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CompletedNCT05090995Updated Dec 13, 2024Results posted

A PPG Sensor-Based Feedback Intervention for Heavy Drinking Young Adults

An interventional study of Behavioral Self-Management and Feedback and Behavioral Self-Management in Heavy Drinking and Harmful; Use, Alcohol, sponsored by Yale University. Completed at 1 site in United States. Open to participants aged 18 Years to 25 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2024-12-13.

Sponsored by Yale University · Not applicable, Interventional, and Treatment

Phase
Not applicable
Study type
Interventional
Enrollment
60
Allocation
Randomized
Ages
18 Years to 25 Years
Sex
All
01

Study summary

Heavy alcohol use among young adults is a significant public health problem. Advances in technology may offer an innovative solution. This project will conduct the first controlled test of a feedback intervention for reducing drinking and improving health in young adults by targeting heart rate variability, resting heart rate, and sleep via biosensors and electronic diary methods.

Read the detailed description

Proposed is a study to conduct the first controlled test of a feedback intervention targeting heart rate variability, resting heart rate, and sleep for heavy-drinking young adults (N=60; ages 18-25) and will leverage the capabilities of a consumer-marketed PPG sensor/mobile app. This study will evaluate the feasibility, acceptability, and preliminary efficacy of this intervention for promoting improvements in drinking, sleep, and health.

02

Conditions studied

  • Heavy Drinking
  • Harmful; Use, Alcohol
03

In context

Lead sponsor

Yale University is the lead sponsor of 1,724 studies on the registry; 298 are open to participants now.

Of its 210 completed or terminated interventional studies of FDA-regulated products, 126 (60%) have results posted.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years to 25 Years
Sexes eligible
All
Accepts healthy volunteers
Yes

Inclusion criteria

  • 18-25 years of age
  • Report ≥ 4 heavy drinking occasions in the past 28 days
  • Report Alcohol Use Disorders Identification Test- Consumption (AUDIT-C) scores indictive of risk of drinking harm
  • English Speaking
  • Have a personal smartphone

Exclusion criteria

Exclusion Criteria:

  • Sleep Disorder History
  • Night/ Rotating work shift
  • Travel two or more time zones in the month prior to the study or anticipated travel two or more times during study participation
  • Clinically severe AUD in past 12 months
  • Currently enrolled in alcohol or sleep treatment
  • Current, severe psychiatric illness
  • Current DSM-V substance use disorder
  • Positive urine drug screen for a substance other than marijuana
05

Study design

Phase
Not applicable
Primary purpose
Treatment
Allocation
Randomized
Intervention model
Parallel assignment
Masking
Single (Participant)
Enrollment
60 participants (actual)

Study arms

  • Active comparator
    Self-Monitoring and Feedback

    The intervention consists of subjects wearing a PPG device for 6 weeks. Subjects will monitor their own health and report their sleep behaviors daily during this time. On weeks two, four, and six subjects will receive personalized health feedback based on the PPG device data and sleep diaries.

    Behavioral: Behavioral Self-Management and Feedback

  • Placebo comparator
    Self-Monitoring

    The intervention consists of subjects wearing a PPG device for 6 weeks. Subjects will monitor their own health and report their sleep behaviors daily during this time.

    Behavioral: Behavioral Self-Management

Interventions

  • BehavioralBehavioral Self-Management and Feedback

    Self-management brief health intervention that involves passive daily health monitoring using a PPG sensor, active self-monitoring of health and behavior using daily diaries, and the provision of personalized health feedback and advice.

  • BehavioralBehavioral Self-Management

    Self-management brief health intervention that involves passive daily health monitoring using a PPG sensor, and active self-monitoring of health and behavior using daily diaries.

06

What researchers measure

Primary outcomes

  1. Total Drinks Consumed

    Total drinks consumed will be measured using the Time Line Followback Interview at baseline, Week 6, and Week 10. This standardized interview asks subjects to self-report how many drinks they consume each day over the past 4 weeks at baseline and then since the last assessment point at Weeks 6 and 10. Higher scores indicate a greater number of drinks consumed. Total drinks will be summed over the past 4 weeks at intake, Week 6, and Week 10. Totals were transformed using a square root transformation since these values were not normally distributed. Mixed effects models were then conducted to evaluate the effect of condition on total drinks over time with condition, time, and their interaction in the model and sex and baseline total drinks as covariates.

