for assessing psycho-behavioral aspects of eating, nutritional attitudes, and dietary control, it also signals a clear need for the development of indigenous psychometric instruments tailored specifically to Middle Eastern dietary cultures.
📊 Psychometric Scorecard
27
Multidimensional
0.85
0.82
📍 Iran
Authors
Purpose
Identifying and quantifying maladaptive thoughts about food is essential for effective cognitive-behavioral interventions in dietetics and obesity management. Clinicians have long recognized that emotional eating, chronic dieting failures, and food addiction are frequently underpinned by absolutist or distorted thinking patterns. By providing a structured way to measure these specific cognitive vulnerabilities, this scale bridges the gap between abstract cognitive theory and applied nutritional counseling.
For researchers and practitioners working with Persian-speaking populations, the availability of a culturally adapted scale is a significant advancement. Prior to this adaptation, professionals in Iran lacked a standardized, localized tool to assess how irrational beliefs sabotage healthy Eating behaviors. This instrument allows healthcare providers to pinpoint exact areas of cognitive distortion—such as using food primarily for emotional regulation or holding unscientific beliefs about calories—thereby enabling highly targeted therapeutic interventions.
Construct
The core psychological construct measured by this instrument is the presence of distorted, unrealistic, or absolutist beliefs regarding food, eating, and weight regulation. Drawing heavily from the foundational cognitive theories of Albert Ellis and Aaron Beck, the framework posits that it is not the food or the environment itself that causes distress or overeating, but rather the individual's flawed interpretation of these elements. These irrational beliefs often manifest as rigid rules, catastrophic thinking about weight gain, or the misguided conviction that food is the only valid coping mechanism for emotional distress.
In this specific adaptation, the overarching construct is operationalized into five distinct but interrelated sub-domains. These include the psychological and behavioral reliance on food for mood regulation, generalized attitudes toward nutrition and fat content, beliefs about the health implications of diet, perceived loss of control over eating, and negative conceptualizations of dieting itself. Together, these dimensions map the cognitive landscape that drives unhealthy Eating behaviors, illustrating how deeply ingrained cultural and personal myths can override physiological hunger cues and nutritional knowledge.
Validity
The validation of this translated instrument involved a comprehensive, multi-stage methodological approach to ensure both cultural relevance and statistical soundness. Initially, qualitative and quantitative face and content validity were established through expert panel reviews, leading to essential linguistic modifications. For instance, terminology that was culturally ambiguous or scientifically unfamiliar to the general public was revised to ensure clarity. The quantitative content validity metrics, including the Content Validity Ratio and Content Validity Index, both exceeded rigorous thresholds (0.91), confirming that the retained items were highly relevant to the target construct.
Construct validity was subsequently evaluated using a split-sample design for exploratory and confirmatory factor analyses. The exploratory phase revealed a significant divergence from the original Western model, necessitating the removal of over half the original items to achieve a clean factor structure. The resulting five-factor model was then subjected to confirmatory Factor analysis in a separate sample, which verified the new structural integrity. However, the relatively low total variance explained by these factors suggests that while the retained items are valid indicators of the construct, the construct itself may possess additional cultural dimensions not captured by the original Western item pool.
Reliability
Reliability testing for the adapted scale demonstrated robust internal consistency and excellent temporal stability, indicating that the instrument measures its target construct with minimal random error. The overall internal consistency was strong, with a global Cronbach's alpha of 0.849. When broken down by subscale, the alpha coefficients ranged from 0.701 to 0.817, which comfortably meets the standard psychometric threshold for acceptable reliability in psychological research. Furthermore, the researchers employed McDonald's Omega, a more robust estimator of reliability that does not assume tau-equivalence, yielding similarly adequate values across the five dimensions.
