Correlates of Competitive Versus Noncompetitive Employment Among Adults With Psychotic Disorders
Abstract
Objective
Studies of the demographic and clinical correlates of employment activity have proven useful for identifying employment assistance needs among people with severe and persistent mental illness. However, the results of prior studies remain unclear, and most reviews of prior studies have not differentiated competitive from noncompetitive employment. This study attempted to clarify the relative strength and consistency of correlates of competitive versus noncompetitive employment.
Methods
Data were drawn from a population-based survey of Australian adults with psychotic disorders between March and December 2010. Demographic, clinical, and employment assistance correlates of competitive and noncompetitive employment were compared. The sample comprised 1,825 participants who agreed to face-to-face interviews.
Results
A total of 408 (22.3%) participants were employed in the previous four weeks, 330 (18.1%) in competitive employment and 78 (4.3%) in noncompetitive employment. Those in competitive employment were more likely to be female and aged 18–34, to have a partner, to have received formal vocational training or education after high school, and to have no literacy difficulties. Better global functioning, shorter illness duration, less severe course of illness, and affective versus nonaffective psychosis were associated with a greater likelihood of competitive employment. Those using Australian government employment services were less likely to be in competitive employment, suggesting a service provider preference for noncompetitive employment.
Conclusions
Four times as many employees were in competitive employment than in noncompetitive employment. The negative relationship between employment assistance and competitive employment highlights the urgent need to improve the effectiveness of Australian employment services for people with severe mental illnesses.
In 2010, Australia conducted its second national survey of psychosis. The survey revealed that more than two-thirds of working-age adults with psychotic disorders wanted to work and that 22% were employed either full-time or part-time in the previous four weeks (1,2). This rate is over three times less than the proportions of healthy, working-age Australians who were employed in 1998 (74%) and 2003 (77%) (1). Employment was positively associated with younger age, immigrant status, partnered status, higher education, and better global functioning. Consistent with the first national survey, in 1997, employment was positively related to educational attainment and a less severe course pattern of illness in the previous 12 months (2–6).
The proportion employed remained largely unchanged since the first survey (2–6), even though labor demand has increased since 1997 and the Australian government has invested extensively in a national network of disability employment services (7). The use of caution in interpreting this stability is warranted because any real differences between the proportions employed may be masked by differences in the survey methods, particularly the use of different labor force exclusion criteria and different time frames for defining current employment.
Previous studies of the correlates of employment among people with severe and persistent mental illness have proved useful for identifying individuals' assistance needs. These studies have identified a large number of covariates at an individual level that are associated with employment, although much disagreement remains about their relative strength and consistency across countries (8,9). Tsang and colleagues (9) found that the most consistent demographic correlates were work history, educational attainment, social support, age, and work skills. The most consistent clinical variables were an absence of negative symptoms, good cognitive functioning, favorable course of illness, and the availability of rehabilitation services. Missing from these reviews were measures of global functioning, which have been found to be strong correlates of current employment in general psychiatry samples (10). Other factors, such as work-related subjective experiences, work-related self-efficacy, severity of work restrictions (10–13), and comorbidities (14), are promising correlates of current employment but have yet to be reviewed.
Previous studies did not consistently differentiate competitive from noncompetitive employment. Competitive employment is typically defined as jobs in the open labor market that are not reserved for people with disabilities. Places in prevocational programs, voluntary work, temporary jobs, transitional employment, and jobs paying less than mandated minimum wages are considered noncompetitive (15). This distinction is important because the nature of the experience of employment and the demands of employers at these two types of employment can vary markedly (16).
Studies that have compared competitive and noncompetitive employment have not consistently demonstrated the relative benefits of one employment type. In one of the few studies to directly compare noncompetitive and competitive employment, the authors found that competitive employment was associated with higher self-esteem, improved psychiatric symptoms, and greater satisfaction with vocational services, leisure activities, and finances (17). However, a more recent study found differences in positive and negative symptoms among persons in steady, competitive employment compared with individuals who had no or minimal employment but not compared with individuals in noncompetitive employment (18). An unexpected result was that those in noncompetitive employment showed greater improvement in social network scores compared with those in sustained competitive employment.
