Clinical Need,Perceived Need,and Treatment Use: Estimating Unmet Need for Mental Health Services in the Adult Population

Abstract

Estimates of unmet need for mental health services in the adult population are too high because many recover without treatment. Untreated recovery suggests that individuals accurately perceive professional help as unnecessary and do not pursue it. If so, perceived need for treatment should predict service use/nonuse more strongly than the presence or seriousness of disorder. With National Comorbidity Survey-Replication data, respondents who recovered from prior disorder by the current year (N = 1,054) were compared to currently unrecovered respondents with less serious (N = 999) and more serious disorders (N = 294). Perceived need covaried positively with the presence and seriousness of disorder and linked to far higher odds of treatment use than disorder seriousness, supporting perceptual accuracy. Two-thirds of respondents who perceived a treatment need obtained care; only one-third had unmet need. Need perceptions may better estimate a treatment gap and prompt research on individuals’ self-assessments and treatment decision-making.

Keywords

mental disorders mental health service use mental health treatment perceived need for care unmet need

Although mental health treatment rates have increased over the past 20 years, the prevalence of mental disorder has remained persistently high (Johnson 2021; Kessler, Demler, 2005; Mojtabai and Jorm 2015). Within any 12-month period, about 20% to 25% of the U.S. adult population—one of every four or five adults—meets diagnostic criteria for having a mood, anxiety, or substance use disorder (Hedden et al. 2012). Because mental disorders can impair individuals’ abilities to function at school, work, or home, estimating population needs for mental health services and understanding barriers to treatment access have been central research endeavors for psychiatric epidemiologists and sociologists of mental health.

The purpose of treatment, of course, is to reduce symptoms and promote improved functioning, that is, to produce recovery or remission.¹ Researchers generally assume that (a) a need for care depends on the seriousness of an individual’s clinical disorder; (b) seeking care depends on the person’s need perceptions, treatment attitudes, and structural circumstances (Andersen 1968, 2008); and (c) recovery and well-being depend on treatment receipt, where “treatment” encompasses hospitalization, psychotherapy, and psychotropic medications. In epidemiological research, people who have met criteria for a mental disorder are considered to have a “clinical need” for treatment, and those who are not currently receiving services have an “unmet need” for care. However, the prevalence of untreated recoveries from disorder suggests that traditional estimates of unmet need are too high (e.g., Sareen et al. 2013; Thoits 2022; Wang et al. 2017). This article proposes that compared to clinically defined need, individuals’ perceived need for treatment may better predict their service use, which in turn determines the degree to which mental health treatment needs in the population are met versus unmet.

Background

Untreated and Treated Recoveries and the Problem of Estimating Population Need

In epidemiological studies since 2000, mental disorders have been defined by criteria outlined in the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; American Psychiatric Association 1994), and recovery exists when individuals no longer meet diagnostic criteria. Epidemiological surveys show that roughly half of all adults who have had any lifetime or past-year mental disorder subsequently recovered (Jones, Noonan, and Compton 2020; Préville et al. 2010; Sareen et al. 2013; Thoits 2022; Wang et al. 2017). Furthermore, about half of recovered adults attained remission without receiving treatment (Grella and Stein 2013; Henriksen et al. 2015; Jones et al. 2020; Sareen et al. 2013; Thoits 2022; Wang et al. 2017). People with alcohol and/or drug use disorders have the highest untreated recovery rates (70%–80%; Grella and Stein 2013; Jones et al. 2020); those with mood/depressive disorders have lower rates (45%–55%; Sareen et al. 2013; Wang et al. 2017).

Investigators describe untreated recoveries as “natural,” “spontaneous,” or “transient cases of acute distress” (e.g., Granfield and Cloud 2001; Wang et al. 2017), attributing them to clinical conditions that were not serious in the first place. In general, epidemiological research finds that people with more serious disorders are more likely to be in treatment (Chen et al. 2013; Roberts et al. 2018; ten Have et al. 2013; Wang et al. 2017; The WHO World Mental Health Survey Consortium 2004). One study found that untreated recoveries were fully explained by adults having less serious initial disorder (Thoits 2022). The prevalence of both “natural” and treated recoveries is important because epidemiologists typically estimate unmet need for mental health services as the proportion of adults with any current DSM-defined disorder who are not presently receiving mental health care (Kessler, Chiu, et al. 2005; Kessler, Demler, et al., 2005; Wang et al. 2017). If roughly half of all adults with a clinically defined disorder are likely to recover and about half of those who recover do so without treatment, then estimates of unmet population need are too high, as critics often point out (e.g., Mechanic 2003; Roberts et al. 2018; Sareen et al. 2013; Slade and Longden 2015). Overestimates create policy and fiscal dilemmas: Where should scarce resources be directed for maximum effect—the general medical sector, the mental health specialty sector, to public health interventions (Sareen et al. 2013)? Should funding priorities be placed on severe disorders that require extensive care or on less serious conditions because brief treatment might avert long-term severe illness (Kessler et al. 2003)?

The usual way that unmet and met clinical needs are estimated in epidemiological research is depicted in Table 1, Panel A, Cells c and d. Cells c and d hold percentages of adults with a current disorder who are and are not presently receiving care. Because a comparison group is often left unspecified, Cells a and b of Panel A are usually not filled or reported. The implicit comparison is to the vast majority of people (75%–80% of the adult population) who are currently clinically well and thus assumed not to need mental health services.²

Table 1.

Unmet Need among Persons with One or More Prior Disorders.

Panel A. Estimates of Unmet and Met Any Clinical Need
	No Current Disorder	Any Current Disorder
	a	c
Not currently in treatment	Recovered (never or previously treated)	Unmet need
	b	d
Currently in treatment	Recovered (managing symptoms)	Met need
Panel B. Estimates of Unmet and Met Serious Clinical Need
		Less Serious	More Serious
	No Current Disorder	Current Disorder	Current Disorder
	a	c	e
Not currently in treatment	Recovered (never or previously treated)	Untreated	Unmet need
	b	d	f
Currently in treatment	Recovered (managing symptoms)	Treated	Met need
Panel C. Estimates of Unmet and Met Perceived Need
	No Current Perceived Need	Current Perceived Need
	a	c
Not currently in treatment	Recovered or have less serious current disorder	Unmet need
	b	d
Currently in treatment	Recovered or have less serious current disorder (managing symptoms)	Met need

Note: Need may be unmet for subjective or objective reasons (i.e., due to personal predispositions or structural barriers).

Unnoticed by most researchers, however, almost all adults with a current 12-month disorder met criteria for one or more disorders prior to the current year—98%, in the National Comorbidity Survey-Replication (NCS-R; Kessler et al. 2004), the data to be employed here. This means that the vast majority of individuals filling Cells c and d in Table 1, Panel A have a chronic or relapsing condition rather than a first-time disorder. In short, they are as yet unrecovered from previous illness. It is appropriate to compare unrecovered persons to those who have recovered (i.e., to adults who similarly had one or more previous disorders and thus similarly had a clinical need for mental health services but are now clinically well). For this reason, Table 1’s theoretical analysis is restricted to individuals with one or more previous mental disorders who are presently recovered versus unrecovered.

Recovered adults who are not currently using services would fall into Cell a of Table 1, Panel A. Some Cell a members were never treated and became well “naturally,” and others were past patients/consumers whose previous treatment was probably effective. Most studies do not distinguish between never-treated individuals and individuals with past treatment experience; both groups are simply not using services in the present. For this article’s purposes, this practice is followed here.³ Persons in Cell b have also recovered but have either continued their past mental health care into the present to handle lingering subthreshold symptoms or have recently initiated treatment for the same purpose.

