Gender Policing During Childhood and the Psychological Well-Being of Young Adult Sexual Minority Men in the United States

Abstract

Hegemonic masculinities (i.e., sets of socially accepted masculine behaviors and beliefs within a given time and culture) may affect the well-being of sexual minority men, yet quantitative relationships between these masculinities and well-being remain largely unexplored. Using data from a national cross-sectional survey of young sexual minority men (N = 1,484; ages 18-24 years), the current study examined the relationship between parental gender policing during childhood and adolescence and subsequent substance use and psychological distress. Over one third of the sample (37.8%) reported their parent(s) or the person(s) who raised them had policed their gender, including the use of disciplinary actions. Using multivariable regression, this study examined the relationship between parental gender policing and psychological well-being and substance use, after adjusting for age, race/ethnicity, educational attainment, and current student status. Gender policing during childhood and adolescence was associated with recent substance use behaviors and psychological distress in multivariable models. A linear association between substance use behaviors and psychological distress and the number of disciplinary actions experienced during childhood and adolescence was also observed. Parents’ attempts to police their sons’ gender expression were associated with markers of distress among young sexual minority men. The relationship between parental gender policing during childhood and adolescence and distress among young sexual minority men are discussed.

Keywords

family masculinity development childhood and adolescence

Hegemonic masculinities (i.e., sets of socially accepted masculine behaviors and beliefs within a given time and culture designed to legitimate male domination; Connell, 1982; Connell & Messerschmidt, 2005) has received increasing attention in the public health literature given its association with numerous risk behaviors across the life course (Fields et al., 2015). Sexual minority men are more likely to be identified as gender nonconforming than heterosexual men (Bailey & Zucker, 1995), and may be more vulnerable to societal messages intended to pressure men to behave in ways that are traditionally masculine. The impact of these societal messages may be especially harmful to young sexual minority men as they explore their sexuality (Alanko et al., 2009; Carragher & Rivers, 2002; D’Augelli, 1991; D’Augelli, Grossman, & Starks, 2008; Van Beusekom, Bos, Kuyper, Overbeek, & Sandfort, 2016). As a result, sexual minority men may have greater vulnerability to psychological distress and may be more likely to adopt negative coping behaviors including use of alcohol, tobacco, and other drugs (ATOD; Hatzenbuehler, 2011; Herek, Gillis, & Cogan, 2009; Meyer, 2003; Saewyc, 2011).

Researchers have increasingly acknowledged that the promotion of hegemonic masculinity norms begins early in the life course. Caregivers may attempt to diminish their sons’ gender nonconforming behaviors and encourage masculine behaviors (Epstein & Ward, 2011; Hill & Menvielle, 2009; Kane, 2006; Solebello & Elliott, 2011). In a study of 528 sexual minority adolescents in New York City (ages 15-19 years), D’Augelli et al. (2008) reported that only 2% of male participants’ mothers and even fewer fathers reacted positively to gender nonconforming behavior. Caregivers may intervene by imposing normative hegemonic masculinity through gender policing (e.g., telling their son to change feminine behavior, restricting activities, forcing counseling or religious interventions, punishing with physical and/or verbal abuse, and forcing enrollment in traditionally masculine activities). This policing is enacted as a means to influence behaviors that are consistent with their own moral ideals or as a way of protecting their child from anticipated societal stigma, regardless of whether their son has disclosed his same-sex attraction (Bailey & Zucker, 1995; D’Augelli et al., 2008; Hill & Menvielle, 2009; Solebello & Elliott, 2011). Qualitative data support these assertions. In a qualitative study of 23 fathers of teenagers between the ages of 13 and 19 years, Solebello and Elliott (2011) reported that fathers encouraged hegemonic masculine behaviors (e.g., girl watching, viewing sexualized images of women) in their sons as a rite of passage that would ensure their son’s masculinity and heterosexuality. Similarly, in a qualitative study by Hill and Menvielle (2009), parents described how they discourage gender nonconforming behaviors in their sons, including actions such as removal of feminine toys, encouragement of masculine activities, modeling masculine behavior, and encouraging the boy to police his own gender expression and/or behaviors to reduce the discomfort of others. Taken together, these findings underscore the importance of exploring the ways in which caregivers’ negative reactions to gender nonconforming behavior in their sons during childhood and adolescence are related to adverse outcomes in young adult sexual minority men.

Gender policing during childhood and adolescence may have long-lasting effects into adulthood. In a matched pairs analysis of 158 men and 148 women who reported same-sex sexual attractions or behaviors, Alanko et al. (2009) reported that participants who recalled gender atypical behaviors in childhood were more likely to exhibit a greater number of current depression and anxiety symptoms. Moreover, researchers have noted that sexual minority young adult men may rely on ATOD as a coping strategy to offset psychological distress (Institute of Medicine, 2011). Young adult sexual minority men may use ATOD because these behaviors are often seen as highly masculine (Peralta, 2007; Peralta, Stewart, Steele, & Wagner, 2016). At present, little is known about the relationship between primary caregiver gender policing and ATOD use among young adult sexual minority men. Therefore, the current study explores whether primary caregivers’ actions to impose hegemonic masculinities in their sons during childhood and adolescence are associated with ATOD use and psychological well-being among young adult sexual minority men.

