Mixed-methods examination of adolescent-reported barriers to accessing mental health services

Abstract

Purpose:

Many adolescents struggle to access the mental healthcare they need. To increase access to mental health services, we must have a clear understanding of the barriers adolescents face from their own perspectives. This online mixed methods study aimed to enhance understanding of access barriers by centering the perspectives of diverse adolescents who had recently tried and failed to access mental health support.

Methods:

In this convergent parallel mixed methods study, adolescents responded to a pre-intervention, open-ended question about barriers they have faced to accessing mental health services when they needed them, and shared information about their background and depressive symptoms. Barriers were assessed using inductive, conventional content analysis. Quantitative analyses examined barrier differences across sociodemographic groups.

Results:

All adolescents (ages 11–17, 50% racially minoritized youth, 15% gender diverse youth, 64% LGBTQ+ youth; 78% with clinically-elevated depressive symptoms) reported at least one barrier to accessing mental health support, and 20% reported multiple barriers. Content analysis revealed 13 barrier categories, with parent-related barriers (3 different categories) accounting for 32% of all barriers. The most common barrier categories related to personal and financial constraints. Asian adolescents, adolescents who were 17 or older, and adolescents who reported uncertainty of their gender identity endorsed the numerically highest mean number of barriers to accessing mental health support.

Conclusions:

High-symptom adolescents reported myriad barriers to accessing mental health support, with 32% of all barriers related to parents.

Implications and Contribution:

Findings from this study point to a need to increase parent mental health literacy, strengthen family communication about adolescent mental health needs, and to empower adolescents to independently access safe, effective mental health supports, sometimes regardless of parental support.

Despite great need, adolescents from various demographic backgrounds in the United States do not access effective mental health services.^1–4 Disparities in access to mental healthcare are especially stark for adolescents who hold marginalized identities including Black, Indigenous, and people of Color (BIPOC) and LGBTQ+ adolescents.^5–9 Furthermore, adolescence is a notoriously stressful developmental stage made even more difficult by increased risk for mental health struggles,^1,10 which—if left untreated—can have deleterious long-term consequences impacting schooling, employment, social functioning, physical health, and overall well-being.^11–13 Thus, it is critical to understand the barriers youth face in accessing mental health services, especially as reported by youth themselves, to help improve access for those who need it the most.

Healthcare access is defined as “the opportunity to identify healthcare needs, to seek healthcare services, to reach, to obtain or use health care services, and to actually have the need for services fulfilled.”¹⁴ Barriers to access occur at various levels, from system to individual-level obstacles. At a broader level, there are systemic and logistical barriers related to the accessibility, availability, and affordability of mental health services. Systematic reviews of studies on both caregiver and adolescent perspectives regarding barriers document limited mental health providers, high cost of care, unpredictable insurance coverage, weeks or months-long waiting times, and complex intake procedures.^4,6,15,16 In addition to service system obstacles, logistical barriers include issues such as limited caregiver availability due to work schedule, competing family obligations, and difficulty securing childcare and transportation. ^4,17

Systematic reviews have also identified intangible barriers that deter adolescents from accessing mental health services.^16–19 These include consumer attitudes, beliefs, and knowledge about mental health services. Specifically, limited caregiver and adolescent mental health literacy (i.e., knowledge about mental health and mental health services) has repeatedly been documented as an access barrier.^16–19 Additionally, stigma (i.e., negative or unaccepting attitudes) regarding mental health illness and help-seeking has also emerged as an access barrier.^16,17 However, across reviews, adolescents (relative to caregivers) seem to more consistently endorse stigma as a barrier to accessing mental health support.¹⁹ This incongruence between caregiver and adolescent perspectives suggests a need for focusing on adolescent perspectives.

Centering adolescent experiences and perspectives on mental healthcare access barriers may provide a particularly illuminating and useful firsthand account. This is because when asked directly and apart from caregivers, adolescents may be more likely to share their personal experiences and candid thoughts, offering insight into what barriers they truly experience, which can allow for more targeted approaches to solutions. Two recent systematic reviews focused on the perspectives of adolescents in the U.S. and abroad regarding mental healthcare access barriers, and found that adolescents repeatedly identified perceived social stigma and embarrassment/shame as major obstacles to accessing mental health support.^16,19 Additionally, studies highlighted that adolescents’ concerns about privacy and confidentiality reduced their motivation to seek out support.

