Contextual Moderators of the Relationship Between Alcohol‐Induced Blackouts and Alcohol‐Related Consequences Among Young Adults

ABSTRACT

Background

Alcohol‐induced blackouts (AIBs) are a common and serious consequence of drinking in young adults. AIBs are associated with experiencing increased alcohol‐related consequences. To inform efforts to reduce alcohol‐related harms on especially risky drinking days that result in AIBs, we sought to identify contextual factors that contribute to excess AIB‐associated harms. This study aims to (1) examine relationships between AIBs and four consequence domains; and (2) explore how these relationships differ by social context and location.

Methods

Young adults (N = 175, 52.6% female, 86.9% White, M _age = 20.8) with recent heavy drinking and AIBs wore alcohol sensors and completed surveys about their consequences (including AIBs) and the social context and locations in which drinking occurred over six weekends. Four consequence domains included positive (reflective of desired alcohol expectancies), common (relatively acute, low potential for personal harm), uncommon (relatively serious, i.e., sexual, legal, great potential for personal harm), and alcohol‐related problems (related to impaired control and physical dependence). Multilevel structural equation models were conducted to test for main effects of AIBs and moderating effects of contextual factors.

Results

AIBs were significantly associated with experiencing 15% more positive consequences, 205% more common consequences, 367% more uncommon consequences, and 166% more alcohol‐related problems. AIBs were more strongly associated with common consequences and alcohol‐related problems when drinking occurred exclusively with family, friend(s), and/or a romantic partner (vs. with a large group). AIBs were also more strongly associated with common consequences when drinking took place exclusively at a residential location (vs. non‐residential). No other significant moderating effects were observed.

Conclusions

Days with an AIB were associated with experiencing significantly more positive and negative alcohol‐related consequences compared to days without an AIB. Our findings support the notion that the context in which drinking occurs is an important consideration for reducing alcohol‐related harms.

This study examined the associations between alcohol‐induced blackouts and four types of other alcohol‐related consequences (positive, common, non‐common, alcohol‐related problems). Blackouts were associated with increased incidences of each type of consequence. Drinking context (social and location) were examined as moderators of these associations. Social context moderated the associations between blackouts and common negative consequences and alcohol‐related problems. Location moderated the association between blackouts and common negative consequences. These findings support drinking context an important consideration for reducing alcohol‐related harms.

1. Introduction

Alcohol‐induced blackouts (AIBs) are a serious consequence of drinking characterized by periods of anterograde amnesia while the affected individual is still conscious and interacting with their environment (White 2003). AIBs are both common and recurrent among young adults who drink (Barnett, Clerkin, et al. 2014; Glenn et al. 2022). Among an especially risky group of young adults (i.e., college students with recent history of AIBs), AIBs occur at a rate of about one in every three drinking days (Richards, Glenn, et al. 2024). The frequency in which AIBs occur is a major concern, given their strong relationship with experiencing other alcohol‐related consequences across a continuum of severity (Hingson et al. 2016).

Many behavioral and psychosocial risk factors have been identified as potential intervention targets to prevent or reduce AIBs (Chartier et al. 2011; LaBrie et al. 2011; Jackson et al. 2020; Ward and Guo 2020; Carpenter and Merrill 2021; Carey et al. 2022; DiBello et al. 2023; Richards, Turrisi, et al. 2023; Litt et al. 2024). Despite our growing understanding of AIB risk and protective factors, AIBs still occur frequently among young adults. There is evidence that young adults often do not perceive AIBs negatively (Mallett et al. 2008; Merrill et al. 2013), and they may plan or intend to experience an AIB in the near future (Miller et al. 2020). It is therefore critical to understand the relationships between AIBs and other consequences in order to reduce alcohol‐related harm on risky drinking days that may result in an AIB.

1.1. AIBs And Excess Harm

Most research examining the AIB‐consequence association has focused on individual consequences. On the less severe end of the alcohol‐related consequences spectrum, Merrill et al. (2019) found that AIB days were associated with significantly higher likelihoods of embarrassing oneself and being hungover than non‐AIB drinking days. On the more severe end, AIBs have been associated with increased average likelihoods of experiencing sexual assault (Voloshyna et al. 2018) and sexual revictimization (Valenstein‐Mah et al. 2015). Research also suggests a prospective link between experiencing AIBs and developing alcohol use disorders (AUD) and/or related symptoms (Glenn et al. 2024; Studer et al. 2019; Yuen et al. 2021). Richards, Turrisi, et al. (2023) expanded on this body of research by examining the associations between AIBs and (a) total number of negative consequences and (b) serious consequences (i.e., sexual, legal, or have great potential for personal harm). They found that AIB days were associated with an increase of more than three total negative consequences compared to non‐AIB days at equivalent levels of drinking. About one of these ‘excess’ consequences were considered serious.

The relationship between AIBs and positive alcohol‐related consequences (i.e., those that are likely perceived as positive by the participant, e.g., having fun, relieving tension) has not yet been explored. Positive alcohol‐related consequences are important because they often serve as a motivating factor for continued risky drinking despite negative consequences that may co‐occur (Corbin et al. 2008; Patrick and Maggs 2008; Lee et al. 2018). This is further supported by research showing that among young adults, the heaviest drinking days often result in the greatest numbers of both positive and negative alcohol‐related consequences (Richards, Mallett, Turrisi, Glenn, and Russell 2025). The experience of increased positive consequences may also contribute to young adults intending or being willing to experience an AIB. In an analysis of over one thousand “pre‐blackout” Tweets, over half contained messages related to intentions or plans to blackout (Riordan et al. 2019). Nearly one‐third contained motives for blacking out, most commonly being to celebrate an occasion (e.g., birthday) or to cope with negative emotions.

1.2. Social Context, Location, and Alcohol Outcomes

The Social‐Ecological Framework of Drinking Contexts and Alcohol‐Related Problems posits that alcohol‐related problems (i.e., consequences) are influenced by individual characteristics (e.g., sex), the contexts in which drinking occurs (e.g., social context, location), and alcohol use (Freisthler et al. 2014). Social context (i.e., the individuals with whom young adults are drinking) and location may present differential risks for the consequences that occur during or after a drinking event. For example, drinking with a close friend or romantic partner may increase one's risk for getting into an argument. Drinking at home may protect against driving a car while intoxicated.

A large body of research supports the influence of social context on drinking behaviors and perceptions. Drinking with friends or in social settings (vs. alone) has often been associated with heavier alcohol consumption (Braitman et al. 2017), increased subjective alcohol intoxication and estimated blood alcohol concentrations (eBAC) (Corbin et al. 2021; Fischer et al. 2023; Kirkpatrick and de Wit 2013), and higher positive and negative alcohol expectancies (Monk and Heim 2014). One study examined whether drinking with others versus alone impacted the relationship between eBAC and subjective alcohol intoxication and did not find any significant moderating effects (Richards, Turrisi, and Russell 2024). Limited studies have examined the impact of social context on alcohol‐related consequences. Merrill et al. (2018) found that young adults viewed consequences more negatively if they occurred among strangers versus friends. Fairbairn et al. (2018) found that drinking in relatively unfamiliar social settings (vs. familiar settings) conferred more emotional rewards (e.g., greater mood enhancement).

