Mental Health and/or Mental Illness: A Scoping Review of the Evidence and Implications of the Dual-Continua Model of Mental Health

Publications

Share / Export Citation / Email / Print / Text size:

Evidence Base

Australia and New Zealand School of Government

Subject: Management

GET ALERTS

eISSN: 1838-9422

DESCRIPTION

234
Reader(s)
771
Visit(s)
0
Comment(s)
0
Share(s)

SEARCH WITHIN CONTENT

FIND ARTICLE

Volume / Issue / page

Related articles

VOLUME 2020 , ISSUE 1 (Mar 2020) > List of articles

  • |

Mental Health and/or Mental Illness: A Scoping Review of the Evidence and Implications of the Dual-Continua Model of Mental Health

Matthew Iasiello * / Joep van Agteren / Eimear Muir Cochrane

Citation Information : Evidence Base. Volume 2020, Issue 1, Pages 1-45, DOI: https://doi.org/10.21307/eb-2020-001

License : (CC-BY-NC-ND 4.0)

Published Online: 18-March-2020

ARTICLE

ABSTRACT

The dual-continua model of mental health suggests that mental illness and positive mental health reflect distinct continua, rather than the extreme ends of a single spectrum. The aim of this review was to scope the literature surrounding the dual-continua model of mental health, to summarise the evidence, highlight the areas of focus for individual studies and discuss the wider implications of the model. A search was conducted in PsycINFO (n = 233), PsycARTICLES (n = 25), Scopus (n = 137) and PubMed (n = 47), after which a snowballing approach was used to scope the remaining literature. The current scoping review identified 83 peer-reviewed empirical articles, including cross-sectional, longitudinal and intervention studies, which found overall support for superior explanatory power of dual-continua models of mental health over the traditional bipolar model. These studies were performed in clinical and non-clinical populations, over the entire life-course and in Western and non-Western populations. This review summarised the evidence suggesting that positive mental health and mental illness are two distinct but interrelated domains of mental health; each having shared and unique predictors, influencing each other via complex interrelationships. The results presented here have implications for policy, practice and research for mental health assessment, intervention design, and mental health care design and reform.

Eaton (1951) proposed that mental health ‘merges imperceptibly and gradually like the colours of the spectrum into mental illness’ (as cited by Herron and Trent, 2000). This description illustrates a bipolar relationship between mental health and mental illness; a relationship and assumption that underpins clinical psychology and mental health care design (Keyes, 2005). The bipolar model implies that mental health and mental illness reflect opposite ends of the same continuum, where an individual ‘moves’ along the continuum, away from mental illness and towards mental health (Trent, 1992). In this model, individuals are either mentally ill or presumed mentally healthy (Keyes, 2005). As the aetiology and treatment of mental illness were researched and progressed faster than that of mental health, the existence of mental health became virtually synonymous with the absence of mental illness. As such, clinical psychology and psychiatry have primarily focused on the reduction of mental illness symptoms or psychopathology in order to improve mental health.

While pervasive, the model is considered an untested assumption, and the philosophical validity of the model has been widely criticised. For instance, many have disparaged the arbitrary point on the continuum where illness transitions to health, the sex and cultural differences that influence this arbitrary point, the impossibility of ‘gaining’ mental health (if it is defined as the absence/loss of illness), and the futility of improving mental health whilst being diagnosed with a mental illness (Herron and Trent, 2000). Criticisms and rejection of the bipolar model in the context of mental health were documented as early as 1958 by Marie Jahoda (Jahoda, 1958) who argued that the absence of disorder constituted an insufficient criterion for mental health. Jahoda outlined six dimensions of positive mental health, which would later be operationalised via Carol Ryff’s work on psychological wellbeing: autonomy, environmental mastery, personal growth, positive relations with others, purpose in life, and self-actualisation (Ryff, 1989). In combination with Ed Diener’s (1984) research into subjective wellbeing, Ryff’s seminal work brought the study of positive mental health into mainstream social science (Keyes, 2013).

Drawing on the work of humanistic psychologists such as Rogers and Maslow, the emergence of positive psychology in the 2000’s formalised the paradigm shift toward the promotion of mental health as something separate to mental illness. Mental health or positive mental health is since defined as the experience of positive feelings or subjective wellbeing and functioning fully or optimally (Huppert, 2005), encompassing individual resources such as life satisfaction (Diener, 1984), positive emotions (Fredrickson, 2001), meaning and purpose in life (Steger et al., 2006), resilience (Bonanno, 2004), character strengths (Peterson and Seligman, 2004), and interpersonal relationships (Reis and Gable, 2003). While positive psychology has brought more attention to the importance of positive mental health, the main body of work did not focus on the relationship between mental illness and mental health, and has largely been conducted in isolation from mental illness (Payton, 2009).

Dual-continua or dual-factor models of mental health have been proposed by various authors as an alternative to the bipolar model, postulating that mental illness and positive mental health reflect distinct continua rather than the extreme ends of a single spectrum; see Figure 1 for a schematic on both models (Jahoda, 1958; Keyes and Lopez, 2002; Suldo and Shaffer, 2008; Epp, 1988; Massé et al., 1998; Greenspoon and Saklofske, 2001). In the dual-continua model, mental health and mental illness are considered related but distinct constructs, and individuals can experience high levels of positive mental health even with the diagnosis of a mental illness (Keyes, 2005).

Figure 1:

Diagrammatic representation of the bipolar (a) and dual-continua (b) models of mental health.

10.21307_eb-2020-001-f001.jpg

A useful analogy for the dual-factor model can be found in the relationship between positive and negative affect. Positive and negative affect were initially assumed bipolar opposites of each other. In-depth statistical analysis of scores on positive and negative affect measures however resulted in the finding that positive and negative affect are in fact independent of each other, despite their ‘logical’ bipolarity (Bradburn, 1969; Nowlis, 1965; Feldman Barrett and Russell, 1998). Similar to the discourse on positive and negative affect, recent and emerging research indicates that high levels of positive mental health assets are possible despite psychopathology and mental illness diagnosis (Goodman et al., 2018), and positive mental health can be built in those with a diagnosed mental illness (Fava et al., 1998; Seligman et al., 2006). A neural precedent of the dual-continua model has been discovered, and evidence suggests that positive emotions are mediated by separate neural processes to negative emotions, and likely serve distinct evolutionary functions (Davidson, 2000; Fredrickson, 2001).

It has been proposed that widespread and systematic adoption of the dual-continua model would inspire significant reform to the mental health care system, which may better prepare systems for the overwhelming burden of mental illness (Vigo et al., 2016). Herron and Trent (2000) interrogated the dual-continua model from a range of philosophical approaches, and concluded that it had five key implications:

  1. It allows a concept (mental health or mental illness) to be described which is independent of other concepts, and so can be tested and measured independently;

  2. It allows an individual to be mentally healthy and mentally ill at the same time, and thus facilitates the creation of groups that are impossible under bipolar models;

  3. It allows an individual to disclose information about mental health while holding confidential information about mental illness;

  4. It provides new avenues for proactive rather than reactive system design in mental health promotion; and

  5. It is less reliant on labour-intensive downstream interventions and therefore can be more widely applied.

Despite these apparently significant implications to our mental healthcare system and its patients, the validity of the dual-continua model has been questioned by some. For instance, Huppert (2014) argued that while it may be possible to periodically experience flourishing in some mental illnesses such as schizophrenia or personality disorder, it is hard to imagine that an individual with severe depression or anxiety (or common mental disorder) is capable of flourishing. In light of the implications stated by Herron and Trent (2000), the question therefore remains whether the dual-factor model has higher utility and explanatory power compared to bipolar models in general, across different mental illnesses and within different contexts and settings.

This review was designed to scope the scientific literature investigating the validity of the dual-continua model of mental health. This review will summarise the evidence of the model, determine the main focus areas in the literature, and collate the implications of the included studies, with the aim of informing policy, practice and future research.

Methods

This scoping review was designed to identify peer-reviewed scientific articles which specifically tested mental health and mental illness as two distinct constructs and was based on the Joanna Briggs Institute methodology (JBI, 2015). As noted by Payton (2009), terminology and nomenclature remains an impasse to progress in the field of mental health research. Mental health, mental illness, distress and wellbeing are often used interchangeably. Similarly, various names for dual-continua models have been proposed, including the dual-factor model, two-factor, two-continua, the complete state model, and complete mental health. Due to this non-specific and imprecise taxonomy, it was determined that a snowballing approach was the most appropriate way to search the literature, first beginning with the studies that specifically mention dual-continua or dual factor model of mental health and then using reference list screening to effectively scope additional literature. For ease of reading, the current review uses the term ‘dual-continua model’ to describe the models.

A search was conducted in February 2019 of four scientific databases (Pubmed, PyscINFO, PsycARTICLES, and Scopus). The search strategy included all known variations of the dual-continua model (dual-continua, dual-continuum, dual-factor, two-continua, two-continuum, two-factor, and complete state) AND ‘model’ AND ‘mental health’. Inclusion criteria included: (1) title, abstract, or keywords explicitly mention or implicitly refer to the dual-continua model of mental health, (2) the studies utilized an empirical study design, and (3) the study was published in a refereed journal in the English language. Two reviewers independently screened titles and abstracts, to determine preliminary inclusion status before conducting a full-text screen. Inter-rater reliability was calculated using SPSS v25 (k = 0.88).

Data extracted included: Author, year of publication, aim of the study, study methodology, sample size, geographical location of participants, sex, age, types of participants, measurement tools used for mental illness and positive mental health, correlations between measurements (if available), key study results relevant to the dual-continua model, and implications of the results.

Data analysis was conducted in a two-stage process, first, extracted data were organised into groups based on either methodological or thematic similarity (for research on the validity of the model and implications of the model respectively). The extracted data were then interpreted and analysed narratively.

Results

Search flow

The search terms across the four databases resulted in 477 articles; PsycINFO (n = 233), PsycARTICLES (n = 25), Scopus (n = 137), PubMed (n = 47). After deduplication, 395 original articles were identified. The most common reason for exclusion during the title and abstract screen was no clear reference to a dual-continua model, despite referencing both positive mental health and mental illness. The comprehensive description of the screening process is displayed in the PRISMA statement, which resulted in 83 original articles to be included in the review (Figure 2; Moher et al., 2009). The characteristics of all included studies can be found in Table A1.

Figure 2:

PRISMA flowchart of the study selection process.

10.21307_eb-2020-001-f002.jpg

Design of included studies

The large majority of studies used an observational design (n = 81). Sixty-six studies used a cross-sectional study design using data stemming from large population-level datasets or using data that was gathered prospectively by the researchers. Sixteen studies used a longitudinal observational design, with follow-up ranging between one year and ten years. One study used a mixed-methods design, while only two studies used an experimental intervention design.

Countries

Most studies were conducted in the United States of America (n = 31), Netherlands (n = 12), Australia (n = 7), United Kingdom (n = 7), Canada (n = 6), China (n = 3), Germany (n = 3), South Korea (n = 2), Russia (n = 2), Italy (n = 2), and Poland (n = 2). Other countries included Spain, Argentina, South Africa, Greece, Sweden, Singapore, Portugal, Turkey, and Serbia.

Study samples and participant characteristics

The study samples consisted of adults (n = 55), youth (n = 23) or both (n = 5). Overall, most studies recruited slightly higher percentage of females (between 50% to 70%). Sample sizes varied between 0-100 (n = 3), 101-500 (n = 21), 501-1000 (n = 12), 1000-5000 (n = 23) and 5000+ (n = 15). Studies were conducted in populations over the life course, with mean ages ranging from 10.5 for the youngest population to 70.3 for the oldest population.

Most study participants were recruited from the general non-clinical population. Thirteen studies targeted participants with a (history of) mental illness, specifically affective disorders (n = 6), substance use disorder (n = 1), suicide ideation (n = 2), post-traumatic stress disorder (n = 1), eating disorders (n = 1), or a combination of mental disorders (n = 2). One study looked at the application of a dual-continua model in participants with various physical illnesses.

Elementary and high school students were used in all but two studies (89%) that focused on application of dual-factor models in youth. In contrast, only nine adult-focused studies (18%) used student samples. Other populations that were specifically targeted in the recruitment included carers (n = 3), older adults (n = 1), the LGBTQI community (n = 2), immigrants (n = 1), siblings of those with a chronic illness or disability (n = 1) and medical interns (n = 1).

