Financial difficulties in bipolar disorder part 2: psychological correlates and a proposed psychological model

Are dysfunctional attitudes elevated and linked to mood in bipolar disorder? A systematic review and meta-analysis

OBJECTIVES

Dysfunctional attitudes (DA) are higher in depression; however, less is understood about their role in bipolar disorder (BD). This paper aimed to explore the presence of DA in BD in comparison to clinical and non-clinical groups. Also explored were the associations between DA and mood states of depression, mania or euthymia in BD.

METHODS

A systematic review and meta-analysis were conducted. A total of 47 articles were included in the systematic review of which 23 were included in the meta-analysis. The quality of each study was rated.

RESULTS

The meta-analysis showed significantly higher DA in BD than healthy controls (d = .70). However, no difference was observed between BD and unipolar participants (d = -.16). When reviewing mood state within BD, a significant mean difference was found between DA scores for euthymic and depressed participants (d = -.71), with those who were depressed scoring higher. Three studies found that psychological therapies significantly reduce DA in BD (d = -.38).

CONCLUSIONS

These findings imply not only that DA are both a characteristic of BD that is not as prevalent in healthy populations but also that a depressed mood state is associated with increased severity. This implies that DA could possibly go 'offline' when mood symptoms are not present. Psychological therapies appear to reduce DA in BD. Implications for future research as well as practice-based implications are expanded on in the discussion.

Mental health in China: exploring the impacts of built environment, work environment, and subjective perception

Introduction

The shifting living and working conditions have profound impacts on the residents' mental health. However, current research in this field has not remarkable investigated.

Methods

This study used the China Labor-force Dynamic Survey (CLDS) dataset from 2018 and relied on a regression model to examine the effects of the built environment, work environment, and subjective perception on the mental health of Chinese citizens. It also considers the circumstances of both migrants and local residents.

Results

This study revealed significant correlations between mental health and greening space rate, road network density, commuting time, work feelings, community trust, economic satisfaction, and other factors. Additionally, the mental health of local residents was shown to be significantly affected by community security, while it shows no significance in migrants. Furthermore, a significant spatial autocorrelation was found in terms of mental health within the central and eastern regions of China.

Discussion

The findings of this study offer valuable insights that can be used to facilitate measures aimed at improving the mental health of residents and promoting the development of healthy cities.

Opportunities for digital health technology: identifying unmet needs for bipolar misdiagnosis and depression care management

Introduction

Digital health technologies (DHTs) driven by artificial intelligence applications, particularly those including predictive models derived with machine learning methods, have garnered substantial attention and financial investment in recent years. Yet, there is little evidence of widespread adoption and scant proof of gains in patient health outcomes. One factor of this paradox is the disconnect between DHT developers and digital health ecosystem stakeholders, which can result in developing technologies that are highly sophisticated but clinically irrelevant. Here, we aimed to uncover challenges faced by psychiatrists treating patients with major depressive disorder (MDD). Specifically, we focused on challenges psychiatrists raised about bipolar disorder (BD) misdiagnosis.

Methods

We conducted semi-structured interviews with 10 United States-based psychiatrists. We applied text and thematic analysis to the resulting interview transcripts.

Results

Three main themes emerged: (1) BD is often misdiagnosed, (2) information crucial to evaluating BD is often occluded from clinical observation, and (3) BD misdiagnosis has important treatment implications.

Discussion

Using upstream stakeholder engagement methods, we were able to identify a narrow, unforeseen, and clinically relevant problem. We propose an organizing framework for development of digital tools based upon clinician-identified unmet need.

The Acceptability and Initial Effectiveness of “Space From Money Worries”: An Online Cognitive Behavioral Therapy Intervention to Tackle the Link Between Financial Difficulties and Poor Mental Health

Background

Previous research has shown a strong relationship between financial difficulties and mental health problems. Psychological factors such as hope and worry about finances appear to be an important factor in this relationship.

Objective

To develop an online based psychological intervention (Space from Money Worries) to tackle the psychological mechanisms underlying the relationship between poor mental health and financial difficulties, and to conduct an initial evaluation of the acceptability and preliminary efficacy of the intervention.

Materials and Methods

30 participants accessing Increasing Access to Psychological Therapies (IAPT) services completed GAD-7 to measure anxiety and PHQ-9 to measure depression upon signing up to the online intervention and again 4 to 8 weeks after this. Participants also completed a measure of perceived financial distress/wellbeing and a “Money and Mental Health Scale” constructed for the evaluation.

Results

Overall, 77% (n = 23) completed the intervention and follow-up assessments. Intent to Treat Analysis showed that there were statistically significant improvements in symptoms of depression, anxiety, improved perceived financial wellbeing and reduced scores on the money and mental health scale. The vast majority of participants rated each module positively.

Conclusions

Space from Money Worries appears to be acceptable and may lead to improvements in mental health, perceived financial wellbeing and a reduced relationship between financial difficulties and poor mental health. However, future research with a larger sample and a control group are needed to confirm that these changes are due to the intervention.

