A Vocational Recovery Model for Young People With Mental Illness: A Pretest

Abstract

Purpose:

This research project aims to evaluate the potential effectiveness of a vocational recovery model promoting both vocational and personal recovery for young people with mental illness.

Methods:

In this study, a one group pre–posttest design was conducted, involving 37 young people with mental illness who received a vocational recovery program that consisted of a psychoeducation group on recovery, social skills and job-related skills training, 3-month job internship, and individual follow-up services. Standardized assessment tools were used for outcomes assessment at baseline, 3 months after treatment began, and 6 months after treatment began.

Results:

Results indicated that the participants showed improved competitive employment rates, personal recovery, and social support at follow-up assessments.

Conclusions:

The present study supports the feasibility and effectiveness of a vocational recovery model for young people with mental illness, suggesting the importance of integrating recovery framework and strategies into community-based vocational service.

Keywords

personal recovery vocational recovery vocational training young people with mental illness

Recent large-scale studies indicate that the past-week prevalence rate of mental disorder, including depression, anxiety, or psychosis, of young people aged 16–25 years is about 13–17% in Hong Kong and other Western societies (Chang et al., 2015; Lam et al., 2015; McManus, Meltzer, Brugha, Bebbington, & Jenkins, 2009). Young people with mental illness have been found to have a lower rate of economic participation and a higher unemployment rate than those without mental illness in Hong Kong and Western societies (Hong Kong Census and Statistical Department, 2014; Lloyd & Waghorn, 2007; Ramsay, Stewart, & Compton, 2012). For example, a survey in the United States indicated that the open employment rate of young people with severe mental illness was 37.8% which was much lower than the employment rate of 54% of young people without mental illness (Ramsay et al., 2012). Similarly, a survey in 2013 in Hong Kong showed that only one third (33.3%) of young people with mental illness were able to achieve open employment, while the unemployment rate of these individuals were 2.4 times of the unemployment rate of young people without mental illness (Hong Kong Census and Statistical Department, 2014). Unemployment results in negative outcomes of young people with mental illness including poorer mental health, lower level of functioning, financial hardship, decreased social support and community integration and (Ramsay et al., 2012). Without suitable assistance, the employment rate of young people with mental illness may further decline (Rinaldi et al., 2010), and many of them are at risk of lifelong exclusion from the workplace (Lloyd & Waghorn, 2007).

Despite of having mental illness, many young people with mental illness are highly motivated to seek for employment (Bond, Drake, & Luciano, 2015; Rinaldi et al., 2010). Achieving competitive employment is associated with various positive outcomes for young people with mental illness including improved self-esteem, greater well-being, greater social contact and independence, and reduced use of community mental health services (Fossey & Harvey, 2010; Modini et al., 2016). Subsequently, achieving competitive employment is regarded as an important element of recovery in Hong Kong and Western societies (Lloyd & Waghorn, 2007; Rinaldi et al., 2010; Tsang, Fung, Leung, Li, & Cheung, 2010; Wong et al., 2008; K. W. Young, Ng, & Pan, 2014, 2017).

What is recovery? And what is vocational recovery? Is vocational recovery equivalent to recovery? According to a U.S. national consensus statement, recovery is defined as a “journey of healing and transformation enabling a person with a mental health problem to live a meaningful life in a community of his or her choice while striving to achieve his or her full potential” (Substance Abuse and Mental Health Service Administration, 2003, p. 1). Nevertheless, various other definitions of recovery have been proposed, and there is no single agreed definition of recovery (Færden, Nesvåg, & Marder, 2008). In general, the literature has defined and focused on recovery as process/personal recovery or recovery as outcome/clinical recovery. Studies regarding recovery as process define recovery as a way of living a satisfying, hopeful, and contributing life, even with the limitations caused by mental illness (Davidson, Sells, Sangster, & O’Connell, 2005; Leamy, Bird, Le Boutillier, Williams, & Slade, 2011). Additionally, this approach has suggested essential components of personal recovery such as self-direction, individualized and person centered, empowerment, holistic, nonlinear, strengths based, peer support, respect, responsibility, and hope (Substance Abuse and Mental Health Service Administration, 2003). Studies defining recovery as outcome tend to focus on symptomatic reduction and improvement in functioning (Rodgers, Norell, Roll, & Dyck, 2007). This approach recommends evidenced-based interventions to facilitate clinical recovery including medication, supported employment, family psychoeducation, assertive community treatment program, illness self-management skills, and integrated treatments for mental illness and substance abuse (Drake et al., 2001). Rather contrasting these two approaches on recovery, these two approaches can be complement with each other. In fact, recovery has been regarded as a complex process and a full recovery involves different dimensions of recovery by researchers (Whitley & Drake, 2010) including personal, symptomatic, physical, social, and vocational recovery. In this study, the above concept of full recovery is adopted which involves personal, symptomatic, physical, social, and vocational recovery. Additionally, vocational recovery is defined as achieving competitive employment, while personal recovery is defined as a way of living a satisfying, hopeful, and contributing life, even with the limitations caused by mental illness.

Various vocational training models have been developed to enhance vocational recovery and outcomes for young people with mental illness (Fossey & Harvey, 2010; Lloyd & Waghorn, 2007; Rinaldi et al., 2010). In particular, individual placement and support model, which is a particular model of supported employment, has been found to be effective in helping young people with mental illness to find and sustain competitive employment, that is, achieving vocational recovery, in Hong Kong and Western societies (Baksheev, Kelly, Jackspon, McGorry, & Killackey, 2012; Bond, Drake, & Becker, 2012; Bond, Drake, & Campbell, 2016; Bond et al., 2015; Modini et al., 2016; Rinaldi et al., 2010; Tsang et al., 2010; Wong et al., 2008). For example, a recent review of research studies on individual placement and support model showed that the employment rate of young people with mental illness receiving individual placement and support model yield was twice as those in the control group who received treatment as usual (Bond et al., 2016). However, many outcomes studies of individual placement and support model focus narrowly on vocational outcomes, in particular, employment rate, but pay little attention on nonvocational outcomes such as sense of hope, empowerment and self-direction, and so on. Thus, whether individual placement and support model is effective in promoting both personal recovery and vocational recovery remains unclear as little research has been conducted in this area. Furthermore, little research has explored those vocational service models that are effective in enhancing both the vocational and personal recovery of young people with mental illness.

Moreover, the relationship between vocational recovery and personal recovery has been the focus among researchers (Connell, King, & Crowe, 2011). In particular, whether vocational recovery is a prerequisite for personal recovery remains controversial among researchers. While some researchers advocate that vocational recovery contributes to better personal recovery (Drake & Whitley, 2014; Lloyd, King, & Moore, 2010), this notion is not supported by others (Connell et al., 2011). For example, in a cross-sectional survey of 161 people with mental illness, those achieving open employment reported a higher level of personal recovery (Lloyd et al., 2010). However, in another cross-sectional survey of 344 people with mental illness, those achieving open employment and those unemployed did not show significant difference in their level of personal recovery (Connell et al., 2011). As the available findings in this area remain inconclusive, more research studies are needed.

Recovery is found to be relevant to Chinese people with mental illness and plays a significant role in the rehabilitation outcomes of these individuals (Chiu, Ho, Lo, & Yiu, 2010; Siu et al., 2012; K. W. Young et al., 2017; K. W. Young, Ng, Pan, Fung, & Cheng, 2016). However, as the research studies and service development on the recovery of people with mental illness in Hong Kong and other Chinese societies are in a beginning stage (Tse, Siu, & Kan, 2013), little research has explored effective interventions for promoting the personal and vocational recovery of young people with mental illness in Chinese society. This research project thus aims to develop and to evaluate the effectiveness of a newly developed vocational recovery model to promote vocational recovery and personal recovery of young people with mental illness in a Chinese society.