Using a national sample of young adult sexual minority men (ages 18-24 years), the current study examined the prevalence of parental gender policing during childhood and adolescence. The authors hypothesized that a large proportion of the sample would recall having experienced gender policing by a primary caregiver. Analyses examined whether these recalled experiences of gender policing were associated with ATOD use and depression and anxiety symptoms. The authors hypothesized that participants who reported gender policing would be more likely to report greater ATOD use and psychological distress than those who had not reported gender policing. Finally, the authors tested whether exposure to a greater number of disciplinary actions related to gender policing was associated with ATOD use and psychological distress. Consistent with the literature, the authors hypothesized that a greater number of disciplinary actions would be associated with greater risk behaviors.

Method

Sample

Data for this article come from a cross-sectional study examining the HIV risk behaviors of sexual minority men who meet partners online (see Bauermeister, 2015). To be eligible for the study, participants had to identify as cisgender, male, be between the ages of 18 and 24 years (inclusive), report being single, and be a resident of the United States (including Puerto Rico). Participants were primarily recruited through advertisements on two popular social networking sites and through participant referrals. Social network advertisements were visible only to men who fit the specified age range and who lived in the United States. Promotional materials included eligibility criteria, a mention of a $10 VISA e-card incentive, and the survey’s website.

Procedures

Eligible and consenting participants answered a 30-minute online questionnaire that assessed their sociodemographic characteristics, sexual orientation, sexual and substance use behaviors, and psychological well-being. Data were protected with 128-bit SSL encryption and kept within a firewalled server. The principal investigator acquired a Certificate of Confidentiality from the National Institutes of Health to protect participants’ data from being subpoenaed or used in legal proceedings. The authors’ institutional review board approved all study procedures.

Measures

Alcohol, Tobacco, and Other Drugs

Participants indicated whether they had used alcohol, cigarettes, marijuana, and nine types of hard drugs in the past 2 months using a dichotomous response (yes or no) for each substance. Hard drugs included cocaine, Ecstasy (3,4-methylenedioxymethamphetamine, or MDMA), crystal meth, ketamine, GHB, poppers, crack, heroin, and hallucinogens (e.g., LSD, mushrooms). Participants who reported at least one type of hard drug use were grouped into a “Any Hard Drug Use” category. The questionnaire also ascertained whether participants had used any pharmaceutical drugs which were not prescribed to them by a physician. Four substance use outcomes were created: any alcohol use, any cigarette use, any hard drug use, and any nonprescribed medication use.

Psychological Distress

The frequency of depressive and anxiety symptoms are used as dependent variables in the analyses. To ascertain depressive symptoms, participants completed a 10-item short form of the Center for Epidemiologic Studies Depression scale (Kohout, Berkman, Evans, & Cornoni-Huntley, 1993). This short form limits the number of survey items and reduces participant burden. Items (e.g., “I felt that everything I did was an effort”) were scored on a 4-point scale: 1 = rarely or none of the time (less than 1 day); 4 = most or all of the time (5-7 days). The total score was calculated by reverse scoring positively worded items (e.g., “I felt hopeful about the future”) and creating a composite sum score. High scores indicated high depressive symptoms in the past week (Cronbach’s α = .85).

Participants completed the six-item anxiety subscale of the Brief Symptom Inventory (Derogatis & Spencer, 1982) using a 4-point scale ranging from 1 = never to 4 = very often, indicating how often they felt a statement applied to them in the past week. Examples of statements were “feeling fearful,” “spells of terror or panic,” and “feeling so restless you couldn’t sit still.” A composite sum score was computed, where higher scores indicated greater levels of anxiety (Cronbach’s α = .92).

Gender Policing

To assess whether and how participants’ expression of gender was discouraged or punished by parental figures, participants were asked a yes or no question (“Did your parent[s] or the person[s] that raised you ever tell you to stop acting feminine?”). Those who responded “yes” were asked to select what methods were used by their parental figures to attempt to change their behavior. Participants had four answer categories: “Told Me to Change My Behavior,” “Punished Me or Restricted My Activities,” “Sent Me to Counseling,” and “Other.” Participants who selected “Other” were asked to describe their parents’ behavior. The study team thematically coded these entries and created two additional categories based on the frequency of certain responses: “Physical and/or Emotional Abuse” and “Placed in Masculine Activities.”

Demographic Characteristics

Participants reported their age, racial/ethnic group membership, sexual orientation, and highest educational attainment. Participants self-reported their race/ethnicity using the following categories: White/Caucasian, Black/African American, Latino/Hispanic, Asian/Pacific Islander, Middle Eastern, Native American, and Other. Participants who selected more than one race (e.g., White/Caucasian and Black/African American) were grouped in a Multiracial category. The Middle Eastern, Native American, Multirace, and Other Race categories were collapsed given the limited number of observations in each category. Dummy variables for each race/ethnicity group were created, having non-Latino White/Caucasian participants serve as the referent group.