    Time frame: up to Week 10

Secondary outcomes

  1. Drinks Per Drinking Day

    Total drinks per drinking day will be measured using the Time Line Followback Interview at baseline, Week 6, and Week 10. Total drinks/drinking day will be summed over the past 4 weeks at intake, Week 6, and Week 10. Totals were transformed using a square root transformation since these values were not normally distributed. Mixed effects models were then conducted to evaluate the effect of condition on total drinks/drinking day over time with condition, time, and their interaction in the model and sex and baseline drinks per drinking day as covariates. This tools asks subjects to self-report how many drinks they consume during a one month period. The score of this measure will be determined by the amount of self-reported alcohol consumption that occurred each day. A heavy drinking day for a man would be ≥5 drinks per sitting and for a women it would be ≥4 drinks per sitting.

    Time frame: up to 10 weeks

  2. Percent Heavy Drinking Days

    Self-reported percent heavy drinking days will be measured using the Time Line Followback Interview at baseline, Week 6, and Week 10. This standardized interview asks subjects to self-report heavy drinking occasions over the past 4 weeks at baseline and then since the last assessment point at Weeks 6 and 10, defined as ≥5 drinks per sitting and for a women it would be ≥4 drinks per sitting. Higher scores indicate a greater percentage of heavy drinking days. The percentage of heavy drinking days will be summed over the past 4 weeks at intake, Week 6, and Week 10. Mixed effects models were then conducted to evaluate the effect of condition on percent heavy drinking days over time with condition, time, and their interaction in the model and sex and baseline percent heavy drinking days as covariates.

    Time frame: up to 10 weeks

  3. Percent Abstinent Days

    Self-reported percent abstinent days will be measured using the Time Line Followback Interview at baseline, Week 6, and Week 10. This standardized interview asks subjects to self-report how many days they did not consume any alcohol each day over the past 4 weeks at baseline and then since the last assessment point at Weeks 6 and 10. Higher scores indicate a greater percentage of abstinent days. The percentage of abstinent days will be summed over the past 4 weeks at intake, Week 6, and Week 10. Mixed effects models were then conducted to evaluate the effect of condition on percent abstinent days over time with condition, time, and their interaction in the model and sex and baseline percent abstinent days as covariates.

    Time frame: up to 10 weeks

  4. Alcohol-related Consequences

    Mean alcohol related consequences were measured using the Brief Young Adult Alcohol Consequences Questionnaire at baseline, Week 6, and Week 10. Each consequence is scored 1 point and a total score reflects the total number of consequences. Higher scores indicated more consequences.Total score range 0-24. The three timepoints are summed then averaged. Mixed effects models were then conducted to evaluate the effect of condition on consequences over time with condition, time, and their interaction in the model and sex and baseline consequences as covariates.

    Time frame: baseline, Week 6, and Week 10

  5. Sleep Quality

    Mean sleep quality will be measured using the PROMIS - Sleep Disturbance Form 8 assessment. The sleep disturbance assessment has 8 questions that yield a total score (summed scores). This raw score is then converted to a standardized T score from 0-100 with a mean score of 50. A score above the mean would indicate that the subject experiences worse sleep quality. Mixed effects models were then conducted to evaluate the effect of condition on sleep quality over time with condition, time, and their interaction in the model and sex and baseline sleep quality as covariates.

    Time frame: baseline and Week 10

  6. Sleep-related Impairment

    Mean sleep quality will be measured using the PROMIS - Sleep-Related Impairment Form 8 assessment. The sleep impairment assessment has 8 questions that yield a total score (summed score). This raw score is then converted to a standardized T score from 0-100 with a mean score of 50. A score above the mean would indicate that the subject experiences more sleep-related impairment. Mixed effects models were then conducted to evaluate the effect of condition on sleep-related impairment over time with condition, time, and their interaction in the model and sex and baseline sleep-related impairment as covariates.

    Time frame: baseline and Week 10

  7. Sleep Duration

    Mean sleep duration will be measured daily for 6 weeks by the PPG device. Sleep duration will then be averaged in 2-week intervals at Weeks 2, 4, and 6 and evaluated over time using mixed effects models with condition, time, and their interaction in the model and sex and an indicator variable of weekday vs. weekend as covariates. Sleep duration was transformed using a square-root transformation.