As mentioned earlier, estimates of unmet need (Cell c of Table 1, Panel A) are probably too high because adults with any presently untreated disorder are counted as having an unmet need. Having any disorder includes people with less serious conditions who may recover naturally in the future without professional care (Grella and Stein 2013; Henriksen et al. 2015; Jones et al. 2020; Sareen et al. 2013; Wang et al. 2017), thus inflating the estimate of unmet population need. An obvious solution to this problem would be to count only cases of untreated serious disorder—Cell e in Panel B of Table 1—thus excluding individuals with less serious disorders who are likely to recover naturally.

Although this strategy would desirably lower the unmet need percentage, commonly used indicators of illness severity (see Roberts et al. 2018) could create problems. Disorder severity is typically indicated by the presence or absence of (a) psychosis, which is only one category of disorder, unreliably captured in epidemiological surveys, and rare; (b) current comorbidity, which fails to incorporate individuals’ lifetime histories of multiple and successive disorders; (c) “serious mental illness” indices, which are complex and identify only a small percentage of the population as seriously ill (4%–6%); or (d) scores on “serious psychological distress” scales, which assess anxiety and depressive symptoms but are nonspecific regarding diagnosis, do not tap substance use or psychosis symptoms, and identify only 4% to 6% of adults as severely distressed. Restricting estimates of unmet and met clinical need to more serious cases only (Cells e and f, Panel b, Table 1) thus might overcorrect the extent of population need.

How else to define and calculate unmet need for services? A frequent alternative is to ask epidemiological survey respondents who had not received care whether they had felt a need for treatment for their emotions, nerves, or substance use problems in the past 12 months (Aoun, Pennebaker, and Wood 2004). Those who felt a need but did not use services have what might be called an “unmet perceived need”; they fall into Cell c, Panel C, of Table 1. Studies of need perceptions consistently show that (a) more adults with a disorder do not perceive a need for treatment than perceive that they do and (b) adults who do not perceive a need are less likely to use services (Andrade et al. 2014; Edlund 2009; Green et al. 2020; Henriksen et al. 2015; Kessler et al. 2001; Mojtabai, Olfson, and Mechanic 2002; Mojtabai et al. 2011; Roberts et al. 2018). Thus, rates of unmet perceived need would be substantially lower than clinically defined rates based on persons with any disorder but possibly higher than rates based only on people with serious clinical illness.

However, subjective perceptions could potentially produce an underestimate of population needs. Many epidemiologists believe that individuals with a diagnosable condition are mistaken when they claim not to have felt a recent need for help. Researchers’ disbelief is evident in references to respondents’ inability to “recognize their illness,” “failures” to see that they need treatment, or “failures” to seek treatment (e.g., Edlund 2009; Henricksen et al. 2015; Stringer and Baker 2018; Wong et al. 2018). From these investigators’ point of view, persons who “fail” to acknowledge their need and “fail” to pursue services would undesirably be placed in Cell a, Panel C of Table 1, lowering the number and “true” percentage of adults with unmet (i.e., clinical) need in Cell c, Panel C.⁴

On the other hand, accepting people’s perceptions could inadvertently lead to overestimates of unmet need. This is because many persons with a disorder admit that they needed professional help yet purposefully did not seek it. These people would land in Cell c, Panel C of Table 1, thus raising rather than lowering the unmet need count.

Why do people who perceive a need for help decide not to pursue it? This question has been extensively studied by service utilization researchers (e.g., Green et al. 2020; Roberts et al. 2018), focusing on factors identified by Andersen’s (1968, 2008) three-factor model of medical treatment-seeking: severity of symptoms (“perceived need”), attitudes toward and beliefs about medical care (“predispositions”), and structural “barriers” (e.g., costs of care, distance to services). Investigators view the most commonly cited reason for not seeking care—“I wanted to handle the problem on my own”—as an “attitudinal” or “psychological” barrier to treatment-seeking (e.g., Andrade et al. 2014; Green et al. 2020; Kessler et al. 2001; Mojtabai et al. 2011; Pinedo and Villatoro 2020; Walker et al. 2015). They additionally see respondents’ frequent belief that treatment is ineffective as a knowledge deficiency to be overcome with better information. By contrast, individuals’ objective reasons for not obtaining care (e.g., lack of insurance, time demands, language barriers) are viewed as acceptable reasons to have perceived but unfulfilled help needs. In essence, when respondents with a clinically defined disorder report that they require care, investigators do not dispute it. They instead accept or reject the legitimacy of respondents’ reasons for avoiding treatment; barriers to access are acceptable, but subjective attitudinal reasons are “erroneous.” From these investigators’ viewpoint, when individuals “correctly” recognize they need assistance but refuse to obtain it for the “wrong” reasons, they nevertheless should count as having an unmet need, thus driving up the number of people placed in cell c, Panel C of Table 1—even though individuals who are unwilling to seek care are unlikely to take advantage of available mental health services.

What if Individuals’ Perceptions of Need Are More Accurate Than Not?

Underlying researcher attitudes toward respondents’ “failures” to recognize illness and their “problematic” rationales for shunning care is a conviction that diagnosed disorders are real, objective phenomena. This conviction is grounded in the medical model of disease and disorder that undergirds most epidemiological and treatment-seeking research (Brown 1995; Conrad 1992; Thoits 2022; Watson 2012).

In the medical model, mental illness is conceived as a biomedical condition, so clinically based diagnostic criteria are viewed as appropriate measures, treatment by medical/psychiatric professionals is believed necessary, and hospitalization, psychotherapy, and/or medications will produce remission and improved functioning. From a medical model/treatment-seeking stance, people who have a clinical disorder but have not sought care for subjective or objective reasons clearly have “unmet needs” for services and therefore will be less likely to recover.

Despite widespread belief in the medical model, the importance and value of seeking professional care is not embraced universally. As noted earlier, many individuals with a disorder prefer to manage their troublesome symptoms themselves or believe that psychiatric/psychological interventions are not helpful. Still others worry they might be stigmatized by seeking mental health services (Alang 2015; Chekroud et al. 2018; Stringer and Baker 2018; Wong et al. 2018). In essence, they view professional help as unnecessary or unwanted.

When might laypersons view professional help as unwarranted? Recall that adults who recovered naturally without treatment had conditions that were not serious by clinical criteria—they did not have psychoses, comorbidities, or high scores on indices of serious mental illness or distress (Grella and Stein 2013; Jones et al. 2020; Préville et al. 2010; Sareen et al. 2013; Thoits 2022; Wang et al. 2017). This observation suggests that when a person’s disorder is less serious, viewing treatment as unnecessary might be an accurate self-assessment rather than an error in judgment (Jang et al. 2015; McAlpine, McCreedy, and Alang 2018).

How do people assess the seriousness of their symptoms and thus their need for help? It is reasonable to assume that individuals’ evaluations of their current mental health status are grounded in their ongoing daily experiences. They are aware of the adequacy of their everyday functioning in social roles, the frequency and intensity of their symptoms, and the coping resources they have available for managing problems (e.g., a sense of self-efficacy, social support) as well as knowledge of past successes in handling emotional difficulties on their own. Assuming accuracy in individuals’ assessments of their current mental health and their coping capabilities, the less serious their clinical condition, the less likely they will view themselves as needing professional help; conversely, the more serious their disorder, the more likely they will see help as necessary (Hypothesis 1). Note that the presence or seriousness of current clinical disorder provides the standard for assessing perceptual accuracy.