Participants also reported their sexual orientation as gay/homosexual, bisexual, straight/heterosexual, same gender loving, men who have sex with men, or other. The majority of participants identified as gay or bisexual; consequently, all other sexual identity categories were grouped into an Other Sexual Identity category. Gay participants served as the referent group in multivariate analyses.

Participants provided their level of highest educational attainment (e.g., 1 = less than high school, 2 = high school/GED, 3 = technical school, 4 = associate degree, 5 = some college, 6 = college, or 7 = some graduate school or more). Given that age would confound participants’ educational attainment post-high school, this variable was recoded to denote whether participants had completed high school. Not having graduated high school served as the referent group.

Data Analytic Strategy

Descriptive statistics for key variables were examined and tested for bivariate differences based on participant recollection of gender policing by their primary caregiver (see Table 1) using t tests and chi-square statistics. Two multivariable models for each outcome were estimated. The first model tested whether there was a linear relationship between gender policing (i.e., being told to stop acting feminine) and the outcome of interest. The second model tested whether there was a linear association between the number of disciplinary actions enacted on participants who experienced gender policing and ATOD use. ATOD use outcomes (see Tables 2 and 3) were modeled using binary logistic regression. Psychological distress outcomes were modeled using ordinary least squares regression (see Table 4).

Table 1.

Sample Characteristics (N = 1,484).

	Total sample	Told stop acting feminine		Test statistic (t/χ²)	Sig.
	Total sample	No (N = 923)	Yes (N = 561)	Test statistic (t/χ²)	Sig.
Age (M, SD)	20.80 (1.93)	20.80 (1.96)	20.52 (1.87)	−0.20	.84
Completed high school	1,431 (96.4%)	882 (95.6%)	549 (97.9%)	5.37	.02
Sexual orientation
Gay	1,371 (92.4%)	852 (92.3%)	519 (92.5%)	0.02	.89
Bisexual	47 (3.2%)	29 (3.1%)	18 (3.2%)	0.01	.94
Other	64 (4.3%)	41 (4.4%)	23 (4.1%)	0.10	.75
Race
White	970 (65.4%)	641 (69.4%)	329 (58.6%)	17.98	.001
Black	130 (8.8%)	76 (8.2%)	54 (9.6%)	0.85	.36
Asian/Pacific Islander	55 (3.7%)	23 (2.5%)	32 (5.7%)	10.09	.001
Latino	254 (17.1%)	137 (14.8%)	117 (20.9%)	8.89	.003
Multiracial/other	75 (5.1%)	46 (5.0%)	29 (5.2%)	0.03	.87
Substance use
Alcohol	1,126 (75.9%)	685 (74.2%)	441 (78.6%)	3.69	.05
Cigarettes	578 (38.9%)	338 (36.6%)	240 (42.8%)	5.57	.02
Marijuana	558 (37.6%)	326 (35.3%)	232 (41.4%)	5.42	.02
Hard drug use	227 (15.3%)	132 (14.3%)	95 (16.9%)	1.87	.17
Prescription drug use	109 (7.3%)	61 (6.6%)	48 (8.6%)	1.94	.16
Psychological distress
Depression (M, SD)	2.17 (0.64)	2.09 (0.62)	2.30 (0.66)	−5.99	.001
Anxiety (M, SD)	2.14 (1.02)	1.99 (0.95)	2.39 (1.09)	−7.16	.001
Gender policing	561 (37.8%)
Disciplinary actions
Told to change behavior	521 (35.1%)		521 (92.9%)
Punished/restricted activities	183 (12.3%)		183 (32.6%)
Sent to counseling	110 (7.4%)		110 (19.6%)
Sent to religious figure	80 (5.4%)		80 (14.3%)
Abuse	38 (2.6%)		38 (6.8%)
Masculine activities	9 (0.6%)		9 (1.6%)
Number of disciplinary actions experienced
0	930 (62.7%)		7 (1.2%)
1	309 (20.8%)		309 (55.1%)
2	143 (9.6%)		143 (25.5%)
3	63 (4.2%)		63 (11.2%)
4 or More	39 (2.7%)		39 (7.0%)

Note. For bivariate comparisons of proportions, chi-square tests were used. For mean comparisons, t-test statistics are reported.

Table 2.

Multivariate Logistic Regressions Examining the Relationship Between Substance Use and Being Told to Stop Acting Feminine (N = 1,484).