In a large multisite study that differentiated competitive and noncompetitive employment (N=1,400), Rosenheck and others (19) found that 14.5% of participants were in competitive employment and 12.6% were in noncompetitive employment in the previous month. Participation in either employment type was associated with less severe symptoms, good neuropsychological functioning, and higher scores for motivation, curiosity, anhedonia, and empathy on the Heinrichs-Carpenter Quality of Life Scale. Competitive employment was also negatively associated with race (being black), positively associated with educational attainment, and negatively associated with higher disability payments.
We had the opportunity to examine correlates of competitive versus noncompetitive employment in the second national survey of psychosis in Australia (2,20). We expected that younger age, partnered status, and higher educational attainment would be associated with competitive employment, but not necessarily with noncompetitive employment. In line with previous findings related to evidence-based employment services, such as the Individual Placement and Support (IPS) approach (15,21–27), we expected utilization of suitable employment assistance to favor competitive over noncompetitive employment.
Methods
Participants
This investigation is a secondary analysis of the data collected in Australia's second national survey of psychotic disorders, the Survey of High Impact Psychosis (SHIP). The full details of the methods are described elsewhere (2,20). In summary, SHIP generated a national probability sample from seven catchment areas, including inner-city, urban, and rural settings, representing 1.5 million people aged 18–64 years, approximately 10% of the Australian population in this age range. A two-phase design began with screening for psychosis. This took place during the census month of March 2010 at public mental health services and nongovernment organizations that support people with severe mental illness. Of 7,955 people who screened positive, a random sample stratified by age group (18–34 and 35–64 years) was invited to participate in further in-depth interviews (N=4,148). A total of 1,825 completed face-to-face interviews, for a response rate of 44% (19), which was in the range expected for this type of study. The study was approved by institutional human research ethics committees at each of the seven study sites, and all participants provided written, informed consent.
Measures
Face-to-face interviews covered psychiatric symptoms, substance use, cognitive performance, functioning, disability, general medical health, mental health service utilization, education, employment, and housing. Trained interviewers, who were predominantly allied health professionals, administered the survey. The survey incorporated the following measures that were relevant to our analysis.
Diagnosis of psychosis.
Diagnosis was determined by using the Diagnostic Interview for Psychosis diagnostic module (DIP-DM) (28), which was developed for the first Australian survey of psychosis (1997–1998) for use by trained mental health professionals (3–4). It uses SCAN prompts (29) to elicit signs and symptoms, then applies the OPCRIT criteria developed by McGuffin and others (30) with a computer algorithm to generate diagnoses according to several classification systems. The DIP-DM has well established psychometric properties (28). Diagnoses were derived by using the ICD-10 (31).
Current employment.
International definitions of labor force activity were applied to determine two mutually exclusive categories: employed versus not employed in the past four weeks. These categories were consistent with definitions of labor force activity used by the Australian Bureau of Statistics (ABS) (32). The ABS typically uses three mutually exclusive categories: not participating in the labor force, available for and actively looking for work, and employed. We collapsed nonparticipants in the labor force and those who were actively looking for work but not yet employed into one category to create a binary labor force variable. Competitive employment was defined as part-time (at least one hour per week) or full-time work in the open labor market with pay at or above the minimum wage in jobs not reserved for people with disabilities. Its complement, noncompetitive employment, was defined as jobs paying below the minimum wage, jobs reserved for people with disabilities, jobs with minimum wages based on relative productivity, or jobs with wage subsidies. Unpaid work was not included in the definition of noncompetitive employment.
Global functioning.
The Personal and Social Performance (PSP) scale is a clinician-rated measure of global personal and social dysfunction (33). The impact of illness is assessed from a structured clinical interview covering four main areas: socially useful activities, personal and social relationships, self-care, and disturbing and aggressive behaviors. Difficulty in each area is rated on a single item by using a 6-point scale indicating absent, mild, manifest but not marked, marked, severe, and very severe. Total scores range from 1 to 100, with lower scores indicating poorer global functioning. The PSP scale has good interrater reliability (intraclass correlation coefficient [ICC]=.87) and moderate to good test-retest reliability (ICC>.90) in this population (34,35).
Course of illness.