Measures used

Measurement of positive mental health or flourishing was most commonly conducted using the Satisfaction with Life Scale (n = 21) or the Mental Health Continuum – Short Form (MHC-SF) (n = 23), administered in a range of languages including English, Dutch, Setswana, Polish, Korean, Spanish, Portuguese, and Italian. Five studies combined the use of Bradburn’s Positive Affect Balance (Bradburn, 1969), Ryff’s Psychological Wellbeing Scales (Ryff and Keyes, 1995), and Keyes Social Wellbeing Scales (Keyes, 1998) to determine the level of positive mental health, which are the same scales that the MHC-SF is based on.

Other commonly used measures included Positive and Negative Affect Schedule for adults or children (n = 21), Psychological Wellbeing scale (n = 12), Student’s Life Satisfaction Scale (n = 10), Bradburn’s Affect Balance Scale (n = 7), Social Wellbeing Scale (n = 7), the full or brief Multidimensional student’s life satisfaction scale (n = 5), and Positive Mental health Scale (n = 4).

Mental illness or symptoms of mental illness was most commonly measured using validated scales assessing affective disorders (depression and anxiety), via the Center for Epidemiologic Studies Depression Scale (CES-D) (n = 11), Kessler psychological distress scale (n = 1), Patient Health Questionnaire (PHQ) (n = 3), Depression Anxiety Stress Scale (DASS-21) (n = 6), Generalized Anxiety Disorder Scale (GAD) (n = 3), Beck Depression Inventory (BDI) (n = 2). Several studies screened for minor or non-psychiatric disorders via the GHQ (n = 10), or general psychopathology via the Symptom Check List-90 (SCL-90) (n = 2) and Brief Symptom Inventory (BSI) (n = 6). Other studies relied on clinical interview diagnosis, using the Composite International Diagnostic Interview (WHO-CIDI) (n = 9) or structured interviews using DSM or ICD10 criteria (n = 2). A range of studies in the youth context, used scales that measure behavioural or emotional problems, or problems with coping, as their proxy to mental illness, for instance the Behavioural Assessment System for Children (BASC), the Youth Self Report form of the child behaviour checklist, the Reynolds adolescent adjustment screening inventory (RAASI), or the Self-Report Coping Scale (SRCS).

Few studies used unvalidated measures of positive mental health or mental illness, which limited the interpretability of their results. For example, some studies (n = 4) used “positive items” of measures that are normally used to measure mental illness, such as the General health Questionnaire (GHQ). Less commonly used scales, including single-item scales can be found in Table A1.

Focus areas of studies

The main focus areas of included studies have been collated and summarised below. The specific aims and results of each individual study are available in Table A1.

Investigation of the dual-continua model fit

Reflecting the central aim of this review, the majority of included studies focused on whether the relationship between positive mental health and mental illness reflect a single bipolar continuum or a dual-continua. This was most commonly performed using Confirmatory Factor Analysis; a statistical technique to test the adequacy of a theorised model to represent the data. Three models were commonly tested, single axis (or bipolar), two orthogonal factors (independent and distinct factors), and two oblique factors (independent and related factors), displayed in Figure 3. It was consistently found that the data best fit the two-factor oblique model, indicating that positive mental health and mental illness represent two separate constructs which share a degree of overlap (Magalhaes and Calheiros, 2017; Massé et al., 1998; Winzer et al., 2014; Kim et al., 2014; Keyes, 2005).

Figure 3:

The three commonly tested models in Confirmatory Factor Analysis used to test the best model fit for the data: Single axis, which would indicate the bipolar model (a), two orthogonal factors, independent and distinct (b), and two oblique factors, independent and related (c). PMH = Positive mental health, MI = mental illness, MH = mental health. Circles indicate latent constructs, and boxes indicate survey items.

10.21307_eb-2020-001-f003.jpg

The analysis was usually performed in the context of measurement tool validation, in particular validating the MHC-SF (Lim, 2014; Lamers et al., 2011; Petrillo et al., 2015; Lupano Perugini et al., 2017; Karas et al., 2014; Keyes et al., 2008), with other studies investigating the MHI (Heubeck and Neill, 2000; Veit and Ware, 1983), or the potential appropriateness of using the GHQ to capture positive mental health and mental illness (Hu et al., 2007).

Validating sub-groups within dual-continua model

A second focus area of the included studies was to determine whether participant responses on positive mental health and mental illness measures could lead to the identification of distinct groups within the dual-continua model. Many studies divided their participants into four groups: ‘Complete mental health’ (no mental illness, high positive mental health), ‘Vulnerable’ (low mental illness, low positive mental health), ‘Symptomatic but content’ (high mental illness, high mental health), and ‘Struggling’ (high mental illness, low mental health), displayed in Figure 4. The exact descriptors of each group used in the included studies varied, often depending on the theoretical background preferred by the authors (Keyes, 2005; Suldo and Shaffer, 2008; Greenspoon and Saklofske, 2001). For ease of reading, we will use Keyes’ terminology throughout the current review and attached appendices. The apparent validity of these sub-groups was often tested by contrasting sub-group performance on a range of psychological, behavioural, or physical outcomes.

Figure 4:

Sub-groups of mental health, as postulated by dual-factor models. Keyes’ (Keyes, 2005) terminology to describe the groups is used in throughout this paper to highlight the four mental health groups: ‘Complete Mental Health’ (no mental illness, high positive mental health), ‘Vulnerable’ (no mental illness, low positive mental health), ‘Symptomatic but content’ (mental illness, high positive mental health), and Struggling (mental illness, low positive mental health).

10.21307_eb-2020-001-f004.jpg

Expanding on this were a small number of longitudinal studies that focused on the stability of group members over time, with the aim of determining whether: (1) current levels of positive mental health influence future scores of measures of mental illness, (2) change in levels of positive mental health influence future scores of measure of mental illness, and (3) whether specific sub-groups are more transient or stable than others (Xiong et al., 2017; Kelly et al., 2012; Lamers et al., 2015; Wood and Joseph, 2010; Grant et al., 2013).

Differential predictors of mental illness and positive mental health and correlations with other key outcomes

A third area of focus of included studies was to determine whether positive mental health and mental illness were associated with different predictors and variables, and whether they were associated with positive or negative outcomes. This was often performed for two reasons, either to establish whether positive mental health and mental illness are predicted by different factors (supporting the claim that they are distinct constructs), or to assess whether measures of mental illness or mental health were differentially associated with other psychological or behavioural resources or outcomes (to maximise explanatory power of measurement tools). Examples of specific resources or outcomes that where studied included curiosity (Jovanovic and Brdaric, 2012), personality (Lyons et al., 2013; Spinhoven et al., 2015; Lamers et al., 2012), self-efficacy (Schonfeld et al., 2016), health-risk behaviour (Venning et al., 2013), genetics (Bartels et al., 2013), risk of cardiovascular disease (Keyes, 2004), coping (Kinderman et al., 2015), positive psychology constructs, and general socio-demographic variables (Westerhof, 2013; Weich et al., 2011; Westerhof and Keyes, 2010; Huppert and Whittington, 2003).

Studies including youth, high school and university students focused on determining the differential associations between mental illness, positive mental health, and educational, behavioural, and developmental outcomes (Rose et al., 2017; Suldo and Shaffer, 2008; Suldo et al., 2016; Lyons et al., 2013; Antaramian, 2011; Magalhaes and Calheiros, 2017; Renshaw and Cohen, 2014; Eklund et al., 2011). Examples of these outcomes included grade point average, suspension rates, social adjustment, self-efficacy beliefs, identity development, social support, and school bonding.

The association with predictors and outcomes was also studied in a range of specific and at-risk populations such as carers (Pruchno et al., 1996; Smith, 1996), older adults (Jiang and Lu, 2018), chronically ill people and their siblings (Hallion et al., 2018; Fontana et al., 1980), LBGT community (Peter, 2018; Bariola et al., 2017), migrants (du Plooy et al., 2018), minority populations (Rose et al., 2017), and for specific mental illness diagnoses (Baiden and Fuller-Thomson, 2016; Seow et al., 2016; Fuller-Thomson et al., 2016; Spinhoven et al., 2015; Van Erp Taalman Kip and Hutschemaekers, 2018; Franken et al., 2018; Diaz et al., 2017; Teismann et al., 2018).

Impact of interventions

A final area of focus was to determine the effect of interventions on measures of mental illness and positive mental health, in the context of the dual-continua model. Bohlmeijer et al. (2015) assessed the efficacy of ACT on flourishing in depressed participants and showed that it was possible to improve the level of positive mental health in those with a mental illness. Trompetter et al. (2017) investigated the differential impact of Acceptance and Commitment Therapy (ACT) on positive mental health and mental illness for patients who were being treated for anxiety and depression. This statistical approach revealed that 64% of the participants improved on either positive mental health or anxiety symptoms post-intervention and 72% improved in either depressive symptoms or positive mental health.

Implications of the dual-continua model

The implications of the dual-continua model were often explicitly discussed in the studies included in this review. The implications extracted from each study are available in Table A1 and were narratively categorised into three broad themes. The first theme of implications involves the measurement approaches to determine mental health and mental illness status, and whether assessment of mental health should include measures of both positive mental health and mental illness. The second theme related to intervention design, delivery, and implementation. This was discussed in the context of treatment and prevention of mental illness, as well as the promotion of positive mental health. The final theme of implications of the dual-continua model centred on the opportunities that the model presents to mental health care reform. This discourse included a re-orientation from deficit- or illness-focused services to strength-focused ones, re-conceptualising how mental health is portrayed to reduce stigma of illness, and the inclusion of services specifically focused on improving positive mental health as an early intervention or preventative approach.

Discussion

This scoping review identified a considerable body of empirical research investigating the validity of the dual-continua model, and the overarching notion that positive mental health and mental illness represent two distinct, yet related, constructs.

Evidence supporting the dual-continua model

The evidence found by the majority of the included 83 studies supports the existence of the dual-continua model. A large proportion of studies used CFA to compare whether the data best fit a bipolar model or the two variations of the dual-continua model (where mental illness and positive mental health are either independent of each other or share a degree of overlap; Figure 2). Studies consistently found that the data best fit the ‘two oblique factor’ model, indicating that mental illness and positive mental health are distinct but related. This finding was replicated across cultures, sex, age, and using different measures of positive mental health and mental illness, thereby supporting the general validity of the dual-continua model (Franken et al., 2018; Petrillo et al., 2015; Keyes et al., 2008).

Another common approach to test the validity of the dual-continua model was to analyse whether various drivers, predictors, or outcomes related similarly to mental illness and positive mental health. This was often done by splitting participants into sub-groups (Figure 4). This approach was used to indicate that the sub-groups existed, and that it was possible for individuals to report high levels of positive mental health despite mental illness. The existence of these sub-groups was validated by the consistent finding that the groups performed differently across a broad range of psychological and behavioural resources and outcomes. Other studies adopted a more rigorous approach and investigated the predictors that were associated with mental illness and positive mental health using regression analysis. This was best exemplified by Kinderman et al. (2015) who showed that different individual and social factors differentially influence positive mental health and mental illness.

Most of this research was cross-sectional, supported by a smaller number of longitudinal studies. Findings consistently demonstrated that positive mental health and mental illness differentially predict various outcomes (Du Plooy et al., 2018; Kinderman et al., 2015). In general, it was found that the absence of illness was not sufficient to predict various desirable outcomes such as academic achievement and interpersonal relationship quality, which were predicted by high levels of or improvements in positive mental health (Suldo and Shaffer, 2008). The fact that mental illness and positive mental health predict or explain different outcomes was a strong indication that the constructs are distinct, and the fact that there was some overlap points to the constructs sharing some degree of overlap.