A New Vocational Recovery Model

Those researchers regarding recovery as a process have developed knowledge on the stages of recovery (Andersen, Caputi, & Oades, 2006; Ralph, 2005; Spaniol, Wewiorski, Gagne, & Anthony, 2002; S. L. Young & Ensing, 1999). For example, Andersen et al. (2006) have developed a five-stage model of recovery. During the first phase of moratorium, consumers experienced a profound sense of loss, hopelessness, and identity confusion. The second stage, awareness, involved realization that all was not lost and that a fulfilling life was possible. The third stage, preparation, involved developing recovery skills. The fourth stage, rebuilding, involved hard work of recovery including setting meaningful goals and taking control on one’s life. The last stage, growth, was characterized by living a full and meaningful life, self-management on the illness, and a positive sense of self. These theoretical models on the stages of recovery share many similarities. In particular, as clients moved through these stages, they worked on the following tasks: having better understanding on their mental illness, managing the disability, developing skills, and involving in productive and meaningful roles.

By adapting the above theoretical models on the stages of recovery, the writers have developed a new vocational recovery model and applied it into an existing community-based vocational training program for young people with mental illness, named Sunnyway. The Sunnyway, which is fully funded by the local government, provides job-related counseling, employment training, job attachment, job trial, and postplacement service (Hong Kong Social Welfare Department, 2017). Due to the limitation of funding, the number of clients receiving the Sunnyway service provided by the nonprofit social service organization involved in this study is limited to 15 clients each year. Under the support of the local nonprofit social service organization, the service content of a Sunnyway project provided by that social service organization is modified by adopting the newly developed vocational recovery model and related intervention strategies.

This new vocational recovery model consists of a four-stage vocational service: gaining knowledge in recovery, skill building, overcoming challenges in employment, and achieving open employment.

At the beginning stage, clients gain knowledge on personal recovery through a psychoeducation group, which aims to equip clients with knowledge on personal recovery and essential elements to achieve personal recovery such as social support, hope, nonlinear recovery process, symptom management, related coping strategies, and resources. Also, clients learn and practice various skills and strategies to enhance their symptom management skills including relaxation, distraction, healthier life style, drug compliance, and coping with medication side effects, and so on. Additionally, the psychoeducation group facilitates mutual support among clients, which was believed to be an essential element for personal recovery.

At the second stage of skill building, each participant receives two aspects of skill trainings: social skills and job-related skills training. Social skills training covers communication skills, teamwork skills, and interviewing skill. Job-related skill training includes use of computer software, language enhancement, job-seeking skills, orientation visits to social enterprises and private business organizations, and so on. At this stage, clients can complete these training workshops and courses according to their own pace of learning and own schedules.

At the third stage of overcoming challenges in employment, each participant is arranged to have 3-month full-time job internship at a nonprofit social service organization with monthly subsidization provided by the government. During the job internship, each participant receives guidance on work-related skills from a supervisor of his or her work setting. Additionally, a social worker, who act as a case manager, provides weekly contact, support, and guidance for clients, especially on work habit, work attitude, teamwork, stress management, and emotional regulation.

At the final stage, after completing the job internship, clients start to seek competitive employment in the open job market and receive regular follow-up service provided by the case manager. While the focus of the follow-up service is to help clients to find and sustain competitive employment, the social worker complies with the recovery-oriented practice with an emphasis on respecting clients’ choices and own goals.

Research Design

In this study, a one group pre–posttest design was used due to the difficulties in recruiting clients for a control group. Clients were recruited from a community-based vocational service run by the local nonprofit social service organization involved. Clients who gave their consent to participate in this research project were assigned to the newly developed vocational recovery model. Each client was followed naturalistically for 6 months. Standardized assessment tools were used for data collection at baseline, 3 months after treatment began (t2), and 6 months after treatment began (t3). Data collection was started in 2013 and completed in 2016.

Client Inclusion Criteria

In this study, the inclusion criteria were (a) being aged 15–29 years, (b) receiving a diagnosis of a mental disorder according to Diagnostic and Statistical Manual of Mental Disorder (5th ed.; American Psychiatric Association, 2013), and (c) receiving community-based mental health services from the local nonprofit social service organization involved.

Vocational Recovery Model

In addition to receiving the treatment as usual at the community-based psychiatric clinic, clients received the vocational recovery model with the following service components: psychoeducational group on personal recovery, social, and job-related skill training; 3-month job internship; and pursuing open employment with regular follow-up provided by the case manager.

Aims and Hypotheses

This research project thus aims to evaluate the effectiveness of the above newly developed vocational recovery model in Hong Kong and explore whether or not vocational recovery contribute to the personal recovery. This study has the following hypotheses.
Hypothesis 1: The vocational recovery model is effective in improving the vocational recovery of young people with mental illness. Specifically, it is hypothesized that, after receiving the vocational recovery service for 6 months, the employment rate of client is significantly higher than the baseline employment rate.

Hypothesis 2: The vocational recovery model is effective in improving the personal recovery of young people with mental illness. Specifically, it is hypothesized that clients show significant higher scores of assessment scale on personal recovery at 3-month and 6-month follow-up, respectively.

Hypothesis 3: The vocational recovery model is effective in improving the social support and hope of young people with mental illness. Specifically, it is hypothesized that clients show significant better scores of assessment scales on social support and hope at 3-month and 6-month follow-up, respectively.

Hypothesis 4: Vocational recovery is not a prerequisite for personal recovery. Specifically, it is hypothesized that personal recovery is not related to and predicted by vocational recovery.

Outcome Assessment Tools

The primary outcomes were personal recovery and vocational recovery, while the secondary outcomes were social support and hope. We used the following measures to operationalize these constructs.

Vocational recovery refers to an individual achieving paid full- or part-time competitive employment at any point during the 6-month follow-up period (t3). Please also note that, at 3-month follow-up, clients were still receiving the 3-month full-time job internship and were not expected to seek for competitive employment in the open job market. Thus vocational recovery and vocational status of clients at t2 were not counted.

The Mental Health Recovery Measure (MHRM) is a 30-item self-administered measure designed to assess the eight elements of personal recovery for individuals living with mental illnesses including overcoming stuckness, self-empowerment, learning and self-redefinition, basic functioning, overall well-being, new potentials, spirituality, and advocacy (Bullock, 2005; S. L. Young & Bullock, 2003). The MHRM is scored using a 5-point Likert-type scale (0–4) for each item. The scores are summed over the items such that higher scores indicate better personal recovery. The internal reliability (Cronbach’s α = .93), test–retest reliability (Cronbach’s α = .92), and validity of the MHRM have been shown to be good (Campbell-Orde, Chamberline, Carpenter, & Leff, 2005; S. L. Young & Ensing, 1999). The Chinese version has demonstrated high internal consistency reliability (Cronbach’s α = .92 to .96; Ye, Pan, Wong, & Bola, 2013).

The Multidimensional Scale of Perceived Social Support (MSPSS) is a 12-item self-administered psychometric scale for the measurement of perceived social support. It addresses respondents’ relationships with sources of support (e.g., family, friends, and significant others; Zimet, Dahlem, Zimet, & Farley, 1988). Each item is rated on a 7-point scale ranging from 1 (strongly disagree) to 7 (strongly agree). The scores are summed over the items such that higher scores indicate better perceived social support. The Chinese version of the MSPSS has demonstrated high internal consistency reliability (Cronbach’s α = .89 to .92; Chiu et al., 2010; Chou, 2000).