Course of illness was assessed and rated by the interviewers, who based their ratings on participant responses throughout the course of the semistructured diagnostic interview. This variable captures the number of episodes of mental illness that a person has experienced and the degree of recovery after each episode. Interviewers used specified probe questions and elicited examples of actual behavior before using their clinical judgment to rate level of impairment, dysfunction, and deterioration on the basis of all available information. Although the interviewer (28) coded recovery into five levels, to conserve power the levels were collapsed into three hierarchical levels: good recovery (one or multiple episodes with good recovery between episodes), partial recovery (multiple episodes with partial recovery in between), and chronic illness (continuous chronic illness both with and without deterioration) (20, page 151). Course of illness has demonstrated good concurrent validity with respect to other clinical dimensions and with social functioning, including employment, in the previous national survey (5,6).
Statistical analyses
Unadjusted correlates of current employment were estimated by using univariate logistic regression (Wald chi square). Unadjusted results are presented in model 1 in Tables 1–3. Model 2, using multiple logistic regression, controlled for the strongest candidates from previous studies that were also available in the data set (1). Analyses were performed by using SAS, version 9.3, and Procedure Surveyfreq and Procedure Surveylogistic (36).
| Competitiveemployment(N=330) | Noncompetitiveemployment(N=78) | Model 1 | Model 2b | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Variable | N | % | N | % | OR | 95% CI | p | OR | 95% CI | p |
| Sex | ||||||||||
| Female | 150 | 45 | 19 | 24 | 2.27 | 1.26–4.09 | .001 | 3.48 | 1.52–7.97 | .001 |
| Male (reference) | 180 | 55 | 59 | 76 | ||||||
| Age (years)c | ||||||||||
| 18–34 | 179 | 54 | 29 | 37 | 2.63 | 1.41–4.93 | .001 | 3.74 | 1.34–10.45 | .001 |
| 35–44 | 84 | 25 | 22 | 28 | 1.50 | .76–2.97 | ns | 3.78 | 1.32–10.85 | .001 |
| 45–64 (reference) | 67 | 20 | 27 | 35 | ||||||
| Immigrant status | ||||||||||
| Yes | 74 | 22 | 16 | 21 | 1.38 | .73–2.62 | ns | 1.02 | .38–2.72 | ns |
| No (reference) | 256 | 78 | 62 | 79 | ||||||
| Partnered status | ||||||||||
| Partner | 76 | 23 | 9 | 12 | 2.41 | 1.10–5.27 | .001 | 1.52 | .43–5.34 | ns |
| No partner (reference) | 254 | 77 | 69 | 88 | ||||||
| Education | ||||||||||
| Vocational training or education after high school | 209 | 64 | 35 | 45 | 2.78 | 1.52–5.07 | .001 | 2.66 | .85–8.35 | ns |
| Secondary | 60 | 18 | 13 | 17 | 2.11 | .96–4.63 | ns | 1.77 | .78–4.04 | ns |
| Less than secondary (reference) | 60 | 18 | 29 | 38 | ||||||
| Difficulty in reading or writing | ||||||||||
| None | 291 | 88 | 16 | 21 | 2.04 | 1.03–4.03 | <.05 | .80 | .27–2.38 | ns |
| Any (reference) | 39 | 12 | 62 | 79 | ||||||
| Age of onset of psychosisd | ||||||||||
| Later age (22–62 years) | 163 | 49 | 28 | 36 | 1.79 | 1.04–3.07 | <.05 | 1.94 | .80–4.71 | ns |
| Early age (5–21 years) (reference) | 164 | 50 | 50 | 64 | ||||||
a
Employment was defined as being employed in the past four weeks.
b
Model 2 was adjusted for age, sex, immigrant status, partnered status, education, global functioning, course of illness, and receipt of support for employment. Global functioning and course of illness were correlated (Kendall tau b=–.25, p<.001), but the estimates were within acceptable limits.
c
To increase power, some age groups were combined (18–24 and 25–34 years and 45–54 and 55–64 years).
d
To increase power, the age-of-onset quartiles (later age [28–62 years] and middle age [22–27 years] and early age [18–21 years] and very early age [5–17 years]) were combined into the two categories shown.