Predictor	Alcohol		Cigarettes		Marijuana		Hard drug use		Prescription drugs
Predictor	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI
Gender policing	1.33*	[1.03, 1.73]	1.37**	[1.10, 1.70]	1.32*	[1.06, 1.64]	1.25	[0.94, 1.68]	1.47	[0.98, 2.19]
Age	1.25***	[1.17, 1.34]	1.03	[0.97, 1.09]	0.97	[0.92, 1.03]	1.10*	[1.02, 1.18]	1.03	[0.93, 1.15]
Completed high school	2.11*	[1.18, 3.77]	0.66	[0.38, 1.17]	0.77	[0.44, 1.36]	1.09	[0.45, 2.64]	1.12	[0.33, 3.77]
Sexual identity
Bisexual	1.70	[0.80, 3.62]	3.25***	[1.75, 6.06]	1.68	[0.93, 3.04]	1.00	[0.41, 2.42]	1.17	[0.35, 3.93]
Other identity	0.58	[0.33, 1.01]	0.90	[0.53, 1.53]	0.88	[0.52, 1.49]	1.20	[0.61, 2.36]	1.88	[0.82, 4.31]
Race/ethnicity
Black	0.32***	[0.21, 0.48]	0.56**	[0.38, 0.85]	1.09	[0.74, 1.59]	0.32**	[0.15, 0.68]	0.07*	[0.01, 0.51]
Asian/Pacific Islander	0.78	[0.39, 1.53]	0.53*	[0.29, 0.97]	0.59	[0.32, 1.09]	0.59	[0.25, 1.41]	0.17	[0.02, 1.23]
Latino	0.56***	[0.41, 0.77]	0.82	[0.61, 1.09]	1.03	[0.77, 1.37]	1.08	[0.75, 1.56]	0.42*	[0.22, 0.80]
Multiracial/other	0.65	[0.38, 1.11]	0.74	[0.45, 1.22]	1.14	[0.70, 1.84]	0.89	[0.46, 1.74]	0.99	[0.44, 2.22]
Omnibus test	χ²(df = 9) = 102.21***		χ²(df = 9) = 33.17***		χ²(df = 9) = 15.55		χ²(df = 9) = 20.11**		χ²(df = 9) = 31.42**
Nagelkerke Pseudo-R²	10%		3.0%		1.4%		2.6%		5.1%

Note. OR = odds ratio; CI = confidence interval; df = degrees of freedom.

p < .05. **p < .01. ***p < .001.

Table 3.

Multivariate Logistic Regressions Examining the Relationship Between Substance Use and Number of Disciplinary Actions Among YMSM Told to Stop Acting Feminine (N = 561).

	Alcohol		Cigarettes		Marijuana		Hard drug use		Prescription drugs
	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI
Disciplinary actions	0.96	[0.77, 1.19]	1.30**	[1.09, 1.55]	1.09	[0.91, 1.31]	1.17	[0.93, 1.48]	1.46**	[1.09, 1.94]
Age	1.32***	[1.17, 1.49]	1.04	[0.95, 1.14]	0.98	[0.89, 1.08]	1.23**	[1.08, 1.39]	1.12	[0.93, 1.15]
Completed high school	2.22	[0.67, 7.41]	1.16	[0.35, 3.85]	1.19	[0.36, 3.98]	0.83	[0.17, 4.13]	0.30	[0.33, 3.77]
Sexual identity
Bisexual	1.42	[0.39, 5.21]	3.04*	[1.10, 8.39]	1.31	[0.43, 2.95]	1.17	[0.32, 4.27]	0.74	[0.35, 3.93]
Other identity	0.47	[0.18, 1.24]	0.54	[0.21, 1.35]	0.87	[0.36, 2.07]	1.13	[0.39, 3.24]	2.25	[0.82, 4.31]
Race/ethnicity
Black	0.47*	[0.23, 0.92]	0.70	[0.38, 1.28]	1.48	[0.83, 2.66]	0.25*	[0.07, 0.83]	0.00	[0.00, 1.00]
Asian/Pacific Islander	0.99	[0.36, 2.76]	0.57	[0.26, 1.26]	0.74	[0.34, 1.62]	0.32	[0.07, 1.38]	0.33	[0.04, 2.54]
Latino	0.49*	[0.30, 0.81]	0.96	[0.62, 1.48]	1.24	[0.81, 1.90]	1.42	[0.84, 2.41]	0.54	[0.23, 1.26]
Multiracial/other	0.56	[0.23, 1.36]	1.22	[0.56, 2.64]	2.65*	[1.21, 5.81]	1.61	[0.65, 4.02]	1.77	[0.61, 5.16]
Omnibus test	χ²(df = 9) = 37.24***		χ²(df = 9) = 17.93*		χ²(df = 9) = 10.06		χ²(df = 9) = 24.84**		χ²(df = 9) = 28.53***
Nagelkerke Pseudo-R²	10.1%		4.2%		2.4%		7.3%		11.2%

Note. YMSM = young men who have sex with men; df = degrees of freedom; OR = odds ratio; CI = confidence interval.

p < .05. **p < .01. ***p < .001.

Table 4.

Multivariate Logistic Regressions Examining the Relationship Between Psychological Distress and Gender Policing (N = 1,484) and Number of Disciplinary Actions Among YMSM Told to Stop Acting Feminine (N = 561).

