How Depression And ADHD Relate To Exercise Addiction: Cross-sectional Study

Exercise addiction, a pattern of excessive exercise despite negative consequences, may be linked to mental health conditions like ADHD and depression.

These disorders might lead individuals to use exercise as a coping mechanism, potentially developing into addictive behavior.

Understanding this relationship is crucial, as ADHD often co-occurs with conditions such as depression and substance use disorders.

This context helps explain why investigating the connections between ADHD, depression, and exercise addiction is important for comprehensive mental health care.

Close up of someone on a spin bike.
Baltes-Flueckiger, L., Wagner, A., Sattler, I., Meyer, M., Tschopp, A., Walter, M., & Colledge, F. How depression and ADHD relate to exercise addiction: A crosssectional study among frequent exercisers. Frontiers in Psychology15, 1427514. https://doi.org/10.3389/fpsyg.2024.1427514

Key Points

  • Depression and ADHD symptoms are positively associated with exercise addiction (EA) symptoms in frequent exercisers.
  • Depressive symptoms appear to be a stronger predictor for EA compared to ADHD symptoms.
  • The relationship between depressive and ADHD symptoms with EA symptoms remained significant after adjusting for age and gender.
  • 24% of participants were found to be at risk for EA.
  • This research has limitations such as its cross-sectional design and reliance on self-reported measures.
  • Exercise addiction is a complex phenomenon with potential links to mental health disorders, highlighting the importance of understanding its psychiatric profile.

Rationale

Exercise addiction (EA) is a physically and psychologically pathological phenomenon characterized by rigid engagement in physical exercise despite adverse consequences (Szabo et al., 2015; Freimuth et al., 2011).

While substance use disorders and addictive behaviors are often accompanied by co-occurring mental disorders (Lai et al., 2015; Emmerik-van et al., 2012), the evidence for psychiatric comorbidities in EA is limited.

Depression and ADHD are common comorbidities in substance use disorders (Kessler et al., 1997; Johansson Capusan et al., 2019), but their relationship with EA remains unclear.

Previous studies have shown mixed results regarding the association between depression and EA (Alcaraz-Ibáñez et al., 2022; Costa et al., 2013; Levit et al., 2018), while research on ADHD and EA is scarce (Berger et al., 2014; Colledge et al., 2022).

This study aims to investigate how depression and ADHD symptoms relate to EA symptoms in frequent exercisers, contributing to the characterization of the psychiatric profile of individuals with EA.

Method

The study employed a cross-sectional design, using self-reported questionnaires to assess exercise addiction, depressive symptoms, and ADHD symptoms.

Procedure

Participants were recruited through flyers in gyms, physiotherapy centers, sports clubs, pharmacies, public transport, and internet advertisements.

Eligible participants provided written informed consent and completed a set of questionnaires. Due to COVID-19 restrictions, some questionnaires were completed electronically.

Sample

The study included 173 participants aged between 18 and 70 years who reported exercising more than 10 hours a week and continued to exercise despite injury or illness.

The sample consisted of 65 females (38%) and 107 males (62%), with a mean age of 30.6 years (SD = 13.3).

Measures

  • Exercise Dependence Scale (EDS): 21-item questionnaire assessing exercise addiction symptoms
  • Beck Depression Inventory (BDI): 21-item scale measuring depressive symptoms
  • Homburger ADHD Scale for Adults (HASE): 22-item scale assessing ADHD symptoms

Statistical measures

Pearson correlations, multiple linear regressions, and stepwise regression analysis were performed.

Assumptions for linear regression were tested, including variance inflation factors for multicollinearity.

Results

  • Depressive symptoms showed a significant positive correlation with exercise addiction (EA) symptoms (r = 0.422, p < 0.001). This relationship remained significant after adjusting for age and gender (B = 20.531, p < 0.001).
  • ADHD symptoms also demonstrated a significant positive correlation with EA symptoms (r = 0.308, p < 0.001). This association persisted after controlling for age and gender (B = 15.507, p < 0.001).
  • Stepwise regression analysis revealed that depressive symptoms were a stronger predictor of EA symptoms compared to ADHD symptoms. Depressive symptoms entered the model first and explained more variance in EA symptoms.
  • The depression model showed good fit (F(3,168) = 15.926, p < 0.001, R² = 0.221, Adjusted R² = 0.208), as did the ADHD model (F(3,168) = 8.436, p < 0.001, R² = 0.131, Adjusted R² = 0.115).
  • Based on EDS scores, 24% of participants (n = 41) were found to be at risk for exercise addiction. Gender was a significant predictor in the ADHD model (B = 6.075, p = 0.033) but not in the depression model (B = 2.173, p = 0.423).
  • Age was a significant predictor in the depression model (B = -0.278, p = 0.005) but not in the ADHD model (B = -0.164, p = 0.130).
  • Variance Inflation Factors (VIF) indicated no problematic multicollinearity in either model.

