Unmet Mental Health Needs and Barriers to Mental Health Treatment Among Persons with Multiple Sclerosis in the NARCOMS Registry
Bibliographic record
Abstract
Background – Multiple sclerosis (MS) is a chronic, neurological disease. Mental health comorbidities, such as depression, anxiety and bipolar disorder, are highly prevalent in persons with MS, and their presence is associated with adverse health and economic consequences. Unfortunately, these conditions are frequently underdiagnosed and undertreated. To better meet the mental health needs of MS patients, it is important to identify the correlates, barriers and consequences associated with untreated mental health comorbidities. Previous studies have generally found socioeconomic factors (e.g., inadequate health insurance, low education) to limit access to mental health care; however, the findings for sociodemographic (i.e., age, race, ethnicity) and clinical factors (i.e., severity of mental health symptoms and level of physical impairment) have been less consistent. While qualitative investigations of MS patients have identified common barriers to mental health treatment, these barriers have been poorly investigated in larger samples of MS patients. Further research is needed to identify disparities in the use of mental health services for the treatment of mental health comorbidities in persons with MS. \n \nResearch Aims – Cross-sectionally, this thesis aimed to assess the prevalence and correlates of untreated mental health comorbidities in persons with MS. This thesis also explored the prevalence and correlates of treatment barriers (in those not receiving treatment) and treatment modalities (in those receiving treatment). Longitudinally, this thesis aimed to assess the temporal association between baseline mental health non-treatment and depressive symptoms and health-related quality of life outcomes (mental and physical domains) at one-year follow-up. \n \nMethods – To address these aims, this thesis utilized cross-sectional (2011) and longitudinal (2011 to 2012) data captured by the North American Research Committee on Multiple Sclerosis (NARCOMS) Registry. The NARCOMS Spring 2011 Survey had a total of 9765 respondents; 3928 of whom were diagnosed with one or more of depression, anxiety or bipolar disorder. Mental health comorbidities were explored separately for all our analyses, resulting in three non-mutually exclusive baseline samples: depression (n=3589), anxiety (n=1487), and bipolar disorder (n=196). Other than initial descriptive data, statistical analyses were restricted to the depression and anxiety cohorts due to the small number of participants with bipolar disorder. Baseline respondents who responded to key outcomes (depressive symptoms, HRQOL scores) on the NARCOMS Spring 2012 Survey were included in follow-up analyses. Cross-sectionally, bivariate and logistic regression analyses were conducted to assess the associations between participant characteristics (with a focus on sociodemographic characteristics) and mental health non-treatment. The barriers to mental health treatment were explored in bivariate analyses through the lens of Andersen’s Behavioural Model of Health Service Utilization. Longitudinally, bivariate and logistic regression analyses were conducted to assess the temporal association between baseline mental health non-treatment and depressive symptoms (NARCOMS Depression Scale) and HRQOL quality of life outcomes (MCS-12 and PCS-12 scores on the RAND-12) at one-year follow-up. Multivariable regression analyses adjusted for baseline scores (NARCOMS Depression Scale and RAND-12 scores) and relevant baseline sociodemographic and clinical confounders. \n \nResults – In 2011, NARCOMS participants were more commonly untreated for anxiety (26.1%; 95%CI=23.9, 28.3) and bipolar disorder (23.5%; 95%CI=17.5, 29.4), followed by depression (15.2%; 95%CI=14.0, 16.4). In adjusted analyses, participants with younger and older ages (vs. 45 to 64 years; the former significant for depression cohort only), racialized participants (significant for depression cohort only), and those with low SES (health insurance for depression cohort, education for anxiety cohort) had significantly higher odds of mental health non-treatment. Participants with clinically meaningful depressive symptoms and those with more severe levels of disability had significantly lower odds of non-treatment. Of those not receiving treatment, participants were most commonly untreated due to need factors (i.e., “not having symptoms now”) (depression cohort: 57.4%, 313/545; anxiety cohort: 65.2%, 253/388), followed by predisposing factors (depression cohort: 43.1%, 235/545; anxiety cohort: 32.5%, 126/388) and enabling factors (depression cohort: 19.5%, 106/545; anxiety cohort: 22.2%, 86/388). Participants with low SES were significantly more likely to report enabling factors but less likely to report need factors as barriers to mental health treatment. Of those receiving treatment, less than one-third of participants were treated with both psychotherapy and medication (depression cohort: 20.1%, 611/3044; anxiety cohort: 27.7%, 304/1099). Participants with low education were less likely to receive the recommended treatment combination of psychotherapy and medication. Approximately two-thirds of treated participants reported clinically meaningful depressive symptoms (depression cohort: 63.3%, 1927/3044; anxiety cohort: 65.1%, 715/1099). After adjusting for key confounders (baseline scores, as well as other sociodemographic and clinical factors), baseline mental health non-treatment was not associated with the presence of clinically meaningful depressive symptoms or a clinically meaningful decline in mental or physical HRQOL at one-year follow-up. \n \nConclusion – The findings of this thesis add to the literature by identifying important sociodemographic and clinical correlates of mental health service use and later health outcomes in MS patients to be considered in future research. Targeting the barriers identified in this thesis may improve access to mental health care for disadvantaged MS patients. To build upon the results of this thesis, future investigations could utilize multiple data sources (administrative, clinical and registry data) to assess the prevalence and correlates of mental health treatment barriers in a more diverse and representative sample of persons with MS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".