Beyond internal consistency, the instrument's stability over time was evaluated using the Intraclass Correlation Coefficient (ICC). The analysis produced an impressive ICC of 0.92, demonstrating that respondents' scores remain highly consistent across multiple testing administrations. This high degree of test-retest reliability is particularly important for clinical applications, as it ensures that any changes in scores over time can be confidently attributed to actual shifts in the patient's cognitive beliefs rather than measurement noise.
Factor Analysis
The structural evaluation of the scale relied on a robust combination of Exploratory Factor analysis (EFA) and Confirmatory Factor analysis (CFA), utilizing two distinct samples of 500 participants each. The EFA was initiated after confirming sampling adequacy with a Kaiser-Meyer-Olkin index of 0.91 and a highly significant Bartlett's test. During the extraction process, it became evident that the original 57-item structure was not viable in this cultural context. A stringent reduction process eliminated 30 items due to poor loading or cross-loading, ultimately distilling the instrument into a 27-item, five-factor model.
These five extracted factors—encompassing psycho-behavioral aspects, nutritional attitudes, healthy eating, controlled eating, and diet—collectively accounted for 30.95% of the total variance. While the CFA subsequently confirmed that this five-factor model provided an acceptable fit to the data, the modest amount of variance explained is a critical psychometric finding. It mathematically illustrates that while the extracted factors are statistically sound, a large portion of the cognitive variance regarding food beliefs in the Iranian population remains unexplained by this specific set of translated items.
Subscales
| Subscale | Items | Description |
|---|---|---|
| Behavioral and psychological aspects | 10, 7, 16, 55, 44, 6, 30, 11 | Measures the reliance on food for emotional regulation, overcoming negative moods, and enhancing social experiences. |
| Nutritional attitudes | 45, 36, 37, 19, 39, 57, 38 | Assesses misconceptions and absolutist beliefs regarding calories, fat content, genetics, and exercise compensation. |
| Healthy eating | 29, 17, 12, 49, 33 | Evaluates beliefs concerning the relationship between diet, lifestyle, and the prevention of chronic diseases. |
| Control eating | 26, 25, 27, 32 | Captures the perceived inability to regulate food intake and the belief that eating pleasure overrides weight management. |
| Diet food | 52, 51, 54 | Measures negative cognitive appraisals of dieting, such as viewing it as a deprivation or a source of sadness. |
Instrument
| Test Type | Self-report questionnaire |
| Format | 27 items |
| Language | Persian |
| Population | General population, Adults |
| Age Group | Adults |
| Administration | Online |
Irrational Food Belief Scale – Persian Version Items
Items are currently not available
The individual items of this scale are not publicly available. Researchers interested in using this instrument should contact the original authors directly to request the scale materials.
Sample
A total of 1,000 participants were recruited online (500 for EFA and 500 for CFA). The sample had a mean age of 37.88 years (SD = 11.47) and a mean BMI of 25.65. Demographically, 55.8% were female, and 54.7% were classified as overweight or obese.
Cite This Paper
Fatemeh Afsahi, Mansoor Alimehdi, Hamid Sharif-Nia (2023). Irrational Food Belief Scale – Persian Version. BMC psychiatry. https://doi.org/10.1186/s12888-023-04909-3
References
59 references
- Khani Jeihooni A, Hidarnia A, Kaveh MH, Hajizadeh E, Askari A. RETRACTED: the effect of an educational program based on health belief model and social cognitive theory in prevention of osteoporosis in women. J Health Psychol. 2017;22(5):NP1–NP11. 🔗 https://doi.org/10.1177/1359105315603696
- Afsahi F, Kachooei M. Relationship between hypertension with irrational health beliefs and health locus of control. J Educ Health Promotion 2020, 9. 🔗 https://doi.org/10.4103/jehp.jehp_650_19
- David D, Lynn SJ, Ellis A. Rational and irrational beliefs: Research, theory, and clinical practice. Oxford University Press; 2009. 🔗 https://doi.org/10.1093/acprof:oso/9780195182231.001.0001
- Rizeq J, Flora DB, Toplak ME. An examination of the underlying dimensional structure of three domains of contaminated mindware: paranormal beliefs, conspiracy beliefs, and anti-science attitudes. Think Reason. 2021;27(2):187–211. 🔗 https://doi.org/10.1080/13546783.2020.1759688
- Laboy JI. Irrational Health Beliefs and Diabetes Type 2: Their Source, Nature, and Impact in the Hispanic Community. 2015.