	Depression symptoms				Anxiety symptoms
	b(SE)	β	b(SE)	β	b(SE)	β	b(SE)	β
Constant	2.83 (0.19)***		3.02 (0.35)***		3.15 (0.29)***		3.24 (0.57)***
Gender policing	0.21 (0.03)***	0.16			0.40 (0.05)***	0.19
Disciplinary actions			0.10 (0.03)***	0.14			0.15 (0.05)**	0.13
Age	−0.03 (0.01)**	−0.08	−0.04 (0.02)**	−0.12	−0.04 (0.01)*	−0.08	−0.07 (0.03)**	−0.12
Completed high school	−0.19 (0.09)*	−0.06	−0.08 (0.19)	−0.02	−0.32 (0.14)*	−0.06	0.26 (0.32)	0.03
Sexual identity
Bisexual	0.09 (0.10)	0.02	0.09 (0.16)	0.02	0.22 (0.15)	0.04	0.48 (0.26)	0.08
Other identity	0.11 (0.08)	0.03	0.33 (0.14)*	0.10	0.29 (0.13)*	0.06	0.56 (0.23)*	0.10
Race/ethnicity
Black	−0.16 (0.06)	−0.07**	−0.03 (0.10)	−0.01	−0.13 (0.09)	−0.04	−0.04 (0.16)	0.01
Asian/Pacific Islander	−0.03 (0.09)	−0.01	0.10 (0.12)	0.04	0.03 (0.14)	0.005	0.17 (0.20)	0.04
Latino	0.07 (0.05)	0.04	0.11 (0.07)	0.07	0.17 (0.07)*	0.06	0.34 (0.12)	0.13
Multiracial/other	−0.10 (0.08)	−0.03	0.11 (0.13)	0.04	−0.18 (0.12)	−0.04	0.03 (0.21)	0.01
Omnibus test	F(9, 1474) = 7.61***		F(9, 550) = 3.27***		F(9, 1474) = 10.16***		F(9, 551) = 4.14***
R ²	3.9%		3.5%		5.3%		4.8%

Note. YMSM = young men who have sex with men; b = unstandardized slope; SE = standard error; β = standardized slope.

p < .05. **p < .01. ***p < .001.

Results

Study Sample

The mean age of the sample was 20.80 (SD = 1.93) years. The majority of the sample was White (N = 970; 65.4%), followed by racial/ethnic minorities including Latino (N = 254; 17.1%), Black (N = 130; 8.8%), Asian/Pacific Islander (N = 55; 3.7%), and other (N = 75; 5.1%). Most participants identified as gay or homosexual (N = 1,371; 92.4%), with the remainder of participants identifying as bisexual (N = 48; 3.2%) or using another identity to describe their sexuality (e.g., queer, same gender loving; N = 64; 4.3%). The vast majority of participants had completed high school (96.4%).

ATOD use was prevalent in the sample. In the prior 2 months, three quarters of participants (N = 1,126) reported consuming alcohol, nearly 40% of the sample reported smoking cigarettes (N = 578; 38.9%) or marijuana (N = 558; 37.6%), 15% reported using at least one hard drug (N = 227), and 7% (N = 109) reported using someone else’s prescription drugs.

Over one third of participants (N = 561; 37.8%) reported being told to act less feminine by a parent(s) or guardian(s) by whom they were raised (see Table 1). The most frequently noted disciplinary action in response to feminine behavior was being told to change one’s behavior (N = 521; 35.1%). Other common disciplinary actions included being punished or having one’s activities restricted (N = 183; 12.3%), being sent to counseling (N = 110; 7.4%), and being sent to talk to a priest/minister/religious figure (N = 80; 5.4%). Thirty-eight participants (2.6%) reported experiences of abuse (mental and physical) as disciplinary action and nine participants (0.6%) reported being placed in/forced into masculine activities. In order to ascertain if there was a dose–response relationship between the number of disciplinary actions and participant well-being, participants were given the option to report multiple disciplinary actions enacted to change their behaviors. Among those reporting multiple types of disciplinary actions, participants reported at least one type of disciplinary action (N = 309; 55.1%), followed by two (N = 143; 25.5%), three (N = 63; 11.2%), and four or more (N = 39; 7.0%).

As noted in Table 1, participants who were told to stop acting feminine were more likely to have completed high school, and were more likely to be Asian/Pacific Islander or Latino. Participants who were told to stop acting feminine also reported higher symptoms of depression and anxiety (see Table 1), and were more likely to report using alcohol, cigarettes, and marijuana (see Table 2).

Multivariable Models

Alcohol

Participants who reported that their parents asked them to stop acting feminine were more likely to use alcohol in the prior 2 months (see Table 2). Older participants who had completed high school had higher odds of alcohol use. Compared with White participants, African American and Latino participants were less likely to report alcohol use. No other differences by race/ethnicity or sexual orientation were observed.

Among those who had been told to stop acting feminine, there was no association between alcohol use and the number of disciplinary actions, after adjusting for age, education, sexual orientation, and race/ethnicity (see Table 3).

Cigarettes

Participants who reported that their parents asked them to stop acting feminine were more likely to smoke cigarettes in the prior 2 months (see Table 2). Cigarette use was greater among bisexual participants than gay counterparts. Compared with White participants, African American and Asian/Pacific Islander participants were less likely to report cigarette use. No other differences by race/ethnicity, sexual orientation, age, or education were identified.

Among those who had been told to stop acting feminine, cigarette use was associated with a greater number of disciplinary actions, after adjusting for age, education, sexual orientation, and race/ethnicity (see Table 3). Bisexual participants were more likely than gay peers to report cigarette use. No other differences by sexual orientation, race/ethnicity, age, or education were noted.

