Skip to main content

Continuum beliefs of mental illness: a systematic review of measures

Abstract

Purpose

The continuum of mental health/illness has been subject to scientific debate for decades. While current research indicates that continuum belief interventions can reduce mental health stigma and improve treatment seeking in affected populations, no study has yet systematically examined measures of continuum beliefs.

Methods

This preregistered systematic review summarizes measures of continuum beliefs. Following the PRISMA statement, three scientific databases (PubMed, PsycInfo and PsycArticles via EBSCOhost, Web of Science) are searched, instruments are described and discussed regarding their scope, and methodological quality.

Results

Overall, 7351 records were identified, with 35 studies reporting relevant findings on 11 measures. Most studies examined general population samples and used vignette-based measures. Schizophrenia and depression were most commonly examined, few studies focused on dementia, ADHD, OCD, eating disorders, and problematic alcohol use, or compared continuum beliefs across disorders. Validity was very good for most measures, but reliability was rarely tested. Measures mostly assessed beliefs in the normality of mental health symptoms or the normality of persons with such symptoms but rarely nosological aspects (i.e., categorical v continuous conceptualization of mental disorders).

Conclusions

Current research provides psychometrically sound instruments to examine continuum beliefs for a variety of mental disorders. While studies suggest utility for general population samples and mental health professionals, more research is necessary to corroborate findings, for instance, regarding age (e.g., in adolescents), gender, or type of mental disorder. Future research should also compare self-report ratings, and vignette-based measures, include measures of nosological concepts to fully grasp the continuum concept of mental illness.

Preregistration

PROSPERO: CRD42019123606.

Introduction

The nosological concept of mental disorders has been subject to long-standing discussions. To date, there is no undisputable consensus on their categorical or dimensional nature, although developments of the DSM 5 [1] as well as comprehensive literature seem to favor continuous measures of psychopathology which furthers a dimensional understanding [2, 3]. Schizophrenia, for example, is described along the proneness–persistence–impairment continuum describing psychotic and subsyndromal experiences among the general population with only a small proportion reporting persistent symptoms that may lead to an impairment [4, 5]. This concept has implications for prevention, diagnosis and treatment, as it informs researchers, policymakers and practitioners alike. For example, a continuum model of schizophrenia emphasizes the need for selective prevention in at-risk groups [6], and identifies subgroups with persistent symptoms for personalized treatment purposes. It also points to groups with subsyndromal experiences as target groups for early prevention [7]. A categorical understanding of schizophrenia, on the other hand, facilitates stigmatizing attitudes, because it allows a clear distinction of social groups, that is people with and without schizophrenia [8]. It should be noted, however, that other researchers criticize such a continuum model from a methodological perspective [9, 10]. Linscott and van Os [9], for example, point to methodological flaws and challenges of the conception of continua that might overshadow categorically derived findings, such as latent classes. A similar debate between categorical and continuous conceptualizations can be seen for eating disorders [11,12,13], obsessive–compulsive disorder [14], generalized anxiety disorder [15], depression [16, 17], and at-risk substance use [18, 19] or gambling [20]. This debate is not limited to the scientific community but it also affects patients and the public. Previous research shows that the public perception of mental illness as a categorical construct is connected to public stigma [21, 22] and mental health stigma is recognized as a barrier to treatment seeking [23,24,25,26,27,28,29]. It is also linked to negative psychosocial outcomes, for example, lower self-esteem and self-efficacy and poor quality of life [30,31,32,33,34]. Conversely, a continuum model of mental illness is related to more positive mental health outcomes [35], and lower stigmatizing attitudes. Therefore, promoting continuum beliefs to the public might be a promising approach to reducing public stigma [36].

In this manner, Angermeyer and Schulze [21] describe two core strategies of public communication in line with either categorical beliefs (i.e., medicalization) or continuum beliefs (i.e., normalization). The first strategy encompasses medical treatments of individuals with distinct disorders, such as schizophrenia, and is more prominent among medical professionals and connected to biomedical causal beliefs of mental disorders [37,38,39]. The second strategy sees psychiatric symptoms as a normal experience but connects mental disorders to an increased level of stress and insufficient coping resources. It is more prominent among non-medical health care workers as well as support groups, and it is more strongly connected to psychosocial causal beliefs [37, 38]. In spite of their potential for public mental health and social psychiatry, for instance, by reducing stigmatizing attitudes and thus lowering the barrier to entry into treatment no study has systematically reviewed and summarized measures for continuum beliefs regarding mental health and mental illness, which makes it difficult to assess their validity and utility. For instance, an experienced-based measure might be more valid for clinical samples but less applicable to general population samples, whereas a vignette-based measure might be more applicable but also more strongly affected by bias (e.g., gender bias in case of gendered vignettes). Therefore, this systematic review aims to review and assess previously utilized measures for continuum beliefs to harmonize research efforts and answer the following questions.

  1. (1)

    What are the characteristics of existing continuum belief instruments (e.g., country of origin, setting/target group, examined disorders, mode of administration)?

  2. (2)

    What are the psychometric properties of continuum belief measures?

  3. (3)

    Which areas of the continuum of mental health and mental illness are covered by continuum belief measures?

Method

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement [40] and is registered with the PROSPERO registry (https://www.crd.york.ac.uk/prospero; CRD42019123606). Three scientific databases (PubMed, PsycInfo and PsycArticles via EBSCOhost, Web of Science) were searched for peer-reviewed articles on continuum beliefs that were published before June 2022. The search was performed in line with a review and meta-analysis on the association between continuum beliefs and mental health stigma [36]; therefore, initial database search and abstract and title screening was similar in this study, but eligibility criteria differed between studies. Search terms comprised continuum AND stigma AND mental health OR mental illness, search strategies are presented in Peter et al. [36]. In addition, reference lists of included studies were checked to identify additional eligible studies.

Eligibility criteria

Eligibility criteria were described in accordance with the PICO process [41]:

Population: Human beings from the general population without any age restrictions.

Intervention: Studies that investigate continuum beliefs were included, either as observational or interventional studies. Continuum beliefs refer to the nosological concept of mental illness, either as a general, transdiagnostic concept of continuity of mental illness/mental health problems or as a specific concept for distinct mental disorders. Other forms of continua, such as the continuum of care [42] or the dual-continua model of mental health and mental illness [43,44,45], were not included, because they represent broader concepts within psychiatric and psychological research regarding health care structures as well as psychological functioning, which transcend the current research question that focuses on the conceptualization of mental disorders.

Comparison: Experimental as well as observational quantitative studies were included; therefore, there was no restriction regarding a potential control group.

Outcome: Studies should measure continuum beliefs, either as a predictor, an intermediary variable, or as an outcome.

