Financial Vulnerability Among Swedish Young Adults with Self-Reported ADHD: A Secondary Analysis of Cross-Sectional Survey Data

Abstract

The increasing prevalence of attention-deficit/hyperactivity disorder (ADHD) in Western countries highlights the need to better understand its impact on everyday functioning, including financial outcomes. This study examines financial vulnerability among Swedish young adults with self-reported ADHD diagnosis. A cross-sectional online survey was conducted among young adults (N = 2057). Group differences were examined between individuals with self-reported ADHD diagnosis (n = 149) and those without a psychiatric diagnosis (n = 1380). Logistic regression analyses assessed associations between ADHD diagnosis, financial health variables (financial strain, financial self-control, and financial literacy), and indicators of financial vulnerability, controlling for age and gender. Individuals with self-reported ADHD exhibited significantly poorer outcomes across all financial health variables compared to controls. In the multivariable analyses, an ADHD diagnosis was significantly associated with two of the three indicators of financial vulnerability, with higher odds of taking out consumer loans without understanding the terms (OR = 2.4) and having informal debt to friends or relatives (OR = 1.8). ADHD was not significantly associated with outstanding consumer loan debt for more than 18 months (OR = 1.5). Young adults with ADHD may therefore be at increased risk of financial vulnerability, potentially reflecting a combination of financial, psychological, and behavioural factors. These findings may inform the development and future evaluation of financial education and support initiatives for young adults with ADHD.

1. Introduction

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by persistent patterns of inattention, hyperactivity, and impulsivity, as defined by the American Psychiatric Association (APA, 2025).

Over the past decade reports of a substantial increase in ADHD diagnoses have been widely covered in the media across several Western countries including Sweden (e.g., Abdelnour et al., 2022; BBC, 2024; Karolinska Institutet, 2024; A. F. Martin et al., 2025; NPR, 2024; UCL News, 2023; Vuori et al., 2025).

At the same time, increasing financial hardship is being reported, reflecting rapidly rising expenses that outpace income growth and, potentially, limited financial capability. These developments are associated with a growing reliance on consumer credit and rising levels of personal debt (OECD, 2023; World Bank, 2022).

Low economic knowledge, particularly among young adults, coincides with reports of tightened financial margins among households, thereby increasing the risk of negative consequences for individuals’ financial situations as well as their mental and physical health (Klapper & Lusardi, 2020; Samuelsson et al., 2023; Swedish Financial Supervisory Authority, 2023).

The American organization Children and Adults with Attention-Deficit/Hyperactivity Disorder (CHADD, n.d.) states that many adults living with ADHD face financial difficulties related to impaired executive functioning as well as impulsive decision-making styles.

The Swedish National Care and Intervention Program for ADHD (Nationella vård- och insatsprogram (SKR/Uppdrag psykisk hälsa), 2021) states that ADHD may be associated with reduced financial competence and maladaptive economic behaviours. These challenges can manifest as difficulties in managing personal finances, loss of control over spending, lower savings, increased reliance on credit, and a heightened risk of indebtedness requiring intervention from the Swedish Enforcement Authority.

Even though there appears to be an overlap between ADHD and impaired financial abilities (Bangma et al., 2019; Beauchaine et al., 2017; Pelham et al., 2020; Stickley et al., 2026), adverse financial behaviours (Bangma et al., 2020; Gathergood, 2012; Koerts et al., 2021; Ottaviani & Vandone, 2011), and unfavourable economic circumstances (Altszuler et al., 2016; Fredriksen et al., 2014; Helgesson et al., 2023; Pelham et al., 2020; Virtanen et al., 2020) there is currently a limited body of research that examines these associations in greater detail, both internationally and in Sweden, particularly during young adulthood. The present study addresses this gap by examining self-reported ADHD in relation to indicators of financial vulnerability among young adults in a cross-sectional design. By focusing on financial behaviours, economic conditions, and perceived financial strain, the study aims to contribute to a more nuanced understanding of financial functioning in this population. A review of previous studies in this area is presented below.

1.1. ADHD

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common mental disorders in childhood (APA, 2025). Early prevalence estimates suggested that approximately 5–6% of children are affected; however, substantial increases in ADHD diagnoses have been reported in recent decades across the United States, the United Kingdom, and Europe (Abdelnour et al., 2022; Brown & Conner, 2022; Danielson et al., 2024). Globally, an umbrella review of meta-analyses comprising more than 3.2 million participants estimated a prevalence of 8.0% among children and adolescents (Ayano et al., 2023).

In Sweden, the increase has been particularly pronounced, with more than a sixfold rise in ADHD diagnoses over the past 15 years, prompting a governmental review (The Local, 2024).

Previous research has consistently shown that individuals with ADHD, at the group level, report lower quality of life across the lifespan, including among children (Klassen et al., 2004), college students (Pinho et al., 2019), and adults (Agarwal et al., 2012; Joseph et al., 2019; Quintero et al., 2019), regardless of assessment method. More severe ADHD symptoms have been associated with poorer health-related quality of life, functional impairment, and reduced work productivity as well as lower educational attainment, unemployment, and financial instability (Biederman et al., 2006; Fredriksen et al., 2014; Gjervan et al., 2012; Klein et al., 2012).

Population-based registry studies from Scandinavia further indicate that young adults with ADHD face substantially elevated risks of labour market marginalisation, including long-term unemployment, sickness absence, and disability pension, (Fredriksen et al., 2014; Helgesson et al., 2023; Virtanen et al., 2020) potentially related to high rates of psychiatric comorbidity (Sobanski, 2006/2008; Virtanen et al., 2020).

1.2. ADHD and Financial Hardship

As ADHD is associated with substantial functional impairments it may also affect an individual’s personal financial situation. A more strained financial situation among individuals with ADHD may further be explained by difficulties related to financial decision-making and a tendency toward more impulsive or spontaneous decision-making styles as well as difficulties with financial judgment (Bangma et al., 2019, 2020; Koerts et al., 2021). A recently published study by Stickley et al. (2026), comprising 3717 Japanese adults, investigated the association between ADHD symptoms and financial debt. ADHD symptoms were assessed using the Adult ADHD Self-Report Scale (ASRS) Screener and treated as a continuous measure. The results showed a significant association between ADHD symptoms and debt in the total sample, as well as among women and adults aged 18–34 years. However, the cross-sectional design did not allow the direction of the association between ADHD symptoms and debt to be determined.

Research has also indicated that individuals with ADHD are less likely to have a savings account and, on average, report lower levels of savings compared to individuals without ADHD, which further reflects broader financial vulnerability in this population (Bangma et al., 2019; Pelham et al., 2020). In addition, longitudinal findings suggest that ADHD may be associated with lower lifetime income and less favourable long-term financial outcomes, indicating that these differences may persist across the lifespan (Altszuler et al., 2016; Pelham et al., 2020). However, findings regarding income and debt are not entirely consistent, as Bangma et al. (2020) found no significant group differences in either income or debt levels.

Records from the Swedish Enforcement Authority reveal that adults with ADHD are significantly more likely to incur new debts and have unpaid claims in all categories, particularly for misuse of bank accounts, unpaid alimony, and unpaid road taxes. Also, individuals with ADHD are overrepresented among those in continuous debt for more than a decade (Beauchaine et al., 2020).

There are several characteristics of ADHD that appear to be more directly related to financial difficulties, including executive functioning, such as difficulties with self-regulation and inhibiting unfavorable behaviors, as well as temporal discounting. Additionally, difficulties with working memory, planning, and organizing may negatively affect individuals’ ability to establish and sustain healthy financial behaviors and routines (Bangma et al., 2019; Barkley, 1997; Beauchaine et al., 2017; CHADD, n.d.; Franken et al., 2008; Mäntylä et al., 2012). Neuroimaging studies have shown that difficulties with executive functioning that are often prominent among individuals with ADHD are associated with abnormalities in brain regions, particularly the prefrontal cortex (e.g., Arnsten, 2009).

1.3. ADHD and Consumption Loans/Payday Loans

Although relatively understudied, previous research has identified associations between ADHD or ADHD symptoms (primarily hyperactive-impulsive symptoms) and problematic financial behaviours, including increased use of credit, higher levels of debt, and reduced savings (Bangma et al., 2019; Beauchaine et al., 2017; Pelham et al., 2020).

