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An empirical conceptualization of the recovery orientation
Schizophrenia Research 75 (2005) 119 – 128 www.elsevier.com/locate/schres
An empirical conceptualization of the recovery orientation Sandra G. Resnicka,*, Alan Fontanaa, Anthony F. Lehmanb, Robert A. Rosenhecka a
Northeast Program Evaluation Center and Yale University School of Medicine, NEPEC 182, 950 Campbell Avenue, West Haven, CT 06516, United States b VA Maryland Healthcare System and University of Maryland School of Medicine, United States Received 18 February 2004; received in revised form 18 May 2004; accepted 21 May 2004 Available online 10 July 2004
Abstract Objective: The recovery movement is having a growing impact on policy for people with severe mental illness. The empirical literature on the recovery orientation, however, is scant, and no empirical conceptualization of recovery has been published. Method: We identified items reflecting recovery themes and measuring aspects of subjective experience, and used principle components and confirmatory factor analyses to develop an empirical conceptualization of the recovery orientation, using data from a large, systematic study of schizophrenia. Results: We identified four domains of the recovery orientation: empowerment, hope and optimism, knowledge and life satisfaction. Conclusions: We propose here an initial approach to measuring and conceptualizing recovery attitudes. We also suggest that the evidence-based practice (EBP) movement may help to identify interventions that promote the recovery orientation and help to advance recovery attitudes. We suggest that there is a bidirectional relationship between recovery attitudes and the positive clinical outcomes that are the goals of EBPs. Through the use of empirically derived conceptualizations of recovery, EBPs can provide a mechanism for identifying treatments that promote the recovery orientation. The conceptualization proposed here can, thus, serve as a tool to assess changes in recovery attitudes during participation in specific EBPs. D 2004 Elsevier B.V. All rights reserved. Keywords: Recovery; Hope; Knowledge; Empowerment; Life satisfaction; Attitudes
1. Introduction The recovery concept has gained increasing prominence among those delivering services to people with * Corresponding author. Tel.: +1 203 932 5711x5106; fax: +1 203 937 3433. E-mail address: [email protected] (S.G. Resnick). 0920-9964/$ - see front matter D 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.schres.2004.05.009
severe mental illness. Traditionally, recovery has been narrowly defined as an outcome occurring at a discrete point in time after an illness when one’s health is entirely regained. Beginning in the 1980s, a new and broader definition of recovery began to emerge in mental health (Anthony, 2000). In this expanded usage, recovery is a process representing the belief that all individuals, even those with severe
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psychiatric disabilities, can develop hope for the future, participate in meaningful activities, exercise self-determination, and live in a society without stigma and discrimination. The recovery orientation, thus defined, has been at the core of a grass-roots social movement that envisions and advocates for major reform of the mental health service system. The recovery movement has grown considerably since its inception and the expanded recovery philosophy is now widely endorsed and promoted by many, including the National Alliance for the Mentally Ill (2003), several state mental health systems (Anthony et al., 2003) and, most recently, by the President’s New Freedom Commission on Mental Health (2003). The recovery movement has begun to influence policy and advocacy concerning mental illness and mental health services, but it is yet to be addressed through empirical research. There is increasing agreement among mental health researchers that empirical studies are needed to identify correlates of the recovery orientation and to develop recovery-oriented interventions. However, the word brecoveryQ lacks precision (Liberman and Kopelowicz, 2002), and until a clear operational definition of the recovery orientation emerges, this research agenda within the recovery vision cannot advance (Liberman and Kopelowicz, 2002; Noordsy et al., 2002). Confusion around the conceptualization of recovery may be partly responsible for the current paucity of instruments to measure it. One primary source of confusion is over the common use of recovery as both process and outcome—the newer, expanded usage of recovery is often described and defined as a process, but then used as an outcome. Another source of confusion is in the complexity of the recovery concept. Recovery is multifaceted, yet also somewhat self-evident. Individuals who have experienced the recovery process are able to provide firsthand accounts of their experiences and there are many descriptions of the recovery orientation in the literature, drawn from personal narratives and qualitative studies (Jacobsen, 2001; Jacobsen and Greenley, 2001; Ralph, 2000; Young and Ensing, 1999). In these descriptions, many different domains have been suggested to be defining features of the recovery orientation, such as the development of spirituality, a sense of identity (Liberman et al., 2002; Noordsy et al., 2002), hope, choice, social relationships, avail-
ability of peer support, feelings of independence and autonomy, and involvement in meaningful activity (Onken et al., 2002). Despite the many domains suggested in the literature to be critical to recovery, to our knowledge, there are no empirically derived conceptualizations. Our resolution to our confusion around the meaning of recovery is to conceptualize it as an attitude or life orientation. As an orientation, we firmly place the concept of recovery in the domain of process, but like all attitudes, it can also be measured and in some contexts used as an outcome. We then can use empirical methods to begin to further conceptualize domains of the recovery orientation and devise measurement strategies. In the current study, we thus aim to provide an initial approach to the conceptualization and measurement of the recovery orientation. We use data from the Schizophrenia Patient Outcomes Research Team (PORT) Client Survey, the largest systematic survey of the treatment of schizophrenia ever conducted. The PORT surveyed a representative sample of people with schizophrenia on a broad range of measures, including measures of clinical status, community adjustment and an array of attitudinal measures (Lehman et al., 1998). After selecting items that measure aspects of the recovery orientation, we conducted a series of principal components analyses and confirmatory factor analysis to identify recovery dimensions.
