Instruments for measuring financial well-being among Veterans: A systematic review

Abstract

Introduction:

Financial health is one of seven aspects that have been identified to appraise the well-being of Veterans. The authors conducted a systematic review to identify instruments that measure financial well-being.

Methods:

The authors searched the MEDLINE, EMBASE, PsycINFO, AgeLine, PTSD Pubs, Sociological Abstracts, and Social Sciences Abstracts databases from inception to April 13, 2023, for development or validation studies reporting on financial well-being instruments. The consensus-based standards for the selection of health measurement instruments (COSMIN) were used to assess risk of bias and measurement properties of eligible studies. Three Canadian Veteran partners independently reviewed and assessed the clarity and applicability of all identified tools.

Results:

Thirteen instruments that assessed financial well-being were identified. Of these instruments, five (38%) demonstrated sufficient structural validity, 12 (92%) internal consistency, three (23%) cross-cultural validity, one (8%) test-retest reliability, and 10 (77%) construct validity. Veteran partners identified four instruments as very clear and very applicable to Veterans: Well-Being Inventory (WBI), Economic Quality of Life Measure (Econ-QOL), Personal Financial Wellness Scale (PFWS), and Living Standards Capabilities for Elders Scale (LSCAPE). The WBI was developed and validated with a Veteran sample. The Econ-QOL was developed with a general sample and validated among Veterans.

Discussion:

Among the four instruments reporting strong psychometric properties and endorsed by the study’s Veteran partners, only the WBI was both developed and validated with a U.S. Veteran population, whereas the Econ-QOL was only validated with that population. The PFWS and LSCAPE appear promising but require validation among Veterans.

Lay Summary

Financial health contributes to Veterans’ well-being. The authors systematically searched the literature to identify tools that measure financial well-being, assessed their quality, and asked three Veteran partners to review their clarity and applicability. This search identified 13 instruments that measure financial well-being, among which the Well-Being Inventory (WBI), Economic Quality of Life Measure (Econ-QOL), Personal Financial Wellness Scale, and Living Standards Capabilities for Elders Scale demonstrated good properties; only the WBI and Econ-QOL have been tested with Veterans. These instruments may be helpful to gauge the financial well-being of Veterans and determine the impact of policies aimed at supporting financial well-being.

Introduction

In May 2021, an estimated 461,240 Veterans were living in Canada.¹ Transitioning from military to civilian life can be challenging, affecting many domains, including financial well-being.² Compared with the general population, Veterans are more likely to experience posttraumatic stress disorder (PTSD), major depressive disorder, chronic pain, and traumatic brain injury.^3–5 These conditions may lead to disability and associated unemployment, resulting in less income and potential debt.^6,7 Also, Veterans may face difficulties in securing jobs after deployment, which may in turn affect financial security and well-being.^8,9

The Research and Policy Directorates of Veterans Affairs Canada have explored the concept of well-being among Veterans and identified seven key domains:^10,11 1) employment or other meaningful activity, 2) finances, 3) health, 4) life skills and preparedness, 5) social integration, 6) housing and physical environment, and 7) cultural and social environment.¹⁰ The framework for financial well-being is defined by household income and financial security, as monitored through income level and financial satisfaction.^10,12 Although various systems have been implemented to facilitate the transition to civilian life, including interventions to reduce financial burden, no systematic efforts are in place to measure financial well-being among Veterans.^10,13 Thus, the authors conducted a systematic review to identify and describe instruments that measure financial well-being among outpatient populations.

Methods

The authors followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) checklist and registered the protocol on the Open Science Framework (https://doi.org/10.17605/OSF.IO/DS3J2).^14,15 The systematic review adhered to the guidelines outlined in the consensus-based standards for the selection of health measurement instruments (COSMIN) for systematic evaluations of patient-reported outcome measures.¹⁶

After registration the authors made one amendment to the protocol and incorporated a manual search of the grey literature via Google Scholar.

Data sources and searches

An experienced medical librarian (RJC) conducted a systematic search of the MEDLINE, EMBASE, PsycINFO, AgeLine, PTSD Pubs, Sociological Abstracts, and Social Sciences Abstracts databases from inception through April 13, 2023 (Supplementary Table 1). This search included both MeSH terms and key words related to measurement tools, finance, and financial well-being and was limited to adults and English-language studies. The authors screened the reference lists of all included studies for additional eligible articles. Also, after identifying all instruments from eligible studies, the authors conducted a grey literature search in Google Scholar using the following terms: [name of the instrument] AND (valid OR validity OR psychometric).

Eligibility criteria

The authors included development or validation studies of instruments measuring financial well-being among community-based adults (aged 18 y and older), including Veterans. For this article, finances are defined as household income and financial security. Instruments measuring financial well-being may include both subjective and objective descriptors (indicators).¹⁰ The authors included instruments that directly measure financial well-being (unidimensional instruments) and general instruments that have a distinct section or construct for financial well-being that can be used separately. The authors excluded studies that reported on a specific population (e.g., specific condition or diagnosis) that was not representative of the general population.

Study selection

Three teams of two reviewers (KT, HNC, DA, GBS, SMA, JX) underwent training and calibration exercises using standardized and pilot-tested forms entered into Distiller SR, an online systematic review software.¹⁷ After calibration, the reviewers screened, independently and in duplicate, the titles and abstracts of all identified citations and subsequently assessed all eligible full texts. The reviewers achieved consensus through discussion, and a third senior reviewer (MK, AJD) resolved disagreements when required.