Barriers specific to marginalized BIPOC and LGBTQ+ adolescents is another important area of focus. Although some empirical progress has been achieved in this area,^20–22 more studies are needed given that these populations continue to be at greater risk of having unmet mental health needs. In the broader sociocultural context, marginalized BIPOC and LGBTQ+ adolescents are already at a great disadvantage given the systematic and individual forms of oppression they face. Thus, there is a particularly urgent need to focus on healthcare-related issues for these populations, especially mental healthcare access. Notably, we know that adolescents are more likely to access mental health support if they are White as opposed to BIPOC. ^23–25 Additionally, LGBTQ+ youth face discrimination and additional barriers in finding affirming mental healthcare.²⁶ Given the distinct challenges BIPOC adolescents face in the U.S., a recent systematic review focused on barriers unique to these populations.⁸ Lu and colleagues identified barriers related to BIPOC adolescents’ internalizing diagnoses, general stigma, identity-related cultural stigma, and parent-related barriers including their attitudes, beliefs, and fears regarding mental healthcare. Lu et al concluded there is a dearth of empirical research on the mental health access barriers faced by BIPOC adolescents, especially relative to the number of studies focusing on White adolescents. Furthermore, even fewer studies have directly examined differences in barriers by adolescent race/ethnicity.⁸

Despite progress, there are several limitations in the existing literature on barriers to adolescents accessing mental health support. As outlined by Radez et al., one of these limitations is the lack of qualitative/mixed studies that adequately capture the descriptive and disparate nature of barriers reported by adolescents, as opposed to using preconceived quantitative measures. Other limitations in the literature include the mixing of both children and adolescents in samples when focusing solely on one age group (especially adolescents) would provide more specific, pertinent, and actionable information. Furthermore, existing reviews only included studies that were conducted prior to the COVID-19 pandemic, which has seriously negatively impacted the mental healthcare system by increasing demand for services in an already strained system, thus exacerbating pre-existing access issues.^27–29

Another limitation of the current empirical literature on adolescent-perceived barriers is that they have almost exclusively recruited adolescents in community and school settings. This is a considerable gap given that most adolescents (especially those who hold minoritized identities) seek mental health information and support online.³⁰ Thus, recruiting adolescents through the internet maximizes representation as well as information for efforts to streamline access to mental health support for adolescents. Relatedly, increased internet access and use in rural settings has created a pathway to mental health support for adolescents in these settings where there is less access to face-to-face mental health and medical services. In addition, while adolescents may be more willing to share their honest thoughts in a context without their parents, this can be difficult, as parents often need to be involved in the informed consent process for adolescent participants. Also, parental involvement in the consent process may unintendedly lead to a self-selecting sample of parents who are more open to or positive about mental health research/services. Therefore, collecting adolescents’ thoughts through anonymous, online means, with a waived parental consent form, may be important to explore.

Studies on adolescent-reported barriers have seldom centered on the experiences and perspectives of adolescents who are actively struggling with mental health concerns and failing to access support. As such, the existing empirical evidence base on barriers may not extend to the youth whom we most need to understand, those who cannot or are struggling to access support, and asking them about barriers while they are experiencing them.

The present study aimed to address limitations and expand the empirical literature on adolescent-reported barriers by conducting a convergent parallel mixed methods³¹ examination of mental healthcare access barriers reported by a large, online sample of diverse adolescents who were experiencing depressive symptoms and wanting, but failing, to access support. Using concurrently collected qualitative and quantitative data from an ongoing, open pilot trial of brief, online mental health interventions for adolescents (ages 11–17) experiencing depression,²¹ this mixed methods investigation had two aims: First, to conduct an inductive content analysis of adolescent-reported barriers to accessing treatment. Second, to examine differences in barriers based on various adolescent sociodemographic characteristics (e.g., race/ethnicity, sexual minority status) and depressive symptomatology.