Studies were not limited to a particular design (e.g., experimental studies or observational cohort studies) or method (e.g., quantitative data assessment). Finally, the search was limited to studies published in English, German, French, or Polish. Titles and abstracts of identified studies were screened by the first and second author and full texts were obtained of potentially relevant studies. Full texts were then screened against eligibility criteria independently by the first and second author. Differences were discussed with the third author and solved by mutual agreement to include or exclude studies.

Data extraction, synthesis, and analysis

The first and second author independently extracted data on authors, date of publication, study design, sample, measures and psychometric properties (if reported in the original studies). The first and third author then independently rated dimensions of methodological quality and psychometric properties of the measures following the reporting guidelines proposed by Bennett et al. [46] to compare measures. The following dimensions were examined: readability (availability and length of the measure), cultural translation (availability in multiple (target) languages), respondent burden (over/under 60 items), content validity (theoretical foundation and expert consultation), criterion validity (correlation with external criteria), construct validity (correlation with related/non-related constructs), internal consistency (Cronbach’s alpha below/above 0.70), inter-rater reliability (agreement between different raters), intra-rater reliability (agreement within one rater), test–retest reliability (significant test–retest correlation across at least two timepoints), floor or ceiling effects, and responsiveness (successful manipulation check). The definitions are also listed in the table notes of Table 3, but a concise definition of these aspects can be found elsewhere [47]. Differences in ratings or extracted information were discussed and solved with the second author. The narrative synthesis reports identified measures of continuum beliefs, their assessment method, their content as well as a rating of their methodological quality. For each study, design, sample size and composition, and country of origin are also reported.

Results

The initial database search resulted in 7351 records (PubMed: 3197, Web of Science: 2209, EBSCOhost: 1945), with 73 records being additionally identified from reference lists of potentially relevant studies. After removing duplicates, 7120 records remained. A screening of titles and abstracts lead to an exclusion of 6995 records. Finally, 125 full texts were assessed for eligibility, wherefrom 90 studies were excluded, leading to a sample of 35 studies for the synthesis (see Fig. 1).

Fig. 1
figure 1

PRISMA flow diagram

The excluded studies did not assess mental health/illness but other aspects, such as the continuum of care; they did not provide measures (e.g., editorials or theoretical work) or they were based on other concepts of a continuum such as the dual continua model [43, 45] that refer to psychological functioning (i.e., the intersection of mental wellbeing and mental health/illness) rather than nosological concepts of mental health/illness.

Study description

The included studies [22, 48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81] investigated continuum beliefs regarding multiple mental disorders (more than one disorder per study in 15 out of 35 studies). Most studies were conducted in Germany (n = 14), followed by the United States of America (n = 10), Australia, Canada, France, and Singapore (n = 2) as well as United Kingdom, Ireland and the Netherlands (n = 1). An overview of included studies is given in Table 1.

Table 1 Overview of included studies measuring continuum beliefs (n = 35)

Overall, most studies focused on schizophrenia (n = 23) or depression (n = 20), followed by alcohol use disorder or addiction (n = 5), OCD (n = 3), and dementia (n = 2). One study each measured continuum beliefs regarding ADHD, social anxiety disorder/generalized anxiety disorder, eating disorder, and bipolar disorder. To elicit continuum beliefs, 27 out of 35 studies utilized vignettes, sometimes personalized with names and/or gender. These vignettes consisted of short descriptions of either a person with a specific disorder or typical symptoms of said disorder based on its diagnostic criteria according to DSM-IV or ICD-10. Eight studies used a rating scale, for instance the Continuum Beliefs Questionnaire (CBQ), that measures continuum beliefs independent of a vignette [52, 58, 64, 65]. All studies, except one [57], used four-point to seven-point Likert scales as response measures (i.e., agreement with statements about a person, symptoms or a condition). The remaining study [57] asked participants to rate the severity of presented vignettes on a scale from 0 to 8 and provided a hint that experts perceived a rating above four as clinically relevant.

Eighteen studies investigated general population samples, with nine explicitly mentioning representativeness of their sample (e.g., stratified sampling and weighted analysis). However, studies rarely mentioned how representativeness was achieved, for instance, via quota sampling or probability sampling; therefore, this information is not included in Table 1. Seven studies examined (undergraduate) students, seven used Amazon Mechanical Turk (MTurk) samples, and three investigated adolescents [51, 70], or mental health professionals [52].

Content of continuum belief measures

Eleven different measures were used across studies, and all were analyzes as one-dimensional measures. They ranged from single-item measures for general continuum beliefs [e.g., “Basically we are all sometimes like this person. It’s just a question how pronounced this state is.“; 60] to illness-specific scales with sixteen items [schizophrenia; 64], four items [schizophrenia; 81] and five items [problem drinking/addiction; 54]. Three measures, namely, Continuum Beliefs Questionnaire (CBQ), Questionnaire of Belief in a Continuum of Schizophrenia (QBCS), and Problem Drinking Belief Scale (PDBS), received distinct labels, and other measures did not, despite being used in multiple studies. The single-item measure by Schomerus et al. [60], for instance, was used or adapted by ten of the included studies [22, 48, 49, 51, 53, 59, 61,62,63, 74], one of which [49] performed additional analyses with the same data set as the original study [60]. Two studies [66, 67] also referred to one data set. Most measures aim to assess beliefs in a continuum of symptom experience (see Table 1). However, a closer look at the items used in these measures reveals three different aspects of continuum beliefs, namely, (1) continuity of symptoms [e.g., "The transition between normal and delusional thinking is fluent"; 58], (2) normality of mental health problems [e.g., “To some extent, most persons will experience problems that are similar to those of Anne”; 59], and (3) normality of persons with mental health problems [e.g., “Basically, we are all sometimes like this person”; 60]. Conceptually, the first continuum closely resembles the continuous understanding of mental health and mental illness, as expressed, for instance, in the dimensional operationalization of mental disorders in the DSM 5 or the psychosis continuum [1, 4]. The second and third continua rely either on a personal experience of symptoms or the identification with a person with mental illness (i.e., a vignette). Both refer to a norm of inclusivity (e.g., we are all like this person, most people experience these symptoms) rather than a continuum of symptoms to represent mental illness. They are not necessarily linked to the nosological concept of an illness but rather to its phenotype and prevalence (second continuum) and the perceived similarity or lack of perceived differentness regarding the vignette (third continuum). Perceived differentness is often used as an indicator of stigmatizing attitudes, since it depicts the differentiation between us and them, which is a core process of stigmatization [8]. The identified continua, exemplary items, and the assigned studies are presented in Fig. 2.

Fig. 2
figure 2

Three measured core aspects of continuum beliefs

While most measures focus on only one or two aspects of continuum beliefs, two measures represent all three aspects of continuum beliefs, namely, the scale developed by Schomerus et al. [59] and the CBQ [64]. The former is generic and vignette-based, the latter was specifically developed as a rating scale for continuum beliefs regarding schizophrenia. Despite their inclusion of all three aspects, both measures were analyzed as one-dimensional scales, and the conceptual differences between continua were not explored any further. In addition, no study has empirically compared different measures or operationalizations of continuum beliefs.