The Adult State Hope Scale (ASHS) is a 6-item self-administered scale that was developed to assess an individual’s hope trait levels, particularly their optimism in achieving their goals (Snyder et al., 1996). Each item is rated on an 8-point scale ranging from 1 (definitely false) to 8 (definitely true). The scores are summed over the items such that higher scores indicate higher levels of hope. It has been shown that the Cronbach’s αs are .79 to .95 (Snyder et al., 1996) and that the test–retest correlations are between .48 and .93 (Lopez, Ciarlelli, Coffman, Stone, & Wyatt, 2000). The Chinese version has demonstrated satisfactory internal consistency reliability (Cronbach’s α = .78; Chiu et al., 2010).

Data Analyses

All data analyses were performed using SPSS Version 22.0 (IBM, 2013). For all analyses, two-tailed p values of <.05 indicated statistical significance. The baseline demographic and clinical characteristics between those who completed all the services provided by the vocational recovery model (completers) and those who lost follow-up (noncompleters) were compared by using χ² tests for the categorical variables and independent t test for continuous variables. A paired t test was used to analyze the significant changes in assessment scores on MHRM, ASHS, and MSPSS between the t1, t2, and t3 periods. Also, repeated-measures one-way analysis of variance (ANOVA) was conducted to compare assessment scores on MHRM, ASHS, and MSPSS at t1, t2, and t3 periods. The effect size for the paired t tests was calculated using Cohen’s d, in which values of .2, .5, and .8 indicated small, moderate, and large effects, respectively (Cohen, 1988). The effect sizes for the ANOVA were calculated using the partial η², in which values of .01, .06, and .14 were considered small, moderate, and large effects, respectively (Cohen, 1988).

Those variables relating to the improvement of personal recovery were identified using one-way ANOVA for categorical variables and Spearman’s correlation analysis for continuous variables due to the small sample size. On the other hand, as vocational recovery is a binary variable (i.e., yes or no), variables relating to vocational recovery were identified using one-way ANOVA for continuous variables and χ² tests for categorical variables. In identifying the predicting variables for personal recovery and improvement in personal recovery, multiple linear regression analyses were conducted with the MHRM score at t3 and change in the MHRM score included as the dependent variables, and their related variables, but excluding baseline MHRM score, were the independent variables. A stepwise selection method was adopted to compare the relative importance of the individual variables in predicting MHRM score at t3 and change in the MHRM score. The collinearity of each regression model was examined using a variance inflation factor (VIF); a VIF less than 10 was considered to be noncollinear. To identify the variables predicting vocational recovery, a multivariate logistic regression analysis was conducted, with vocational recovery included as the dependent variable and its related variables included as the independent variables.

Ethical Considerations

The ethical considerations of this study were evaluated and approved by the research committee of the nonprofit social service organization involved. Please name the organization, unless you are required to not do so. Written informed consent was obtained from all clients on the day of the pretreatment assessment.

Research Results

A total of 45 young people with mental illness were recruited from the community-based vocational service involved, and finally 37 of these individual received the vocational recovery program. Three clients lost follow-up at 3-month follow-up, while additional four clients lost follow-up at the 6-month follow-up. Thus, this study involved 30 completers and 7 noncompleters. Figure 1 illustrates the flow of clients through each stage of the study.

Figure 1.
Flow of participants through each stage of the study.

Characteristics of Clients

The demographic and clinical characteristics of the clients, including completers and noncompleters, are shown in Table 1. Independent t test and χ² analyses showed no significant difference between the 30 completers and the 7 noncompleters in all baseline demographic variables as well as baseline assessment scores on personal recovery and hope. The only difference between the completers and the noncompleters was that the noncompleters had significant lower level of baseline social support as assessed by MSPSS. Additionally, these seven noncompleters gave rise to an attrition rate of 18.92%. These noncompleters did not give any prior notice nor reason for losing follow-up, which is perhaps the common characteristic of youngsters in the local society. Thus, the missing data can be assumed as missing at random. In order to maintain the full sample for data analysis, prior to data analysis, multiple imputation method was used to replace missing data.

Table 1.
Participants’ Baseline Demographics and Clinical Characteristics.

Completers (N = 30) NonCompleters (N = 7) Total (N = 37) F (p)

Variables n (%) n (%) n (%)

Gender^a

Male 18 (60.00) 4 (57.1) 22 (59.46) .019 (.890)

Female 12 (40.00) 3 (42.9) 15 (40.54)

Education^a .493 (.781)

University 8 (26.67) 2 (28.57) 10 (27.03)

Secondary school 20 (66.67) 5 (71.43) 25 (67.57)

Others 2 (6.66) 0 (0.00) 2 (5.40)

Marital status^a

Single 30 (100) 7 (100) 37 (100) NA

Living arrangement^a

With family members 30 (100) 7 (100) 37 (100) NA

Diagnosis^a 3.753 (.808)

Schizophrenia and psychosis 13 (43.33) 4 (57.14) 17 (45.95)

Depression 4 (13.33) 0 (0.00) 4 (10.81)

Bipolar disorder 3 (10.00) 0 (0.00) 3 (8.11)

Anxiety 4 (13.33) 1 (14.30) 5 (13.51)

Others 6 (20.00) 2 (28.57) 8 (21.62)

Was previously being employed?^a 0.010 (.919)

Yes 8 (26.67) 2 (28.57) 10 (27.03)

Being employed at baseline?^a 0.442 (.506)

Yes 2 (6.66) 0 (0.00) 2 (5.41)

M (SD) M (SD) M (SD) F (p)

Age^b 22.23 (2.43) 23.57 (1.51) 22.49 (2.35) 1.386 (.174)

Number of family member^b 3.52 (0.83) 3.57 (1.62) 3.53 (1.00) 0.127 (.900)

MHRM^b 78.47 (18.74) 73.99 (15.74) 77.89 (18.27) 0.584 (.563)

MSPSS^b 57.10 (14.28) 44.14 (16.95) 54.65 (15.45) 2.090 (.044)*

ASHS^b 29.27 (10.05) 29.14 (8.24) 29.24 (9.63) 0.030 (.976)

Note. MHRM = Mental Health Recovery Measure; MSPSS = Multidimensional Scale of Perceived Social Support; ASHS = Adult State Hope Scale.

^aPearson χ². ^bIndependent sample t test.

*Significant at p < .05. **Significant at p < .01.

Taking together, most of the clients were male (59.5%, n = 22) and had achieved a secondary school education level or above (94.6%, n = 35). The mean age was 22.44 years (SD = 2.35). All clients were single and living with their family members, and the mean number of family members was 3.53 (SD = 1.00). Nearly half (46.0%, n = 17) of the clients were diagnosed with schizophrenia or psychosis, followed by anxiety disorders (13.5%, n = 5), depression (10.8%, n = 4), and bipolar (8.1%, n = 3).

Baseline Assessment Scores

Nearly three quarters (72.9.5%, n = 27) of clients did not have any previous employment experience. Among those who had previous employment experiences (n = 10), about one third (30.0%, n = 3) engaged in a full-time competitive job for less than 3 months, while the rest (70.0%, n = 7) engaged in a part-time competitive job with an average of 5.4 working hours per day. At baseline and just before joining the vocational recovery model, two clients (5.4%) engaged in a part-time job with an average of 6 working hours per day. Additionally, clients reported a moderate level of MHRM (M = 77.63, SD = 18.10), a moderate level of MSPSS (M = 54.65, SD = 15.45), and a moderate level of ASHS (M = 29.24, SD = 9.63).