Marijuana

Participants who reported that their parents asked them to stop acting feminine were more likely to smoke marijuana in the prior 2 months (see Table 2). There was no association between marijuana use and age, education, race/ethnicity, or sexual orientation. Among those who had been told to stop acting feminine, there was no association between marijuana use and the number of disciplinary actions, after adjusting for age, education, sexual orientation, and race/ethnicity (see Table 3).

Hard Drug Use

There was no association between hard drug use and being told to stop acting feminine or the number of disciplinary actions after adjusting for age, education, sexual orientation, and race/ethnicity.

Prescription Drug Use

There was no association between illicit use of prescription drugs and being told to stop acting feminine (see Table 2). Compared with White participants, African American and Latino participants were less likely to report prescription drug use. No other differences by race/ethnicity, sexual orientation, age, or education were observed.

Among those who had been told to stop acting feminine, there was no association between illicit use of prescription drugs and the number of disciplinary actions, after adjusting for age, education, sexual orientation, and race/ethnicity (see Table 3).

Depression

Depressive symptoms were higher among participants who reported being told to stop acting feminine when they were growing up. Depressive symptoms were higher among participants who were younger. Depressive symptoms were higher among participants who had completed high school. Compared with White participants, Black participants reported fewer depressive symptoms. No other differences by race/ethnicity or sexual orientation were identified (see Table 4).

Among those who had been told to stop acting feminine, participants who reported a greater number of disciplinary actions reported greater depressive symptoms (see Table 4). Depressive symptoms were higher among participants who were older. Compared with their gay counterparts, participants who identified as another sexual orientation reported higher depression symptoms. No other differences by sexual orientation, high school completion, or race/ethnicity were identified.

Anxiety

Anxiety symptoms were higher among participants who reported being told to stop acting feminine when they were growing up (see Table 4). Anxiety symptoms were higher among participants who were older and who had completed high school. Compared with White participants, Latino participants reported greater anxiety symptoms. Compared with gay participants, participants who identified as any other sexual orientation reported higher anxiety symptoms. There were no other differences by race/ethnicity.

Among those who had been told to stop acting feminine, participants who reported a greater number of disciplinary actions reported greater anxiety symptoms (see Table 4). Anxiety symptoms were lower among participants who were older. Compared with their gay counterparts, participants who identified as another sexual orientation reported higher anxiety symptoms. There were no differences by high school completion or race/ethnicity.

Discussion

Over a third of the sample reported gender policing by a parental or other caretaker during childhood and adolescence. The most common method of gender policing was being told to correct behavior so as not to appear feminine. In some cases, gender policing included punitive actions such as sending youth to counseling, restricting them from activities, and even physical or emotional abuse. Prior research has suggested that pressure to adhere to social norms stemming from hegemonic masculinity may be negatively linked to the health and well-being of sexual minority youth and adult men (Collier, Van Beusekom, Bos, & Sandfort, 2013; Emslie, Ridge, Ziebland, & Hunt, 2006; Hatzenbuehler, 2011; Ioerger, Henry, Chen, Cigularov, & Tomazic, 2015; Plöderl & Fartacek, 2009; Rieger & Savin-Williams, 2012). The current findings align with these prior studies and suggest that parent or caretaker gender policing is associated with ATOD use and psychological distress among young adult sexual minority men.

Experiences of parental gender policing were associated with recent ATOD use in the multivariable models. Specifically, participants who reported that their parents asked them to stop acting feminine were more likely to use alcohol, tobacco, and marijuana in the prior 2 months. Given that alcohol, cigarettes, and marijuana are the most common substances used by young adults (Substance Abuse and Mental Health Services Administration, 2014), these substances may be most readily available in their social contexts and more likely to be used as negative coping behaviors (Debnam, Milam, Furr-Holden, & Bradshaw, 2016). A dose effect was also observed: Participants who experienced a greater number of disciplinary actions for acting too feminine were more likely to report recent marijuana and prescription drug misuse. Consistent with prior literature with heterosexually identified young men (Oliffe & Phillips, 2008), it might be possible that young sexual minority men use certain substances to comply with different social norms (e.g., use alcohol or cigarettes to appear more masculine in social settings) or to self-medicate in the presence of more severe psychosocial stress (e.g., history of punitive actions). In the current analysis, however, it was impossible to examine whether ATOD use varied based on frequency of parental gender policing and/or the long-term consequences of the disciplinary actions. Consequently, these interpretations remain subject to empirical verification through prospective longitudinal quantitative and qualitative studies.

Psychological distress was associated with having been told by a parent or caretaker to act less feminine in the multivariable models. Participants who reported experiencing parental gender policing had higher depression and anxiety scores than participants who did not experience gender policing. Moreover, a dose–response association between psychological distress and the number of disciplinary actions experienced was identified. These findings coincide with prior research suggesting that gender policing and gender nonconformity are linked to increased mood and anxiety disorders (Skidmore, Linsenmeier, & Bailey, 2006) and lower ratings of general psychological well-being (Rieger & Savin-Williams, 2012; Van Beusekom et al., 2016). Although parents and caretakers may have their children’s best interest at heart when they engage in gender policing, the current findings suggest that parental gender policing is associated with psychological distress. Nevertheless, this study is unable to tease out whether the salience of these associations are moderated by parents’ sociodemographic (e.g., gender, educational attainment) and social (e.g., endorsement of traditional gender norms, sexual prejudice) characteristics, the circumstances behind gender policing (e.g., to shield them from anticipated stigma vs. to make them conform to normative masculine roles), and/or the timing of these behaviors (e.g., childhood vs. adolescence). Future research examining both parent and child experiences of gender policing may help inform family-level intervention strategies for sexual minority young men and their parents.