In the next step, we examined methodological quality, psychometric properties, and utility (i.e., readability, cultural translation, respondent burden) of continuum belief measures across studies. Categories and ratings were based on previous research [46, 47], and rated independently by the first and third author. Differences were discussed and resolved with the second author (see Table 2).

Table 2 Psychometric properties of continuum belief measures in the included studies (n = 35)

Overall, most studies pointed to good readability, content validity and low respondent burden. Criterion validity was also very positive for most measures across studies. Cultural translation of some measures was proven, for instance, the adapted measure of Schomerus et al. [60]. All measures were comparably short (1–16 items), which makes them highly economical and efficient. Content validity and criterion validity were also high for most studies, since measures were based on theoretical considerations, pretested and validated, for example, via manipulation tests, and expert consultations. Construct validity was mostly tested as discriminant validity resulting in either low or negative correlations between continuum beliefs and stigmatizing attitudes in most studies except for one study on OCD [50]. Fewer studies reported (satisfactory) internal consistency (e.g., Cronbach’s alpha > 0.7), test–retest reliability was reported in two studies [55, 56]. Floor or ceiling effects were not explicitly reported in any of the included studies. Since all measures were self-reports and few studies examined continuum beliefs at multiple timepoints to calculate test–retest reliability, intra-rater reliability as well as inter-rater reliability were also not reported. Responsiveness was very good, as many studies used experimental designs and manipulation checks to measure changes in continuum beliefs following continuum belief interventions. None of the studies reported known-groups validity (e.g., based on gender, age or type of disorder) regarding continuum beliefs measures. As a summary, an overview of measures is provided in Table 3.

Table 3 Overview of eleven measures of continuum beliefs (plus a revised version of the Continuum Beliefs Questionnaire) including their origin, number of items, assessment method, and the dimensions of continuum reflected with each measure as well as examined disorders

Discussion

This systematic review summarizes and evaluates measures of continuum beliefs of mental illness. The search identified eleven different measures that ranged from single items to multi-item scales. Most scales were generic, but some were developed for specific disorders (i.e., schizophrenia, alcohol use disorder). The measures seem to have high objectivity, since the instructions are clear, readability is high, and they are easy to implement. Most measures also have high validity due to their theory-based development, pretests, and psychometric testing (see Table 2). Yet, other psychometric properties such as reliability (e.g., test–retest reliability) as well as clinical utility have rarely been investigated beyond initial piloting studies and reports of internal consistency. Thus, more extensive psychometric studies are needed to test factorial validity and measurement invariance, test–retest reliability, and cross-cultural validity. The latter is particularly important given cross-cultural differences in conceptualizing mental disorders that might influence continuum beliefs [e.g., 82, 83].

Although some measures have been adapted to different European, American, and Asian contexts [60], further comparative cross-cultural research is encouraged. Moreover, the development, harmonization, and monitoring of continuum belief measures should be connected to novel developments in describing and diagnosing mental disorders. Paradigms such as HiTOP [84] aim to provide an overarching hierarchy of psychopathology that pays respect to cross-cultural differences and focuses on phenotypical similarities, thus continuum belief measures could be developed and extended in tandem.

The continuum belief measures were mostly implemented in general population samples which supports their feasibility and applicability for epidemiological research. Epidemiological mental health cohorts, for instance, could incorporate these measures to assess not only stigmatizing attitudes but also continuum beliefs. Similarly, anti-stigma campaigns could include continuum belief measures to measure efficacy concerning public health impact, due to mostly robust negative associations between continuum beliefs and stigmatizing attitudes [36]. However, in some studies [e.g., 50, 81], this association was not significant; the continuum belief intervention even lead to an increase in self-stigma (i.e., being weird/unpredictable is typical of me) in one study [81]. The authors [81] argue that this type of non-threatening self-stigma (e.g., weird as opposed to dangerous) is an expression of increasing perceived similarities to the target group thus strengthening shared social identity. However, it is unclear how this affects persons with more severe symptoms and perceived similarity with more threatening attributes (e.g., dangerous). Potentially, continuum belief interventions could exacerbate group differences in samples with more severe symptoms, because vignettes of disorders with mild to moderate severity (as used in continuum belief measures) highlight the discrepancy between normal functioning and their personal experience. For example, in a study by Thibodeau and Peterson [78], the continuum belief intervention increased fear. This conclusion is merely hypothetical, though because of a lack of studies with a varying severity of symptoms and mental disorders.

Overall, more studies with clinical samples and mental health professionals are needed to assess clinical utility and practicability. One study with persons with at risk alcohol use [54] provided tentative evidence that promoting continuum beliefs might increase problem recognition. Problem recognition is an important predictor of treatment motivation following the transtheoretical model of health behavior change [85, 86], and it can lead to lower drop-out rates, which is very promising for this field [87]. Therefore, the function of continuum beliefs in treatment processes needs to be studied more closely. This is also true for more diverse populations (e.g., children and adolescents, older adults). One study with adolescents showed good psychometric properties of continuum belief measures [51], but more research is necessary to confirm these findings. Since several studies used random online samples (gathered via MTurk), their results should also be interpreted with caution when thinking about adapting scales to applied contexts, since there is an ongoing debate about data quality and validity of MTurk data and similar online panels and services compared to pragmatic, and community samples [88,89,90]. Hence, multi-group comparisons of samples from different providers and sources are recommended.

Furthermore, the conceptualization of continuum beliefs needs to be examined. The CBQ, the PDBS, and the QBCS were developed for specific disorders, which is why they can refer to disorder-specific symptoms without including vignettes or descriptions of mental disorders as a frame of reference. Consequently, other studies did not need to adapt or pretest additional materials. These scales could also directly describe a disorder-specific continuum of symptoms (e.g., the psychosis continuum; [4]) as an indicator of mental stress leading to mental illness, which is in line with the approach of normalization proposed by Angermeyer und Schulze [21]. Vignette-based studies with more generic scales, on the other hand, were more flexible and allow direct comparisons of beliefs regarding different disorders—which lends credibility to the idea of an underlying concept of continuity or dimension of mental health and illness. This way of thinking corresponds to current positive psychological approaches, such as the dual continuum model of mental health [43, 44], and the HiTOP model with its focus on phenotypes rather than diagnostic labels or categories [84].