Methods

Data for this study were drawn from the baseline questionnaire of an ongoing online program evaluation project, Project YES, which evaluates brief, online, self-guided single-session interventions for adolescent mental health (see Schleider et al., 2020).³² Participants learned about Project YES via unpaid posts to social media websites, paid advertisements on Instagram, or a Vox article highlighting the authors’ research. Social media advertisements included an invitation to participate in an anonymous program evaluation in which “teens can learn new ways of dealing with stress and help others do the same.” Since Project YES is publicly accessible and anonymous, no inclusion or exclusion criteria are used. Thus, adults and children 10 years old or younger may decide to participate, though the Project YES website states it is intended for youths under age 18. Within Project YES, participants are required to report their age range and whether they are adults (>18). Criteria for inclusion in the current analyses included participants whose reported age was 11–17 or older (i.e., adolescents, our population of interest), and who responded to this question: “Have you gotten support for emotional or mental health problems before? By ‘support’, we mean professional therapy, seeing a counselor, or seeing a doctor for any of these problems,” by selecting, “no, but I’ve wanted to get support before.”The original study was deemed exempt by the IRB. We followed the Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines in this report of the study.³³

Procedure

The present study included demographic and qualitative data from 211 participants who responded to a pre-intervention, open-ended question about access barriers. Data used in this secondary data analysis project were collected between August 2019 and November 2020. Overall program evaluation outcomes have been reported previously.³² However, the qualitative data examined in this study have not been previously analyzed or reported.

Measures

Demographics.

Participants self-reported their age (provided in ranges of 2 years to maintain anonymity), sex assigned at birth (male/female/intersex), gender identity, sexual orientation, and race/ethnicity.

Mood and Feelings Questionnaire-Short

(MFQ-S) ³⁴ is a 13-item measure that assesses levels of depression in adolescents. Participants rated the extent to which they agree with thoughts and feelings they may have experienced (e.g., “I felt miserable or unhappy”) in the past two weeks on a 0 to 2 scale of “not true, sometimes, or true.” Total scores range from 0 to 26. Clinical-level depression is indicated by a MFQ-S sum score of 11 or higher. The internal consistency of the MFQ-S in the current sample was α = .92.

Adolescent perceived barriers to accessing mental health support.

Adolescents reported barriers to accessing mental health support only if they endorsed having wanted such support but being unable to receive it in the past. Then, they provided a response to the question, “What kept you from getting mental health support when you wanted it?” Adolescents received no instructions as to the preferred length or content of their response.

Analysis

Three authors conducted an inductive conventional content analysis from December 2020 and to September 2021.³⁵ Initially, the lead coder randomly selected 10% of the total individual responses and distributed them to the two other coders to independently read and develop codes based on patterns they observed, following an inductive approach. All coders then met to discuss response patterns ascertained and to develop a coding manual. All discrepancies and agreements were noted. The lead coder used this information to develop a preliminary codebook, including codes, definitions, and examples of coded text. Next, the coders used the preliminary codebook to independently code a new subset of randomly selected responses. Coding occurred in a format that facilitated quantitative analyses: each code is a variable and coders assigned a 1 (if the response endorses that code) or 0 (if the response does not endorse that code) using Microsoft Excel. Subsequently, all coders met to discuss the most recent round of coding, to reconcile any discrepancies, and to update the codebook as needed. This procedure was repeated until all discrepancies were resolved. Interrater reliability Kappa values ranged from .731 to 1.00. In the few instances where reliability was not met (pre-registered benchmark of .80 or higher), coders met to discuss the discrepancies. Once reliability was achieved, the remaining responses were distributed among coders for independent coding. Then, all the codes were assembled in a master document to be reviewed by two coders to check the accuracy of the master document of all coded responses. After confirming all participant responses were coded accurately, coders met to jointly examine codes and through discussion, agree on whether a code was a distinct barrier category, or whether codes could be merged or split to form a category.