Treatment Outcomes

Hypothesis 1 vocational recovery

The results indicated that, after receiving vocational service for 6 months, the percentage of clients achieving competitive employment increased significantly, from 5.4% (n = 2) at baseline (t1) to 32.4% (n = 12) at t3 (McNemar test < .01).

Hypothesis 2 personal recovery

Tables 2 and 3 summarize the change in the MHRM scores. The results of a paired t test demonstrated that the clients showed significant improvement in their MHRM score from t1 to t2, which increased from 77.63 (SD = 17.97) at t1 to 82.79 (SD = 15.41) at t2 (t = 2.17, p < .05; 95% confidence interval [CI] [0.035, 8.29]), with a small to moderate effect size (Cohen’s d = .36). Then MHRM score showed nonsignificantly declined to 77.84 (SD = 17.97) at t3. Additionally, the repeated-measures ANOVA showed that the change of MSPSS score from t1 to t3 was nonsignificant (F = 1.93, p > .05).

Table 2.
Repeated-Measures Analysis of Variance (ANOVA) on Outcome Measures.

t1 t2 t3 F p

Mean (SD) Mean (SD) Mean (SD)

MHRM 77.63 (18.10) 82.79 (15.41) 77.84 (17.97) 2.885 .062 (ns)

MSPSS 54.50 (15.45) 60.33 (12.24) 59.66 (15.28) 3.643 .031*

ASHS 29.24 (9.63) 31.11 (7.13) 29.64 (7.90) 0.775 .464 (ns)

Note. ns = not significant; F = repeated-measure ANOVA; t1 = baseline; t2 = 3rd-month follow-up; t3 = 6th-month follow-up; MHRM = Mental Health Recovery Measure; MSPSS = Multidimensional Scale of Perceived Social Support; ASHS = Adult State Hope Scale.

*Significant at p < .05. **Significant at p < .01.

Table 3.
Paired Sample t Test on Outcome Assessment Scores.

Variables t (p) t (p) 95% CI of the Change Score Cohen’s d

MHRM

t1–t2 4.97 2.165 (.030)* [0.470, 9.474] .356

t2–t3 −4.47 −1.782 (.075) [−9.392, 0.446] −.293

t1–t3 0.50 0.192 (.848) [−4.592, 5.590] .032

MSPSS

t1–t2 5.69 2.436 (.015)* [0.112, 10.267] .401

t2–t3 −0.74 −0.345 (.730) [−4.969, 3.485] −.57

t1–t3 4.95 1.998 (.046)* [0.093, 9.802] .328

ASHS

t1–t2 1.71 1.030 (.303) [−1.539, 4.949] .169

t2–t3 −1.10 −0.787 (.431) [−3.832, 1.638] .129

t1–t3 0.61 0.423 (.673) [−2.211, 3.427] .070

Note. F = repeated-measure analysis of variance; t1 = baseline; t2 = 3rd-month follow-up; t3 = 6th-month follow-up; MHRM = Mental Health Recovery Measure; MSPSS = Multidimensional Scale of Perceived Social Support; ASHS = Adult State Hope Scale; CI = confidence interval.

*Significant at p < .05. **Significant at p < .01.

Hypothesis 3 social support and hope

Tables 2 and 3 summarize the change in the MSPSS and ASHS scores. The results of a paired t test demonstrated that clients showed significant improvements in their MSPSS scores, which increased significantly, from 54.65 (SD = 15.45) at t1 to 60.33 (SD = 12.24) at t2 (t = 2.03, p = .05; 95% CI [0.112, 10.267]), with a moderate effect size (Cohen’s d = .40). Then MSPSS score showed nonsignificantly declined to 59.66 (SD = 15.28) at t3. Additionally, the repeated-measures ANOVA showed that the improvement of MSPSS score from t1 to t3 was significant (F = 3.64, p < .05), with a moderate effect size (partial η² = .09).

On the other hand, the results of a paired t test and repeated-measures ANOVA indicated that clients did not show any significant improvement in the ASHS score from t1 to t2, t2 to t3, and t1 to t3.

Hypothesis 4 factors related to and predicting personal and vocational recovery

Factors related to personal recovery

Table 4 summarizes those variables related to the personal recovery and vocational recovery of the treatment group. The results indicated that the MHRM score at t3 (MHRMt3) was related to the baseline MHRM score (ρ = .65, p < .01), baseline MSPSS score (ρ = .56, p < .01), baseline ASHS score (ρ = .54, p < .01), and gender (ρ = .45, p < .05). The improvement in the MHRM score from t1 to t2 (ΔMHRMt1_t2) was related to the improvement in the ASHS score from t1 to t2 (ΔASHSt1_t2; ρ = .70, p < .05), the improvement in the MSPSS score from t1 to t2 (ΔMSPSSt1_t2; ρ = .38, p < .05), baseline ASHS score (ρ = −.65, p < .01), baseline MSPSS score (ρ = −.33, p < .05), baseline MHRM score (ρ = −.63, p < .01), and gender (ρ = 5.43, p < .05). Interestingly, the MHRMt3 and ΔMHRMt1_t2 were not related to vocational recovery, that is, achieving competitive employment at t3 as well as baseline employment and employment history.

Table 4.
Correlation Between Personal Recovery, Recovery Outcome, and Demographic and Outcomes Variables.

Variables Vocational Recovery MHRMt3 ΔMHRMt2_t1

χ^2a p Value F ^b p Value F ^b p Value

Sex 0.383 .536 0.453 .040* 5.425 .026*

Diagnosis 2.904 .407 1.412 .252 0.702 .558

Education level 0.311 .856 0.530 .593 2.151 .132

Having employment history 0.110 .740 2.820 .102 0.962 .333

Having employment at baseline 0.298 .585 0.150 .701 0.149 .702

Achieving competitive employment at t3 (vocational recovery) 1.00 — 1.439 .251 1.355 .279

F ^b p value ρ^c p value ρ^c p value

Age 0.016 .902 −0.144 .414 0.307 .067

MHRMt1 0.988 .327 0.648 .000 −0.625 .000

MSPSSt1 2.685 .110 0.564 .000** −0.333 .044*

ASHSt1 1.762 .193 0.536 .000 −0.652 .000

ΔMHRMt1_t2 0.007 .933 −0.323 .064 − −

ΔMSPSSt1_t2 0.812 .374 −0.087 .616 0.383 .019*

ΔASHSt1_t2 0.014 .906 −0.258 .146 0.702 .000**

Note. ρ = Spearman’s ρ; t1 = baseline; t2 = 3rd-month follow-up; t3 = 6th-month follow-up; MHRM = Mental Health Recovery Measure; MSPSS = Multidimensional Scale of Perceived Social Support; ASHS = Adult State Hope Scale; MHRMt1 = baseline MHRM score; MSPSSt1 = baseline MSPSS; ASHSt1 = Baseline Adult State Hope Scale; ΔMHRMt1_t2 = change of MHRM score from t1 to t2; ΔMSPSSt1_t2 = change of MSPSS score from t1 to t2; ΔASHSt1_t2 = change of ASHS score from t1 to t2.

^aPearson χ². ^bAnalysis of variance. ^cSpearman correlation analysis.

*Significant at p < .05. Significant at p < .01.