Data extraction

After conducting calibration exercises, teams of two reviewers extracted data independently and in duplicate from all eligible studies using a pilot-tested data extraction form. Reviewers consulted with a third senior reviewer (MK or AJD) to resolve disagreements. Reviewers extracted data on 1) type of study (i.e., development, validation, or impact), 2) study design (i.e., cross-sectional, longitudinal), 3) population (i.e., non-Veteran or Veteran community sample or mixed), 4) demographics (i.e., age, sex, socio-economic status), 5) participants’ country or countries of residence, and 6) instrument characteristics (e.g., reliability, validity, number of items, cost).

The authors engaged three Canadian Veteran partners to independently assess the clarity and applicability to Veterans of all identified instruments. Specifically, they were asked to appraise each instrument using five-point Likert scales for clarity (1 = very clear, 2 = somewhat clear, 3 = uncertain, 4 = somewhat unclear, 5 = very unclear) and applicability (1 = very applicable, 2 = somewhat applicable, 3 = unsure, 4 = somewhat inapplicable, 5 = very inapplicable). The authors provided the Veterans with the following definitions of clarity and applicability to assist them in their assessment. Clarity of an instrument refers to how easy it was for the Veteran partners to understand the content; applicability of an instrument refers to the degree to which the Veteran partners felt the tool was relevant, comprehensive, and appropriate for the Veteran population. The Veterans were given the opportunity to include additional comments or justifications. The final rating of the instruments was dependent on the lowest rating given by the Veterans using the worse-score counts process.

Risk-of-bias assessment

Teams of reviewers assessed, independently and in duplicate, the risk of bias of eligible studies using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) tool.¹⁸ COSMIN is used to assess the methodological quality of studies on the basis of 10 criteria: 1) development, 2) content validity, 3) structural validity, 4) internal consistency, 5) cross-cultural validity or measurement invariance, 6) reliability, 7) measurement error, 8) criterion validity, 9) construct validity, and 10) responsiveness.¹⁸ First, the authors selected the measurement properties that were evaluated in the included studies, and those factors were then assessed for risk of bias following COSMIN guidance. Risk of bias for each study was rated as very good (i.e., low risk), adequate, doubtful, or inadequate (i.e., high risk), depending on the lowest-rated item for each criterion. Reviewers resolved all disagreements through discussion.

Data synthesis and presentation of findings

The authors conducted a narrative synthesis of the included studies and summarised their findings. Dichotomous and categorical variables are presented as counts and proportions and continuous data as median, interquartile range (IQR), and ranges. The authors described the identified instruments that measure financial well-being or aspects of it, their performance (and psychometric properties, when available), and gaps in their development or validation. The authors compared each instrument’s measurement properties against the COSMIN criteria for good measurement properties and rated every instrument as having sufficient, insufficient, or indeterminate evidence.¹⁶

Results

Figure 1 shows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram.¹⁴ The authors’ search identified 22,460 unique citations, of which 17 English-language studies were eligible. These 17 studies reported on 20,044 participants and 13 instruments measuring aspects of financial well-being.

Figure 1.

Preferred Reporting Items for Systematic reviews and Meta-Analyses flow chart

Characteristics of included studies

Among the 17 studies, 14 (82%) were cross-sectional in design,^19–32 whereas 3 (18%) incorporated a mixed study design including cross-sectional and longitudinal assessment.^33–35 Eight studies (47%) were development and internal validation studies,^{20,21,23,25,27,29,32,34} 2 were (12%) development and external validation studies,^33,35 and 7 (41%) were external validation studies.^{19,22,24,26,28,30,31} All studies drew samples from the general population, with 2 (12%) including Veterans and 1 (6%) focusing exclusively on women.^19,21,35 Among the 17 studies, 4 (24%) were identified through a search of Google Scholar (Supplementary Table 2).^24,25,28,29 Table 1 describes detailed characteristics of the included studies. Excluded studies with justifications are presented in Supplementary Table 3.

Table 1.

Characteristics of the included studies (N = 17)