This more generic approach, however, also requires validated vignettes to assess continuum beliefs. This is challenging for multiple reasons: First, the included studies used different vignettes which could have biased the results. Second, most studies controlled for confounding influences by either presenting no gender or name or randomizing gendered vignettes. However, these vignettes still required participants to imagine the person and their symptoms, which requires sufficient perceived realism of each vignette and consensus regarding the described experience (e.g., of a depressive episode) [91]. Therefore, future research should compare continuum beliefs across different vignettes. Third, other aspects such as age or ethnicity of the presented or imagined person were not controlled and might have additional influence on continuum beliefs [92]. Hence, future studies should examine the differential impact of different disorder-specific vignettes on multiple measures of continuum beliefs. These vignettes could also be tested or constructed based on population assessments, similar to the measure of Paulus et al. [57] In their study, they asked participants to rate the severity of different symptoms and behaviors ranging from healthy to clinically relevant. While this is closely connected to a diagnostic approach (e.g., in psychotherapeutic training), it also provides the opportunity to customize (sub-)clinical vignettes of specific disorders concerning type and intensity of symptoms and assess subsequent ratings to examine the extent of continuum beliefs. In this sense, future research could build upon scale-based measures, such as the CBQ that requires similar assessments (e.g., regarding hallucinations) via Likert scales.

Finally, different operationalizations of continuum beliefs are also a promising avenue for future research, similar to the area of health literacy, where multiple objective tests and subjective self-reports are state of the art [93, 94]. While the identified measures captured between one and three aspects of the continuum (see Fig. 2), certain aspects were rarely examined, for example, the categorical v continuous conceptualization of mental illness [2, 3]. Items measuring this nosological concept were included in the development of the CBQ, but they were eventually excluded from the final measure [64]. It might be beneficial to compare measures of such conceptual beliefs with continuum beliefs measures, and compare multiple measures of continuum beliefs, to assess similarities and differences and examine their responsiveness in future interventional studies. Nevertheless, it should also be added that a more conceptual measure of continuum beliefs requires a more abstract assessment of nosological concepts of illness and health, which might be rather difficult for laypersons, meaning population samples without previous education about this issue.

In sum, when choosing a measure of continuum beliefs, a researcher needs to think about the population (e.g., a sample with clinical depression vis-à-vis a healthy population sample), the context (e.g., disorder-specific versus transdiagnostic assessments), the method (e.g., rating scales versus vignettes), and the overall aim of the study (e.g., comparing attitudes across groups or disorders versus examining predictive utility or validity of continuum beliefs). In an epidemiological study of depression-related attitudes in the population, a disorder-specific measure using vignettes might be most appropriate, whereas a comparative study of continuum beliefs across different disorders might benefit from a short, generic measure that has a low respondent burden and allows for transdiagnostic comparisons. While our review shows that some types of measures have received more attention than others so far, the usefulness and merit of each measure strongly depends on the context of investigation. This review provides a framework for decision-making and further research in continuum beliefs of mental illness.

The review is not without limitations. The search was limited to three data bases, and preregistered search criteria (e.g., regarding search terms, language) as well as peer-reviewed literature, which might have neglected grey literature and other studies that could not be identified by the initial search. The review focused on continuum beliefs of mental illness, while previous literature defined different continua (e.g., continuum of care, dual continua model) that might be associated with continuum beliefs. For instance, the continuum of care assumes different needs and responsibilities for different stages of an illness, such as prevention, acute treatment, or recovery [95]. These stages are associated with different levels of severity of an illness, which might serve as a reference for assessing continuum beliefs. Similarly, the dual continua model assumes parallel continua of mental well-being and mental health/illness. It is unclear how different constellations of well-being and mental health (e.g., flourishing) are associated with continuum beliefs. The study used established ratings of methodological quality and it reported results in accordance with the PRISMA statement, but it did not examine risk of bias or use different rating systems of measures. This could be the focus of future work. Despite its weaknesses, however, this review identified several measurement instruments of continuum beliefs with applications in multiple cultural contexts, and initial evidence of good validity, and applicability in general population samples. Hence, the potential of continuum beliefs regarding public mental health and the economic modes of assessment are quite promising.

Data availability statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

References

  1. American Psychiatric Association (2013) Diagnostic and statistical manual of mental disorders: DSM 5 5edn. American Psychiatric Association, Washington

    Book  Google Scholar 

  2. Markon KE, Chmielewski M, Miller CJ (2011) The reliability and validity of discrete and continuous measures of psychopathology: a quantitative review. Psychol Bull 137(5):856–879. https://doi.org/10.1037/a0023678

    Article  PubMed  Google Scholar 

  3. Haslam N, Holland E, Kuppens P (2012) Categories versus dimensions in personality and psychopathology: a quantitative review of taxometric research. Psychol Med 42(5):903–920. https://doi.org/10.1017/s0033291711001966

    CAS  Article  PubMed  Google Scholar 

  4. van Os J, Linscott RJ, Myin-Germeys I, Delespaul P, Krabbendam L (2009) A systematic review and meta-analysis of the psychosis continuum: evidence for a psychosis proneness–persistence–impairment model of psychotic disorder. Psychol Med 39(2):179–195. https://doi.org/10.1017/s0033291708003814

    Article  PubMed  Google Scholar 

  5. Asai T, Yamauchi T, Sugimori E, Bando N, Tanno Y (2010) Schizotypy and schizophrenia as points on a continuum. Japanese Psychol Rev 53(2):240–261

    Google Scholar 

  6. Seidman LJ, Nordentoft M (2015) New targets for prevention of schizophrenia: Is it time for interventions in the premorbid phase? Schizophr Bull 41(4):795–800. https://doi.org/10.1093/schbul/sbv050

    Article  PubMed  PubMed Central  Google Scholar 

  7. Appelbaum PS (2015) Ethical challenges in the primary prevention of schizophrenia. Schizophr Bull 41(4):773–775. https://doi.org/10.1093/schbul/sbv053

    Article  PubMed  PubMed Central  Google Scholar 

  8. Link BG, Phelan JC (2001) Conceptualizing stigma. Ann Rev Sociol 27(1):363–385. https://doi.org/10.1146/annurev.soc.27.1.363

    Article  Google Scholar 

  9. Linscott RJ, van Os J (2013) An updated and conservative systematic review and meta-analysis of epidemiological evidence on psychotic experiences in children and adults: on the pathway from proneness to persistence to dimensional expression across mental disorders. Psychol Med 43(6):1133–1149. https://doi.org/10.1017/s0033291712001626

    CAS  Article  PubMed  Google Scholar 

  10. Sulis W (2018) Assessing the continuum between temperament and affective illness: psychiatric and mathematical perspectives. Philosoph Transact Royal Soc B-Biol Sci 373:1744. https://doi.org/10.1098/rstb.2017.0168

    Article  Google Scholar 

  11. Elbourne KE, Chen J (2007) The continuum model of obligatory exercise: A preliminary investigation. J Psychosom Res 62(1):73–80. https://doi.org/10.1016/j.jpsychores.2004.12.003

