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. Author manuscript; available in PMC: 2025 Feb 25.
Published in final edited form as: Subst Use Misuse. 2024 Feb 25;59(7):1031–1038. doi: 10.1080/10826084.2024.2320371

Examining the Role of Cultural and Family Factors in Substance Use Risk among Indian American Youth

RS John 1,*, M Amodeo 2, P Montero-Zamora 3, SJ Schwartz 3, CP Salas-Wright 4
PMCID: PMC11034790  NIHMSID: NIHMS1978165  PMID: 38403989

Abstract

Introduction:

Although Indian Americans constitute the second-largest immigrant group in the United States, there is a paucity of information about Indian American youth, particularly with respect to substance use risk. We examined the relationship of social factors to permissive substance use beliefs (a proxy for substance use risk since they can lead to adulthood substance use and misuse) and family functioning.

Methods:

The study used structural equation modeling to examine the prevalence of permissive substance use beliefs in a sample of Indian American youth ages 12–17 (N=223) and examined the degree to which discrimination, bicultural identity integration, and endorsement of the model minority stereotype were associated with permissive substance use beliefs.

Results:

Findings suggest that bicultural identity integration (B=0.267 [SE=0.112], p=.01) and discrimination (B=0.294 [SE=0.087], p=.001) are positively associated with permissive substance use beliefs. Bicultural identity integration (B=0.415 [SE=0.090], p=.0001) was positively associated with family support (B= −0.329 [SE=0.108], p=.002) which, in turn, was associated with less permissive substance use beliefs. In contrast, endorsement of the model minority stereotype (B=0.351 [SE=0.090], p=.001) was positively associated with family closeness (B=0.232 [SE=0.927], p=.01) which, in turn, was associated with family support and then with less permissive substance use beliefs.

Conclusions:

Discrimination and bicultural identity integration emerged as key constructs related to substance use risk among Indian American youth. These youth could benefit from culturally appropriate prevention programming that addresses the negative impact of discrimination and its effect on permissive substance use beliefs and highlights protective factors.

Keywords: cultural factors, permissive substance use beliefs, adolescence, model minority stereotype, family functioning

1. Introduction

Four million Indian Americans (those born in India and those born in the U.S. to Indian parents) reside in the United States (U.S.). Indian Americans constitute the nation’s second-largest foreign-born population group (Badrinathan et al., 2021; Budiman, 2021); it is rapidly growing and is decidedly young, as over 40% are under the age of 30 (Budiman, 2021). Many Indian American youth experience discrimination and psychological distress (Basri et al., 2022; John et al., 2022; Karasz et al., 2019; Sharma and Shaligram, 2018). However, prior research has not examined how discrimination and other culture-related issues, such as bicultural identity integration and the model minority stereotype, contribute to substance use risk among these youth.

Recent studies with Asian American youth (although not Indian American youth) suggest unique challenges associated with immigration and behavioral health (Park et al., 2021; Woo et al., 2019). Among Asian American young adults and youth, exposure to culture-related stressors can lead to impaired family functioning which, in turn, can increase risk for many behavioral outcomes, including substance use initiation (Shaligram et al., 2022; Sharma and Shaligram, 2018). Indian Americans are underrepresented in this research (Lui and Zamboanga, 2018). However, a study using nationally representative data showed that Indian Americans have high alcohol, illicit drug and cannabis use (Ahmmad and Adkins, 2021).

This study focuses on permissive substance use beliefs, a concept which is robustly associated with substance use initiation and misuse (Barkin et al., 2002; Elder et al., 2000; Salas-Wright et al., 2017). Cultural stress theory is used as a framework to understand how migration related stressors such as discrimination and bicultural identity integration can impact behavioral health and family relationships (Salas-Wright and Schwartz, 2019). Moreover, since the model minority stereotype is central to the experience of Indian American youth, it is important to examine the contribution of this construct to determine its impact (Saran, 2015). The study examines the association between discrimination, bicultural identity integration and model minority stereotype endorsement --- and substance use risk---- among Indian American youth, both directly and via family functioning (Salas-Wright et al., 2021; Salas-Wright and Schwartz, 2019). Discrimination involves the unfair behaviors of individuals/groups toward other individuals/groups through negative attitudes and judgments due to institutional and systemic bias (Banks et al., 2006; Pascoe and Richman, 2009). Bicultural identity integration is the degree to which an individual perceives their dual cultures to be compatible or contradictory (Benet-Martínez and Haritatos, 2005).