| Competitiveemployment(N=330) | NoncompetitiveEmployment(N=78) | Model 1 | Model 2b | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Variable | N | % | N | % | OR | 95% CI | p | OR | 95% CI | p |
| Global functioningc | ||||||||||
| Very good | 202 | 61 | 15 | 19 | 25.04 | 10.36–60.51 | .001 | 18.69 | 5.98–58.46 | .001 |
| Good | 83 | 25 | 18 | 23 | 8.92 | 3.72–21.39 | .001 | 13.81 | 4.08–46.81 | .001 |
| Severe | 31 | 9 | 21 | 26 | 2.55 | 1.03–6.30 | <.050 | 2.05 | .59–7.06 | ns |
| Very severe (reference) | 14 | 4 | 24 | 31 | ||||||
| Course of illnessd | ||||||||||
| Good recovery | 193 | 58 | 25 | 32 | 2.56 | 1.28–5.17 | <.05 | 1.23 | .41–3.66 | ns |
| Partial recovery | 83 | 25 | 33 | 42 | .76 | .38–1.52 | ns | .45 | .18–1.11 | ns |
| Chronic illness (reference) | 54 | 16 | 20 | 26 | ||||||
| Duration of illness (years) | ||||||||||
| 1–6 | 121 | 37 | 10 | 13 | 7.57 | 2.90–19.72 | .001 | 7.02 | 1.17–42.07 | .010 |
| 7–12 | 94 | 29 | 18 | 24 | 2.62 | 1.23–5.59 | .010 | 1.70 | .47–6.11 | ns |
| 13–20 | 61 | 19 | 21 | 28 | 1.28 | .61–2.67 | ns | .94 | .26–3.34 | ns |
| 20–50 (reference) | 51 | 15 | 27 | 36 | ||||||
| Psychotic disorder | ||||||||||
| Affectivec | 146 | 50 | 12 | 17 | ||||||
| Nonaffectived | 145 | 49 | 58 | 83 | ||||||
| NOSe | 33 | 10 | 7 | 9 | ||||||
| Schizoaffective | 46 | 14 | 8 | 10 | ||||||
| Bipolar | 80 | 24 | 4 | 5 | ||||||
| Schizophrenia | 132 | 40 | 50 | 64 | ||||||
| Affective versus nonaffective (reference) | 3.50 | 1.98–6.18 | .001 | 3.49 | 1.36–8.95 | <.050 | ||||
| Bipolar and NOS versus schizophrenia and schizoaffective (reference) | 6.08 | 2.98–12.36 | .001 | 6.68 | 1.62–27.44 | .01 | ||||
| Bipolar versus other (reference) | 7.94 | 2.54–24.82 | .001 | —f | ||||||
| Bipolar versus schizophrenia (reference) | 10.20 | 3.19–32.55 | .001 | —f | ||||||
a
Employment was defined as being employed in the past four weeks.
b
Adjusted for age, sex, immigrant status, partnered status, education, global functioning, course of illness, and receipt of support for employment. Global functioning and course of illness were correlated (Kendall tau b=–.25, p<.001); however, the estimates were within acceptable limits.
c
Includes schizoaffective, bipolar, and depressive disorders and mania
d
Includes schizophrenia and delusional and nonorganic psychoses
e
NOS, not otherwise specified; includes severe depression without psychosis and a positive screen for psychosis without meeting ICD–10 criteria for psychosis
f
Estimates were not available because of low sample size.
| Competitive employment (N=330) | Noncompetitive employment (N=78) | Model 1 | Model 2b | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Variable | N | % | N | % | OR | 95% CI | p | OR | 95% CI | p |
| Acquisition | ||||||||||
| Own means | 284 | 87 | 27 | 37 | 9.44 | 5.17–17.24 | .001 | 14.26 | 4.96–41.0 | .001 |
| Employment service (reference) | 44 | 13 | 46 | 63 | ||||||
| Supportc | ||||||||||
| Any | 44 | 13 | 21 | 29 | .39 | .21–.73 | .001 | .64 | .24–1.79 | ns |
| None (reference) | 286 | 87 | 51 | 71 | ||||||
a
Employment was defined as being employed in the past four weeks.
b
Adjusted for age, sex, immigrant status, partnered status, education, global functioning, course of illness, and receipt of support for employment. Global functioning and course of illness were correlated (Kendall tau b=–.25, p<.001); however, the estimates were within acceptable limits.
c
Support, advice, or counseling from an employment support worker in the last 12 months
Results
Among the 1,825 participants who completed personal interviews, 408 were employed in the previous four weeks, 330 (18.1%) in competitive employment and 78 (4.3%) in noncompetitive employment. Four times as many participants were employed in competitive (80.9%) than in noncompetitive employment (19.1%).