Consistent with a convergent parallel mixed methods approach, after completing the content analysis, descriptive statistics were generated on: (1) the total number of each barrier indicated by youth; (2) total number of barriers endorsed by groups based on demographic variables of interest: ethnicity, age, biological sex, gender minority/non-minority status, sexual minority/non-minority status; (3) frequency of each barriers indicated by demographic variables of interest: ethnicity, age, biological sex, gender minority/non-minority status, sexual minority/non-minority status and (4) total number of barriers indicated by the clinical levels of depression endorsed (MFQ-S sum score of 11 or higher).

Quantitative exploratory analyses examined whether youths reporting marginalized identities (e.g. sexual, gender, and racially minoritized) and youths reporting clinical levels of depressive symptoms reported (1) significantly different total numbers of access barriers, and (2) were differentially likely to endorse each specific barrier identified. Independent sample t-tests were run to examine differences in the total number of treatment access barriers. Paired t-tests were run to examine code specific differences. Bonferroni corrections were applied to each t-test to correct for multiple tests. We processed and analyzed quantitative data in R.³⁶

Results

Pre-registration of all methods and research questions, anonymized participant-level data, the resulting coding manual, and codes for all quantitative analyses reported in this manuscript are available via Open Science Framework (https://osf.io/9d2ev).

Participants identified as 50.23% White, 14.69% Latin/Hispanic, 6.64% Asian, 3.32% African American, 9.00% more than one race, and 16.11% other. Participants were majority female (92.49%), and most (71.36%) were 14–16 years old. Most participants identified with the sex they were born with (85.78%) and reported to identify with diverse sexual orientations. Table 1 reports all participant demographics.

Table 1.

Participant demographics (N=211)

Characteristics	n	% of Total
Race
African American	7	3.32 %
Asian	14	6.64 %
White	106	50.24 %
Latin/Hispanic	31	14.69 %
More than one race	19	9.00 %
Other	34	16.11 %
Age
10 or younger	0	0.00 %
11–13 years old	33	15.49 %
14–16 years old	150	71.09 %
17 or older	28	13.27 %
Biological sex
Female	196	92.89 %
Male	15	7.11 %
Gender identity different from biological sex
No	181	85.78%
Unsure	13	6.16%
Yes	17	8.06%
Sexual orientation
Asexual	3	1.42%
Bisexual	48	22.75%
Gay	2	0.95%
Heterosexual	76	36.02%
Homosexual	4	1.90%
I do not want to respond	8	3.79%
Lesbian	17	8.06%
NA	6	2.84%
Other (please specify)	6	2.84%
Pansexual	14	6.64%
Queer	4	1.90%
Unsure/questioning	23	10.90%

Adolescent responses resulted in 13 access barriers, of which 3 were related to issues with parents (general issues with parents, communication issues with parents, and parent resistance) and accounted for 32% of all barriers. While most adolescents (78.67%, n = 166) indicated one barrier, 17.06% (n = 36) of adolescents indicated 2 barriers, and 4.24% of adolescents indicated 3 to 4 barriers (n = 9). “Other personal constraints” was the most frequently endorsed barrier (n = 38; 14%).The other two most frequently endorsed barriers were “communication issues with parents” (n = 34; 13%)), and financial concerns (n = 34; 13%), with many adolescents noting insurance coverage and cost as barriers. Table 2 contains barrier frequencies, percentages based on minoritized status, definitions, and exemplar responses.

Table 2.

Name, count, percentage, definition, and quote for access barriers. Adolescents (N=211) could indicate more than one barrier.