    Article  PubMed  Google Scholar 

  12. Hesse-Biber S (1992) Report on a panel longitudinal study of college women’s eating patterns and eating disorders: Noncontinuum versus continuum measures. Health Care Women Int 13(4):375–391. https://doi.org/10.1080/07399339209516015

    CAS  Article  PubMed  Google Scholar 

  13. Lindeman M, Stark K, Keskivaara P (2001) Continuum and linearity hypotheses on the relationship between psychopathology and eating disorder symptomatology. Eating Weight Disorders Stud Anorexia Bulimia Obesity 6(4):181–187. https://doi.org/10.1007/bf03339741

    CAS  Article  Google Scholar 

  14. Fullana MA, Mataix-Cols D, Caspi A, Harrington H, Grisham JR, Moffitt TE, Poulton R (2009) Obsessions and compulsions in the community: prevalence, interference, help-seeking, developmental stability, and co-occurring psychiatric conditions. Am J Psychiatry 166(3):329–336

    Article  Google Scholar 

  15. Kertz SJ, McHugh RK, Lee J, Björgvinsson T (2014) Examining the latent structure of worry and generalized anxiety in a clinical sample. J Anxiety Disord 28(1):8–15. https://doi.org/10.1016/j.janxdis.2013.11.003

    Article  PubMed  Google Scholar 

  16. Siddaway AP, Wood AM, Taylor PJ (2017) The center for epidemiologic studies-depression (CES-D) scale measures a continuum from well-being to depression: Testing two key predictions of positive clinical psychology. J Affect Disord 213:180–186. https://doi.org/10.1016/j.jad.2017.02.015

    Article  PubMed  PubMed Central  Google Scholar 

  17. Goldstein B, Rosselli F (2003) Etiological paradigms of depression: The relationship between perceived causes, empowerment, treatment preferences, and stigma. J Ment Health 12(6):551–563. https://doi.org/10.1080/09638230310001627919

    Article  Google Scholar 

  18. Mahmoud KF, Finnell D, Savage CL, Puskar KR, Mitchell AM (2017) A concept analysis of substance misuse to inform contemporary terminology. Arch Psychiatr Nurs 31(6):532–540. https://doi.org/10.1016/j.apnu.2017.06.004

    Article  PubMed  Google Scholar 

  19. Rehm J, Marmet S, Anderson P, Gual A, Kraus L, Nutt DJ, Room R, Samokhvalov AV, Scafato E, Trapencieris M, Wiers RW, Gmel G (2013) Defining substance use disorders: do we really need more than heavy use? Alcohol Alcohol 48(6):633–640. https://doi.org/10.1093/alcalc/agt127

    CAS  Article  PubMed  Google Scholar 

  20. Strong DR, Kahler CW (2007) Evaluation of the continuum of gambling problems using the DSM-IV. Addiction 102(5):713–721. https://doi.org/10.1111/j.1360-0443.2007.01789.x

    Article  PubMed  Google Scholar 

  21. Angermeyer MC, Schulze B (2001) Reinforcing stereotypes: How the focus on forensic cases in news reporting may influence public attitudes towards the mentally ill. Int J Law Psychiatry 24(4–5):469–486. https://doi.org/10.1016/s0160-2527(01)00079-6

    CAS  Article  PubMed  Google Scholar 

  22. von dem Knesebeck O, Mnich E, Angermeyer MC, Kofahl C, Makowski A (2015) Changes in depression stigma after the Germanwings crash—Findings from German population surveys. J Affect Disord 186:261–265. https://doi.org/10.1016/j.jad.2015.07.029

    Article  Google Scholar 

  23. Schomerus G, Auer C, Rhode D, Luppa M, Freyberger HJ, Schmidt S (2012) Personal stigma, problem appraisal and perceived need for professional help in currently untreated depressed persons. J Affect Disord 139(1):94–97. https://doi.org/10.1016/j.jad.2012.02.022

    Article  PubMed  Google Scholar 

  24. Schomerus G, Stolzenburg S, Freitag S, Speerforck S, Janowitz D, Evans-Lacko S, Muehlan H, Schmidt S (2019) Recognizing personal mental illness and seeking help – a prospective study among untreated persons with mental illness. Eur Arch Psychiatry Clin Neurosci 269(4):469–479. https://doi.org/10.1007/s00406-018-0896-0

    Article  PubMed  Google Scholar 

  25. Schnyder N, Michel C, Panczak R, Ochsenbein S, Schimmelmann BG, Schultze-Lutter F (2018) The interplay of etiological knowledge and mental illness stigma on healthcare utilisation in the community: A structural equation model. Eur Psychiatr 51:48–56. https://doi.org/10.1016/j.eurpsy.2017.12.027

    CAS  Article  Google Scholar 

  26. Schnyder N, Panczak R, Groth N, Schultze-Lutter F (2017) Association between mental health-related stigma and active help-seeking: systematic review and meta-analysis. Br J Psychiatry 210(4):261–268. https://doi.org/10.1192/bjp.bp.116.189464

    Article  PubMed  Google Scholar 

  27. Clement S, Schauman O, Graham T, Maggioni F, Evans-Lacko S, Bezborodovs N, Morgan C, Rüsch N, Brown JSL, Thornicroft G (2015) What is the impact of mental health-related stigma on help-seeking? A systematic review of quantitative and qualitative studies. Psychol Med 45(1):11–27. https://doi.org/10.1017/s0033291714000129

    CAS  Article  PubMed  Google Scholar 

  28. Jennings KS, Cheung JH, Britt TW, Goguen KN, Jeffirs SM, Peasley AL, Lee AC (2015) How are perceived stigma, self-stigma, and self-reliance related to treatment-seeking? A three-path model. Psych Rehab J 38(2):109–116. https://doi.org/10.1037/prj0000138

    Article  Google Scholar 

  29. Vogel DL, Wade NG, Hackler AH (2007) Perceived public stigma and the willingness to seek counseling: The mediating roles of self-stigma and attitudes toward counseling. J Couns Psychol 54(1):40–50. https://doi.org/10.1037/0022-0167.54.1.40

    Article  Google Scholar 

  30. Corrigan PW, Watson AC, Barr L (2006) The self-stigma of mental illness: Implications for self-esteem and self-efficacy. J Soc Clin Psychol 25(8):875–884. https://doi.org/10.1521/jscp.2006.25.8.875

    Article  Google Scholar 

  31. Rüsch N, Corrigan PW, Powell K, Rajah A, Olschewski M, Wilkniss S, Batia K (2009) A stress-coping model of mental illness stigma: II. Emotional stress responses, coping behavior and outcome. Schizophrenia Res 110(13):65–71. https://doi.org/10.1016/j.schres.2009.01.005

