Financial Exploitation of Older AdultsNCT07682727
Leveraging Behavioral Economics to Understand and Improve Financial Decision Making Among Vulnerable Older Adults (Discovery)
An observational study of Financial Exploitation of Older Adults, run by The University of Texas Health Science Center, Houston at 1 site in United States.
Trial summary
This study seeks to: Identify behavioral preference patterns that characterize older adults vulnerable to financial exploitation. Estimate the extent to which biases in decision-making process influence financial decisions among older adults vulnerable to financial exploitation to refine information content and… Read more about this study
- Who is it for?
- Ages 60 years and olderHealthy volunteers can take part
- Conditions the study is for
- Financial Exploitation of Older Adults
- How many people
- 400 participants
- Where
- 1 siteUnited States
- Study dates
- 1 Aug 2026to 1 Dec 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 60 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: For online-only participation, 200 older adults (OAs) recruited via Prolific, a crowdsourcing platform. Those participating in-lab at the Health Decision Science Lab will include 200 OAs recruited from the Houston area (that is, participants who signed up to the study team's SONA system database).
Who may be able to join
- Adults over the age of 60
- English speakers, to ensure comprehension of study tasks
Who cannot join
- Less than age 60
- Non-English speaker
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site
The University of Texas Health Science Center at Houston
Houston, Texas, 77030
About this study
Official title: Leveraging Behavioral Economics to Understand and Improve Financial Decision Making Among Vulnerable Older Adults
This study seeks to:
- Identify behavioral preference patterns that characterize older adults vulnerable to financial exploitation.
- Estimate the extent to which biases in decision-making process influence financial decisions among older adults vulnerable to financial exploitation to refine information content and behavioral 'nudge' strategies.
- Conditions
- Financial Exploitation of Older Adults
- Keywords
- financial exploitation, financial decision-making, scam, behavioral nudging
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Older Adults who are less vulnerable to financial exploitation | Vulnerability to financial exploitation will be assessed via the Financial Exploitation Vulnerability Scale (FEVS) assessment. | |
| Older Adults who are more vulnerable to financial exploitation | Vulnerability to financial exploitation will be assessed via the Financial Exploitation Vulnerability Scale (FEVS) assessment. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Frequency of choosing the riskier option on the risk tolerance decision-making task
Participants will complete a decision-making session that captures multiple dimensions of behavioral preferences via incentivized choice-based tasks with real monetary rewards. The study team will administer the following decision-making task via a web-based survey platform to characterize risk tolerance (willingness to accept uncertain outcomes). The task involves multiple rounds (between 20 to 40) that vary option-specific information to facilitate mapping of elicited behavioral responses onto parameters characterizing standard utility functions.
Measured: During the time of the decision-making task (about 5-10 minutes)
Frequency of choosing the more trusting option on the trust decision-making task
Participants will complete a decision-making session that captures multiple dimensions of behavioral preferences via incentivized choice-based tasks with real monetary rewards. The study team will administer the following decision-making task via a web-based survey platform to characterize interpersonal trust (willingness to accept being vulnerable to other people). The task involves multiple rounds (between 20 to 40) that vary option-specific information to facilitate mapping of elicited behavioral responses onto parameters characterizing standard utility functions.
Measured: During the time of the decision-making task (about 5-10 minutes)
Frequency of choosing the more altruistic option on the altruism decision-making task
Participants will complete a decision-making session that captures multiple dimensions of behavioral preferences via incentivized choice-based tasks with real monetary rewards. The study team will administer the following decision-making task via a web-based survey platform to characterize altruism (willingness to incur a financial cost to benefit another person). The task involves multiple rounds (between 20 to 40) that vary option-specific information to facilitate mapping of elicited behavioral responses onto parameters characterizing standard utility functions.
Measured: During the time of the decision-making task (about 5-10 minutes)
Frequency of choosing the more patient option on the impatience decision-making task
Participants will complete a decision-making session that captures multiple dimensions of behavioral preferences via incentivized choice-based tasks with real monetary rewards. The study team will administer the following decision-making task via a web-based survey platform to characterize patience (willingness to forego a sooner reward for a bigger future reward). The task involves multiple rounds (between 20 to 40) that vary option-specific information to facilitate mapping of elicited behavioral responses onto parameters characterizing standard utility functions.