Barrier	# of adolescents endorsing barrier (%)			Barrier definition	Exemplar response
	Total	Racially minoritizeda n=105	Sexual/gender minoritizedb n=123
Communication issues with parents	34 (13%)	19(56%)	19(56%)	Responses about having trouble communicating with parents.	“I didnt* want to tell me parents because I thought they would blame it on me…”
General issues with parents	29(11%)	9(31%)	19(66%)	Responses about parents, but not specific or do not fit in the other parent categories. Includes responses with only the word “parents” or variations of it.	“I dont want my parents to know how i feel…”
Parent resistance	22(8%)	14(64%)	16(73%)	Responses about parents being “resistant” of or having reservations about mental health issues or services. This can include comments about parents saying this (according to adolescent) or comments where the adolescent anticipates this will be their parent’s reaction.	“my parents didnt think i needed it.”
Parent-related barriers	85(32%)	42(49%)	54(64%)	–	–
Other personal constraints	38(14%)	18(47%)	21(55%)	Responses about specific personal issues such as time constraints, and issues about the self, such as, self-criticism, self-esteem, insecurity, etc.	“i think i sound stupid and no would understand.”
Financial concerns	34(13%)	17(50%)	21(62%)	Responses about lacking financial resources to pursue mental health support.	“Not enough money…”
Fear of disclosure	25(9%)	12(48%)	16(64%)	Responses about having trouble “opening up” or telling others about emotions/mental health issues/needing mental health support.	“Too embarrassed to talk about my emotions with adults.”
General fear/anxiety	22(8%)	12(55%)	6(27%)	Responses noting fear or anxiety but not saying what this is specific to. Often comments with the words, “scared” or “anxiety.”	“I’m too scared to.”
Fear of stigma/judgement	13(5%)	8(62%)	9(69%)	Responses about being afraid of others’ reactions, including judgement or “what others think.”	“Mantality of others. Because if you talk with a psychologist they will say that you suffer from a mental disease. Irritating.”
Lack of support	13(5%)	7(54%)	7(54%)	Responses about a perceived sense of lacking social support.	“no support from anyone close.”
Perceived subclinical severity	10(4%)	1(10%)	6(60%)	Responses expressing mental health struggles as “not that serious.”	“I felt bad asking my parents for anything like therapy because I didn’t feel my problems were very serious.”
Concerns about mental health services	9(3%)	5(56%)	5(56%)	Responses stating concerns or hesitations about the nature/process of mental health services.	“I went to therapy once and it just wasn’t a good time and I hate every moment of it.”
Lack of knowledge about mental health services	9(3%)	5(56%)	4(44%)	Responses about lacking knowledge about mentalhealth issues and/or how to access/maintain/complete mental health services.	“Not knowing who to ask to get the support.”
Lack of access to mental health resources	8(3%)	3(38%)	3(38%)	Responses mentioning resource limitations including lack of providers, long wait times, etc.	“Not having access to credible school counselor because I dont have access at home.”
Total Number of Barriers	266	130(49%)	152(57%)	–	–

^*Exemplar responses are as adolescents typed them. We did not make alternations to fix punctuation and/or grammar.

^aRacially minoritized relative to not racially minoritized

^bSexual/gender minoritized relative to not sexual/gender minoritized

Next, we numerically examined whether barrier means varied by sociodemographic factors, and depressive symptomatology. For these comparisons, we used the mean number of barriers endorsed as this is more appropriate given that the number of participants is not equal across demographic characteristics. The mean number of barriers endorsed was numerically highest by Asian adolescents (M = 1.64, SD = 0.93) compared to adolescents with all other racial identities. Adolescents who were 17 or older reported the highest number of barriers (M = 1.46, SD = 0.74) relative to younger adolescents. Female participants reported a mean number of 1.27 (SD = 0.56) barriers and males reported a mean number of 1.2 (SD = 0.41) barriers. Adolescents who reported uncertainty of their gender identity endorsed the highest mean number of barriers to accessing treatment (M = 1.38, SD = 0.87) compared to adolescents with all other gender identities. Most adolescents reported that they do not identify as heterosexual, with those identifying as bisexual reporting the highest number of barriers (M = 1.33, SD = 0.60). Most of the current sample (N = 164; 78%) endorsed clinical levels of depression (>11 on MFQ-S). Adolescents with clinical levels of depression reported a mean number of 1.27 (SD = 0.57) barriers; adolescents without clinical levels of depression reported a mean number of 1.25 (SD = 0.55) barriers. See Table 3 for all barrier totals and means across demographic and depressive categories.

Table 3.