    Article  Google Scholar 

  32. Corrigan PW, Morris SB, Michaels PJ, Rafacz JD, Rusch N (2012) Challenging the public stigma of mental illness: a meta-analysis of outcome studies. Psychiatr Serv 63(10):963–973. https://doi.org/10.1176/appi.ps.201100529

    Article  PubMed  Google Scholar 

  33. Corrigan PW, Watson AC (2002) Understanding the impact of stigma on people with mental illness. World Psychiatry 1(1):16-20

    PubMed  PubMed Central  Google Scholar 

  34. Rüsch N, Angermeyer MC, Corrigan PW (2005) Mental illness stigma: Concepts, consequences, and initiatives to reduce stigma. Eur Psychiatr 20(8):529–539. https://doi.org/10.1016/j.eurpsy.2005.04.004

    Article  Google Scholar 

  35. Persson L, Dobson KS, Frampton NMA (2021) Evaluation of a mental health continuum model in two samples. Canad J Behav Sci/ Revue canadienne des sciences du comportement: Adv Online Publ https://doi.org/10.1037/cbs0000273

  36. Peter L-J, Schindler S, Sander C, Schmidt S, Muehlan H, McLaren T, Tomczyk S, Speerforck S, Schomerus G (2021) Continuum beliefs and mental illness stigma: a systematic review and meta-analysis of correlation and intervention studies. Psychol Med 51(5):716–726. https://doi.org/10.1017/S0033291721000854

    Article  PubMed  PubMed Central  Google Scholar 

  37. Read R, Moberly NJ, Salter D, Broome MR (2017) Concepts of mental disorders in trainee clinical psychologists. Clin Psychol Psychother 24(2):441–450. https://doi.org/10.1002/cpp.2013

    CAS  Article  PubMed  Google Scholar 

  38. Wyatt RC, Livson N (1994) The not so great divide? Psychologists and psychiatrists take stands on the medical and psychosocial models of mental illness. Prof Psychol Res Pract 25(2):120–131. https://doi.org/10.1037/0735-7028.25.2.120

    Article  Google Scholar 

  39. Harland R, Antonova E, Owen GS, Broome M, Landau S, Deeley Q, Murray R (2009) A study of psychiatrists’ concepts of mental illness. Psychol Med 39(6):967–976. https://doi.org/10.1017/s0033291708004881

    CAS  Article  PubMed  Google Scholar 

  40. Moher D, Liberati A, Tetzlaff J, Altman DG, Prisma Group (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Int Med 151(4):264–269. https://doi.org/10.7326/0003-4819-151-4-200908180-00135

    Article  PubMed  Google Scholar 

  41. Schardt C, Adams MB, Owens T, Keitz S, Fontelo P (2007) Utilization of the PICO framework to improve searching PubMed for clinical questions. BMC Med Inf Decis Making 7(1):16. https://doi.org/10.1186/1472-6947-7-16

    Article  Google Scholar 

  42. Berendsen AJ, Groenier KH, de Jong GM, Meyboom-de Jong B, van der Veen WJ, Dekker J, de Waal MWM, Schuling J (2009) Assessment of patient’s experiences across the interface between primary and secondary care: Consumer Quality Index Continuum of Care. Patient Educ Couns 77(1):123–127. https://doi.org/10.1016/j.pec.2009.01.011

    Article  PubMed  Google Scholar 

  43. Keyes CLM (2002) The mental health continuum: From languishing to flourishing in life. J Health Soc Behav 43(2):207–222. https://doi.org/10.2307/3090197

    Article  PubMed  Google Scholar 

  44. Keyes KM, Krueger RF, Grant BF, Hasin DS (2011) Alcohol craving and the dimensionality of alcohol disorders. Psychol Med 41(3):629–640. https://doi.org/10.1017/s003329171000053x

    CAS  Article  PubMed  Google Scholar 

  45. Michalec B, Keyes CLM (2013) A multidimensional perspective of the mental health of preclinical medical students. Psychol Health Med 18(1):89–97. https://doi.org/10.1080/13548506.2012.687825

    Article  PubMed  Google Scholar 

  46. Bennett C, Khangura S, Brehaut JC, Graham ID, Moher D, Potter BK, Grimshaw JM (2010) Reporting guidelines for survey research: an analysis of published guidance and reporting practices. PLoS Med 8(8):e1001069–e1001069. https://doi.org/10.1371/journal.pmed.1001069

    Article  PubMed  Google Scholar 

  47. Scarcella A, Page R, Furtado V (2016) Terrorism, radicalisation, extremism, authoritarianism and fundamentalism: a systematic review of the quality and psychometric properties of assessments. PLoS ONE 11(12):e0166947. https://doi.org/10.1371/journal.pone.0166947

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  48. Angermeyer MC, Millier A, Remuzat C, Refai T, Schomerus G, Toumi M (2015) Continuum beliefs and attitudes towards people with mental illness: Results from a national survey in France. Int J Soc Psychiatry 61(3):297–303. https://doi.org/10.1177/0020764014543312

    Article  PubMed  Google Scholar 

  49. Bahlmann J, Schomerus G, Angermeyer MC (2015) Nicht ganz dasselbe: Krankheitsvorstellungen von Burnout und Depression in der Allgemeinbevölkerung [Not quite the same: illness beliefs regarding burnout and depression among the general population]. Psychiatr Prax 42(8):443–447. https://doi.org/10.1055/s-0034-1387365

    Article  PubMed  Google Scholar 

  50. Cole JL, Warman DM (2019) An examination of Continuum Beliefs Versus Biogenetic beliefs in reducing stigma toward violent intrusive thoughts in OCD. J Obsess Compuls Relat Disord 23: 100478. https://doi.org/10.1016/j.jocrd.2019.100478

    Article  Google Scholar 

  51. Dolphin L, Hennessy E (2017) Labelling effects and adolescent responses to peers with depression: An experimental investigation. BMC Psychiatry 17(1):228. https://doi.org/10.1186/s12888-017-1389-9

    Article  PubMed  PubMed Central  Google Scholar 

  52. Helmus K, Schaars IK, Wierenga H, de Glint E, van Os J (2019) Decreasing stigmatization: Reducing the discrepancy between “us” and “them”. An intervention for mental health care professionals. Front Psych 10:243. https://doi.org/10.3389/fpsyt.2019.00243

    Article  Google Scholar 

  53. Makowski AC, Mnich EE, Angermeyer MC, Knesebeck OV (2016) Continuum beliefs in the stigma process regarding persons with schizophrenia and depression: results of path analyses. PeerJ 4:e2360. https://doi.org/10.7717/peerj.2360

    Article  PubMed  PubMed Central  Google Scholar 

  54. Morris J, Albery IP, Heather N, Moss AC (2020) Continuum beliefs are associated with higher problem recognition than binary beliefs among harmful drinkers without addiction experience. Addict Behav 105:106292. https://doi.org/10.1016/j.addbeh.2020.106292

