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. 2019 Sep 10;6(3):187–195. doi: 10.1089/vio.2018.0023

Alcohol Use and Intimate Partner Violence Among Community College Women: An Exploration of Protective Factors

Judelysse Gomez 1,✉, Lindsay Orchowski 2, Deborah N Pearlman 3, Caron Zlotnick 2,,4
PMCID: PMC6744945  PMID: 31528653

Abstract

Little is known regarding the association between alcohol use and violence among community college women. Accordingly, this study investigated daily-level associations between alcohol use and intimate partner victimization (IPV) in a sample of young women (ages 18–24) in a community college setting, and the potentially protective role of education aspirations and living with family. Using a calendar-based assessment, women enrolled in a large community college (N = 212) completed past-month surveys of IPV and alcohol use. Unadjusted Generalized Estimating Equations showed nonsignificant positive associations between alcohol consumption (any alcohol use and number of drinks) and IPV at the daily level. Adjusted models showed a slight (but nonsignificant) increase in the odds of experiencing IPV on a drinking day. Those reporting a family income above $20,000 were at increased risk of experiencing violence. Living with family and wanting to attain a master's or doctoral degree reduced the risk of experiencing IPV on drinking days. Although the literature suggests that drinking among 4-year college women elevates the odds of experiencing IPV, our findings suggest the importance of examining contextual variables when understanding risk among community college women. Particularly, the role of family and educational aspirations may serve as protective factors in the association between alcohol use and IPV on a daily basis. As this is the first day-level study of IPV and alcohol use among community college women, further research is warranted to better explicate these findings.

Keywords: intimate partner violence victimization, alcohol use, family, protective factors, community college women

Introduction

According to the National Intimate Partner and Sexual Violence Survey (NIPSVS), between 22% and 47% of women experience severe physical intimate partner victimization (IPV) and psychological aggression, respectively, in their lifetime (Breiding et al. 2014). IPV is defined as any incident of physical, psychological (including coercion), sexual violence/aggression and/or stalking by a current or past intimate partner (Breiding et al. 2015). Numerous studies document a strong association between IPV and a range of mental health consequences such as depression, anxiety, post-traumatic stress symptomatology and suicidality (Black et al. 2011; see Dillon et al. 2013). IPV is also associated with attaining fewer years of formal education and lower income earnings across the lifespan (Adams et al. 2013).

Young adult women are at particularly high risk for IPV (Acevedo et al. 2013; American College Health Association 2015; Capaldi et al. 2012; Halpern et al. 2009; Parks et al. 2008; Reingle et al. 2012; Stöckl et al. 2014). Numerous studies document moderate to high rates of IPV among college women (American College Health Association 2015; Coker et al. 2015; Shorey et al. 2015; Straus 2004), whereas far less research has focused on IPV specifically among women enrolled in community college (Daley and Noland 2001; Trieu et al. 2013; Voth Schrag and Edmond 2018). What the data do appear to show is that the rate and severity of IPV among community college women is comparable to that of women enrolled in 4-year colleges, with 16–44% of community college women reporting a history of some form of physical, verbal, or emotional violence in their relationships (Daley and Noland 2001; Voth Schrag and Edmond 2018a,b).

Research examining IPV among community college women is warranted for several reasons. According to the American Association of Community Colleges (AACU) (2017), community college students make up almost half (41%) of all undergraduate students in the United States. Further, women attending community college tend to differ from their peers enrolled at 4-year colleges in a number of significant ways: They tend to be older, live with dependent children, work full- or part-time, experience financial need, worry about having to provide for their families, and experience difficulties paying their bills on time (Center for Community College Student Engagement [CCCSE] 2017; Eisenberg et al. 2016; Voth Schrag and Edmond 2018a,b). Importantly, the accumulation of psychosocial stressors is associated with increased risk for IPV among young adults (Schwabb-Reese et al. 2016; Velazquez et al. 2011).

Community college students also report high levels of untreated mental health conditions (Eisenberg et al. 2016)—which can increase risk for IPV (Capaldi et al. 2012)—and community college students are often not provided with psychoeducational workshops or prevention programs as a part of their college orientation (Lenk et al., 2015). This is problematic, as recent research suggests that the college years might be a time of increased exposure to risk (e.g., IPV, problematic drinking, etc.), potentially setting the stage for related harms such as physical injury and trauma, and adverse mental health outcomes (e.g., depression, anxiety, and suicidality) over the course of the lifespan (Carter et al. 2010; Hingson et al. 2017a,b). Some studies suggest that community college women report greater health and mental health-related difficulties such as physical health complaints and depressive symptomatology than their male and 4-year college counterparts (Decker et al. 2014; Nelson et al. 2009; Sanem et al. 2009; Simons-Morton et al. 2017; Trieu et al. 2013). The association of these factors with IPV (Simons-Morton et al. 2017) underscores the importance of research focused on community college students.

Foa et al.'s (2000) Environmental Model for the Cessation of IPV provides a roadmap to understand the intrapersonal, interpersonal, and environmental risk and protective factors associated with IPV among women. Family resources and formal educational attainment serve as two important protective factors for IPV (Acevedo et al. 2013; Sullivan et al. 2012). For example, one mixed-methods study conducted among community college women suggested that although IPV was related to lower levels of social support, the presence of school- and family-based supports (e.g., financial and emotional support, help with childcare, etc.) were particularly helpful in navigating academic and occupational impairments, and psychological (well-being) consequences of IPV (Voth Schrag and Edmond 2018b). Perpetrators of IPV rely on controlling their partners' behaviors (Albaugh and Natua 2005), whereas educational attainment is an important way in which women resist and overcome abuse (Voth Schrag and Edmond 2017). Studies examining inter- and intrapersonal risk factors for IPV among community college women must also take into account whether women are raising children, as the benefit of higher educational attainment from IPV diminishes with higher numbers of children (Acevedo et al. 2013).