Total number of barriers endorsed by demographic variables

Race	Total number of barriers endorsed	Mean (SD)	Minimum	Maximum
African American	8	1.14 (0.38)	1	2
Asian	23	1.64 (0.93)	1	4
White	136	1.27 (0.55)	1	3
Latino/Hispanic	37	1.19 (0.48)	1	3
More than one race	23	1.21 (0.54)	1	3
Other	39	1.15 (0.36)	1	2
Age
11–13 years old	37	1.12 (0.33)	1	2
14–16 years old	188	1.25 (0.53)	1	4
17 or order	41	1.46 (0.74)	1	3
Biological Sex
Female	248	1.26 (0.56)	1	4
Male	18	1.2 (0.41)	1	2
Gender Minority
Identifies with bio sex	227	1.25 (0.53)	1	3
Unsure	18	1.38 (0.87)	1	4
Does not identify with bio sex	21	1.24 (0.44)	1	2
Sexual Orientation
Asexual	6	2 (1.73)	1	4
Bisexual	64	1.33 (0.60)	1	3
Gay	2	1 (0)	1	1
Heterosexual	99	1.30 (0.57)	1	3
Homosexual	5	1.25 (0.50)	1	2
I do not want to respond	10	1.25 (0.46)	1	2
Lesbian	17	1 (0)	1	1
NA	7	1.33 (0.52)	1	2
Other (please specify)	7	1.17 (0.41)	1	2
Pansexual	16	1.14 (0.36)	1	2
Queer	4	1 (0)	1	1
Unsure/questioning	28	1.22 (0.52)	1	3

Exploratory Analysis

We statistically compared the mean number of barriers endorsed by various demographic groups. We found differences, however, none of them remained statistically significant after a Bonferroni correction. Given the unequal representation of participants that endorsed each racial/ethnic identity, we grouped participants as endorsing a minoritized identity versus a non-minoritized identity. The average number of barriers endorsed by adolescents with a minoritized racial/ethnic identity (M = 1.24) was not significantly different from adolescents with a non-minoritized identity (M = 1.30) [t(208.99) = 0.60, p = .55]. Although the differences were not significant after applying a Bonferroni correction, on average, White adolescents endorsed “General issues with parents” and “Perceived subclinical severity” significantly more than racially/ethnically minoritized adolescents [General issues with parents: t(188.01) = 2.22, p =.03; Perceived subclinical severity txsz(130.34) = 2.62, p =.01)]. Please see Tables 4 and 5 for all means, standard deviations, and statistics.

Table 4.

Barrier-specific differences in racial minority vs racial non-minority status

Barrier	# of racially minoritized participants who endorsed barrier (n=105)	Percentage of barrier endorsed	M (SD)	# of racially non-minoritized participants who endorsed barrier (n=106)	Percentage of barrier endorsed	M(SD)	P-value of a t-test between the two sample means
General issues with parents	9	8.57%	0.09 (0.28)	20	18.87%	0.19 (0.39)	0.03*
Communication issues with parents	19	18.10%	0.18 (0.39)	15	14.15%	0.14 (0.35)	0.44
Parent resistance	14	13.33%	0.13 (0.34)	8	7.55%	0.08 (0.27)	0.17
General fear/anxiety	12	11.43%	0.11 (0.32)	10	9.43%	0.09 (0.29)	0.64
Fear of disclosure	12	11.43%	0.11 (0.32)	13	12.26%	0.12 (0.33)	0.85
Fear of stigma/judgement	8	7.62%	0.08 (0.27)	5	4.72%	0.05 (0.21)	0.38
Concerns about mental health services	5	4.76%	0.05 (0.21)	4	3.77%	0.04 (0.19)	0.72
Lack of knowledge about mental health services	5	4.76%	0.05 (0.21)	4	3.77%	0.04 (0.19)	0.72
Lack of access to mental health resources	3	2.86%	0.03 (0.17)	5	4.72%	0.05 (0.21)	0.48
Perceived subclinical severity	1	0.95%	0.01 (0.10)	9	8.49%	0.08 (0.28)	0.01*
Financial concerns	17	16.19%	0.16 (0.37)	17	16.04%	0.16 (0.37)	0.98
Lack of support	7	6.67%	0.07 (0.25)	6	5.66%	0.06 (0.23)	0.76
Other personal constraints	18	17.14%	0.17 (0.38)	20	18.87%	0.19 (0.39)	0.75

^*Significant, but only before Bonferroni correction

Table 5.