Measured: During the time of the decision-making task (about 5-10 minutes)
Frequency of choosing the less loss-averse option on the loss-aversion decision-making task
Participants will complete a decision-making session that captures multiple dimensions of behavioral preferences via incentivized choice-based tasks with real monetary rewards. The study team will administer the following decision-making task via a web-based survey platform to characterize loss aversion (tendency to weigh potential losses more heavily than equivalent gains). The task involves multiple rounds (between 20 to 40) that vary option-specific information to facilitate mapping of elicited behavioral responses onto parameters characterizing standard utility functions.
Measured: During the time of the decision-making task (about 5-10 minutes)
Physiological arousal as measured via heart rate
Participants recruited for in-lab sessions will complete the decision-making tasks while also sitting before a monitor with an eye-tracker to monitor attention, a webcam to monitor facial expressions, and with a wireless device (non-invasive transmitter placed on participant's wrist with two electrodes attached to finger) worn to monitor physiological measurements (heart rate and skin conductance) while completing the choice-based tasks.
Measured: During the time of the decision-making tasks (about 20-40 minutes)
Physiological arousal as measured via skin conductance
Participants recruited for in-lab sessions will complete the decision-making tasks while also sitting before a monitor with an eye-tracker to monitor attention, a webcam to monitor facial expressions, and with a wireless device (non-invasive transmitter placed on participant's wrist with two electrodes attached to finger) worn to monitor physiological measurements (heart rate and skin conductance) while completing the choice-based tasks.
Measured: During the time of the decision-making tasks (about 20-40 minutes)
Physiological arousal as measured via pupil dilation
Participants recruited for in-lab sessions will complete the decision-making tasks while also sitting before a monitor with an eye-tracker to monitor attention, a webcam to monitor facial expressions, and with a wireless device (non-invasive transmitter placed on participant's wrist with two electrodes attached to finger) worn to monitor physiological measurements (heart rate and skin conductance) while completing the choice-based tasks.
Measured: During the time of the decision-making tasks (about 20-40 minutes)
Frequency of facial expressions associated with valence and engagement
Participants recruited for in-lab sessions will complete the decision-making tasks while also sitting before a monitor with an eye-tracker to monitor attention, a webcam to monitor facial expressions, and with a wireless device (non-invasive transmitter placed on participant's wrist with two electrodes attached to finger) worn to monitor physiological measurements (heart rate and skin conductance) while completing the choice-based tasks. Facial expressions will be assessed using a facial expression analysis system (iMotions software).
Measured: During the time of the decision-making tasks (about 20-40 minutes)
Attention as assessed by eye fixations
Participants recruited for in-lab sessions will complete the decision-making tasks while also sitting before a monitor with an eye-tracker to monitor attention, a webcam to monitor facial expressions, and with a wireless device (non-invasive transmitter placed on participant's wrist with two electrodes attached to finger) worn to monitor physiological measurements (heart rate and skin conductance) while completing the choice-based tasks. Relative fixation duration on each option in the behavioral tasks will be measured via an eye tracker (SmartEye).
Measured: During the time of the decision-making tasks (about 20-40 minutes)
Secondary outcomes (1)
Response time during the behavioral tasks
Response time will be reported as the time from stimulus presentation to choice, in milliseconds.
Measured: During the time of the decision-making tasks (about 20-40 minutes)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted6 Jul 2026
- Study start1 Aug 2026 (estimated)
- Primary completion1 Dec 2027 (estimated)
- Study completion1 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Financial Exploitation of Older AdultsStudies of the same condition, open and under way.