Study	Risk of bias*	Instrument	Study type (design)	Country	Population and N	Mean age (SD), y	% Female
Ksendzova et al.33	Adequate	Brief Money Management Scale	Study 1: development (cross-sectional) Studies 2a and 3: external validation (cross-sectional) Study 2b: external validation (longitudinal)	United States	General population (N = 1,473) Study 1: n = 1,078 Study 2a: = 154 Study 2b: = 80 Study 3: = 161	Study 1: 33.48 (14.12) Study 2a: 35.32 (15.20) Study 2b: 37.51 (12.14) Study 3: 24.59 (4.87)	Study 1: 73% Study 2a: 51% Study 2b: 42% Study 3: 51%
Carlozzi et al.19	Very good	Economic Quality of Life Measure	External validation (cross-sectional)	United States	General population (N = 213 Veteran (n = 163)	48 (14.5)	84%
Spinella et al.20	Doubtful	Executive Personal Finance Scale	Development and internal validation (cross-sectional)	United States	General population (N = 225)	26.2 (10.3)	63%
Nguyen21	Adequate	Women’s Financial Self-Efficacy Scale†	Development and internal validation (cross-sectional)	United States	General population (N = 299)	NR (NR)	100%
Marjanovic et al.22	Doubtful	Financial Threat Scale	External validation (cross-sectional)	Belgium, Germany, Portugal, Spain	General population (N = 806)	Belgium: 41.05 (13.29) Germany: 37.60 (10.31) Portugal: 39.10 (11.18) Spain: 43.78 (9.34)	56%
Prawitz et al.23	Adequate	Personal Financial Wellness Scale‡	Development and internal validation (cross-sectional)	United States	General population (N = 1,097)	NR	NR
Buabang et al.24	Very good	Personal Financial Wellness Scale	External validation (cross-sectional)	Germany, Italy, Netherlands, Slovenia, Spain, United Kingdom, United States	General population (N = 1,550)	NR	55%
Lichtenberg et al.25	Doubtful	Lichtenberg Financial Decision Rating Scale	Development and internal validation (cross-sectional)	United States	General population (N = 109)	75.3 (10.7)	58%
Lichtenberg et al.26	Very good	Lichtenberg Financial Decision Rating Scale	External validation (cross-sectional)	United States	General population (N = 69)	69.59 (5.99)	90%
Udayar et al.27	Adequate	LIVES Daily Hassles Scale	Development and internal validation (cross-sectional)	Switzerland	General population (N = 1,170)	47.92 (8.31)	52%
Liu et al.28	Adequate	LIVES Daily Hassles Scale	External validation (cross-sectional)	China	General population (N = 815)	35.23 (9.83)	47%
Mattes29	Inadequate	Lived Poverty Index	Development and internal validation (cross-sectional)	18 countries in East, West, and South Africa§	General population (NR)	NR	NR
Meyer & Keyser30	Adequate	Lived Poverty Index	External validation (cross-sectional)	South Africa	General population (NR)	NR	NR
Alhambra-Borrás et al.31	Very good	Living Standards Capabilities for Elders Scale	External validation (cross-sectional)	Spain	General population (N = 441)	77 (NR)	62%
Loix et al.34	Doubtful	Orientation Toward Finances Scale	Development and internal validation (cross-sectional and longitudinal)	Belgium	General population (N = 1,007)	29.9 (NR)	47%
Tang32	Inadequate	Short Money Ethic Scale	Development and internal validation (cross-sectional)	United States	General population (N = 740)	27.85 (10.03)	NR
Vogt et al.35	Very good	Well-Being Inventory	Study 1: development (cross-sectional) Study 2: external validation (longitudinal)	United States	Development sample Time point 1: Veterans (n = 301) Time point 2:¶ Veterans (n = 286) Validation sample Time point 1: Veterans (n = 9,566) Time point 2:¶ Veterans (n = 7,342)	Development sample Time point 1: 44.66 (13.28) Time point 2:¶ NR Validation sample Time point 1: 34.47 (9.55) Time point 2:¶ NR	Development sample Time point 1: 26% Time point 2:¶ NR Validation sample Time point 1: 18% Time point 2: NR

*This column presents each study’s overall risk of bias. Refer to Supplementary Table 4 for a detailed breakdown of the risk-of-bias assessments across each COSMIN measurement property.

^†The Women’s Financial Self-Efficacy Scale was initially named Financial Self-Efficacy in the dissertation written by Nguyen in 2016 and was then renamed in a proceeding publication by Nguyen in 2019.^21,36

^‡The instrument developed by Prawitz and colleagues in 2006 was initially named InCharge Financial Distress/Financial Well-Being Scale but later renamed the Personal Financial Wellness Scale.^23,24

^§Benin, Botswana, Cape Verde, Ghana, Kenya, Lesotho, Madagascar, Malawi, Mali, Mozambique, Namibia, Nigeria, Senegal, South Africa, Tanzania, Uganda, Zambia, and Zimbabwe.

^¶The second time point for the validation sample took place approximately six months after the first time point.

COSMIN = consensus-based standards for the selection of health measurement instruments; NR = not reported.

Risk of bias

Among the 17 included studies, risk of bias was found to be very good (i.e., low risk) for 5 studies (30%),^{19,24,26,31,35} adequate for 6 (35%),^{21,23,27,28,30,33} doubtful for 4 (24%),^20,22,25,34 and inadequate (i.e., high risk) for 2 (12%)^29,32 (Supplementary Table 4).

Financial well-being instruments

Of 13 instruments related to the measurement of financial well-being, the median number of items was 15 (IQR 8–21), and the number of items ranged from 5 (Financial Threat Scale [FTS]) to 77 (Lichtenberg Financial Decision Rating Scale [LFDRS]). Only the Well-Being Inventory (WBI) was both developed and validated with a U.S. Veteran population; the development sample consisted of 301 Veterans, and the external validation sample consisted of 9,566 Veterans. The only other tool for which the Veteran population was considered was the Economic Quality of Life Measure (Econ-QOL), which was validated with a population of 376 that included 163 (43%) Veterans. All instruments are free for use; 12 (92%) are available online and 1 (8%) is free for use with permission from the authors (Table 2).

Table 2.

Characteristics of the included instruments (n = 13)