Generalisability of the evidence

There was a great degree of variety in the methodology of the studies included in this review, indicating a considerable degree of confidence in the generalisability of the support of the dual-continua model. The studies were conducted in twenty Western and non-Western countries, indicating that the evidence presented is not culturally specific. The most common method of participant sampling was through population-level survey data, producing nationally representative data which has low risk of sampling bias (Banerjee and Chaudhury, 2010). Although this approach ensures appropriate representation across sex and age, there is a possible underrepresentation of groups that are usually excluded from population-level surveys, for instance the most elderly, homeless people, and mental health inpatients. The evidence provided by studies using population-level surveys was supported by a range of studies that specifically recruited minority and at-risk groups, as well as participants with various degrees of mental illness, increasing confidence in the generalisability of the results across societies.

Studies relied on a broad spectrum of validated measurement tools, reducing potential bias introduced by using a specific measurement tool (Egloff, 1998). Mental illness was measured using validated self-report tools designed to measure various disorders continuously, including depression, anxiety, and general psychopathology. Studies using these measures were complemented by research that relied on assessment using clinical interviews (e.g. using CIDI or based on DSM-IV criteria), instilling a high degree of confidence that the dual-factor model is not merely a statistical phenomenon of a particular measurement design.

Similarly, positive mental health assessment relied on assessment using a number of validated measures, targeting different constructs ranging from satisfaction with life and positive affect, to overall flourishing, social wellbeing and psychological well-being. Many articles included in this review were validation papers of the MHC-SF, consistently finding good internal consistency and validity. Unlike all other continuous measures of positive mental health, the MHC-SF is particular because it can be used to either measure positive mental health continuously or to categorically ‘diagnose’ flourishing similar to the DSM-V protocol. Generally, the continuous approach was used in confirmatory factor analysis, while the categorical approach was used to create sub-groups and analyse group differences. Renshaw et al. (2016) compared the categorical and continuous approaches, albeit using measures other than the MHC-SF, and found that each approach resulted in conflicting interpretations. This implies that the method used to investigate the single- versus dual-continua models can influence assessment results in practice. While categorical assessment may be criticised for a lack of discriminative power (Doll, 2008), it is closest to the current way that individual mental illness assessment and population-based screening work in practice, thereby supporting the applicability of its use in practice.

Generalisability across mental illness

High levels of positive mental health assets are attainable in individuals diagnosed with a mental illness, demonstrated across major depressive disorder, bipolar disorder, social anxiety, schizophrenia, and trauma-related disorders (Goodman et al., 2018). Of the studies included in the current review, the dual-continua model was investigated across a range of mental illnesses and related concepts, including participants experiencing suicidal ideation, general psychopathology and psychological distress, depression, anxiety, stress, trauma, loneliness, and eating disorders. Of the studies that focused on recruiting patients with a mental illness, as opposed to using general populations, the large majority supported the validity of the dual-continua model, particularly when looking at patients with mild to moderate mental illness.

Results for populations of patients with severe to extremely severe mental illness are less convincing. Van Erp Taalman Kip and Hutschemaekers (2018) found that mental illness and positive mental health were highly negatively correlated (r = −0.071) in severely mentally ill populations, with positive mental health contributing significantly less to a two-factor model compared to the symptoms of mental illness. Other research found high correlations between mental illness and mental health in mentally ill, particularly in depressed patients (Bartels et al., 2013), and supported the researchers finding differential levels of positive mental health depending on mental illness diagnosis, e.g. depression versus anxiety (Seow et al., 2016; Franken et al., 2018). The study by Van Erp Taalman Kip and Hutschemaekers (2018) was the sole study identified in this review that contradicted the dual-continua model. These results imply that in extremely severe psychopathology, particularly in depression, positive mental health constructs may be highly correlated with mental illness symptoms and patients may exhibit difficulty distinguishing mental illness symptoms from symptoms of positive mental health. There is evidence to suggest that the precision of positive mental health measures may change across the range of scores, and this may also be true for the level of psychopathology (Abbott et al., 2010).

The notion that it is possible to have a high level of positive mental health and common mental illness at the same time has been contested in the literature. Huppert (2005) argued that it was difficult to imagine a situation where an individual diagnosed with severe depression is able to function well psychologically. We suggest that this criticism is influenced by the ‘observational window’ and measurement approaches considered, or in other ways we measure both outcomes. Asking someone to judge their positive mental health and mood symptoms in the moment, or asking them to reflect back over their mood and positive mental health over a longer period, will lead to different subjective interpretations. Similarly, using measures that consist of a large number of the same items, as is the case for depression measures, will lead to large overlap. For example, ratings on a meaningful life are often asked in wellbeing questionnaires, whereas ratings on life being meaningless are often included in depression measures. Feldman Barrett and Russell (1998) recommended that such ‘bipolar antonyms’ can be misleading in analysis of independence or bipolarity, and can be avoided by ensuring that measurement tools include items that adequately represent the breadth of each construct. In this context, this would include measuring a diverse range of psychological illness constructs, as well as a range of psychological well-being constructs.

Massé et al. (1998) provided an example of this approach, albeit with constructs that are no longer considered central to either positive mental health or mental illness. This study used CFA to test the model fit of mental health as a second order structure, underpinned by the distinct but related latent factors of positive mental health and mental illness. As visible in Figure 5, they included a range of constructs under positive mental health and mental illness, some of which relate to both positive mental health and mental illness. Following the depression example, if only happiness and anhedonia were used as indicative measures of positive mental health and mental illness, then a bipolar model would become easily apparent. However, using a broader, multifaceted approach to positive mental health (e.g. using the MHC-SF) and mental illness (e.g. using the BSI), the dual-continua model would emerge as a more appropriate fit of the data.

Figure 5:

Higher order theoretical relationship between mental illness (distress) and positive mental health (wellbeing), adapted from the model presented in Massé et al. (Massé et al., 1998). PMH = Positive mental health, MI = mental illness, MH = mental health. Circles indicate latent constructs, and boxes indicate survey items.

10.21307_eb-2020-001-f005.jpg

Overall, there is sufficient evidence to support the validity of the dual-continua model of mental health. Longitudinal and cross-sectional data from around the world indicates that positive mental health and mental illness reflect two distinct, yet related phenomena. The validity of the dual-continua model may however be relative to the window of time and the definitions and assessment methods of positive mental health and mental illness. In particular, more work should be conducted to investigate whether the dual-continua is appropriate in severe forms of psychological distress or mental illness.

Implications of the dual-continua model for policy, practice, and research

The validity of the dual-continua model has important implication for policy, practice, and research and the current scoping review extracted the implications discussed by the authors of included studies. Across the eighty-three publications, the implications were relatively convergent and overlapping, and were collected into three broad themes; implications for mental health measurement and assessment, mental health treatment and intervention design, and mental health care system reform.

Mental health assessment

Study authors strongly advocated to assess positive mental health and mental illness together, rather than using only one or the other. There was a consensus, based on their research results, that a focus on either positive mental health or mental illness alone would not provide a complete image of the mental health status of an individual or population. It is well established in positive psychology that the absence of mental illness does guarantee optimal mental health (Slade, 2010). The dual-continua model would equally suggest that high levels of positive mental health do not guarantee the absence of mental illness. Studies found up to 36% of participants who displayed high levels of positive mental health with symptoms of mental illness (Venning et al., 2013).

At a population level, the inclusion of positive mental health measures with existing indicators of mental illness enables researchers to understand the economic, social, and individual drivers of both positive mental health and mental illness. It was shown that these drivers are not necessarily the same, although there is some overlap (Kinderman et al., 2015). This degree of insight is not available in most population-level research, as positive mental health measures are often not included.

At the individual level it enables professionals in various settings to identify previously invisible sub-groups. For example, research in schools commonly constructed the four sub-groups (‘Complete Mental Health’, ‘Vulnerable’, ‘Symptomatic but content’ and Struggling’ groups) and would continue to assess group-membership on educational, behavioural, cognitive and emotional outcomes. Across the studies, participants in the ‘Complete Mental Health’ group outperformed the other groups, while the ‘Vulnerable’ group scored significantly worse than those with Complete Mental health, being consistently associated with poor performance across the studies (Suldo and Shaffer, 2008; Renshaw and Cohen, 2014; Antaramian, 2015). In traditional assessment (mental illness only), the ‘Vulnerable’ and ‘Complete mental health’ group would have been combined as a ‘no mental illness’ category, despite the fact that these two groups show different performance on a range of education, behavioural, cognitive, and emotional outcomes.

One of the most striking examples of the importance of capturing the sub-groups, and thereby identifying at-risk individuals, comes from studies that investigated the role of positive mental health as a predictor of mental illness risk. Keyes et al. (2010) conducted a longitudinal study of mentally healthy participants (without a diagnosis of mental illness) of the 1995 and 2005 waves of the Midlife in the United States (MIDUS) National Study of Health and Well-being. The study showed that participants who gained or maintained high levels of positive mental health over the 10-year period had a decreased risk of developing a mental illness (being depression, anxiety, and panic disorder), and that participants whose positive mental health declined or remained low had significantly increased risk of developing mental illness. Similar results were observed by Wood and Joseph (2010), who found that people with low levels of positive mental health were several times more likely to be depressed 10 years later. Grant et al. (2013) and Lamers et al. (2015) supported these findings, finding that low levels of positive mental health predicted risk of higher depressive symptoms within one year. There is also evidence to suggest that high levels or increased levels of positive mental health dramatically improve the likelihood of recovering from a mental illness (Iasiello et al., 2019).

Positive mental health and mental illness need to be assessed together when trying to establish a picture of an individual’s or population mental health status. This must be done using measurement tools specifically designed to capture either construct in a representative manner; as simply using positive items of mental illness questionnaires is not a valid measurement approach (Winzer et al., 2014). Failing to use fit-for-use measurement tools for both mental health and mental illness when performing mental health assessments will lead to suboptimal explanatory power of drivers and outcomes, and does not allow for the identification of key at-risk groups.

Intervention design and evaluation

A second key theme of implications relates to mental health intervention design, with the recurring finding that interventions that improve positive mental health and reduce mental illness can be complementary but different (Kinderman et al., 2015). Further, it was found that a positive response in one continua does not exclude, nor guarantee a positive response in the other. Instead, interventions and mental health promotion programs will benefit from targeting both the reduction of illness symptoms and improvement of positive mental health.

The efficacy of mental health interventions is generally evaluated using average change in positive mental health or mental illness of the entire group. However, research using the dual-continua model suggested that while an intervention may improve overall positive mental health and reduce mental illness on average, more complex interactions may be occurring at the individual level. In particular, Trompetter et al. (2017) re-evaluated a randomized controlled trial of an ACT intervention that measured dimensions of both mental illness and positive mental health (n = 250). While this RCT revealed average improvements in positive mental health and reductions in mental illness at the group level, using reliable change analysis it was found that the majority of individuals improved in either mental illness or positive mental health. The traditional bipolar model would suggest that an improvement in positive mental health and a reduction in mental illness signify the same outcome. Instead, through the dual-continua model, when an intervention focuses on or can address both positive mental health and mental illness, a failure to see an effect in either outcome does not mean that the intervention did not have a positive effect for the participants.

The authors commented on the utility of ACT in relation to the dual-continua model, as it is a commonly used treatment paradigm that can be used to reduce psychopathological vulnerabilities and build resources for improving positive mental health. Other clinical interventions have been designed to improve the wellbeing of individuals with psychopathology including Wellbeing Therapy (Fava et al., 1998) and Positive Psychotherapy (Seligman et al., 2006), which all fall under the larger umbrella of Positive Clinical Psychology (Wood and Tarrier, 2010). Using traditional clinical techniques such as cognitive restructuring, scheduling of activities, assertiveness training, and problem solving, these interventions aim to improve positive mental health assets such as Ryff’s domains of psychological wellbeing (Fava et al., 1998; Duckworth et al., 2005), while also treating mental illness. These interventions and treatment paradigms have implicitly or explicitly adopted the dual-continua model, by designing program components that improve wellbeing, despite the client’s diagnosis of mental illness.

Greater sophistication should be employed to understand which individuals might benefit most from interventions specifically designed to improve positive mental health and reduce mental illness, whether delivered simultaneously or consecutively (Schueller, 2014). An example of this sophistication comes from Jans-Beken et al. (2017) who investigated the dual-continua model in a longitudinal study of gratitude, psychopathology, and subjective wellbeing. This study found that practicing gratitude may positively impact an individual’s future level of positive mental health and psychopathology, but is less likely to ameliorate symptoms of psychopathology when they are present. This indicates that interventions to improve traits such as gratitude should be carefully designed to consider the trait dynamics with both mental illness and mental health.