A similar level of evidence exists for the influence of location on drinking behaviors and perceptions. Bars and similar non‐residential settings (e.g., parties) have often been associated with heavier alcohol consumption (Braitman et al. 2017), increased subjective alcohol intoxication and eBAC (Corbin et al. 2021; Fischer et al. 2023), and higher positive and negative alcohol expectancies (Monk and Heim 2014). Clapp et al. (2008) investigated the effects of themed college parties, reporting increased average breath alcohol concentrations (BrACs) at themed parties compared to non‐themed parties. Richards, Turrisi, and Russell (2024) found a weaker relationship between eBAC and subjective intoxication when drinking in a non‐residential location (e.g., bar/club/party) versus a residential location. Merrill et al. (2018) found that young adults viewed consequences more negatively if they occurred at a bar or party versus at home.

Social context and location may influence the amount of excess harm associated with AIBs, but this has not yet been explored. With whom young adults are drinking, and where they drink, may be especially important during an AIB. Prior work provides evidence that by creating a safer drinking environment through increased serious harm reduction protective behavioral strategy (PBS) use (i.e., behaviors related to reducing alcohol‐related consequences rather than intoxication; e.g., only drinking with people you trust), the relationship between AIBs and other negative alcohol‐related consequences can be weakened (Richards, Turrisi, Glenn, Mallett, et al. 2025). This study showed that college students experienced about 50% fewer negative consequences on AIB days when above average numbers of serious harm reduction PBS were used compared to AIB days with below average use of these strategies. Another study supports the idea that drinking location is associated with other types of PBS use related to drinking behaviors (Braitman et al. 2017). These studies provide justification to theorize that the social context and physical location in which AIBs occur may also impact the associations between AIBs and other alcohol‐related consequences.

1.3. The Current Study

The current study aimed to expand on previous research by examining the AIB‐consequence relationships within the social contexts and locations in which they occur. We examined data from an intensive event‐level study comprising 175 young adults with recent history of heavy drinking and AIBs. Participants completed daily assessments of their drinking behaviors and related outcomes and wore transdermal alcohol concentration (TAC) sensors over six weekends.

First, we examined the associations between AIBs and four distinct types of alcohol‐related consequences: (1) positive consequences (e.g., having fun), (2) common negative consequences (e.g., hangovers), (3) uncommon negative consequences (i.e., relatively serious consequences; e.g., sexual consequences), and (4) alcohol‐related problems (e.g., impaired control). We hypothesized (H1) that AIBs would be associated with increased incidence rate ratios (IRRs) of each type of consequence. These findings may provide an explanation for why young adults continue to engage in risky drinking behaviors (including ‘blackout drinking’) despite experiencing significant harms.

Second, we explored whether the AIB‐consequence relationships varied by social context and/or location. We hypothesized that both social context (H2) and drinking location (H3) would be significant moderators of the AIB‐consequence relationships but did not hypothesize the directionality based on limited prior research on this topic. It may be that drinking in familiar settings (i.e., with family, friend(s), and/or a romantic partner vs. with a large group or drinking in a residential setting vs. non‐residential) strengthens the AIB‐consequence relationships because the drinker feels safer or more comfortable to partake in riskier behaviors or use fewer protective behaviors, resulting in experiencing more consequences. It may also be the opposite, that drinking in less familiar settings leads to a poorer estimation of actual level of intoxication or greater expectancies, or that less familiar settings are potentially less safe, resulting in more consequences. These may also vary by consequence type.

Findings from the current study may inform alcohol‐related harm reduction efforts by identifying opportunities to adapt interventions based on the specific drinking context. For example, identifying stronger associations between AIBs and types of consequences may provide insight into specific types of PBS that are most effective within that context, especially during drinking episodes that are likely to result in an AIB (i.e., fast‐paced heavy drinking episodes; Richards, Glenn, et al. 2024). Such information could aid in the personalization of harm reduction interventions based on where and with whom the individual is planning to drink that day.

2. Materials and Methods

2.1. Procedures and Participants

This study comprised 175 young adults who regularly engaged in ‘risky’ drinking. We defined ‘risky’ drinking as engaging in heavy episodic drinking (HED; 4+/5+ drinks on a single drinking occasion for women/men) at least once during a typical weekend and reporting at least one recent AIB in the past 3‐months, based on research linking these behaviors to increased risk for alcohol‐related harms (Hingson et al. 2016; Richards, Glenn, et al. 2023). All procedures were approved by the University's Institutional Review Board and all participants provided informed consent. To recruit the sample, 15,000 students were randomly selected from the university registrar's database at a large, public university in the northeastern United States. Participants were sent an email invitation describing the study and inviting their participation. Recruitment emails (and up to six reminders) contained a personalized URL to access a screening survey. Thirty‐one individuals were also recruited via flyers posted at on‐ and off‐campus locations (e.g., dorms, restaurants, coffee shops). After emailing the study team to indicate interest, these individuals were sent the same email invitation and followed the same procedures as students who were randomly contacted from the registrar's database. Individuals were eligible to participate if they were (a) aged 18–23 years, (b) reported drinking 4+/5+ drinks (women/men) on a typical Friday or Saturday in the past 3 months, (c) reported at least one AIB in the past 3 months, which was defined as endorsement of at least one of the following: not being able to remember large stretches of time while drinking heavily; having fuzzy memories of events that occurred while drinking; unable to remember what happened the previous day/night because of drinking, (d) owned an iPhone, and (e) were willing to wear an alcohol sensor during the study period. Individuals were excluded if they were (a) enrolled in high school, (b) did not live or work in the area surrounding the university, or (c) were planning to abstain from drinking during the dates of data collection (e.g., due to sorority rush).

Eligible participants were immediately redirected to a baseline survey, which took approximately 20 min to complete. At the end of this survey, participants scheduled a 20‐min enrollment visit appointment to come into the laboratory to pick up the sensor and receive training on the protocol (i.e., how to use the sensor and the survey application). Enrollment visit appointments were scheduled within a week following completion of the baseline survey and occurred over the span of 6 days. Of the 15,031 individuals invited to complete this study, 1370 (9%) completed the screening survey of whom 289 (21%) were eligible to participate. A total of 227 (79%) of eligible individuals completed the baseline survey and 175 (77%) were enrolled in the study. The remaining 52 unenrolled eligible individuals were not enrolled in the study due to: (1) dropping from the study after completing baseline (n = 9), (2) not scheduling an appointment for the enrollment visit (n = 4), (3) being deemed ineligible during the enrollment visit for issues such as not having a functional iPhone (n = 3), and (4) not showing up for the enrollment visit appointment (n = 26). An additional 10 participants were dropped from the study due to availability of alcohol sensors. We did not observe any significant differences by sex, past three‐month drinking, or past three‐month AIBs between eligible participants who were enrolled versus not enrolled.