    Time frame: up to 6 weeks

  8. Heart Rate Variability (HRV)

    Heart rate variability (HRV) will be measured daily for 6 weeks by the PPG device. HRV will then be averaged in 2-week intervals at Weeks 2, 4, and 6 and evaluated over time using mixed effects models with condition, time, and their interaction in the model and sex and an indicator variable of weekday vs. weekend as covariates. Sleep duration was transformed using a log transformation.

    Time frame: up to 6 weeks

  9. Lowest Resting Heart Rate (RHR)

    Lowest Resting Heart Rate (RHR) will be measured daily for 6 weeks by the PPG device. The lowest value will then be averaged in 2-week intervals at Weeks 2, 4, and 6 and evaluated over time using mixed effects models with condition, time, and their interaction in the model and sex and an indicator variable of weekday vs. weekend as covariates. Sleep duration was transformed using a log transformation. RHR can vary anywhere between 40-100 beats per minute. Lower RHR would indicate better cardiovascular health.

    Time frame: up to 6 weeks

07

Results

Posted Dec 13, 2024

Participant flow

Participant flow — Overall Study
MilestoneSelf-Monitoring and FeedbackSelf-Monitoring
Started3030
Completed week 63030
Completed week 103029
Completed3029
Not completed01

Outcome measures

PrimaryTotal Drinks Consumed

Total drinks consumed will be measured using the Time Line Followback Interview at baseline, Week 6, and Week 10. This standardized interview asks subjects to self-report how many drinks they consume each day over the past 4 weeks at baseline and then since the last assessment point at Weeks 6 and 10. Higher scores indicate a greater number of drinks consumed. Total drinks will be summed over the past 4 weeks at intake, Week 6, and Week 10. Totals were transformed using a square root transformation since these values were not normally distributed. Mixed effects models were then conducted to evaluate the effect of condition on total drinks over time with condition, time, and their interaction in the model and sex and baseline total drinks as covariates.

Time frame:
up to Week 10
Reported as:
Least squares mean · drinks
Total Drinks Consumed
drinksSelf-Monitoring and FeedbackSelf-Monitoring
Total Drinks Consumed6.76 ± .267.07 ± .26
Statistical analysis
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = <0.0001
SecondaryDrinks Per Drinking Day

Total drinks per drinking day will be measured using the Time Line Followback Interview at baseline, Week 6, and Week 10. Total drinks/drinking day will be summed over the past 4 weeks at intake, Week 6, and Week 10. Totals were transformed using a square root transformation since these values were not normally distributed. Mixed effects models were then conducted to evaluate the effect of condition on total drinks/drinking day over time with condition, time, and their interaction in the model and sex and baseline drinks per drinking day as covariates. This tools asks subjects to self-report how many drinks they consume during a one month period. The score of this measure will be determined by the amount of self-reported alcohol consumption that occurred each day. A heavy drinking day for a man would be ≥5 drinks per sitting and for a women it would be ≥4 drinks per sitting.

Time frame:
up to 10 weeks
Reported as:
Least squares mean · drinks per drinking day
Drinks Per Drinking Day
drinks per drinking daySelf-Monitoring and FeedbackSelf-Monitoring
Drinks Per Drinking Day2.26 ± 0.052.34 ± 0.05
Statistical analysis
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = <0.0001
SecondaryPercent Heavy Drinking Days

Self-reported percent heavy drinking days will be measured using the Time Line Followback Interview at baseline, Week 6, and Week 10. This standardized interview asks subjects to self-report heavy drinking occasions over the past 4 weeks at baseline and then since the last assessment point at Weeks 6 and 10, defined as ≥5 drinks per sitting and for a women it would be ≥4 drinks per sitting. Higher scores indicate a greater percentage of heavy drinking days. The percentage of heavy drinking days will be summed over the past 4 weeks at intake, Week 6, and Week 10. Mixed effects models were then conducted to evaluate the effect of condition on percent heavy drinking days over time with condition, time, and their interaction in the model and sex and baseline percent heavy drinking days as covariates.