Adoption of the dual-continua model on intervention design has significant potential, especially when combined with the ability to identify at-risk subgroups. At the individual level this can inform better intervention design, while at the community and society level, it may allow governments to prioritise policies and create more targeted interventions. The evidence to drive this change does not just need to come from future studies; there is a substantial literature of randomised controlled trials which have measured both positive mental health and mental illness. Secondary analysis of these data using the aforementioned method proposed by Trompetter et al. (2017) would provide much needed insight into the efficacy of interventions through the dual-continua model lens, and will provide greater clarity for intervention design by identifying ‘for whom’ interventions are most effective.

Reform to the health care system

The final theme of implications of the dual-continua model of mental health is related to mental health care system reform, where a need to integrate and unify traditional psychotherapy and positive psychology was commonly advocated; a call that is not new (Wood and Tarrier, 2010), but certainly has not gained traction as of yet. Current approaches are deficit-focused and preference the reduction of mental illness symptoms, resulting in reactive health care (Herron and Trent, 2000). Hence, the specific inclusion of positive mental health initiatives into the health care system to complement current services was commonly cited as a much desired reform to the mental health care system. In addition to aforementioned changes in relation to measurement and intervention, two specific treatment approaches that could benefit from examining the evidence provided for dual-factor models are integrated care approaches and stepped-care approaches.

Integrated care strives to achieve optimal outcomes for patient, provider and system (Kodner and Spreeuwenberg, 2002); overlooking the important role that positive mental health plays would be detrimental to outcomes for integrated care, regardless of whether the main presenting symptoms are mental or physical. An important precedent for successful implementation of positive mental health into integrated mental health care has already been established through interventions such as Wellbeing Therapy and Positive Psychotherapy, and overarching fields such as positive clinical psychology and positive psychiatry (Jeste et al., 2015; Wood and Tarrier, 2010). These therapies have been designed to broaden the scope of traditional psychopathology with the central thesis that building positive mental health assets, in addition to treating symptoms, is effective and may engender more meaningful recovery and reduce the likelihood of relapse (Slade, 2009). Research found in this review indicated that individuals who have had severe depression or suicidal ideation can achieve complete mental health (Baiden and Fuller-Thomson, 2016), that positive assessments of wellbeing and strengths may transform how clients view themselves and their satisfaction with clinical assessment (Macaskill, 2012). Positive mental health assets such as character strengths may provide clinicians new resources to help individuals manage their illness (Macaskill and Denovan, 2014). The systemic neglect of functioning after depression is emerging in the literature (Rottenberg et al., 2018), and positive mental health and the dual-continua of mental health could facilitate the shift in recovery narrative (Slade, 2010).

In a stepped-care model of mental health care, prevention and health promotion precede self-guided help and low-resource intensive interventions, before clinical intervention is required. Longitudinal research identified in the current review indicated that positive mental health is an important resource to reduce the incidence of mental illness (and other physical illness) and therefore should be a primary focus of public policy and health promotion (Lamers et al., 2015; Keyes et al., 2010; Wood and Joseph, 2010; Schotanus-Dijkstra et al., 2017). This will subsequently or conjointly lead to improvements in other crucial areas such as health risk behaviour (Venning et al., 2013). An important key group that needs to be targeted, in both preventative and early intervention efforts are those who reside in the ‘Vulnerable’ group; this group is the most transient (Kelly et al., 2012; Xiong et al., 2017) and across studies associated with worse outcomes than participants with ‘Complete Mental Health’.

Limitations

Despite identifying a broad range of publications investigating the dual-continua model of mental health, our ability to effectively scope the literature was restricted by imprecise taxonomy and nomenclature that is pervasive throughout wellbeing and positive psychology literature (Salvador-Carulla et al., 2014; Dodge et al., 2012). This is an avoidable impasse, but will require consolidation, collaboration, and standardised use of language between positive mental health and mental illness researchers. The non-systematic snowballing method utilised to overcome this barrier may present a bias towards finding papers that support the dual-continua model. This was minimised by broad reference list screening, which did not return a single study that contradicted the validity of the dual-continua model. Another potential limitation was the use of English-only studies; however, this was likely mitigated by the inclusion of many studies conducted in non-Western and non-English speaking countries. Finally, assessment of research quality was not included in this scoping review, and poorly conducted research may have influenced the results. The bias may be offset by the inclusion of a wide range of study designs and overwhelming consistency of the findings.

Conclusion

There is a sufficient body of evidence to suggest that positive mental health and mental illness are not the opposite ends of the same continuum, and instead reflect two distinct yet related continua. The current review identified eighty-three publications, which were conducted in clinical and non-clinical populations, over the entire life-course and in Western and non-Western cultures. The review summarised the evidence that positive mental health and mental illness are two distinct but interrelated domains of mental health; each having shared and unique predictors, influencing each other via complex relationships. Further research should be conducted to understand whether the dual-continua model of mental health is valid in the most severe cases of mental illness, and the influence that particular measurement tools may have on the relationship between mental illness and mental health.

The authors of included studies strongly advocated for the adoption of the dual-continua model in policy, research, and practice. The main implications of the adoption of the dual-continua model were related to the inclusion of positive mental health measurement into mental health assessment, utilising interventions to improve positive mental health to promote mental health and prevent mental illness, and the addition of positive mental health measurement and intervention to complement the traditional approaches to inspire mental health care system reform.

Acknowledgements

This research was supported by the Australian and New Zealand School of Government.

Conflict of Interest

The authors declare no conflict of interest

Appendices

Appendix 1

Table A1.

Summary of reviewed literature extraction.

