Hedonic Overeating-Questionnaire

📜
Abstract

The Hedonic Overeating-Questionnaire (HEDO-Q) represents a significant advancement in the psychological measurement of problematic eating behaviors. Historically, researchers have heavily debated whether overeating should be classified under a substance addiction framework, often termed 'food addiction.' However, because evidence for specific addictive biochemicals in food remains inconclusive, many psychometricians and clinicians have sought alternative ways to conceptualize Addictive-like Eating. The HEDO-Q was developed to address this need by shifting the focus away from clinical addiction models and toward a biopsychological understanding of Food Reward.

Designed as a brief, six-item self-report instrument, the HEDO-Q captures the trait-level propensity for Hedonic Overeating. It operationalizes three core components of Food Reward: 'wanting' (the incentive salience or craving for food), 'liking' (the hedonic pleasure derived from eating), and 'Dyscontrol' (the breakdown of cognitive restraint). By measuring these elements as stable traits rather than fleeting states, the scale provides researchers with a robust tool to evaluate how individuals interact with modern obesogenic environments. Validated in a large, representative German sample of 2,531 participants, the instrument demonstrates strong psychometric properties, making it a highly efficient tool for both population-based and clinical research.

🏷
Keywords
Hedonic Overeating
Food Reward
Wanting and Liking
Dyscontrol
Addictive-like Eating
psychometrics
Obesity

📊 Psychometric Scorecard

Items Count
6
Structure
Unidimensional
Validation Country
📍 Germany

Authors

👤 Anja Hilbert
✉ [email protected]
🏛 Integrated Research and Treatment Center Adiposity Diseases, Behavioral Medicine Research Unit, Department of Psychosomatic Medicine and Psychotherapy, University of Leipzig Medical Center

👤 Veronica Witte
✉ [email protected]
🏛 Clinic for Cognitive Neurology, University of Leipzig Medical Center

👤 Adrian Meule
✉ [email protected]
🏛 Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich

👤 Elmar Braehler
✉ [email protected]
🏛 Integrated Research and Treatment Center Adiposity Diseases, Behavioral Medicine Research Unit, Department of Psychosomatic Medicine and Psychotherapy, University of Leipzig Medical Center

👤 Soeren Kliem
✉ [email protected]
🏛 Ernst-Abbe-Hochschule, University of Applied Sciences

Purpose

For years, the scientific community has relied on tools like the Yale Food Addiction Scale, which adapts DSM criteria for substance use disorders to eating behaviors. While popular, this approach has drawn criticism because eating lacks classic addiction hallmarks like physiological withdrawal, and specific foods have not been proven to contain inherently addictive substances. The HEDO-Q fills a critical conceptual and methodological gap by offering a way to measure Addictive-like Eating without relying on a controversial substance-abuse framework.

By framing overeating as a behavioral issue driven by reward sensitivity and executive dysfunction, the HEDO-Q provides a more biologically and psychologically plausible model. For clinicians and researchers, this brief scale offers an economical way to assess vulnerability to overeating in an environment saturated with highly palatable foods. It allows professionals to identify individuals who may struggle with the hedonic drive to eat, facilitating better-targeted interventions for Obesity and binge-eating behaviors without unnecessarily pathologizing them as 'addicts.'

Construct

The theoretical foundation of the HEDO-Q rests on the biopsychological framework of Food Reward, which fundamentally distinguishes between the motivational and hedonic aspects of eating. The first dimension, 'wanting,' refers to incentive salience—the intense urge or craving to consume food, driven primarily by mesocorticolimbic dopaminergic pathways. The second dimension, 'liking,' captures the actual pleasure or hedonic impact experienced during consumption, which is mediated by smaller opioid hotspots in the brain. In a healthy system, Wanting and Liking are coupled; however, in an obesogenic environment, individuals may experience 'incentive sensitization,' where the intense desire to eat becomes detached from the actual pleasure received.

To these two reward components, the HEDO-Q adds a crucial third dimension: 'Dyscontrol.' This reflects the failure of top-down cognitive inhibition, typically governed by the prefrontal cortex. When the hedonic drive overwhelms cognitive restraint, Hedonic Overeating occurs. While previous laboratory tasks have measured Wanting and Liking as temporary states, the HEDO-Q innovatively captures all three dimensions—wanting, liking, and Dyscontrol—as stable, dispositional traits, offering a comprehensive snapshot of an individual's enduring vulnerability to reward-driven overeating.