Time frame:
up to 10 weeks
Reported as:
Least squares mean · percentage of heavy drinking days
Percent Heavy Drinking Days
percentage of heavy drinking daysSelf-Monitoring and FeedbackSelf-Monitoring
Percent Heavy Drinking Days18.62 ± 1.4819.83 ± 1.49
Statistical analysis
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = <0.0001
SecondaryPercent Abstinent Days

Self-reported percent abstinent days will be measured using the Time Line Followback Interview at baseline, Week 6, and Week 10. This standardized interview asks subjects to self-report how many days they did not consume any alcohol each day over the past 4 weeks at baseline and then since the last assessment point at Weeks 6 and 10. Higher scores indicate a greater percentage of abstinent days. The percentage of abstinent days will be summed over the past 4 weeks at intake, Week 6, and Week 10. Mixed effects models were then conducted to evaluate the effect of condition on percent abstinent days over time with condition, time, and their interaction in the model and sex and baseline percent abstinent days as covariates.

Time frame:
up to 10 weeks
Reported as:
Least squares mean · percentage of abstinent days
Percent Abstinent Days
percentage of abstinent daysSelf-Monitoring and FeedbackSelf-Monitoring
Percent Abstinent Days66.04 ± 1.7665.56 ± 1.78
Statistical analysis
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = <0.0001
SecondaryAlcohol-related Consequences

Mean alcohol related consequences were measured using the Brief Young Adult Alcohol Consequences Questionnaire at baseline, Week 6, and Week 10. Each consequence is scored 1 point and a total score reflects the total number of consequences. Higher scores indicated more consequences.Total score range 0-24. The three timepoints are summed then averaged. Mixed effects models were then conducted to evaluate the effect of condition on consequences over time with condition, time, and their interaction in the model and sex and baseline consequences as covariates.

Time frame:
baseline, Week 6, and Week 10
Reported as:
Least squares mean · score on scale
Alcohol-related Consequences
score on scaleSelf-Monitoring and FeedbackSelf-Monitoring
Alcohol-related Consequences8.56 ± .758.23 ± .76
Statistical analysis
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = <.0001
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = <.0001
SecondarySleep Quality

Mean sleep quality will be measured using the PROMIS - Sleep Disturbance Form 8 assessment. The sleep disturbance assessment has 8 questions that yield a total score (summed scores). This raw score is then converted to a standardized T score from 0-100 with a mean score of 50. A score above the mean would indicate that the subject experiences worse sleep quality. Mixed effects models were then conducted to evaluate the effect of condition on sleep quality over time with condition, time, and their interaction in the model and sex and baseline sleep quality as covariates.

Time frame:
baseline and Week 10
Reported as:
Least squares mean · T-score
Sleep Quality
T-scoreSelf-Monitoring and FeedbackSelf-Monitoring
Sleep Quality50.59 ± .9350.38 ± .93
Statistical analysis
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = <.0001
SecondarySleep-related Impairment

Mean sleep quality will be measured using the PROMIS - Sleep-Related Impairment Form 8 assessment. The sleep impairment assessment has 8 questions that yield a total score (summed score). This raw score is then converted to a standardized T score from 0-100 with a mean score of 50. A score above the mean would indicate that the subject experiences more sleep-related impairment. Mixed effects models were then conducted to evaluate the effect of condition on sleep-related impairment over time with condition, time, and their interaction in the model and sex and baseline sleep-related impairment as covariates.

Time frame:
baseline and Week 10
Reported as:
Least squares mean · T-score
Sleep-related Impairment
T-scoreSelf-Monitoring and FeedbackSelf-Monitoring
Sleep-related Impairment53.98 ± 1.1055.05 ± 1.11
Statistical analysis
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = <.0001
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = 0.04
SecondarySleep Duration

Mean sleep duration will be measured daily for 6 weeks by the PPG device. Sleep duration will then be averaged in 2-week intervals at Weeks 2, 4, and 6 and evaluated over time using mixed effects models with condition, time, and their interaction in the model and sex and an indicator variable of weekday vs. weekend as covariates. Sleep duration was transformed using a square-root transformation.

Time frame:
up to 6 weeks
Reported as:
Least squares mean · square root in milliseconds
Sleep Duration
square root in millisecondsSelf-Monitoring and FeedbackSelf-Monitoring
Weeks 1-2168.73 ± 1.37170.78 ± 1.37
Weeks 3-4172.18 ± 1.37169.38 ± 1.38
Weeks 5-6171.74 ± 1.37170.11 ± 1.41
Statistical analysis
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = 0.02
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = 0.02
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = 0.0007
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = 0.02
SecondaryHeart Rate Variability (HRV)

Heart rate variability (HRV) will be measured daily for 6 weeks by the PPG device. HRV will then be averaged in 2-week intervals at Weeks 2, 4, and 6 and evaluated over time using mixed effects models with condition, time, and their interaction in the model and sex and an indicator variable of weekday vs. weekend as covariates. Sleep duration was transformed using a log transformation.