Perceiving a need for professional help should also predict service use. Recall that adults with more serious clinical disorders have a higher probability of treatment involvement (Chen et al. 2013; Roberts et al. 2018; ten Have et al. 2013; Wang et al. 2017; The WHO World Mental Health Survey Consortium 2004). If perceived needs for care reflect clinical needs accurately, these perceptions should be just as strongly—if not more strongly—related to treatment involvement than clinical need indicators are (Hypothesis 2).

In sum, if Hypotheses 1 and 2 were confirmed, individuals’ need perceptions might provide alternative estimates of unmet and met population needs for mental health services, neither overestimated by counting any disorder as clinical need nor underestimated by counting only persons with very serious disorder.

Perceived Need as a Mediator

If need perceptions are fairly accurate reflections of clinically defined needs, then an unfolding sequence of effects is implied. The seriousness of individuals’ current disorders (ranging from recovered/clinically well to less serious and more serious disorder) should directly influence their perceived need for care, which in turn should link positively to recent treatment involvement. Put another way, viewing professional assistance as necessary should explain (mediate) the relationship between current disorder seriousness and current service use (Hypothesis 3a). Should clinical and perceived needs instead have independent relationships with treatment participation, their relative associations with utilization still can be usefully contrasted. In this case, because perceptions of need arise from people’s evaluations of their day-to-day symptoms and functioning, they should more strongly relate to current service use than needs that are clinically defined (Hypothesis 3b). This is because clinical indicators are summaries constructed from individuals’ self-reports of symptom frequencies, symptom durations, and difficulties performing their social roles, so they are a step removed from persons’ detailed experiential self-knowledge (including their past successes in coping with troublesome symptoms).

If people’s perceptions were accurate mirrors of their clinical states, future epidemiological surveys could require answers to only two questions: Did you perceive a need for help in the past year, and did you obtain treatment in the past year? The percentage of respondents with a perceived need but no recent service use would capture unmet population need more simply than estimates based on clinical indicators. Furthermore, researchers and practitioners who are wed to the medical model might gain greater respect for and interest in laypersons’ self-assessments, agency, and treatment decisions. Examining the accuracy of individuals’ perceptions is a first step toward such possibilities.

Data and Methods

Survey Design and Sampling

This study employed data from the National Comorbidity Survey-Replication (NCS-R), fielded between 2001 and 2003.⁵ The NCS-R’s purpose was to assess the prevalence of the most common mood, anxiety, and substance use disorders in the adult population and their comorbidity. A sample of community-residing, English-speaking adults was drawn from households in the continental United States with multistage clustered area probability sampling and a response rate of 71% (Kessler et al. 2004). Interviews were conducted in person. A total of 9,282 respondents participated in Part 1 of the survey, which assessed whether and when they had one or more mental disorders during their lifetimes, including the past 12 months. Part 2 was administered to all respondents who had at least one lifetime disorder and to a random subset of respondents with no lifetime disorder (total N = 5,692). This study employs the Part 2 data set because information on individuals’ past and current use of mental health services was collected in Part 2 and then merged with their Part 1 data.

Measures

This study focuses on respondents who met DSM-IV criteria for one or more mental disorders that began prior to the current 12 months. They are subdivided by their clinical status as of the current 12 months: recovered (i.e., clinically well) and unrecovered. Disorder and recovery measures are described first.

Clinical disorders

Mental disorders were assessed with the World Mental Health-Composite International Diagnostic Interview, which operationalized diagnostic criteria for a wide range of DSM-IV disorders (Kessler et al. 2004). Dichotomous variables created by NCS-R algorithms indicated whether respondents met criteria for each canvassed disorder during their lifetimes, including the past year. Severe disorders and the most common adult disorders were counted in this study: bipolar I and II, major depressive disorder, dysthymia, panic disorder, agoraphobia, social phobia, simple phobia, generalized anxiety disorder, posttraumatic stress disorder, eating disorder, alcohol abuse and dependence, and drug abuse and dependence (15 disorders).

Recovery from past disorder

Two variables were constructed from the onset dates of each of the 15 disorders and from their presence or absence in the past year: Did the respondent have an onset of each disorder prior to the past 12 months (1 = yes, 0 = no), and was each disorder present during the past 12 months (1 = yes, 0 = no)? Respondents with one or more disorders prior to the current year but none during the current year were coded as having recovered (1 = yes, 0 = no). Respondents with any disorders present both prior to and during the past year were unrecovered (i.e., recovered was coded 0). Unrecovered respondents are described here as having a “current (or recent) disorder.”

After three respondents were dropped due to missing values on this study’s variables, the analytical sample consisted of Part 2 respondents who had one or more past disorders (N = 2,347) from which they had recovered (N = 1,054) or were unrecovered (N = 1,293).

Seriousness of current disorder

As noted earlier, there are a number of ways to measure the severity or seriousness of mental disorder. Because comorbidity and serious mental illness scores are strongly related (Kessler, Demler, et al. 2005), current disorder seriousness was measured as the sum of conditions for which respondents met diagnostic criteria during the past 12 months. Seriousness was collapsed into three dichotomous variables: recovered (no current disorders), less serious (one or two disorders), and more serious (three or more disorders). Sensitivity analyses with four dummy variables (none, one, two, and three or more disorders) and with the total sum of disorders as alternative indicators produced the same study findings, so the three dichotomous variables were retained for their simplicity.

Seriousness of past illness

The seriousness of respondents’ past illness was controlled in multivariate analyses to check for spurious relationships. Seriousness of past illness was the sum of disorders with onsets more than 12 months ago (observed range = 1–12), capturing respondents’ histories of successively-occurring and comorbid disorders. The more past disorders, the more serious the respondent’s past illness history. Past illness seriousness was collapsed into two categories: 0 = less serious (one or two prior disorders) and 1 = more serious (three or more prior disorders). Sensitivity analyses with the sum of prior disorders produced the same study results.

Current treatment

The interviews assessed whether three types of professional treatment had been received “for problems with your emotions or nerves or your use of alcohol or drugs” during the past 12 months: hospitalization, counseling/psychotherapy, and taking a prescribed psychoactive medication. Questions were asked about emergency room visits, overnight stays in a hospital, seeing any of a list of professionals, and taking any of a list of psychotherapeutic medications under a doctor’s supervision. Respondents were classified as being in current/recent treatment (1 = yes, 0 = no) if they were hospitalized, saw a professional, or took prescribed medications in the past year for their mental health.

Perceived need for treatment

Respondents who were not in treatment during the past year were asked, “Was there ever a time during the past 12 months when you felt that you might need to see a professional because of problems with your emotions or nerves or your use of alcohol or drugs?” Perceived need for treatment was coded no = 0, yes = 1 (84% said no, 16% yes). By study design, respondents in treatment in the past year were not asked this question. Instead, they were queried whether their involvement was by choice: “When you went to see a professional about your emotions or substance use in the past year, was this something you wanted to do, or did you go only because someone else was putting pressure on you?” Those who said they had wanted to go (71%) were coded 1 = yes on perceived need for treatment; those who reported pressure (29%) were coded 0 = no, they did not perceive a care need, but others had insisted. Although this question could be seen as indicating voluntary versus involuntary pathways into treatment, unwilling entry implies that one disagreed with other people’s views of one’s mental health. Importantly, this question prevented the operational confounding of perceived need for care with treatment involvement itself.