10.21307_eb-2020-001-t0A1.jpg10.21307_eb-2020-001-t0A2.jpg

References


  1. Abbott, R. A. , Ploubidis, G. B. , Huppert, F. A. , Kuh, D. and Croudace, T. J. 2010. An evaluation of the precision of measurement of Ryff’s psychological well-being scales in a population sample. Social Indicators Research 97: 357–373.
  2. Alterman, A. I. , Cacciola, J. S. , Ivey, M. A. , Coviello, D. M. , Lynch, K. G. , Dugosh, K. L. and Habing, B. 2010. Relationship of mental health and illness in substance abuse patients. Personality and Individual Differences 49(8): 880–884.
  3. Antaramian, S. 2015. Assessing psychological symptoms and well-being: application of a dual-factor mental health model to understand college student performance. Journal of Psychoeducational Assessment 33 (5): 419–429.
  4. Antaramian, S. P. 2011. A dual-factor model of mental health: understanding student engagement and school performance using a person-centered approach. Dissertation Abstracts International: Section B: The Sciences and Engineering 71: 5823.
  5. Antaramian, S. P. , Huebner, E. S. , Hills, K. J. and Valois, R. F. 2010. A dual-factor model of mental health: toward a more comprehensive understanding of youth functioning. American Journal of Orthopsychiatry 80 (4): 462–472.
  6. Baiden, P. and Fuller-Thomson, E. 2016. Factors associated with achieving complete mental health among individuals with lifetime suicidal ideation. Suicide and Life-Threatening Behavior 46 (4): 427–446.
  7. Banerjee, A. and Chaudhury, S. 2010. Statistics without tears: Populations and samples. Industrial Psychiatry Journal 19 (1): 60.
  8. Bariola, E. , Lyons, A. and Lucke, J. 2017. Flourishing among sexual minority individuals: Application of the dual continuum model of mental health in a sample of lesbians and gay men. Psychology of Sexual Orientation and Gender Diversity 4 (4): 43–53.
  9. Bartels, M. , Cacioppo, J. T. , Van Beijsterveldt, T. C. and Boomsma, D. I. 2013. Exploring the association between well-being and psychopathology in adolescents. Behavior Genetics 43 (3): 177–190.
  10. Bohlmeijer, E. T. , Lamers, S. M. and Fledderus, M. 2015. Flourishing in people with depressive symptomatology increases with Acceptance and Commitment Therapy. Post-hoc analyses of a randomized controlled trial. Behaviour Research and Therapy 65: 101–106.
  11. Bonanno, G. A. 2004. Loss, trauma, and human resilience: have we underestimated the human capacity to thrive after extremely aversive events? American Psychologist 59 (1): 20.
  12. Bradburn, N. M. 1969. The structure of psychological well-being.
  13. Davidson, R. J. 2000. Affective style, psychopathology, and resilience: brain mechanisms and plasticity. American Psychologist 55 (11): 1196.
  14. Diaz, D. , Stavraki, M. , Blanco, A. and Bajo, M. 2017. 11-m victims 3 years after madrid terrorist attacks: Looking for health beyond trauma. Journal of Happiness Studies: An Interdisciplinary Forum on Subjective Well-Being 19 (3): 663–675.
  15. Diener, E. 1984. Subjective well-being. Psychological Bulletin 95 (5): 542.
  16. Dodge, R. , Daly, A. P. , Huyton, J. and Sanders, L. D. 2012. The challenge of defining wellbeing. International Journal of Wellbeing 2 (3).
  17. Doll, B. 2008. The dual-factor model of mental health in youth. School Psychology Review 37 (1): 69–73.
  18. Dowdy, E. , Furlong, M. , Raines, T. C. , Bovery, B. , Kauffman, B. , Kamphaus, R. W. and Murdock, J. 2015. Enhancing school-based mental health services with a preventive and promotive approach to universal screening for complete mental health. Journal of Educational and Psychological Consultation 25 (2-3): 178–197.
  19. Du Plooy, D. R. , Lyons, A. and Kashima, E. S. 2018. Predictors of flourishing and psychological distress among migrants to australia: a dual continuum approach. Journal of Happiness Studies: An Interdisciplinary Forum on Subjective Well-Being 20 (2): 561–578.
  20. Duckworth, A. , Steen, T. A. and Seligman, M. E. 2005. Positive psychology in clinical practice. Annu. Rev. Clin. Psychol 1: 629–651.
  21. Eaton, J. W. 1951. The assessment of mental health. American Journal of Psychiatry 108 (2): 81–90.
  22. Egloff, B. 1998. The independence of positive and negative affect depends on the affect measure. Personality and Individual Differences 25 (6): 1101–1109.
  23. Eklund, K. , Dowdy, E. , Jones, C. and Furlong, M. 2011. Applicability of the dual-factor model of mental health for college students. Journal of College Student Psychotherapy 25: 79–92.
  24. Epp, J. 1988. Mental health for Canadians: striking a balance. Canadian Journal of Public Health/Revue Canadienne de Sante’e Publique 79 (5): 327–349.
  25. Fava, G. A. , Rafanelli, C. , Cazzaro, M. , Conti, S. and Grandi, S. 1998. Well-being therapy. A novel psychotherapeutic approach for residual symptoms of affective disorders. Psychological Medicine 28 (2): 475–480.
  26. Feldman Barrett, L. and Russell, J. A. 1998. Independence and bipolarity in the structure of current affect. Journal of Personality and Social Psychology 74 (4): 967.
  27. Fontana, A. F. , Marcus, J. L. , Dowds, B. N. and Hughes, L. A. 1980. Psychological impairment and psychological health in the psychological well-being of the physically ill. Psychosom Med 42: 279–88.
  28. Franken, K. , Lamers, S. M. , Ten Klooster, P. M. , Bohlmeijer, E.T. and Westerhof, G. J. 2018. Validation of the mental health continuum-short form and the dual continua model of well-being and psychopathology in an adult mental health setting. Journal of Clinical Psychology 74 (12): 2187–2202.
  29. Fredrickson, B. L. 2001. The role of positive emotions in positive psychology: the broaden-and-build theory of positive emotions. American Psychologist 56: 218.
  30. Fuller-Thomson, E. , Agbeyaka, S. , Lafond, D. M. and Bern-Klug, M. 2016. Flourishing after depression: Factors associated with achieving complete mental health among those with a history of depression. Psychiatry Research 242: 111–120.
  31. Furlong, M. J. , Fullchange, A. and Dowdy, E. 2017. Effects of mischievous responding on universal mental health screening: I love rum raisin ice cream, really I do!. School Psychology Quarterly 32(3): 320–325.
  32. Gilmour, H. 2014. Positive mental health and mental illness. Statistics Canada 25 (9): 3–9.
  33. Goodman, F. , Doorley, J. and Kashdan, T. 2018. Well-being and psychopathology: a deep exploration into positive emotions, meaning and purpose in life, and social relationships. in Diener, E, Oishi, S and Tay, L (Eds), Handbook of Well-Being, DEF Publishers, Salt Lake City, UT, DOI: nobascholar.com.
  34. Grant, F. , Guille, C. and Sen, S. 2013. Well-being and the risk of depression under stress. PLoS one 8 (7): e67395.
  35. Greenspoon, P. J. and Saklofske, D. H. 2001. Toward an integration of subjective well-being and psychopathology. Social Indicators Research 54 (1): 81–108.
  36. Hallion, M. , Taylor, A. and Roberts, R. 2018. Complete mental health in adult siblings of those with a chronic illness or disability. Disability and Rehabilitation: An International, Multidisciplinary Journal 40 (3): 296–301.
  37. Headey, B. , Kelley, J. and Wearing, A. 1993. Dimensions of mental health: Life satisfaction, positive affect, anxiety and depression. Social Indicators Research 29 (1): 63–82.
  38. Herron, S. and Trent, D. 2000. Mental health: a secondary concept to mental illness. Journal of Public Mental Health 2 (2): 29–38.
  39. Heubeck, B. G. and Neill, J. T. 2000. Confirmatory factor analysis and reliability of the mental health inventory for australian adolescents. Psychological Reports 87 (2): 431–440.
  40. Hu, Y. , Stewart-Brown, S. , Twigg, L. and Weich, S. 2007. Can the 12-item general health questionnaire be used to measure positive mental health? Psychological Medicine 37 (7): 1005–1013.
  41. Huppert, F. A. 2005. Positive mental health in individuals and populations.
  42. Huppert, F. A. 2014. The State of Wellbeing Science John Wiley & Sons, Wellbeing.
  43. Huppert, F. A. and Whittington, J. E. 2003. Evidence for the independence of positive and negative well-being: Implications for quality of life assessment. British Journal of Health Psychology 8 (1): 107–122.
  44. Iasiello, M. , Van Agteren, J. , Keyes, C. L. and Muir-Cochrane, E. 2019. Positive mental health as a predictor of recovery from mental illness. Journal of Affective Disorders 251: 227–230.
  45. Jahoda, M. 1958. Current Concepts of Positive Mental Health, Basic Books, New York, NY.
  46. Jans-Beken, L. , Lataster, J. , Peels, D. , Lechner, L. and Jacobs, N. 2017. Gratitude, psychopathology and subjective well-being: Results from a 7.5-month prospective general population study. Journal of Happiness Studies: An Interdisciplinary Forum on Subjective Well-Being 19 (6): 1673–1689.
  47. JBI 2015. The Joanna Briggs Institute Reviewers’ Manual 2015: Methodology for JBI Scoping Reviews The Joanna Briggs Institute, Adelaide, Australia.
  48. Jeste, D. V. , Palmer, B. W. , Rettew, D. C. and Boardman, S. 2015. Positive psychiatry: its time has come. J Clin Psychiatry 76 (6): 675–83.
  49. Joseph, S. and McCollam, P. 1993. A bipolar happiness and depression scale. The Journal of Genetic Psychology 154 (1): 127–129.
  50. Jiang, N. and Lu, N. 2018. Correlates of mental illness and health categories among older adults in china: an empirical study based on the two continua model. Clinical Gerontologist: The Journal of Aging and Mental Health 42 (1): 80–89.
  51. Jovanovic, V. and Brdaric, D. 2012. Did curiosity kill the cat? Evidence from subjective well-being in adolescents. Personality and Individual Differences 52 (3): 380–384.
  52. Karademas, E. C. 2007. Positive and negative aspects of well-being: common and specific predictors. Personality and Individual Differences, 43 (2): 277–287.
  53. Karas, D. , Cieciuch, J. and Keyes, C. L. 2014. The Polish adaptation of the Mental Health Continuum-Short Form (MHC-SF). Personality and Individual Differences 69: 104–109.
  54. Kelly, R. M. , Hills, K. J. , Huebner, E. and Mcquillin, S. D. 2012. The longitudinal stability and dynamics of group membership in the dual-factor model of mental health: Psychosocial predictors of mental health. Canadian Journal of School Psychology 27 (4): 337–355.
  55. Keyes, C. L. 2004. The nexus of cardiovascular disease and depression revisited: The complete mental health perspective and the moderating role of age and gender. Aging & Mental Health 8 (3): 266–274.
  56. Keyes, C. L. and Lopez, S. J. 2002. Toward a science of mental health, in Snyder, R and Lopez, S (Eds), Handbook of Positive Psychology, 45–59.
  57. Keyes, C. L. , Wissing, M. , Potgieter, J. P. , Temane, M. , Kruger, A. and Van Rooy, S. 2008. Evaluation of the Mental Health Continuum-short form (MHC-SF) in Setswana-speaking South Africans. Clinical Psychology & Psychotherapy 15 (3): 181–192.
  58. Keyes, C. L. M. 1998. Social well-being. Social Psychology Quarterly 61 (2): 121–140.
  59. Keyes, C. L. M. 2005. Mental illness and/or mental health? Investigating axioms of the complete state model of health. Journal of Consulting and Clinical Psychology 73 (3): 539.
  60. Keyes, C. L. M. 2013. Promoting and protecting positive mental health: early and often throughout the lifespan, in Keyes, C (Ed.), Mental Well-Being: International Contributions to the Study of Positive Mental Health. Springer Science + Business Media, New York, NY, 3–28.
  61. Keyes, C. L. M. , Dhingra, S. S. and Simoes, E. J. 2010. Change in level of positive mental health as a predictor of future risk of mental illness. American Journal of Public Health 100 (12): 2366–2371.
  62. Kim, E.K. , Furlong, M. J. , Dowdy, E. and Felix, E. D. 2014. Exploring the relative contributions of the strength and distress components of dual-factor complete mental health screening. Canadian Journal of School Psychology 29 (2): 127–140.
  63. Kim, S. E. 2017. Complete mental health and suicide resilience among University Students in South Korea. International Information Institute (Tokyo). Information 20 (8B): 5959–5966.
  64. Kinderman, P. , Tai, S. , Pontin, E. , Schwannauer, M. , Jarman, I. and Lisboa, P. 2015. Causal and mediating factors for anxiety, depression and well-being. The British Journal of Psychiatry 206: 456–460.
  65. Kodner, D. L. and Spreeuwenberg, C. 2002. Integrated care: meaning, logic, applications, and implications-a discussion paper. International Journal of Integrated Care 2 (12): e12.
  66. Lamers, S. M. , Westerhof, G. J. , Glas, C. A. and Bohlmeijer, E. T. 2015. The bidirectional relation between positive mental health and psychopathology in a longitudinal representative panel study. The Journal of Positive Psychology 10 (6): 553–560.
