Evidence map›Paper›PMID 31696205›Full record

ArticleArchives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists2020

Technology Use in Everyday Financial Activities: Evidence from Online and Offline Survey Data.

Preeti Sunderaraman, Sarah Ho, Silvia Chapman, Jillian L Joyce, Leigh Colvin, Shalom Omollo, Maria Pleshkevich, Stephanie Cosentino

Open access · bronzeAbstract read
In one paragraph

Article in Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% of its field
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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
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

8 authors at 1 institution in 1 country.

Preeti SunderaramanCognitive Neuroscience Division, Taub Institute for Research on Alzheimer's Disease and the Aging Brain Columbia University Medical Center, New York, NY, USA.
Sarah HoCognitive Neuroscience Division, Taub Institute for Research on Alzheimer's Disease and the Aging Brain Columbia University Medical Center, New York, NY, USA.
Silvia ChapmanCognitive Neuroscience Division, Taub Institute for Research on Alzheimer's Disease and the Aging Brain Columbia University Medical Center, New York, NY, USA.
Jillian L JoyceCognitive Neuroscience Division, Taub Institute for Research on Alzheimer's Disease and the Aging Brain Columbia University Medical Center, New York, NY, USA.
Leigh ColvinCognitive Neuroscience Division, Taub Institute for Research on Alzheimer's Disease and the Aging Brain Columbia University Medical Center, New York, NY, USA.
Shalom OmolloCognitive Neuroscience Division, Taub Institute for Research on Alzheimer's Disease and the Aging Brain Columbia University Medical Center, New York, NY, USA.
Maria PleshkevichCognitive Neuroscience Division, Taub Institute for Research on Alzheimer's Disease and the Aging Brain Columbia University Medical Center, New York, NY, USA.
Stephanie CosentinoCognitive Neuroscience Division, Taub Institute for Research on Alzheimer's Disease and the Aging Brain Columbia University Medical Center, New York, NY, USA.
Columbia University Irving Medical Center · US

Funding

Research Education CoreP30AG066462 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI ADAM M BRICKMAN · 2020 to 2026
$30.1M
Factors Influencing Financial Capacity and Awareness of Capacity in Cognitive AgingF32AG053035 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SUNDERARAMAN, PREETI · 2016 to 2019
$150k
NIA NIH HHS F32 AG053035NIA NIH HHS P30 AG066462
6 · The paper itself

Abstract

objectiveInternet use and mobile devices permeate every aspect of our lives and are changing our financial habits. Assessment of financial decision-making (FDM) has not yet caught up to apparent changes in financial behavior. To modernize assessment methods and create current and comprehensive FDM frameworks, we first need to establish the most commonly used and most preferred methods of performing specific financial activities.

methodCross-sectional survey data were collected using an online platform and offline approaches (in person and by mail) (N = 234). The frequency of using technological (e.g., laptop) and non-technological (e.g., in-person banking) means of completing seven financial activities was assessed first, including Depositing checks, Reviewing bank statements, Keeping track of money spent, Transferring funds, Withdrawing cash, Paying bills, and Purchasing products online. Second, preference for technological versus non-technological methods was assessed. Finally, linear regression models examined associations between demographics and preference for technological methods for each financial activity.

resultsThe majority of respondents (77% online, 74% offline) used technology to perform various financial activities and preferred technological to non-technological methods for completing five out of the six financial activities. Increased preference for technological methods was associated with younger age for all the financial activities, and higher education was associated with reviewing bank statement and transferring funds.

conclusionsOur survey findings provide empirical evidence for the changing nature of our financial habits. We discuss the implications of this change for researchers, clinicians, and the individuals themselves and emphasize the importance of modernizing FDM tools.

Indexed as

InternetMobile ApplicationsAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedNeuropsychological TestsSurveys and QuestionnairesTechnologyAssessmentFinancial capacityFinancial decision-makingInformation technologyMobile bankingOnline banking

Identifiers

PMID31696205
PMCPMC7244884
OpenAlexW2988958130

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.