Background variables

Sociodemographic variables were controlled in multivariate equations. Female was coded (0, 1). Age was in years. Race-ethnicity was a set of mutually exclusive dummy variables for white (0, 1), black (0, 1), Hispanic (0, 1), and other race-ethnicity (0, 1); whites served as the omitted comparison group. Education was in years, top-coded at 17 years or more of schooling.

Table 2 presents respondents’ characteristics. Not surprisingly, far more respondents had less serious than more serious past illness. Consistent with previous research, nearly half (44.9%) of respondents had recovered by the current year. Two-thirds of respondents were not presently receiving treatment, and two-thirds perceived no recent need for professional help.

Table 2.

Characteristics of Study Respondents (N = 2,347).

	Percent	Mean (SD)
Past illness seriousness
Number of prior disorders	—	2.4 (1.7)
Less serious past illness	66.0	—
More serious past illness	34.0	—
Current disorder seriousness
Number of past-year disorders	—	1.1 (1.4)
Recovered	44.9	—
Less serious past-year disorder	42.6	—
More serious past-year disorder	12.5	—
Current treatment involvement
No past-year treatment use	66.5	—
Past-year treatment use	33.5	—
Current perceived need for treatment
No perceived need for care	65.7	—
Perceived need for care	34.3	—
Background variables
Male	45.0	—
Female	55.0	—
Age	—	42.4 (15.3)
White	75.3	—
Black	9.9	—
Hispanic	10.2	—
Other race-ethnicity	4.6	—
Years of education	—	13.2 (2.4)

Note: All study respondents had one or more mental disorders prior to the current 12 months. Data are weighted. Data are from the National Comorbidity Survey-Replication.

Analytical Strategies

The NCS-R had a complex sampling design, so survey design methods were necessary to adjust variances, standard errors, and confidence intervals to represent the U.S. national population in Census 2000. Complex survey commands in Stata/SE 10.0 for logistic regression were employed in the analyses, including the Taylor series linearization method for variance estimation. Table Ns and percentages were weighted.

Results

Hypothesis 1

Do respondents’ perceptions of their need for care accurately reflect their clinically defined need? Hypothesis 1 proposed that respondents with more serious current disorder were more likely to perceive a need for treatment. Conversely, the less serious their disorder, the less likely they would see a need for help. From a medical model viewpoint, the stronger the association between objective clinical seriousness and subjective need, the more accurate are respondents’ assessments of their mental health. Table 3 reports cross-tabulations of current perceived need by the seriousness of current disorders, where seriousness ranges from recovered (no longer meeting diagnostic criteria [i.e., clinically well]) to less serious and more serious clinical disorder.

Table 3.

Does Perceived Need Accurately Reflect Current Clinical Need?.

		Seriousness of Current Disorder
		Recovered	Low Seriousness	High Seriousness
Current perceived need	No	81.6 (860)	59.6 (595)	29.3 (86)
	Yes	18.4 (194)	40.4 (404)	70.7 (208)
	Total	100.0 (1,054)	100.0 (999)	100.0 (294)
		χ² = 308.0, df = 2, Cramer’s V = .36***

Note: Data are weighted; percentages are reported. N = 2,347. Data are from the National Comorbidity Survey-Replication.

***

p < .001.

Supporting Hypothesis 1, there is a significant positive relationship between current disorder seriousness and perceiving a need for professional help. Note that clinical and lay agreement is high at the “extremes” of clinical seriousness: 81.6% of recovered respondents perceived no current need for care, and 70.7% of those with more serious disorder reported they had a need for help. The overall relationship between clinical need and perceived need is modest in strength because respondents with less serious disorder differed on whether they required mental health care; 59.6% saw help as unneeded, and 40.4% viewed help as necessary. Still, when agreements between the two variables were counted (i.e., when disorder and perceived need were both present and when disorder and perceived need were both absent), 63% of respondents’ self-assessments concurred with their clinical statuses, again indicating that respondents’ perceptions were more frequently accurate than not.

The Table 3 relationship was reexamined in logistic regressions that controlled respondents’ background characteristics (available on request). Respondents with less serious current disorder were almost 3 times more likely than recovered individuals to perceive a treatment need (odds ratio [OR] = 2.8, p < .001, 95% confidence interval [CI] = 2.3, 3.5), whereas those with more serious disorder were 10 times more likely than the recovered to see a care need (OR = 10.3, p < .001, 95% CI = 8.2, 13.0), again supporting the hypothesis that respondents’ perceptions reflect their clinically defined need.

Hypothesis 2

Hypothesis 2 extends the analysis to individuals’ help-seeking behavior. If respondents’ perceived needs for care accurately reflected their clinically defined needs, need perceptions should be as strongly (if not more strongly) related to current treatment involvement as clinical needs are. Table 4 presents cross-classifications of treatment involvement by any current clinical disorder (Panel A), the seriousness of respondents’ current clinical disorders (Panel B), and their need perceptions (Panel C).

Table 4.

Associations of Current Treatment Use with Any Current Disorder, More Serious Current Disorder, and Current Perceived Need for Treatment.

		Any Current Disorder
Panel A		No	Yes
Currently in treatment	No	77.2 (814)	57.7 (746)
	Yes	22.8 (240)	42.3 (547)
	Total	100.0 (1,054)	100.0 (1,293)
		χ² = 99.4, df = 1, phi = .21***
		Seriousness of Current Disorder
Panel B		Recovered	Low Seriousness	High Seriousness
Currently in treatment	No	77.2 (814)	62.6 (625)	41.2 (121)
	Yes	22.8 (240)	37.4 (374)	58.8 (173)
	Total	100.0 (1,054)	100.0 (999)	100.0 (294)
		χ² = 146.1, df = 2, Cramer’s V = .25***
		Perceived Need for Care
Panel C		No	Yes
Currently in treatment	No	85.3 (1,316)	30.4 (245)
	Yes	14.7 (226)	69.6 (562)
	Total	100.0 (1,542)	100.0 (807)
		χ² = 718.4, df = 1, phi = .55***

Note: Data are weighted; percentages are reported. N = 2,347. Data are from the National Comorbidity Survey-Replication.

***

p < .001.

Two patterns stand out in Table 4. First, any clinically defined need, seriousness of clinical need, and perceived need each were positively and significantly related to treatment participation, with perceived need more strongly associated with utilization (phi = .55) than the clinical need indicators (.21 and .25, respectively). This confirms Hypothesis 2: Perceived need is a stronger predictor of service use than indicators of clinical necessity, suggesting again that perceptions may be a more accurate gauge of clinical need than not. It is relevant to note in Table 4, Panel B that 62.6% of respondents with less serious disorder had not entered treatment. Recall from prior research that individuals with less serious past illness were more likely to recover and to do so without treatment (Thoits 2022). So, respondents with less serious current illness perhaps anticipated being able to resolve their symptoms on their own and therefore did not seek services.

As a second pattern, Table 4 shows that estimates of unmet population need were highest (57.7%, Panel A) when having any disorder in the past 12 months indicated clinically defined need, consistent with prior studies (Kessler et al. 2001; Kessler, Demler, et al. 2005; Wang et al. 2005, 2017). A lower estimate (41.2%, Panel B) was obtained when more serious disorder indicated unmet need instead. Perceived need for treatment produced the lowest estimate of unmet need (30.4%, Panel C).

Hypotheses 3a and 3b

Hypothesis 3a was that perceived need should mediate the relationship between current disorder seriousness and current service use. Hypothesis 3b added that if clinically defined need and perceived need independently related to treatment involvement instead, the relationship of perceived need with treatment should be stronger than that of clinical need, given individuals’ in-depth personal knowledge of their coping capabilities.

