What is the key take away?
This study found that young adults who participated in Special Olympics experienced a 49% risk reduction for developing depression compared to young adults who did not participate in Special Olympics.
Where can I access this article?
The article is published online in Social Psychiatry and Psychiatric Epidemiology. The article is freely available to view at: https://rdcu.be/c13Pi.
Lloyd, M., Temple, V.A., Foley, J.T., Yeatman, S., Lunksy, Y., Huang, A. & Balogh, R. (2022). Young adults with intellectual and developmental disabilities who participate in Special Olympics are less likely to be diagnosed with depression. Social Psychiatry and Psychiatric Epidemiology, https://doi.org/10.1007/s00127-022-02406-8.
Who wrote this article?
The lead authors on this paper are Dr. Meghann Lloyd and Dr. Robert Balogh from the Faculty of Health Sciences at Ontario Tech University. Dr. Lloyd was supported in this work by co-authors Viviene A. Temple (University of Victoria), John T. Foley (State University of New York), Sharyn Yeatman (Ontario Tech University), Yona Lunksy (Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute at the Centre for Addiction and Mental Health) and Anjie Huang (ICES),
What is the impact factor of this journal?
Social Psychiatry and Psychiatric Epidemiology has an impact factor of 4.519 within 2021.
An impact factor is a measure or metric the importance or quality of a journal (higher the number the more prestigious). It represents to average number of articles in the journal have been cited by others. The average is calculated by the number of citations divided by the number of articles published over a two-year period.
How was this study funded?
Special Olympics Canada provided a small research grant to Dr. Balogh and Dr. Lloyd in 2015.
How was any potential conflict of interest mitigated?
Dr. Yona Lunsky was asked to join the research team after the funding was provided by Special Olympics, she later joined the Special Olympics Canada Board of Directors in 2019 well after the funding was provided to the research team. To mitigate any potential bias, Special Olympics Canada and Special Olympics Ontario were not involved in the analysis, interpretation or reporting of results. All other authors had no conflict of interest to declare.
What is the definition of intellectual and developmental disabilities?
Intellectual disabilities are a subgroup of neurodevelopmental disorders that have three key characteristics:
- People have limitations in their intellectual functioning.
- People have limitations in adaptive functioning, particularly in the conceptual, practical and social domains.
- People begin having signs of a disability during their developmental years.
Developmental disabilities often include people with intellectual disabilities, because of the shared limitations in cognitive and adaptive functioning that:
- Begins before 18 years of age.
- Is likely life-long.
- Affects major life activities like independence.
What is the current prevalence of IDD in Canada?
In the province of Ontario, the prevalence of adults ages 18 to 64 years with IDD makes up approximately 0.8% of the population. This number may be higher (approximately 1%) when children and youth are included.
How many people were included in this study?
The health records of 51,103 young adults with IDD were included in this study. 8,710 Special Olympics participants and 42, 393 non-participants.
What were the age of people included in this study?
The health records of young people between the ages of 19 to 29 were included in this study and followed for up to 20 years.
Why did you choose this age group?
- IDD must be diagnosed before the age of 18
- The analysis algorithms used for clinical depression have been previously used on adults but not children
- Researchers had large sample size of this age group
- Researchers wanted to follow the athletes for up to 20 years so starting between 19 to 29, which participants from age 20 up to a maximum of age 49.
When did this study take place?
This was a retrospective cohort study, which meant we looked back in time across 20 years to collect information. The data collected was from between 1995 and 2015 and we analyzed the data from that time period for our publication.
Why does this study focus only on people with IDD?
There is considerable evidence that people with IDD (children, youth, adults, older adults) experience significant health disparities. They have higher number of hospitalizations, fewer preventive health screenings, higher rates of psychiatric conditions among other factors. Therefore, it is important that evidence-based health promotion initiatives be studied to determine their effectiveness. Special Olympics is the largest international organization that supports people with IDD and more research is needed on the effectiveness of their programs.
Where did you get this data?
This study is a secondary analysis of existing administrative data. This means the data was already collected for other purposes and we analyzed it to answer our research questions. To do this study we partnered with Special Olympics Ontario and, after extensive privacy and research ethics review, registration data from Special Olympics Ontario was linked with provincial health data at ICES. Linking the datasets made it possible to determine if a person with an IDD living in Ontario was also a Special Olympics athlete. Once linked, the data were analyzed at ICES to answer the research questions.
ICES is an independent, non-profit research institute that uses population-based health information to produce knowledge on a broad range of health care issues. Researchers at ICES use the data housed at ICES to measure health system performance, provide a clearer understanding of the shifting health care needs of Ontarians, and a stimulate discussion of practical solutions to optimize scarce resources.
ICES has many years of experience receiving data from third parties and linking it to the existing health databases maintained by ICES. ICES is a Prescribed Entity under the Personal Health Information Act (PHIPA) which permits ICES to hold and use administrative, population health, clinical and other data files for the purposes of analysis, evaluation, and decision support. Access to ICES data is governed by policies and procedures that comply with the requirements of the Information and Privacy Commissioner of Ontario.
ICES knowledge is highly regarded in Canada and abroad, and is widely used by government, hospitals, planners, and practitioners to make decisions about care delivery and to develop policy. In October 2018, the institute formerly known as the Institute for Clinical Evaluative Sciences formally adopted the initialism ICES as its official name.
What was the purpose of the study?
The purpose of this study was to compare the rates of depression among young adult Special Olympics participants with IDD compared to non-participants with IDD.
How were study participants with a diagnosis of depression identified?
An algorithm developed by the Mental Health and Addictions Program Framework research team at ICES was used. We identified if participants had depression from secured health records held at ICES; these records were from databases of hospitalizations, visits to the doctor or emergency department between April 1, 1995 and March 31, 2015. A diagnosis of depression was confirmed if participants had at least two physician visits for depression or one hospitalization or emergency care visit for depression.