Alcohol use and IPV

Alcohol use is a salient intrapersonal risk factor for IPV (Adams et al. 2013; Capaldi et al. 2012; Devries et al. 2014; Okuda et al. 2015; Shorey et al. 2011). Although community college students, in general, tend to engage in lower levels of problematic drinking (e.g., binge drinking defined as four or more drinks for women; five or more for men within a 2-h period) than their 4-year counterparts (National Institute on Alcohol Abuse and Alcoholism [NIAAA], n.d.; Simons-Morton et al. 2017), examining the association between IPV and alcohol use among young adults is especially important as risky drinking reaches peak rates in emerging adulthood (Chen et al. 2004; Grucza et al. 2009).

According to cross-sectional research, higher past-month estimated blood alcohol concentration is associated with IPV among college students (Roudsari et al. 2009). Longitudinal research also suggests that experiences of victimization increases risk for subsequent alcohol use (Devries et al. 2014), and meeting clinical criteria for alcohol abuse doubles the odds of reporting victimization (Kilpatrick et al. 1997). Women ages 18 or older who report past-year victimization are six times more likely to meet criteria for moderate to severe past-year problem drinking, compared with women without past-year IPV (La Flair et al. 2012). Although alcohol use can influence risk for IPV through several potential pathways (Lipsey et al. 1997; Rothman et al. 2011; Shorey et al. 2011), findings support the self-medication model, such that alcohol may be used as a way to mitigate the associated emotional sequelae (Chilcoat and Breslau 1998; Kilpatrick et al. 1997; Testa et al. 2003).

Evidence for a proximal association between alcohol use and IPV comes from day-level studies of married adults (Leonard and Quigley 1999) and college students (Moore et al. 2011; Parks et al. 2008; Shorey et al. 2011, 2014; Stappenbeck et al. 2016), incarcerated adult women (Stuart et al. 2003), and adolescents presenting to the emergency department (Rothman et al. 2012). Rothman et al.'s (2012) day-level analysis of adolescents presenting to the emergency department indicated that women had higher odds of psychological IPV on drinking days compared with nondrinking days. Similarly, studies among 4-year college students found that the odds of IPV perpetration (men) and victimization (women) increased on days when participants reported drinking and as a function number of drinks, heavy drinking, and on drinking days compared with nondrinking days (Shorey et al. 2014, 2015). These day-level studies provide an important opportunity to examine within-person effects of alcohol use on risk for IPV, whereas to our knowledge there are no day-level studies examining alcohol use and IPV among community college women.

There are several possible explanations for why alcohol use on a given day may increase risk for IPV. Women who consume alcohol may be targeted for IPV by their partner as a result of decreased ability to resist against aggressive behavior when intoxicated (Mohler-Kuo et al. 2004). The day-level association between alcohol use and IPV may also be explained by the Proximal Effects Model, which suggests a causative link between alcohol consumption and IPV (Crane et al. 2015). For example, the psycho-physiological (inhibitory) effects of alcohol consumption attenuate top-down processes such as decision making, emotional regulation, impulse control, and reductions in empathy, placing individuals at risk for IPV (Chermack and Taylor 1995; see Crane et al. 2015). Taken together, reductions in tension/anxiety (Sayette 1993), impulse control (Giancola 2000; Sher et al. 1996), as well as impairments in judgment and decision making (Curtin and Fairchild 2003) can make it difficult to process and respond to complex cues in the environment (Steele and Josephs 1990), thereby increasing risk for IPV.

The present study

This study sought to conduct a day-level analysis of the association between alcohol use and IPV among community college women. Although research among 4-year undergraduate college students suggests a robust relationship between IPV and alcohol use (Chen et al. 2004; Shorey et al. 2011), to our knowledge, no research has been conducted to examine the association between past-month alcohol use and IPV among community college female students in the United States. It is possible that the association between alcohol use and intimate partner violence is similar to 4-year undergraduate college students, whereas variation in sociodemographic characteristics and risk profiles between community college students and their peers at 4-year colleges may result in important differences in the ways that alcohol use influences risk for IPV.

As highlighted by the Dynamic Developmental Systems Perspective (Capaldi et al. 2012), there are a multitude of factors at the interpersonal, intrapersonal, and environmental level that need to be considered when attempting to reduce individuals' risk of experiencing IPV (Capaldi et al. 2012; Foa et al. 2000). Thus, in this study, we also explored the protective role of educational goals (i.e., a desire to attain a master's or doctoral degree) as well as social resources (i.e., living with family and/or dependent children) as protective factors for IPV. As discussed by Shorey et al. (2014), understanding risk and protective factors for IPV is an essential component in the development and improvement of IPV intervention programs, and should not be utilized as evidence suggesting that those exposed to IPV are to blame for the violence inflicted on them. Several specific hypotheses were proposed:

Hypothesis #1: IPV victimization on a given day would be more likely to occur on drinking days.

Hypothesis #2: IPV victimization on a given day would be associated with a greater number of drinks per drinking day.

Hypothesis #3: Educational aspirations and living with family will be related to a lower likelihood of experiencing IPV victimization on a given drinking day.

Methods

Participants

Participants included 212 women, between 18 and 24 years of age, attending a large Northeastern community college who agreed to participate in a study on their social, health, and dating experiences. To be included in the study, women had to be enrolled at one of the six campuses of the community college. Participants were, on average, 19.6 years of age (standard deviation [SD] = 1.7) and predominantly heterosexual (89.4%; Table 1). Slightly more than one-third of the women self-identified as Latinx (35.4%, n = 75). Other participants were non-Hispanic/Latinx White (33.0%, n = 70), non-Hispanic/Latinx Black (17.4%, n = 37), or other non-Hispanic/Latinx racial/ethnic group or multiracial (21.9%, n = 30). Twenty-three percent of women reported a current annual family income below $20,000 and most were living with family members at the time of the survey (78.8%). Current marital status was as follows: 93.4% of the sample self-identified as non-married (N = 197), and 6.6% self-identified as co-habiting, married, or widowed (N = 14). Participant demographics are listed in Table 1.

Table 1.