Respondents’ current treatment involvement was first regressed logistically on the seriousness of their current disorder, with background variables controlled and recovered (clinically well) respondents serving as the omitted comparison group. In the next step, perceived need was added to the equation as the potential mediator. Last, the seriousness of respondents’ past illness was included to check for possible spurious relationships. Results are in Table 5.

Table 5.

Are Relationships of Less and More Serious Current Disorder with Service Use Mediated by Perceived Need?.

	Current Treatment Use
	1		2		3
	OR	95% CI	OR	95% CI	OR	95% CI
Currently recovered	Reference	—	Reference	—	Reference	—
Less serious current disorder	2.1***	[1.7, 2.6]	1.3**	[1.1, 1.7]	1.3*	[1.0, 1.6]
More serious current disorder	5.2***	[4.0, 6.9]	1.8***	[1.4, 2.5]	1.4	[1.0, 2.2]
Perceived need	—	—	13.4***	[10.9, 16.4]	13.2***	[10.7, 16.2]
More serious past illness	—	—	—	—	1.4**	[1.1, 1.8]
Background variables
Female	1.6***	[1.4, 2.0]	1.4**	[1.1, 1.7]	1.4**	[1.1, 1.7]
Age	1.1	[1.0, 1.1]	1.2***	[1.1, 1.3]	1.2***	[1.1, 1.3]
Black	.6***	[.4, .8]	.4***	[.3, .6]	.4***	[.3, .6]
Hispanic	.6**	[.4, .8]	.5**	[.3, .8]	.5**	[.3, .8]
Other race-ethnicity	.5***	[.4, .7]	.5**	[.3, .8]	.5**	[.3, .8]
Years of education	1.0	[1.0, 1.1]	1.0	[1.0, 1.0]	1.0	[1.0, 1.0]
F	32.0***		106.1***		97.1***

Note: Age is divided by 10. N = 2,347. Data are from the National Comorbidity Survey-Replication. OR = odds ratio; CI = confidence interval.

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

If perceived need fully mediated (explained) the relationship between clinical need and treatment involvement, the odds ratios for disorders of low and high seriousness should become 1.0 and nonsignificant when perceived need is controlled. In Model 1, respondents with less and more serious current disorders were significantly more likely to be in treatment than recovered respondents, raising the odds of treatment involvement 2.1 times and 5.2 times, respectively, compared to the recovered. In Model 2, when perceived need for care was added, the odds ratios for current levels of disorder each were lower but remained significant, indicating that perceiving a need for help only partially explained the positive associations of less and more serious current illness with treatment use. Importantly, the odds of being in treatment were 13.4 times higher for respondents who perceived that they needed care. When the seriousness of past illness was controlled in Model 3 as a check for spuriousness, the link of less serious disorder with treatment use remained positive and significant, but the odds ratio for more serious disorder with treatment approached 1.0 and was nonsignificant. Thus, past serious illness fully explained why respondents with more severe current disorder had a higher probability of using services. Notice in Model 3 that controlling for prior serious illness did not alter the sizable association of perceived need with the odds of service use (OR = 13.2).

In general, Hypotheses 3a and 3b each received partial confirmation. Supporting Hypothesis 3a, perceived need partially (rather than fully) mediated the relationships between levels of disorder seriousness and the odds of being in treatment. Supporting Hypothesis 3b, the association between perceived need and the probability of using services was far greater than between levels of serious disorder and service use.

Is There an Interaction between Clinical and Perceived Needs?

Thus far, the focus has been on whether personal judgments of need reflect need as defined by clinical criteria. However, mental health treatment use may be more likely when clinical and perceived needs coincide, for example, when serious clinical need and subjective recognition of need are both present. In other words, treatment involvement may depend on the combination of these need variables.

To explore, six interaction terms were constructed for current disorder seriousness (recovered, less serious disorder, more serious disorder) with perceived need (yes, no), each coded 1 = this combination is present and 0 = this combination is absent. Treatment involvement was regressed logistically on these interaction terms, with background variables controlled. Respondents who were recovered and felt no recent need for care served as the omitted comparison group. In a second step, past serious illness was added to the equation to check for spurious relationships. Table 6 reports results.

Table 6.

Treatment Use Predicted by Combinations of Current Perceived and Clinical Need.

	Current Treatment Use
	1		2
	OR	95% CI	OR	95% CI
No perceived need × Currently recovered	Reference	—	Reference	—
No perceived need × Less serious current disorder	1.8***	[1.4, 2.3]	1.7***	[1.3, 2.2]
No perceived need × More serious current disorder	5.5***	[3.7, 8.1]	4.2***	[2.8, 6.5]
Yes perceived need × Currently recovered	27.2***	[20.0, 36.9]	26.8***	[19.7, 36.6]
Yes perceived need × Less serious current disorder	21.2***	[16.1, 27.9]	20.0***	[15.0, 26.6]
Yes perceived need × More serious current disorder	21.7***	[14.8, 31.6]	16.7***	[10.4, 26.9]
More serious past illness	—	—	1.4*	[1.1, 1.8]
F	104.2***		90.7***

Note: Background variables are controlled in each equation. N = 2,347. Data are from the National Comorbidity Survey-Replication. OR = odds ratio; CI = confidence interval.

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

The Model 1 coefficients revealed an unexpected pattern. Among respondents perceiving no recent need for care, treatment involvement was positively related to the seriousness of disorder, as one might expect. Specifically, compared to recovered individuals with no care need, those with less serious disorder were 1.8 times more likely to be in treatment, whereas persons with more serious disorder were 5.5 times more likely. By contrast, disorder seriousness was almost irrelevant among individuals who saw that they needed help; these respondents had 21.2 to 27.2 times higher odds of current treatment involvement than recovered respondents who saw no need for care. When serious past illness was controlled in Model 2, these relationships were not substantially changed, indicating no spuriousness. In short, the perception that one requires help dramatically raises the odds of treatment involvement, regardless of the seriousness of one’s disorder.

It is instructive to compare estimates of unmet population need that are obtained when clinical and perceived needs co-occur in the ways just explored. Recall that epidemiological estimates of met and unmet need are typically based solely on individuals who meet criteria for a past-year disorder. For this reason, recovered respondents are excluded from the next analysis. Table 7 examines relationships between current disorder seriousness and treatment involvement for (a) all respondents with a past-year disorder, disregarding their need perceptions (Panel A); (b) the subset of respondents who perceived no current need for help (Panel B); and (c) the subset who did perceive a need for help (Panel C).

Table 7.

Associations of Current Disorder Seriousness with Treatment Use, by Perceived Need.

Panel A: All Respondents (Need Perceptions Unconsidered)
		Seriousness of Current Disorder
		Low Seriousness	High Seriousness	Total
Currently in treatment	No	62.6 (625)	41.2 (121)	57.7 (746) unmet need
	Yes	37.4 (374)	58.8 (173)	42.3 (547)
	Total	100.0 (999)	100.0 (294)	100.0 (1,293)
		χ² = 42.6, df = 1, phi = .18***
Panel B: Respondents with No Recent Perceived Need
		Seriousness of Current Disorder
		Low Seriousness	High Seriousness	Total
Currently in treatment	No	83.4 (496)	64.0 (55)	80.9 (551) “unmet need”
	Yes	16.6 (99)	36.0 (31)	19.1 (130)
	Total	100.0 (595)	100.0 (86)	100.0 (681)
		χ² = 18.3, df = 1, phi = .16***
Panel C: Respondents with Recent Perceived Need
		Seriousness of Current Disorder
		Low Seriousness	High Seriousness	Total
Currently in treatment	No	31.9 (129)	31.7 (66)	31.9 (195) unmet need
	Yes	68.1 (275)	68.3 (142)	68.1 (417)
	Total	100.0 (404)	100.0 (208)	100.0 (612)
		χ² = 0.0, df = 1, phi = .00

Note: Data are weighted. Percentages are reported. N = 2,347. Data are from the National Comorbidity Survey-Replication. All respondents have a current disorder; estimates of unmet need for care are bolded in each Panel.