Validity

The validation of the HEDO-Q involved rigorous testing against established psychometric standards. The researchers demonstrated strong discriminant validity by showing that the scale successfully differentiates between individuals with and without Obesity, as well as those with eating disturbances. This indicates that the scale accurately captures behavioral patterns that have real-world clinical and physiological implications.

Furthermore, the instrument's convergent and divergent validity were supported through expected associations with existing measures of eating disorders and general psychopathology. A particularly notable strength of the validation process was the establishment of measurement invariance. The scale showed strict invariance across biological sex and partial invariance across age groups and weight statuses. This means that the HEDO-Q measures the construct of Hedonic Overeating consistently across different demographic groups, ensuring that group comparisons are statistically meaningful and not artifacts of measurement bias.

Reliability

In psychometrics, a scale's reliability dictates its consistency and precision. During its development in a large population-based sample, the HEDO-Q demonstrated highly favorable reliability metrics. The validation study confirmed that the scale achieved high internal consistency, indicating that the six items reliably co-vary and consistently measure the underlying construct of Hedonic Overeating.

Additionally, the researchers reported good corrected item-total correlations. This suggests that each individual item contributes meaningfully to the overall scale score without being redundant. The item difficulty and homogeneity were also deemed acceptable, meaning the questions are appropriately calibrated to capture variance across the General population. While the initial cross-sectional data strongly supports the scale's internal reliability, future longitudinal studies will be necessary to establish its test-retest reliability and confirm its stability over time.

Factor Analysis

The structural validity of the HEDO-Q was evaluated using Confirmatory Factor Analysis (CFA) with robust maximum likelihood estimation, an approach well-suited for handling potential deviations from normality. The researchers initially tested a broader pool of items but discarded three negatively worded items due to poor psychometric performance—a common phenomenon where reverse-coded items introduce method variance that distorts the factor structure.

The final CFA supported a higher-order factor model. Specifically, the analysis confirmed that the six remaining items map onto the three postulated lower-order components (wanting, liking, and Dyscontrol), which all load onto a single, overarching unidimensional construct of Hedonic Overeating. This structural conceptualization is highly practical, as it allows researchers to calculate a single composite score representing an individual's overall trait vulnerability to reward-driven eating, while still theoretically honoring the distinct biopsychological mechanisms at play.

Subscales

Subscale Items Description
Wanting Measures the incentive salience, craving, or strong motivational urge to consume food.
Liking Measures the qualitative-evaluative experience of pleasure derived from eating.
Dyscontrol Measures the breakdown of cognitive control or inhibition over eating behaviors.

Instrument

Test Type Self-report questionnaire
Format 6 items
Scoring Sum or mean of the 6 items to form a unidimensional score
Language German
Population General population, Adults
Age Group 14 years and older
Administration Self-administered

Scoring & Interpretation Guidelines

Scoring Instructions Three negatively polarized items with reversed wording were excluded during the initial data analysis phase due to psychometric deficiencies.

Hedonic Overeating-Questionnaire 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

N = 2531 individuals from a random, representative sample of the German population. The sample consisted of 53.3% women and 46.7% men, with a mean age of 48.4 years (SD = 17.9) and a mean BMI of 25.82 kg/m2 (SD = 5.02).

📄
Cite This Paper

Anja Hilbert, Veronica Witte, Adrian Meule, Elmar Braehler, Soeren Kliem (2022). Hedonic Overeating-Questionnaire. Nutrients. https://doi.org/10.3390/nu14091865