The univariate analyses also suggested that negative social outcomes may also be linked to gender policing. Specifically, participants who reported parental gender policing were less likely to have finished high school. Given that high school completion is a critical socioeconomic milestone and could potentially be a protective factor in our psychological distress models, future research examining how gender policing may be associated with young sexual minority men’s social advancement is warranted. Moreover, future research should refine and validate the current study’s assessment of gender policing using a larger social network perspective. For instance, it remains unclear whether experiences of gender policing from other key actors in sexual minority young men’s lives (including other family members, friends, and school personnel) have different or additional effects from those of parents or caretakers. In addition to familial, peer, or school settings, future research should examine if the presence of policies (e.g., school, workplace) regarding gender expression are associated with sexual minority young men’s well-being (Gleason et al., 2016).

There are several limitations meriting mention. First, the sample may not be generalizable to all sexual minority young men. Given the absence of a population frame from which to recruit a random sample of sexual minority young men, a convenience sampling method was used. Participants were recruited online, so the current analyses do not include the experiences of men who do not have access to the Internet. Second, this study is cross-sectional by design; therefore, no causal relationships should be inferred from the findings. Third, the data are restricted to sexual minority young men who identify as cisgender (e.g., both their sex assigned at birth and current gender are male); thus, future research examining the relationship between gender policing and the well-being of other sexual (e.g., lesbians) and gender (e.g., gender nonconforming, transgender) minorities is warranted. Fourth, the analyses did not account for participants’ stress, frequency of drug use and misuse, and/or polydrug use. The absence of these indicators in the models may underestimate the true association between gender policing, ATOD use, and psychological distress. Finally, the frequency of parental gender policing and/or the perceived severity ascribed to these actions was not assessed. The findings are further restricted by participants’ recall of gender policing. It is possible that sexual minority young men experienced greater gender policing, but only remember salient events. These variables will be important to consider in future studies that further refine the implications of gender policing on substance use and mental health, and may explain the modest effect sizes observed between gender policing and well-being. Future research that seeks to develop and test more nuanced measures of gender policing may be warranted.

Despite the inherent limitations of the current cross-sectional work, this study reports evidence of both the prevalence of gender policing by parents and caretakers of young adult sexual minority men during childhood and adolescence and negative behavioral health outcomes associated with these experiences. Consistent with prior findings, gender policing behavior was associated with psychological distress among gay and bisexual men (Rieger & Savin-Williams, 2012; Skidmore et al., 2006; Van Beusekom et al., 2016) and with maladaptive coping strategies such as ATOD use (Ioerger et al., 2015). The current study suggests that experiences of gender policing behavior on young adult sexual minority men in childhood and adolescence is significantly associated with higher odds of psychological distress and ATOD use during the transition into young adulthood. The evidence presented here illustrates a need to develop clinical interventions for both parents and young sexual minority men that can address the presence of and potential long-term outcomes associated with gender policing.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project was funded by the National Institutes of Mental Health Career Development Award to Dr. Bauermeister (K01-MH087242).

References

Alanko

Santtila

Witting

Varjonen

Jern

Johansson

. . . Kenneth Sandnabba

(2009). Psychiatric symptoms and same-sex sexual attraction and behavior in light of childhood gender atypical behavior and parental relationships. Journal of Sex Research, 46, 494-504.

Bailey

J. M.

Zucker

K. J.

(1995). Childhood sex-typed behavior and sexual orientation: A conceptual analysis. Developmental Psychology, 31, 43-56.

Bauermeister

J. A.

(2015). Sexual partner typologies among single young men who have sex with men. AIDS and Behavior, 19, 1116-1128.

Carragher

Rivers

(2002). Trying to hide: A cross-national study of growing up for non-identified gay and bisexual male youth. Clinical Child Psychology and Psychiatry, 7, 457-474.

Collier

K. L.

Van Beusekom

Bos

H. M. W.

Sandfort

T. G.

(2013). Sexual orientation and gender identity/expression related peer victimization in adolescence: A systematic review of associated psychosocial and health outcomes. Journal of Sex Research, 50, 299-317.

Connell

R. W.

(1982). Class, patriarchy, and Sartre’s theory of practice. Theory and Society, 11, 305-320.

Connell

R. W.

Messerschmidt

J. W.

(2005). Hegemonic masculinity: Rethinking the concept. Gender & Society, 19, 829-859.

D’Augelli

A. R.

(1991). Gay men in college: Identity processes and adaptations. Journal of College Student Development, 32, 140-146.

D’Augelli

A. R.

Grossman

A. H.

Starks

M. T.

(2008). Gender atypicality and sexual orientation development among lesbian, gay, and bisexual youth: Prevalence, sex differences, and parental responses. Journal of Gay & Lesbian Mental Health, 12, 121-143.

10.