Instrument	Objective and brief overview of instrument	No. of items	Accessibility
Brief Money Management Scale (BMMS)33	The BMMS assesses individuals’ financial behaviour across four domains: 1) cash, 2) credit, 3) savings, and 4) insurance management. The tool is structured to assess people’s money management practices.	18	Free; Table 333
Economic Quality of Life Measure (Econ-QOL)19	The Econ-QOL assesses how economic variables influence health-related quality of life and community engagement among individuals with disabilities, who often face heightened financial challenges and reduced community involvement due to their conditions.	8	Free; Appendix 119
Executive Personal Finance Scale (EPFS)20	The EPFS assesses executive functions related to personal finance management, by evaluating the following four domains: 1) impulse control, 2) organization, 3) planning, and 4) motivational drive.	20	Free; Table 120
Women’s Financial Self-Efficacy Scale21 (WFSES; previously named the Financial Self-Efficacy Scale)37	The WFSES assesses women’s confidence in managing personal finances, covering the following domains: 1) cash flow, 2) debt management, 3) credit repair, 4) financial goal setting, 5) saving, 6) investing, 7) taxation, and 8) financial protection. It aims to evaluate both internal capacities and external conditions that influence financial self-sufficiency.	21	Free; Table 421
Financial Threat Scale (FTS)22	The FTS assesses levels of fear, uncertainty, and preoccupation concerning the stability and security of one’s finances, particularly in the context of economic recessions and personal financial situations.	5	Free; Appendix22
Personal Financial Wellness Scale24 (PFWS; previously named the InCharge Financial Distress/Financial Well-Being Scale)23	The PFWS assesses levels of stress and well-being stemming from one’s financial situation. It captures a spectrum from high financial distress to high financial well-being, reflecting one’s emotional and practical reactions to one’s financial situation.	8	Free; Appendix23
Lichtenberg Financial Decision Rating Scale (LFDRS)25,26	The LFDRS assesses the particular financial choices an older adult is making or has made and evaluates whether they possess the necessary decision-making abilities. The scale measures the following domains: 1) financial situational awareness, 2) psychological vulnerability, 3) undue influence, 4) past financial exploitation, and 5) intellectual factors.	77	Free on request (p.lichtenberg@wayne.edu)
LIVES Daily Hassles Scale (LIVES-DHS)27,28	The LIVES-DHS assesses daily hassles across five domains: 1) financial, 2) physical, 3) relational, 4) environmental, and 5) professional. The scale focuses on measuring individual concerns about these daily hassles and how they are perceived as preoccupations by the respondents.	18	Free; Table 127
Lived Poverty Index (LPI)29,30	The LPI assesses the provision of an individual’s basic necessities, focusing on the following core essentials: 1) housing, 2) food, 3) water, 4) work, 5) income, 6) clothes, 7) education, 8) health care, 9) electricity, and 10) safety and security.	9	Free; Table 330
Living Standards Capabilities for Elders Scale (LSCAPE)31	The LSCAPE assesses living standards of older adults across 6 domains: 1) health, 2) social integration, 3) contribution, 4) enjoyment, 5) security, and 6) restriction.	25	Free; Table 131
Orientation Toward Finances Scale (ORTOFIN)34	The ORTOFIN assesses individual behavioural dispositions related to personal financial management. This scale consists of two domains, 1) financial information and 2) personal financial planning, and evaluates how individuals handle their financial resources, including aspects such as actively seeking financial knowledge and systematically planning personal expenses.	8	Free; Table 634
Short Money Ethic Scale (Short MES)32	The Short MES assesses people’s attitude toward money, focusing on three domains: 1) success, 2) budget, and 3) evil.	12	Free; Table 232
Well-Being Inventory (WBI)35	The WBI assesses 3 dimensions of well-being — 1) status, 2) functioning, and 3) satisfaction — across 4 domains; 1) vocation (work, education), 2) finances, 3) health, and 4) social relationship (intimate, parenting, and broader social relationship).*	Full inventory: 126 Finance related: 24	Free; Appendix A35

Note: The domains listed under the instrument descriptions are arranged in the same order as presented in the studies.

*The WBI uses a multidimensional scoring system that generates 30 unique measures, which can be applied individually or in combination. For this review, the authors focus solely on the financial-related measures of the WBI, which are financial status, financial functioning, and financial satisfaction.

Of the 13 identified instruments, 10 (77%)^{20–23,25,27,29,32,33,35} were evaluated for structural validity, of which 5 (50%)^{22,23,25,27,35} demonstrated sufficient properties based on the threshold of comparative fit index > 0.95 under classical test theory.¹⁶ Twelve instruments (92%)^{19–21,23,25,27,29,31–35} were assessed for internal consistency, and all demonstrated sufficient properties based on the set threshold of Cronbach’s α ≥ 0.70.¹⁶ Three instruments (23%)^22,23,27 were tested and found to be sufficient for cross-cultural validity or measurement invariance, because no important differences were detected on the basis of group factors such as age and sex in different countries of administration.¹⁶

Test-retest reliability was evaluated for 3 instruments (23%),^25,33,34 of which only 1 (33%)³³ demonstrated sufficient properties based on the set threshold of test-retest reliability ≥ 0.80.¹⁶ As for criterion validity, 5 instruments (38%)^{20,21,23,25,31} were assessed; however, none met the correlation threshold of ≥ 0.70 when compared with a gold-standard tool.¹⁶ In terms of hypothesis testing for construct validity, 10 instruments (77%)^{19,20,22,23,27,31–35} were assessed, and their results were in accordance with their hypothesis.¹⁶ None of the instruments reported measurement error or responsiveness (Table 3, Supplementary Table 5).

Table 3.

Psychometric properties of the financial well-being instruments and mini assessment by Veteran partners (n = 13)