Factors related to vocational recovery

Vocational recovery was found to be unrelated to all demographic and outcome measures including baseline MHRM score, baseline MSPSS score, baseline ASHS score, ΔMHRMt1_t2, ΔASHSt1_t2, and ΔMSPSSt1_t2 (see Table 4).

Factors predicting personal recovery

Table 5 shows the stepwise multiple linear regression analyses of MHRMt3 and ΔMHRMt1_t2. The collinearity is verified, and the collinearity statistics suggest that collinearity can be neglected for all of the regression models (VIF < 10).

Table 5.
Stepwise Multiple Linear Regression Analysis on Personal Recovery.

Model Predictor Adj. R² B β Significance F Significance Collinearity Statistics

Tolerance VIF

Multiple linear regression for personal recovery at t3

Dependent variable: MHRMt3

1 (Constant) 0.254 44.541 .000 12.23 .001

MSPSS 0.609 .542 .001 1 1

2 (Constant) 0.322 36.083 .000 4.504 .041

MSPSS 0.438 .377 .010** 0.797 1.255

ASHS 0.609 .326 .038* 0.797 1.255

Multiple linear regression for improvement of personal recovery from t1 to t2

Dependent variable: ΔMHRMt1_t2

3 (Constant) 0.599 3.142 .038* 54.812 .000

ΔASHSt1_t2 1.074 0.781 .000 1 1

4 (Constant) 0.656 20.829 .002** 6.804 .013*

ΔASHSt1_t2 0.906 0.663 .000 0.824 1.213

MHRMt1 −0.224 −0.281 .008 0.824 1.213

Note. Adj. R² = adjusted R²; t1 = baseline; t2 = 3rd-month follow-up; t3 = 6th-month follow-up; MHRM = Mental Health Recovery Measure; MSPSS = Multidimensional Scale of Perceived Social Support; ASHS = Adult State Hope Scale; ΔMHRMt1_t2 = change of MHRM score from t1 to t2; ΔASHSt1_t2 = change of ASHS score from t1 to t2; VIF = variance inflation factor.

*Significant at p < .05. **Significant at p < .01.

The regression model for MHRMt3 explains 32.2% of its total variance. The baseline MSPSS score is the strongest predictor of MHRMt3 and contributes to 25.4% of its total variance, while the pretreatment ASHS score contributes to 6.8% of the total variance of the MHRMt3.

The regression model of ΔMHRMt1_t2 explains 65.6% of its total variance. The ΔASHSt1_t2 is the strongest predictor of ΔMHRMt1_t2 and contributes to 59.9% of its total variance, while the baseline MHRH score contributes to 5.7% of the total variance of the ΔMHRMt1_t2.

Factors predicting vocational recovery

As vocational recovery was found to be unrelated to all demographic and outcome measures, no predictors could be found. It seemed that participating in the vocational recovery was the only factor apparently contributing to vocational recovery.

Discussion and Application to Practice

In this study, clients’ baseline MHRM score was 76.63 (SD = 18.10), which was comparable to that reported in a previous study in Western societies (Bullock, 2005) but slightly higher than that reported (M = 68.8; SD = 20.7) in a previous study performed in Hong Kong (Ye et al., 2013). The difference in the MHRM scores is probably due to the difference in the illness severity of the studied subjects. Compared with the previous study performed in Hong Kong (Ye et al., 2013), the clients in the present study were younger in age, and fewer subjects had received a diagnosis of schizophrenia.

Consistent with the Hypothesis 1, the present study demonstrates that the vocational recovery model improves vocational recovery significantly for young people with mental illness. Specifically, the vocational recovery model yields a significant higher employment rate for clients at 6-month follow-up than at baseline. Hypothesis 2 is partially supported because the paired t tests and repeated-measures ANOVA demonstrate that the vocational recovery model improves personal recovery of clients significantly from baseline to 3-month follow-up, but not from baseline to 6-month follow-up. Similarly, Hypothesis 3 is partially supported because the paired t tests and repeated-measures ANOVA demonstrate that clients showed significant improvement in social support score at 3-month and 6-month follow-up. However, the clients’ sense of hope remained unchanged from baseline to 3-month follow-up as well as from baseline to 6-month follow-up. In sum, this study demonstrates that the vocational recovery model improves vocational recovery at 6-month follow-up, improves personal recovery at 3-month follow-up, and improves social support at 3-month and 6-month follow-up and thus supports the feasibility and effectiveness of the vocational recovery model for young people with mental illness in the context of a Chinese society. As this research study is one of few to support the feasibility and effectiveness of recovery-oriented community-based vocational services to improve both the vocational and personal recovery of young people with mental illness, more research studies are needed to further validate this research in other cultures and societies. Nevertheless, as suggested by these present research results, it is feasible and worthwhile to integrate strategies to promote personal recovery into existing community-based vocational service models.

Consistent with the Hypothesis 4, the present study shows that personal recovery is not significantly related to vocational recovery and that personal recovery and vocational recovery are related to and predicted by different factors. These research findings have several implications for community-based vocational services. First, personal and vocational recovery should be viewed as independent and different outcomes for community-based vocational services, and thus, it is important to include both personal and vocational recovery as important treatment outcome measures for community-based vocational services.

Second, vocational recovery is not a prerequisite for personal recovery. In particular, as shown in this study, attaining competitive employment is not a necessary condition for improving personal recovery for clients, which is supported by a previous study (Connell et al., 2011). Rather, personal recovery and vocational recovery are predicted by different factors, and thus, community-based vocational services should adopt different strategies to facilitate personal and vocational recovery, respectively.

Third, the present research results indicate that vocational recovery for young people with mental illness is not predicted by almost all demographic and clinical variables, which is supported by a previous research study (Baksheev et al., 2012). This finding suggests that service components of the vocational service are the only significant elements facilitating vocational recovery for young people with mental illness (Baksheev et al., 2012). According to our observations, skills training and job internship of this vocational recovery model may contribute to the vocational recovery of young people with mental illness. Anyway, more research study is needed in this area.

Fourth, as shown in this study, personal recovery is related to and predicted by baseline perceived social support and baseline sense of hope, while the improvement in personal recovery is related to the improvement in perceived social support and sense of hope, which are consistent with previous research findings (Davidson et al., 2005; Fossey & Harvey, 2010; Leamy et al., 2011; Rianldi et al., 2010). These findings suggest that improving social support and inducing a sense of hope are important elements and strategies for community-based vocational services to promote personal recovery for young people with mental illness. In particular, the psychoeducational group of this recovery-orientated vocational training model can improve the social support of clients significantly up to 6-month follow-up, suggesting that group intervention is a good component to enhance social support and personal recovery for young people with mental illness. However, as shown in this study, the treatment group clients only showed nonsignificant improvement in their sense of hope, suggesting that more efforts are needed to induce the sense of hope for clients in order to facilitate their personal recovery.

Additionally, the nonsignificant decline in outcome assessment scores on personal recovery, social support, and hope from 3-month follow-up to 6-month follow-up draws our concern. From 3-month follow-up to 6-month follow-up, clients completed the first three stages of service, including psychoeducational group on personal recovery, social, and job-related skill training and 3-month job internship and moved to pursue open employment with regular follow-up provided by the case manager. The declines in outcome assessment scores reflected that the follow-up service provided by case manager may need to be strengthened. Or additional interventions and supports need to be provided for clients during the final stage of pursuing competitive employment in open job market. More research study is needed in this area.