- More trials run by The University of Texas Health Science Center, HoustonThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Prospective
- Enrolment
- 400 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Collaborators
- National Institute on Aging (NIA)
- Responsible party
- Principal investigator, Abdelaziz Alsharawy, The University of Texas Health Science Center, Houston
- Investigators
- Abdelaziz Alsharawy, PhD, Principal investigator, The University of Texas Health Science Center, Houston
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07682727
- Sponsor's protocol ID
- HSC-SPH-25-0344 (Discovery)
- Other IDs
- P30AG086563
- Status last verified
- Jul 2026
- First submitted
- 26 Jun 2026
- Last updated
- 7 Jul 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 7 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Leveraging Behavioral Economics to Understand and Improve Financial Decision Making Among Vulnerable Older Adults
- ClinicalTrials.gov ID
- NCT07682727
- Acronym / sponsor ID
- HSC-SPH-25-0344 (Discovery)
- Conditions
- Financial Exploitation of Older Adults
- Keywords
- financial exploitation, financial decision-making, scam, behavioral nudging
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 400 participants (estimated)
- Lead sponsor
- The University of Texas Health Science Center, HoustonUniversity, hospital or other
- Collaborators
- National Institute on Aging (NIA)
- Study start
- 1 Aug 2026 (estimated)
- Primary completion
- 1 Dec 2027 (estimated)
- Study completion
- 1 Dec 2027 (estimated)
- First posted
- 6 Jul 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study seeks to:
- Identify behavioral preference patterns that characterize older adults vulnerable to financial exploitation.
- Estimate the extent to which biases in decision-making process influence financial decisions among older adults vulnerable to financial exploitation to refine information content and behavioral 'nudge' strategies.
Study design
- Observational model
- Case-control
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Older Adults who are less vulnerable to financial exploitation | – | –Vulnerability to financial exploitation will be assessed via the Financial Exploitation Vulnerability Scale (FEVS) assessment. |
| Older Adults who are more vulnerable to financial exploitation | – | –Vulnerability to financial exploitation will be assessed via the Financial Exploitation Vulnerability Scale (FEVS) assessment. |
Who may qualify
- Ages
- 60 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- For online-only participation, 200 older adults (OAs) recruited via Prolific, a crowdsourcing platform. Those participating in-lab at the Health Decision Science Lab will include 200 OAs recruited from the Houston area (that is, participants who signed up to the study team's SONA system database).
Key inclusion criteria (2 listed)
- Adults over the age of 60
- English speakers, to ensure comprehension of study tasks
Key exclusion criteria (2 listed)
- Less than age 60
- Non-English speaker
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Frequency of choosing the riskier option on the risk tolerance decision-making task
Time frame: During the time of the decision-making task (about 5-10 minutes)
Participants will complete a decision-making session that captures multiple dimensions of behavioral preferences via incentivized choice-based tasks with real monetary rewards. The study team will administer the following decision-making task via a web-based survey platform to characterize risk tolerance (willingness to accept uncertain outcomes). The task involves multiple rounds (between 20 to 40) that vary option-specific information to facilitate mapping of elicited behavioral responses onto parameters characterizing standard utility functions.
Frequency of choosing the more trusting option on the trust decision-making task
Time frame: During the time of the decision-making task (about 5-10 minutes)
Participants will complete a decision-making session that captures multiple dimensions of behavioral preferences via incentivized choice-based tasks with real monetary rewards. The study team will administer the following decision-making task via a web-based survey platform to characterize interpersonal trust (willingness to accept being vulnerable to other people). The task involves multiple rounds (between 20 to 40) that vary option-specific information to facilitate mapping of elicited behavioral responses onto parameters characterizing standard utility functions.
Frequency of choosing the more altruistic option on the altruism decision-making task
Time frame: During the time of the decision-making task (about 5-10 minutes)
Participants will complete a decision-making session that captures multiple dimensions of behavioral preferences via incentivized choice-based tasks with real monetary rewards. The study team will administer the following decision-making task via a web-based survey platform to characterize altruism (willingness to incur a financial cost to benefit another person). The task involves multiple rounds (between 20 to 40) that vary option-specific information to facilitate mapping of elicited behavioral responses onto parameters characterizing standard utility functions.
Frequency of choosing the more patient option on the impatience decision-making task
Time frame: During the time of the decision-making task (about 5-10 minutes)
Participants will complete a decision-making session that captures multiple dimensions of behavioral preferences via incentivized choice-based tasks with real monetary rewards. The study team will administer the following decision-making task via a web-based survey platform to characterize patience (willingness to forego a sooner reward for a bigger future reward). The task involves multiple rounds (between 20 to 40) that vary option-specific information to facilitate mapping of elicited behavioral responses onto parameters characterizing standard utility functions.