Barrier-specific differences in sexual/gender minority versus non-minority status

Barrier	# of sex/gen minoritized participants who endorsed barrier n=123)	Percentage of barrier endorsed	M (SD)	# of sex/gen non-minoritized participants who endorsed barrier (n=79)	Percentage of barrier endorsed	M(SD)	P-value of a t-test between the two sample means
General issues with parents	19	15.45%	0.15 (0.36)	8	10.13%	0.10 (0.31)	0.3
Communication issues with parents	19	15.45%	0.15 (0.36)	15	18.99%	0.19 (0.39)	0.51
Parent resistance	16	13.01%	0.13 (0.34)	5	6.33%	0.06 (0.25)	0.13
General fear/anxiety	6	4.88%	0.05 (0.22)	14	17.72%	0.18 (0.38)	0.003*
Fear of disclosure	16	13.01%	0.13 (.34)	9	11.39%	0.11 (0.32)	0.74
Fear of stigma/judgement	9	7.32%	0.07 (0.26)	3	3.80%	0.04 (0.19)	0.30
Concerns about mental health services	5	4.07%	0.04 (0.20)	3	3.80%	0.04 (0.19)	0.93
Lack of knowledge about mental health services	4	3.25%	0.03 (0.18)	5	6.33%	0.06 (0.25)	0.3
Lack of access to mental health resources	3	2.44%	0.02 (0.15)	5	6.33%	0.06 (0.25)	0.17
Perceived subclinical severity	6	4.88%	0.05 (0.22)	4	5.06%	0.05 (0.22)	0.95
Financial concerns	21	17.07%	0.17 (0.38)	13	16.46%	0.16 (0.37)	0.91
Lack of support	7	5.69%	0.06 (0.23)	6	7.59%	0.08 (0.27)	0.59
Other personal constraints	21	17.07%	0.17 (0.38)	13	16.46%	0.16 (0.37)	0.91

^*Significant, but only before Bonferroni correction

There was no significant difference in the mean number of barriers endorsed by sexual/gender minoritized adolescents (M = 1.24) versus non-minoritized adolescents (M = 1.30) [t(162.42) = 0.85, p =.40]. Although the difference was not significant after applying a Bonferroni correction, sexual/gender minoritized adolescents endorsed “general fear/anxiety” (M = 0.05) as a barrier to accessing mental health support significantly less than non-minoritized adolescents (M = 0.18) [t(110.06) = 2.70, p = .003] before the Bonferroni correction. Finally, we also did not find a significant difference in mean number of barriers endorsed by those with clinical levels of depression versus those with subclinical levels of depression, based on a score of ≥11 on the Short Mood and Feelings Questionnaire [t(182) = −0.14, p = 0.98].

Discussion

Through this online, mixed methods study we directly asked a large and diverse sample of adolescents about the barriers they faced in accessing mental health support when they needed it. All adolescents reported at least one barrier, and over 20% reported more than one barrier. Inductive, conventional content analysis revealed 13 distinct barrier categories, 3 of which were related to parents, and accounted for 32% of all barriers. The three most common barrier categories pertained to personal constraints, communications issues with parents, and financial concerns.

Parent-related barriers to accessing mental health services emerged at the forefront of this study. These barriers included communication issues with parents, parent resistance to or disagreement with their child seeking support, including minimizing mental health concerns, and other general issues with parents. The prevalence of parent-related barriers is concerning even though it makes sense given that this sample of adolescents was seeking mental health support online, without the requirement of parental guidance and consent. This may indicate a need for multidimensional mental healthcare access solutions. Solutions might focus on the parent-child relationship in situations where the adolescent and parent are struggling to communicate, especially about mental health issues. Solutions focused on mental health literacy resources for parents, particularly focused on supporting treatment-seeking, may also help. A relevant, promising approach that is currently under investigation is the use of outreach presentations to parents by “key opinion leader” parents that aim to increase parent mental health help-seeking for their children.³⁷ One thing to keep in mind when conceiving of mental healthcare access solutions that focus on the parent-child relationship is the importance of accounting for culture and contexts. For example, the content of these solutions/programs might differ if adolescents are having trouble communicating with parents due to their LGBTQ+ identity, versus because their family’s culture historically doesn’t acknowledge/talk about mental illness. Increasing access to mental health services that require minimal parental guidance and no parent consent may also reduce obstacles for adolescents.