- Ellis A. The revised ABC’s of rational-emotive therapy (RET). J rational-emotive cognitive-behavior therapy. 1991;9(3):139–72. 🔗 https://doi.org/10.1007/BF01061227
- Beck AT. Cognitive therapy and the emotional disorders. Penguin; 1979.
- Harreiter J, Dovjak G, Kautzky-Willer A. Gestational diabetes mellitus and cardiovascular risk after pregnancy. Women’s health. 2014;10(1):91–108.
- Bellamy L, Casas J-P, Hingorani AD, Williams D. Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. The Lancet. 2009;373(9677):1773–9. 🔗 https://doi.org/10.1016/S0140-6736(09)60731-5
- Lauenborg J, Hansen T, Jensen DM, Vestergaard H, Mølsted-Pedersen L, Hornnes P, Locht H, Pedersen O, Damm P. Increasing incidence of diabetes after gestational diabetes: a long-term follow-up in a danish population. Diabetes Care. 2004;27(5):1194–9. 🔗 https://doi.org/10.2337/diacare.27.5.1194
- Sridhar SB, Ferrara A, Ehrlich SF, Brown SD, Hedderson MM. Risk of large-for-gestational-age newborns in women with gestational diabetes by race and ethnicity and body mass index categories. Obstet Gynecol. 2013;121(6):1255. 🔗 https://doi.org/10.1097/AOG.0b013e318291b15c
- Gilmartin A, Ural SH, Repke JT. Gestational diabetes mellitus. Rev Obstet Gynecol. 2008;1(3):129–34.
- Lawlor DA, Lichtenstein P, Långström N. Association of maternal diabetes mellitus in pregnancy with offspring adiposity into early adulthood: sibling study in a prospective cohort of 280 866 men from 248 293 families. Circulation. 2011;123(3):258–65. 🔗 https://doi.org/10.1161/CIRCULATIONAHA.110.980169
- Goryakin Y, Lobstein T, James WPT, Suhrcke M. The impact of economic, political and social globalization on overweight and obesity in the 56 low and middle income countries. Soc Sci Med. 2015;133:67–76. 🔗 https://doi.org/10.1016/j.socscimed.2015.03.030
- Atkinson L, Shaw RL, French DP. Is pregnancy a teachable moment for diet and physical activity behaviour change? An interpretative phenomenological analysis of the experiences of women during their first pregnancy. Br J Health Psychol. 2016;21(4):842–58. 🔗 https://doi.org/10.1111/bjhp.12200
- Hendrie G, Sohonpal G, Lange K, Golley R. Change in the family food environment is associated with positive dietary change in children. Int J Behav Nutr Phys Activity. 2013;10(1):1–11. 🔗 https://doi.org/10.1186/1479-5868-10-4
- Magro-Malosso ER, Saccone G, Di Mascio D, Di Tommaso M, Berghella V. Exercise during pregnancy and risk of preterm birth in overweight and obese women: a systematic review and meta‐analysis of randomized controlled trials. Acta Obstet Gynecol Scand. 2017;96(3):263–73. 🔗 https://doi.org/10.1111/aogs.13087
- Crowther CA, Hiller JE, Moss JR, McPhee AJ, Jeffries WS, Robinson JS. Effect of treatment of gestational diabetes mellitus on pregnancy outcomes. N Engl J Med. 2005;352(24):2477–86. 🔗 https://doi.org/10.1056/NEJMoa042973
- Carolan M, Gill GK, Steele C. Women’s experiences of factors that facilitate or inhibit gestational diabetes self-management. BMC Pregnancy Childbirth. 2012;12(1):1–12. 🔗 https://doi.org/10.1186/1471-2393-12-99
- Hurst CP, Rakkapao N, Hay K. Impact of diabetes self-management, diabetes management self-efficacy and diabetes knowledge on glycemic control in people with type 2 diabetes (T2D): a multi-center study in Thailand. PLoS ONE. 2020;15(12):e0244692. 🔗 https://doi.org/10.1371/journal.pone.0244692