Data collection occurred in two periods over the span of one semester, each consisting of three social weekends (Thursday through Saturday). Data collection periods were timed to avoid events that may be less representative of typical drinking (e.g., spring break, final exams). Following the first data collection period, participants returned their sensors to the lab and scheduled a refresher appointment to pick up the same sensor during the week preceding the second data collection period. We observed a 90.9% retention rate between the two data collection periods. During each data collection period, participants were instructed to wear the alcohol sensor continuously starting Thursday evening at 5 pm through Sunday morning at 9 am, with the exception of removing the device to shower. Alcohol sensors provide a complement to self‐reported data on alcohol consumption by providing a measure of alcohol use less prone to intoxication‐related decreases in reliability, especially in the context of memory‐loss (i.e., AIBs) (Northcote and Livingston 2011). Participants received reminders each Thursday at 5 pm to wear their sensor. Participants also received a morning survey (open from 9:00 am until 4:00 pm) and evening survey (open from 4:00 pm until 7:00 pm) each Thursday, Friday, Saturday, and Sunday during the data collection periods. Drinking behaviors and outcomes were only assessed on Friday through Sunday (about Thursday through Saturday behaviors). Average completion time for the morning surveys was 7.4 min (SD = 21.7 min) and for the evening surveys was 3.4 min (SD = 11.3 min). Morning surveys had an average completion rate of 87.1% (median = 100%) and evening surveys had an average completion rate of 80.6% (median = 91.7%), resulting in an overall average completion rate of 83.9% (median = 95.8%) across the 48 total daily surveys. Self‐initiated drinking ecological momentary assessments (EMAs) and hourly follow‐ups were also completed as part of this study (not included in current analysis).

Participants were compensated $20 for completing the baseline survey, $4 for each morning survey, $3 for each evening survey, and $5 for each sensor return visit. To increase compliance, participants were awarded a “perfect weekend” bonus for each weekend that they completed all four morning surveys, all four evening surveys, and wore the sensor at least 75% of the time. The bonus was $2 during data collection period 1, resulting in up to $30 of compensation per weekend. The bonus was increased to $7 during data collection period 2, resulting in up to $35 of compensation per weekend. The total amount of compensation possible during the entire study was $225. An additional bonus was available based on total study completion. Once a participant completed 18 “perfect days” (days with morning and evening surveys completed and at least 75% sensor wear), they were entered for a chance to win one of 20 $100 gift cards. Completing 18 days resulted in 18 chances per participant, with this increasing by two for each additional completed day (up to 30 chances).

In the current sample of 175 participants, the mean age at baseline was 20.8 years (SD = 1.1) and the majority were females (52.6%) and White (86.9%). Participants also identified as Hispanic/Latino (9.8%), Asian (5.1%), Black (4.0%), and multiracial (2.3%). Most participants were full‐time undergraduate students (93.1%).

2.2. Measures

2.2.1. Alcohol‐Induced Blackouts

AIBs were assessed using 8 items from The Alcohol‐Induced Blackout Measure‐2 (ABOM‐2; Boness et al. 2022), in the morning and evening surveys after drinking occurred on Friday, Saturday, and Sunday (standard drink count > 0). The morning assessment was designed to measure AIB consequences that participants immediately remembered upon taking the survey. It is possible that a participant may not remember an AIB consequence until later in the day (e.g., “able to remember a small part of the day after being reminded,” “reminded about things you had previously forgotten”). The evening assessment was designed to increase sensitivity of the AIB measure by asking participants if they recall any additional AIB consequences from the previous drinking episode. In the morning survey, participants were asked, “As a result of drinking yesterday, did you… (insert AIB item)?”. In the evening survey, participants were asked, “Since your morning report, did you find out or remember that as a result of drinking yesterday you… (insert AIB item)?”. The ABOM‐2 was adapted to assess AIBs at the day‐level with dichotomous response options of no (0) and yes (1). Fragmentary AIBs were defined as endorsement of at least one of the first four items, whereas en bloc AIBs were defined as endorsement of at least one of the last four items. Fragmentary and en bloc AIBs are theorized to result from distinct neurological processes (Hartzler and Fromme 2003; White 2003), thus were not mutually exclusive outcomes (i.e., both types of AIBs could be experienced on one drinking day). The primary outcome, any AIB, was defined as endorsement of at least one of the eight items. For exploratory analyses, we created a three‐level AIB variable comprising (0) no AIB, (1) fragmentary AIB only, and (2) en bloc AIB (inclusive of fragmentary AIB). The ABOM‐2 measures both fragmentary (partial) and en bloc (complete) AIBs with high reliability (total: ω_day = 0.98, ω_person = 0.97; fragmentary: ω_day = 0.98, ω_person = 0.96; en bloc: ω_day = 0.96, ω_person = 0.97).

2.2.2. Alcohol‐Related Consequences

If participants self‐reported alcohol use, they then reported whether a set of alcohol‐related consequences had occurred as a result of drinking yesterday. A full list of assessed consequences is presented in Table 1.

TABLE 1.

Alcohol‐related consequences experienced per drinking day by AIB status.

	No AIB (n = 1049) frequency (%)	AIB (n = 535) frequency (%)	Total (n = 1584) frequency (%)
Positive consequences a
Total daily mean (SD)	3.57 (2.69)	5.07 (2.42)	4.09 (2.69)
Have more fun	710 (72.30%)	466 (90.49%)	1176 (78.56%)
Feel closer to your friends	555 (56.52%)	404 (78.45%)	959 (64.06%)
Relieve tension	456 (46.44%)	337 (65.44%)	793 (52.97%)
Become more social	630 (64.15%)	458 (88.93%)	1088 (72.68%)
Relax after a stressful situation	358 (36.49%)	254 (49.32%)	612 (40.91%)
Cope with daily life	234 (23.83%)	170 (33.01%)	404 (26.99%)
Seem more exciting to others	283 (28.82%)	266 (51.65%)	549 (36.67%)
Have a good sexual experience	101 (10.29%)	87 (16.89%)	188 (12.56%)
Look interesting to other people	181 (18.43%)	168 (32.62%)	349 (23.31%)
Relieve boredom	378 (38.49%)	289 (56.12%)	667 (44.56%)
Common consequences
Total daily mean (SD)	0.53 (1.00)	2.36 (1.80)	1.15 (1.58)
Have a hangover	189 (18.02%)	342 (63.93%)	531 (33.52%)
Feel sick to your stomach or throw up	93 (8.87%)	163 (30.47%)	256 (16.16%)
Get into an argument with someone	26 (2.48%)	68 (12.71%)	94 (5.93%)
Say or do embarrassing things	68 (6.48%)	237 (44.30%)	305 (19.26%)
Become rude, obnoxious, or insulting	14 (1.33%)	87 (16.26%)	101 (6.38%)
Neglect your obligations to family, work, or school	33 (3.15%)	63 (11.78%)	96 (6.06%)
Feel badly about yourself	70 (6.67%)	119 (22.24%)	189 (11.93%)
Experience “hangxiety” (i.e., wake up feeling anxious as a result of drinking)	62 (5.91%)	184 (34.39%)	246 (15.53%)
Uncommon consequences
Total daily mean (SD)	0.04 (0.23)	0.28 (0.65)	0.12 (0.43)
Pass out	2 (0.19%)	28 (5.23%)	30 (1.89%)
Get in trouble with the police or Penn State Authorities for drinking	1 (0.10%)	1 (0.19%)	2 (0.13%)
Do something sexually you wouldn't have done if you hadn't been drinking	21 (2.00%)	43 (8.04%)	64 (4.04%)
Have a sexual experience you regret	6 (0.57%)	12 (2.24%)	18 (1.14%)
Wake up in an unexpected place	0 (0.00%)	16 (2.99%)	16 (1.01%)
Get into a physical fight with someone	4 (0.38%)	7 (1.31%)	11 (0.69%)
Hurt or injure yourself on accident	6 (0.57%)	27 (5.05%)	33 (2.08%)
Drive a car when you knew you had too much to drink to drive safely	2 (0.19%)	6 (1.12%)	8 (0.51%)
Get in the car as a passenger when you knew the driver had too much to drink to drive safely	1 (0.10%)	8 (1.50%)	9 (0.57%)
Alcohol‐related problems
Total daily mean (SD)	0.30 (0.68)	1.34 (1.24)	0.65 (1.03)
Drink more than planned	168 (16.02%)	324 (60.56%)	492 (31.06%)
Find it difficult to limit how much you drank	34 (3.24%)	160 (29.91%)	194 (12.25%)
Feel like you needed a drink after you'd gotten up (i.e., before your first meal)	9 (0.86%)	15 (2.80%)	24 (1.52%)
Have “the shakes” (e.g., hands shake so coffee cup rattles)	28 (2.67%)	91 (17.01%)	119 (7.51%)
Feel like you needed larger amounts of alcohol yesterday to feel any effect	42 (4.00%)	66 (12.34%)	108 (6.82%)
Feel like you could not get drunk on the same amount of alcohol that usually gets you drunk	33 (3.15%)	62 (11.59%)	95 (6.00%)