Model minority stereotype is the belief that Asian Americans, including Indian Americans, perform better than other minority groups academically, socially, and professionally (Hartlep, 2021). It casts Asian Americans as the “model” minority group, well behaved, industrious and successful; provides an illusion to society of “success,” while creating unrealistic standards of achievement (Cherng and Liu, 2017); and refers to Asian Americans as a monolithic group, ignoring the vast cultural disparities within the group. Since researchers aggregate results when studying Asian American youth, there is little reliable information on substance use among these youth (Gordon et al., 2019; Hai et al., 2021; Kauh et al., 2021).

Discrimination has been linked to externalizing behaviors such as stealing and drinking among immigrant youth (Lorenzo-Blanco and Unger, 2015). For instance, Cano and colleagues (2015) found that, among recently immigrated Latinx adolescents, discrimination along with other cultural stressors predicted high alcohol and cigarette use. The link between discrimination and externalizing behaviors has been understudied in Indian Americans. However, research on Asian Americans show an association between discrimination and substance use (Gee et al., 2009; Spencer et al., 2023; Yoo et al., 2010b). There is limited research on how bicultural identity integration impacts substance use among the immigrant population (Zamboanga et al., 2020). However, high bicultural identity integration has been associated with lower stress in college-age Latino students (Yim et al., 2019).

The model minority stereotype, when accepted by providers and researchers, can interfere with an accurate assessment of substance use among Asian American youth, since it conveys the idea that Asian American youth are too well behaved and high achieving to engage in such behaviors (Saran, 2015; Sharma and Shaligram, 2018). Also, Indian American youths’ efforts to conform to the stereotype may lead them to withhold information about their substance use.

Family is an important part of an adolescent’s support system and can impact youth outcomes (Prado et al., 2012). The basic components of family functioning are parenting practices (i.e., discipline and monitoring) and relationship characteristics such as cohesion, beliefs about the importance of family, and organizational structure (Gorman-Smith et al., 2000). Positive family functioning includes factors such as high levels of family support, clear parent/adolescent communication and family bonding (Cordova et al., 2014). Researchers (Fan and Chen, 2012; Vandewater and Lansford, 2005; Yeh et al., 2016) found that family functioning has mediating effects on adolescent health and externalizing and internalizing behaviors. Schwartz and colleagues’ research (2013) with Latinx adolescents also demonstrates that family functioning (parental involvement, parent-adolescent communication and positive parenting) has a mediating effect on adolescent biculturalism and risky health behavioral outcomes.

2. Methods and materials

2.1. Procedures

Recruitment used peer and community representative referrals. A cross-sectional online survey on Qualtrics was administered to 223 Indian American youth who were 12–17 years of age, resided in the U.S., spoke and read English, and had one or more parents who were born in India (Moreno et al., 2020). A recruitment flier was sent to community agencies and individuals working with this population across the U.S. who were asked to distribute the flier and encourage youth to participate. Youth who were interested in participating clicked on the link in the flier to review the assent statement and provide assent. Researchers obtained informed consent from the parents as well as assent from the youth. Youth who completed the survey received a $10 gift card. The Institutional Review Board of the first author’s university approved the study.

2.2. Measures

Discrimination was measured by seven questions adapted from the Perceived Discrimination Scale (Phinney et al., 1998) using a 5-point Likert scale from 1 (never) to 5 (daily or nearly daily) (α=.89). Sample items include: “How often do teachers treat you unfairly or negatively because of your ethnic background, and “How often do people your age treat you unfairly or negatively because of your ethnic background?”

Bicultural identity integration was measured by the eleven statements in the Bicultural Identity Integration survey (Huynh, 2009; Huynh et al., 2011) using a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree) (α=.76). Sample items include: “I find it easy to balance both Indian and American cultures,” and “I feel that Indian and American cultural orientations are incompatible.”

Model Minority Stereotype was measured using the 10-item “achievement orientation” subscale of the Internalization of the Model Minority Myth Measure (Yoo et al., 2010a). The achievement orientation subscale measured the participants’ belief that Indian Americans are more successful because of their hard work (REF). All items were on a 7-point Likert scale from 1 (strongly disagree) to 7 (strongly agree) (α=.85). Sample items include: “Indians are harder workers, and “Indians get better grades in school because they study harder.”