- Žeželj I, Lazarević LB. Irrational beliefs. Europe’s J Psychol. 2019;15(1):1. 🔗 https://doi.org/10.5964/ejop.v15i1.1903
- Flegal KM, Kruszon-Moran D, Carroll MD, Fryar CD, Ogden CL. Trends in obesity among Adults in the United States, 2005 to 2014. JAMA. 2016;315(21):2284–91. 🔗 https://doi.org/10.1001/jama.2016.6458
- Bicocca MJ, Mendez-Figueroa H, Chauhan SP, Sibai BM. Maternal obesity and the risk of early-onset and late-onset hypertensive disorders of pregnancy. Obstet Gynecol. 2020;136(1):118–27. 🔗 https://doi.org/10.1097/AOG.0000000000003901
- Grohmann B, Brazeau-Gravelle P, Momoli F, Moreau K, Zhang T, Keely J. Obstetric healthcare providers’ perceptions of communicating gestational weight gain recommendations to overweight/obese pregnant women. Obstetric Med. 2012;5(4):161–5. 🔗 https://doi.org/10.1258/om.2012.120003
- Vahedi H, Khosravi A, Sadeghi Z, Aliyari R, Shabankhamseh A, Mahdavian M, Binesh E, Amiri M. Health-promoting lifestyle in patients with and without diabetes in Iran. Health Scope 2017, 6(2). 🔗 https://doi.org/10.5812/jhealthscope.39428
- Petrakis D, Margină D, Tsarouhas K, Tekos F, Stan M, Nikitovic D, Kouretas D, Spandidos DA, Tsatsakis A. Obesity–a risk factor for increased COVID–19 prevalence, severity and lethality. Mol Med Rep. 2020;22(1):9–19. 🔗 https://doi.org/10.3892/mmr.2020.11127
- Byrne SM, Allen KL, Dove ER, Watt FJ, Nathan PR. The reliability and validity of the dichotomous thinking in eating disorders scale. Eat Behav. 2008;9(2):154–62. 🔗 https://doi.org/10.1016/j.eatbeh.2007.07.002
- Fairchild H, Cooper M. A multidimensional measure of core beliefs relevant to eating disorders: preliminary development and validation. Eat Behav. 2010;11(4):239–46. 🔗 https://doi.org/10.1016/j.eatbeh.2010.05.004
- Cooper M, Cohen-Tovée E, Todd G, Wells A, Tovée M. The eating disorder belief questionnaire: preliminary development. Behav Res Ther. 1997;35(4):381–8. 🔗 https://doi.org/10.1016/S0005-7967(96)00115-5
- Barnes RD, White MA. Psychometric properties of the Food Thought suppression inventory in men. J Health Psychol. 2010;15(7):1113–20. 🔗 https://doi.org/10.1177/1359105310365179
- Osberg TM, Eggert M. Direct and indirect effects of stress on bulimic symptoms and BMI: the mediating role of Irrational food beliefs. Eat Behav. 2012;13(1):54–7. 🔗 https://doi.org/10.1016/j.eatbeh.2011.09.008
- Nemeth N, Rudnak I, Ymeri P, Fogarassy C. The role of cultural factors in sustainable food consumption—An investigation of the consumption habits among international students in Hungary. Sustainability. 2019;11(11):3052. 🔗 https://doi.org/10.3390/su11113052
- Navidpour F, Dolatian M, Yaghmaei F, Majd HA, Hashemi SS. Examining factor structure and validating the Persian version of the pregnancy’s worries and stress questionnaire for pregnant iranian women. Global J Health Sci. 2015;7(6):308. 🔗 https://doi.org/10.5539/gjhs.v7n6p308
- Organization WH. Process of translation and adaptation of instruments. http://www.who.int/substance_abuse/research_tools/translation/en/2009
- Lawshe CH. A quantitative approach to content validity. Pers Psychol. 1975;28(4):563–75. 🔗 https://doi.org/10.1111/j.1744-6570.1975.tb01393.x
- Polit DF, Beck CT. Nursing research: Generating and assessing evidence for nursing practice. Lippincott Williams & Wilkins; 2008.