Sample Characteristics

  Total sample IPV victimization past 30 days  
Characteristics % (n), N = 212 No, 79.2% (n = 167) Yes, 20.8% (n = 44) pa
Age       0.65
 18–20 75.5 (160) 79.9 (127) 20.1 (32)  
 21–24 24.5 (52) 76.9 (40) 23.1 (12)  
 Age (in years), mean (SD) 19.6 (1.68)      
Latinx       0.90
 No 64.6 (137) 79.4 (108) 20.6 (28)  
 Yes 35.4 (75) 78.7 (59) 21.3 (16)  
Sexual orientation       0.06
 LGBQ 10.6 (22) 63.6 (14) 36.4 (8)  
 Heterosexual 89.4 (186) 81.1 (150) 18.9 (35)  
Educational goalsb       0.06
 Bachelor's degree or less 63.2 (134) 75.2 (100) 24.8 (33)  
 Master's or doctorate degree 36.8 (78) 85.9 (67) 14.1 (11)  
Family income       0.28
 ≤$20,000 23.2 (49) 75.5 (37) 24.5 (12)  
 >$20,000 27.5 (59) 74.1 (44) 25.9 (15)  
Unknown 49.3 (104) 83.7 (87) 16.4 (17) 0.006
Living arrangementsc
 Lives with nonfamily members or alone 21.2 (45) 64.4 (29) 35.6 (16)  
 Lives with family members 78.8 (167) 83.1 (138) 16.9 (28)  
Any alcohol use (past 30 days)       0.0001
 No 51.0 (107) 89.7 (96) 10.3 (11)  
 Yes 49.0 (103) 68.0 (70) 32.0 (33)  
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a

Chi-squared tests of independence for categorical variables in relationship to IPV victimization.

b

Educational goals: HS diploma, some college or technical school, 2-year associate degree, or 4-year bachelor's degree (0) versus master's or doctorate degree (1).

c

Living arrangements: lives with nonfamily members (friend, roommate, spouse/partner, or alone) (0) versus parents, other relatives, or own children (1).

LGBQ, lesbian, gay, bisexual, questioning; SD, standard deviation.

Data source: Person-level data file. Sample size varies due to missing data.

Procedures

All procedures were approved by the Institutional Review Board. Participants were recruited through print advertisements posted on campus. The study was advertised as a study of social and dating experiences among community college women. Surveys were administered in a private on-campus computer lab by a trained female Research Assistant. Demographic assessments were administered on a computer, via commercially available online survey software. Calendar measures were administered by the Research Assistant on a pencil and paper questionnaire. Participants were compensated $25 for their time and were provided with a list of campus and local resources. Participation took ∼1 h.

Measures

Demographics

Participants reported their age, sexual orientation, race/ethnicity, living arrangements, level of education, educational goals, and current family income on a short questionnaire. Some women did not know their family income. As such, family income was coded as a categorical variable, including the categories of: $20,000 per year or less or greater than 20,000 per year, or as “Unknown.”

Alcohol use

Past-month alcohol use was assessed with the timeline follow back (TLFB), a 30-day calendar grid that measures the frequency and intensity of alcohol consumption (Sobell and Sobell 1995). The Research Assistant worked with the participant to mark holidays and any other important dates over the past month with the goal of enhancing recall of daily alcohol use. Participants were next provided with a definition of a standard drink, and they were instructed to indicate the number of standard drinks consumed each day. The TLFB demonstrated reliability and validity across numerous studies and populations (see Sobell and Sobell 2003 for a review).

Intimate partner violence

Following the procedures reported by Rothman et al. (2012), an adapted TLFB procedure was utilized to assess experience of IPV over the past month. Participants were provided with a list of 25 items representing five subtypes of IPV (i.e., physical, severe physical, sexual, psychological, or invasion of privacy/harassment), and they were asked to indicate whether they experienced any of those forms of violence on a given day. Eighteen of the items were derived from the Safe Dates Dating Violence Acts Scale (Foshee et al. 1998, 2009), which has excellent reliability (Foshee et al. 2008), and seven additional items were included to assess stalking, threatening behavior, and invasion of privacy by a dating partner. Participants were provided with a 30-day calendar, and a card listing the 25 forms of violence, with a number listed next to each. Participants were instructed to write the number corresponding to each behavior they experienced from a dating partner each day. The validity of the TLFB procedure for collecting sensitive information relating to IPV is excellent (Fals-Stewart et al. 2003; Lam et al. 2009).

Data analysis

Two datasets were used: one person-level (wide) dataset for describing the sample, and one multiple-record (long) event-level dataset reflecting drinking and IPV at the daily level. Both these datasets were gleaned from participants' calendar entries. Data were analyzed by using SAS (version 9.4) to examine the association between risk and protective factors for IPV. First, a series of χ2 analyses were conducted to assess bivariate relationships between predictor variables and IPV. We estimated the unadjusted effect of women's drinking on IPV and then adjusted for all other study covariates. A Generalized Estimating Equation model was produced with a binomial distribution, exchangeable correlation structure, and logit link (hereafter called logistic GEE) to examine whether any alcohol use per day (Model 1) and number of drinks per drinking day (Model 2) were associated with IPV on a given day, controlling for other covariates (GEE; Zeger and Liang 1986). In analyses that controlled for number of drinks per day, the variable was square root transformed for interpretability of beta coefficients as number of drinks per day had a negatively skewed distribution.

Results are reported as odds ratios since the outcome was rare (prevalence <10%). Analyses were conducted by using all available data and an assumption of covariate dependent missingness (i.e., that differences in rates of assessment completion were accounted for by adjusting for covariates).

Results

Sample characteristics at the Person Level

One-fifth of participants (21%, n = 44) were victims of IPV in the past month. The most common form of IPV was psychological violence, which included being socially shamed. Thirty-four percent of women reported physical violence, such as being hit, choked, or beaten up, excluding sexual violence/rape. A full list of IPV experiences among participants is provided in Table 2. Among women who reported IPV victimization in the past month, the number of days with victimization ranged from 1 to 13, with 27.2% reporting 1 day (N = 12), 25% reporting 2–3 days (N = 11), 25% reporting 4–6 days (N = 11), and 22.7% reporting 7–13 days with victimization in the past month (N = 10). IPV in the past 30 days did not vary by age, race/ethnicity, or current annual family income.