Instrument	Overall clarity assessment*	Overall applicability assessment*	Cronbach’s 〈	Test-retest reliability	Validity
Brief Money Management Scale (BMMS)33	Somewhat clear	Somewhat applicable	0.84	0.81†	Convergent validity Savings management with savings (r = 0.49). Credit management with credit card debt (r = −2.39). Insurance/investment management with investments (r = 0.47). Exploratory factor analysis Items retained exhibited loadings > 0.6. Sufficient construct validity, internal consistency, and test-retest reliability due to the convergent validity, Cronbach’s α, and test-retest reliability results, respectively. Indeterminate structural validity, because COSMIN only provides criteria of good measurement property for confirmatory factor analysis under classical test theory. Measurement error, criterion validity, responsiveness, and cross-cultural validity or measurement invariance were not reported.
Economic Quality of Life Measure (Econ-QOL)19	Very clear	Very applicable	0.93	NR	Convergent Validity Econ-QOL with Income: Combined sample (r = 0.48) Caregivers of civilians (r = 0.56) Caregivers of service members and Veterans (r = 0.47) Discriminant Validity Econ-QOL with caregiver strain Combined sample (r = −0.26) Caregivers of civilians (r = −0.23) Caregivers of service members and Veterans (r = −0.23) Discriminant Validity Econ-QOL with caregiver-specific anxiety Combined sample (r = −0.30) Caregivers of civilians (r = −0.24) Caregivers of service members or Veterans (r = −0.34) Discriminant Validity Econ-QOL with caregiver positive affect and well-being Combined sample (r = 0.35) Caregivers of civilians (r = 0.33) Caregivers of service members and Veterans (r = 0.36). Discriminant Validity Econ-QOL with caregiver sleep-related impairment Combined sample (r = −0.31) Caregivers of civilians (r = −0.26) Caregivers of service members and Veterans (r = −0.35). Sufficient construct validity based on the convergent and discriminant validity results. Sufficient internal consistency based on the Cronbach’s α result. Structural validity, cross-cultural validity or measurement invariance, test-retest reliability, measurement error, criterion validity, and responsiveness were not reported.
Executive Personal Finance Scale (EPFS)20	Uncertain	Unsure	0.86	NR	Convergent validity EPFS with current credit card debt (r = −0.21) EPFS with maximum credit card debt (r = −0.24) EPFS with debt-to-income ratio (r = −0.25) EPFS with savings (r = 0.23) Criterion validity EPFS with CBS (r = 0.60) EPFS with MAS, retention time (r = 0.54) EPFS with MAS distrust (r = −0.07) EPFS with MAS power-prestige (r = −0.16) EPFS with MAS anxiety (r = −0.29) Exploratory factor analysis Items retained exhibited loadings ranging from 0.54 to 0.89. Sufficient construct validity based on the convergent validity results. Sufficient internal consistency based on the Cronbach’s α result. Indeterminate structural validity, because COSMIN only provides criteria of good measurement property for confirmatory factor analysis under classical test theory. Insufficient criterion validity due to correlation with CBS or MAS < 0.7. Cross-cultural validity or measurement invariance, test-retest reliability, measurement error, and responsiveness were not reported.
Women’s Financial Self-Efficacy Scale (WFSES)21	Very clear	Somewhat inapplicable	0.93	NR	Criterion validity WFSES with NGSES (r = 0.43) Confirmatory factor analysis Items retained exhibited loadings > 0.5, ranging from 0.586 to 0.971. Sufficient internal consistency based on the Cronbach’s α result. Indeterminant structural validity since the comparative fit index, the Tucker-Lewis Index, or another comparable measure was not reported for the confirmatory factor analysis. Insufficient criterion validity due to correlation with NGSES < 0.7. Cross-cultural or measurement invariance, test-retest reliability, measurement error, hypothesis testing for construct validity, and responsiveness were not reported.
Financial Threat Scale (FTS)22	Very clear	Very inapplicable	NR	NR	Convergent validity FTS with psychological distress (r = 0.38), depression (r = 0.36), anxiety (r = 0.34), and mood disturbance as related to one’s current financial situation (r = 0.65). Financial threat among individuals who reported low financial well-being (r = 0.54), worsening income change over the past few years (r = 0.48), and high economic hardship (r = 0.44). Confirmatory factor analysis Comparative fit index > 0.9 in all 4 countries (Belgium, Germany, Portugal, and Spain) Cross-cultural validity Across Belgium, Germany, Portugal, and Spain, the correlation between age and the FTS is negligible to weak, with Belgium showing a slight negative correlation (r = −0.15). For sex, the correlations range from −0.08 in Portugal to 0.08 in Spain. Sufficient structural validity, hypothesis testing for construct validity, and cross-cultural validity due to the high comparative fit index, the convergent validity results, and no important difference found between age and sex across all 4 countries, respectively. Internal consistency, test-retest reliability, measurement error, criterion validity, and responsiveness were not reported.
Personal Financial Wellness Scale (PFWS)23,24	Very clear	Very applicable	0.95623	NR	Criterion validity‡24 Correlation between PFWS and PSS (Perceived Stress Scale) in United States (r = 0.61), Spain (r = 0.51), Germany (r = 0.52), Slovenia (r = 0.52), United Kingdom (r = 0.47), Netherlands (r = 0.43), and Italy (r = 0.38). Discriminant validity24 Correlation between PFW and TIMI: Conscientiousness — in Germany (r = 0.46), United Kingdom (r = 0.35), Netherlands (r = 0.15), United States (r = 0.28), Slovenia (r= 0.16), Spain (r = 0.07), and Italy (r = 0.03). Neuroticism — in Netherlands (r = 0.36), United States (r = 0.38), Germany (r = 0.33), Slovenia (r = 0.28), Italy (r = 0.21), United Kingdom (r = 0.29), and Spain (r = 0.21). Agreeableness, Openness, and Extraversion — in Germany (r = 0.20). Exploratory factor analysis23 Items retained exhibited loadings ranging from 0.833 to 0.926. Confirmatory factor analysis24 Comparative Fit Index > 0.95 in Germany, > 0.92 in Italy, Netherlands, and Slovenia, and > 0.89 in Spain and the United Kingdom. Measurement invariance24 Metric invariance across the 7 countries (Germany, Italy, the Netherlands, Slovenia, Spain, United Kingdom, and United States): Δ comparative fit index = 0.00 Sufficient structural validity, internal consistency, cross-cultural or measurement invariance, and hypothesis testing for construct validity due to the high Comparative Fit Index, Cronbach’s α, no important differences for the Comparative Fit Index across the 7 countries, and the discriminant validity results, respectively. Insufficient criterion validity due to correlation with PSS < 0.7. Test-retest reliability, measurement error, and responsiveness were not reported.