Insight

This study provides evidence that both depressive and ADHD symptoms are associated with exercise addiction symptoms in frequent exercisers.

The findings suggest that depressive symptoms may play a stronger role in EA compared to ADHD symptoms.

This is particularly informative as it highlights the complex relationship between mental health and exercise behavior.

The results extend previous research by simultaneously examining depression and ADHD in relation to EA, which has not been widely studied before.

The stronger association of depressive symptoms with EA suggests that individuals with depression might be more prone to developing problematic exercise patterns, possibly as a maladaptive coping mechanism.

Further research could explore:

  • The temporal relationship between depression, ADHD, and EA through longitudinal studies.
  • The effectiveness of interventions targeting depressive symptoms in reducing EA risk.
  • The role of different ADHD subtypes in the development of EA.
  • The potential protective factors that may prevent individuals with ADHD from developing EA despite high levels of exercise.

Strengths

The study had several methodological strengths including:

  • A focus on frequent exercisers, providing insights into a high-risk population for EA
  • The use of validated measures for assessing EA, depression, and ADHD symptoms
  • Consideration of potential confounding factors such as age and gender
  • Employment of multiple statistical approaches to examine the relationships between variables

Limitations

This study also had several methodological limitations, including:

  • Cross-sectional design limits causal inferences about the relationships between mental disorders and EA
  • Reliance on self-reported measures may lead to overestimation of EA prevalence
  • Lack of clinical diagnoses for depression and ADHD
  • The study was conducted during the COVID-19 pandemic, which may have influenced exercise behaviors and mental health symptoms
  • Absence of a non-exercising control group limits comparisons of depression and ADHD rates between exercisers and non-exercisers

These limitations imply that the results should be interpreted cautiously and that longitudinal studies with clinical assessments are needed to establish causal relationships and more accurate prevalence rates.

Implications

The results have significant implications for clinical psychology practice and public health interventions:

  • Screening for depressive symptoms in individuals reporting high levels of exercise may help identify those at risk for EA.
  • Exercise prescriptions for depression should be carefully monitored to prevent the development of EA.
  • The different associations of depression and ADHD with EA suggest that tailored interventions may be necessary for individuals with these disorders who engage in frequent exercise.
  • Public health campaigns promoting exercise should include information about the potential risks of excessive exercise, especially for individuals with depressive symptoms.
  • The findings underline the need for a nuanced approach to exercise promotion in mental health treatment, balancing its benefits with potential risks.

Variables that may influence the results include:

  • The severity of depressive or ADHD symptoms
  • The type and intensity of exercise
  • Individual coping strategies and personality traits
  • Social and environmental factors influencing exercise behavior

References

Primary reference

Baltes-Flueckiger, L., Wagner, A., Sattler, I., Meyer, M., Tschopp, A., Walter, M., & Colledge, F. How depression and ADHD relate to exercise addiction: A crosssectional study among frequent exercisers. Frontiers in Psychology15, 1427514. https://doi.org/10.3389/fpsyg.2024.1427514

Other references

Alcaraz-Ibáñez, M., Paterna, A., Griffiths, M. D., & Sicilia, Á. (2022). An exploratory examination of the relationship between symptoms of depression and exercise addiction among undergraduate recreational exercisers. International Journal of Mental Health and Addiction20(3), 1385-1397. https://doi.org/10.1007/s11469-020-00450-6

Berger, N. A., Müller, A., Brähler, E., Philipsen, A., & de Zwaan, M. (2014). Association of symptoms of attention-deficit/hyperactivity disorder with symptoms of excessive exercising in an adult general population sample. BMC psychiatry14, 1-9. https://doi.org/10.1186/s12888-014-0250-7