Abbreviations: AIB, alcohol‐induced blackout; SD , standard deviation.

^a Assessed in morning survey only resulting in n = 67 days of missing data on non‐AIB days, n = 20 days of missing data on AIB days.

2.2.2.1. Positive Consequences

Positive consequences (10 items) were assessed during the morning survey only (ω_day = 0.95, ω_person = 0.95). Consequences were taken from the Importance of Consequences of Drinking‐Short Form (Patrick and Maggs 2011) and adapted for daily use. Positive consequences reflected the occurrence of desired outcomes expressed in positive alcohol expectancy measures in previous work (Kushner et al. 1994).

2.2.2.2. Negative consequences

Negative consequences (all types) were assessed in both the morning and evening surveys. In the evening survey, participants were asked, “Since your morning report, did you find out or remember that as a result of drinking yesterday you… (insert consequence item)?”. Most consequences were taken from the Brief Young Adult Alcohol Consequences Questionnaire (B‐YAACQ; Kahler et al. 2005), adapted for daily use. Negative consequences were assigned to one of three distinct types of consequence: common (8 items), uncommon (9 items), and alcohol‐related problems (6 items). Common negative consequences occurred on more than 5% of drinking days and were defined as negative consequences that are relatively acute in nature and do not have great potential for personal harm (ω_day = 0.92, ω_person = 0.87). Uncommon negative consequences occurred on less than 5% of drinking days and were defined based on previous literature, as those considered relatively serious in nature (i.e., sexual, legal, or have great potential for personal harm; ω_day = 0.88, ω_person = 0.80) (Richards, Glenn, et al. 2023). Alcohol‐related problems were those previously identified to fit within the impaired control and physical dependence symptoms subscales of the YAACQ (ω_day = 0.89, ω_person = 0.84) (Read et al. 2006, 2007; Howe et al. 2025; Russell et al. 2025). Alcohol‐related problems reflect dysregulation in a person's relationship with alcohol and form the basis of DSM‐5 AUD criteria (American Psychiatric Association 2013).

2.2.3. Social Context

If participants self‐reported alcohol use on the morning survey, they were asked whether they drank alone or with people yesterday. Only 2.8% of all drinking days involved drinking alone. We therefore did not examine drinking alone versus with others as a potential moderator. If they indicated they drank with people, they were then asked who they drank with (check all that apply). Response options included friends, boyfriend/girlfriend/partner, parent(s), sibling(s), large group, and others. Responses were dichotomized to drinking exclusively with family, friend(s), and/or a romantic partner (0) or with a large group and/or others (1). Responses that included options from both were classified as drinking with a large group and/or others.

We recognize that there are many ways in which the social context could be categorized. The option we used prioritizes (assumed) familiarity of the social group. However, there may be important distinctions between drinking with a family member versus drinking with a friend or partner. Due to the infrequency of reports endorsing drinking with a family member (n = 107 days), of which even fewer occurred exclusively with a family member (n = 28 days), we opted to group family members with friends and partners.

2.2.4. Location

If participants self‐reported alcohol use on the morning survey, they were asked where they drank yesterday (check all that apply). Response options included home (apartment, dorm, house), a friend's place, boyfriend's/girlfriend's/partner's place, party (house party, Greek party), bar/club, restaurant, walking somewhere, major entertainment event (sports, tailgate, concert), and other. Responses were categorized to characterize location type as drinking exclusively at a residential setting (home, friend's place, and/or partner's place; 0), exclusively at a non‐residential setting party, bar/club, restaurant, walking somewhere, major entertainment event, and/or other; (1), or combined residential and non‐residential settings (2). Note that while certain uncommon serious consequences (getting in trouble with the police, driving while intoxicated, getting in the car with an intoxicated driver) are more likely to be reported when drinking occurs outside one's home, we opted to group all residential settings together: (1) because these consequences were reported at very low frequencies (see Table 1), and (2) to maintain analytic parsimony.

2.2.5. Covariates

2.2.5.1. Transdermal Alcohol Concentration Area Under the Curve (TAC AUC)

TAC data procedures have been previously published (Richards, Glenn, et al. 2024; Richards and Russell 2025) and are discussed in detail in the supporting information. TAC data was segmented into “social days” because drinking often extends past midnight and does not fit neatly into a midnight‐midnight calendar day. We used 9:00 am as the boundary for the end of the social day because it matched the time of the morning survey. The current analyses use TAC AUC which is most analogous to drink count and represents the cumulative total biological alcohol exposure experienced by the person that day (Russell et al. 2022). AUC was extracted from each social day with TAC‐positive episode data and calculated using ∑[(𝑇𝐴𝐶_𝑖𝑡+𝑇𝐴𝐶_𝑖, 𝑡+1)/2]*[ℎ𝑜𝑢𝑟𝑠_𝑖, 𝑡+1 − ℎ𝑜𝑢𝑟𝑠_𝑡]. If a day contained multiple TAC episodes, AUC was calculated using all data for the day. TAC AUC was set to 0 if the sensor was worn for 80% or more of the hours of the social day but there were no episodes present (n = 418 days), as this suggested that no drinking had occurred. TAC AUC was left missing if no episodes were present, but the sensor was worn for less than 80% of the hours of the social day (i.e., 9 am–9 am; n = 160 days). Of the 1589 self‐reported drinking days (5 with missing AIB data), TAC was missing on 164 (10.3%) days. Fifty‐two (3.3%) self‐reported drinking days did not have a TAC episode present but remained in the current analyses.