In contrast to these, Barkley et al. (2006) found no significant differences between individuals diagnosed with hyperactivity in childhood and controls, when followed into young adulthood, with regard to ever having had a car loan or other bank loans, or currently owing money to others. However, a smaller proportion of individuals in the hyperactive group had a savings account, and a greater proportion reported having difficulties saving money to cover monthly expenses. Similarly, Norvilitis et al. (2021) found no association between ADHD symptoms, income, and credit card or student loan debt among college students.

Swedish reports have shown that individuals with psychiatric disabilities have significant economic disadvantages, including lower disposable income, greater reliance on financial assistance, narrower financial margins, and increased difficulty coping with economic stressors (Levinsson & Jiborn, 2013) as well as lower levels of financial competence and more difficulties in financial decision-making (Swedish Consumer Agency, 2026). These challenges may manifest as difficulties in managing personal finances, lower levels of savings, and an overrepresentation in debt enforcement records (e.g., the Swedish Enforcement Authority).

1.4. ADHD and Financial Support from Relatives

Lower income and a greater tendency for risky financial behaviours among individuals with ADHD may increase their reliance on financial support from both relatives and social welfare systems. Altszuler et al. (2016) found that individuals with ADHD were more financially dependent on family members and the welfare system, suggesting a greater reliance on external sources of financial support.

Other studies support these findings, highlighting an increased need for social assistance among individuals with mental illness (Levinsson & Jiborn, 2013) as well as ADHD (Fletcher, 2014) and the necessity for parental guidance in financial matters (Norvilitis et al., 2021). There is also evidence suggesting that young adults with ADHD tend to remain in the parental home for a longer period of time (Pelham et al., 2020). However, Barkley et al. (2006) reported that adults who were hyperactive as children did not owe significantly more money to others than control groups.

1.5. Financial Strain and ADHD

ADHD has been associated with a negative impact on financial capability, including difficulties related to income and debt levels (Bangma et al., 2019; Pelham et al., 2020). Such financial difficulties may restrict opportunities for leisure activities and social participation, which in turn can contribute to social exclusion and negatively affect mental health (e.g., Haugland et al., 2024). This interplay may be associated with worsening ADHD symptoms and an increased risk of comorbid conditions, such as depression and anxiety, which are commonly observed among individuals with ADHD (Blackman et al., 2005; Gnanavel et al., 2019). Consequently, a “vicious cycle” may emerge, in which financial difficulties and impaired mental health reinforce one another over time (Ryu & Fan, 2023; Sweet et al., 2013).

Research has shown that ADHD is associated with an increased risk of financial stress, with some studies indicating up to a threefold higher risk compared to individuals without ADHD (Brook et al., 2013; Norvilitis et al., 2021). Persistent economic stress among individuals with ADHD is also strongly associated with elevated suicide risk (Beauchaine et al., 2020).

1.6. Financial Self-Control, Financial Decision-Making and ADHD

In financial behaviour research, self-control is conceptualized as the ability to resist temptations and override impulses in favour of more advantageous long-term choices; a lack of self-control has been shown to predict problematic financial behaviour, financial illiteracy, and lower financial well-being, as well as higher levels of financial stress and anxiety (Gathergood, 2012; Strömbäck et al., 2017). In general, individuals tend to overvalue immediate benefits while underestimating future negative consequences. Previous research (L. E. Martin & Potts, 2009; Wittmann & Paulus, 2008) has shown that the tendency to discount future costs is related to individual impulsivity.

Individuals with ADHD may exhibit impaired decision-making abilities (Barkley, 1997; Beauchaine et al., 2017; Franken et al., 2008), which may be particularly problematic when access to credit provides immediate access to products while allowing payment to be deferred (Gathergood, 2012; Ottaviani & Vandone, 2011). In addition, higher levels of emotional impulsiveness have been reported among individuals with persistent ADHD, with both emotional impulsiveness and ADHD persistence being associated with impaired financial self-control and decision-making (Barkley & Fischer, 2010).

1.7. Financial Competence and ADHD

International research has reported low levels of financial literacy both in the general population across different countries (Demertzis et al., 2024; Lusardi, 2015) as well as for young adults (Cision, 2019; Lusardi & Streeter, 2023; Samuelsson et al., 2023; Swedish Financial Supervisory Authority, 2023). Furthermore, many studies document a gender gap with men tending to have higher knowledge than women, and women being more likely to select the response ‘Don’t know’ (Demertzis et al., 2024; Lusardi & Streeter, 2023; Samuelsson et al., 2023). Several studies have reported associations between financial literacy and personal financial variables, such as consumer loans (Disney & Gathergood, 2012; Levinsson et al., 2026; T. Martin et al., 2021).

Despite growing interest in the financial consequences of ADHD, empirical research explicitly examining financial competence, such as financial literacy, among individuals with ADHD remains limited. In a study by Koerts et al. (2023) the ADHD group performed significantly lower on items concerning understanding and keeping track of one’s own financial situation as well as having savings. However, differences in “basic arithmetic calculations” were small and non-significant.

Evidence from Sweden further indicates that financial competence is a challenge among young people more broadly. A national survey reported that approximately half of Swedish adolescents perceived themselves as lacking basic financial knowledge, which contributed to doubts about their ability to make sound financial decisions, and 44% reported that personal finances constituted a major source of concern (Cision, 2019).

1.8. Aim and Research Questions

Both an ADHD diagnosis and financial difficulties can have significant negative effects on an individual’s health and their ability to function in daily life. Deterioration in well-being may lead to increased sick leave, greater reliance on healthcare services, and have a negative impact on everyday functioning, factors that negatively affect not only the individual but also their immediate social environment and society at large. The combination of ADHD and financial difficulties may further increase vulnerability to such adverse outcomes.

Previous studies have indicated that adults with ADHD symptoms or diagnoses experience various forms of financial difficulties, including debt, reduced savings, and impaired financial decision-making. Thus, research on the relationship between ADHD and financial difficulties already exists. However, knowledge remains limited regarding this relationship among young adults in Sweden. In addition, specific aspects of financial vulnerability, such as financial literacy and informal debt, remain relatively understudied in relation to ADHD, both in Sweden and internationally. Furthermore, relatively few studies have examined multiple dimensions of financial vulnerability within the same study, including financial strain, financial self-control, financial literacy, and different forms of debt.

As a result, knowledge remains limited regarding the nature and extent of financial vulnerability among young adults with ADHD, particularly during a developmental period characterized by increasing financial independence and responsibility.

The aim of this study is therefore to examine financial vulnerability among young adults who reported having an ADHD diagnosis, in relation to key financial health indicators: financial strain, financial self-control, and financial literacy as well as different forms of debt. The findings may contribute to a better understanding of financial vulnerability among young adults with ADHD and may have implications for policy initiatives, preventive interventions, and clinical practice aimed at addressing financial difficulties and reducing the risk of long-term financial ill-being. The results may also contribute to increased understanding of how financial education and support initiatives can be more effectively tailored to the specific needs and challenges of young adults with ADHD.

The objectives of the present study will be addressed through the following research questions:

• Do young adults with self-reported ADHD differ from those without a psychiatric diagnosis in terms of financial strain, financial self-control, and financial literacy?
• To what extent do an ADHD diagnosis and financial health variables (financial strain, financial self-control and financial literacy) relate to three outcome variables representing indicators of financial vulnerability: (a) having outstanding consumer loan debt for more than 18 months, (b) having taken out a consumer loan without understanding or reviewing the terms, and (c) having informal debt to friends or relatives, while controlling for age and gender.

2. Method

2.1. Design and Procedure

The study was based on data collected through an online survey. Data collection was conducted over a two-week period in October 2021.

The survey was administered by the external research company Enkätfabriken, which specializes in web-panel data collection. Enkätfabriken was paid by the Department of Psychology at Lund University for data collection. The research team was responsible for the study design, survey content, data analysis, and interpretation of the findings. Enkätfabriken were not involved in the analysis or interpretation of the results.