Lichtenberg Financial Decision Rating Scale (LFDRS)25,26	Somewhat unclear	Somewhat inapplicable	0.95826	NR	Inter-rater judgement agreement among 10 experts using LFDRS25 Case studies 1–3: 100% agreement Case Study 4: 80% agreement Case study 5: 90% agreement Criterion Validity26 LFDRS decisional ability with MMSE score (r = 0.327) LFDRS decisional ability with ILS Managing Money score (r = 0.254) Sufficient internal consistency due to the Cronbach’s α result. Indeterminate test-retest reliability because neither interclass correlation coefficient nor weighted kappa was reported. Insufficient criterion validity due to correlation with MMSE or ILS < 0.7. Structural validity, cross-cultural validity or measurement invariance, measurement error, hypothesis testing for construct validity, and responsiveness were not reported.
LIVES Daily Hassles Scale (LIVES-DHS)27,28	Very clear	Somewhat inapplicable	0.9228	NR	Convergent validity27 Financial Hassles with income adequacy (r = −0.56), the Physical Hassles with self-rated health (r = −0.36), the Relational Hassles with social support (r = −0.37), and the Professional Hassles with job insecurity (r = 0.41). Confirmatory factor analysis27 Comparative fit index = 0.941 Measurement Invariance28 Metric Invariance — Age: Δ comparative fit index = −0.003 Metric invariance — Gender: Δ comparative fit index = −0.003 Sufficient structural validity, internal consistency, cross-cultural or measurement invariance, and hypothesis testing for construct validity, due to the high comparative fit index, Cronbach’s 〈 result, no important differences for the comparative fit index across age and gender, and the convergent validity results, respectively. Test-retest reliability, measurement error, criterion validity, and responsiveness were not reported.
Lived Poverty Index (LPI)29,30	Very clear	Somewhat inapplicable	0.71–0.7730	NR	Exploratory Factor Analysis29 Items retained exhibited loadings ranging from 0.57–0.74. Sufficient internal consistency due to the Cronbach’s α result. Indeterminant structural validity, because COSMIN only provides criteria of good measurement property for confirmatory factor analysis under classical test theory. Cross-cultural validity or measurement invariance, test-retest reliability, measurement error, criterion validity, hypothesis testing for construct validity and responsiveness were not reported.
Living Standards Capabilities for Elders Scale (LSCAPE)31	Very clear	Very applicable	0.96	NR	Confirmatory factor analysis Comparative fit index and Tucker-Lewis index > 0.9. Criterion validity LSCAPE with SF-12 physical health (r = 0.622). LSCAPE with SF-12 mental health (r = 0.636). Convergent validity Average variance extracted for the 6 factors of LSCAPE > 0.5. LSCAPE with monthly personal income (r = 0.304). Sufficient structural validity, internal consistency, and hypothesis testing for construct validity, due to the high comparative fit index and Tucker-Lewis index, high Cronbach’s α, and convergent validity results. Insufficient criterion validity due to correlation with SF-12 physical and mental health < 0.7. Cross-cultural or measurement invariance, test-retest reliability, measurement error and responsivity were not reported.
Orientation Toward Finances Scale (ORTOFIN)34	Somewhat clear	Somewhat inapplicable	0.744	0.59†	Convergent validity ORTOFIN with financial information (r = 0.840), personal financial planning (r = 0.642), financial experience index (r = 0.445), number of debit cards (r = 0.098), frequency of using debit cards (r = 0.108), number of credit cards (r = 0.166), frequency of using credit cards (r = 0.152), knowing the amount in deposit account (r = 0.270), number of savings accounts (r = 0.172), knowing the amount in savings accounts (r = 0.281), investments other than savings accounts (r = 0.288), money attitudes (obsession) (r = 0.390), money attitudes (power) (r = 0.264), money attitudes (budget) (r = 0.232), money attitudes (achievement) (r = 0.286), money attitudes (evaluation) (r = 0.054), and money attitudes (anxiety) (r = 0.190). Sufficient internal consistency and construct validity due to the high Cronbach’s α and the convergent validity results. Insufficient test-retest reliability due to the low test-retest reliability. Structural validity, cross-cultural or measurement invariance, measurement error, criterion validity, and responsiveness were not reported.
Short Money Ethic Scale (MES)32	Somewhat clear	Somewhat inapplicable	0.7	NR	Convergent validity Short MES with Factors Success (r = 0.90), Budget (r = 0.39), and Evil (r = −0.39). Short MES with work satisfaction (r = −0.06), pay satisfaction (r = −0.11), promotions satisfaction (r = 0.05), supervision (r = 0.04), and co-workers (r = −0.06). Exploratory factor analysis Items retained exhibited loadings > 0.45. Sufficient internal consistency and hypothesis testing for construct validity due to the high Cronbach’s α and the convergent validity results. Indeterminant structural validity, because COSMIN only provides criteria of good measurement property for confirmatory factor analysis under classical test theory. Cross-cultural validity or measurement invariance, test-retest reliability, measurement error, criterion validity, and responsiveness were not reported.
Well-Being Inventory (WBI)35	Very clear	Very applicable	0.86	NR	Confirmatory factor analysis Comparative fit index (16-factor corrected model) = 0.905 Convergent and discriminant validity Functioning and satisfaction scales showed higher within-content area correlations (average rs = 0.61 and 0.63) compared to across-content areas (average rs = 0.34 and 0.37). The scales were not highly associated, indicating no concerning conceptual overlap. Discriminative validity At the second timepoint, those with probable mental health conditions showed significantly lower functioning and satisfaction across all domains compared with those without conditions. Sufficient structural validity, internal consistency, and hypothesis testing for construct validity due to the high comparative fit index, Cronbach’s α, and the convergent, discriminant, and discriminative validity results. Content validity, cross-cultural validity, test-retest reliability, measurement error, criterion validity, and responsiveness were not reported.