2.2.5.2. Other Substance Use

Each morning of the study, participants were presented with a list of 11 categories of substances and asked to check each substance used the previous day. The option for nicotine was stated as “Nicotine (cigarettes, e‐cigarettes, hookah, chewing tobacco, cigars, etc.).” The option for cannabis was stated as “Cannabis (marijuana, pot, weed, reefer, or hashish).” Nicotine and cannabis were each coded as same‐day substance not endorsed (0) or same‐day substance endorsed (1). Nicotine and cannabis were included as covariates based on previous research showing co‐use with alcohol to be associated with AIBs and/or other alcohol‐related consequences (e.g., Jackson et al. 2020; Lee et al. 2022; Richards, Mallett, Turrisi, Oliver, et al. 2025).

2.2.5.3. Baseline Characteristics

Participants reported on their demographics on the baseline survey. Sex at birth was coded as male (0) and female (1). Participants separately reported on their ethnoracial self‐identification. Responses to these questions were recoded to non‐Hispanic/Latino White (0) or ethnoracial self‐identification minority groups (1).

2.3. Statistical Analysis

All analyses were conducted in Mplus version 8 (Muthén and Muthén 2017). Sample size was determined using Monte Carlo power simulations. A sample size of 175 with 90% compliance had > 99% power to detect small effect sizes (0.1 SDs) at the within‐person level and 74%–96% power to detect small‐to‐medium effect sizes (0.2–0.3 SDs) at the between‐person level. Two‐level negative binomial multilevel structural equation models (MSEM) with Bayesian estimation were conducted. Three sets of analyses were conducted following the same procedures. Our primary analyses (set one) examined fragmentary and en bloc AIBs together as a single variable (any type of AIB). The secondary analyses (sets two and three) were exploratory and examined fragmentary and en bloc AIBs separately. To account for unexplained shared variance, residual covariances among the outcome variables (positive consequences, common consequences, uncommon consequences, alcohol‐related problems) were freely estimated. All models included random intercepts and controlled for TAC AUC, nicotine use, cannabis use, data collection period, sex, and ethnoracial self‐identification. Because none of our hypotheses necessitated random slopes, we did not test for them to preserve model parsimony, to reduce the risk of overfitting, and to maximize statistical power (Matuschek et al. 2017). Observations with missing values for predictors were excluded. We first conducted an initial model without an interaction term to test for the main effects of AIBs on consequences (n = 1402 days). To test for moderating effects of contextual factors on the AIB‐consequence relationship, an interaction term between AIBs and a single contextual factor at the day‐level was included (n = 1311 days for social context moderation and n = 1351 days for location moderation). Social context was dichotomous, whereas location was trichotomous and treated as a continuous variable in the moderation model. An additional set of exploratory analyses was conducted examining a three‐level AIB variable as the primary predictor for consequences. Interclass correlations (ICCs) and between‐ and within‐person SDs were generated from empty multilevel models using R 4.4.1 (see Table S1). We used a 2‐level centering strategy to partition the variance of each day‐level variable into day‐ and person‐levels using R. Raw values were centered on person‐means (creating a day‐level variable) and person‐means were centered on the grand mean (creating a person‐level variable). TAC AUC was z‐scored for interpretability. Variables that were only assessed at baseline were mean‐centered. Model estimates are the means of posterior parameter distributions; significant IRRs were determined using 95% credibility intervals (CIs). CIs that did not contain 1.00 were considered significant.

3. Results

3.1. Descriptive Statistics

Approximately one‐third (n = 535) of all drinking days resulted in an AIB. The evening surveys detected 81 AIBs that were not reported in the morning surveys. Most AIB‐days had only fragmentary AIBs (n = 445, 83.2%) reported. Approximately 16% (n = 87) had both fragmentary and en bloc AIBs reported. Only 3 days (0.6%) had only an en bloc AIB reported. Table S2 shows correlations (computed across all days and participants) between AIBs (any, fragmentary, en bloc) and TAC. Positive alcohol‐related consequences were the most frequent type of consequence reported, followed by common consequences, alcohol‐related problems, and uncommon consequences. Over the 18‐day study period, participants reported an average of about 8.9 (SD = 4.2) drinking days with about 6.6 (SD = 4.1) drinks reported in the morning, 6.1 (SD = 4.4) drinks reported in the evening, and 9.2 (SD = 8.5) drinks reported during drinking episodes. These drinking reports were moderately to strongly correlated with one another (r's between 0.42–0.81, ps < 0.001). Nicotine use was endorsed by 98 participants (56%) at least once and was reported on over 40% of all drinking days (n = 649, 41.7%). Cannabis use was endorsed by 71 participants (40.6%) at least once and was reported on about 20% (n = 316, 20.3%) of all drinking days. Participants experienced an average of approximately 34.5 (SD = 25.4) positive consequences, 10.4 (SD = 10.8) common consequences, 1.1 (SD = 1.8) uncommon consequences, and 5.9 (SD = 6.8) alcohol‐related problems during the study. Table 1 shows the average day‐level number of each type of alcohol‐related consequence and the frequency of each consequence by AIB status. Table S3 shows the frequencies of social context and drinking location by AIB status.

3.2. Main Effects of AIBs on Alcohol‐Related Consequences

Table 2 shows day‐level results and Table S4 shows person‐level results from the MSEMs examining the association between AIBs and alcohol‐related consequences. Table S5 displays the results from exploratory analyses examining the three‐level AIB variable. Days in which any type of AIB was experienced were associated with significantly more consequences of each type compared to days without an AIB. Drinking days resulting in any type of AIB were associated with approximately 15% more positive consequences, 205% more common consequences, 367% more uncommon consequences, and 166% more alcohol‐related problems compared to non‐AIB drinking days. Results from the MSEMs examining fragmentary and en bloc AIBs separately were similar (i.e., same significant associations between primary variables of interest) with one notable exception: en bloc AIBs were not significantly associated with positive consequences.

TABLE 2.

Day‐level results from the multilevel structural equation models examining the association between AIBs and alcohol‐related consequences (n = 1402).

	Any AIB IRR (95% CI)	Fragmentary AIB IRR (95% CI)	En bloc AIB IRR (95% CI)
Positive consequences
AIB	1.15 (1.07, 1.24)	1.15 (1.07, 1.24)	0.96 (0.85, 1.08)
TAC	1.11 (1.08, 1.15)	1.11 (1.08, 1.15)	1.14 (1.11, 1.18)
Nicotine use	1.14 (1.02, 1.28)	1.14 (1.02, 1.26)	1.16 (1.04, 1.29)
Cannabis use	1.11 (1.00, 1.23)	1.11 (1.00, 1.24)	1.11 (1.00, 1.24)
Burst	1.01 (0.95, 1.07)	1.01 (0.96, 1.07)	1.02 (0.96, 1.07)
Common consequences
AIB	3.05 (2.64, 3.52)	3.09 (2.68, 3.57)	1.98 (1.61, 2.50)
TAC	1.31 (1.24, 1.39)	1.31 (1.24, 1.38)	1.54 (1.45, 1.65)
Nicotine use	1.28 (1.03, 1.57)	1.26 (1.01, 1.56)	1.46 (1.15, 1.83)
Cannabis use	0.80 (0.63, 1.03)	0.80 (0.63, 1.02)	0.84 (0.64, 1.07)
Burst	0.99 (0.90, 1.10)	0.99 (0.90, 1.11)	1.02 (0.90, 1.14)
Uncommon consequences
AIB	4.67 (2.89, 8.24)	4.75 (2.96, 7.49)	4.53 (2.56, 8.69)
TAC	1.29 (1.10, 1.52)	1.27 (1.08, 1.54)	1.38 (1.17, 1.71)
Nicotine use	1.98 (0.99, 4.37)	1.99 (1.05, 4.41)	2.54 (1.21, 5.37)
Cannabis use	1.32 (0.62, 3.09)	1.42 (0.60, 2.99)	1.65 (0.73, 3.56)
Burst	0.86 (0.61, 1.23)	0.89 (0.63, 1.32)	0.84 (0.58, 1.26)
Alcohol‐related problems
AIB	2.66 (2.21, 3.16)	2.57 (2.13, 3.13)	1.87 (1.47, 2.39)
TAC	1.29 (1.20, 1.39)	1.3 (1.21, 1.39)	1.45 (1.36, 1.56)
Nicotine use	1.70 (1.26, 2.30)	1.67 (1.25, 2.24)	1.88 (1.45, 2.58)
Cannabis use	0.89 (0.61, 1.19)	0.90 (0.64, 1.22)	0.95 (0.69, 1.30)
Burst	0.95 (0.83, 1.10)	0.96 (0.83, 1.12)	0.97 (0.84, 1.11)