Demographic correlates
Table 1 shows both unadjusted and adjusted correlates, comparing the odds of being in competitive employment with noncompetitive employment as the reference group. Compared with males, females had over twice the unadjusted odds of being in competitive employment. This effect was not moderated by statistical adjustments for age, immigrant status, partnered status, formal vocational training or education after high school, global functioning, illness duration, course of illness, and support received for employment. Younger age was significantly associated with increased odds of competitive employment, and this effect remained significant following adjustment for these covariates.
Partnered persons and those with no literacy difficulties had greater unadjusted odds of being in competitive employment. This association became nonsignificant after adjustment for the covariates listed above. Further analysis identified an interaction between gender and partnered status, in which partnered males had significantly greater odds than partnered females of being in competitive versus noncompetitive employment (partnered males: odds ratio [OR]=2.49, 95% confidence interval [CI]=1.58–3.90, p<.001; partnered females: OR=1.23, CI=.79–1.89, p<.001).
Educational attainment was positively associated with competitive employment, and this effect persisted with only minor moderation after adjustment for the covariates mentioned above. Immigrant status appeared to increase the odds of competitive employment, but this promising ratio was not statistically significant and was even less apparent in the adjusted model.
Clinical correlates
Clinical correlates of current employment are shown in Table 2 in descending order of effect size. Better global functioning (higher scores on the PSP) was the most important correlate of competitive versus noncompetitive employment. This effect persisted after adjustment for the covariates listed above. Duration of illness and course of illness were also significantly correlated with competitive employment in the unadjusted model. Both effects were moderated by adjustment for global functioning and the other variables included in the adjusted model. The trend values for both illness duration and course of illness remained significant after adjustment.
Diagnostic category within the psychotic disorders differentiated competitive from noncompetitive employment. Of these, the largest effect size compared bipolar affective disorder (with psychosis) with schizophrenia. This effect was moderated in other categories of psychosis yet showed that affective disorders (bipolar disorder, mania, schizoaffective disorder, and depressive psychosis) were more positively associated with competitive employment than nonaffective disorders (schizophrenia and delusional and nonorganic psychosis).
Those in competitive employment had nine times greater odds of having found a job by using their own resources rather than via assistance from an employment service (Table 3). Pathways to noncompetitive employment were facilitated by employment services. Nearly two-thirds (63%) of those in noncompetitive employment had received assistance from an employment service. Those in competitive employment received support to retain employment less often than those in noncompetitive forms of employment, although this effect did not persist following adjustment for the covariates listed above. Employment support was defined as support, advice, or counseling from an employment support worker in the past 12 months.
Discussion
Those in competitive employment were more likely to be female, aged 18–34, and partnered and to have formal vocational training or education after high school and no literacy difficulties. Overall global functioning (higher PSP scores), shorter duration of illness, partial or good recovery course pattern of illness, and an affective rather than a nonaffective psychosis favored competitive over noncompetitive employment. Our results with respect to age, educational attainment, and global functioning are consistent with prior reviews (8,9,37). However, our finding for sex contrasted with a previous review (9), which concluded that sex is not associated with employment. Differentiating competitive from noncompetitive employment may explain this divergence, because we found that by aggregating competitive and noncompetitive employment, this sex difference vanished.
We could not investigate race or ethnic minority group, which has been found to be negatively related to competitive employment (19,37). However, we found no significant relationship between immigrant status and type of employment in either the unadjusted or adjusted models.
Consistent with results from the first Australian survey of psychosis, course of illness emerged as a useful correlate of employment and of competitive employment, in particular (5,6). Although overshadowed by PSP scale results, both illness duration and course of illness are comparatively easy to assess from clinical history in combination with self-report. The finding with respect to illness duration is at odds with previous meta-analyses of this type of study (8,9). The four clinical variables are relatively mutually independent and together provide a promising basis for classifying those in need of the most intensive forms of employment assistance (15,23–25).
Several previous reviews suggest that the nature of employment assistance is an important predictor of competitive employment (15,21–23,26,27). However, we found that assistance from Australian employment services was negatively associated with competitive employment. In the adjusted model, compared with noncompetitive employment, competitive employment was associated with nine times greater odds of finding one’s own job and over twice the odds of not receiving ongoing support for employment. Furthermore, 51.1% of those placed in employment were placed in noncompetitive forms. In contrast, only 8.7% of those who obtained employment on their own entered noncompetitive employment.