📄 Download Full-Text PDF

📚
References
97 references
  1. World Health Organisation (2022, March 29). Obesity and Overweight—Key Facts. Available online: http://www.who.int/news-room/fact-sheets/detail/Obesity-and-overweight.
  2. Abdeen (2017). The NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in body-mass index, underweight, overweight, and Obesity from 1975 to 2016: A pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and Adults. Lancet, 390 2627. 🔗 https://doi.org/10.1016/S0140-6736(17)32129-3
  3. Vandevijvere (2019). Global trends in ultraprocessed food and drink product sales and their association with adult body mass index trajectories. Obes. Rev., 20 10. 🔗 https://doi.org/10.1111/obr.12860
  4. Ferretti (2021). Is the development of obesogenic food environments a self-reinforcing process? Evidence from soft drink consumption. Glob. Health, 17 91. 🔗 https://doi.org/10.1186/s12992-021-00735-y
  5. Gearhardt (2009). Preliminary validation of the Yale Food Addiction Scale. Appetite, 52 430. 🔗 https://doi.org/10.1016/j.appet.2008.12.003
  6. Gearhardt (2021). Is food addictive? A review of the science. Annu. Rev. Nut., 41 387. 🔗 https://doi.org/10.1146/annurev-nutr-110420-111710
  7. American Psychiatric Association (2000). Diagnostic and Statistical Manual of Mental Disorders Fourth Edition (DSM-IV-TR), American Psychiatric Publishing.
  8. American Psychiatric Association (2013). Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5), American Psychiatric Publishing. 🔗 https://doi.org/10.1176/appi.books.9780890425596
  9. Schulte (2020). An evaluation of food addiction as a distinct psychiatric disorder. Int. J. Eat. Disord., 53 1610. 🔗 https://doi.org/10.1002/eat.23350
  10. Gearhardt (2021). The concept of “food addiction” helps inform the understanding of overeating and Obesity: Debate consensus. Am. J. Clin. Nutr., 113 274. 🔗 https://doi.org/10.1093/ajcn/nqaa345
  11. Hebebrand (2014). “Eating addiction”, rather than “food addiction”, better captures Addictive-like Eating behavior. Neurosci. Biobehav. Rev., 47 295. 🔗 https://doi.org/10.1016/j.neubiorev.2014.08.016
  12. Lacroix (2018). Moving beyond the “eating addiction” versus “food addiction” debate: Comment on Schulte et al. (2017). Appetite, 130 286. 🔗 https://doi.org/10.1016/j.appet.2018.06.025
  13. Schulte (2018). Specific theoretical considerations and future research directions for evaluating Addictive-like Eating as a substance-based, food addiction: Comment on Lacroix et al. (2018). Appetite, 130 293. 🔗 https://doi.org/10.1016/j.appet.2018.06.026
  14. Finlayson (2017). Food addiction and Obesity: Unnecessary medicalization of Hedonic Overeating. Nat. Rev. Endocrinol., 13 493. 🔗 https://doi.org/10.1038/nrendo.2017.61
  15. Meule (2019). Ten years of the Yale Food Addiction Scale: A review of version 2.0. Curr. Addict. Rep., 6 218. 🔗 https://doi.org/10.1007/s40429-019-00261-3
  16. Ziauddeen (2013). Is food addiction a valid and useful concept?. Obes. Rev., 14 19. 🔗 https://doi.org/10.1111/j.1467-789X.2012.01046.x
  17. Westwater (2016). Sugar addiction: The state of the science. Eur. J. Nutr., 55 55. 🔗 https://doi.org/10.1007/s00394-016-1229-6
  18. Tomasi (2013). Striatocortical pathway dysfunction in addiction and Obesity: Differences and similarities. Crit. Rev. Biochem. Mol. Biol., 48 1. 🔗 https://doi.org/10.3109/10409238.2012.735642
  19. Ziauddeen (2012). Obesity and the brain: How convincing is the addiction model?. Nat. Rev. Neurosci., 13 279. 🔗 https://doi.org/10.1038/nrn3212
  20. Ruddock (2017). Food addiction beliefs amongst the lay public: What are the consequences for eating behaviour?. Curr. Addict. Rep., 4 110. 🔗 https://doi.org/10.1007/s40429-017-0136-0
  21. Schulte, E.M., Avena, N.M., and Gearhardt, A.N. (2015). Which foods may be addictive? The roles of processing, fat content, and glycemic load. PLoS ONE, 10. 🔗 https://doi.org/10.1371/journal.pone.0117959
  22. Ruddock (2017). Exploring Food Reward and calorie intake in self-perceived food addicts. Appetite, 115 36. 🔗 https://doi.org/10.1016/j.appet.2016.12.003
  23. Schulte (2018). Development of the Highly Processed Food Withdrawal Scale. Appetite, 131 148. 🔗 https://doi.org/10.1016/j.appet.2018.09.013
  24. Davis (2013). Compulsive overeating as an addictive behavior: Overlap between food addiction and binge eating disorder. Curr. Obes. Rep., 2 171. 🔗 https://doi.org/10.1007/s13679-013-0049-8