All questions were required to be completed prior to submission, ensuring that no incomplete responses were included in the dataset. Prior to participation, respondents were informed about the study’s purpose, content and that participation was anonymous, voluntary, and could be withdrawn at any time. Like in most other web panels the participants received a small economic compensation from the panel provider which could be transformed to gift cards or donations.

2.2. Participants

The sample consisted of 2057 young adults aged 18–29 years and was recruited from a web panel of approximately 200,000 individuals. The panel provider, Enkätfabriken, uses background information on demographic characteristics, including age, gender, and geographic location, when constructing samples and quotas. In the present study, quotas for age, gender, and geographic region were applied during data collection to approximate the demographic distribution of the Swedish population. Apart from the age restrictions, the inclusion criteria were that the respondents could read and understand Swedish, which was the language used for the survey, and that they had online access. Of the 2057 participants, 1059 were women and 998 were men, with a mean age of 23.6 years (SD = 3.5). See Table 1 for demographic data on the participants. Nearly 33% (n = 677) reported having one or more psychiatric diagnoses.

Table 1. Demographic data on the participants (N = 2057).

Characteristics	n	%
Gender
Male	998	48.5
Female	1059	51.5
Completed education
Compulsory education	255	12.4
Further education/upper secondary education	1032	50.2
Higher education	770	37.4
Marital status
Single	986	47.9
In a relationship	917	44.6
Other	154	7.5
Accommodation
Homeowner	429	20,9
Tenant-ownership apartment	386	18.8
Rented apartment	843	41.0
Lodger/sub-letting	73	3.5
Living with parents	279	13.6
Other	47	2.3
Employment status
Employed full-/part-time	959	46.6
Self-employed	156	7.6
Student	632	30.7
Job-seeker	202	9.8
Other	108	5.3
Source of income
Salary from work	1121	54.5
Benefits	215	10.5
Student loan	440	21.4
Other	281	13.7
Psychiatric diagnosis
No	1380	67.1
Yes	677	32.9
Types of Psychiatric Diagnoses
Neurodevelopmental disorders	141	6.9
Depressive disorders	106	5.2
Anxiety disorders	80	3.9
>1 type of psychiatric diagnosis	140	6.8
Other psychiatric diagnoses	35	1.7
Prefer not to specify	175	8.5

To address Research Question 1, two groups of participants were compared: Group 1 consisted of individuals who self-reported an ADHD diagnosis (n = 149), and Group 2 included those who reported having no psychiatric diagnosis (n = 1380). Individuals who reported both an ADHD diagnosis and one or more additional psychiatric diagnoses were included in Group 1. Notably, differences were observed in educational attainment, with more than one in five participants in Group 1 having completed only compulsory education, compared with just under one in ten in Group 2. Demographic characteristics for the two groups are presented in Table 2 in order to demonstrate similarities and differences.

Table 2. Demographic and financial data on the two groups (n = 1529).

		Group 1: ADHD-Diagnosis (n = 149)		Group 2: No Psychiatric Diagnoses (n = 1380)
Demographic Characteristics		n	%	n	%
Gender	Male	74	49.7	717	52.0
	Female	75	50.3	663	48.0
Age groups	Younger (18–23)	72	48.3	660	47.8
	Older (24–29)	77	51.7	720	52.2
Completed education	Compulsory education	31	20.8	127	9.2
	Further education/upper secondary education	77	51.7	693	50.2
	Higher education < 2 years	26	17.4	216	15.7
	Higher education > 2 years	15	10.1	344	24.9
Marital status	Single	71	47.7	656	47.5
	In a relationship	72	48.3	619	44.9
	Other	6	4.0	105	7.6
Accommodation	Homeowner	28	18.8	284	20.6
	Tenant-ownership apartment	26	17.4	265	19.2
	Rented apartment	65	43.6	561	40.7
	Lodger/sub-letting	5	3.4	50	3.6
	Living with parents	21	14.1	188	13.6
	Other	4	2.7	32	2.3
Employment status	Employed full-/part-time	69	46.3	686	49.7
	Self-employed	16	10.7	86	6.2
	Student	36	24.2	442	32.0
	Job-seeker	16	10.7	118	8.6
	Other	12	8.1	48	3.5
Source of income	Salary from work	70	47.0	824	59.7
	Benefits	25	16.8	93	6.7
	Student loan	28	18.8	301	21.8
	Other	26	17.4	162	11.7
Financial variables	Consumer loan debt	50	33.6	260	18.8
	Perceived financial difficulties	93	62.4	548	39.7
	Informal debt to friends or relatives	59	39.6	304	22.0

2.3. Materials

The questionnaire included a spectrum of questions and measurements about financial literacy, personal financial situation, and mental health. Only those measures used in the current analyses are described. The survey contained both established scales and questions formulated by the research group. These are presented below. Demographic variables included in the statistical analyses used were gender, which consisted of two categories: male and female, and age which was treated as a continuous variable.

2.3.1. Financial Outcome Variables

The three financial outcome variables were deliberately formulated in relatively simple terms as single-item binary indicators, and were intended to capture key aspects of respondents’ financial circumstances. In the regression analyses, these self-reported indicators were treated as indicators of financial vulnerability rather than validated measurements. The first outcome variable was whether the respondents had outstanding consumer loan debt taken out at least 18 months ago (“Yes”/”No”). The 18-month threshold was chosen to identify debt that had remained outstanding over a relatively extended period and was therefore intended to capture a more persistent form of financial difficulty rather than recent or short-term borrowing. Although the term consumer loan is used throughout this manuscript, the Swedish term refers specifically to high-cost, short-term loans with easy access and high interest rates, commonly described as payday loans, rather than to consumer credit more broadly.

The second outcome variable was based on a follow-up question to the question about consumer loans: “Have you ever taken out a consumer loan without fully understanding or reviewing the loan terms (e.g., interest rates)?” The question was presented to all respondents; however, for the data analysis, only respondents who had answered affirmatively to the preceding question about having taken out a consumer loan were included. The third outcome variable was whether they had any informal debt, defined as money owed to friends or relatives (“Yes/”No”). Having any informal debt may reflect different financial circumstances and should therefore be interpreted as an indicator of financial vulnerability rather than a uniform measure of financial difficulty. No formal assessment of the content or face validity of these researcher-developed indicators was conducted.

2.3.2. ADHD Diagnosis

Respondents were asked whether they were living with a psychiatric diagnosis. Those who answered Yes were encouraged to specify their diagnosis. This allowed us to identify participants living with an ADHD diagnosis. No requirement was imposed that the reported ADHD diagnosis had to be clinically verified by a healthcare professional. Furthermore, no information was collected regarding the timing of the diagnosis. The group of participants who reported an ADHD diagnosis was then compared with those who reported having no psychiatric diagnosis.

2.3.3. Financial Strain

Financial strain was assessed using two items designed to capture the psychological burden associated with participants’ financial situations: “How psychologically stressful have you found your financial situation in the past year?” and “How much time have you spent worrying about your financial situation?”. Responses were recorded on 5-point Likert scales (1 = not stressful at all to 5 = highly psychologically stressful; 1 = no time at all to 5 = a lot of time), with higher scores indicating greater financial strain. For the t-tests, the two items were analysed separately. For the regression analyses, a composite financial strain score was calculated by summing the two items (range = 2–10). The two-item scale demonstrated acceptable internal consistency (Cronbach’s α = 0.80).

2.3.4. Financial Self-Control

In the present study, we use the term ‘financial self-control’ to refer to an individual’s ability to regulate financial behaviours and impulses in order to achieve long-term economic goals. The measure of financial self-control was constructed for the present study by combining five items from the Swedish Financial Supervisory Authority’s Report on Household Finances (Swedish Financial Supervisory Authority, 2020). Although the items were included in the original report, they were not previously used as a composite scale. The items capture different but related aspects of financial self-control, including impulsive consumption, preference for purchasing on credit, spontaneity, preference for immediate gratification, and whether the respondent identifies more as a “saver” or a “spender.” They were combined because they all relate to the regulation of spending and saving behaviours and the prioritization of immediate versus longer-term financial goals.