How long were participants required to be included in Special Olympics?
To be considered a Special Olympics participant within this study, individuals had to be registered with Special Olympics for at least one year. If an individual had no record of participation or was involved with Special Olympics for less than one year, they were not considered a “Special Olympics participant.”
Did participants have depression when they started the study?
No. If a person with IDD had a diagnosis of depression in the 5 years before the cohort window, they were excluded from the study.
Can we say that Special Olympics prevented depression?
Our findings show that among Special Olympics participants, the risk of developing depression was reduced by half. This being the first study to report this finding, it is conservative to state that we found an association between Special Olympics participation and a decreased risk for depression. A study conducted by other researchers in a different jurisdiction is needed to confirm our finding. The more evidence that is found to corroborate our study’s findings, the stronger the evidence will become showing a causal relationship exists between Special Olympics participation and the prevention of depression.
What were the variables in this study?
The primary dependent variable was depression diagnosis (yes versus no). The Independent variable was Special Olympics participation status (participant versus non-participant).
What is a confounding variable?
A confounding variable is a characteristic or factor that may influence the results or account for the findings. It is important to consider confounding variables in any study to ensure the relationship between the dependent and independent variables are not impacted by something else. In this study, the potential confounding variables we accounted for included:
- Area of residence
- Neighbourhood affluence
What is an effect size?
The effect size is an output of a statistical test that tells you the magnitude of the difference, or how meaningful the relationship is between the two factors you’re studying. If the effect size is small, there are limited practical applications of your findings. If the effect size is large, your research has great significance to practice. Our findings found a moderate effect size.
What is a Cox Proportional Hazard Model?
The Cox Proportional Hazard model is a statistical method that can be used to study the relationship between the time to an event for an outcome (e.g. diagnosis of depression) and an explanatory variable (e.g. participation in Special Olympics). The Cox model was useful in this study because of the longitudinal nature of the data and because it allows the researchers to control for multiple potential confounding variables at the same time. The model produces a hazard ratio.
What is a hazard ratio?
A hazard ratio is a measure of an effect of an exposure (e.g. Special Olympics participation) on an outcome (diagnosis of depression) over time. The hazard ratio is a ratio of the hazard rate for developing an outcome (e.g. depression) among those exposed to a variable (e.g. the group of Special Olympics participants) divided by the hazard rate for developing an outcome among those NOT exposed to a variable.
A hazard ratio equal to 0.5 indicates that at any particular time, half as many patients in the exposure group are experiencing an outcome event compared to those in the non-exposed group. A hazard ratio equal to 1 indicates that at any particular time, the hazard rates are the same in both groups. Put another way, a hazard ratio tells us whether a subject in the treatment group (e.g. Special Olympics participant) who is unaffected (e.g. diagnosis of depression) at any given time has a greater, equal, or lower probability (i.e., hazard rate) of experiencing the event (e.g. diagnosis of depression) during the next unit of time than an unaffected subject in the control group (e.g. non-participant).
For our example, the hazard rate of depression for Special Olympics participants compared to the rate of depression for non-participants generates a hazard ratio of 0.51. The hazard ratio is less than 1, indicating that the hazard for developing depression was less among Special Olympics participants than in non-participants. At any time during the follow-up, Special Olympics participants were 0.51 times as likely to develop depression compared to those who did not participate in Special Olympics. Another way to describe this is that they had a reduction in risk of 49%.
What is an adjusted hazard ratio?
An adjusted hazard ratio is a hazard ratio generated by the Cox statistical model that controls for the influence of potential cofounding variables. In the case of this study, we adjusted for sex, area of residence, neighbourhood affluence, and a measure of morbidity.
How were the two groups of participants different?
Our analyses indicated that these group, Special Olympics participant versus non-participant were not meaningfully different from each other on any of the variables included: income quintile, rural versus urban, and measure of morbidity.
What does 19.95 and 9.49 per 1,000 person years mean?
In epidemiology, these values are referred to incidence rates. They represent the number of new cases of depression per 1000 persons per year among the two groups we studied. In our study, if you followed 1000 non-participants for one year, 19.95 instances of depression would occur; meanwhile, if you followed 1000 Special Olympics participants for 1 year, 9.49 instances of depression would occur.
Why does participation in Special Olympics impact depression?
We don’t know exactly why participation in Special Olympics impacts depression, but we hypothesize that in addition to spending time being physically active or exercising, the social-connectedness of being part of a group, increases in feelings of self-worth, self-efficacy, increases in overall mood related to feelings of success, self-determination, independence related to mastery of skills, mentoring, friendships, and fun.
How relevant are these findings to others Province/Territories or countries?
Given that this study was a population-level analysis, we are confident that the findings are applicable to regions across Canada. However, to be certain future studies should investigate, when possible, if these findings persist in other jurisdictions.
What are the limitations of this study?
No study is without limitations, in this study we were not able to control for the type or intensity of the sports/activities the Special Olympics athletes participated in, or whether they were individual sports (e.g., track and field) or team sports (e.g., basketball). However, even participants competing in individual sports would still attend group practices and benefit from the overall team dynamic.
Additionally, we do not know what types of supports these adults with IDD are receiving in their daily life and whether the level of support differs between those who are engaged in Special Olympics compared to those who are not (e.g., family, social services, coaches, personal support workers, etc.).
This dataset also does not allow for expressive skills, or similarly, level of IDD to be determined to compare between groups. These are important limitations because it could lead to underdiagnosing depression.
We also do not know if participation in Special Olympics reduces depression symptoms in those who are already depressed. Likewise, we cannot know if the non-participants in this study were physically active in programs or activities outside of Special Olympics.