  25. Schulte (2018). Associations of food addiction in a sample recruited to be nationally representative of the United States. Eur. Eat. Disord. Rev., 26 112. 🔗 https://doi.org/10.1002/erv.2575
  26. Ruddock (2017). The development and validation of the Addiction-like Eating Behaviour Scale. Int. J. Obes., 41 1710. 🔗 https://doi.org/10.1038/ijo.2017.158
  27. Schulte (2018). How much does the Addiction-Like Eating Behavior Scale add to the debate regarding food versus eating addictions?. Int. J. Obes., 42 946. 🔗 https://doi.org/10.1038/ijo.2017.265
  28. Ruddock (2018). Response to ‘Jangle fallacy epidemic in Obesity research: A comment on Ruddock et al. (2017)’. Int. J. Obes., 42 586. 🔗 https://doi.org/10.1038/ijo.2017.290
  29. Berridge (1996). Food Reward: Brain substrates of Wanting and Liking. Neurosci. Biobehav. Rev., 20 1. 🔗 https://doi.org/10.1016/0149-7634(95)00033-B
  30. Mela (2006). Eating for pleasure or just wanting to eat? Reconsidering sensory hedonic responses as a driver of Obesity. Appetite, 47 10. 🔗 https://doi.org/10.1016/j.appet.2006.02.006
  31. Berridge (2016). Liking, wanting, and the incentive-sensitization theory of addiction. Am. Psychol., 71 670. 🔗 https://doi.org/10.1037/amp0000059
  32. Berridge (2015). Pleasure systems in the brain. Neuron, 86 646. 🔗 https://doi.org/10.1016/j.neuron.2015.02.018
  33. Morales (2020). ‘Liking’ and ‘wanting’ in eating and Food Reward: Brain mechanisms and clinical implications. Physiol. Behav., 227 113152. 🔗 https://doi.org/10.1016/j.physbeh.2020.113152
  34. Kreegipuu (2019). Assessing the overlap between three measures of Food Reward. Front. Psychol., 10 883. 🔗 https://doi.org/10.3389/fpsyg.2019.00883
  35. Finlayson (2007). Is it possible to dissociate ‘liking’ and ‘wanting’ for foods in humans? A novel experimental procedure. Physiol. Behav., 90 36. 🔗 https://doi.org/10.1016/j.physbeh.2006.08.020
  36. Finlayson (2012). Susceptibility to overeating affects the impact of savory or sweet drinks on satiation, reward, and food intake in nonobese women. J. Nutr., 142 125. 🔗 https://doi.org/10.3945/jn.111.148106
  37. French (2014). Questionnaire and laboratory measures of eating behavior. Associations with energy intake and BMI in a community sample of working Adults. Appetite, 72 50. 🔗 https://doi.org/10.1016/j.appet.2013.09.020
  38. Finlayson (2011). Implicit wanting and explicit liking are markers for trait binge eating. A susceptible phenotype for overeating. Appetite, 57 722. 🔗 https://doi.org/10.1016/j.appet.2011.08.012
  39. Geiser (2017). States and traits. Theories, models, and assessment. Eur. J. Psychol. Ass., 33 219. 🔗 https://doi.org/10.1027/1015-5759/a000413
  40. Gleaves (2000). The development and validation of the State and Trait Food-Cravings Questionnaires. Behav. Res. Ther., 31 151. 🔗 https://doi.org/10.1016/S0005-7894(00)80009-X
  41. Meule (2014). A short version of the Food Cravings Questionnaire-Trait: The FCQ-T-reduced. Front. Psychol., 5 190. 🔗 https://doi.org/10.3389/fpsyg.2014.00190
  42. Lowe (2009). The Power of Food Scale. A new measure of the psychological influence of the food environment. Appetite, 53 114. 🔗 https://doi.org/10.1016/j.appet.2009.05.016
  43. Epel, E.S., Tomiyama, A.J., Mason, A.E., Laraia, B.A., Hartman, W., Ready, K., Acree, M., Adam, T.C., Jeor, S.S., and Kessler, D. (2014). The Reward-based Eating Drive Scale: A self-report index of reward-based eating. PLoS ONE, 9. 🔗 https://doi.org/10.1037/t53609-000
  44. Vainik (2019). Rapid assessment of reward-related eating: The RED-X5. Obesity, 27 325. 🔗 https://doi.org/10.1002/oby.22374
  45. Yang (2018). Executive function performance in Obesity and overweight individuals: A meta-analysis and review. Neurosci. Biobehav. Rev., 84 225. 🔗 https://doi.org/10.1016/j.neubiorev.2017.11.020
  46. Stice (2016). Neural vulnerability factors that increase risk for future weight gain. Psychol. Bull., 142 447. 🔗 https://doi.org/10.1037/bul0000044
  47. Paterson (2019). Conceptualizing Addictive-like Eating: A qualitative analysis. Appetite, 141 104326. 🔗 https://doi.org/10.1016/j.appet.2019.104326
  48. Saruco (2021). A systematic review of Obesity and binge eating associated impairment of the cognitive inhibition system. Front. Nutr., 8 609012. 🔗 https://doi.org/10.3389/fnut.2021.609012
  49. Suzuki (2017). Elucidating the underlying components of food valuation in the human orbitofrontal cortex. Nat. Neurosci., 20 1780. 🔗 https://doi.org/10.1038/s41593-017-0008-x