Responses were recorded on a 4-point Likert scale ranging from 1 to 4 (Strongly agree to Do not agree at all), with an additional “Don’t know” option. An example item is: “I prefer to buy things on credit rather than wait until I have saved enough to purchase what I want.” Prior to analysis, items were recoded and, where necessary, reverse-coded so that higher scores consistently reflected greater financial impulsivity and, consequently, lower levels of financial self-control. The response option “Don’t know” was treated as missing data. Participants who selected “Don’t know” on at least one of the five financial self-control items were therefore excluded from analyses involving the financial self-control measure. The financial self-control score was calculated as the sum of the five items for participants with valid responses to all five items. The scale was treated as a continuous measure. The internal consistency of the scale was modest (Cronbach’s α = 0.71).

Since one of the five items included in the measure explicitly referred to purchasing on credit, there was a potential overlap between the measure and the consumer loan outcomes. To assess whether this potential overlap influenced the regression results, sensitivity analyses were conducted by excluding this item and recalculating the financial self-control measure based on the remaining four items. The three logistic regression models were then rerun using the four-item measure, while all other variables and model specifications were kept unchanged.

2.3.5. Financial Literacy

Financial literacy is a key construct in economic and behavioural research, referring to individuals’ ability to understand and effectively use economic knowledge in financial decision-making. It is defined by the OECD (2019) as ‘knowledge and understanding of financial concepts and risks, and the skills, motivation, and confidence to apply such knowledge and understanding in order to make effective decisions across a range of financial contexts, to improve the financial wellbeing of individuals and society, and to enable participation in economic life.’

To measure financial literacy, the “Big Three” questions first introduced by Lusardi and Mitchell (2008, 2011) were administered. The battery consists of three questions and measures respondents’ understanding of (1) interest rates, (2) inflation, and (3) risk diversification. The scale has been implemented in several surveys, (as described in Levinsson et al., 2025). For all three questions the respondent has the option to answer ‘Don’t know’. Answering ‘Don’t know’ was in this report considered as an indication of lack of financial literacy (see Lusardi & Streeter, 2023). Respondents who answered all three questions correctly were classified as having financial literacy, while all other respondents were classified as lacking financial literacy. This dichotomization is consistent with common practice in studies using the “Big Three” questions (e.g., Kaiser et al., 2026; Lusardi & Mitchell, 2011). The resulting dichotomous variable was used in subsequent statistical analyses to facilitate comparison with previous research.

In the present sample, as described in (Levinsson et al., 2025), the reliability of the ‘Big Three’ scale was relatively low (Cronbach’s α = 0.51), which may partly reflect the small number of items and their coverage of distinct financial concepts. However, the average inter-item correlation between items was 0.26, which is within the recommended span of 0.2 and 0.4 (Piedmont, 2014). The Swedish version of the “Big Three” questions was taken from a report by the Swedish Financial Supervisory Authority (2020).

2.4. Data Analysis

All analyses were performed using IBM SPSS Statistics (Version 30).

Before addressing the research questions and to explore potential relationships between associated factors and the outcome variables, bivariate correlations were analysed using Pearson’s correlation coefficient (r). For associations between two dichotomous variables, the phi coefficient (φ) was used. Assumptions for correlation analyses, including approximate normality and linearity, were assessed through inspection of histograms, skewness and kurtosis, and scatterplots.

To address the first research question, examining differences between Group 1 and Group 2, independent samples t-tests and χ²-tests were conducted. Effect sizes were calculated using Cohen’s d for continuous variables and the phi (φ) coefficient for categorical variables. Assumptions for the t-tests, including normality and homogeneity of variances, were assessed prior to analysis. When the assumption of homogeneity of variances was violated, Welch’s t-test was used.

To address the second research question, logistic regression analyses were conducted to examine the associations between ADHD diagnosis, financial strain, financial self-control, and financial literacy and the outcomes of (a) having consumer loan debt, (b) having taken a consumer loan without understanding or reviewing the terms, and (c) having informal debt to friends or relatives. Age and gender were included as covariates. Outcome variables were coded as binary indicators (0 = no, 1 = yes). ADHD diagnosis was coded as 0 = no psychiatric diagnosis and 1 = ADHD diagnosis, and financial literacy as 0 = financially literate and 1 = lacking financial literacy. Female was used as the reference category for gender.

All covariates were included in the models based on prior research and theoretical relevance. Given the absence of a clear hierarchical structure among the variables, they were entered simultaneously rather than in separate blocks.

Model fit was evaluated using Nagelkerke’s R². Multicollinearity was assessed using variance inflation factors (VIF), all of which were close to 1 (range: 1.02–1.30), indicating multicollinearity was not a concern. Odds ratios (ORs) with 95% confidence intervals were reported to quantify associations between key variables and the outcome variables.

Relationship to Previous Publications Based on the Same Dataset

The present study is a secondary analysis of survey data collected from 2057 Swedish young adults in 2021. The dataset has previously been used in three publications.

The first publication (Samuelsson et al., 2023), published in the Journal of Financial Literacy and Wellbeing, provided a descriptive account of financial literacy, personal financial situation, and self-reported mental health among young adults. The second publication, Between Knowledge and Strategy: A Cross-Sectional Study on Financial Literacy, Coping, Consumer Loans, and Payment Preferences Among Young Adults in Sweden (Levinsson et al., 2025), published in Behavioral Sciences, examined relationships between consumer-loan use, financial literacy, and coping strategies, including problem-focused, emotion-focused, and avoidant coping. The third publication (Levinsson et al., 2026), also published in Behavioral Sciences, examined associations between financial literacy, mental health, social and emotional loneliness, and consumer-loan debt.

The present study addresses a distinct research question by examining financial vulnerability in relation to self-reported ADHD. Although the outcome in Model 1 has been examined in previous publications based on this dataset, the present study investigates its association with self-reported ADHD, which was not examined in the previous studies.

Some variables included in the present study, including financial strain and debt to family members or friends, were described descriptively in the initial publication (Samuelsson et al., 2023), but were not examined using inferential analyses in that publication. Our review of the three previous publications indicates that financial strain and financial self-control have not previously been statistically analysed. Furthermore, taking out a consumer loan without understanding its terms and having informal debt to friends or relatives have not previously been analysed as outcomes in these publications.

The present study therefore extends the previous work by examining the association between self-reported ADHD and financial vulnerability, including additional financial outcomes and characteristics that have not previously been investigated in this dataset.

2.5. Ethical Considerations

The study was not subject to ethical review under Swedish law (2003:460) (Swedish Parliament, n.d.), as the survey was anonymous and no personal data were collected. Participants were informed that their participation was voluntary and that they could withdraw at any time without providing a reason. The survey included questions on topics that could, in some cases, lead to distress, such as personal finances and mental health. Therefore, at the beginning of the survey, participants were informed that if they experienced distress, they could seek help from healthcare services. After reading this introductory information, participants gave informed consent before proceeding to the actual survey.

3. Results

Before addressing the research questions, bivariate associations were examined. The correlation matrix is presented in Table 3. Overall, financial self-control was positively associated with financial literacy and negatively associated with financial strain and indicators of financial vulnerability, including consumer loan use, lack of understanding of loan terms, and informal debt. ADHD diagnosis showed small but significant positive correlations with financial strain and several vulnerability indicators. Age was positively associated with financial literacy and showed small associations with financial strain and consumer loan use. Gender was also associated with several financial vulnerability indicators, as reported in subsequent chi-square analyses. It should be noted that, although the analysis showed multiple significant correlations, the correlation coefficients were relatively small.

Table 3. Correlation matrix of financial health variables, ADHD diagnosis, demographic variables and indicators of financial vulnerability.

Variable	1.	2.	3.	4.	5.	6.	7.	8.	9.
1. ADHD	1.00
2. Fin. strain	0.13 **	1.00
3. Fin. self-control	0.14 **	0.31 **	1.00
4. Fin. literacy	0.06 *	0.15 **	0.31 **	1.00
5. Consumption loans	0.11 **	0.25 **	0.38 **	0.16 **	1.00
6. Not investigating terms	0.18 **	0.22 **	0.38 **	0.18 **	0.58 **	1.00
7. Informal debt	0.12 **	0.29 **	0.32 **	0.12 **	0.38 **	0.38 **	1.00
8. Gender	−0.01	−0.07 **	0.13 **	−0.11 **	0.12 **	0.12 **	0.08 **	1.00
9. Age	−0.01	0.05 *	−0.09 **	−0.11 **	0.05 *	0.03	−0.004	−0.03	1.00

Note. Pearson correlations are reported; point-biserial correlations are reported for dichotomous variables. Dichotomous variables were coded 0/1. ** p ≤ 0.001, * p < 0.05. The number of observations varies across correlations because of missing data and variable-specific eligibility criteria.