***

p < .001.

The marginal percentages bolded in Table 7 capture the percentage of individuals with a current disorder—disregarding seriousness—who are not using mental health services. Panel A shows that a high proportion of unmet need (57.7%) is observed when respondents’ need perceptions are not considered. In Panel B, among respondents who perceive no need for care, 80.9% are not in treatment; from a medical model standpoint, these individuals are considered to have an “unmet (clinical) need.” However, note that the vast majority of untreated Panel B respondents (496 out of 551 in that row, or 90%) have a less serious disorder; these are people who are most likely to recover naturally without professional aid. In Panel C, among respondents who do see themselves as needing care, two-thirds are currently using services; only 31.9% have an unmet need. In short, the traditional unmet need estimate in Panel A is high because it incorporates a considerable number of respondents from Panel B who do not believe they need help, have not sought it, and are most likely to recover naturally.

In general, heeding respondents’ perceptions helps to narrow down unmet need estimates to persons who are most likely to want and take advantage of services if they can: individuals who have a current disorder and also perceive a need for help—those in Table 7, Panel C (68.1%).

Note that disorder seriousness links positively but weakly to treatment involvement (phi = .16, p < .001) only when individuals do not perceive a need for care (Table 7, Panel B), hinting that their treatment participation might be involuntary. By contrast, when individuals judge that they require help (Table 7, Panel C), the severity of their clinical symptoms is irrelevant (phi = .00)—they are more likely to be in treatment regardless (as observed previously, Table 6).⁶

Discussion and Conclusion

Given that roughly half of adults who recover from a clinical disorder do so naturally without treatment, traditional epidemiological estimates of unmet need for mental health services are probably too high. Natural recoveries suggest that people who experience disorder symptoms evaluate the intensity of their distress and the adequacy of their functioning and acknowledge a need for professional help only when resolving these problems unaided seems too difficult. If this self-evaluative process occurs, individuals’ perceptions of need should reflect the severity of their disorder and predict their service use just as well as, or perhaps more strongly than, their need as defined solely by clinical criteria.

Analyses confirmed these expectations. There was a moderately strong positive association between clinical need and perceptual need, and treatment involvement was more closely tied to perceiving a need for care than to disorder seriousness. In short, adults’ subjective assessments of their mental health appear superior to objective diagnostic indicators in forecasting their service use. This observation echoes the finding that individuals’ self-ratings of their physical health (excellent, very good, good, fair, poor) are superior to objective medical measures in predicting their mortality risk (Idler et al. 2004; see also Jang et al. 2015; McAlpine et al. 2018). People may be good judges of both their physical and mental health needs.

It seemed plausible that service use would be especially likely when subjectively assessed and clinically assessed needs corresponded to one another. Exploratory analyses were revealing: Disorder seriousness was positively but only weakly related to treatment use when individuals did not see a need for care. When they did perceive a care need, disorder severity was irrelevant—the majority obtained treatment regardless (see also Mojtabai et al. 2002). Further investigation showed that when adults’ self-assessments were not taken into consideration, the traditional epidemiological estimate of unmet need was high; 58% had a clinical disorder that was untreated. This elevated percentage was due to the medical model-based assumption that all adults with an untreated disorder have “unmet need,” whether the condition was clinically serious or not. But that 58% includes the vast majority of individuals who have a less serious disorder, perceive no treatment need, and do not pursue services (i.e., those most likely to recover naturally). Individuals who have a current disorder (serious or not) and perceive a need for help are most likely to take advantage of professional assistance, leaving only a third (32%) of the currently ill with care needs unmet, a much less alarming service gap. In short, perception of need is what matters for treatment use; clinical seriousness is less pertinent. Given these observations, it seems sensible to give primacy to people’s self-evaluations when estimating unfulfilled population needs for mental health services.

The treatment gap might be even smaller if individuals’ reasons for not seeking care were taken into consideration. For researchers with a medical model orientation, all persons with a diagnosable disorder will benefit from treatment receipt (Kessler et al. 2003), so it is unnecessary to distinguish between needs that are unmet for objective reasons (e.g., lack of health insurance) versus subjective reasons (e.g., a preference for self-reliance). Pragmatically, however, people who prefer to handle problems on their own, believe treatment is ineffective, or fear stigma are unlikely to want or seek help; only individuals citing structural impediments would have desires for assistance that are truly unmet, a less expansive conception of unmet need. Unfortunately, disentangling objective from subjective reasons for not seeking care is difficult. In exploratory analyses (not shown), 6% of NCS-R respondents cited structural reasons only, 33% endorsed subjective reasons only, whereas 61% supplied both objective and subjective reasons for not seeking needed help. Whether people lack care primarily because of structural or predispositional barriers requires further research. This would aid in setting policy and funding priorities, for example, whether to direct more resources to removing obstacles to treatment access versus lessening people’s reluctance to use services.

Several study limitations exist. First, these epidemiological data were collected in 2001 to 2003. In the two decades since its fielding, public knowledge about mental health problems, positive attitudes toward treatment, and use of psychotropic medications have grown, among other changes. Nevertheless, more recent epidemiological surveys (which focus on substance use disorders plus a handful of other mental health conditions) find similar rates of lifetime and 12-month disorders and of untreated and treated recoveries (Hedden et al. 2012), suggesting the findings here are relevant.

Second, the data are retrospective rather than longitudinal. To counter recall problems and social desirability biases when participants report on their mental health and treatment involvements, the survey incorporated evidence-based interviewing strategies that enhance memory and reduce embarrassment (Kessler, Chiu, et al. 2005). To the extent that such biases influenced this study’s results, they made hypothesis tests and estimates of unmet need more conservative.

Third, no longer meeting clinical criteria for disorder is a crude recovery measure, encompassing symptoms ranging from none at all to high subthreshold levels. Because each disorder has distinctive defining symptoms, assessing degrees of recovery is difficult. Despite its lack of precision, the absence of clinical disorder is frequently used in epidemiological studies to indicate recovery, compelling its use here for comparison purposes. Furthermore, it provides an important clinical standard for assessing the accuracy of individuals’ perceptions.

Last, the causal ordering of perceived need and treatment involvement is ambiguous because both are measured in terms of the past 12 months. Although it is widely assumed that perceived need precedes and motivates treatment-seeking, reverse causality is also plausible: Current treatment involvement may reinforce a perception that one is in need of care. Relatedly, past treatment experience raises the probability of using mental health services again (Aneshensel et al. 2019), suggesting that former patients/consumers may become more adept at recognizing a recent care need than treatment-inexperienced individuals. An unfolding reciprocal relationship may exist between perceiving a care need and treatment involvement, calling for further investigation.

In general, findings here indicate that perceived need could be a useful proxy for clinical need, especially when it is not feasible to fund and field lengthy, complex interviews assessing adults’ experiences of lifetime and past-year disorders. To estimate unmet needs, one would simply ask whether respondents felt a need for help in the past year and whether they received treatment. To check whether individuals in fact had clinically significant conditions, three additional questions could be added: Were they ever told by a medical or mental health professional that they had a problem with their emotions, nerves, or use of alcohol or drugs? What diagnosis did the professional mention? When was this? Respondents with a probable clinical disorder, a perceived need for help in the past year, and no recent treatment involvement would supply an unmet need estimate that takes both clinically defined and perceptual needs into account.