  50. Michaud (2017). Overlapping neural endophenotypes in addiction and Obesity. Front. Endocrinol., 8 127. 🔗 https://doi.org/10.3389/fendo.2017.00127
  51. Kalon (2016). Psychological and neurobiological correlates of food addiction. Int. Rev. Neurobiol., 129 85. 🔗 https://doi.org/10.1016/bs.irn.2016.06.003
  52. Boateng (2018). Best practices for developing and validating scales for health, social and behavioral research: A primer. Front. Public Health, 11 149. 🔗 https://doi.org/10.3389/fpubh.2018.00149
  53. Simms (2008). Classical and modern methods of psychological scale construction. Soc. Personal. Psychol. Compass, 2 149. 🔗 https://doi.org/10.1111/j.1751-9004.2007.00044.x
  54. Mason (2017). Improving assessment of the spectrum of reward-related eating: The RED-13. Front. Psychol., 8 795. 🔗 https://doi.org/10.3389/fpsyg.2017.00795
  55. Andreeva (2019). Validation of the German version of the Power of Food Scale in a General population sample. Obes. Facts., 12 416. 🔗 https://doi.org/10.1159/000500489
  56. Gearhardt (2016). Development of the Yale Food Addiction Scale Version 2.0. Psychol. Addict. Behav., 30 113. 🔗 https://doi.org/10.1037/adb0000136
  57. Kliemann (2016). Development and validation of the Self-Regulation of Eating Behaviour Questionnaire for Adults. Int. J. Behav. Nutr. Phys. Act., 13 87. 🔗 https://doi.org/10.1186/s12966-016-0414-6
  58. Schmalbach (2021). Psychometric properties of the German version of the Self-Regulation of Eating Behavior Questionnaire. Front. Psychol., 12 649867. 🔗 https://doi.org/10.3389/fpsyg.2021.649867
  59. Stunkard (1985). The Three-factor Eating Questionnaire to measure dietary restraint, disinhibition and hunger. J. Psychosom. Res., 29 71. 🔗 https://doi.org/10.1016/0022-3999(85)90010-8
  60. Pudel, V., and Westenhoefer, J. (1989). Fragebogen zum Essverhalten, Hogrefe.
  61. Fairburn, C.G., and Beglin, S.J. (2022, March 29). Eating Disorder Examination-Questionnaire (Edition 6.0). Available online: http://www.credo-oxford.com/7.2.html.
  62. Hilbert, A., and Tuschen-Caffier, B. (2016). Eating Disorder Examination-Questionnaire. Deutschsprachige Übersetzung, Dgvt-Verlag. [2nd ed.].
  63. Kliem (2016). The Eating Disorder Examination-Questionnaire 8: A brief measure of eating disorder psychopathology (EDE–Q8). Int. J. Eat. Disord., 49 613. 🔗 https://doi.org/10.1002/eat.22487
  64. Wahl (2010). A 4-item measure of depression and anxiety: Validation and standardization of the Patient Health Questionnaire-4 (PHQ-4) in the General population. J. Affect. Disord., 122 86. 🔗 https://doi.org/10.1016/j.jad.2009.06.019
  65. Spitzer (1999). Validation and utility of a self-report version of PRIME-MD: The PHQ primary care study. JAMA, 282 1737. 🔗 https://doi.org/10.1001/jama.282.18.1737
  66. Chao (2016). Food cravings, binge eating, and eating disorder psychopathology: Exploring the moderating roles of gender and race. Eat. Behav., 21 41. 🔗 https://doi.org/10.1016/j.eatbeh.2015.12.007
  67. Hilbert, A., de Zwaan, M., and Braehler, E. (2012). How frequent are eating disturbances in the population? Norms of the Eating Disorder Examination-Questionnaire. PLoS ONE, 7. 🔗 https://doi.org/10.1371/journal.pone.0029125
  68. Zhang (2016). Multiple imputation with multivariate imputation by chained equation (MICE) package. Ann. Transl. Med., 4 30.
  69. (2011). mice: Multivariate imputation by chained equations in R. J. Stat. Soft., 45 1.
  70. Hu (1999). Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Struct. Equ. Model. Multidiscip. J., 6 1. 🔗 https://doi.org/10.1080/10705519909540118
  71. Browne, M.W., and Cudeck, R. (1993). Alternative ways of assessing model fit. Sage Focus Ed., 21. 🔗 https://doi.org/10.1177/0049124192021002005
  72. Chen (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Struct. Equ. Model. A Multidiscip. J., 14 464. 🔗 https://doi.org/10.1080/10705510701301834
  73. Chen (2005). Teacher’s corner: Testing measurement invariance of second-order factor models. Struct. Equ. Model. A Multidiscip. J., 12 471. 🔗 https://doi.org/10.1207/s15328007sem1203_7
  74. Byrne (1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychol. Bull., 105 456. 🔗 https://doi.org/10.1037/0033-2909.105.3.456
  75. Rosseel (2012). lavaan: An R package for structural equation modeling. J. Stat. Soft., 48 1. 🔗 https://doi.org/10.18637/jss.v048.i02