Table 2.

Past-Month Intimate Partner Victimization

  N %
Any type of IPV 44 20.8
Psychological IPV
 Insulted, sworn at 32 72.7
 Nasty rumors circulated 6 13.6
 Made to feel afraid 5 11.4
 Stalked 5 11.4
 Destroyed (or tried to destroy) property or broke into cell phone, email 4 9.1
 Perpetrator threated suicide or hurt self if relationship ended 1 2.3
Physical IPV
 Hit with fist, slapped, kicked, bitten, choked, slammed (or held) against a wall, beaten up 15 34.1
 Pushed, grabbed, or shoved 4 9.1
 Forced to have sex (or do sexual things) against one's will 4 9.1
 Required medical attention for hurt or injury 1 2.3
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IPV, intimate partner victimization.

Data source: Person-level data file.

Initial analyses using chi-square tests showed that living with family members decreased the likelihood of IPV, χ2 (2, N = 212) = 7.49, p < 0.01. Further, any alcohol use per day increased the risk of IPV, χ2 (2, N = 210) = 15.00, p < 0.001. Of the women reporting any IPV in the past 30 days, 75% reported drinking on one or more days (n = 33), with an average of 11.2 drinking days in the past month (SD = 13.2).

IPV victimization at the day level

The total number of days of data submitted on the 30-day calendar across the sample was 6360. Of the total number of days recorded, 191 (3.0%) were classified as IPV days. Of these days, 122 days included multiple forms of psychological denigration (being insulted, sworn at, and a victim of nasty rumors), and 33 days (17.3%) included stalking. One or more forms of physical violence, such as being grabbed, shoved, slapped, bitten, hit, kicked, slammed into a wall, choked, or being beaten up, occurred on 59 of the 191 days (30.9%) where IPV was reported. Women reported being raped on 13 of 191 days (7%) where IPV was reported.

Any alcohol use, potential protective factors, and IPV victimization (Hypotheses 1 and 3)

Same-day alcohol use was not associated with IPV in the unadjusted logistic GEE model (Table 3, Model 1, Step 1). In the model adjusted for all study covariates (Model 1, Step 2), there was a positive (although not significant) association between same-day alcohol use and IPV. A current annual family income at or below $20,000 a year was associated with a lower likelihood of IPV (adjusted odds ratio [AOR]: 0.35; 95% confidence interval [CI]: 0.14–0.86). Similarly, living with family members (AOR: 0.37; 95% CI: 0.15–0.89) and setting high educational goals (AOR: 0.30; 95% CI: 0.14–0.67) were associated with decreased risk, indicating a 63% and 70%, respectively, lower likelihood of victimization on a given day.

Table 3.

Predictors of Intimate Partner Violence at the Daily Level

Variable B SE B OR 95% CI
Model 1: Predictors of IPV victimization adjusted for same-day alcohol use at the daily level
 Step 1
  Same-day alcohol use 0.64 0.39 1.90 0.88–4.10
 Step 2
  Same-day alcohol use 0.65 0.37 1.92 0.93–3.98
  Age 21–24 −0.18 0.45 0.84 0.34–2.06
  Latinx 0.24 0.36 1.27 0.63–2.56
  Lives with parents, other relatives, or own children* −1.00 0.46 0.37 0.15–0.89
  Family income ≤$20,000* −1.06 0.46 0.35 0.14–0.86
  Family income unknown −0.41 0.45 0.66 0.27–1.61
  Educational goals: master's or doctorate degree * −1.19 0.40 0.30 0.14–0.67
Model 2. Predictors of IPV victimization adjusted for number of alcohol drinks at the daily level
 Step 1
  No. of drinks per drinking day 0.32 0.20 1.38 0.93–2.03
 Step 2
  No. of drinks per drinking day 0.32 0.19 1.38 0.95–1.99
  Age 21–24 −0.13 0.46 0.88 0.36–2.15
  Latinx 0.25 0.36 1.28 0.63–2.59
  Lives with parents, other relatives, or own children* −1.01 0.45 0.36 0.15–0.87
  Family income ≤$20,000 −0.42 0.46 0.65 0.27–1.61
  Family income unknown** −1.21 0.40 0.30 0.14–0.65
  Educational goals: master's or doctorate degree * −1.02 0.46 0.36 0.15–0.88
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Reference groups: ages 18–20 years; non-Latinx race/ethnicity; lives with nonrelatives; family income >$20,000; educational goals HS diploma, some college or technical school, 2-year associate degree, or 4-year bachelor's degree. Count of number of alcohol drinks was square root transformed. Model accounted for the day of report (0–30) on the TLFB 30-day calendar.

*

p < 0.05; **p < 0.01.

CI, confidence interval; TLFB, timeline follow back.

Data source: Multiple-record data file.

Number of drinks per day, potential protective factors, and IPV victimization (Hypotheses 2 and 3)

Accounting for other variables in the model, the number of alcohol drinks consumed on a given drinking day was marginally associated with IPV on a given day. Living with family members and setting high educational goals were associated with decreased risk (Table 3, see Model 2 Step 2). Women whose income was unknown had lower odds of IPV compared with women with family incomes above $20,000 a year (Table 3, see Model 2 Step 2).

Discussion

The present research examined risk and protective factors for IPV among a sample of young adult women attending community college. Approximately 21% of the community college women in this study reported some form of IPV over the past month. For those experiencing violence in the past 30 days, psychological forms of IPV were the most common (being insulted or sworn at), followed by physical forms of IPV (being hit by partner). To our knowledge, this is the first study focused on both risk (alcohol use) and protective factors (living with family and educational goals) for IPV among community college women.

Given the well-developed literature examining alcohol consumption and IPV among 4-year college students, this study advances science by conducting a day-level analysis of the association between alcohol use and IPV among community college women. That is, on a given drinking day, does any alcohol use and number of drinks increase the risk of experiencing IPV? Contrary to hypotheses, although any alcohol use and increasing number of drinks on a drinking day elevated the risk for experiencing IPV, these associations were not statistically significant. This was a surprising finding as previous research examining day-level associations between alcohol use and IPV among 4-year college students suggests that drinking is a risk factor (Shorey et al. 2011).