Although perceived need may be a useful proxy for clinical need in epidemiological work, its strong positive link to treatment involvement has broader implications. Most people who see they need help obtain it; people perceiving no need for help (because they have recovered or have less serious disorder) rarely pursue it. These findings suggest that most adults with a diagnosable disorder are capable managers of their well-being, which in turn highlights their self-awareness and agency. However, recognition of these capabilities by professionals (including researchers) is uncommon, given the dominance of medical model presumptions: Professionals are experts in identifying and treating mental disorder; therefore, their judgments should trump individuals’ self-assessments and treatment decisions when they differ from professionals’ own (e.g., Beresford, Nettle, and Perring 2010; Faulkner 2017).

Although not always in agreement with providers’ or researchers’ assessments, people’s generally accurate evaluations of their mental health and their needs deserve acknowledgment and greater research attention. As a counterpoint to medical-model-based investigations, how individuals evaluate their mental health, their ability to recover on their own, and their treatment needs should be qualitatively and quantitatively explored. Of special interest are peoples’ past experiences of coping successfully or unsuccessfully with periods in their lives marked by discomfiting symptoms. Distressed individuals with successful past experiences of recovering naturally may view professional help as unnecessary or delay treatment-seeking longer than persons confronting symptom onsets for the first time. By contrast, distressed persons with past treatment experience may understand they need care and seek it more quickly (depending on its perceived prior helpfulness) than persons without such experience. Patient/consumer-centered studies examining laypersons’ perceptions and decision-making may more fully explain how and why adults’ mental health care needs are fulfilled or remain unmet.

Footnotes

ORCID iD

Peggy A. Thoits

Notes

Author Biography

Peggy A. Thoits is professor emeritus of sociology at Indiana University - Bloomington. Her interests are in physical and mental illness; stress, coping, and social support processes; self and identity; and emotion. Her current research examines the role of social support from experientially similar others in reducing distress and ill health; the conditions under which individuals label themselves, become labeled by others, or resist being labeled as mentally ill; and the determinants and consequences of recovery from mental disorder.

References

Alang

Sirry M.

2015. “Sociodemographic Disparities Associated with Perceived Causes of Unmet Need for Mental Health Care.” Psychiatric Rehabilitation Journal 38(4):293–99.

American Psychiatric Association. 1994. Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: American Psychiatric Association.

Andersen

Ronald

. 1968. A Behavioral Model of Families’ Use of Health Services. Chicago, IL: University of Chicago Press.

Andersen

Ronald

. 2008. “National Health Surveys and the Behavioral Model of Health Services Use.” Medical Care 46(7):647–53.

Andrade

L. H.

Alonso

Mneimneh

Wells

Al-Hamzawi

Borges

Bromet

, et al 2014. “Barriers to Mental Health Treatment: Results from the WHO World Mental Health Surveys.” Psychological Medicine 44(6):1303–17.

Aneshensel

Carol S.

van Draanen

Jenna

Riess

Helene

Villatoro

Alice P.

2019. “Newcomers and Old Timers: An Erroneous Assumption in Mental Health Services Research.” Journal of Health and Social Behavior 60(4):453–73.

Aoun

Samar

Pennebaker

Duane

Wood

Christie

. 2004. “Assessing Population Need for Mental Health Care: A Review of Approaches and Predictors.” Mental Health Services Research 6(1):33–46.

Beresford

Peter

Nettle

Mary

Perring

Rebecca

. 2010. Towards a Social Model of Madness and Distress? Exploring What Service Users Say. York, UK: Joseph Rowntree Foundation.

Brown

Phil

. 1995. “Naming and Framing: The Social Construction of Diagnosis and Illness.” Journal of Health and Social Behavior 35(Extra Issue):34–52.

10.

Chekroud

Adam M.

Foster

David

Zheutlin

Amanda B.

Gerhard

Danielle M.

Roy

Brita

Koutsouleris

Nikolaos

Chandra

Abhishek

, et al 2018. “Predicting Barriers to Treatment for Depression in a U.S. National Sample: A Cross-Sectional, Proof-of-Concept Study.” Psychiatric Services 69(8):927–34.

11.

Chen

Lian-Yu

Crum

Rosa M.

Martins

Silvia S.

Kaufmann

Christopher N.

Strain

Eric C.

Mojtabai

Ramin

. 2013. “Service Use and Barriers to Mental Health Care in Major Depression and Comorbid Substance Use Disorders.” Psychiatric Services 64(9):863–70.

12.

Conrad

Peter

. 1992. “Medicalization and Social Control.” Annual Review of Sociology 18:209–32.

13.

Edlund

Mark J.

2009. “Perceived Need for Treatment for Alcohol Use Disorders: Results from Two National Surveys.” Psychiatric Services 60(12):1618–28.

14.

Faulkner

Alison

. 2017. “Survivor Research and Mad Studies: The Role and Value of Experiential Knowledge in Mental Health Research.” Disability & Society 32(4):500–20.

15.

Granfield

Robert

Cloud

William

. 2001. “Social Context and ‘Natural Recovery’: The Role of Social Capital in the Resolution of Drug-Associated Problems.” Substance Use & Misuse 36(11):1543–70.

16.

Green

Jennifer Greif

McLaughlin

Katie A.

Fillbrunn

Mirko

Fukuda

Marie

Jackson

James S.

Kessler

Ronald C.

Sadikova

Ekaterina

, et al 2020. “Barriers to Mental Health Service Use and Predictors of Treatment Drop Out: Racial-Ethnic Variation in a Population-Based Study.” Administration and Policy in Mental Health and Mental Health Services Research 47:606–16.

17.

Grella

Christine E.

Stein

Judith A.

2013. “Remission from Substance Dependence: Differences between Individuals in a General Population Longitudinal Survey Who Do and Do Not Seek Help.” Drug and Alcohol Dependence 133(1):146–53.

18.

Hedden

Sarra

Gfroerer

Joe

Barker

Peggy

Smith

Shelagh

Pemberton

Michael R.

Saavedra

Lissette M.

Forman-Hoffman

Valerie L.

Ringeisen

Heather

Novak

Scott P.

2012. Comparison of NSDUH Mental Health Data and Methods with Other Data Sources. CBHSQ Data Review (March). Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration. https://www.samhsa.gov/data/sites/default/files/CBHSQ_Data_Review_C2_MentalHealth_2012/CBHSQ_Data_Review_C2_MentalHealth_2012.htm.

19.

Henriksen

Christine Anne

Stein

Murray B.

Afifi

Tracie O.

Enns

Murray W.

Lix

Lisa M.

Sareen

Jitender

. 2015. “Identifying Factors That Predict Longitudinal Outcomes of Untreated Common Mental Disorders.” Psychiatric Services 66(2):163–70.

20.

Idler

Ellen

Leventhal

Howard

McLaughlin

Julie

Leventhal

Elaine

. 2004. “In Sickness but Not in Health: Self-Ratings, Identity, and Mortality.” Journal of Health and Social Behavior 45(3):336–56.

21.

Jang

Yuri

Yoon

Hyunwoo

Chiriboga

David A.

Mollinari

Victor

Powers

Daniel A.