Time frame:
up to 6 weeks
Reported as:
Least squares mean · milliseconds
Heart Rate Variability (HRV)
millisecondsSelf-Monitoring and FeedbackSelf-Monitoring
Weeks 1-27.55 ± 0.357.79 ± 0.35
Weeks 3-47.63 ± 0.357.81 ± 0.35
Weeks 5-67.68 ± 0.357.84 ± 0.35
Statistical analysis
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = 0.0001
SecondaryLowest Resting Heart Rate (RHR)

Lowest Resting Heart Rate (RHR) will be measured daily for 6 weeks by the PPG device. The lowest value will then be averaged in 2-week intervals at Weeks 2, 4, and 6 and evaluated over time using mixed effects models with condition, time, and their interaction in the model and sex and an indicator variable of weekday vs. weekend as covariates. Sleep duration was transformed using a log transformation. RHR can vary anywhere between 40-100 beats per minute. Lower RHR would indicate better cardiovascular health.

Time frame:
up to 6 weeks
Reported as:
Least squares mean · beats per minute
Lowest Resting Heart Rate (RHR)
beats per minuteSelf-Monitoring and FeedbackSelf-Monitoring
Weeks 1-24.06 ± 0.024.03 ± 0.02
Weeks 3-44.06 ± 0.024.03 ± 0.02
Weeks 5-64.05 ± 0.024.03 ± 0.02
Statistical analysis
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = 0.04
  • Self-Monitoring and Feedback · Mixed Models Analysis · p = <.0001
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = <0.0001
  • Self-Monitoring and Feedback vs Self-Monitoring · Mixed Models Analysis · p = 0.03

Adverse events

Collected over 10 weeks. Non-serious events are listed at a 5% frequency threshold.

Adverse event summary by group
GroupDeathsSeriousOther
Self-Monitoring and Feedback0/30 (0%)0/30 (0%)0/30 (0%)
Self-Monitoring0/30 (0%)0/30 (0%)0/30 (0%)

Baseline characteristics

Age, Continuous
Age, Continuous(years)Self-Monitoring and FeedbackSelf-MonitoringTotal
Mean22.33 ± 1.8321.71 ± 2.1322.02 ± 1.99
Sex: Female, Male
Sex: Female, Male(Participants)Self-Monitoring and FeedbackSelf-MonitoringTotal
Female151429
Male151631
Ethnicity (NIH/OMB)
Ethnicity (NIH/OMB)(Participants)Self-Monitoring and FeedbackSelf-MonitoringTotal
Hispanic or Latino459
Not Hispanic or Latino262551
Unknown or Not Reported000
Race (NIH/OMB)
Race (NIH/OMB)(Participants)Self-Monitoring and FeedbackSelf-MonitoringTotal
American Indian or Alaska Native000
Asian123
Native Hawaiian or Other Pacific Islander000
Black or African American336
White252449
More than one race101
Unknown or Not Reported011
Region of Enrollment
Region of Enrollment(participants)Self-Monitoring and FeedbackSelf-MonitoringTotal
United States303060
Gender
Gender(Participants)Self-Monitoring and FeedbackSelf-MonitoringTotal
Female151429
Male141630
Nonbinary101
08

Study locations

1 site
  • Yale University
    New Haven, Connecticut 06510, United States
09

References and documents

Publications

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Study documents

  • Protocol and statistical analysis plan · Nov 11, 2022
  • Informed consent form · Jan 27, 2022

Documents are hosted by the registry — open the source record to download them.

Individual participant data

Plan to share: No

10

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Dec 13, 2024, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
11

Registry details

Key details

Study ID
NCT05090995
Lead sponsor
Yale University
Collaborators
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Responsible party
Sponsor
First posted
Oct 25, 2021
Start date
Feb 23, 2022
Primary completion
Jun 1, 2023
Completion
Jun 1, 2023
Results posted
Dec 13, 2024
Last update
Dec 13, 2024

Study contacts

Lisa Fucito, PhD
principal investigator · Associate Professor of Psychiatry; Director, Tobacco Treatment Service, Psychiatry

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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