  67. Lamers, S. M. , Westerhof, G. J. , Kovacs, V. and Bohlmeijer, E. T. 2012. Differential relationships in the association of the Big Five personality traits with positive mental health and psychopathology. Journal of Research in Personality 46 (5): 517–524.
  68. Lamers, S. M. A. , Westerhof, G. J. , Bohlmeijer, E. T. , Ten Klooster, P. M. and Keyes, C. L. M. 2011. Evaluating the psychometric properties of the mental health continuum-short form (MHC-SF). Journal of Clinical Psychology 67 (1): 99–110.
  69. Lim, Y.-J. 2014. Psychometric characteristics of the Korean Mental Health Continuum-short form in an adolescent sample. Journal of Psychoeducational Assessment 32 (4): 356–364.
  70. Lupano Perugini, M. L. , De La Iglesia, G. , Castro Solano, A. and Keyes, C. L. 2017. The Mental Health Continuum-Short Form (MHC-SF) in the Argentinean Context: Confirmatory Factor Analysis and Measurement Invariance. Eur. J. Psychol 13 (1): 93–108.
  71. Lyons, M. D. , Huebner, E. and Hills, K. J. 2013. The dual-factor model of mental health: A short-term longitudinal study of school-related outcomes. Social Indicators Research 114 (2): 549–565.
  72. Lyons, M. D. , Huebner, E. S. , Hills, K. J. and Shinkareva, S. V. 2012. The dual-factor model of mental health: further study of the determinants of group differences. Canadian Journal of School Psychology, 27 (2): 183–196.
  73. Macaskill, A. 2012. A feasibility study of psychological strengths and well-being assessment in individuals living with recurrent depression. The Journal of Positive Psychology 7 (5): 372–386.
  74. Macaskill, A. and Denovan, A. 2014. Assessing psychological health: The contribution of psychological strengths. British Journal of Guidance & Counselling 42 (3): 320–337.
  75. Magalhaes, E. and Calheiros, M. M. 2017. A dual-factor model of mental health and social support: Evidence with adolescents in residential care. Children and Youth Services Review 79: 442–449.
  76. Massé, R. , Poulin, C. , Dassa, C. , Lambert, J. , Bélair, S. and Battaglini, A. 1998. The structure of mental health: Higher-order confirmatory factor analyses of psychological distress and well-being measures. Social Indicators Research 45 (1–3): 475–504.
  77. Moher, D. , Liberati, A. , Tetzlaff, J. and Altman, D. G. , The Prisma Group 2009. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Medicine 6 (7): e1000100.
  78. Nowlis, V. 1965. Research with the mood adjective check list, in Tompkins, S. S. and Izard, C. E. (Eds), Affect, Cognition, and Personality: Empirical Studies, Springer, New York, NY.
  79. Olszewski, J. 2012. Correlations between subjective well-being – psychopathology and coping with stress of people with different forms of mental health. Psychiatria i Psychologia Kliniczna 12 (4): 265–272.
  80. Payton, A. R. 2009. Mental health, mental illness, and psychological distress: same continuum or distinct phenomena? Journal of Health and Social Behavior 50 (2): 213–227.
  81. Peter, T. 2018. More than a feeling? An empirical analysis of the dual-continua model on a national sample of lesbian, gay, and bisexual identified Canadians. Journal of Homosexuality 65 (6): 814–831.
  82. Peterson, C. and Seligman, M. E. 2004. Character Strengths and Virtues: A Handbook and Classification Oxford University Press, Oxford.
  83. Petrillo, G. , Capone, V. , Caso, D. and Keyes, C. L. 2015. The Mental Health Continuum-Short Form (MHC-SF) as a measure of well-being in the Italian context. Social Indicators Research 121 (1): 291–312.
  84. Pruchno, R. A. , Peters, N. D. and Burant, C. J. 1995. Mental health of coresident family caregivers examination of a two-factor model. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences 50 (5): P247–P256.
  85. Pruchno, R. A. , Patrick, J. H. and Burant, C. J. 1996. Mental health of aging women with children who are chronically disabled: examination of a two-factor model. The Journals of Gerontology: Series B: Psychological Sciences and Social Sciences 51 (6): S284–S296.
  86. Reis, H. T. and Gable, S. L. 2003. Toward a positive psychology of relationships, in Keyes, C. L. M. and Haidt, J. (Eds), Flourishing: Positive Psychology and the Life Well-lived, American Psychological Association, Washington, DC, 129–159.
  87. Renshaw, T. L. and Cohen, A. S. 2014. Life satisfaction as a distinguishing indicator of college student functioning: further validation of the two-continua model of mental health. Social Indicators Research 117 (1): 319–334.
  88. Renshaw, T. L. , Eklund, K. R. , Bolognino, S. J. and Adodo, I. 2016. Bidimensional emotional health in college students: a comparison of categorical and continuous analytic approaches. Journal of Psychopathology and Behavioral Assessment 38 (4): 681–694.
  89. Rose, T. , Lindsey, M. A. , Xiao, Y. , Finigan-Carr, N. M. and Joe, S. 2017. Mental health and educational experiences among Black youth: a latent class analysis. Journal of Youth and Adolescence 46 (11): 2321–2340.
  90. Rottenberg, J. , Devendorf, A. R. , Kashdan, T. B. and Disabato, D. J. 2018. The curious neglect of high functioning after psychopathology: the case of depression. Perspectives on Psychological Science 13 (5): 549–566.
  91. Ryff, C. D. 1989. Happiness is everything, or is it? Explorations on the meaning of psychological well-being. Journal of Personality and Social Psychology 57: 1069.
  92. Ryff, C. D. and Keyes, C. L. M. 1995. The structure of psychological well-being revisited. Journal of Personality and Social Psychology 69 (4): 719.
  93. Salvador-Carulla, L. , Lucas, R. , Ayuso-Mateos, J. L. and Miret, M. 2014. Use of the terms ‘Wellbeing’ and ‘Quality of Life’ in health sciences: a conceptual framework. The European Journal of Psychiatry 28 (1): 50–65.
  94. Schönfeld, P. , Brailovskaia, J. and Margraf, J. 2017. Positive and negative mental health across the lifespan: A cross-cultural comparison. International Journal of Clinical and Health Psychology 17 (3): 197–206.
  95. Schonfeld, P. , Brailovskaia, J. , Bieda, A. , Zhang, X. C. and Margraf, J. 2016. The effects of daily stress on positive and negative mental health: mediation through self-efficacy. International Journal of Clinical and Health Psychology 16 (1): 1–10.
  96. Schotanus-Dijkstra, M. , Ten Have, M. , Lamers, S. M. A. , De Graaf, R. and Bohlmeijer, E. T. 2017. The longitudinal relationship between flourishing mental health and incident mood, anxiety and substance use disorders. Eur. J. Public Health 27 (3): 563–568.
  97. Schueller, S. M. 2014. Person–activity fit in positive psychological interventions, in Parks, A C and Schueller, S M (Eds), The Wiley Blackwell Handbook of Positive Psychological Interventions, Wiley-Blackwell, Oxford, 385–402.
  98. Seligman, M. E. , Rashid, T. and Parks, A. C. 2006. Positive psychotherapy. American Psychologist 61 (8): 774.
  99. Seow, L. S. E. , Vaingankar, J. A. , Abdin, E. , Sambasivam, R. , Jeyagurunathan, A. , Pang, S. , Chong, S. A. and Subramaniam, M. 2016. Positive mental health in outpatients with affective disorders: associations with life satisfaction and general functioning. Journal of Affective Disorders 190: 499–507.
  100. Shaffer-Hudkins, E. , Suldo, S. , Loker, T. and March, A. 2010. How adolescents’ mental health predicts their physical health: unique contributions of indicators of subjective well-being and psychopathology. Applied Research in Quality of Life 5 (3): 203–217.
  101. Slade, M. 2009. Personal Recovery and Mental Illness: A Guide for Mental Health Professionals Cambridge University Press, Cambridge.
  102. Slade, M. 2010. Mental illness and well-being: the central importance of positive psychology and recovery approaches. BMC Health Services Research 10 (1): 26.
  103. Smith, G. C. 1996. Caregiving outcomes for older mothers of adults with mental retardation: a test of the two-factor model of psychological well-being. Psychology & Aging 11 (2): 353–361.
  104. Spinhoven, P. , Elzinga, B. M. , Giltay, E. and Penninx, B. W. 2015. Anxious or depressed and still happy? PLoS One 10 (10): e0139912.
  105. Steger, M. F. , Frazier, P. , Oishi, S. and Kaler, M. 2006. The meaning in life questionnaire: assessing the presence of and search for meaning in life. Journal of Counseling Psychology 53 (1): 80.
  106. Suldo, S. , Thalji, A. and Ferron, J. 2011. Longitudinal academic outcomes predicted by early adolescents’ subjective well-being, psychopathology, and mental health status yielded from a dual factor model. The Journal of Positive Psychology 6 (1): 17–30.
  107. Suldo, S. M. and Shaffer, E. J. 2008. Looking beyond psychopathology: the dual-factor model of mental health in youth. School Psychology Review 37 (1): 52–68.
  108. Suldo, S. M. , Thalji-Raitano, A. , Kiefer, S. M. and Ferron, J. M. 2016. Conceptualizing high school students’ mental health through a dual-factor model. School Psychology Review 45 (4): 434–457.
  109. Teismann, T. , Brailovskaia, J. , Siegmann, P. , Nyhuis, P. , Wolter, M. and Willutzki, U. 2018. Dual factor model of mental health: Co-occurrence of positive mental health and suicide ideation in inpatients and outpatients. Psychiatry Research 260: 343–345.
  110. Tomba, E. , Offidani, E. , Tecuta, L. , Schumann, R. and Ballardini, D. 2014. Psychological well-being in out-patients with eating disorders: a controlled study. International Journal of Eating Disorders 47 (3): 252–258.
  111. Trent, D. R. 1992. The promotion of mental health: fallacies of current thinking, in Trent, D R and Reed, C (Eds), Promotion of Mental Health, Aldershot: Avebury, 2: 561–568.
  112. Trompetter, H. , Lamers, S. , Westerhof, G. , Fledderus, M. and Bohlmeijer, E. 2017. Both positive mental health and psychopathology should be monitored in psychotherapy: Confirmation for the dual-factor model in acceptance and commitment therapy. Behaviour Research and Therapy 91: 58–63.
  113. Van Erp Taalman Kip, R. M. and Hutschemaekers, G. J. 2018. Health, well-being, and psychopathology in a clinical population: structure and discriminant validity of Mental Health Continuum Short Form (MHC-SF). Journal of Clinical Psychology 74 (10): 1719–1729.
  114. Veit, C. T. and Ware, J. E. 1983. The structure of psychological distress and well-being in general populations. Journal of Consulting and Clinical Psychology 51 (5): 730.
  115. Vela, J. C. , Lu, M. T. P. , Lenz, A. S. , Savage, M. C. and Guardiola, R. 2016. Positive psychology and Mexican American college students’ subjective well-being and depression. Hispanic Journal of Behavioral Sciences 38 (3): 324–340.
  116. Venning, A. , Wilson, A. , Kettler, L. and Eliott, J. 2013. Mental health among youth in South Australia: a survey of flourishing, languishing, struggling, and floundering. Australian Psychologist 48 (4): 299–310.
  117. Vigo, D. , Thornicroft, G. and Atun, R. 2016. Estimating the true global burden of mental illness. The Lancet. Psychiatry 3 (2): 171–178.
  118. Weich, S. M. D. , Brugha, T. M. D. , King, M. P. , Mcmanus, S. M. , Bebbington, P. P. , Jenkins, R. M. D. , Cooper, C. P. , Mcbride, O. P. and Stewart-Brown, S. P. 2011. Mental well-being and mental illness: findings from the Adult Psychiatric Morbidity Survey for England 2007. British Journal of Psychiatry 199 (1): 23–28.
  119. Westerhof, G. J. 2013. The complete mental health model: the social distribution of mental health and mental illness in the Dutch population in Keyes, C. (Ed.), Mental Well-Being: International Contributions to the Study of Positive Mental Health Springer Science + Business Media, New York, NY, 51–70.
  120. Westerhof, G. J. and Keyes, C. L. 2010. Mental illness and mental health: The two continua model across the lifespan. Journal of Adult Development 17 (2): 110–119.
  121. Winzer, R. , Lindblad, F. , Sorjonen, K. and Lindberg, L. 2014. Positive versus negative mental health in emerging adulthood: a national cross-sectional survey. BMC Public Health 14 (1).
  122. Wilkinson R. B. Walford W. A. 1998 The measurement of adolescent psychological health: One or two dimensions? Journal of Youth and Adolescence 27 (4): 443–455.
  123. Wood, A. M. and Joseph, S. 2010. The absence of positive psychological (eudemonic) well-being as a risk factor for depression: A ten year cohort study. Journal of Affective Disorders 122 (3): 213–217.
  124. Wood, A. M. and Tarrier, N. 2010. Positive clinical psychology: A new vision and strategy for integrated research and practice. Clinical Psychology Review 30 (7): 819–829.
  125. Xiong, J. , Qin, Y. , Gao, M. and Hai, M. 2017. Longitudinal study of a dual-factor model of mental health in Chinese youth. School Psychology International 38 (3): 287–303.
  126. Yoo, C. and Kahng, S. K. 2019. Two-dimensional mental health and related predictors among adolescents in Korea. Asian Social Work and Policy Review 13 (1): 66–77.
XML PDF Share