Note: Significant values are bolded (95% CIs do not contain 1.00).

Abbreviations: AIB, alcohol‐induced blackout; CI, credible interval; IRR, incidence rate ratio; TAC, transdermal alcohol concentration.

3.3. Social Context as a Moderator on the AIB‐Consequence Relationships

Table S6 displays the simple slopes by moderator for significant interaction effects. Table 3 shows day‐level results and Table S7 shows person‐level results from the MSEMs examining the moderating effects of social context on the AIB‐consequence relationships. Social context was a significant moderator of the relationships between any type of AIB and (a) common negative consequences and (b) alcohol‐related problems. When drinking occurred exclusively with family, friend(s), and/or a romantic partner, AIBs were associated with a 3.4‐fold increase in common consequences and a 3.0‐fold increase in alcohol‐related problems compared to non‐AIB days. These associations were weaker when drinking occurred with a large group, with AIBs associated with an approximately 2.3‐fold increase in common consequences and a 2.0‐fold increase in alcohol‐related consequences. Results from the MSEMs examining fragmentary and en bloc AIBs separately were similar with one exception: social context was also a significant moderator of the relationship between fragmentary AIBs and positive consequences. However, estimates and 95% CIs varied from the primary analysis examining any type of AIB by only 0.01–0.02.

TABLE 3.

Day‐level results from multilevel structural equation models testing social context as a moderator of the AIB‐consequence relationship (n = 1311).

	Any AIB IRR (95% CI)	Fragmentary AIB IRR (95% CI)	En bloc AIB IRR (95% CI)
Positive consequences
AIB	1.15 (1.07, 1.24)	1.15 (1.06, 1.23)	0.94 (0.82, 1.07)
Social context	1.11 (1.02, 1.20)	1.11 (1.02, 1.20)	1.12 (1.03, 1.21)
AIB*Social context	0.82 (0.67, 1.01)	0.81 (0.66, 0.99)	1.06 (0.75, 1.51)
TAC	1.10 (1.07, 1.14)	1.10 (1.07, 1.14)	1.13 (1.10, 1.16)
Nicotine use	1.09 (0.98, 1.22)	1.09 (0.98, 1.23)	1.10 (0.99, 1.24)
Cannabis use	1.13 (1.02, 1.25)	1.13 (1.02, 1.26)	1.13 (1.01, 1.26)
Burst	1.01 (0.96, 1.07)	1.01 (0.96, 1.08)	1.02 (0.96, 1.08)
Common consequences
AIB	3.04 (2.61, 3.51)	3.09 (2.65, 3.63)	2.14 (1.71, 2.69)
Social context	1.24 (1.05, 1.51)	1.25 (1.06, 1.48)	1.34 (1.14, 1.59)
AIB*Social context	0.52 (0.35, 0.77)	0.51 (0.34, 0.76)	0.42 (0.24, 0.75)
TAC	1.28 (1.22, 1.36)	1.28 (1.21, 1.36)	1.48 (1.39, 1.58)
Nicotine use	1.22 (0.98, 1.57)	1.24 (0.98, 1.55)	1.32 (1.03, 1.70)
Cannabis use	0.80 (0.62, 1.01)	0.80 (0.62, 1.03)	0.83 (0.64, 1.10)
Burst	0.98 (0.87, 1.09)	0.98 (0.88, 1.09)	0.99 (0.88, 1.13)
Uncommon consequences
AIB	5.21 (3.01, 11.53)	4.92 (3.05, 7.88)	4.92 (2.75, 8.92)
Social context	1.34 (0.68, 2.53)	1.45 (0.80, 2.72)	1.63 (0.99, 2.69)
AIB*Social context	0.53 (0.15, 1.93)	0.41 (0.12, 1.54)	0.34 (0.07, 1.37)
TAC	1.23 (1.04, 1.46)	1.23 (1.03, 1.44)	1.28 (1.08, 1.59)
Nicotine use	1.74 (0.94, 3.67)	1.79 (0.98, 3.51)	1.82 (0.89, 3.91)
Cannabis use	1.48 (0.74, 2.78)	1.31 (0.65, 2.73)	1.74 (0.79, 3.75)
Burst	0.85 (0.61, 1.23)	0.87 (0.60, 1.25)	0.84 (0.60, 1.20)
Alcohol‐related problems
AIB	2.66 (2.20, 3.18)	2.61 (2.12, 3.19)	2.05 (1.58, 2.63)
Social context	1.30 (1.03, 1.61)	1.32 (1.05, 1.61)	1.33 (1.10, 1.60)
AIB*Social context	0.52 (0.31, 0.88)	0.48 (0.29, 0.76)	0.46 (0.24, 0.77)
TAC	1.26 (1.18, 1.36)	1.27 (1.19, 1.36)	1.41 (1.32, 1.51)
Nicotine use	1.06 (1.17, 2.16)	1.61 (1.19, 2.20)	1.70 (1.26, 2.23)
Cannabis use	0.87 (0.63, 1.24)	0.89 (0.65, 1.23)	0.96 (0.70, 1.30)
Burst	0.96 (0.82, 1.10)	0.95 (0.83, 1.10)	0.97 (0.84, 1.11)

Note: Social context was coded as (0) drinking exclusively with family, friend(s), and/or a romantic partner or (1) with a large group and/or others. Significant values are bolded (95% CIs do not contain 1.00).

Abbreviations: AIB, alcohol‐induced blackout; CI, credible interval; IRR, incidence rate ratio; TAC, transdermal alcohol concentration.

3.4. Location as a Moderator on the AIB‐Consequence Relationships

Table 4 shows day‐level results and Table S8 shows person‐level results from the MSEMs examining the moderating effects of social context and location on the AIB‐consequence relationships. Drinking location was a significant moderator on the relationship between any type of AIBs and common negative consequences. The relationship between AIBs and common negative consequences was about 4.4‐times greater than non‐AIB days when drinking occurred exclusively in a residential setting. The relationship between AIBs and common negative consequences was about 3.2‐times greater than non‐AIB days when drinking occurred exclusively in a non‐residential setting. The relationship between AIBs and common negative consequences was about 2.5‐times greater than non‐AIB days when drinking occurred in both residential and non‐residential settings. Results from the MSEMs examining fragmentary and en bloc AIBs separately were similar with no exceptions. See Figure 1 and Table S6 for a visualization and IRRs of all significant moderation effects of context on the relationship between any type of AIB and consequences.