Family Functioning was measured by The Family Relations Scale and Multidimensional Scale of Perceived Social Support. The Family Relations Scale (Olson, 1985) is a six-item questionnaire with a 4-point Likert scale from 1 (not at all true) to 4 (almost always or always true) (α=.81). Sample items include: “We can easily think of things to do together as family,” and “Family members like to spend free time with each other.” Finally, participants used a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree) (α=.92) to respond to four questions from the Multidimensional Scale of Perceived Social Support (Zimet et al., 1988). Sample items include: “We ask questions when we don’t understand each other,” and “I can talk about my problems with my family.”

Permissive Substance Use Beliefs were measured by three questions on intention to use alcohol, cigarettes and cannabis (Hansen and Graham, 1991), for example, “Is it okay for someone my age to (a) drink alcohol/ (b) smoke cigarettes/ (c) use marijuana?” (1= definitely not okay, 4=definitely okay) (α=.67). Literature on permissive substance use beliefs show that it is a strong predictor of use later in life (Salas-Wright et al., 2020).

Sociodemographic Data was collected on age (12–17), sex (male, female), grade (6th–12th), country of birth (US, India, other) and perceived family economic status taken from the Health Behavior of School Aged Children study (Roberts et al., 2009).

2.3. Analysis

All analyses were performed using Mplus 8, a widely used statistical modeling software developed by Muthén & Muthén (2011), is extensively employed for analyzing intricate data structures, focusing on applications in structural equation modeling and path analysis. First, preceding the primary analysis, we estimated a measurement model, using confirmatory factor analysis, to ensure the adequacy of latent measures (i.e., discrimination, bicultural identity integration, model minority stereotype, family support, and family closeness) before their integration into the hypothesis test of associations among all constructs in the final model. Second, following the measurement evaluation, we made necessary modifications to enhance the model fit, and these refined elements were integrated into the final model.

Finally, we estimated a structural model (SEM) to examine the study questions using Mplus 8. SEM was used to examine the degree to which cultural stress factors and endorsement of model minority stereotype relate to permissive substance use beliefs (Figure 1). SEM is an umbrella for many approaches such as path analysis, factor analysis and multiple regression and allows for both observed and latent (unobserved) variables in a model (Crockett, 2012). Although the data are cross-sectional (cannot be used to infer causal relationships or mediation), we examined indirect effects. Using latent variables, we examined direct paths from the exogenous factors (discrimination, bicultural identity integration, and model minority stereotype) to intervening variables (family support, family closeness), and from intervening variables to the outcome (permissive substance use beliefs). We also allowed for direct paths from the exogenous factors to the outcome, so that we could examine both direct and indirect associations.

Figure 1:

Figure 1:

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Hypothesized Relationships Among Variables

The hypothesized SEM model

We evaluated model fit using one incremental fit index (the Comparative Fit Index [CFI]) and one absolute fit index (root mean square error of approximation [RMSEA]). Broadly, good model fit can be indexed as CFI ≥ .95 and RMSEA ≤ .06 (Hoyle, R. (Ed.), 2012), although values that deviate somewhat from one of these cutoffs should not necessarily be taken as invalidating a specified model (Lai and Green, 2016). The RMSEA index also provides a 90% confidence interval, which ideally should not surpass the proposed cutoff for the point estimate (Hoyle, R. (Ed.), 2012)

3. Results

Table 1 presents descriptive statistics and substance use information on participants (n=204). Fifty-one percent of participants were boys; the average age was 15 (15.51 ± 1.21). The largest group was in 9th grade (22%), followed by 11th grade (21%). Most participants (76%) were born in the U.S. Forty-six percent thought their family was of “average” affluence. The mean values for permissive substance use beliefs were higher for alcohol (M=1.90, SD=0.85), than for cannabis (M=1.70, SD=0.89) or cigarettes (M=1.67, SD=0.84). The answers to these questions ranged from “definitely okay” to “definitely not okay.” For a detailed breakdown of response option distributions by substance and age categories (12–13, 14–15, 16 years and older), please refer to Appendix 1.