FIGURES & TABLES

Figure 1:

Diagrammatic representation of the bipolar (a) and dual-continua (b) models of mental health.

Full Size   |   Slide (.pptx)

Figure 2:

PRISMA flowchart of the study selection process.

Full Size   |   Slide (.pptx)

Figure 3:

The three commonly tested models in Confirmatory Factor Analysis used to test the best model fit for the data: Single axis, which would indicate the bipolar model (a), two orthogonal factors, independent and distinct (b), and two oblique factors, independent and related (c). PMH = Positive mental health, MI = mental illness, MH = mental health. Circles indicate latent constructs, and boxes indicate survey items.

Full Size   |   Slide (.pptx)

Figure 4:

Sub-groups of mental health, as postulated by dual-factor models. Keyes’ (Keyes, 2005) terminology to describe the groups is used in throughout this paper to highlight the four mental health groups: ‘Complete Mental Health’ (no mental illness, high positive mental health), ‘Vulnerable’ (no mental illness, low positive mental health), ‘Symptomatic but content’ (mental illness, high positive mental health), and Struggling (mental illness, low positive mental health).

Full Size   |   Slide (.pptx)

Figure 5:

Higher order theoretical relationship between mental illness (distress) and positive mental health (wellbeing), adapted from the model presented in Massé et al. (Massé et al., 1998). PMH = Positive mental health, MI = mental illness, MH = mental health. Circles indicate latent constructs, and boxes indicate survey items.

Full Size   |   Slide (.pptx)