This was surprising because Australian employment services are intended to deliver competitive, not noncompetitive, employment (38). The lack of impact of Australian employment assistance may indicate that these services are not as focused on competitive employment as evidence-based services designed specifically for this client group (15,22,23). A recent evaluation by the Australian government supports this explanation (39). After linear extrapolation of the assistance duration from nine to 12 months in the evaluation report (by increasing employment outcomes by the ratio 12:9) (39), we conservatively estimate that no more than 30% of those with a psychiatric disability would have commenced competitive employment. That is less than half of the mean rate (62%) at which individuals commence competitive employment in controlled trials of IPS services (15,23,24). In March 2010, at the time of this survey, it appears that Australian services had deviated from the IPS principle of focusing on competitive employment and were providing postemployment support less frequently than is usually needed to sustain employment. Anecdotal reports from employment services in 2013 suggest that in March 2012 the funding provider tightened definitions of employment outcomes to exclude jobs in sheltered environments. This step may have partly corrected this problem (39).
Some may argue that a focus on competitive employment is unnecessary because noncompetitive jobs are just as valuable to clients, service providers, and the wider community. Yet it is reasonable to report on competitive and noncompetitive employment separately until we know more about how each kind contributes to health outcomes or to longer-term social inclusion (25). For instance, sustained periods of competitive employment appear to be associated with health improvements, financial security, and reduced health service utilization (18,19), but it remains unclear whether these benefits are shared by those in noncompetitive employment. In addition, noncompetitive employment may involve high additional costs, such as the cost of setting up a new business, which may require ongoing subsidies to compete with commercial operations (25).
Although the second national survey of psychosis is one of the best to date for this purpose, it had important limitations. The survey design did not include persons entirely in the care of private mental health providers, such as general medical practitioners or psychiatrists, nor those who had dropped all contact with mental health and nongovernment agencies. This could matter because it is feasible that these individuals may have better employment outcomes. Only those 18 years of age and older were eligible for inclusion; hence the survey does not estimate the impact of psychotic disorders on educational and vocational outcomes among persons aged 15–18 years.
Some questions about looking for work were asked in the context of a 12-month period rather than a one-month time frame. Thus finer-grained information about labor force activity was not obtained. Nor could we explore the extent to which participants were volunteers for employment assistance or were obligated to look for work in return for welfare benefits. More detailed examination of the role of service provision was not possible because only those employed were asked about employment assistance.
We had no information on the distribution and accessibility of suitable employment services within the catchment area, nor did we have any information on the extent to which these services implement IPS principles. However, similar types of mainstream disability employment services are available throughout Australia (7). Hence there is no reason to expect that access to employment services differed in the catchment area versus the nation as a whole. Survey questions that differentiated competitive from noncompetitive employment were adequate, but they had important limitations, given that almost 13% of those in competitive employment reported earning below minimum wage. In addition, the exact nature of the noncompetitive employment cannot be specified, so it remains unclear as to which types of noncompetitive employment contributed most to this result.
Conclusions
These results highlight the utility of differentiating competitive employment from noncompetitive employment when examining individual characteristics as correlates of employment. The unexpected finding of a negative relationship between receiving employment assistance and competitive employment highlights an urgent need to improve the effectiveness of Australian employment services for people with severe mental illnesses.
Acknowledgments and disclosures
This report was funded in full by the Queensland Centre for Mental Health Research and is a secondary analysis of data collected in the framework of the 2010 Australian National Survey of High Impact Psychosis (SHIP). The members of the SHIP study group are Vera A. Morgan, Ph.D. (project director); Assen Jablensky, M.D., D.Med.Sc. (chief scientific advisor); Anna Waterreus, Grad.Dip.Clin.Epid. (project coordinator); Andrew Mackinnon, Ph.D. (statistician); Robert Bush, Ph.D., David Castle, Ph.D., Martin Cohen, M.B.B.S., Cherrie Galletly, Ph.D., Carol Harvey, M.D., Patrick McGorry, Ph.D., Dr. McGrath, and Helen Stain, Ph.D. (site directors); Vaughan Carr, Ph.D. (Australian Schizophrenia Research Bank); Amanda Neil, Ph.D.; Barbara Hocking, B.Sc. (Hons.) (SANE Australia); Sonal Shah, Ph.D. (University of Western Australia); and Suzy Saw (Australian Department of Health and Aging). The SHIP was funded by the Australian Department of Health and Aging. The authors thank the hundreds of mental health professionals who participated in the preparation and conduct of the survey and the many Australians with psychotic disorders who gave their time and whose responses form the basis of this publication.