Although it is not clear why prior findings documenting day-level associations between alcohol use and IPV were not replicated, it is possible that varying sociodemographic contexts between community college and 4-year college students may influence the association between alcohol use and IPV. Moreover, our sample reported relatively low rates of alcohol use in the past month, something that has not been examined among this specific group of women. More research that compares alcohol use prevalence rates between 4-year and community college women, as well as the association between alcohol use and IPV among community college students is warranted. In fact, the 2017–2021 Strategic Plan of the National Institute on Alcohol Abuse and Alcoholism (2017) prioritizes the development of intervention strategies for young adults who are not enrolled in a 4-year college.

Although Hypothesis #1 and Hypothesis #2 were not supported, several notable findings were revealed regarding protective factors for IPV (Hypothesis #3). Specifically, living with family was associated with reduced odds of experiencing IPV. These findings, combined with previous studies (Voth Schrag and Edmond 2017, 2018b), among a community college sample provide a complex picture of social/family support as they relate to IPV and call for carefully examining the quality of these resources (Capaldi et al. 2012). As some research suggests that family may not always be a source of support for women who experience IPV (Tsui and Santamaria 2015), in-depth research is needed to understand whether community college students who experience IPV while living with family receive the support they need.

Consistent with previous findings (Acevedo et al. 2013), we found that educational level was not associated with IPV, whereas educational aspirations (defined as a desire to attain a master's or doctorate degree) were associated with reduced odds of experiencing IPV. IPV victimization can limit a young woman's educational aspirations, especially when violence is exerted as a control tactic to limit their growth and mobility; thereby keeping women potentially dependent on their partners (Tsui and Santamaria 2015). Women who experience sexual coercion within an intimate relationship also report lower levels of self-efficacy in their educational career (Albaugh and Natua 2005).

More research is needed to understand the mechanisms through which educational aspirations may serve as a protective factor against IPV; it is possible that having and meeting educational and career goals may provide women with a sense of empowerment. Moreover, pursuing and attaining these goals might expose women to social contexts outside of the abusive milieu where they can find support and help when experiencing IPV (Foa et al. 2000; Tsui and Santamaria 2015, 2018b; Voth Schrag and Edmond 2017). Exposure to social supports outside of the immediate context of abuse might help women access and accumulate recourses (Foa et al. 2000; Tsui and Santamaria 2015). From a strengths-based perspective, understanding the ways in which women negotiate, survive in, and navigate abusive relationships can help in identifying intrapersonal-based factors that can be useful in helping women both meet their academic goals and increase their safety (Albaugh and Nauta 2005).

Finally, it was notable that in the model adjusted for same-day alcohol use at the daily level, reporting a family income at or below $20,000 was associated with lower odds of experiencing IPV (as compared with those with higher reported income), independent of other study predictors. This finding is contrary to previous studies suggesting that financial stress is positively linked to IPV (Capaldi et al. 2012; Schwabb-Reese et al. 2016). Nearly three-fourths of community college women in our sample in the lowest income group or whose family income was unknown were living with parents or other relatives (71.9%) as compared with 28.1% of their higher income peers. Although speculative, it is possible that community college women in our sample with the economic resources to live apart from family resided in living situations that increased their vulnerability to IPV, such as living with a controlling partner, or with roommates who provide limited social support. Moreover, living away from family may be associated with greater exposure to drinking and potentially risky environments (Marzell et al. 2015). Living with family may function as an important protective factor mitigating the risks associated with experiencing economic and financial hardship, and/or alcohol use and IPV among community college women.

Limitations and implications for future research

Several limitations should be noted. First, given the cross-sectional nature of the present data, analyses cannot speak to the temporal link between alcohol use and IPV. On a given drinking day, it is possible that alcohol use preceded IPV and it is also possible that IPV preceded alcohol use. Past research indicates that alcohol use both precedes and follows IPV (Devries et al. 2014; Kilpatrick et al. 1997; La Flair et al. 2012; Testa et al. 2003). Second, it is possible that we did not find an association between alcohol use and IPV because women in our sample reported low levels of drinking and IPV. The study garnered more than 6000 days of calendar-based data, whereas future research with larger sample sizes is needed to further probe the extent to which daily alcohol use may increase risk for IPV among community college women, and understand how protective factors may modify the relationship between alcohol consumption and IPV.

Further, there is considerable heterogeneity in the factors that contribute to risk for IPV among community college women, specifically, and young women, more broadly. Future studies that utilize latent profile analysis to examine patterns of risk for IPV may be useful in understanding patterns among risk and protective factors for IPV. Third, this study did not include an assessment of self-efficacy. Thus, it may be the case that the women in our sample who reported wanting to pursue a master's and/or doctoral degree would report higher self-efficacy than those who did not report such career aspirations. Including a measure of self-efficacy in future research can help to better understand why educational aspirations may serve as a protective factor for IPV.

Fourth, given the potential for bias in analyses that exclude those who do not report income data, our regression models included a separate category of women who reported their income as “unknown” (Kim et al. 2007). This is a challenge for many survey-based studies; thus, future studies examining IPV among community college women should consider additional measures of economic well-being, such as home ownership and food security.

Fifth, most of the community college women in our sample identified as heterosexual. As such, present findings cannot be generalized to Lesbian, Bisexual, or Queer/Questioning women. Further, our findings cannot be generalized to Trans* women as we did not explicitly ask for self-reported gender identity (cisgender or Trans*). Finally, this study assessed marital status, but it did not include an assessment of relationship status over the past 30 days. In future studies, it would be ideal to examine the intersection of alcohol use and IPV victimization among only those who reported a dating relationship or intimate relationship in the past month.

Conclusion

This study represents a step forward in understanding how living with family and/or dependent children, and educational aspirations, act as potential protective factors for IPV among a sample of young adult women attending community college. These findings may inform the development and expansion of resource networks in the service of reducing IPV and its effects among community college women. One way to do this could be by creating context-specific/relevant educational programming around the risks of IPV among college age women, how this is related to educational attainment, and how factors such as adequate support at the interpersonal and college level might help reduce the risks involved.