COSMIN = consensus-based standards for the selection of health measurement instruments; NR = not reported; CBS = Compulsive Buying Scale; MAS = Money Attitude Scale; NGSES = General Self-Efficacy Scale; PSS = Perceived Stress Scale; PFW = perceived financial wellness; TIMI = Ten Item Personality Inventory; MMSE = Mini-Mental State Examination; ILS = Independent Living Scale; SF-12 = Short-Form 12.

Note: The psychometric properties of the instruments stated in this table were evaluated based on the criteria set by COSMIN for good measurement properties, and were rated as being sufficient, indeterminate, or insufficient. Refer to Supplementary Table 5 for a detailed description of the evaluation of these measurement properties in a table format.

*The clarity and applicability of each instrument was rated independently by the three Veteran partners. The overall rating shown here is calculated based on the worse score count method. Refer to Supplementary Table 6 for a more comprehensive view of the ratings by each of the Veterans.

^†The test-retest reliability for both BMMS and ORTOFIN was measured at a two-week interval.

^‡No global correlations were present for the validity data of the PFWS. Correlations were divided by country.

In terms of assessments from the Veteran partners, the WBI,³⁵ Econ-QOL,¹⁹ Personal Financial Wellness Scale (PFWS),^23,24 and Living Standards Capabilities for Elders Scale (LSCAPE)³¹ were considered very clear and very applicable to Veterans; the Brief Money Management Scale was rated as somewhat clear and somewhat applicable.³³ The Women’s Financial Self-Efficacy Scale,²¹ FTS,²² LIVES Daily Hassles Scale,^27,28 and Lived Poverty Index^29,30 were found to be very clear; however, in terms of applicability to Veterans, they were rated as somewhat inapplicable or very inapplicable. The remaining four instruments were considered unclear, inapplicable, or both (Supplementary Table 6).^{20,25,26,32,34} Refer to Supplementary Table 7 for the Veterans’ comments justifying their clarity and applicability ratings.

On the basis of the tools’ psychometric properties and the assessments of the Veteran partners, the four most promising tools were the WBI,³⁵ Econ-QOL,¹⁹ PFWS,^23,24 and LSCAPE.³¹ The WBI includes 24 items assessing financial well-being with the following dimensions: status, functioning, and satisfaction (Table 2). It demonstrated sufficient structural validity, internal consistency, and hypothesis testing for construct validity (Table 3), and the development and external validation study scored very good for risk of bias.³⁵ The Veteran partners had the following to say about the WBI instrument:

It’s the clearest tool we’ve been presented with, taking into account not only a person’s financial situation, but also habits and behaviours that are either in conflict with or conducive to good financial health.

This tool is highly applicable to Veterans. Financial habits are often a problem for Veterans. I’ve often seen Veterans in good financial health, but with risky habits/behaviours, and I think this tool helps shed light on that aspect.

The Econ-QOL includes eight items and was developed to evaluate how economic variables influence health-related quality of life and community engagement among individuals with disabilities. It demonstrated sufficient internal consistency and hypothesis testing for construct validity (Table 3). The Econ-QOL validation study scored very good for risk of bias.¹⁹

The PFWS includes eight items and assesses levels of stress and well-being stemming from an individual’s financial situation.²⁴ It was previously known as the InCharge Financial Distress/Financial Well-Being Scale.²³ This instrument captures a spectrum from high financial distress to high financial well-being, reflecting a person’s emotional and practical reactions to their financial situation. The PFWS demonstrated sufficient structural validity, internal consistency, cross-cultural validity and measurement invariance, and hypothesis testing for construct validity (Table 3). The development and internal validation study for the PFWS scored adequate for risk of bias and very good for its external validation study.^23,24 The PFWS has been cross-culturally validated in seven countries across Europe;²⁴ however, it has not been developed or validated with a Veteran sample.

LSCAPE has 25 items and was developed to measure living standards for older adults across the following six domains: 1) health, 2) social integration, 3) contribution, 4) enjoyment, 5) security, and 6) restriction.³¹ The LSCAPE demonstrated sufficient structural validity, internal consistency, and hypothesis testing for construct validity (Table 3). It scored very good on risk of bias for its external validation study,³¹ and it evoked the following comment from one of the Veteran partners: “Provides a framework to understand well-being as it relates to finances.”

The other two Veteran partners added that to further enhance the LSCAPE’s applicability to the Veteran population, other factors should be included in the instrument, such as “financial security of housing, food, and travel (car, bus etc.)” and “questions on military mindset and identity.”

Discussion

The authors identified 13 instruments that measured financial well-being and found evidence of sufficient structural validity for 5 (38%),^{22–24,27,28,31,35} sufficient internal consistency for 12 (92%),^{19–21,23–35} sufficient cross-cultural validity and measurement invariance for 3 (23%),^{22–24,27,28} sufficient test-retest reliability for only 1 (8%),³³ and sufficient hypothesis testing for construct validity for 10 (77%).^{19,20,22–24,27,28,31–35} From these, only 4 (31%) – the WBI, Econ-QOL, PFWS, and LSCAPE – were found to be very clear and very applicable to Veterans.^{19,23,24,31,35} Of those, the WBI was the only instrument that was both developed and validated with a Veteran sample.³⁵ The Econ-QOL was developed with a general sample and validated in a population that included Veterans.¹⁹ Of the other 2, the LSCAPE was deemed most promising in terms of applicability because it accounted for social factors.³¹

Relevant literature

A recent systematic review identified 10 financial well-being instruments.³⁷ Despite a similar objective, it had several differences compared with this review, notably in the eligibility criteria. The authors excluded instruments designed for specialized populations (e.g., students, parents, farmers) and those created for unique circumstances (e.g., during a pandemic) to ensure the included tools were representative of the general population. Consequently, these criteria led to the exclusion of 9 of the 10 instruments included in the previous review and the inclusion of an additional 12 instruments in the current review. Also, the authors assessed the risk of bias of the included studies and each instrument’s psychometric properties using the COSMIN criteria, neither of which were explored in the prior systematic review.