Financial Hardship, Hope, and Life Satisfaction Among Un/Underemployed Individuals With Psychiatric Diagnoses: A Mediation Analysis

BACKGROUND

Individuals with psychiatric diagnoses who are unemployed or underemployed are likely to disproportionately experience financial hardship and, in turn, lower life satisfaction (LS). Understanding the mechanisms though which financial hardship affects LS is essential to inform effective economic empowerment interventions for this population.

AIM

To examine if subjective financial hardship (SFH) mediates the relationship between objective financial hardship (OFH) and LS, and whether hope, and its agency and pathways components, further mediate the effect of SFH on LS among individuals with psychiatric diagnoses seeking employment.

METHODS

We conducted structured interviews with participants (N = 215) of two peer-run employment programs using indicators of OFH and SFH and standardized scales for hope (overall hope, hope agency, and hope pathways) and LS. Three structural equation models were employed to test measurement models for OFH and SFH, and mediational relationships. Covariates included gender, age, psychiatric diagnosis, race/ethnicity, education, income, employment status, SSI/SSDI receipt, and site.

RESULTS

Confirmatory factor analysis (CFA) for items measuring OFH and SFH supported two separate hypothesized factors. OFH had a strong and significant total effect on SFH [standardized beta (B) = 0.68] and LS (B = 0.49), and a weak-to-moderate effect on hope (B = -0.31). SFH alone mediated up to 94% of the effect of OFH on LS (indirect effect B = -0.46, p < 0.01). The effect of SFH on LS through hope was small (indirect effect B = -0.09, p < 0.05), primarily through hope agency (indirect effect B = -0.13, p < 0.01) and not hope pathways. Black and Hispanic ethno-racial identification seemed to buffer the effect of financial hardship on hope and LS. Individuals identifying as Black reported significantly higher overall hope (B = 0.41-0.47) and higher LS (B = 0.29-0.46), net of the effect of OFH and SFH.

CONCLUSION

SFH is a strong mediator of the relationship between OFH and LS in our study of unemployed and underemployed individuals with psychiatric diagnoses. Hope, and particularly its agency component, further mediate a modest but significant proportion of the association between SFH and LS. Economic empowerment interventions for this population should address objective and subjective financial stressors, foster a sense of agency, and consider the diverse effects of financial hardship across ethno-racial groups.

Financial technologies (FinTech) for mental health: The potential of objective financial data to better understand the relationships between financial behavior and mental health

Financial stability is a key challenge for individuals with mental illnesses. Symptomatic periods often manifest in poor financial decision-making including compulsive spending and risky behaviors. This article explores research opportunities and challenges in developing financial technologies (FinTech) to support individuals with mental health. Specifically, we focus on how objective financial data might lead to novel mental health assessment and intervention methods. We have used data from one individual with bipolar disorder (BD) (i.e., an N = 1 case study) to illustrate feasibility of collecting and analyzing objective financial data alongside mental health factors. While we have not found statistically significant trends nor our findings are generalizable beyond this case, our approach provides an insight into the potential of using objective financial data to identify early warning signs and thereby, enable preemptive care for individuals with serious mental illnesses. We have also identified challenges of accessing objective financial data. The paper outlines what data is currently available, what can be done with it, and what factors to consider when working with financial data. We have also explored future directions for developing interventions to support financial well-being and stability. Furthermore, we have described the technical, ethical, and equity challenges for financial data-driven assessments and intervention methods, as well as provided a broad research agenda to address these challenges.

Debt matters? Mental wellbeing of older adults with household debt in England

Background

A record number of older individuals have household debt, but little is known about possible links between debts and their mental wellbeing. This study examines the extent to which different aspects of household indebtedness predict mental wellbeing among this population.

Methods

A sample of 17,091 individuals (72,700 observations) aged 50 and over in England was derived from waves 1–8 of the English Longitudinal Study of Ageing. Mental wellbeing was assessed by two outcome measures: number of depressive symptoms (CES-D 8) and quality of life (CASP-19 score). The predictors of mental wellbeing were examined using quartiles of non-zero overall debt amount, debt-to-income and debt-to-non-housing wealth ratios as alternative measures of debt burden. Linear regression models estimated the associations of mortgage and non-mortgage debt measures with mental wellbeing while adjusting for observable socioeconomic confounding factors. Individual fixed effect models were used to control for all time-constant factors among a longitudinal subsample.

Results

Individuals in the highest debt-to-wealth quartile were particularly at risk of lower mental wellbeing, that is, a higher number of depressive symptoms and lower quality of life. After covariate adjustment, non-mortgage debt predicted lower mental wellbeing on both measures but mortgage debt was only linked to lower quality of life. Among the subsample who experienced changes in high non-mortgage debt levels, a small association of these changes with mental wellbeing outcomes were observed. Asymmetric within-individual estimation showed that both getting rid of and acquiring new debts during the study period predicted symmetrically (small) increases and decreases, respectively, in mental wellbeing.

Conclusion

These findings indicate that among older individuals in England, non-mortgage debt status is linked to poor mental wellbeing. High, non-mortgage, debt-to-wealth ratios may help identify risk of mental wellbeing issues in older people with debts.

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Little is known on debt and mental wellbeing among older individuals in England.

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Debt type and debt measures matter for mental wellbeing.

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Non-mortgage debt was linked to lower mental wellbeing between observations.

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However, smaller effects of non-mortgage debts were observed within-individuals.