Several methodological limitations of this pilot study require attention. First, the generalizability of the research results is limited by the small sample size, the use of a convenience sample of clients, and the lack of a control group for comparison. Second, an attribution rate of 18.9% reported in this study may give rise to biased estimation of intervention effects. Nevertheless, this attribution rate is still below the warning attribution rate of 20% (Dumville, Torgerson, & Hewitt, 2006), and the close similarities between the completers and the noncompleters in almost all baseline characteristics can help to minimize any bias to the research results. Third, in this study, vocational recovery is regarded as attaining paid full- or part-time competitive employment at any point during the 6-month follow-up period, reflecting the fact that vocational services in Hong Kong focus narrowly on helping clients to attain competitive employment and fails to consider entering full-time education as a vocational outcome. Thus, it is better for future research studies to define vocational recovery as the attainment of competitive employment or full-time education at any point during the 6-month follow-up period, as advocated by previous research studies in Western societies (Baksheev et al., 2012; Bond et al., 2015). Fourth, although skill training and job internship are suggested to be effective and essential elements for vocational recovery, no standardized assessment tools have been adopted to assess these components in this study. In the future, it would be better to conduct a larger scale randomized control study to further validate the effectiveness and essential components of the vocational recovery model in promoting personal and vocational recovery for young people with mental illness.

The present study provides evidences to support the feasibility and effectiveness of a new vocational recovery model in improving both personal recovery and vocational recovery for young persons with mental illness. Thus, it is important for community-based vocational services to adopt a recovery framework and strategies to promote both personal and vocational recovery in existing vocational services for young people with mental illness. Moreover, as vocational and personal recovery are related to and predicted by different factors, different strategies should be adopted, respectively, in community-based vocational services to promote personal and vocational recovery.

	Completers (N = 30)	NonCompleters (N = 7)	Total (N = 37)	F (p)
Gender^a
Male	18 (60.00)	4 (57.1)	22 (59.46)	.019 (.890)
Female	12 (40.00)	3 (42.9)	15 (40.54)
Education^a				.493 (.781)
University	8 (26.67)	2 (28.57)	10 (27.03)
Secondary school	20 (66.67)	5 (71.43)	25 (67.57)
Others	2 (6.66)	0 (0.00)	2 (5.40)
Marital status^a
Single	30 (100)	7 (100)	37 (100)	NA
Living arrangement^a
With family members	30 (100)	7 (100)	37 (100)	NA
Diagnosis^a				3.753 (.808)
Schizophrenia and psychosis	13 (43.33)	4 (57.14)	17 (45.95)
Depression	4 (13.33)	0 (0.00)	4 (10.81)
Bipolar disorder	3 (10.00)	0 (0.00)	3 (8.11)
Anxiety	4 (13.33)	1 (14.30)	5 (13.51)
Others	6 (20.00)	2 (28.57)	8 (21.62)
Was previously being employed?^a				0.010 (.919)
Yes	8 (26.67)	2 (28.57)	10 (27.03)
Being employed at baseline?^a				0.442 (.506)
Yes	2 (6.66)	0 (0.00)	2 (5.41)
	M (SD)	M (SD)	M (SD)	F (p)
Age^b	22.23 (2.43)	23.57 (1.51)	22.49 (2.35)	1.386 (.174)
Number of family member^b	3.52 (0.83)	3.57 (1.62)	3.53 (1.00)	0.127 (.900)
MHRM^b	78.47 (18.74)	73.99 (15.74)	77.89 (18.27)	0.584 (.563)
MSPSS^b	57.10 (14.28)	44.14 (16.95)	54.65 (15.45)	2.090 (.044)*
ASHS^b	29.27 (10.05)	29.14 (8.24)	29.24 (9.63)	0.030 (.976)

	t1	t2	t3	F	p
MHRM	77.63 (18.10)	82.79 (15.41)	77.84 (17.97)	2.885	.062 (ns)
MSPSS	54.50 (15.45)	60.33 (12.24)	59.66 (15.28)	3.643	.031*
ASHS	29.24 (9.63)	31.11 (7.13)	29.64 (7.90)	0.775	.464 (ns)

Variables	t (p)	t (p)	95% CI of the Change Score	Cohen’s d
MHRM
t1–t2	4.97	2.165 (.030)*	[0.470, 9.474]	.356
t2–t3	−4.47	−1.782 (.075)	[−9.392, 0.446]	−.293
t1–t3	0.50	0.192 (.848)	[−4.592, 5.590]	.032
MSPSS
t1–t2	5.69	2.436 (.015)*	[0.112, 10.267]	.401
t2–t3	−0.74	−0.345 (.730)	[−4.969, 3.485]	−.57
t1–t3	4.95	1.998 (.046)*	[0.093, 9.802]	.328
ASHS
t1–t2	1.71	1.030 (.303)	[−1.539, 4.949]	.169
t2–t3	−1.10	−0.787 (.431)	[−3.832, 1.638]	.129
t1–t3	0.61	0.423 (.673)	[−2.211, 3.427]	.070

Variables	Vocational Recovery	MHRMt3	ΔMHRMt2_t1
Sex	0.383	.536	0.453	.040*	5.425	.026*
Diagnosis	2.904	.407	1.412	.252	0.702	.558
Education level	0.311	.856	0.530	.593	2.151	.132
Having employment history	0.110	.740	2.820	.102	0.962	.333
Having employment at baseline	0.298	.585	0.150	.701	0.149	.702
Achieving competitive employment at t3 (vocational recovery)	1.00	—	1.439	.251	1.355	.279
	F ^b	p value	ρ^c	p value	ρ^c	p value
Age	0.016	.902	−0.144	.414	0.307	.067
MHRMt1	0.988	.327	0.648	.000**	−0.625	.000**
MSPSSt1	2.685	.110	0.564	.000**	−0.333	.044*
ASHSt1	1.762	.193	0.536	.000**	−0.652	.000**
ΔMHRMt1_t2	0.007	.933	−0.323	.064	−	−
ΔMSPSSt1_t2	0.812	.374	−0.087	.616	0.383	.019*
ΔASHSt1_t2	0.014	.906	−0.258	.146	0.702	.000**

Model	Predictor	Adj. R²	B	β	Significance	F	Significance	Collinearity Statistics
Multiple linear regression for personal recovery at t3
Dependent variable: MHRMt3
1	(Constant)	0.254	44.541		.000**	12.23	.001**
	MSPSS		0.609	.542	.001**			1	1
2	(Constant)	0.322	36.083		.000**	4.504	.041**
	MSPSS		0.438	.377	.010**			0.797	1.255
	ASHS		0.609	.326	.038*			0.797	1.255
Multiple linear regression for improvement of personal recovery from t1 to t2
Dependent variable: ΔMHRMt1_t2
3	(Constant)	0.599	3.142		.038*	54.812	.000**
	ΔASHSt1_t2		1.074	0.781	.000**			1	1
4	(Constant)	0.656	20.829		.002**	6.804	.013*
	ΔASHSt1_t2		0.906	0.663	.000**			0.824	1.213
	MHRMt1		−0.224	−0.281	.008**			0.824	1.213

Footnotes

Acknowledgments

Special thanks are given to the nonprofit social service organization, that is, Baptist Oi Kwan Social Service, for its kind support of this research project. The authors would like to sincerely thank the participants and staff members for their involvement.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was generously fully sponsored by the Social Science Faculty Hong Kong Baptist University [Ref. No. 3840094].

References

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author.

Andresen

Caputi

Oades

(2006). Stages of recovery instrument: Development of a measure of recovery from serious mental illness. Australian and New Zealand Journal of Psychiatry, 40, 972–980.