- Hanh VTX, Guillemin F, Cong DD, Parkerson GR Jr, Thu PB, Quynh PT, Briançon S. Health related quality of life of adolescents in Vietnam: cross-cultural adaptation and validation of the adolescent Duke Health Profile. J Adolesc. 2005;28(1):127–46. 🔗 https://doi.org/10.1016/j.adolescence.2003.11.016
- Thorndike RM, Cunningham GK, Thorndike RL, Hagen EP. Measurement and evaluation in psychology and education. Macmillan Publishing Co, Inc; 1991.
- Plichta SB, Kelvin EA. Munro’s statistical methods for health care research. 2013:378.
- Sharif Nia H, Ebadi A, Lehto RH, Mousavi B, Peyrovi H, Chan YH. Reliability and validity of the Persian version of templer death anxiety scale-extended in veterans of Iran–Iraq warfare. Iran J psychiatry Behav Sci. 2014;8(4):29.
- Çokluk Ö, Koçak D. Using Horn’s parallel analysis method in exploratory Factor analysis for determining the number of factors. Educational Sciences: Theory and Practice. 2016;16(2):537–51.
- Colton D, Covert RW. Designing and constructing instruments for social research and evaluation. John Wiley & Sons; 2007.
- Sharif Nia H, Kaur H, Fomani FK, Rahmatpour P, Kaveh O, Pahlevan Sharif S, Venugopal AV, Hosseini L. Psychometric properties of the impact of events scale-revised (IES-R) among general iranian population during the COVID-19 pandemic. Front Psychiatry. 2021;12:692498. 🔗 https://doi.org/10.3389/fpsyt.2021.692498
- Ayre C, Scally AJ. Critical values for Lawshe’s content validity ratio: revisiting the original methods of calculation. Meas evaluation Couns Dev. 2014;47(1):79–86. 🔗 https://doi.org/10.1177/0748175613513808
- Polit DF, Beck CT. The content validity index: are you sure you know what’s being reported? Critique and recommendations. Res Nurs Health. 2006;29(5):489–97. 🔗 https://doi.org/10.1002/nur.20147
- Konttinen H, Männistö S, Sarlio-Lähteenkorva S, Silventoinen K, Haukkala A. Emotional eating, depressive symptoms and self-reported food consumption. A population-based study. Appetite. 2010;54(3):473–9. 🔗 https://doi.org/10.1016/j.appet.2010.01.014
- Di Renzo L, Gualtieri P, Cinelli G, Bigioni G, Soldati L, Attinà A, Bianco FF, Caparello G, Camodeca V, Carrano E. Psychological aspects and eating habits during COVID-19 home confinement: results of EHLC-COVID-19 italian online survey. Nutrients. 2020;12(7):2152. 🔗 https://doi.org/10.3390/nu12072152
- AlAmmar WA, Albeesh FH, Khattab RY. Food and mood: the corresponsive effect. Curr Nutr Rep. 2020;9(3):296–308. 🔗 https://doi.org/10.1007/s13668-020-00331-3
- Barati M, Yarmohammadi A, Mostafaei S, Gholi Z, Razani S, Miry Hazave SS. Evaluating the relationship between attitudes and beliefs, influencing fast-food eating among students of Hamadan University of medical sciences. J Health Syst Res. 2014;10(3):500–8.