Table 1:

Descriptive and Substance Use Statistics of the Analytic Sample

Full sample of youth
(N=223)
Variable Mean SD Range
Age 15.51 1.21 (12-17)
Sex (%) - - -
 0. Girl 47.55 - -
 1. Boy 51.47 - -
Grade 9.58 1.55 (6-12)
Country of birth (%)
 1. United States 75.98 - -
 2. India 23.04 - -
 3. Other 0.98 - -
Family economic status
 Not well off 10.29 - -
 Average 45.59 - -
 Quite well off 36.76 - -
 Very well off 7.35 - -
Substance use risk
 Permissive Substance Use Beliefs
  Alcohol 1.90 0.85 (1-4)
  Cannabis 1.70 0.89 (1-4)
  Cigarettes 1.67 0.84 (1-4)
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The original structural model (i.e., measurement model) had modest fit, χ 2(576) = 842.42, p < .001; CFI = .889; RMSEA = .054 (90% CI = .046-.062). Stepwise reduction was conducted using factor and content analysis to re-fit the model (Derksen and Keselman, 1992). Factor loadings for each latent variable were examined for indicators that did not meet either the threshold for cutoffs greater than 0.32 (Comrey and Lee, 1992) and/or did not align with the extant literature. Our first step included removing negative worded items (n=6) from the bicultural identity integration scale (e.g., I feel that Indian and American cultural orientations are incompatible). These items were initially reverse-coded and were confusing for participants. We removed these six items to enhance clarity and accuracy in participant responses. Next, we eliminated sex and age from the SEM model since these covariates were insignificant predictors. Also, we identified that bicultural identity integration did not significantly influence family relations, so we removed this potential association from the model, allowing us to have a more parsimonious model. Finally, we removed three items from the family support scale to be consistent with our threshold cut-off criteria (>0.32). The revised model fit the data adequately, χ 2(534) = 727.01, p < .001; CFI = .924; RMSEA = .047 (90% CI = .038-.055). The proportion of total variance explained by our intervening variables (i.e., endogenous variables) was .40 (family support= .17; family relations=.12; substance use intentions=.11).

As shown in Figure 2, bicultural identity integration (B=0.267 [SE=0.112], p=.01), and discrimination (B=0.294 [SE=0.087], p=.001) were both positively associated with permissive substance use beliefs. Bicultural identity integration (B=0.415 [SE=0.090], p=.0001) was positively associated with family support (B= −0.329 [SE=0.108], p=.002) which, in turn, was associated with less permissive substance use beliefs; endorsement of the model minority stereotype (B=0.351 [SE=0.090], p=.001) was positively associated with family closeness (B=0.232 [SE=0.927], p=.01) which, in turn, was positively related to family support and then was associated with less permissive substance use beliefs. In addition, discrimination (B=−0.237 [SE=0.093], p=.01) was associated with less family closeness which was positively associated with family support and then, in turn, with less permissive substance use beliefs. In relation to indirect effects, we identified a significant specific indirect effect exclusively from the endorsement of the model minority stereotype to family support through bicultural identity integration (B=0.084 [SE=0.035], p=.02). It’s important to note that all reported estimates are standardized coefficients.

Figure 2:

Figure 2:

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Coefficients for final model

The final model (Figure 2) displays both the direct and indirect effects of the latent variables.

4. Discussion

This study examined the degree to which discrimination, bicultural identity integration and endorsement of the model minority stereotype were associated with permissive substance use beliefs among a sample of Indian American youth. Discrimination and bicultural identity integration were linked to permissive substance use beliefs. The finding of direct effects for discrimination was consistent with prior studies (Kulis et al., 2009; Salas-Wright et al., 2020; Schwartz et al., 2015a). However, unexpectedly, findings suggest that greater bicultural identity integration was associated with more permissive substance use beliefs. Bicultural identity integration is thought to be adaptive in relation to behavioral health but it may be capturing greater acculturation which has been shown to be related to greater substance use risk in immigrant samples (Ahmmad and Adkins, 2021; Schwartz et al., 2011).

The relationship between endorsement of the model minority stereotype and positive family functioning is consistent with the literature on Indian American family upbringing and youth development: Indian American adolescents can feel compelled to uphold the expectations and beliefs of their parents (Alexander et al., 2021) which thereby facilitates less conflict (Farver et al., 2007). Future studies should examine whether these findings also hold for young adults, who likely have greater independence from their parents. The relationship between positive family functioning and less permissive substance use beliefs is consistent with literature on how relationships with parents can influence adolescent risky behaviors (Loke and Mak, 2013; Salas-Wright and Schwartz, 2019).