2. Methods 2.1. Participants Data for the current study were derived from two sources: the PORT study, which examined usual care in a random sample of people with schizophrenia in Ohio and Georgia (Lehman et al., 1998); and a VA PORT extension, which followed a parallel sampling strategy in order to provide an expanded VA-specific comparison group to the original study (Rosenheck et al., 2000), for a total sample of 1076 participants. All participants were 18 years of age or older, legally competent, English speaking, had a working clinical diagnosis of schizophrenia, and provided written informed consent after a full explanation of
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the study and procedures. Characteristics of the final sample can be seen in Table 1.
originate, all items are enumerated in Table 2 and identified by their item numbers below.
2.2. Measures
2.2.1. Quality of life The PORT Client Survey included portions of the Quality of Life Interview (Lehman, 1983). The Quality of Life Interview is a widely used instrument that measures both objective information and subjective perceptions. We retained subjective items measuring satisfaction with family relationships (items 6–9), relationships with friends (items 10– 14), living arrangements (items 15–18), one’s community (items 19–23), overall safety (items 24–28), satisfaction with leisure (items 50–55) and one item measuring overall quality of life (item 56).
We carefully reviewed all measures from the PORT Client Survey, and identified measures that reflected a theme in the existing recovery literature, such as quality of life, hope and empowerment. Because our interest is in recovery as an attitude or orientation, we eliminated all objective items, such as whether a participant was living independently, was working, adequacy of finances, etc. We retained all subjective measures that potentially reflected recovery attitudes. In order to identify the measures from which items
Table 1 Sample characteristics Variable Gender (n=1075) Male Female Ethnicity (n=1070) White Black Other Marital status (n=1072) Currently married Previously married Never married Housing status Independent housing Living with family/friends Supervised in community Institution or other Income from all sources in the prior month 0–US$300 US$301–900 NUS$900 Missing Working for pay No Yes Admitted to the hospital for emotional problems in the past year (n=1017) No Yes Age (M, S.D.) Number years school (M, S.D.)
Current sample, N=1076, n (%) 792 (73.61%) 283 (26.30%) 621 (57.71%) 402 (37.36%) 47 (4.37%) 196 (18.22%) 363 (33.74%) 513 (47.68%) 575 233 209 59
(53.44%) (21.65%) (19.42%) (5.48%)
166 525 297 88
(15.43%) (48.79%) (27.60%) (8.18%)
912 (84.76%) 164 (15.24%)
454 (42.19%) 563 (52.32%) 45.61 (12.61) 11.86 (2.43)
2.2.2. Mastery of mental health treatment Items about participation in treatment and feeling cared about by treaters are from a questionnaire measuring perceptions of mastery with mental health treatment (Rosenfield, 1992). 2.2.3. Perceptions of mental health Perceptions of current, future, and past mental health were adapted from questions used in the Medical Outcomes Study (Ware and Sherbourne, 1992). 2.2.4. Knowledge Items measuring self-perception of knowledge of mental illness and services were developed specifically for the PORT Client Survey (Lehman et al., 1998) and were used as a proxy for objective knowledge. 2.2.5. Background and mental health variables Demographics and other variables used to describe the sample (age, gender, ethnicity, education, income, employment status, history of mental health treatment and housing stability) were obtained via interview. 2.3. Data analysis We used standard psychometric procedures to develop a conceptual model of recovery (Tabachnick and Fidell, 2001). First, we randomly divided our data set into two separate data sets, each with 538 participants. Then, in order to eliminate weak items and identify orthogonal factors, we conducted a principal components analysis on the selected sub-
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Table 2 Exploratory factor analysis: factor solution Item
Factor loading
Current mental health a 1. In general, at the present time, would you say your mental or emotional health is. . . 2. Compared to 12 months ago, would you say your mental or emotional health is. . . 3. Compared to 5 years ago, would you say your mental or emotional health is. . .