- Shah M, Bouza B, Adams-Huet B, Jaffery M, Esposito P, Dart L. Effect of calorie or exercise labels on menus on calories and macronutrients ordered and calories from specific foods in hispanic participants: a randomized study. J Investig Med. 2016;64(8):1261–8. 🔗 https://doi.org/10.1136/jim-2016-000227
- Wolfson JA, Leung CW, Richardson CR. More frequent cooking at home is associated with higher healthy eating Index-2015 score. Public Health Nutr. 2020;23(13):2384–94. 🔗 https://doi.org/10.1017/S1368980019003549
- Osberg TM, Poland D, Aguayo G, MacDougall S. The Irrational food beliefs scale: development and validation. Eat Behav. 2008;9(1):25–40. 🔗 https://doi.org/10.1016/j.eatbeh.2007.02.001
- Lobera IJ, Bolaños P. Spanish version of the Irrational food beliefs scale. Nutrición hospitalaria. 2010;25(5):852–9.
- Jaiyungyuen U, Suwonnaroop N, Priyatruk P, Moopayak K. Factors influencing health-promoting behaviors of older people with hypertension. In: 1st Mae Fah Luang University International Conference: 2012; 2012: 1.
- Willett WC, Stampfer MJ. Current evidence on healthy eating. Annu Rev Public Health. 2013;34:77–95. 🔗 https://doi.org/10.1146/annurev-publhealth-031811-124646
- Kampov-Polevoy AB, Alterman A, Khalitov E, Garbutt JC. Sweet preference predicts mood altering effect of and impaired control over eating sweet foods. Eat Behav. 2006;7(3):181–7. 🔗 https://doi.org/10.1016/j.eatbeh.2005.09.005
- Mc Morrow L, Ludbrook A, Macdiarmid JI, Olajide D. Perceived barriers towards healthy eating and their association with fruit and vegetable consumption. J Public Health. 2017;39(2):330–8.
- Azizi F, Azadbakht L, MIRMIRAN P, Saadati N. Assessment of diet quality in Adults: Tehran lipid and glucose study. 2003.
- Aggarwal A, Monsivais P, Cook AJ, Drewnowski A. Positive attitude toward healthy eating predicts higher diet quality at all cost levels of supermarkets. J Acad Nutr Dietetics. 2014;114(2):266–72. 🔗 https://doi.org/10.1016/j.jand.2013.06.006
Cite this article
Mohammed looti (2026). Irrational Food Belief Scale – Persian Version. PSYCHOLOGICAL SCALES. Retrieved from https://scales.arabpsychology.com/s/irrational-food-belief-scale-persian-version/
Mohammed looti. "Irrational Food Belief Scale – Persian Version." PSYCHOLOGICAL SCALES, 14 Aug. 2026, https://scales.arabpsychology.com/s/irrational-food-belief-scale-persian-version/.
Mohammed looti. "Irrational Food Belief Scale – Persian Version." PSYCHOLOGICAL SCALES, 2026. https://scales.arabpsychology.com/s/irrational-food-belief-scale-persian-version/.
Mohammed looti (2026) 'Irrational Food Belief Scale – Persian Version', PSYCHOLOGICAL SCALES. Available at: https://scales.arabpsychology.com/s/irrational-food-belief-scale-persian-version/.
[1] Mohammed looti, "Irrational Food Belief Scale – Persian Version," PSYCHOLOGICAL SCALES, vol. X, no. Y, ص Z-Z, August, 2026.
Mohammed looti. Irrational Food Belief Scale – Persian Version. PSYCHOLOGICAL SCALES. 2026;vol(issue):pages.