  76. Eisinga (2013). The reliability of a two-item scale: Pearson, Cronbach or Spearman-Brown?. Int. J. Public Health, 58 637. 🔗 https://doi.org/10.1007/s00038-012-0416-3
  77. R Core Team (2020). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing. Available online: https://www.R-project.org/.
  78. Moosbrugger, H., and Kelava, A. (2020). Testtheorie und Fragebogenkonstruktion (3. Überarbeitete Auflage), Springer. 🔗 https://doi.org/10.1007/978-3-662-61532-4
  79. Darby (2007). Disordered eating behaviours and cognitions in young women with Obesity: Relationship with psychological status. Int. J. Obes., 31 876. 🔗 https://doi.org/10.1038/sj.ijo.0803501
  80. Wiedemann (2021). Examining the construct validity of food addiction severity specifiers. Eat. Weight. Disord., 26 1503. 🔗 https://doi.org/10.1007/s40519-020-00957-w
  81. Dolan (2022). Anhedonia in eating disorders: A meta-analysis and systematic review. Int. J. Eat. Disord., 55 161. 🔗 https://doi.org/10.1002/eat.23645
  82. Sandman, C.F., and Craske, M.G. (2021). Psychological Treatments for Anhedonia, Current Topics in Behavioral Neurosciences, Springer. 🔗 https://doi.org/10.1007/7854_2021_291
  83. German National Cohort Consortium (2014). The German National Cohort: Aims, study design and organization. Eur. J. Epidemiol., 29, 371–382. 🔗 https://doi.org/10.1007/s10654-014-9890-7
  84. Tremblay (2007). A comparison of direct vs. self-report measures for assessing height, weight and body mass index: A systematic review. Obes. Rev., 8 307. 🔗 https://doi.org/10.1111/j.1467-789X.2007.00347.x
  85. Pursey, K., Burrows, T.L., Stanwell, P., and Collins, C.E. (2014). How accurate is web-based self-reported height, weight, and body mass index in young Adults?. J. Med. Internet. Res., 16. 🔗 https://doi.org/10.2196/jmir.2909
  86. Mensink (2013). Übergewicht und Adipositas in Deutschland. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz, 56 786. 🔗 https://doi.org/10.1007/s00103-012-1656-3
  87. Federal Statistical Office (2022, March 29). Einkommens- und Verbrauchsstichprobe: Einnahmen und Ausgaben Privater Haushalte 2018, Available online: https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Einkommen-Konsum-Lebensbedingungen/Einkommen-Einnahmen-Ausgaben/Publikationen/Downloads-Einkommen/evs-einnahmen-ausgaben-privater-haushalte-2152604189004.pdf?__blob=publicationFile.
  88. Federal Statistical Office (2022, March 29). Bevölkerung nach. Nationalität und Geschlecht, Available online: https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Bevoelkerung/Bevoelkerungsstand/Tabellen/zensus-geschlecht-staatsangehoerigkeit-2019.html.
  89. Schatzker (2020). Rethinking Food Reward. Annu. Rev. Psychol., 71 139. 🔗 https://doi.org/10.1146/annurev-psych-122216-011643
  90. Sherman (2021). The four deadly sins of implicit attitude research. Front. Psychol., 11 604340. 🔗 https://doi.org/10.3389/fpsyg.2020.604340
  91. Havermans (2011). “You say it’s liking, I say it’s wanting …” On the difficulty of disentangling Food Reward in man. Appetite, 57 286. 🔗 https://doi.org/10.1016/j.appet.2011.05.310
  92. Finlayson (2012). Current progress in the assessment of ‘liking’ vs. ‘wanting’ food in human appetite. Comment on ‘“You say it’s liking, I say it’s wanting..”. On the difficulty of disentangling Food Reward in man’. Appetite, 58 373. 🔗 https://doi.org/10.1016/j.appet.2011.10.011
  93. Oustric, P., Beaulieu, K., Casanova, N., O’Connor, D., Gibbons, C., Hopkins, M., Blundell, J., and Finlayson, G. (2021). Food liking but not wanting decreases after controlled intermittent or continuous energy restriction to ≥5% weight loss in women with overweight/Obesity. Nutrients, 13. 🔗 https://doi.org/10.3390/nu13010182
  94. Oustric (2018). Changes in Food Reward during weight management interventions—A systematic review. Obes. Rev., 19 1642. 🔗 https://doi.org/10.1111/obr.12754
  95. Hardman (2021). Food-related attentional bias and its associations with appetitive motivation and body weight: A systematic review and meta-analysis. Appetite, 157 104986. 🔗 https://doi.org/10.1016/j.appet.2020.104986
  96. Stott (2021). Attentional bias in eating disorders: A meta-review. Int. J. Eat. Disord., 54 1377. 🔗 https://doi.org/10.1002/eat.23560
  97. Boswell (2016). Food cue reactivity and craving predict eating and weight gain: A meta-analytic review. Obes. Rev., 17 159. 🔗 https://doi.org/10.1111/obr.12354