Strengths and limitations

This systematic review has several strengths: 1) a search of the grey literature to ensure comprehensiveness, 2) use of COSMIN to evaluate risk of bias associated with the development and validation of all identified instruments, 3) clear criteria for evaluating the sufficiency of an instrument’s psychometric properties,¹⁶ and 4) assessment of clarity and applicability to Veterans.

In terms of limitations, although the authors collaborated with three Veteran partners to independently evaluate the clarity and applicability of each instrument, their insights may not be representative of all Veterans.

Implications for research and practice

Of the four instruments measuring financial well-being that were most promising, two, the PFWS and LSCAPE, require external validation among Veterans.^23,24,31 Also, aside from the WBI,³⁵ the Veteran partners advised that the Econ-QOL, PFWS, and LSCAPE require augmentation with additional factors.^19,23,24,31 One main missing factor is related to military identity and culture, which was deemed essential to optimally assess military transition to civilian life and Veteran well-being. The elements of military identity and culture should be considered when developing financial well-being tools de novo or augmenting existing ones.

Additionally, the findings of this study reveal significant gaps in the psychometric properties of the identified financial well-being instruments. None of the instruments reports data on measurement error or responsiveness, and the majority (10 of 13 instruments) have not been assessed for cross-cultural validity and measurement invariance or test-retest reliability. Criterion validity is also under-reported, with 8 of the 13 instruments lacking these data. These identified gaps underscore the need for further external validation of these measures to ensure robust assessment of financial well-being when using these tools.

These findings will support researchers and health care professionals in selecting an instrument to measure financial well-being among Veterans and decision makers in assessing the impact of policies, interventions, and strategies to address financial well-being among Veterans.

Conclusion

This systematic review identified 13 instruments that measure financial well-being. Among those with good psychometric properties, the WBI, Econ-QOL, PFWS, and LSCAPE were found to be clear and applicable to Veterans. Only the WBI and Econ-QOL have been validated among Veterans.

Biographies

Kian Torabiardakani is the co-first author, along with Mirey Karavetian. He is currently a bachelor of health sciences student at McMaster University. He is also a research assistant and project coordinator at the Michael G. DeGroote National Pain Centre in Hamilton.

Mirey Karavetian, PhD, is the co-first author, along with Kian Torabiardakani. She earned her doctorate in health promotion from Maastricht University and holds a dietetics degree from the American University of Beirut. She has worked as a university professor and clinical dietitian in several Middle Eastern countries. Karavetian is currently a senior research associate at the University of Toronto’s Faculty of Kinesiology and Physical Education, focusing on strategies to improve dietary habits and manage chronic diseases.

Holly N. Crandon, BHSc, MBiotech, is a research coordinator at the Michael G. DeGroote Institute for Pain Research and Care at McMaster University in Hamilton.

Dana Alameddine, MD, is currently a postdoctoral research fellow at the Yale University School of Medicine in New Haven, Connecticut.

Samer G. Karam, MD, is currently a PhD student in health research methodology at McMaster University. He is a medical doctor who specializes in general surgery and trauma care.

Gonzalo Bravo Soto, MD, is currently a PhD student in health research methodology at McMaster University. He is also a research assistant at the Michael G. DeGroote National Pain Centre. Gonzalo is a medical doctor from the Pontifical Catholic University of Chile.

Seyedeh Maryam Abdollahzadeh, PhD, earned her doctorate in nutrition sciences from Shiraz University of Medical Sciences.

Janice Xu is a researcher and medical student at the University of Toronto.

Rachel J. Couban, MISt, is a health research impact librarian at the Michael G. DeGroote National Pain Centre.

Tom Hoppe, MSC, MB, CD, MA, is currently a member of the Advisory Council for Veterans at the Chronic Pain Centre of Excellence. He served in the Canadian Armed Forces for 20 years and has since been actively involved in Veterans’ issues, holding key positions, such as former Chair of the Veterans Affairs Ombudsman Advisory Committee, and contributing to research on military identity and chronic pain.

Hélène Le Scelleur is the vice-chair of the Centre of Excellence Advisory Council for Veterans and a retired Captain of the Canadian Armed Forces. After her distinguished 26-year military career, she is now pursuing doctoral studies focused on addressing the identity crisis experienced by military personnel transitioning to civilian life with operational stress injuries.

Jason W. Busse, DC, PhD, is a professor in the Departments of Anesthesia and Health, Evidence, and Impact at McMaster University. He serves as the director of the National Pain Centre, associate director of the Michael G. DeGroote Centre for Medicinal Cannabis Research, and director of research for the Chronic Pain Centre of Excellence for Canadian Veterans.

Andrea J. Darzi, MD, MPH, PhD, is an Assistant Professor in the Departments of Anesthesia and Health, Evidence, and Impact at McMaster University. She also serves as an Associate Convenor of the Campbell and Cochrane Health Equity Thematic Group. Her research centres on evidence synthesis and guideline development and mobilization, specifically in chronic pain and Veteran well-being.

Funding Statement

This study received funding from the Chronic Pain Centre of Excellence for Canadian Veterans.