The authors report no competing interests.
References
1.
Waghorn G, Saha S, Harvey C, et al.: Earning and learning in people with psychotic disorders: results from Australia's second survey of psychotic disorders. Australian and New Zealand Journal of Psychiatry 46:774–785, 2012
2.
Morgan VA, Waterreus A, Jablensky A, et al.: People living with psychotic illness in 2010: the second Australian national survey of psychosis. Australian and New Zealand Journal of Psychiatry 46:735–752, 2012
3.
Jablensky A, McGrath J, Herrman H, et al.: People Living With Psychotic Illness: An Australian Study, 1997–98. Canberra, Australia, Department of Health and Aged Care, 1999. Available at www.psychiatry.uwa.edu.au/__data/assets/pdf_file/0020/2311904/1999-Jablensky-et-al-LowPrev-Report4-AGPS.pdf
4.
Jablensky A, McGrath J, Herrman H, et al.: Psychotic disorders in urban areas: an overview of the methods and findings of the Study on Low Prevalence Disorders, National Survey of Mental Health and Wellbeing, 1996–1998. Australian and New Zealand Journal of Psychiatry 34:221–236, 2000
5.
Waghorn G, Chant D: Clinical and nonclinical predictors of vocational recovery for Australians with psychotic disorders. Journal of Rehabilitation 68:40–51, 2002
6.
Waghorn G, Chant D, Whiteford H: The strength of self-reported course of illness in predicting vocational recovery for persons with schizophrenia. Journal of Vocational Rehabilitation 18:33–41, 2003
7.
National Mental Health and Disability Employment Strategy. Canberra, Australia, Department of Employment, Education and Workplace Relations, 2009
8.
Tsang H, Lam P, Ng B, et al.: Predictors of employment outcome for people with psychiatric disabilities: a review of the literature since the mid ’80s. Journal of Rehabilitation 66:19–31, 2000
9.
Tsang HWH, Leung AY, Chung RCK, et al.: Review on vocational predictors: a systematic review of predictors of vocational outcomes among individuals with schizophrenia: an update since 1998. Australian and New Zealand Journal of Psychiatry 44:495–504, 2010
10.
Bond GR: Supported employment: evidence for an evidence-based practice. Psychiatric Rehabilitation Journal 27:345–359, 2004
11.
Wehman P, Revell G, Brooke V: Competitive employment: has it become the “first choice” yet? Journal of Disability Policy Studies 14:163–173, 2003
12.
Waghorn G, Chant D, King R: Work-related subjective experiences, work-related self-efficacy, and career learning among people with psychiatric disabilities. American Journal of Psychiatric Rehabilitation 10:275–300, 2007
13.
Waghorn G, Chant D, White P, et al.: Delineating disability, labour force participation, and employment restrictions among persons with psychosis. Acta Psychiatrica Scandinavica 109:279–288, 2004
14.
Waghorn G, Chant D, Harris MG: The stability of correlates of labour force activity. Acta Psychiatrica Scandinavica 119:393–405, 2009
15.
Waghorn G, Chant D, Lloyd C, et al.: Labour market conditions, labour force activity and prevalence of psychiatric disorders. Social Psychiatry and Psychiatric Epidemiology 44:171–178, 2009
16.
Waghorn G, Chant D, Jonsdottir A: Comorbidity and labor force activity among people with psychiatric disorders. Journal of Occupational and Environmental Medicine 53:68–73, 2011
17.
Bond GR, Resnick SG, Drake RE, et al.: Does competitive employment improve nonvocational outcomes for people with severe mental illness? Journal of Consulting and Clinical Psychology 69:489–501, 2001
18.
Kukla M, Bond GR, Xie H: A prospective investigation of work and nonvocational outcomes in adults with severe mental illness. Journal of Nervous and Mental Disease 200:214–222, 2012
19.