The other categories adolescents in this study most endorsed were personal and financial constraints. Personal constraints included time constraints and issues about the self, such as, self-criticism, self-esteem, and insecurity. Financial constraints included lacking insurance and other concerns about costs related to mental health services. These barriers have been reported before, and are consistent with the “affordability” (i.e., ability to pay for health services) dimension of the Levesque, Harris, & Russel’s healthcare access framework.¹⁴ These barriers also highlight a need for increased availability of free mental health support such as through free and publicly available single-session interventions for adolescents.^38,39 Interestingly, the least endorsed barriers were all related to issues about mental health services and knowledge, which are more distal from adolescents’ everyday personal experiences and feelings (e.g., their interactions with their parents; how they feel about themselves). This may indicate that adolescents are more likely to perceive and report access barriers that feel most proximal in terms of their personal experience.

We also numerically examined and found that Asian adolescents, adolescents 17 or older, and adolescents who reported uncertainty of their gender identity endorsed the highest mean number of barriers to accessing mental health support. These results are consistent with past findings that indicate Asians access mental health support at low rates despite experiencing clinical-level symptoms.⁴⁰ Additionally, by age 17 more mental health problems have likely onset or grown more severe, yet access barriers have not diminished. We also examined and did not find significant differences in average number of barriers endorsed by various groups (e.g., minoritized versus non-minoritized adolescents). This may be explained by the small range of barriers endorsed by each adolescent since most of the sample reported only one barrier. Such differences in the number of barriers reported by adolescents may be related to other unassessed variables such as recency effects (e.g., having just experienced a specific barrier), verbal abilities (e.g., ability to summarize the barriers in their own words), or even time constraints. Additionally, briefer responses may be a result of collecting responses through writing. Future studies should consider more in-depth qualitative methods (e.g., individual interviews or focus groups) to assess adolescent-reported barriers.

The greatest strength of this study is the representation of diverse adolescent perspectives captured in an online setting natural to adolescents. Additionally, our use of mixed methods allowed us to examine adolescent responses closely and systematically. Relatedly, participants were not restricted in their responses in any way, as they were answering an open-ended question, which allowed us to collect a range of responses unrestricted by preconceived barrier categories. This study also had several limitations. Given the online nature, it is impossible to confirm demographic information. Based on the demographic information we collected, very few adolescents (n = 18) reported their biological sex as male. Thus, our sample and their perspectives were mostly limited to those who identified as biologically female. We also excluded non-English speakers, and the unequal number of participants in various demographic characteristics limited our analysis. We also only assessed adolescents’ depressive symptoms, which may not represent their full clinical picture. Further, the sample is restricted to adolescents who self-selected to seek treatment online as part of a larger, brief treatment study. Thus, we may not have captured the range of barriers of those who were not able to connect to any kind of treatment.

Adolescents are in a uniquely vulnerable position in the mental healthcare system as they are growing into their independence yet may lack the knowledge, ability, and resources to independently navigate and access a complex mental healthcare system without parental guidance. Furthermore, depending on their age, and where they live, they may not be able to access mental health services at all, without parent consent.⁴¹ The prevalence of parent-related barriers highlights the need for future studies to evaluate and address treatment access barriers based on multiple perspectives – including both parents and their children. Waiving parental consent in this study proved to be an important method of collecting diverse youth opinions and creating a safe environment to freely share their thoughts; such benefits should be widely considered in studies examining youth perspectives in various contexts. Given that parent-related barriers were commonly endorsed by adolescents, efforts to increase mental health literacy and reduce stigma related to treatment seeking in parents is warranted. Further, an increased focus on repairing parent-child relationships and/or aligning treatment goals between the parent and adolescent child may be important to consider even after youth connect to mental health supports.