Baksheev

G. N.

Kelly

Jackspon

H. J.

McGorry

P. D.

Killackey

. (2012). Predictors of vocational recovery among young people with first-episode psychosis: Findings from a randomized controlled trial. Psychiatric Rehabilitation Journal, 35, 421–427.

Bond

G. R.

Drake

R. E.

Becker

D. R.

(2012). Generalizability of the Individual Placement and Support (IPS) model of supported employment outside the US. World Psychiatry, 11, 32–39.

Bond

G. R.

Drake

R. E.

Campbell

(2016). Effectiveness of Individual Placement and Support supported employment for young adults. Early Intervention in Psychiatry, 10, 300–307. doi:10.1111/eip.12175

Bond

G. R.

Drake

R. E.

Luciano

(2015). Employment and educational outcomes in early intervention programmes for early psychosis: A systematic review. Epidemiology and Psychiatric Sciences, 24, 446–457.

Bullock

W. A

. (2005). The mental health recovery measure. In Campbell-Orde

Chamberlin

Carpenter

Leff

H. S.

(Eds.), Measuring the promise of recovery: A compendium of recovery measures (Vol. II, pp. 36–41). Cambridge, MA: The Evaluation Center @ HSRI.

Campbell-Orde

Chamberline

Carpenter

Leff

H. S.

(Eds.). (2005). Proceedings from the Evaluation Center Invitational Conference 2004: Measuring the promise: Assessing recovery and self-determination instruments for evidence-based practices. Cambridge, MA: Human Services Research Institute.

Chang

W. C.

Wong

C. S. M.

Lam

L. C. W.

Lee

E. H. M.

Chen

E. Y. H.

Chan

W. C.

… Babington

. (2015). Prevalence, psychosocial and physical health correlates of psychotic disorders in Hong Kong: The Hong Kong Mental Health Morbidity Survey. Schizophrenia Bulletin, 41, S135.

10.

Chiu

M. Y.

W. W.

W. T.

Yiu

M. G.

(2010). Operationalization of the SAMHSA model of recovery: A quality of life perspective. Quality of Life Research, 19, 1–13.

11.

Chou

K. L.

(2000). Assessing Chinese adolescents’ social support: The multidimensional scale of perceived social support. Personality and Individual Differences, 28, 299–307.

12.

Cohen

(1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.

13.

Connell

King

Crowe

(2011). Can employment positively affect the recovery of people with psychiatric disabilities? Psychiatric Rehabilitation Journal, 35, 59–63.

14.

Davidson

Sells

Sangster

O’Connell

(2005). Qualitative studies of recovery: What we can learn from the person? In Ralph

R. O.

Corrigan

P. W.

(Eds.), Recovery in mental illness—Broadening our understanding of wellness (pp. 147–170). Washington, DC: American Psychological Association.

15.

Drake

R. E.

Goldman

H. H.

Leff

H. S.

Lehman

A. F.

Dixon

Mueser

K. T.

… Torrey

W. C

. (2001). Implementing evidence-based practices in routine mental health service settings. Psychiatric Services, 52, 179–182.

16.

Drake

R. E.

Whitley

(2014). Recovery and severe mental illness: Description and analysis. Canadian Journal of Psychiatry, 59, 236–242.

17.

Dumville

J. C.

Torgerson

D. J.

Hewitt

C. E.

(2006). Reporting attrition in randomised controlled trials. British Medical Journal, 332, 969–971.

18.

Færden

Nesvåg

Marder

S. R.

(2008). Definitions of the term ‘recovered’ in schizophrenia and other disorders. Psychopathology, 41, 271–278.

19.

Fossey

E. M.

Harvey

C. A.

(2010). Finding and sustaining employment: A qualitative meta-synthesis of mental health consumer views. Canada Journal of Occupational Therapy, 77, 303–314.

20.

Hong Kong Census and Statistical Department. (2014). Special topics report no. 62—Person with disabilities and chronic disease. Kowloon, Hong Kong: Author. Retrieved from http://www.statistics.gov.hk/pub/B11301622014XXXXB0100.pdf

21.

Hong Kong Social Welfare Department. (2017). Sunnyway—On the job training programme for young people with disabilities. Wanchai, Hong Kong: Author. Retrieved from https://www.swd.gov.hk/doc/Subv_SAMPLE%20FSAs%202015/Rehabilitation%20Services/RM40-e.pdf

22.

IBM Corp. (2013). IBM SPSS Statistics for Windows (Version 22.0). Armonk, NY: Author.

23.

Lam

L. C. W.

Wong

C. S. M.

Wang

M. J.

Chan

W. C.

Chen

E. Y. H.

R. M. K.

… Hung

S. F

. (2015). Prevalence, psychosocial correlates and service utilization of depressive and anxiety disorders in Hong Kong: The Hong Kong Mental Morbidity Survey (HKMMS). Social Psychiatry and Psychiatric Epidemiology, 50, 1379–1388.

24.

Leamy

Bird

Le Boutillier

Williams

Slade

(2011). Conceptual framework for personal recovery in mental health: Systematic review and narrative synthesis. British Journal of Psychiatry, 199, 445–452.

25.

Lloyd

King

Moore

(2010). Subjective and objective indicators of recovery in severe mental illness: A cross-sectional study. International Journal of Social Psychiatry, 56, 220–229.

26.

Lloyd

Waghorn

(2007). The importance of vocation in recovery for young people with psychiatric disabilities. British Journal of Occupational Therapy, 70, 50–59.

27.

Lopez

S. J.

Ciarlelli

Coffman

Stone

Wyatt

(2000). Diagnosing for strengths: On measuring hope building blocks. In Snyder

C. R.

(Ed.), Handbook of hope theory, measures and applications (pp. 57–85). San Diego, CA: Academic Press.

28.

McManus

Meltzer

Brugha

Bebbington

Jenkins

(2009). Adult psychiatric morbidity in England, 2007: Results of a household survey. Leeds, England: The NHS Information Centre for Health and Social Care.

29.

Modini

Tan

Brinchmann

Wang

M. J.

Killackey

Glozier

… Harvey

S. B

. (2016). Supported employment for people with severe mental illness: Systematic review and meta-analysis of the international evidence. British Journal of Psychiatry, 209, 14–22.

30.

Ralph

R. O.

(2005). Verbal definition and visual models of recovery: Focus on recovery model. In Ralph

R. O.

Corrigan

P. W.

(Eds.), Recovery in mental illness—Broadening our understanding of wellness. (pp. 131–145). Washington, DC: American Psychological Association.

31.

Ramsay

Stewart

Compton

M. T.

(2012). Unemployment among patients with newly diagnosed first-episode psychosis: Prevalence and clinical correlates in a US sample. Social Psychiatric and Psychiatric Epidemiology, 47, 797–803.

32.

Rinaldi

Killackey

Smith

Shepherd

Singh

S. P.

Craig

(2010). First episode psychosis and employment: A review. International Review of Psychiatry, 22, 148–162. doi:10.3109/09540261003661825

33.

Rodgers

M. L.

Norell

D. M.

Roll

J. M.

Dyck

D. G.

(2007). An overview of mental health recovery. Primary Psychiatry, 14, 76–85.

34.

Siu

B. W. M.

B. F. L.

V. C. K.

Yeung

Y. M.

Lee

M. K. L.

Leung

A. Y. H.

(2012). Mental health recovery for psychiatric inpatient services: Perceived importance of the elements of recovery. East Asian Archives of Psychiatry, 22, 39–48.

35.

Snyder

C. R.

Sympson

S. C.

Ybasco

F. C.

Borders

T. F.

Babyak

M. A.

Higgins

R. L.

(1996). Development and validation of the State Hope Scale. Journal of Personality and Social Psychology, 70, 321–335.