Debnam

Milam

A. J.

Furr-Holden

C. D.

Bradshaw

(2016). The role of stress and spirituality in adolescent substance use. Substance Use & Misuse, 51, 733-741.

11.

Derogatis

L. R.

Spencer

P. M.

(1982). The Brief Symptom Inventory (BSI): Administration and scoring procedures. Baltimore, MD: Johns Hopkins University.

12.

Emslie

Ridge

Ziebland

Hunt

(2006). Men’s accounts of depression: Reconstructing or resisting hegemonic masculinity? Social Science & Medicine, 62, 2246-2257.

13.

Epstein

Ward

L. L.

(2011). Exploring parent-adolescent communication about gender: Results from adolescent and emerging adult samples. Sex Roles, 65, 108-118.

14.

Fields

E. L.

Bogart

L. M.

Smith

K. C.

Malebranche

D. J.

Ellen

Schuster

M. A.

(2015). “I always felt I had to prove my manhood”: Homosexuality, masculinity, gender role strain, and HIV risk among young Black men who have sex with men. American Journal of Public Health, 105, 122-131. doi:10.2105/AJPH.2013.301866

15.

Gleason

H. A.

Livingston

N. A.

Peters

M. M.

Oost

K. M.

Reely

Cochran

B. N.

(2016). Effects of state nondiscrimination laws on transgender and gender-nonconforming individuals’ perceived community stigma and mental health. Journal of Gay & Lesbian Mental Health, 20, 350-362. doi:10.1080/19359705.2016.1207582

16.

Hatzenbuehler

M. L.

(2011). The social environment and suicide attempts in lesbian, gay, and bisexual youth. Pediatrics, 127, 896-903.

17.

Herek

G. M.

Gillis

Cogan

J. C.

(2009). Internalized stigma among sexual minority adults: Insights from a social psychological perspective. Journal of Counseling Psychology, 56, 32-43.

18.

Hill

Menvielle

(2009). “You have to give them a place where they feel protected and safe and loved”: The views of parents who have gender-variant children and adolescents. Journal of LGBT Youth, 6, 243-271.

19.

Institute of Medicine. (2011). The health of lesbian, gay, bisexual, and transgender people: Building a foundation for better understanding. Washington, DC: Author.

20.

Ioerger

Henry

K. L.

Chen

P. Y.

Cigularov

K. P.

Tomazic

R. G.

(2015). Beyond same-sex attraction: Gender-variant-based victimization is associated with suicidal behavior and substance use for other-sex attracted adolescents. PLoS ONE, 10(6), e0129976.

21.

Kane

E. W.

(2006). “No way my boys are going to be like that!” Parents’ responses to children’s gender nonconformity. Gender & Society, 20, 149-176.

22.

Kohout

F. J.

Berkman

L. F.

Evans

D. A.

Cornoni-Huntley

(1993). Two shorter forms of the CES-D Depression Symptoms Index. Journal of Aging and Health, 5, 179-193.

23.

Meyer

I. H.

(2003). Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: Conceptual issues and research evidence. Psychological Bulletin, 129, 674-697.

24.

Oliffe

J. L.

Phillips

M. J.

(2008). Men, depression and masculinities: A review and recommendations. Journal of Men’s Health, 5, 194-202.

25.

Peralta

(2007). College alcohol use and the embodiment of hegemonic masculinity among European American Men. Sex Roles, 56, 741-756.

26.

Peralta

Stewart

B. C.

Steele

J. L.

Wagner

F. A.

(2016). Nonmedical use of prescription drugs in emerging adulthood: Differentiating sex from gender. Addiction Research & Theory, 24, 389-397.

27.

Plöderl

Fartacek

(2009). Childhood gender nonconformity and harassment as predictors of suicidality among gay, lesbian, bisexual, and heterosexual Austrians. Archives of Sexual Behavior, 38, 400-410.

28.

Rieger

Savin-Williams

(2012). Gender nonconformity, sexual orientation, and psychological well-being. Archives of Sexual Behavior, 41, 611-621.

29.

Saewyc

(2011). Research on adolescent sexual orientation: Development, health disparities, stigma, and resilience. Journal of Research on Adolescence, 21, 266-272.

30.

Skidmore

Linsenmeier

J. W.

Bailey

(2006). Gender nonconformity and psychological distress in lesbians and gay men. Archives of Sexual Behavior, 35, 685-697.

31.

Solebello

Elliott

(2011). “We want them to be as heterosexual as possible”: Fathers talk about their teen children’s sexuality. Gender & Society, 25, 293-315.

32.

Substance Abuse and Mental Health Services Administration. (2014). The NSDUH Report: Substance use and mental health estimates from the 2013 National Survey on drug use and health: Overview of findings. Retrieved from https://store.samhsa.gov/shin/content/NSDUH14-0904/NSDUH14-0904.pdf

33.

Van Beusekom

Bos

H. M.

Kuyper

Overbeek

Sandfort

T. G.

(2016). Gender nonconformity and mental health among lesbian, gay, and bisexual adults: Homophobic stigmatization and internalized homophobia as mediators. Journal of Health Psychology. Advance online publication. doi:10.1177/1359105316643378