Acknowledgments

This study was supported in part by a National Institutes on Alcohol Abuse and Alcoholism (NIAAA) Diversity Supplement 3R01AA020705-02 S1, PI Anthony Spirito, PhD, awarded to the first author while she was a postdoctoral research fellow at The Alpert Warren Medical School at Brown University. Mentoring was supported in part by a National Institute of Mental Health (2K24MH070769-06) K-24 Mid-Career Mentoring Grant. Gratitude is expressed to Dr. Anthony Spirito for comments on earlier drafts of this article. This article is not submitted for publication to any other journal.

Author Disclosure Statement

No competing financial interests exist.

References

  1. Acevedo BP, Lowe SR, Griffin KW, Botvin GJ. (2013). Predictors of intimate partner violence in a sample of multiethnic urban young adults. J Interpers Violence. 28, 3004–3022 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Adams AE, Greeson MR, Kennedy AC, Tolman RM. (2013). The effects of adolescent intimate partner violence on women's educational attainment and earnings. J Interpers Violence. 28, 3283–3300 [DOI] [PubMed] [Google Scholar]
  3. Albaugh LM, Nauta MM. (2005). Career decision self-efficacy, career barriers, and college women's experiences of intimate partner violence. J Career Assessment. 13, 288–306 [Google Scholar]
  4. American Association of Community Colleges (AACU). (2017). Fast facts. Retrieved from https://www.aacc.nche.edu/wp-content/uploads/2017/09/AACCFactSheet2017.pdf (Accessed March7, 2019)
  5. American College Health Association. (2015). American College Health Association-National College Health Assessment II: Spring 2015 Reference Group Executive Summary. (American College Health Association, Hanover, MD: ). Retrieved from www.acha-ncha.org/docs/NCHA-II_WEB_SPRING_2015_REFERENCE_GROUP_EXECUTIVE_SUMMARY.pdf (Accessed March7, 2019) [Google Scholar]
  6. Black MC, Basile KC, Breiding MJ, et al. (2011). The National Intimate Partner and Sexual Violence Survey (NISVS): 2010 Summary Report. (National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, GA: ) [Google Scholar]
  7. Breiding MJ, Basile KC, Smith SG, et al. (2015). Intimate Partner Violence Surveillance: Uniform Definitions and Recommended Data Elements, Version 2.0. (National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, GA: ) [Google Scholar]
  8. Breiding MJ, Smith SG, Basile KC, et al. (2014). Prevalence and Characteristics of Sexual Violence, Stalking, and Intimate Partner Violence Victimization—National Intimate Partner and Sexual Violence Survey, United States, 2011. MMWR Surveill Summ. 63 (SS08), 1–18 [PMC free article] [PubMed] [Google Scholar]
  9. Capaldi DM, Knoble NB, Shortt JW, Kim HK. (2012). A systematic review of risk factors for intimate partner violence. Partner Abuse. 3, 231–280 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Carter AC, Brandon KO, Goldman MS. (2010). The college and non-college experience: A review of the factors that influence drinking behavior in young adulthood. J Stud Alcohol Drugs. 71, 742–750 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Center for Community College Student Engagement. (2017). Making ends meet: The role of community colleges in student financial health. (The University of Texas at Austin, College of Education, Department of Educational Administration, Program in Higher Education Leadership, Austin, TX: ). Retrieved from www.ccsse.org/docs/Making_Ends_Meet.pdf (Accessed March7, 2019) [Google Scholar]
  12. Chen CM, Dufour MC, Yi HY. (2004). Alcohol consumption among young adults ages 18–24 in the United States: Results from the 2001–2002 NESARC Survey. Alcohol Res Health. 28, 269–281 [Google Scholar]
  13. Chermack ST, Taylor SP. (1995). Alcohol and human physical aggression: Pharmacological versus expectancy effects. J Stud Alcohol. 56, 449–456 [DOI] [PubMed] [Google Scholar]
  14. Chilcoat HD, Breslau N. (1998). Posttraumatic stress disorder and drug disorders: Testing causal pathways. Arch Gen Psychiatry. 55, 913–917 [DOI] [PubMed] [Google Scholar]
  15. Coker AL, Follingstad DR, Bush HM, Fisher BS. (2015). Are interpersonal violence rates higher among young women in college compared with those never attending college? J Interpers Violence. 31, 1413–1429 [DOI] [PubMed] [Google Scholar]
  16. Crane CA, Godleski SA, Przybyla SM, et al. (2016). The proximal effects of acute alcohol consumption on male-to-female aggression: A meta-analytic review of the experimental literature. Trauma Violence Abuse. 17:520–531 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Curtin JJ, Fairchild BA. (2003). Alcohol and cognitive control: Implications for regulation of behavior during response conflict. J Abnorm Psychol. 112, 424. [DOI] [PubMed] [Google Scholar]
  18. Daley EM, Noland VJ. (2001). Intimate partner violence in college students: A cross-cultural comparison. Int Electron J Health Educ. 4, 35–40 [Google Scholar]
  19. Decker MR, Peitzmeier S, Olumide A, et al. (2014). Prevalence and health impact of intimate partner violence and non-partner sexual violence among female adolescents aged 15–19 years in vulnerable urban environments: A multi-country study. J Adolesc Health. 55, S58–S67 [DOI] [PubMed] [Google Scholar]
  20. Devries KM, Child JC, Bacchus LJ, et al. (2014). Intimate partner violence victimization and alcohol consumption in women: A systematic review and meta-analysis. Addiction. 109, 379–391 [DOI] [PubMed] [Google Scholar]
  21. Dillon G, Hussain R, Loxton D, Rahman S. (2013). Mental and physical health and intimate partner violence against women: A review of the literature. Int J Family Med. 2013, 1–15 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Eisenberg D, Goldrick-Rab S, Lipson SK, Broton K. (2016). Too distressed to learn? Mental health among community college students. Retrieved from www.wihopelab.com/publications/Wisconsin_HOPE_Lab-Too_Distressed_To_Learn.pdf (Accessed March7, 2019)
  23. Fals-Stewart W, Birchler GR, Kelley ML. (2003). The timeline followback spousal violence interview to assess physical aggression between intimate partners: Reliability and validity. J Fam Violence. 18, 131–142 [Google Scholar]
