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Record W7053493254

Unmet Mental Health Needs and Barriers to Mental Health Treatment Among Persons with Multiple Sclerosis in the NARCOMS Registry

2024· dissertation· en· W7053493254 on OpenAlexaff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2024
Typedissertation
Languageen
FieldEngineering
TopicMagneto-Optical Properties and Applications
Canadian institutionsRegional Municipality of Waterloo
Fundersnot available
KeywordsMental healthAnxietyQuality of life (healthcare)Psychological interventionDepression (economics)Multiple sclerosisSocioeconomic statusComorbidity
DOInot available

Abstract

fetched live from OpenAlex

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.
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\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. 
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\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. 
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\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. 
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\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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.194
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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