3.1. Research Question 1

To address Research question 1, participants were divided into two groups. Group 1 consisted of respondents with self-reported ADHD diagnosis, whereas Group 2 included respondents reporting no psychiatric diagnosis. Differences between the two groups were assessed with respect to financial strain, financial self-control, and financial literacy.

3.1.1. Financial Strain

Two independent samples t-tests were conducted to examine whether the two groups differed in financial strain. The test revealed that Group 1 reported experiencing their financial situation as more psychologically distressing over the past year (M = 3.60, SD = 1.16) than Group 2 (M = 3.02, SD = 1.18). This difference was statistically significant, t(1527) = −5.73, p < 0.001, with a mean difference of −0.58 (95% CI [−0.78, −0.38]). The effect size was moderate (Cohen’s d = 0.49).

Group 1 also reported spending more time worrying about their financial situation over the past year (M = 3.40, SD = 1.28) than Group 2 (M = 3.05, SD = 1.21). This difference was statistically significant, t(1527) = −3.27, p = 0.001, with a mean difference of −0.34 (95% CI [−0.55, −0.14]). The effect size was small to moderate (Cohen’s d = 0.28).

3.1.2. Financial Self-Control

The scale measuring financial self-control consisted of five items; means and standard deviations for each item for Group 1 and 2 are presented in Supplementary Table S1.

For the total composite scale of financial self-control, Group 1 scored significantly higher (M = 11.90, SD = 3.08) than Group 2 (M = 10.14, SD = 3.36), indicating greater financial impulsivity and, consequently, lower financial self-control among individuals with ADHD. This difference was statistically significant, t(147.48) = −5.89, p < 0.001, with a mean difference of −1.76 points (95% CI [−2.35, −1.17]). The effect size was moderate (Cohen’s d = 0.53).

3.1.3. Financial Literacy

Before conducting the analyses, participants were categorized as financially literate (all three answers correct) or lacking financial literacy. A chi-square test showed a significant association between ADHD diagnosis and financial literacy, χ²(1, N = 1529) = 5.36, p = 0.02. Group 1 were somewhat more likely to be classified as lacking financial literacy compared to Group 2 (84.6% vs. 76.2%). The association was small (Φ = 0.06).

3.2. Research Question 2

To examine the extent to which ADHD diagnosis, financial strain, financial self-control, and financial literacy were associated with each outcome variable of financial vulnerability, while controlling for age and gender, three binary logistic regression analyses were conducted.

3.2.1. Model 1: Consumer Loan Debt

For the first outcome, having outstanding consumer loan debt for more than 18 months, the full model was statistically significant, χ²(6) = 223.96, p < 0.001, based on N = 1308 participants. The model had a Nagelkerke’s R² of 0.245.

As shown in Table 4, financial strain, financial self-control, financial literacy, gender, and age were significantly associated with the likelihood of having outstanding consumer loan debt.

Table 4. Multiple logistic regression of having outstanding consumer loan debt for more than 18 months.

Variables	B	Wald	Sig.	Odds-Ratio	CI 95%
					L	U
ADHD	0.44	3.81	0.051	1.55	0.998	2.40
Financial strain	0.23	32.14	<0.001 **	1.26	1.16	1.36
Financial self-control	0.22	76.42	<0.001 **	1.25	1.19	1.31
Financial literacy	0.58	6.98	0.008 *	1.78	1.16	2.73
Gender	0.46	8.53	0.003 *	1.58	1.16	2.14
Age	0.06	6.51	0.011 *	1.06	1.01	1.11
Constant	−7.44	112.74	<0.001	0.001

Note: ** p ≤ 0.001, * p < 0.05. CI = confidence interval. L = lower, U = upper.

The most notable associations indicated that individuals with lower financial literacy had 78% higher odds of having consumer loan debt, while men had 58% higher odds. In addition, each one-point increase in financial strain increased the odds of having outstanding consumer loan debt increased by 26%. Financial self-control and age were also significant associated variables. ADHD diagnosis was not statistically significantly associated with having outstanding consumer loan debt (OR = 1.55, p = 0.051), although the point estimate indicated higher odds among participants with ADHD. Full regression results are presented in Table 4.

3.2.2. Model 2: Consumer Loan Without Understanding or Reviewing the Terms

For the second outcome, having taken out a consumer loan without fully understanding or reviewing the loan terms (e.g., interest rates), the full model was statistically significant, χ²(6) = 35.91, p < 0.001, based on N = 274 participants, with a Nagelkerke’s R² of 0.165. Of the 274 participants included in the analysis, 158 (58%) reported having taken out a consumer loan without fully understanding or reviewing the loan terms.

In this model, ADHD diagnosis, financial self-control, financial literacy and age were significantly associated with the odds of reporting having taken out a consumer loan without understanding or reviewing the terms. However, financial strain (p = 0.081) and gender (p = 0.379) were not significantly associated with the outcome.

The most notable associations indicated that individuals with lower financial literacy had 159% higher odds of having taken out a consumer loan without understanding or reviewing the terms, while individuals with an ADHD diagnosis had more than twice the odds (135%) of the same outcome. In addition, each one-point increase in the scale for financial self-control, reflecting lower financial self-control, increased the odds of having taken out a consumer loan without understanding or reviewing the terms. Age was also a significant independent variable. Full regression results are presented in Table 5.

Table 5. Multiple logistic regression of having taken out a consumer loan without fully understanding or reviewing the loan terms.

Variables	B	Wald	Sig.	Odds-Ratio	CI 95%
					L	U
ADHD	0.86	4.85	0.028 *	2.35	1.10	5.04
Financial strain	0.15	3.05	0.081	1.16	0.98	1.37
Financial self-control	0.19	13.13	<0.001 **	1.21	1.09	1.33
Financial literacy	0.95	5.41	0.020 *	2.59	1.16	5.78
Gender	0.24	0.78	0.379	1.28	0.74	2.19
Age	0.09	4.63	0.031 *	1.09	1.01	1.18
Constant	−6.28	20.00	<0.001	0.002

Note: ** p ≤ 0.001, * p < 0.05. CI = confidence interval. L = lower, U = upper.

3.2.3. Model 3: Informal Debt to Friends or Relatives

For the third outcome, having informal debt to friends or relatives, the full model was statistically significant, χ²(6) = 176.76, p < 0.001, based on N = 1308 participants with a Nagelkerke’s R² of 0.19.

In this model, ADHD diagnosis, financial strain, financial self-control and gender were significantly associated with informal debt. However, financial literacy (p = 0.092) and age (p = 0.941) were not significantly associated with the outcome.

The most notable associations indicated that individuals with an ADHD diagnosis had 81% higher odds of having informal debt, while men had 38% higher odds of the same outcome. In addition, each one-point increase in financial strain increased the odds of having informal debt by 32%. Financial self-control was also a significant independent variable. Full regression results are presented in Table 6.

Table 6. Multiple logistic regression of having informal debt to friends or relatives.

Variables	B	Wald	Sig.	Odds-Ratio	CI 95%
					L	U
ADHD	0.59	7.77	0.005 *	1.81	1.19	2.74
Financial strain	0.28	52.95	<0.001 **	1.32	1.22	1.42
Financial self-control	0.14	36.74	<0.001 **	1.15	1.10	1.20
Financial literacy	0.32	2.84	0.092	1.38	0.95	2.00
Gender	0.32	4.96	0.026 *	1.38	1.04	1.84
Age	0.002	0.006	0.941	1.00	0.96	1.04
Constant	−5.04	66.96	<0.001	0.006

Note: ** p ≤ 0.001, * p < 0.05. CI = confidence interval. L = lower, U = upper.