    CAS  Article  PubMed  Google Scholar 

  55. Norman RMG, Sorrentino RM, Windell D, Manchanda R (2008) The role of perceived norms in the stigmatization of mental illness. Soc Psychiatry Psychiatr Epidemiol 43(11):851. https://doi.org/10.1007/s00127-008-0375-4

    Article  PubMed  Google Scholar 

  56. Norman RMG, Windell D, Manchanda R (2010) Examining differences in the stigma of depression and schizophrenia. Int J Soc Psychiatry 58(1):69–78. https://doi.org/10.1177/0020764010387062

    Article  PubMed  Google Scholar 

  57. Paulus DJ, Wadsworth LP, Hayes-Skelton SA (2015) Mental health literacy for anxiety disorders: How perceptions of symptom severity might relate to recognition of psychological distress. J Public Ment Health 14(2):94–106. https://doi.org/10.1108/JPMH-09-2013-0064

    Article  PubMed  PubMed Central  Google Scholar 

  58. Schlier B, Scheunemann J, Lincoln TM (2016) Continuum beliefs about psychotic symptoms are a valid, unidimensional construct: Construction and validation of a revised continuum beliefs questionnaire. Psychiatry Res 241:147–153. https://doi.org/10.1016/j.psychres.2016.04.085

    Article  PubMed  Google Scholar 

  59. Schomerus G, Angermeyer MC, Baumeister SE, Stolzenburg S, Link BG, Phelan JC (2016) An online intervention using information on the mental health-mental illness continuum to reduce stigma. Eur Psychiatr 32:21–27. https://doi.org/10.1016/j.eurpsy.2015.11.006

    CAS  Article  Google Scholar 

  60. Schomerus G, Matschinger H, Angermeyer MC (2013) Continuum beliefs and stigmatizing attitudes towards persons with schizophrenia, depression and alcohol dependence. Psychiatry Res 209(3):665–669. https://doi.org/10.1016/j.psychres.2013.02.006

    Article  PubMed  Google Scholar 

  61. Schomerus G, Stolzenburg S, Angermeyer MC (2015) Impact of the Germanwings plane crash on mental illness stigma: results from two population surveys in Germany before and after the incident. World Psychiatry 14(3):362–363. https://doi.org/10.1002/wps.20257

    Article  PubMed  PubMed Central  Google Scholar 

  62. Speerforck S, Stolzenburg S, Hertel J, Grabe HJ, Strauß M, Carta MG, Angermeyer MC, Schomerus G (2019) ADHD, stigma and continuum beliefs: A population survey on public attitudes towards children and adults with attention deficit hyperactivity disorder. Psychiatry Res 282:112570. https://doi.org/10.1016/j.psychres.2019.112570

    Article  PubMed  Google Scholar 

  63. Subramaniam M, Abdin E, Picco L, Shahwan S, Jeyagurunathan A, Vaingankar JA, Chong SA (2017) Continuum beliefs and stigmatising beliefs about mental illness: results from an Asian community survey. BMJ Open 7(4):e014993. https://doi.org/10.1136/bmjopen-2016-014993

    Article  PubMed  PubMed Central  Google Scholar 

  64. Wiesjahn M, Brabban A, Jung E, Gebauer UB, Lincoln TM (2014) Are continuum beliefs about psychotic symptoms associated with stereotypes about schizophrenia? Psychosis: Psychological. Soc Integrat Approach 6(1):50–60. https://doi.org/10.1080/17522439.2012.740068

    Article  Google Scholar 

  65. Wiesjahn M, Jung E, Kremser JD, Rief W, Lincoln TM (2016) The potential of continuum versus biogenetic beliefs in reducing stigmatization against persons with schizophrenia: An experimental study. J Behav Ther Exp Psychiatry 50:231–237. https://doi.org/10.1016/j.jbtep.2015.09.007

    Article  PubMed  Google Scholar 

  66. Buckwitz V, Porter PA, Bommes JN, Schomerus G, Hinshaw SP (2021) Continuum beliefs and the stigma of depression: An online investigation. Stigma and Health 6(1):113–122. https://doi.org/10.1037/sah0000272

    Article  Google Scholar 

  67. Buckwitz V, Bommes JN, Hinshaw SP, Schomerus G (2022) Continuum beliefs and the perception of similarities and differences to a person with depression. Compr Psychiatry 116:152314. https://doi.org/10.1016/j.comppsych.2022.152314

    CAS  Article  PubMed  Google Scholar 

  68. Cassidy C, Erdal K (2020) Assessing and addressing stigma in bipolar disorder: The impact of cause and treatment information on stigma. Stigma Health 5:104–113. https://doi.org/10.1037/sah0000181

    Article  Google Scholar 

  69. Corrigan PW, Schmidt A, Bink AB, Nieweglowski K, Al-Khouja MA, Qin S, Discont S (2016) Changing public stigma with continuum beliefs. J Ment Health 26(5):411–418. https://doi.org/10.1080/09638237.2016.1207224

    Article  PubMed  Google Scholar 

  70. Fernandez DK, Deane FP, Vella SA (2022) Adolescents’ continuum and categorical beliefs, help-seeking intentions, and stigma towards people experiencing depression or schizophrenia. Int J Ment Health Addict. https://doi.org/10.1007/s11469-022-00766-5

    Article  Google Scholar 

  71. Fernandez DK, Deane FP, Vella SA (2022) Effects of online continuum and categorical belief manipulations on schizophrenia stigma, help-seeking, and help-provision. Psychiatry Res 307:114293. https://doi.org/10.1016/j.psychres.2021.114293

    Article  PubMed  Google Scholar 

  72. Makowski AC, Schomerus G, von dem Knesebeck O (2021) Public continuum beliefs for different levels of depression severity. Front Psych 12:666489. https://doi.org/10.3389/fpsyt.2021.666489

    Article  Google Scholar 

  73. Schlier B, Lincoln TM (2019) The stigma of mental illness: Testing for the implicit bias in diagnostic labels. Psychiatry Res 275:221–227. https://doi.org/10.1016/j.psychres.2019.03.028

    Article  PubMed  Google Scholar 

  74. Schomerus G, Schindler S, Baumann E, Angermeyer MC (2022) Changes in continuum beliefs for depression and schizophrenia in the general population 2011–2020: a widening gap. Soc Psychiatry Psychiatr Epidemiol. https://doi.org/10.1007/s00127-022-02272-4

    Article  PubMed  Google Scholar 

  75. Seow LSE, Chua BY, Xie H, Wang J, Ong HL, Abdin E, Chong SA, Subramaniam M (2017) Correct recognition and continuum belief of mental disorders in a nursing student population. BMC Psychiatry 17(1):289. https://doi.org/10.1186/s12888-017-1447-3