Cite this article

Mohammed looti (2026). Hedonic Overeating-Questionnaire. PSYCHOLOGICAL SCALES. Retrieved from https://scales.arabpsychology.com/s/hedonic-overeating-questionnaire/

Mohammed looti. "Hedonic Overeating-Questionnaire." PSYCHOLOGICAL SCALES, 14 Aug. 2026, https://scales.arabpsychology.com/s/hedonic-overeating-questionnaire/.

Mohammed looti. "Hedonic Overeating-Questionnaire." PSYCHOLOGICAL SCALES, 2026. https://scales.arabpsychology.com/s/hedonic-overeating-questionnaire/.

Mohammed looti (2026) 'Hedonic Overeating-Questionnaire', PSYCHOLOGICAL SCALES. Available at: https://scales.arabpsychology.com/s/hedonic-overeating-questionnaire/.

[1] Mohammed looti, "Hedonic Overeating-Questionnaire," PSYCHOLOGICAL SCALES, vol. X, no. Y, ص Z-Z, August, 2026.

Mohammed looti. Hedonic Overeating-Questionnaire. PSYCHOLOGICAL SCALES. 2026;vol(issue):pages.

Related terms:

  1. Antecedents and Outcomes of Purchase Justification in a Hedonic Online Context–Model Questionnaire
  2. Lung Information Needs Questionnaire / Longziekten Informatie Behoefte Questionnaire
  3. Questionnaire for Beginning Teachers and Questionnaire for Mentor Teachers
  4. Brief Illness Perception Questionnaire / Illness Perception Questionnaire-Kort / Ziekteperceptievragenlijst
  5. Assistive Technology Usability Questionnaire for people with Neurological diseases Questionnaire (NATU Quest)
  6. Arabic Version of the Musculoskeletal Health Questionnaire
  7. Multiple Sclerosis Intimacy and Sexuality Questionnaire-15
  8. Questionnaire about the Process of Recovery
  9. Victorian Institute of Sports Assessment – Achilles questionnaire, German version
  10. Mental Health Quality of Life questionnaire
× Figure
PDF
Scroll to Top