3.2.4. Sensitivity Analyses

Sensitivity analyses excluding the item referring to purchasing on credit in the financial self-control measure yielded results comparable to those of the primary analyses across all three logistic regression models. The estimated associations between self-reported ADHD and the outcomes remained similar in magnitude across the models. The four-item measure showed lower internal consistency than the original five-item measure (Cronbach’s α = 0.63 vs. 0.71), but exclusion of the credit-related item did not materially alter the overall pattern of regression results. However, in Model 1, the association between self-reported ADHD and the outcome reached statistical significance after removal of the credit-related item (OR = 1.57, 95% CI [1.02, 2.42], p = 0.040), whereas it did not reach statistical significance in the primary analysis (OR = 1.55, 95% CI [0.998, 2.402], p = 0.051). The sensitivity analyses are reported in Supplementary Tables S2–S4.

As a sensitivity analysis, the dichotomized Big Three measure was replaced with a continuous score ranging from 0 to 3. Full sensitivity analysis results are presented in Supplementary Tables S5–S7.

In model 1, the association between self-reported ADHD and the outcome remained similar in magnitude but did not reach conventional statistical significance (OR = 1.53, 95% CI [0.99, 2.34], p = 0.058). In contrast, the association between financial literacy and the outcome differed from the primary analysis and was no longer statistically significant (OR = 0.86, 95% CI [0.74, 1.01], p = 0.061).

In Model 2, the association between self-reported ADHD and the outcome remained largely unchanged and statistically significant when financial literacy was operationalized as a continuous Big Three score rather than a dichotomous measure (OR = 2.34, 95% CI [1.10, 4.99], p = 0.028). The association with financial literacy differed by operationalization: it was statistically significant in the primary analysis (OR = 2.59, p = 0.020) but not when using the continuous score (OR = 0.75, p = 0.057).

In Model 3, the association between self-reported ADHD and the outcome remained largely unchanged and statistically significant when the dichotomized Big Three measure was replaced with a continuous score (OR = 1.80, 95% CI [1.19, 2.73], p = 0.006). The association between financial literacy and the outcome remained non-significant (OR = 0.94, 95% CI [0.81, 1.08], p = 0.377).

To assess the robustness of the findings to potential residual confounding, sensitivity analyses were also conducted with additional adjustment for completed education and employment status.

Model 1: After additional adjustment for completed education and employment status, the association between self-reported ADHD and outstanding consumer loan debt lasting more than 18 months remained similar in magnitude, with a slightly higher p-value (OR = 1.54, 95% CI 0.97–2.43, p = 0.067), compared with the original model (OR = 1.55, 95% CI 1.00–2.40, p = 0.051). Full results are presented in Supplementary Table S8.

Model 2: After additional adjustment for completed education and employment status, the association between self-reported ADHD and having taken out a consumer loan without fully understanding or reviewing the loan terms was attenuated and no longer statistically significant (OR = 2.06, 95% CI 0.94–4.48, p = 0.070), compared with the original model (OR = 2.35, 95% CI 1.10–5.04, p = 0.028). Full results are presented in Supplementary Table S9.

Model 3: After additional adjustment for completed education and employment status, the association between self-reported ADHD and informal debt to friends or relatives remained statistically significant, with a slightly attenuated odds ratio (OR = 1.73, 95% CI 1.12–2.68, p = 0.014), compared with the original model (OR = 1.81, 95% CI 1.19–2.74, p = 0.005). Full results are presented in Supplementary Table S10.

4. Discussion

4.1. Research Question 1

Significant differences between the two groups were observed on both items measuring financial strain, where individuals with ADHD reported both a more psychologically distressing financial situation and spending more time worrying about their finances compared to respondents reporting no psychiatric diagnosis. These findings are consistent with previous research by Brook et al. (2013) and Norvilitis et al. (2021), describing ADHD as a risk factor for elevated financial stress. Although the present study is cross-sectional and therefore cannot establish causal conclusions, the results suggest that young adults with ADHD experience higher levels of financial strain.

One possible explanation is that ADHD is associated with a higher risk of comorbid conditions such as depression and anxiety (Blackman et al., 2005; Gnanavel et al., 2019), as well as structural financial disadvantages, including lower income and increased debt levels (Bangma et al., 2019; Pelham et al., 2020). In addition, financial difficulties may exacerbate psychological distress, which in turn further impairs financial decision-making, consistent with the “vicious cycle” described in previous research (Ryu & Fan, 2023; Sweet et al., 2013). Findings by Beauchaine et al. (2020), demonstrating that persistent economic stress is associated with elevated suicide risk among individuals with ADHD, further highlight the severe mental health consequences that may arise in this context.

Regarding financial self-control there was a moderate difference where individuals with ADHD scored higher on the total composite scale indicating a lower level of financial self-control. As stated above, earlier research (Barkley & Fischer, 2010; Beauchaine et al., 2017) has seen that people with ADHD often exhibit symptoms of impulsivity and that these in turn can affect financial decision-making and behaviour making long-term goals seem less rewarding. In the current study, operationalizing financial self-control as the ability to regulate financial behaviour and impulses in order to achieve long-term economic goals, the results thus seem to be in line with previous studies. The scale includes one item that explicitly concerns paying by credit and thereby promotes instant gratification, as described by Ottaviani and Vandone (2011). The constructs discussed by Beauchaine et al. (2017), including debt, poor self-control, and delay discounting, can all be conceptualized as components of financial self-control.

A significantly lower level of financial literacy, according to the dichotomized Big Three criterion, was observed among individuals with ADHD. While the difference between the groups was small, the descriptive results indicate that adequate financial literacy was relatively uncommon among individuals with ADHD, with only about 15% demonstrating adequate levels, compared to roughly 25% in the non-psychiatric group. Although the proportion for both groups is lower than that reported in some previous studies (Swedish Financial Supervisory Authority, 2020), international research has consistently shown that financial literacy among young adults tends to be lower than in the general population (Lusardi & Streeter, 2023). Reports by Cision (2019), suggesting that one in two Swedes perceive themselves as lacking basic financial knowledge, therefore appear reasonable. As noted by Koerts et al. (2023), research on the financial capability, such as financial literacy, of adults with ADHD remains limited. However, their findings indicate differences in financial capability, which is consistent with the results of the present study.

4.2. Research Question 2

The results indicate that consumer loan debt among young adults is associated with financial, psychological, and behavioural factors. For Model 1 financial literacy, financial strain, and financial self-control were significantly associated with consumer loan debt, suggesting that lack of financial literacy, heightened financial strain and low financial self-control are important to the risk of prolonged debt.

Based on the odds ratios, financial literacy was significantly associated with consumer loan debt. This finding highlights the potential role of financial knowledge and decision-making capabilities in shaping financial behaviour and financial outcomes. The result is in line with previous research demonstrating a relationship between financial literacy and financial behaviour (Chu et al., 2017; Robb & Woodyard, 2011; Samuelsson et al., 2023).

Gender was also significantly associated with consumer loan debt, with men showing higher odds despite, on average, reporting higher levels of financial literacy. This gender disparity is consistent with previous research (Demertzis et al., 2024; Levinsson et al., 2026; Lusardi & Streeter, 2023; Samuelsson et al., 2023), and suggests that greater financial knowledge does not necessarily translate into lower levels of borrowing or financial vulnerability.

The finding that financial strain, reflecting the level of psychological stress related to an individual’s financial situation and the amount of time spent worrying about it, was significantly associated with consumer loan debt is plausible, as financial difficulties and the need to access credit may be closely intertwined with financial stress. However, given the cross-sectional design of the study, no conclusions can be drawn regarding the direction or causality of this association. Furthermore, Beauchaine et al. (2020) found an association between persistent economic stress and elevated suicide risk among individuals with ADHD, although their study did not examine consumer loan debt.

ADHD diagnosis was not statistically significantly associated with consumer loan debt. However, the point estimate indicated higher estimated odds of consumer loan debt among participants with ADHD after adjustment for financial strain, financial self-control, financial literacy, gender, and age. This finding may be of interest in light of previous research, although it should be interpreted cautiously given that the confidence interval included the null value and the association did not reach the conventional significance threshold.

The findings reported by Barkley et al. (2006), showing no significant differences between individuals diagnosed with hyperactivity in childhood and controls regarding having had a car loan or other bank loans, is in line with the present findings. Koerts et al. (2023) similarly reported heterogeneous differences in financial competence between adults with and without ADHD, with some basic financial skills showing small or non-significant group differences. However, our findings contrast with those of Stickley et al. (2026), who found a significant association between ADHD symptoms and personal debt, including among adults aged 18–34 years.