Rosenheck R, Leslie D, Keefe R, et al.: Barriers to employment for people with schizophrenia. American Journal of Psychiatry 163:411–417, 2006
20.
Morgan VA, Waterreus A, Jablensky A, et al.: People Living With Psychotic Illness 2010. Report on the Second Australian National Survey of Psychotic Illness. Canberra, Australia, Department of Health and Aged Care, 2011
21.
McGurk SR, Mueser KT, Harvey PD, et al.: Cognitive and symptom predictors of work outcomes for clients with schizophrenia in supported employment. Psychiatric Services 54:1129–1135, 2003
22.
Bond GR, Drake RE: Predictors of competitive employment among patients with schizophrenia. Current Opinion in Psychiatry 21:362–369, 2008
23.
Bond GR, Drake RE, Becker DR: An update on randomized controlled trials of evidence-based supported employment. Psychiatric Rehabilitation Journal 31:280–290, 2008
24.
Bond GR, Drake RE, Becker DR: Generalizability of the Individual Placement and Support (IPS) model of supported employment outside the US. World Psychiatry 11:32–39, 2012
25.
Campbell K, Bond GR, Drake RE: Who benefits from supported employment? A meta-analytic study. Schizophrenia Bulletin 37:370–380, 2011
26.
Drake RE, Bond GR: IPS supported employment: a 20-year update. American Journal of Psychiatric Rehabilitation 14:155–164, 2011
27.
Michon HW, van Weeghel J, Kroon H, et al.: Person-related predictors of employment outcomes after participation in psychiatric vocational rehabilitation programmes—a systematic review. Social Psychiatry and Psychiatric Epidemiology 40:408–416, 2005
28.
Castle DJ, Jablensky A, McGrath JJ, et al.: The Diagnostic Interview for Psychoses (DIP): development, reliability and applications. Psychological Medicine 36:69–80, 2006
29.
Schedules for Clinical Assessment in Neuropsychiatry. Geneva, World Health Organization, 1999
30.
McGuffin PC, Farmer A, Harvey I: A polydiagnostic application of operational criteria in studies of psychotic illness: development and reliability of the OPCRIT system. Archives of General Psychiatry 48:764–770, 1991
31.
The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. Geneva, World Health Organization, 1993
32.
Standards for Social, Labour and Demographic Variables. Canberra, Australia Bureau of Statistics, 2010. Available at www.abs.gov.au/AUSSTATS/[email protected]/Lookup/1288.0Main+Features11996?OpenDocument. Accessed Dec 11, 2012
33.
Morosini PL, Magliano L, Brambilla L, et al.: Development, reliability and acceptability of a new version of the DSM-IV Social and Occupational Functioning Assessment Scale (SOFAS) to assess routine social functioning. Acta Psychiatrica Scandinavica 101:323–329, 2000
34.
Nafees B, van Hanswijck de Jonge P, Stull D, et al.: Reliability and validity of the Personal and Social Performance scale in patients with schizophrenia. Schizophrenia Research 140:71–76, 2012
35.
Patrick DL, Burns T, Morosini P, et al.: Reliability, validity and ability to detect change of the clinician-rated Personal and Social Performance scale in patients with acute symptoms of schizophrenia. Current Medical Research and Opinion 25:325–338, 2009
36.
An AB: Performing logistic regression on survey data with the new survey logistic procedure. Proceedings of the 27th Annual SAS Users Group International Conference, 2004. Available at www2.sas.com/proceedings/sugi27/p258-27.pdf
37.
Wewiorski NJ, Fabian ES: Association between demographic and diagnostic factors and employment outcomes for people with psychiatric disabilities: a synthesis of recent research. Mental Health Services Research 6:9–21, 2004
38.
Waghorn G, Collister L, Killackey E, et al.: Challenges to the implementation of evidence-based employment services in Australia. Journal of Vocational Rehabilitation 27:29–37, 2007
39.
Evaluation of Disability Employment Services (interim report). Canberra, Australia, Department of Education, Employment and Workplace Relations, 2012
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Cover: Marooned, by Howard Pyle, 1909. Oil on canvas. Delaware Art Museum, Museum Purchase, 1912.
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Published in print: April 2014
Published online: 15 October 2014
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