TABLE 4.

Day‐level results from multilevel structural equation models testing location as a moderator of the AIB‐consequence relationship (n = 1351).

	Any AIB IRR (95% CI)	Fragmentary AIB IRR (95% CI)	En bloc AIB IRR (95% CI)
Positive consequences
AIB	1.14 (1.06, 1.23)	1.15 (1.06, 1.24)	0.98 (0.86, 1.11)
Location	1.08 (1.04, 1.12)	1.08 (1.04, 1.12)	1.08 (1.04, 1.13)
AIB*Location	0.91 (0.82, 1.00)	0.90 (0.81, 1.00)	0.95 (0.79, 1.12)
TAC	1.1 (1.07, 1.14)	1.1 (1.07, 1.14)	1.13 (1.09, 1.16)
Nicotine use	1.12 (1.00, 1.25)	1.12 (1.00, 1.25)	1.14 (1.02, 1.27)
Cannabis use	1.12 (1.01, 1.25)	1.12 (1.01, 1.25)	1.13 (1.02, 1.25)
Burst	1.01 (0.95, 1.07)	1.01 (0.95, 1.07)	1.01 (0.95, 1.07)
Common consequences
AIB	3.12 (2.68, 3.64)	3.15 (2.70, 3.63)	2.24 (1.82, 2.79)
Location	1.22 (1.12, 1.33)	1.22 (1.13, 1.33)	1.23 (1.14, 1.34)
AIB*Location	0.61 (0.50, 0.74)	0.61 (0.50, 0.74)	0.62 (0.48, 0.82)
TAC	1.28 (1.21, 1.35)	1.27 (1.21, 1.35)	1.46 (1.37, 1.56)
Nicotine use	1.20 (0.96, 1.51)	1.19 (0.96, 1.48)	1.30 (1.03, 1.66)
Cannabis use	0.81 (0.63, 1.03)	0.81 (0.64, 1.02)	0.88 (0.67, 1.14)
Burst	0.99 (0.89, 1.11)	0.99 (0.89, 1.11)	0.99 (0.88, 1.12)
Uncommon consequences
AIB	4.86 (2.68, 8.21)	4.96 (2.82, 8.22)	4.82 (2.57, 9.19)
Location	1.34 (0.97, 1.74)	1.31 (0.96, 1.82)	1.29 (0.98, 1.73)
AIB*Location	0.62 (0.33, 1.25)	0.61 (0.29, 1.29)	0.95 (0.41, 2.03)
TAC	1.20 (1.03, 1.47)	1.24 (1.02, 1.52)	1.31 (1.08, 1.63)
Nicotine use	1.96 (1.06, 4.21)	2.07 (0.97, 4.57)	2.27 (1.07, 4.95)
Cannabis use	1.22 (0.50, 2.71)	1.43 (0.61, 3.13)	1.54 (0.74, 3.63)
Burst	0.87 (0.62, 1.31)	0.88 (0.58, 1.30)	0.80 (0.55, 1.23)
Alcohol‐related problems
AIB	2.69 (2.25, 3.25)	2.62 (2.16, 3.22)	1.96 (1.54, 2.56)
Location	1.11 (1.00, 1.23)	1.13 (1.00, 1.26)	1.14 (1.02, 1.26)
AIB*Location	0.80 (0.61, 1.04)	0.80 (0.61, 1.02)	0.92 (0.67, 1.26)
TAC	1.26 (1.17, 1.36)	1.27 (1.17, 1.36)	1.41 (1.32, 1.51)
Nicotine use	1.63 (1.22, 2.10)	1.59 (1.21, 2.2)	1.81 (1.39, 2.4)
Cannabis use	0.90 (0.63, 1.20)	0.89 (0.61, 1.25)	0.98 (0.71, 1.38)
Burst	0.96 (0.84, 1.09)	0.96 (0.84, 1.11)	0.98 (0.84, 1.14)

Note: Location was coded as (0) drinking exclusively at a residential setting (home, friend's place, and/or partner's place), (1) exclusively at a non‐residential setting (party, bar/club, restaurant, walking somewhere, major entertainment event, and/or other), or (2) combined residential and non‐residential settings. Significant values are bolded (95% CIs do not contain 1.00).

Abbreviations: AIB, alcohol‐induced blackout; CI, credible interval; IRR, incidence rate ratio; TAC, transdermal alcohol concentration.

FIGURE 1.

Incidence rate ratios (IRRs) with 95% credible intervals for significant contextual moderators of the relationship between alcohol‐induced blackouts and other alcohol‐related consequences. All differences between effect sizes are statistically significant.

4. Discussion

We examined the associations between AIBs and four types of consequences and then tested whether these relationships varied by social context and drinking location among a sample of 175 heavy drinking young adults with recent history of an AIB. Our first hypothesis (H1) was fully supported. We observed AIBs (of any type) to be significantly associated with all types of alcohol‐related consequences (positive, common negative, uncommon (serious) negative, alcohol‐related problems) while controlling for TAC and other substance use. These results were generally replicated when distinguishing the type of AIB (fragmentary or en bloc) with one exception. En bloc AIBs were not significantly associated with positive consequences. These findings expand on previous research that suggest AIBs are associated with excess alcohol‐related harms compared to drinking days with equivalent levels of alcohol use without an AIB. Our findings also suggest that fragmentary AIBs were associated with additional positive experiences, but not en bloc AIBs. This contributes to the body of literature suggesting that experiencing negative consequences does not necessarily discourage individuals from continuing risky drinking behaviors, perhaps due to increased positive alcohol‐related experiences (Wicki et al. 2018). This supports the benefit of assessing both positive and negative outcomes associated with alcohol use (and AIB severity) when considering prevention and intervention efforts.

Experiencing increased positive consequences with AIBs may be reinforcing risky drinking behaviors and young adults' motivations to blackout. Additional research is needed to investigate approaches that allow young adults to experience desired positive effects of alcohol (for cases in which the individual is not willing to replace alcohol use with another behavior that may also result in positive outcomes such as having fun or being social) without also experiencing AIBs and other negative consequences. It may be helpful to emphasize the differential magnitudes in which AIBs are associated with positive consequences compared to each type of negative consequence. With an average increase in positive consequences by 15% on AIB days (vs. non‐AIB days), compared to an average increase of 367% for uncommon negative consequences (and increases of 166% to 205% for other types of negative consequences), the balance towards excess harm associated with AIBs is clear. It is also important to note that while we assessed ‘positive’ consequences using a questionnaire developed based on the reported desired effects of alcohol (Kushner et al. 1994), we cannot be sure how these outcomes are perceived by the individual or their peers. Evidence suggests that ‘positive’ consequences are not universally rated as ‘good’ and ‘negative consequences’ are not universally rated as ‘bad’ by college students (Patrick and Maggs 2011). Future research assessing self and peer perceptions of alcohol‐related consequences may help inform interventions aimed to reduce alcohol‐related harms.