2015. “Bridging the Gap between Common Mental Disorders and Service Use: The Role of Self-Rated Mental Health among African Americans.” American Journal of Geriatric Psychiatry 3(7):658–65.

22.

Johnson

Amy L.

2021. “Changes in Mental Health and Treatment, 1997–2017.” Journal of Health and Social Behavior 62(1):53–68.

23.

Jones

Christopher M.

Noonan

Rita K.

Compton

Wilson M.

2020. “Prevalence and Correlates of Ever Having a Substance Use Problem and Substance Use Recovery Status among Adults in the United States.” Drug and Alcohol Dependence 214:108169. doi:10.1016/j.drugalcdep.2020.108169.

24.

Kessler

Ronald C.

Berglund

Patricia A.

Bruce

Martha L.

Koch

J. Randy

Laska

Eugene M.

Leaf

Philip J.

Manderscheid

Ronald W.

Rosenheck

Robert A.

Walters

Ellen E.

Wang

Philip S.

2001. “The Prevalence and Correlates of Untreated Serious Mental Illness.” Health Services Research 36(6):987–1007.

25.

Kessler

Ronald C.

Berglund

Patricia

Chiu

Wai Tat

Demler

Olga

Heeringa

Steven

Hiripi

Eva

Jin

Robert

, et al 2004. “The U.S. National Comorbidity Survey Replication (NCS-R): Design and Field Procedures.” International Journal of Methods in Psychiatric Research 13(2):69–92.

26.

Kessler

Ronald C.

Chiu

Wai Tai

Demler

Olga

Merikangas

Kathleen R.

Walters

Ellen E.

2005. “Prevalence, Severity, and Comorbidity of 12-Month DSM-IV Disorders in the National Comorbidity Survey Replication.” Archives of General Psychiatry 62(6):617–27.

27.

Kessler

Ronald C.

Demler

Olga

Frank

Richard G.

Olfson

Mark

Pincus

Harold Alan

Walters

Ellen E.

Wang

Philip

Wells

Kenneth B.

Zaslavsky

Alan M.

2005. “Prevalence and Treatment of Mental Disorders, 1990 to 2003.” New England Journal of Medicine 352(24):2515–23.

28.

Kessler

Ronald C.

Merikangas

Kathleen R.

Berglund

Patricia

Eaton

William W.

Koretz

Doreen S.

Walters

Ellen E.

2003. “Mild Disorders Should Not Be Eliminated from the DSM-V.” Archives of General Psychiatry 60(11):1117−22.

29.

McAlpine

Donna D.

McCreedy

Ellen

Alang

Sirry

. 2018. “The Meaning and Predictive Value of Self-Rated Mental Health among Persons with a Mental Health Problem.” Journal of Health and Social Behavior 59(2):200–14.

30.

Mechanic

David

. 2003. “Is the Prevalence of Mental Disorders a Good Measure of the Need for Services?” Health Affairs 22(5):8–20.

31.

Mojtabai

Ramin

Jorm

Anthony F.

2015. “Trends in Psychological Distress, Depressive Episodes and Mental Health Treatment-Seeking in the United States: 2001–2012.” Journal of Affective Disorders 174:556–61.

32.

Mojtabai

Ramin

Olfson

Mark

Mechanic

David

. 2002. “Perceived Need and Help-Seeking with Mood, Anxiety, or Substance Use Disorders.” Archives of General Psychiatry 59(1):77–84.

33.

Mojtabai

Olfson

Sampson

N. A.

Jin

Druss

Wang

P. S.

Wells

K. B.

Pincus

H. A.

Kessler

R. C.

2011. “Barriers to Mental Health Treatment: Results from the National Comorbidity Survey Replication.” Psychological Medicine 41(8):1751–61.

34.

Pinedo

Villatoro

A. P.

2020. “The Role of Perceived Treatment Need in Explaining Racial-Ethnic Disparities in the Use of Substance Abuse Treatment Services.” Journal of Substance Abuse Treatment 118:108105. doi:10.1016/j.jsat.2020.108105.

35.

Préville

Michel

Boyer

Richard

Vasiliadis

Helen-Maria

Grenier

Sébastien

Streiner

David

Cairney

John

Brassard

Joëlle

, and Scientific Committee of the ESA Study. 2010. “Persistence and Remission of Psychiatric Disorders in the Quebec Older Adult Population.” Canadian Journal of Psychiatry 55(8):514–22.

36.

Roberts

Tessa

Esponda

Georgina Miguel

Krupchanka

Dzmitry

Shidhaye

Rahul

Patel

Vikram

Rathod

Sujit

. 2018. “Factors Associated with Health Service Utilisation for Common Mental Disorders: A Systematic Review.” BMC Psychiatry 118:262–82.

37.

Sareen

Henriksen

C. A.

Stein

M. B.

Afifi

T. O.

Lix

L. M.

Enns

M. W.

2013. “Common Mental Disorder Diagnosis and Need for Treatment Are Not the Same: Findings from a Population-Based Longitudinal Survey.” Psychological Medicine 43(9):1941–51.

38.

Slade

Mike

Longden

Eleanor

. 2015. “Empirical Evidence about Recovery and Mental Health.” BMC Psychiatry 15. doi:10.1186/s12888-015-0678-4.

39.

Stringer

Kristi L.

Baker

Elizabeth H.

2018. “Stigma as a Barrier to Substance Abuse Treatment among Those with Unmet Need: An Analysis of Parenthood and Marital Status.” Journal of Family Issues 39(1):3–27.

40.

ten Have

Nuyen

Beekman

de Graaf

2013. “Common Mental Disorder Severity and Its Association with Treatment Contact and Treatment Intensity for Mental Health Problems.” Psychological Medicine 43(10):2203–13.

41.

Thoits

Peggy A.

2022. “Mental Health Treatment Histories, Recovery, and Well-Being.” Society and Mental Health 12(1):1–16.

42.

Walker

Elizabeth Reisinger

Cummings

Janet R.

Hockenberry

Jason M.

Druss

Benjamin G.

2015. “Insurance Status, Use of Mental Health Services, and Unmet Need for Mental Health Care in the United States.” Psychiatric Services 66(6):578–84.

43.

Wang

Philip S.

Lane

Michael

Olfson

Mark

Pincus

Harold A.

Wells

Kenneth B.

Kessler

Ronald C.

2005. “Twelve-Month Use of Mental Health Services in the United States: Results from the National Comorbidity Survey Replication.” Archives of General Psychiatry 62(6):629–40.

44.

Wang

Yunqiao

Henriksen

Christine A.

ten Have

Margreet

de Graaf

Ron

Stein

Murray B.

Enns

Murray W.

Sareen

Jitender

. 2017. “Common Mental Disorder Diagnosis and Need for Treatment Are Not the Same: Findings from the NEMESIS Study.” Administration and Policy in Mental Health and Mental Health Services 44(4):572–81.

45.

Watson

Dennis P.

2012. “The Evolving Understanding of Recovery: What Does the Sociology of Mental Health Have to Offer?” Humanity & Society 36(4):290–308.

46.

The WHO World Mental Health Survey Consortium. 2004. “Prevalence, Severity, and Unmet Need for Treatment of Mental Disorders in the World Health Organization World Mental Health Surveys.” JAMA 291(21):2581–90.

47.

Wong

Eunice C.

Collins

Rebecca L.

Breslau

Joshua

Burnam

M. Audrey

Cefalu

Matthew

Roth

Elizabeth

. 2018. “Differential Association of Stigma with Perceived Need and Mental Health Service Use.” Journal of Nervous and Mental Disease 206(6):461–68.