Bicultural identity integration was positively associated with family support, which was then associated with less permissive substance use beliefs; thus, family support served as a protective factor. Individuals with higher bicultural identity integration are more likely to report positive family functioning and less family conflict (Schwartz et al., 2015b; Smokowski and Bacallao, 2011). However, bicultural identity integration had a direct positive association with permissive substance use beliefs. Because most youth were second-generation, they may have had higher bicultural identity integration than their first-generation peers and were able to navigate family expectations while also fitting in with their friends regarding substance use beliefs.

We underscore that there is no direct path from model minority stereotype to family support, which makes sense as bicultural identity functions as an essential bridge that allows a parent to successfully engage and support their more bicultural child. For example, an adolescent may internalize the model minority expectations that they should excel in academic environment by studying hard and prioritizing academics while navigating expectations of their U.S. peers (maintain bicultural identity integration that is compatible). The notion here is that, when a youth internalizes or embraces such values, they may be able to manage not only more comfortably U.S.- but also Indian cultural expectations and, in turn, experience greater support from their parents (who are, presumably, pleased by their child’s conduct).

Study limitations include: (1) Causal conclusions cannot be drawn from this cross-sectional survey (Levin, 2006). (2) The prevalence of substance use can change over time, as can prevalence of discrimination, endorsement of model minority stereotype, and family functioning. (3) Measures were self-reported which can create a social desirability bias (Paulhus, 1984). (4) We recruited participants using a non-probability sampling method, where participants were selected based on convenience or availability rather than a random or systematic approach. Consequently, this approach limits the extent to which our study findings can be extrapolated or applied to the larger Indian American population in terms of demographic, cultural, and socioeconomic characteristics of the broader Indian American community. Further research employing a more representative sampling methodology would be valuable for a comprehensive understanding of this population(Tyrer and Heyman, 2016).

5. Conclusions

This study expanded on research on permissive substance use beliefs to include Indian American youth, a population rarely addressed in the literature. Discrimination and bicultural identity integration were major influences regarding permissive substance use beliefs. Indian American youth could benefit from culturally appropriate prevention programming addressing the negative impact of discrimination and its effect on permissive substance use beliefs and emphasizing positive family relationships and greater bicultural identity integration. Since findings showed that discrimination and less bicultural identity integration led to permissive substance use beliefs, youths’ intention to use substances and peers’ substance use (Cheng et al., 2018) should also be explored.

Appendix 1. Frequencies and proportion of response endorsement for permissive substance use beliefs by type of substance and age categories

variable Full sample of youth 12 to 13 years 14 to 15 years 16 to 17 years p-value
It is okay for someone my age to drink alcohol
1. Definitely not 88 (40%) 10 (59%) 39 (45%) 39 (34%) 0.052
2. Not okay 68 (31%) 4 (24%) 20 (23%) 44 (38%) 0.052
3. Okay 51 (23%) 2 (12%) 19 (22%) 30 (26%) 0.052
4. Definitely 12 (5%) 1 (6%) 8 (9%) 3 (3%) 0.052
Mean Score (SD) 1.94 (0.92) 1.65 (0.93) 1.95 (1.03) 1.97 (0.92) 0.392
It is okay for someone my age to smoke cigarettes
1. Definitely not 125 (58%) 13 (81%) 48 (56%) 64 (55%) 0.27
2. Not okay 52 (24%) 1 (6%) 22 (26%) 29 (25%) 0.27
3. Okay 33 (15%) 1 (6%) 11 (13%) 21 (18%) 0.27
4. Definitely 7 (3%) 1 (6%) 4 (5%) 2 (2%) 0.27
Mean Score (SD) 1.64 (0.86) 1.38 (0.88) 1.65 (0.89) 1.75 (0.86) 0.436
It is okay for someone my age to use marijuana
1. Definitely not 125 (57%) 12 (71%) 55 (64%) 58 (50%) 0.061
2. Not okay 48 (22%) 2 (12%) 13 (15%) 33 (28%) 0.061
3. Okay 38 (17%) 1 (6%) 14 (16%) 23 (20%) 0.061
4. Definitely 9 (4%) 2 (12%) 4 (5%) 3 (3%) 0.061
Mean Score (SD) 1.69 (0.80) 1.59 (1.06) 1.62 (0.92) 1.75 (0.86) 0.512
Sample Size 223 17 87 119
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Footnotes

The authors report there are no competing interests to declare.

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