  24. Foa EB, Cascardi M, Zoellner LA, Feeny NC. (2000). Psychological and environmental factors associated with partner violence. Trauma Violence Abuse. 1, 67–91 [Google Scholar]
  25. Foshee VA, Bauman KE, Arriaga XB, et al. (1998). An evaluation of Safe Dates, an adolescent dating violence prevention program. Am J Public Health. 88, 45–50 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Foshee VA, Benefield T, Suchindran C, et al. (2009). The development of four types of adolescent dating abuse and selected demographic correlates. J Res Adolesc. 19, 380–400 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Foshee VA, Karriker-Jaffe KJ, Reyes HLM, et al. (2008). What accounts for demographic differences in trajectories of adolescent dating violence? An examination of intrapersonal and contextual mediators. J Adolesc Health. 42, 596–604 [DOI] [PubMed] [Google Scholar]
  28. Giancola PR. (2000). Executive functioning: A conceptual framework for alcohol-related aggression. Exp Clin Psychopharmacol. 8, 576–597 [DOI] [PubMed] [Google Scholar]
  29. Grucza RA, Norberg KE, Bierut LJ. (2009). Binge drinking among youths and young adults in the United States: 1979–2006. J Am Acad Child Adolesc Psychiatry. 48, 692–702 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Halpern CT, Spriggs AL, Martin SL, Kupper LL. (2009). Patterns of intimate partner violence victimization from adolescence to young adulthood in a nationally representative sample. J Adolesc Health. 45, 508–516 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Hingson RW, Zha W, Smyth D. (2017a). Magnitude and trends in heavy episodic drinking, alcohol-impaired driving, and alcohol-related mortality and overdose hospitalizations among emerging adults of college ages 18–24 in the United States, 1998–2014. J Stud Alcohol Drugs. 78, 540–548 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Hingson RW, Zha W, White AM. (2017b) Drinking beyond the binge threshold: Predictors, consequences, and changes in the US. Am J Prev Med. 52, 717–727 [DOI] [PubMed] [Google Scholar]
  33. Kilpatrick DG, Acierno R, Resnick HS, et al. (1997). A 2-year longitudinal analysis of the relationships between violent assault and substance use in women. J Consult Clin Psychol. 65, 834. [DOI] [PubMed] [Google Scholar]
  34. Kim S, Egerter S, Cubbin C, et al. (2007). Potential implications of missing income data in population-based surveys: An example from a postpartum survey in California. Public Health Rep. 122, 753–763 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. La Flair LN, Bradshaw CP, Storr CL, et al. (2012). Intimate partner violence and patterns of alcohol abuse and dependence criteria among women: A latent class analysis. J Stud Alcohol Drugs. 73, 351–360 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Lam WK, Fals-Stewart W, Kelley M. (2009). The timeline followback interview to assess children's exposure to partner violence: Reliability and validity. J Family Viol. 24, 133–143 [Google Scholar]
  37. Lenk KM, Nelson TF, Erickson DJ, Toomey TL. (2015). How are 2-year US colleges addressing student alcohol use and related problems? J Coll Stud Dev. 56, 380–385 [Google Scholar]
  38. Leonard KE, Quigley BM. (1999). Drinking and marital aggression in newlyweds: An event-based analysis of drinking and the occurrence of husband marital aggression. J Stud Alcohol. 60, 537–545 [DOI] [PubMed] [Google Scholar]
  39. Lipsey MW, Wilson DB, Cohen MA, Derzon JH. (1997). Is there a causal relationship between alcohol use and violence? A synthesis of evidence. Recent Dev Alcohol. 13, 245–282 [DOI] [PubMed] [Google Scholar]
  40. Marzell M, Bavarian N, Paschall MJ, et al. (2015). Party characteristics, drinking settings, and college students' risk of intoxication: A multi-campus study. J Prim Prev. 36, 247–258 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Mohler-Kuo M, Dowdall GW, Koss MP, Wechsler H. (2004). Correlates of rape while intoxicated in a national sample of college women. J Stud Alcohol. 65, 37–45 [DOI] [PubMed] [Google Scholar]
  42. Moore TM, Elkins SR, McNulty JK, et al. (2011). Alcohol use and intimate partner violence perpetration among college students: Assessing the temporal association using electronic diary technology. Psychol Violence. 1, 315 [Google Scholar]
  43. National Institute on Alcohol Abuse and Alcoholism (NIAAA). (2017). National Institute on Alcohol Abuse and Alcoholism Strategic Plan 2017–2021. Retrieved from https://www.niaaa.nih.gov/strategic-plan (Accessed March7, 2019)
  44. National Institute on Alcohol Abuse and Alcoholism (NIAAA). (n.d.). Drinking levels defined. Retrieved from https://www.niaaa.nih.gov/alcohol-health/overview-alcohol-consumption/moderate-binge-drinking (Accessed March7, 2019)
  45. Nelson MC, Larson NI, Barr-Anderson D, et al. (2009). Disparities in dietary intake, meal patterning, and home food environments among young adult nonstudents and 2- and 4-year college students. Am J Public Health. 99, 1216–1219 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Okuda M, Olfson M, Wang S, et al. (2015). Correlates of intimate partner violence perpetration: Results from a National Epidemiologic Survey. J Trauma Stress. 28, 49–56 [DOI] [PubMed] [Google Scholar]
  47. Parks KA, Hsieh YP, Bradizza CM, Romosz AM. (2008). Factors influencing the temporal relationship between alcohol consumption and experiences with aggression among college women. Psychol Addict Behav. 22, 210. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Parks KA, Romosz AM, Bradizza CM, Hsieh YP. (2008). A dangerous transition: Women's drinking and related victimization from high school to the first year at college. J Stud Alcohol Drugs. 69, 65–74 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Reingle JM, Staras SA, Jennings WG, et al. (2012). The relationship between marijuana use and intimate partner violence in a nationally representative, longitudinal sample. J Interpers Violence. 27, 1562–1578 [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Rothman EF, Reyes LM, Johnson RM, LaValley M. (2011). Does the alcohol make them do it? Dating violence perpetration and drinking among youth. Epidemiol Rev. 34, 109–113 [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Rothman EF, Stuart GL, Winter M, et al. (2012). Youth alcohol use and dating abuse victimization and perpetration: A test of the relationships at the daily level in a sample of pediatric emergency department patients who use alcohol. J Interpers Violence. 27, 2959–2979 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Roudsari BS, Leahy MM, Walters ST. (2009). Correlates of dating violence among male and female heavy-drinking college students. J Interpers Violence. 24, 1892–1905 [DOI] [PubMed] [Google Scholar]