36.

Spaniol

Wewiorski

N. J.

Gagne

Anthony

W. A.

(2002). The process of recovery from schizophrenia. International Review of Psychiatry, 14, 327–336.

37.

Substance Abuse and Mental Health Service Administration. (2003). National consensus statement on mental health recovery. Retrieved from http://store.samhsa.gov/shin/content/SMA05-4129/SMA05-4129.pdf

38.

Tsang

H. W. H.

Fung

K. M. T.

Leung

A. Y.

S. M. Y.

Cheung

W. M.

(2010). Three-year follow-up study of an integrated supported employment for individuals with severe mental illness. Australian and New Zealand Journal of Psychiatry, 44, 49–58.

39.

Tse

Siu

W. M.

Kan

A. L.

(2013). Can recovery-oriented mental health services be created in Hong Kong? Struggles and strategies. Administration and Policy in Mental Health and Mental Health Services Research, 40, 155–158. doi:10.1007/s10488-011-0391-7

40.

Whitley

Drake

(2010). Recovery: A dimensional approach. Psychiatric Services, 61, 1248–1250.

41.

Wong

K. K.

Chiu

Tang

Mak

Liu

Chiu

S. H.

(2008). A randomized controlled trial of a supported employment program for persons with long-term mental illness in Hong Kong. Psychiatric Services, 59, 84–90.

42.

Pan

J. Y.

Wong

F. K.

Bola

J. R.

(2013). Cross-validation of mental health recovery measures in a Hong Kong Chinese sample. Research on Social Work Practice, 23, 311–325.

43.

Young

S. L.

Bullock

W. A.

(2003). The mental health recovery measure. Toledo, Spain: University of Toledo.

44.

Young

S. L.

Ensing

D. S.

(1999). Exploring recovery from the perspective of people with psychiatric disabilities. Psychiatric Rehabilitation Journal, 22, 219–231.

45.

Young

K. W.

Pan

J. Y.

(2014). Functional recovery for consumers discharged from mental hospital and received community-based psychosocial program provided by a Non-Government Organization. East Asian Archives of Psychiatry, 24, 139–147.

46.

Young

K. W.

Pan

J. Y.

(2017). Predictors and prevalence of recovery and remission for consumers discharged from mental hospitals in a Chinese society. Psychiatric Quarterly (first published online: 23 February 2017). doi:10.1007/s11126-017-9497-8

47.

Young

K. W.

Pan

J. Y.

Fung

Cheng

(2016). Validity and reliability of Recovery Assessment Scale for Cantonese speaking Chinese consumers with mental illness. International Journal of Mental Health and Addiction, 15, 198–208. doi:10.1007/s11469-016-9657-3

48.

Zimet

G. D.

Dahlem

N. W.

Zimet

S. G.

Farley

G. K.

(1988). The multidimensional scale of perceived social support. Journal of Personality Assessment, 52, 30–41.

	Completers (N = 30)	NonCompleters (N = 7)	Total (N = 37)	F (p)
Variables	n (%)	n (%)	n (%)	F (p)
Gender^a
Male	18 (60.00)	4 (57.1)	22 (59.46)	.019 (.890)
Female	12 (40.00)	3 (42.9)	15 (40.54)
Education^a				.493 (.781)
University	8 (26.67)	2 (28.57)	10 (27.03)
Secondary school	20 (66.67)	5 (71.43)	25 (67.57)
Others	2 (6.66)	0 (0.00)	2 (5.40)
Marital status^a
Single	30 (100)	7 (100)	37 (100)	NA
Living arrangement^a
With family members	30 (100)	7 (100)	37 (100)	NA
Diagnosis^a				3.753 (.808)
Schizophrenia and psychosis	13 (43.33)	4 (57.14)	17 (45.95)
Depression	4 (13.33)	0 (0.00)	4 (10.81)
Bipolar disorder	3 (10.00)	0 (0.00)	3 (8.11)
Anxiety	4 (13.33)	1 (14.30)	5 (13.51)
Others	6 (20.00)	2 (28.57)	8 (21.62)
Was previously being employed?^a				0.010 (.919)
Yes	8 (26.67)	2 (28.57)	10 (27.03)
Being employed at baseline?^a				0.442 (.506)
Yes	2 (6.66)	0 (0.00)	2 (5.41)
	M (SD)	M (SD)	M (SD)	F (p)
Age^b	22.23 (2.43)	23.57 (1.51)	22.49 (2.35)	1.386 (.174)
Number of family member^b	3.52 (0.83)	3.57 (1.62)	3.53 (1.00)	0.127 (.900)
MHRM^b	78.47 (18.74)	73.99 (15.74)	77.89 (18.27)	0.584 (.563)
MSPSS^b	57.10 (14.28)	44.14 (16.95)	54.65 (15.45)	2.090 (.044)*
ASHS^b	29.27 (10.05)	29.14 (8.24)	29.24 (9.63)	0.030 (.976)

	t1	t2	t3	F	p
	Mean (SD)	Mean (SD)	Mean (SD)	F	p
MHRM	77.63 (18.10)	82.79 (15.41)	77.84 (17.97)	2.885	.062 (ns)
MSPSS	54.50 (15.45)	60.33 (12.24)	59.66 (15.28)	3.643	.031*
ASHS	29.24 (9.63)	31.11 (7.13)	29.64 (7.90)	0.775	.464 (ns)

Variables	Vocational Recovery		MHRMt3		ΔMHRMt2_t1
Variables	χ^2a	p Value	F ^b	p Value	F ^b	p Value
Sex	0.383	.536	0.453	.040*	5.425	.026*
Diagnosis	2.904	.407	1.412	.252	0.702	.558
Education level	0.311	.856	0.530	.593	2.151	.132
Having employment history	0.110	.740	2.820	.102	0.962	.333
Having employment at baseline	0.298	.585	0.150	.701	0.149	.702
Achieving competitive employment at t3 (vocational recovery)	1.00	—	1.439	.251	1.355	.279
	F ^b	p value	ρ^c	p value	ρ^c	p value
Age	0.016	.902	−0.144	.414	0.307	.067
MHRMt1	0.988	.327	0.648	.000**	−0.625	.000**
MSPSSt1	2.685	.110	0.564	.000**	−0.333	.044*
ASHSt1	1.762	.193	0.536	.000**	−0.652	.000**
ΔMHRMt1_t2	0.007	.933	−0.323	.064	−	−
ΔMSPSSt1_t2	0.812	.374	−0.087	.616	0.383	.019*
ΔASHSt1_t2	0.014	.906	−0.258	.146	0.702	.000**

A Vocational Recovery Model for Young People With Mental Illness: A Pretest–Posttest

Abstract

Purpose:

Methods:

Results:

Conclusions:

Keywords

A New Vocational Recovery Model

Research Design

Client Inclusion Criteria

Vocational Recovery Model

Aims and Hypotheses

Outcome Assessment Tools

Data Analyses

Ethical Considerations

Research Results

Characteristics of Clients

Baseline Assessment Scores

Treatment Outcomes

Hypothesis 1 vocational recovery

Hypothesis 2 personal recovery

Hypothesis 3 social support and hope

Hypothesis 4 factors related to and predicting personal and vocational recovery

Factors related to personal recovery

Factors related to vocational recovery

Factors predicting personal recovery

Factors predicting vocational recovery

Discussion and Application to Practice

Footnotes

Acknowledgments

Declaration of Conflicting Interests

Funding

References