Frequency of choosing the less loss-averse option on the loss-aversion decision-making task
Time frame: During the time of the decision-making task (about 5-10 minutes)
Participants will complete a decision-making session that captures multiple dimensions of behavioral preferences via incentivized choice-based tasks with real monetary rewards. The study team will administer the following decision-making task via a web-based survey platform to characterize loss aversion (tendency to weigh potential losses more heavily than equivalent gains). The task involves multiple rounds (between 20 to 40) that vary option-specific information to facilitate mapping of elicited behavioral responses onto parameters characterizing standard utility functions.
Physiological arousal as measured via heart rate
Time frame: During the time of the decision-making tasks (about 20-40 minutes)
Participants recruited for in-lab sessions will complete the decision-making tasks while also sitting before a monitor with an eye-tracker to monitor attention, a webcam to monitor facial expressions, and with a wireless device (non-invasive transmitter placed on participant's wrist with two electrodes attached to finger) worn to monitor physiological measurements (heart rate and skin conductance) while completing the choice-based tasks.
Physiological arousal as measured via skin conductance
Time frame: During the time of the decision-making tasks (about 20-40 minutes)
Participants recruited for in-lab sessions will complete the decision-making tasks while also sitting before a monitor with an eye-tracker to monitor attention, a webcam to monitor facial expressions, and with a wireless device (non-invasive transmitter placed on participant's wrist with two electrodes attached to finger) worn to monitor physiological measurements (heart rate and skin conductance) while completing the choice-based tasks.
Physiological arousal as measured via pupil dilation
Time frame: During the time of the decision-making tasks (about 20-40 minutes)
Participants recruited for in-lab sessions will complete the decision-making tasks while also sitting before a monitor with an eye-tracker to monitor attention, a webcam to monitor facial expressions, and with a wireless device (non-invasive transmitter placed on participant's wrist with two electrodes attached to finger) worn to monitor physiological measurements (heart rate and skin conductance) while completing the choice-based tasks.
Frequency of facial expressions associated with valence and engagement
Time frame: During the time of the decision-making tasks (about 20-40 minutes)
Participants recruited for in-lab sessions will complete the decision-making tasks while also sitting before a monitor with an eye-tracker to monitor attention, a webcam to monitor facial expressions, and with a wireless device (non-invasive transmitter placed on participant's wrist with two electrodes attached to finger) worn to monitor physiological measurements (heart rate and skin conductance) while completing the choice-based tasks. Facial expressions will be assessed using a facial expression analysis system (iMotions software).
Attention as assessed by eye fixations
Time frame: During the time of the decision-making tasks (about 20-40 minutes)
Participants recruited for in-lab sessions will complete the decision-making tasks while also sitting before a monitor with an eye-tracker to monitor attention, a webcam to monitor facial expressions, and with a wireless device (non-invasive transmitter placed on participant's wrist with two electrodes attached to finger) worn to monitor physiological measurements (heart rate and skin conductance) while completing the choice-based tasks. Relative fixation duration on each option in the behavioral tasks will be measured via an eye tracker (SmartEye).
1 secondary outcome
Response time during the behavioral tasks
Time frame: During the time of the decision-making tasks (about 20-40 minutes)
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Jul 2026.
- Individual participant dataSharing planned: No
Related trials for Financial Exploitation of Older Adults
Not yet recruiting
Leveraging Behavioral Economics to Understand and Improve Financial Decision Making Among Vulnerable Older Adults
Financial Exploitation of Older Adults
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Abdelaziz Alsharawy, PhD principal investigator
The University of Texas Health Science Center, Houston
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Financial Exploitation of Older Adults, run by The University of Texas Health Science Center, Houston at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 7 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Abdelaziz Alsharawy, PhD ((713) 500-9000, Abdelaziz.Alsharawy@uth.tmc.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Frequency of choosing the riskier option on the risk tolerance decision-making task (time frame: During the time of the decision-making task (about 5-10 minutes)). The study lists 10 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 7 Jul 2026.