REFERENCES

  1. Abbott, R. A. , Ploubidis, G. B. , Huppert, F. A. , Kuh, D. and Croudace, T. J. 2010. An evaluation of the precision of measurement of Ryff’s psychological well-being scales in a population sample. Social Indicators Research 97: 357–373.
  2. Alterman, A. I. , Cacciola, J. S. , Ivey, M. A. , Coviello, D. M. , Lynch, K. G. , Dugosh, K. L. and Habing, B. 2010. Relationship of mental health and illness in substance abuse patients. Personality and Individual Differences 49(8): 880–884.
  3. Antaramian, S. 2015. Assessing psychological symptoms and well-being: application of a dual-factor mental health model to understand college student performance. Journal of Psychoeducational Assessment 33 (5): 419–429.
  4. Antaramian, S. P. 2011. A dual-factor model of mental health: understanding student engagement and school performance using a person-centered approach. Dissertation Abstracts International: Section B: The Sciences and Engineering 71: 5823.
  5. Antaramian, S. P. , Huebner, E. S. , Hills, K. J. and Valois, R. F. 2010. A dual-factor model of mental health: toward a more comprehensive understanding of youth functioning. American Journal of Orthopsychiatry 80 (4): 462–472.
  6. Baiden, P. and Fuller-Thomson, E. 2016. Factors associated with achieving complete mental health among individuals with lifetime suicidal ideation. Suicide and Life-Threatening Behavior 46 (4): 427–446.
  7. Banerjee, A. and Chaudhury, S. 2010. Statistics without tears: Populations and samples. Industrial Psychiatry Journal 19 (1): 60.
  8. Bariola, E. , Lyons, A. and Lucke, J. 2017. Flourishing among sexual minority individuals: Application of the dual continuum model of mental health in a sample of lesbians and gay men. Psychology of Sexual Orientation and Gender Diversity 4 (4): 43–53.
  9. Bartels, M. , Cacioppo, J. T. , Van Beijsterveldt, T. C. and Boomsma, D. I. 2013. Exploring the association between well-being and psychopathology in adolescents. Behavior Genetics 43 (3): 177–190.
  10. Bohlmeijer, E. T. , Lamers, S. M. and Fledderus, M. 2015. Flourishing in people with depressive symptomatology increases with Acceptance and Commitment Therapy. Post-hoc analyses of a randomized controlled trial. Behaviour Research and Therapy 65: 101–106.
  11. Bonanno, G. A. 2004. Loss, trauma, and human resilience: have we underestimated the human capacity to thrive after extremely aversive events? American Psychologist 59 (1): 20.
  12. Bradburn, N. M. 1969. The structure of psychological well-being.
  13. Davidson, R. J. 2000. Affective style, psychopathology, and resilience: brain mechanisms and plasticity. American Psychologist 55 (11): 1196.
  14. Diaz, D. , Stavraki, M. , Blanco, A. and Bajo, M. 2017. 11-m victims 3 years after madrid terrorist attacks: Looking for health beyond trauma. Journal of Happiness Studies: An Interdisciplinary Forum on Subjective Well-Being 19 (3): 663–675.
  15. Diener, E. 1984. Subjective well-being. Psychological Bulletin 95 (5): 542.
  16. Dodge, R. , Daly, A. P. , Huyton, J. and Sanders, L. D. 2012. The challenge of defining wellbeing. International Journal of Wellbeing 2 (3).
  17. Doll, B. 2008. The dual-factor model of mental health in youth. School Psychology Review 37 (1): 69–73.
  18. Dowdy, E. , Furlong, M. , Raines, T. C. , Bovery, B. , Kauffman, B. , Kamphaus, R. W. and Murdock, J. 2015. Enhancing school-based mental health services with a preventive and promotive approach to universal screening for complete mental health. Journal of Educational and Psychological Consultation 25 (2-3): 178–197.
  19. Du Plooy, D. R. , Lyons, A. and Kashima, E. S. 2018. Predictors of flourishing and psychological distress among migrants to australia: a dual continuum approach. Journal of Happiness Studies: An Interdisciplinary Forum on Subjective Well-Being 20 (2): 561–578.
  20. Duckworth, A. , Steen, T. A. and Seligman, M. E. 2005. Positive psychology in clinical practice. Annu. Rev. Clin. Psychol 1: 629–651.
  21. Eaton, J. W. 1951. The assessment of mental health. American Journal of Psychiatry 108 (2): 81–90.
  22. Egloff, B. 1998. The independence of positive and negative affect depends on the affect measure. Personality and Individual Differences 25 (6): 1101–1109.
  23. Eklund, K. , Dowdy, E. , Jones, C. and Furlong, M. 2011. Applicability of the dual-factor model of mental health for college students. Journal of College Student Psychotherapy 25: 79–92.
  24. Epp, J. 1988. Mental health for Canadians: striking a balance. Canadian Journal of Public Health/Revue Canadienne de Sante’e Publique 79 (5): 327–349.
  25. Fava, G. A. , Rafanelli, C. , Cazzaro, M. , Conti, S. and Grandi, S. 1998. Well-being therapy. A novel psychotherapeutic approach for residual symptoms of affective disorders. Psychological Medicine 28 (2): 475–480.
  26. Feldman Barrett, L. and Russell, J. A. 1998. Independence and bipolarity in the structure of current affect. Journal of Personality and Social Psychology 74 (4): 967.
  27. Fontana, A. F. , Marcus, J. L. , Dowds, B. N. and Hughes, L. A. 1980. Psychological impairment and psychological health in the psychological well-being of the physically ill. Psychosom Med 42: 279–88.
  28. Franken, K. , Lamers, S. M. , Ten Klooster, P. M. , Bohlmeijer, E.T. and Westerhof, G. J. 2018. Validation of the mental health continuum-short form and the dual continua model of well-being and psychopathology in an adult mental health setting. Journal of Clinical Psychology 74 (12): 2187–2202.
  29. Fredrickson, B. L. 2001. The role of positive emotions in positive psychology: the broaden-and-build theory of positive emotions. American Psychologist 56: 218.
  30. Fuller-Thomson, E. , Agbeyaka, S. , Lafond, D. M. and Bern-Klug, M. 2016. Flourishing after depression: Factors associated with achieving complete mental health among those with a history of depression. Psychiatry Research 242: 111–120.
  31. Furlong, M. J. , Fullchange, A. and Dowdy, E. 2017. Effects of mischievous responding on universal mental health screening: I love rum raisin ice cream, really I do!. School Psychology Quarterly 32(3): 320–325.
  32. Gilmour, H. 2014. Positive mental health and mental illness. Statistics Canada 25 (9): 3–9.
  33. Goodman, F. , Doorley, J. and Kashdan, T. 2018. Well-being and psychopathology: a deep exploration into positive emotions, meaning and purpose in life, and social relationships. in Diener, E, Oishi, S and Tay, L (Eds), Handbook of Well-Being, DEF Publishers, Salt Lake City, UT, DOI: nobascholar.com.
  34. Grant, F. , Guille, C. and Sen, S. 2013. Well-being and the risk of depression under stress. PLoS one 8 (7): e67395.
  35. Greenspoon, P. J. and Saklofske, D. H. 2001. Toward an integration of subjective well-being and psychopathology. Social Indicators Research 54 (1): 81–108.
  36. Hallion, M. , Taylor, A. and Roberts, R. 2018. Complete mental health in adult siblings of those with a chronic illness or disability. Disability and Rehabilitation: An International, Multidisciplinary Journal 40 (3): 296–301.
  37. Headey, B. , Kelley, J. and Wearing, A. 1993. Dimensions of mental health: Life satisfaction, positive affect, anxiety and depression. Social Indicators Research 29 (1): 63–82.
  38. Herron, S. and Trent, D. 2000. Mental health: a secondary concept to mental illness. Journal of Public Mental Health 2 (2): 29–38.
  39. Heubeck, B. G. and Neill, J. T. 2000. Confirmatory factor analysis and reliability of the mental health inventory for australian adolescents. Psychological Reports 87 (2): 431–440.
  40. Hu, Y. , Stewart-Brown, S. , Twigg, L. and Weich, S. 2007. Can the 12-item general health questionnaire be used to measure positive mental health? Psychological Medicine 37 (7): 1005–1013.
  41. Huppert, F. A. 2005. Positive mental health in individuals and populations.
  42. Huppert, F. A. 2014. The State of Wellbeing Science John Wiley & Sons, Wellbeing.
  43. Huppert, F. A. and Whittington, J. E. 2003. Evidence for the independence of positive and negative well-being: Implications for quality of life assessment. British Journal of Health Psychology 8 (1): 107–122.
  44. Iasiello, M. , Van Agteren, J. , Keyes, C. L. and Muir-Cochrane, E. 2019. Positive mental health as a predictor of recovery from mental illness. Journal of Affective Disorders 251: 227–230.
  45. Jahoda, M. 1958. Current Concepts of Positive Mental Health, Basic Books, New York, NY.
  46. Jans-Beken, L. , Lataster, J. , Peels, D. , Lechner, L. and Jacobs, N. 2017. Gratitude, psychopathology and subjective well-being: Results from a 7.5-month prospective general population study. Journal of Happiness Studies: An Interdisciplinary Forum on Subjective Well-Being 19 (6): 1673–1689.
  47. JBI 2015. The Joanna Briggs Institute Reviewers’ Manual 2015: Methodology for JBI Scoping Reviews The Joanna Briggs Institute, Adelaide, Australia.
  48. Jeste, D. V. , Palmer, B. W. , Rettew, D. C. and Boardman, S. 2015. Positive psychiatry: its time has come. J Clin Psychiatry 76 (6): 675–83.
  49. Joseph, S. and McCollam, P. 1993. A bipolar happiness and depression scale. The Journal of Genetic Psychology 154 (1): 127–129.
  50. Jiang, N. and Lu, N. 2018. Correlates of mental illness and health categories among older adults in china: an empirical study based on the two continua model. Clinical Gerontologist: The Journal of Aging and Mental Health 42 (1): 80–89.
  51. Jovanovic, V. and Brdaric, D. 2012. Did curiosity kill the cat? Evidence from subjective well-being in adolescents. Personality and Individual Differences 52 (3): 380–384.
  52. Karademas, E. C. 2007. Positive and negative aspects of well-being: common and specific predictors. Personality and Individual Differences, 43 (2): 277–287.
  53. Karas, D. , Cieciuch, J. and Keyes, C. L. 2014. The Polish adaptation of the Mental Health Continuum-Short Form (MHC-SF). Personality and Individual Differences 69: 104–109.
  54. Kelly, R. M. , Hills, K. J. , Huebner, E. and Mcquillin, S. D. 2012. The longitudinal stability and dynamics of group membership in the dual-factor model of mental health: Psychosocial predictors of mental health. Canadian Journal of School Psychology 27 (4): 337–355.
  55. Keyes, C. L. 2004. The nexus of cardiovascular disease and depression revisited: The complete mental health perspective and the moderating role of age and gender. Aging & Mental Health 8 (3): 266–274.
  56. Keyes, C. L. and Lopez, S. J. 2002. Toward a science of mental health, in Snyder, R and Lopez, S (Eds), Handbook of Positive Psychology, 45–59.
  57. Keyes, C. L. , Wissing, M. , Potgieter, J. P. , Temane, M. , Kruger, A. and Van Rooy, S. 2008. Evaluation of the Mental Health Continuum-short form (MHC-SF) in Setswana-speaking South Africans. Clinical Psychology & Psychotherapy 15 (3): 181–192.
  58. Keyes, C. L. M. 1998. Social well-being. Social Psychology Quarterly 61 (2): 121–140.
  59. Keyes, C. L. M. 2005. Mental illness and/or mental health? Investigating axioms of the complete state model of health. Journal of Consulting and Clinical Psychology 73 (3): 539.
  60. Keyes, C. L. M. 2013. Promoting and protecting positive mental health: early and often throughout the lifespan, in Keyes, C (Ed.), Mental Well-Being: International Contributions to the Study of Positive Mental Health. Springer Science + Business Media, New York, NY, 3–28.
  61. Keyes, C. L. M. , Dhingra, S. S. and Simoes, E. J. 2010. Change in level of positive mental health as a predictor of future risk of mental illness. American Journal of Public Health 100 (12): 2366–2371.
  62. Kim, E.K. , Furlong, M. J. , Dowdy, E. and Felix, E. D. 2014. Exploring the relative contributions of the strength and distress components of dual-factor complete mental health screening. Canadian Journal of School Psychology 29 (2): 127–140.
  63. Kim, S. E. 2017. Complete mental health and suicide resilience among University Students in South Korea. International Information Institute (Tokyo). Information 20 (8B): 5959–5966.
  64. Kinderman, P. , Tai, S. , Pontin, E. , Schwannauer, M. , Jarman, I. and Lisboa, P. 2015. Causal and mediating factors for anxiety, depression and well-being. The British Journal of Psychiatry 206: 456–460.
  65. Kodner, D. L. and Spreeuwenberg, C. 2002. Integrated care: meaning, logic, applications, and implications-a discussion paper. International Journal of Integrated Care 2 (12): e12.
  66. Lamers, S. M. , Westerhof, G. J. , Glas, C. A. and Bohlmeijer, E. T. 2015. The bidirectional relation between positive mental health and psychopathology in a longitudinal representative panel study. The Journal of Positive Psychology 10 (6): 553–560.
  67. Lamers, S. M. , Westerhof, G. J. , Kovacs, V. and Bohlmeijer, E. T. 2012. Differential relationships in the association of the Big Five personality traits with positive mental health and psychopathology. Journal of Research in Personality 46 (5): 517–524.
  68. Lamers, S. M. A. , Westerhof, G. J. , Bohlmeijer, E. T. , Ten Klooster, P. M. and Keyes, C. L. M. 2011. Evaluating the psychometric properties of the mental health continuum-short form (MHC-SF). Journal of Clinical Psychology 67 (1): 99–110.
  69. Lim, Y.-J. 2014. Psychometric characteristics of the Korean Mental Health Continuum-short form in an adolescent sample. Journal of Psychoeducational Assessment 32 (4): 356–364.
  70. Lupano Perugini, M. L. , De La Iglesia, G. , Castro Solano, A. and Keyes, C. L. 2017. The Mental Health Continuum-Short Form (MHC-SF) in the Argentinean Context: Confirmatory Factor Analysis and Measurement Invariance. Eur. J. Psychol 13 (1): 93–108.
  71. Lyons, M. D. , Huebner, E. and Hills, K. J. 2013. The dual-factor model of mental health: A short-term longitudinal study of school-related outcomes. Social Indicators Research 114 (2): 549–565.
  72. Lyons, M. D. , Huebner, E. S. , Hills, K. J. and Shinkareva, S. V. 2012. The dual-factor model of mental health: further study of the determinants of group differences. Canadian Journal of School Psychology, 27 (2): 183–196.
  73. Macaskill, A. 2012. A feasibility study of psychological strengths and well-being assessment in individuals living with recurrent depression. The Journal of Positive Psychology 7 (5): 372–386.
  74. Macaskill, A. and Denovan, A. 2014. Assessing psychological health: The contribution of psychological strengths. British Journal of Guidance & Counselling 42 (3): 320–337.
  75. Magalhaes, E. and Calheiros, M. M. 2017. A dual-factor model of mental health and social support: Evidence with adolescents in residential care. Children and Youth Services Review 79: 442–449.
  76. Massé, R. , Poulin, C. , Dassa, C. , Lambert, J. , Bélair, S. and Battaglini, A. 1998. The structure of mental health: Higher-order confirmatory factor analyses of psychological distress and well-being measures. Social Indicators Research 45 (1–3): 475–504.
  77. Moher, D. , Liberati, A. , Tetzlaff, J. and Altman, D. G. , The Prisma Group 2009. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Medicine 6 (7): e1000100.
  78. Nowlis, V. 1965. Research with the mood adjective check list, in Tompkins, S. S. and Izard, C. E. (Eds), Affect, Cognition, and Personality: Empirical Studies, Springer, New York, NY.
  79. Olszewski, J. 2012. Correlations between subjective well-being – psychopathology and coping with stress of people with different forms of mental health. Psychiatria i Psychologia Kliniczna 12 (4): 265–272.
  80. Payton, A. R. 2009. Mental health, mental illness, and psychological distress: same continuum or distinct phenomena? Journal of Health and Social Behavior 50 (2): 213–227.
  81. Peter, T. 2018. More than a feeling? An empirical analysis of the dual-continua model on a national sample of lesbian, gay, and bisexual identified Canadians. Journal of Homosexuality 65 (6): 814–831.
  82. Peterson, C. and Seligman, M. E. 2004. Character Strengths and Virtues: A Handbook and Classification Oxford University Press, Oxford.
  83. Petrillo, G. , Capone, V. , Caso, D. and Keyes, C. L. 2015. The Mental Health Continuum-Short Form (MHC-SF) as a measure of well-being in the Italian context. Social Indicators Research 121 (1): 291–312.
  84. Pruchno, R. A. , Peters, N. D. and Burant, C. J. 1995. Mental health of coresident family caregivers examination of a two-factor model. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences 50 (5): P247–P256.
  85. Pruchno, R. A. , Patrick, J. H. and Burant, C. J. 1996. Mental health of aging women with children who are chronically disabled: examination of a two-factor model. The Journals of Gerontology: Series B: Psychological Sciences and Social Sciences 51 (6): S284–S296.
  86. Reis, H. T. and Gable, S. L. 2003. Toward a positive psychology of relationships, in Keyes, C. L. M. and Haidt, J. (Eds), Flourishing: Positive Psychology and the Life Well-lived, American Psychological Association, Washington, DC, 129–159.
  87. Renshaw, T. L. and Cohen, A. S. 2014. Life satisfaction as a distinguishing indicator of college student functioning: further validation of the two-continua model of mental health. Social Indicators Research 117 (1): 319–334.
  88. Renshaw, T. L. , Eklund, K. R. , Bolognino, S. J. and Adodo, I. 2016. Bidimensional emotional health in college students: a comparison of categorical and continuous analytic approaches. Journal of Psychopathology and Behavioral Assessment 38 (4): 681–694.
  89. Rose, T. , Lindsey, M. A. , Xiao, Y. , Finigan-Carr, N. M. and Joe, S. 2017. Mental health and educational experiences among Black youth: a latent class analysis. Journal of Youth and Adolescence 46 (11): 2321–2340.
  90. Rottenberg, J. , Devendorf, A. R. , Kashdan, T. B. and Disabato, D. J. 2018. The curious neglect of high functioning after psychopathology: the case of depression. Perspectives on Psychological Science 13 (5): 549–566.
  91. Ryff, C. D. 1989. Happiness is everything, or is it? Explorations on the meaning of psychological well-being. Journal of Personality and Social Psychology 57: 1069.
  92. Ryff, C. D. and Keyes, C. L. M. 1995. The structure of psychological well-being revisited. Journal of Personality and Social Psychology 69 (4): 719.
  93. Salvador-Carulla, L. , Lucas, R. , Ayuso-Mateos, J. L. and Miret, M. 2014. Use of the terms ‘Wellbeing’ and ‘Quality of Life’ in health sciences: a conceptual framework. The European Journal of Psychiatry 28 (1): 50–65.
  94. Schönfeld, P. , Brailovskaia, J. and Margraf, J. 2017. Positive and negative mental health across the lifespan: A cross-cultural comparison. International Journal of Clinical and Health Psychology 17 (3): 197–206.
  95. Schonfeld, P. , Brailovskaia, J. , Bieda, A. , Zhang, X. C. and Margraf, J. 2016. The effects of daily stress on positive and negative mental health: mediation through self-efficacy. International Journal of Clinical and Health Psychology 16 (1): 1–10.
  96. Schotanus-Dijkstra, M. , Ten Have, M. , Lamers, S. M. A. , De Graaf, R. and Bohlmeijer, E. T. 2017. The longitudinal relationship between flourishing mental health and incident mood, anxiety and substance use disorders. Eur. J. Public Health 27 (3): 563–568.
  97. Schueller, S. M. 2014. Person–activity fit in positive psychological interventions, in Parks, A C and Schueller, S M (Eds), The Wiley Blackwell Handbook of Positive Psychological Interventions, Wiley-Blackwell, Oxford, 385–402.
  98. Seligman, M. E. , Rashid, T. and Parks, A. C. 2006. Positive psychotherapy. American Psychologist 61 (8): 774.
  99. Seow, L. S. E. , Vaingankar, J. A. , Abdin, E. , Sambasivam, R. , Jeyagurunathan, A. , Pang, S. , Chong, S. A. and Subramaniam, M. 2016. Positive mental health in outpatients with affective disorders: associations with life satisfaction and general functioning. Journal of Affective Disorders 190: 499–507.
  100. Shaffer-Hudkins, E. , Suldo, S. , Loker, T. and March, A. 2010. How adolescents’ mental health predicts their physical health: unique contributions of indicators of subjective well-being and psychopathology. Applied Research in Quality of Life 5 (3): 203–217.
  101. Slade, M. 2009. Personal Recovery and Mental Illness: A Guide for Mental Health Professionals Cambridge University Press, Cambridge.
  102. Slade, M. 2010. Mental illness and well-being: the central importance of positive psychology and recovery approaches. BMC Health Services Research 10 (1): 26.
  103. Smith, G. C. 1996. Caregiving outcomes for older mothers of adults with mental retardation: a test of the two-factor model of psychological well-being. Psychology & Aging 11 (2): 353–361.
  104. Spinhoven, P. , Elzinga, B. M. , Giltay, E. and Penninx, B. W. 2015. Anxious or depressed and still happy? PLoS One 10 (10): e0139912.
  105. Steger, M. F. , Frazier, P. , Oishi, S. and Kaler, M. 2006. The meaning in life questionnaire: assessing the presence of and search for meaning in life. Journal of Counseling Psychology 53 (1): 80.
  106. Suldo, S. , Thalji, A. and Ferron, J. 2011. Longitudinal academic outcomes predicted by early adolescents’ subjective well-being, psychopathology, and mental health status yielded from a dual factor model. The Journal of Positive Psychology 6 (1): 17–30.
  107. Suldo, S. M. and Shaffer, E. J. 2008. Looking beyond psychopathology: the dual-factor model of mental health in youth. School Psychology Review 37 (1): 52–68.
  108. Suldo, S. M. , Thalji-Raitano, A. , Kiefer, S. M. and Ferron, J. M. 2016. Conceptualizing high school students’ mental health through a dual-factor model. School Psychology Review 45 (4): 434–457.
  109. Teismann, T. , Brailovskaia, J. , Siegmann, P. , Nyhuis, P. , Wolter, M. and Willutzki, U. 2018. Dual factor model of mental health: Co-occurrence of positive mental health and suicide ideation in inpatients and outpatients. Psychiatry Research 260: 343–345.
  110. Tomba, E. , Offidani, E. , Tecuta, L. , Schumann, R. and Ballardini, D. 2014. Psychological well-being in out-patients with eating disorders: a controlled study. International Journal of Eating Disorders 47 (3): 252–258.
  111. Trent, D. R. 1992. The promotion of mental health: fallacies of current thinking, in Trent, D R and Reed, C (Eds), Promotion of Mental Health, Aldershot: Avebury, 2: 561–568.
  112. Trompetter, H. , Lamers, S. , Westerhof, G. , Fledderus, M. and Bohlmeijer, E. 2017. Both positive mental health and psychopathology should be monitored in psychotherapy: Confirmation for the dual-factor model in acceptance and commitment therapy. Behaviour Research and Therapy 91: 58–63.
  113. Van Erp Taalman Kip, R. M. and Hutschemaekers, G. J. 2018. Health, well-being, and psychopathology in a clinical population: structure and discriminant validity of Mental Health Continuum Short Form (MHC-SF). Journal of Clinical Psychology 74 (10): 1719–1729.
  114. Veit, C. T. and Ware, J. E. 1983. The structure of psychological distress and well-being in general populations. Journal of Consulting and Clinical Psychology 51 (5): 730.
  115. Vela, J. C. , Lu, M. T. P. , Lenz, A. S. , Savage, M. C. and Guardiola, R. 2016. Positive psychology and Mexican American college students’ subjective well-being and depression. Hispanic Journal of Behavioral Sciences 38 (3): 324–340.
  116. Venning, A. , Wilson, A. , Kettler, L. and Eliott, J. 2013. Mental health among youth in South Australia: a survey of flourishing, languishing, struggling, and floundering. Australian Psychologist 48 (4): 299–310.
  117. Vigo, D. , Thornicroft, G. and Atun, R. 2016. Estimating the true global burden of mental illness. The Lancet. Psychiatry 3 (2): 171–178.
  118. Weich, S. M. D. , Brugha, T. M. D. , King, M. P. , Mcmanus, S. M. , Bebbington, P. P. , Jenkins, R. M. D. , Cooper, C. P. , Mcbride, O. P. and Stewart-Brown, S. P. 2011. Mental well-being and mental illness: findings from the Adult Psychiatric Morbidity Survey for England 2007. British Journal of Psychiatry 199 (1): 23–28.
  119. Westerhof, G. J. 2013. The complete mental health model: the social distribution of mental health and mental illness in the Dutch population in Keyes, C. (Ed.), Mental Well-Being: International Contributions to the Study of Positive Mental Health Springer Science + Business Media, New York, NY, 51–70.
  120. Westerhof, G. J. and Keyes, C. L. 2010. Mental illness and mental health: The two continua model across the lifespan. Journal of Adult Development 17 (2): 110–119.
  121. Winzer, R. , Lindblad, F. , Sorjonen, K. and Lindberg, L. 2014. Positive versus negative mental health in emerging adulthood: a national cross-sectional survey. BMC Public Health 14 (1).
  122. Wilkinson R. B. Walford W. A. 1998 The measurement of adolescent psychological health: One or two dimensions? Journal of Youth and Adolescence 27 (4): 443–455.
  123. Wood, A. M. and Joseph, S. 2010. The absence of positive psychological (eudemonic) well-being as a risk factor for depression: A ten year cohort study. Journal of Affective Disorders 122 (3): 213–217.
  124. Wood, A. M. and Tarrier, N. 2010. Positive clinical psychology: A new vision and strategy for integrated research and practice. Clinical Psychology Review 30 (7): 819–829.
  125. Xiong, J. , Qin, Y. , Gao, M. and Hai, M. 2017. Longitudinal study of a dual-factor model of mental health in Chinese youth. School Psychology International 38 (3): 287–303.
  126. Yoo, C. and Kahng, S. K. 2019. Two-dimensional mental health and related predictors among adolescents in Korea. Asian Social Work and Policy Review 13 (1): 66–77.

EXTRA FILES

COMMENTS

  • |