Evidence map›Paper›PMID 42756969›Full record

ArticleJournal of financial services marketing2026

Latent dimensions of financial behaviour derived by principal component and factor analysis.

Maryam Sholevar

Abstract read
In one paragraph

Article in Journal of financial services marketing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Maryam SholevarEdinburgh Business School, Heriot-Watt University, Edinburgh, UK.ORCID 0000-0002-2078-9817

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rather than directly measuring the dimensions of financial behaviour, this study constructs latent dimensions from observed indicators through multivariate analysis. These latent constructs are subsequently aligned with conceptually developed dimensions. Dimensionality reduction of the survey data informs the construction of the latent space. Data were collected using a tailored questionnaire administered to a sub-Saharan African sample (470 participants from urban and rural Ethiopia). Principal component analysis (PCA) and factor analysis (FA) were employed to test the framework and examine interrelationships among dimensions. The results provide exploratory support for aspects of the proposed multidimensional framework; however, further validation through confirmatory factor analysis (CFA), replication, or external behavioural outcomes is necessary. Financial inclusion emerges as a relatively distinct, access-related dimension associated with usage, but its status as a prerequisite for broader financial behaviour requires additional investigation. Financial literacy is most strongly linked to usage and knowledge-related indicators, and while its role in risk management remains conceptually plausible, it requires direct empirical testing. The findings highlight the limitations of inclusion-focused metrics and underscore the multidimensional nature of financial literacy. By integrating a novel conceptual framework, original data, and advanced statistical techniques, this study provides a comprehensive approach to understanding financial behaviour and challenges traditional assumptions, thereby establishing a foundation for future research and more effective strategies in financial education and inclusion. Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1057/s41264-026-00384-5.

Indexed as

Factor analysisFinancial behaviourFinancial inclusionFinancial literacyPrincipal component analysisRisk management

Identifiers

PMID42756969
PMCPMC13584979

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.