    Article  PubMed  PubMed Central  Google Scholar 

  76. Thibodeau R, Shanks LN, Smith BP (2017) Do continuum beliefs reduce schizophrenia stigma? Effects of a laboratory intervention on behavioral and self-reported stigma. J Behav Ther Exp Psychiatry 58:29–35. https://doi.org/10.1016/j.jbtep.2017.08.002

    Article  PubMed  Google Scholar 

  77. Thibodeau R (2017) Continuum beliefs and schizophrenia stigma: Correlational and experimental evidence. Stigma Health 2(4):266–270. https://doi.org/10.1037/sah0000061

    Article  Google Scholar 

  78. Thibodeau R, Peterson KM (2018) On continuum beliefs and psychiatric stigma: Similarity to a person with schizophrenia can feel too close for comfort. Psychiatry Res 270:731–737. https://doi.org/10.1016/j.psychres.2018.10.070

    Article  PubMed  Google Scholar 

  79. Thibodeau R (2020) Continuum belief, categorical belief, and depression stigma: Correlational evidence and outcomes of an online intervention. Stigma Health 5(4):404–412. https://doi.org/10.1037/sah0000211

    Article  Google Scholar 

  80. Thörel N, Thörel E, Tuschen-Caffier B (2022) Effects of continuum and categorical beliefs on attitudes related to eating disorder stigma. Stigma Health. https://doi.org/10.1037/sah0000386.supp(Supplemental)

    Article  Google Scholar 

  81. Violeau L, Valery KM, Fournier T, Prouteau A (2020) How continuum beliefs can reduce stigma of schizophrenia: The role of perceived similarities. Schizophr Res 220:46–53. https://doi.org/10.1016/j.schres.2020.04.014

    Article  PubMed  Google Scholar 

  82. Schomerus G, Angermeyer MC (2021) Blind spots in stigma research? Broadening our perspective on mental illness stigma by exploring ‘what matters most’ in modern Western societies. Epidemiol Psychiatr Sci 30:e26. https://doi.org/10.1017/S2045796021000111

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  83. Sam DL, Moreira V (2012) Revisiting the mutual embeddedness of culture and mental illness. Online Read Psychol Cult. https://doi.org/10.9707/2307-0919.1078

    Article  Google Scholar 

  84. Kotov R, Krueger RF, Watson D (2018) A paradigm shift in psychiatric classification: the Hierarchical Taxonomy Of Psychopathology (HiTOP). World Psychiatry 17(1):24–25. https://doi.org/10.1002/wps.20478

    Article  PubMed  PubMed Central  Google Scholar 

  85. Prochaska JO, DiClemente CC (1992) Stages of change in the modification of problem behaviors. Progress on behavior modification. Sycamore Press, Sycamore

  86. Prochaska JO, Velicer WF (1997) The transtheoretical model of health behavior change. Am J Health Prom 12(1):38–48. https://doi.org/10.4278/0890-1171-12.1.38

    CAS  Article  Google Scholar 

  87. Ray LA, Hutchison KE, Bryan A (2006) Psychosocial predictors of treatment outcome, dropout, and change processes in a pharmacological clinical trial for alcohol dependence. Addict Disord Treat 5(4):179–190. https://doi.org/10.1097/01.adt.0000210701.63165.5a

    Article  Google Scholar 

  88. Kees J, Berry C, Burton S, Sheehan K (2017) An analysis of data quality: Professional panels, student subject pools, and Amazon’s Mechanical Turk. J Advert 46(1):141–155. https://doi.org/10.1080/00913367.2016.1269304

    Article  Google Scholar 

  89. Chmielewski M, Kucker SC (2020) An MTurk crisis? Shifts in data quality and the impact on study results. Soc Psychol Personal Sci 11(4):464–473. https://doi.org/10.1177/1948550619875149

    Article  Google Scholar 

  90. Smith SM, Roster CA, Golden LL, Albaum GS (2016) A multi-group analysis of online survey respondent data quality: Comparing a regular USA consumer panel to MTurk samples. J Bus Res 69(8):3139–3148. https://doi.org/10.1016/j.jbusres.2015.12.002

    Article  Google Scholar 

  91. O’Dell L, Crafter S, de Abreu G, Cline T (2012) The problem of interpretation in vignette methodology in research with young people. Qual Res 12(6):702–714. https://doi.org/10.1177/1468794112439003

    Article  Google Scholar 

  92. Swami V (2012) Mental health literacy of depression: gender differences and attitudinal antecedents in a representative british sample. PLoS ONE 7(11):e49779. https://doi.org/10.1371/journal.pone.0049779

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  93. Mancuso JM (2009) Assessment and measurement of health literacy: An integrative review of the literature. Nurs Health Sci 11(1):77–89. https://doi.org/10.1111/j.1442-2018.2008.00408.x

    Article  PubMed  Google Scholar 

  94. Haun JN, Valerio MA, McCormack LA, Sørensen K, Paasche-Orlow MK (2014) Health literacy measurement: An inventory and descriptive summary of 51 instruments. J Health Commun 19(S2):302–333. https://doi.org/10.1080/10810730.2014.936571

    Article  PubMed  Google Scholar 

  95. Evashwick C (1989) Creating the continuum of care. Health Matrix 7(1):30–39

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This review was supported by the German Research Foundation (DFG; GS, grant number SCHO-1337/4-2; SiS, grant number SCHM-2683/4-2). The DFG did not have any role in study development, analysis, or interpretation of the data. The funding body was not involved in writing this report nor the decision to submit it for publication.

Funding

Open Access funding enabled and organized by Projekt DEAL.

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization, ST and HoM.; methodology, ST, SaS, TG, and LJP.; software, ST; validation, ST, SaS, TG, TM, and HoM; formal analysis, ST, SaS, and TG; investigation, ST, SaS, TG, and LJP; resources, ST, SaS, TG, and LJP; data curation, ST, SaS, TG, and LJP; writing—original draft, ST; writing—review and editing, TM, HoM, LJP, GS, and SiS; visualization, ST; supervision, ST, TG, and HoM; supervision, ST, HoM, GS, and SiS; project administration, ST, HoM, GS, and SiS; funding acquisition, GS and SiS. All authors have read and approved the final version of the manuscript.

Corresponding author

Correspondence to S. Tomczyk.

Ethics declarations

Conflict of interests

All authors declare that they have no conflicts of interest.

Ethical standards

Not applicable.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Tomczyk, S., Schlick, S., Gansler, T. et al. Continuum beliefs of mental illness: a systematic review of measures. Soc Psychiatry Psychiatr Epidemiol (2022). https://doi.org/10.1007/s00127-022-02345-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00127-022-02345-4

Keywords

  • Mental health
  • Public health
  • Systematic review
  • Stereotyping
  • Continuum
  • Assessment