Taken together, the findings suggest that financial strain, financial self-control, and financial literacy are important factors in understanding consumer loan debt among young adults. Demographic variables, specifically gender and age, also contributed to the model.

The second outcome, showed that individuals with self-reported ADHD had more than twice the odds of having taken out consumer loans without first investigating or understanding the loan terms compared to respondents reporting no psychiatric diagnosis.

The finding that an ADHD diagnosis was associated with increased odds of having taken consumer loans without investigating or understanding the loan terms is consistent with theories highlighting impulsivity and impaired self-regulation in ADHD, as described in Barkley (1997) and Beauchaine et al. (2017). This includes, for example, executive functioning, information processing, and the capacity for delayed decision-making. In contrast to consumer loan debt, for which no statistically significant association with ADHD was found after adjustment for financial and behavioural factors, ADHD remained associated with insufficient loan scrutiny. This pattern may suggest that ADHD could be relevant to financial decision-making at the point of borrowing, rather than to the long-term accumulation of debt. This is in line with earlier research (Bangma et al., 2019; Beauchaine et al., 2017; Pelham et al., 2020) identifying ADHD as a risk factor for impulsive or spontaneous decision-making styles and related financial behaviours. In addition, difficulties in executive functions, such as planning and organization, may help explain an increased tendency to end up in undesirable situations, including late credit card payments and carrying credit card balances (Beauchaine et al., 2017).

Research by Bangma et al. (2019), which showed that individuals with ADHD have lower financial buffers, provides a possible explanation for why ADHD appears to be associated with increased risk for impulsive consumer loans, as the study identified household finances characterized by more limited economic margins among individuals with this diagnosis. This pattern is also supported by other studies (Barkley et al., 2006; Beauchaine et al., 2017; Pelham et al., 2020). Limited financial buffers may entail an increased need for access to financial resources, such as consumer loans, at short notice.

In addition to ADHD diagnosis, financial literacy and financial self-control were also significantly associated with having taken consumer loans without investigating or understanding the loan terms. The findings that both financial literacy and financial self-control were significantly associated with having consumer loans (Model 1) as well as with having taken loans without investigating or understanding the terms (Model 2) suggest that these factors are associated not only with indebtedness, but also with loan-related decision-making. Low financial literacy, as described by OECD (2019), may limit individuals’ ability to evaluate loan conditions, compare alternatives, and anticipate long-term consequences. Lack of financial self-control may also influence the ability to inhibit taking loans with unfavorable terms. This could increase both the likelihood of entering consumer credit arrangements and the risk of accepting loans without adequately evaluating the terms.

Gender was not significantly associated with the second outcome, indicating that the pattern of men being more likely to have consumer loan debt did not persist when considering whether loans were taken out without evaluating the loan terms. One possible explanation is that men’s higher level of financial literacy may contribute to greater awareness and evaluation of loan terms.

Age was significantly associated with both outcomes. This may partly reflect differences in financial circumstances across early adulthood, including generally lower living costs and shorter periods of financial exposure among younger adults. In addition, accumulating consumer debt may take time, which could contribute to higher levels of consumer loan debt among older participants.

The third outcome, having informal debt to friends or relatives, was closely associated with psychological and behavioural factors. ADHD, financial strain, and financial self-control emerged as associated factors, suggesting that these variables may be linked to relying on informal borrowing from friends or relatives when facing financial difficulties. Individuals reporting an ADHD diagnosis had 81% higher odds of having informal debt compared to respondents reporting no psychiatric diagnosis.

The finding that an ADHD diagnosis was associated with increased odds of having informal debt may suggest that individuals with ADHD, at a group level, are either more likely to receive or to seek financial support from close relations compared to individuals with no psychiatric diagnosis. However, based on the wording of the survey item, it is unclear how respondents interpreted the term “informal debt”, which may range from small, temporary loans to more substantial or long-term financial obligations.

The underlying reasons for borrowing from close relations are also likely to vary considerably. One possible explanation, supported by previous research (Fredriksen et al., 2014; Helgesson et al., 2023; Virtanen et al., 2020), is that individuals with ADHD tend to have lower income levels, higher unemployment rates, and more limited financial buffers (Bangma et al., 2019; Pelham et al., 2020). Impulsivity in financial decision-making, as described by Bangma et al. (2020) and Koerts et al. (2021), may help explain difficulties in saving money to cover monthly expenses and may also result in purchases that are not covered by available financial resources.

Given that the sample in the present study consists of relatively young individuals, it is plausible that a substantial proportion of informal debt reflects borrowing from parents. This is in line with Altszuler et al. (2016), who reported a greater need for financial support among individuals with ADHD, as well as increased financial dependence on family members. The findings are, however, somewhat contrasted by Barkley et al. (2006), who reported that adults who were hyperactive as children did not owe more money to others than control groups.

An ADHD diagnosis may also influence how close relatives (e.g., parents) respond to financial needs, as the condition is associated with reduced quality of life and functional impairment (Pinho et al., 2019; Quintero et al., 2019). This may increase the likelihood that parents or other relatives provide financial support. It may also relate to the fact that adults with ADHD have been shown to engage in more risky financial behaviours, such as unpaid claims, as well as having a higher risk of long-term debt (Beauchaine et al., 2020). Bangma et al. (2019) found that nearly half of their sample with an ADHD diagnosis had loans not related to mortgages or student loans.

The association between financial strain and informal debt may reflect multiple mechanisms: individuals experiencing financial strain may be more likely to seek financial support from close relations, while having informal debt may also contribute to financial stress or anxiety, or both. Lack of financial self-control was associated with informal debt, which may reflect a greater tendency to seek financial assistance from friends or relatives when experiencing financial difficulties. The association may also be related to the relationship between financial self-control and other forms of consumer debt.

A larger proportion of men reported informal debt, which is consistent with previous research indicating that men tend to have higher levels of debt and may engage more actively in financial decision-making.

Financial literacy was not associated with having informal debt, which may suggest that individuals, regardless of their level of financial literacy, may seek or accept financial support from close relations when needed. Nevertheless, as previously shown, financial literacy appeared to function as a protective factor in relation to consumer loan outcomes, including both long-term consumer loan debt and having taken out a loan without understanding or reviewing the terms.

Age was not associated with informal debt, which may reflect the relatively narrow age range of the sample, suggesting that financial difficulties in young adulthood may be related to psychological and financial factors rather than to age per se.

In summary, the study demonstrates significant associations between self-reported ADHD diagnosis and financial vulnerability, although the study design does not allow causal conclusions to be drawn. Difficulties with self-regulation and executive functioning, as well as a tendency to postpone non-preferred activities and to favor immediate rewards over future benefits, have been associated with ADHD and may partly contribute to the financial vulnerabilities observed in this study. However, future research using longitudinal or experimental designs is needed to clarify the direction and potential causal mechanisms underlying these associations, including the role of potential moderating and mediating factors.

4.3. Limitations

The present study has several limitations that should be considered when interpreting the findings. The cross-sectional design prevents us from drawing any conclusions about causal relationships between key variables and the financial outcomes. Although ADHD was included as a variable in the regression models and may be associated with financial hardship, the analyses may reflect underlying vulnerabilities rather than causal effects and do not allow conclusions about whether an ADHD diagnosis in itself causally increases the risk of financial vulnerability.

The data were collected using a web panel. This sampling method may limit the generalizability of the results, as individuals who participate in web panels may differ systematically from the general population in terms of socioeconomic status, digital literacy, or willingness to participate in surveys. Although the distributor aimed to achieve a sample representative of the target population through quota-based selection in terms of gender, age, and geographical region, the risk of selection bias cannot be ruled out. In addition, social desirability bias may have influenced responses, as questions related to mental health and personal finances can be associated with stigma or shame. However, as respondents’ anonymity was guaranteed, this potential bias is likely to have had a limited impact on the results. Participants received a small compensation for completing the survey, which may have influenced participation or response patterns. However, whether the compensation affected responses to potentially sensitive questions is difficult to assess.