  53. Sanem JR, Berg CJ, An LC, et al. (2009). Differences in tobacco use among two-year and four-year college students in Minnesota. J Am Coll Health. 58, 151–159 [DOI] [PubMed] [Google Scholar]
  54. Sayette MA. (1993). An appraisal-disruption model of alcohol's effects on stress responses in social drinkers. Psychol Bull. 114, 459–476 [DOI] [PubMed] [Google Scholar]
  55. Schwab-Reese LM, Peek-Asa C, Parker E. (2016). Associations of financial stressors and physical intimate partner violence perpetration. Inj Epidemiol. 3, 6, 1–10 [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Sher KJ, Wood MD, Wood PK, Raskin G. (1996). Alcohol outcome expectancies and alcohol use: A latent variable cross-lagged panel study. J Abnorm Psychol. 105, 561. [DOI] [PubMed] [Google Scholar]
  57. Shorey RC, Moore TM, McNulty JK, Stuart GL. (2015). Do alcohol and marijuana increase the risk for female dating violence victimization? A prospective daily diary investigation. Psychol Violence. 6, 509–518 [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Shorey RC, Stuart GL, Cornelius TL. (2011). Dating violence and substance use in college students: A review of the literature. Aggress Violent Behav. 16, 541–550 [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Shorey RC, Stuart GL, McNulty JK, Moore TM. (2014). Acute alcohol use temporally increases the odds of male perpetrated dating violence: A 90-day diary analysis. Addict Behav. 39, 365–368 [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Shorey RC, Tirone V, Stuart GL. (2014). Coordinated community response components for victims of intimate partner violence: A review of the literature. Aggress Violent Behav. 19, 363–371 [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Simons-Morton B, Haynie D, O'Brien F, et al. (2017). Variability in measures of health and health behavior among emerging adults 1 year after high school according to college status. J Am Coll Health. 65, 58–66 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Sobell LC, Sobell MB. (1995). Alcohol Timeline Followback Users' Manual. (Addiction Research Foundation, Toronto, Canada: ) [Google Scholar]
  63. Sobell LC, Sobell MB. (2003). Alcohol consumption measures. In Assessing Alcohol Problems: A Guide for Clinicians and Researchers (2nd edition.). Allen P, Wilson VB, eds. (National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD: ), pp. 75–99 [Google Scholar]
  64. Stappenbeck CA, Gulati NK, Fromme K. (2016). Daily associations between alcohol consumption and dating violence perpetration among men and women: Effects of self-regulation. J Stud Alcohol Drugs. 77, 150–159 [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Steele CM, Josephs RA. (1990). Alcohol myopia: Its prized and dangerous effects. Am Psychol. 45, 921–933 [DOI] [PubMed] [Google Scholar]
  66. Stöckl H, March L, Pallitto C, Garcia-Moreno C. (2014). Intimate partner violence among adolescents and young women: Prevalence and associated factors in nine countries: A cross-sectional study. BMC Public Health. 14, 1–14 [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Straus MA. (2004). Prevalence of violence against dating partners by male and female university students worldwide. Viol Against Women. 10, 790–811 [Google Scholar]
  68. Stuart GL, Ramsey SE, Moore TM, et al. (2003). Reductions in marital violence following treatment for alcohol dependence. J Interpers Violence. 18, 1113–1131 [DOI] [PubMed] [Google Scholar]
  69. Sullivan TP, McPartland TS, Armeli S, et al. (2012). Is it the exception or the rule? Daily co-occurrence of physical, sexual, and psychological partner violence in a 90-day study of substance-using, community women. Psychol Viol. 2, 1–15 [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Testa M, Livingston JA, Leonard KE. (2003). Women's substance use and experiences of intimate partner violence: A longitudinal investigation among a community sample. Addict Behav. 28, 1649–1664 [DOI] [PubMed] [Google Scholar]
  71. Trieu SL, Marshak HH, Bratton SI. (2013). Sexual and reproductive health behaviors of Asian Pacific Islander community college students. Commun Coll J Res Pract. 37, 467–477 [Google Scholar]
  72. Tsui EK, Santamaria EK. (2015). Intimate partner violence risk among undergraduate women from an urban commuter college: The role of navigating off-and on-campus social environments. J Urban Health. 92, 513–526 [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Velazquez CE, Pasch KE, Laska MN, et al. (2011). Differential prevalence of alcohol use among 2-year and 4-year college students. Addict Behav. 36, 1353–1356 [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Voth Schrag RJ, Edmond TE. (2018a). Intimate partner violence, trauma, and mental health need among female community college students. J Am Coll Health. 66:702–711 [DOI] [PubMed] [Google Scholar]
  75. Voth Schrag RJ, Edmond TE. (2018b). Service use and needs among female survivors of intimate partner violence attending community college. J Fam Viol. 33(6), 393–404 [Google Scholar]
  76. Voth Schrag RJ, Edmond T. (2017). School sabotage as a form of intimate partner violence: Provider perspectives. Affilia. 32, 171–187 [Google Scholar]
  77. Zeger SL, Liang KY. (1986). Longitudinal data analysis for discrete and continuous outcomes. Biometrics. 42, 121–130 [PubMed] [Google Scholar]

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