Colledge, F., Buchner, U., Schmidt, A., Wiesbeck, G., Lang, U., Pühse, U., … & Walter, M. (2022). Individuals at risk of exercise addiction have higher scores for depression, ADHD, and childhood trauma. Frontiers in sports and active living3, 761844. https://doi.org/10.3389/fspor.2021.761844

Costa, S., Hausenblas, H. A., Oliva, P., Cuzzocrea, F., & Larcan, R. (2013). The role of age, gender, mood states and exercise frequency on exercise dependence. Journal of behavioral addictions2(4), 216-223. https://doi.org/10.1556/jba.2.2013.014

van Emmerik-van Oortmerssen, K., van de Glind, G., van den Brink, W., Smit, F., Crunelle, C. L., Swets, M., & Schoevers, R. A. (2012). Prevalence of attention-deficit hyperactivity disorder in substance use disorder patients: a meta-analysis and meta-regression analysis. Drug and alcohol dependence122(1-2), 11-19. https://doi.org/10.1016/j.drugalcdep.2011.12.007

Freimuth, M., Moniz, S., & Kim, S. R. (2011). Clarifying exercise addiction: Differential diagnosis, co-occurring disorders, and phases of addiction. International journal of environmental research and public health8(10), 4069-4081. https://doi.org/10.3390/ijerph8104069

Capusan, A. J., Bendtsen, P., Marteinsdottir, I., & Larsson, H. (2019). Comorbidity of adult ADHD and its subtypes with substance use disorder in a large population-based epidemiological study. Journal of attention disorders23(12), 1416-1426. https://doi.org/10.1177/1087054715626511

Kessler, R. C., Crum, R. M., Warner, L. A., Nelson, C. B., Schulenberg, J., & Anthony, J. C. (1997). Lifetime co-occurrence of DSM-III-R alcohol abuse and dependence with other psychiatric disorders in the National Comorbidity Survey. Archives of general psychiatry54(4), 313-321.

Lai, H. M. X., Cleary, M., Sitharthan, T., & Hunt, G. E. (2015). Prevalence of comorbid substance use, anxiety and mood disorders in epidemiological surveys, 1990–2014: A systematic review and meta-analysis. Drug and alcohol dependence154, 1-13. https://doi.org/10.1016/j.drugalcdep.2015.05.031

Levit, M., Weinstein, A., Weinstein, Y., Tzur-Bitan, D., & Weinstein, A. (2018). A study on the relationship between exercise addiction, abnormal eating attitudes, anxiety and depression among athletes in Israel. Journal of behavioral addictions7(3), 800-805. https://doi.org/10.1556/2006.7.2018.83

Szabo, A., Griffiths, M. D., de La Vega, M. R., Mervó, B., & Demetrovics, Z. (2015). Methodological and conceptual limitations in exercise addiction research. Yale Journal of Biology and Medicine, 88, 303-308.

Keep Learning

Socratic questions for a college class to discuss this paper:

  1. How might the relationship between depression and exercise addiction differ in professional athletes compared to recreational exercisers?
  2. What ethical considerations should be taken into account when prescribing exercise as a treatment for depression, given the potential risk of exercise addiction?
  3. How might cultural differences influence the relationship between mental health disorders and exercise addiction?
  4. In what ways could the COVID-19 pandemic have affected the results of this study, and how might future research account for such global events?
  5. How might the concept of exercise addiction challenge our understanding of addiction as primarily substance-related?
  6. What are the potential implications of this research for public health policies related to exercise promotion?
  7. How might the relationship between ADHD and exercise addiction vary across different ADHD subtypes (inattentive, hyperactive-impulsive, combined)?
  8. What role might personality traits play in mediating the relationship between mental health disorders and exercise addiction?
  9. How could future research designs improve upon the limitations of this study to provide more robust evidence?
  10. What are the potential long-term health consequences of exercise addiction, and how might they interact with symptoms of depression or ADHD?

Saul McLeod, PhD

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Editor-in-Chief for Simply Psychology

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.


Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

h4 { font-weight: bold; } h1 { font-size: 40px; } h5 { font-weight: bold; } .mv-ad-box * { display: none !important; } .content-unmask .mv-ad-box { display:none; } #printfriendly { line-height: 1.7; } #printfriendly #pf-title { font-size: 40px; }