Our second exploratory hypothesis (H2) was partially supported. The relationship between AIBs and common consequences varied by social context. Our findings suggest that drinking exclusively with family, friend(s), and/or a romantic partner may strengthen the relationship between AIBs and common consequences, compared to drinking with a large group. Common consequences included several interpersonal items such as “get into an argument with someone” and “become rude, obnoxious, or insulting”. Individuals likely had more opportunities to experience (or be made aware of experiencing) such consequences when drinking with those they are closer with (e.g., friends) than with acquaintances (i.e., large groups). This finding is supported by the Social Ecological Framework of Drinking Contexts and Alcohol‐Related Problems (Freisthler et al. 2014) which posits that different drinking contexts provide differential risks for experiencing alcohol‐related consequences.

The relationship between AIBs and alcohol‐related problems also varied by social context in the same direction. Drinking that occurred exclusively with family, friend(s), and/or a romantic partner strengthened the relationship between AIBs and alcohol‐related problems. The most frequently reported items in this consequence type include “drink more than planned” and “find it difficult to limit how much you drank.” These items (and others) are largely related to the amount of alcohol consumed, which has been shown to be strongly influenced by direct and indirect peer influence and further influenced by the degree of closeness (Borsari and Carey 2001; Ali and Dwyer 2010; Lewis et al. 2011; Leung et al. 2014; Ecker et al. 2017; Mason et al. 2017). This finding also provides evidence that using PBS related to drinking behaviors (e.g., stopping or limiting drinking) may be especially impactful while drinking with family, friend(s), and/or romantic partners. Future research should investigate the influence of peer closeness and drinking norms on these relationships to prevent alcohol‐related harms, including those that may develop into chronic alcohol‐related problems.

Our third exploratory hypothesis (H3) was partially supported. Only the relationship between AIBs and common negative consequences was moderated by drinking location. Our results showed this relationship was strongest when drinking occurred exclusively at a residential setting, followed by exclusively at a non‐residential setting, and weakest when drinking occurred at both residential and non‐residential settings. There are several possible explanations for this finding. Previous research showed that use of PBS differed by location and that higher PBS use weakened the AIB‐negative consequence relationship (Lewis et al. 2011; Richards, Turrisi, Glenn, Mallett, et al. 2025). It is possible that the young adults in this study used fewer PBS while drinking in environments they felt safer in (e.g., their home) compared to less familiar environments. Research has shown that the presence of hard alcohol and illicit drugs, availability of food, being around other intoxicated individuals, and social motivations are each associated with self‐reported alcohol consumption and/or objective alcohol intoxication (BrAC) (Clapp and Shillington 2001; Clapp et al. 2007). Future research considering more fine‐grained details about the location in which drinking occurs may provide valuable insight into specific features of the drinking environment that may increase AIB risk and other alcohol‐related consequences to serve as targets of harm‐reduction interventions.

This study was largely guided by The Social‐Ecological Framework of Drinking Contexts and Alcohol‐Related Problems, which posits that individual characteristics such as sex and ethnoracial identification may have a meaningful influence on alcohol‐related consequences (Freisthler et al. 2014). With one exception, our findings generally did not support this. We observed one significant association between sex and common negative consequences, suggesting that females may experience higher rates than males. No other types of consequences were associated with sex. Ethnoracial self‐identification was not significantly associated with any type of consequence. It is possible that these overall null demographic findings may be due to the study sample, design, and/or setting.

This study has several limitations. First, the sample consisted of 18–23‐year‐olds who were primarily non‐Hispanic White undergraduate students enrolled in a single university. It is possible that the drinking environment and related risks at this university differ from other institutions (e.g., fewer opportunities for driving while intoxicated). Additional research with a more diverse sample, including non‐student young adults, is needed. Second, this study was limited to six social weekends spanning one semester. Future research spanning longer periods of time, including weekdays and the full range of seasons, are needed to provide additional insight into if or how AIBs and associated consequences change over time. Third, it is possible that the sensors missed lower intensity drinking days (Barnett, Meade, and Glynn 2014). However, our data show that this is unlikely to be a major concern, as the sensors correctly captured 96% of self‐reported drinking days on days in which both self‐report and TAC data were available (i.e., sensitivity). Fourth, uncommon, serious negative consequences were experienced infrequently which may have limited our ability to detect significant moderation effects between AIBs and uncommon consequences. Fifth, these analyses were unable to establish directionality between AIBs and other consequences. It is possible that consequences were experienced before an AIB occurred, rather than after. Experiencing other consequences early in a drinking event, in particular positive consequences, could influence the likelihood of experiencing an AIB, rather than vice versa. Future research should investigate the relative timing in which AIBs and other consequences occur. Sixth, we were unable to examine more nuanced associations between different social contexts (e.g., family vs. friends) due to low numbers of reported drinking episodes occurring exclusively with family members (n = 28). Additionally, no criterion was presented to participants for defining a ‘large group’. It is possible that ‘large group’ was selected when drinking with a large group of close friends, rather than in a less familiar social context. Future studies should provide definitions to participants to reduce potential misclassification. Seventh, screening survey completion rates were low (~9%), though similar to other published studies using similar recruitment methods and study designs (Richards, Glenn, et al. 2024). The high non‐response rate may be due to participants self‐selecting to not participate due to disinterest in wearing an alcohol sensor over an extended period of time. Lastly, we examined number of consequences, which may not fully capture the meaningfulness or intensity of those experiences on a given day.

5. Conclusion

Among a sample of ‘risky’ drinking young adults who completed six weekends of intensive data collection, AIBs were significantly associated with experiencing more positive and negative (common, uncommon, alcohol‐related problems) consequences. AIB days in which drinking occurred exclusively with family, friend(s), and/or a romantic partner were more strongly associated with common negative consequences and alcohol‐related problems compared to AIB days in which drinking occurred with a large group. AIB days in which drinking occurred exclusively at a residential setting were most strongly associated with common consequences compared to AIB days in which drinking occurred at non‐residential settings. Our findings support the notion that the context in which drinking occurs is an important consideration for reducing certain types of alcohol‐related harms.

Funding

This work was supported by National Institute on Alcohol Abuse and Alcoholism, R21AA031528, F31AA031607 National Cancer Institute, P30CA225520.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Table S1: Interclass correlations (ICC) and standard deviations (SD) of primary predictor and outcome variables.

Table S2: Correlations between alcohol‐related predictors.

Table S3: Frequencies of moderators by alcohol‐induced blackout (AIB) status.

Table S4: Person‐level results from the multilevel structural equation models examining the association between AIBs and alcohol‐related consequences.

Table S5: Results from the multilevel structural equation models examining the association between AIB type as a three‐level variable and alcohol‐related consequences.

Table S6: Simple slopes of the relationships between any type of AIB and alcohol‐related consequences by significant moderators.

Table S7: Person‐level results from multilevel structural equation models testing social context as a moderator of the AIB‐consequence relationship.

Table S8: Person‐level results from multilevel structural equation models testing location as a moderator of the AIB‐consequence relationship.

Data Availability Statement

The data that support the findings of this study are openly available in NIAAA Data Archive at https://nda.nih.gov, reference number https://doi.org/10.15154/b5tb‐1h3.