Furthermore, ADHD diagnosis and financial variables were self-reported, which may introduce reporting bias or misclassification. While registry-based studies have demonstrated robust associations between ADHD and adverse financial outcomes, self-report designs allow for the assessment of subjective financial vulnerability and related behavioural mechanisms that are not captured in administrative data. An ADHD diagnosis can be established at different ages and stages of life. Consequently, some participants may not yet have received a diagnosis but still exhibit symptoms, while individuals diagnosed at a young age do not necessarily continue to meet the diagnostic criteria later in life. The study did not include participants without an ADHD diagnosis but who experienced ADHD symptoms.

A limitation concerns the measurement of financial self-control. The five items used to construct the measure were not originally developed as a single validated scale, and the internal consistency was modest (Cronbach’s α = 0.71). In addition, one item referred explicitly to purchasing on credit, which may overlap with the consumer loan outcomes examined. When this item was excluded in sensitivity analyses, the internal consistency of the resulting four-item measure was lower (α = 0.63), although the estimated associations remained similar in magnitude across the regression models. However, the association between self-reported ADHD and the outcome in Model 1 reached statistical significance following removal of the credit-related item, whereas it did not reach statistical significance in the primary analysis. This indicates that the statistical significance of this association was sensitive to the operationalization of financial self-control. Thus, although the results were largely comparable across analyses, the measurement of financial self-control remains a limitation.

Some of the analyses examined differences between two groups: participants who reported having an ADHD diagnosis and participants who reported having no psychiatric diagnosis. Consequently, a substantial portion of the total sample was excluded from these analyses in order to focus on a clear group comparison. The purpose of this approach was to compare individuals with ADHD to those reporting better mental well-being in terms of no psychiatric diagnosis. However, other psychiatric conditions present in the sample were not examined in the current study, and it is therefore possible that individuals with such conditions may also experience financial difficulties, although this remains outside the scope of the present analyses.

A limitation regarding the regression analysis in model 2 is the sample size, since those who answered not having consumer loans were excluded from the analysis. However, the sample size remains acceptable (n = 274).

Another limitation concerns the use of researcher-developed, single-item indicators of financial vulnerability. These indicators were not subjected to a formal assessment of content or face validity, and some, particularly informal debt to friends or relatives, may reflect heterogeneous financial circumstances. The consumer loan outcome variable was developed for the present study and was limited to an 18-month (1.5-year) observation window to capture persistent financial difficulties. However, the choice of this time frame may require further reflection. The financial strain variables were measured using two single-item indicators on a five-point Likert scale, capturing perceived stress and worry related to one’s financial situation. Although single-item measures may have limitations in terms of reliability compared to multi-item scales, the items were designed as global assessments. While such measures do not capture distinct dimensions of financial strain, they provide a broad indication of subjective financial stress.

Sensitivity analyses using the continuous Big Three score yielded largely unchanged results for ADHD, whereas associations with financial literacy varied across models. Although the continuous score captures more nuanced variation in financial literacy, the dichotomized measure was used in the main models as the aim was to distinguish young adults who correctly answered all three questions from those who did not, rather than to examine differences across the full score range (0–3). This well-established approach, used in previous studies, is also societally relevant given the generally low levels of financial literacy among young adults, and the importance of identifying those who lack basic financial literacy.

Sensitivity analyses adjusting for completed education and employment status suggested that the associations between self-reported ADHD and financial outcomes were not equally robust to additional adjustment. The associations with prolonged consumer loan debt and self-reported ADHD remained similar in magnitude while the p-value slightly increased. Limited understanding of loan terms were attenuated and no longer statistically significant, whereas the association with informal debt to friends or relatives remained statistically significant. However, educational level was measured as the highest completed level of education and did not capture ongoing education. Consequently, individuals pursuing higher education without having completed a degree may have been classified according to their previously completed education. This measurement limitation should be considered when interpreting the adjusted estimates. Although several theoretically relevant variables were included in the regression models, the analyses did not adjust for potential confounders such as income level and psychiatric comorbidity, which may also contribute to financial vulnerability among young adults with ADHD. Other factors, such as access to financial support from relatives, may likewise influence financial vulnerability.

A further limitation is that the data were collected in October 2021. Given the time since data collection, the findings may not fully reflect current patterns of financial vulnerability among young adults.

Taken together, these limitations highlight the need for caution when interpreting the observed associations between ADHD, financial strain, financial self-control, financial literacy, and financial outcomes, which reflect potential vulnerabilities or heightened risk rather than causal relationships. However, a larger sample may yield additional insights into the relationships between these variables and contribute to the knowledge base within the scope of the present study. The findings should be regarded as hypothesis-generating and serve as a foundation for future research.

4.4. Future Research and Practical Implications

As the current cross-sectional design does not allow for causal inferences, future research would benefit from longitudinal designs that allow for the examination of temporal ordering and potential causal pathways between ADHD and the studied variables. Such approaches could clarify whether ADHD-related traits precede the development of financial difficulties, whether financial health issues exacerbate ADHD-related impairments, or whether the relationship is bidirectional.

Moreover, incorporating objective measures of financial behaviour, such as credit records or repayment histories, and national registry data on mental health would strengthen the validity of the findings and reduce reliance on self-reported data.

In addition, future studies should examine the role of protective factors, such as access to financial education, social or familial financial support, and targeted interventions aimed at improving financial self-control. Understanding how these factors may buffer the impact of ADHD-related vulnerabilities could inform the development of preventive strategies and tailored support for young adults at risk of financial hardship.

Finally, it would be of great value to not just look at self-reported ADHD diagnosis but also consider other forms of mental health problems, as well as to differentiate between individuals with varying levels of ADHD severity and those who suffer from comorbidity. Regarding ADHD symptoms, a measurement such as the Adult ADHD Self-Report Scale could be administered to assess the level of ADHD symptoms and subsequently used as a continuous variable in the analyses.

The findings from the present study indicate that while broader financial difficulties among individuals with ADHD were associated with financial health variables and gender, vulnerabilities in understanding or evaluating loan conditions may represent a more specific area of financial vulnerability associated with ADHD.

In addition, the findings related to informal debt suggest that financial vulnerability may extend beyond formal credit markets and also involve reliance on close social networks. This highlights the importance of considering interpersonal and contextual factors, such as access to family support and informal financial arrangements, when examining financial behaviour among young adults. It also suggests that financial difficulties may have broader social implications, potentially affecting not only individuals but also their close relations.

Even though several organizations, both internationally and in Sweden, provide information indicating that ADHD may negatively affect an individual’s personal finances, more comprehensive and accessible information for the general public remains limited. This lack of accessible information highlights the importance of more systematic efforts to inform both affected individuals and their families, as well as to raise public awareness of the financial challenges associated with ADHD.

A large proportion of Swedish adolescents report feeling uncertain about their financial competence and express a need for more financial education in schools. The differences observed between individuals with ADHD and those without a psychiatric diagnosis in the current study, together with previous research, highlight a gap that may warrant further research into targeted informational resources and interventions aimed at supporting teenagers and young adults. Since individuals with ADHD may experience difficulties with concentration, as well as with processing and retaining verbal information, future research could also explore whether financial education and support delivered in multiple formats may be beneficial.

Considering that an ADHD diagnosis is often established at a young age, future research could investigate whether child and adolescent psychiatric services, primary care, and adult mental health services could provide young individuals and their families with access to relevant financial information and practical tools to support financial decision-making and long-term financial well-being.

4.5. Conclusions

The current study suggests that individuals with self-reported ADHD experience greater financial strain, including a more psychologically distressing financial situation and more time spent worrying about their finances compared to respondents reporting no psychiatric diagnosis. Only about 15% were classified as financially literate according to the Big Three criterion, compared with roughly 25% in the non-psychiatric group. Financial literacy emerged as a key variable associated with consumer loan debt. ADHD was not significantly associated with consumer loan debt, but was associated with taking consumer loans without fully understanding or reviewing the loan terms and with informal debt. The odds of taking consumer loans without fully understanding or reviewing the terms were 2.4 times higher, while the odds of informal debt were 81% higher among participants with self-reported ADHD. Given the cross-sectional design, longitudinal studies are needed to clarify temporal and causal relationships.