0.54 0.78 0.72
Optimism a 4. Thinking ahead to 12 months from now, do you expect your mental or emotional health to be. . . 5. Now thinking about 5 years from now, do you expect your mental or emotional health to be. . .
0.85 0.82
Satisfaction with family b 6. How do you feel about your family in general? 7. How do you feel about how often you have contact with your family? 8. How do you feel about the way you and your family act toward each other? 9. The way things are in general between you and your family?
0.79 0.62 0.85 0.84
Satisfaction with social network b 10. How do you feel about the things you do with other people? 11. How do you feel about the amount of time you spend with other people? 12. How do you feel about the people you see socially? 13. How do you feel about how you get along with other people in general? 14. How do you feel about the chance you have to know people with whom you really feel comfortable?
0.77 0.76 0.70 0.67 0.75
Satisfaction with living arrangements b 15. How do you feel about the living arrangements where you live? 16. How do you feel about the food there? 17. How do you feel about the rules there? 18. How do you feel about the privacy you have there?
0.67 0.45 0.76 0.78
Satisfaction with community b 19. How do you feel about the people who live in the houses, apartments, near yours? 20. How do you feel about people who live in this community? 21. How do you feel about the outdoor space there is for you to use outside your home? 22. How do you feel about the particular neighborhood as a place to live? 23. How do you feel about this community as a place to live?
0.67 0.74 0.59 0.77 0.77
Satisfaction with safety b 24. How do you feel about 25. How do you feel about 26. How do you feel about 27. How do you feel about 28. How do you feel about
0.74 0.74 0.77 0.83 0.58
your personal safety? how safe you are on the streets in your neighborhood? how safe you are where you live? the protection you have against being robbed or attacked? your chance of finding a policeman if you need one?
Knowledge of mental health and mental health services c 29. How much do you feel you know about schizophrenia, including symptoms and illness management? 30. How much do you feel you know about providers of mental health care in your area? 31. How much do you feel you know about the best and worst providers of care in your area? 32. How much do you feel you know about emergency and crisis services in your area? 33. How much do you feel you know about social and recreational activities in your area for people with mental illness? 34. How much do you feel you know about support groups or meeting in your area where you can talk with other people with mental illness? 35. How much do you feel you know about organizations in your area for family members of people with mental illness?
0.38 0.52 0.62 0.57 0.75 0.79 0.73
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Table 2 (continued) Item
Factor loading
Knowledge of procedural assistance c 36. How much do you feel you know about how to find help with housing? 37. How much do you feel you know about how to find help with employment or job training? 38. How much do you feel you know about how to find help with applying for benefits like SSDI or Medicaid?
0.80 0.79 0.72
Empowerment—self agency c 39. How much do your opinions and ideas count in which services you get? 40. How much responsibility do you feel you have for the services you get? 41. How much input do you have into your rehabilitation plan and personal goals? 42. How much do these services help you learn to make your own decisions about your life? 43. How much do you rely on these services to help you through difficult times?
0.57 0.66 0.64 0.66 0.54
Empowerment—mental health services c 44. Do the people at these services care about you? 45. How much do you have the feeling of being cared about at these services? 46. How much does your overall service plan fit what you want? 47. How much do you feel your therapists or counselors really know what you need? 48. How much do these services give you a sense of competence that you have skills you can use? 49. How much do you think people providing these services want to see you get better?
0.77 0.78 0.64 0.67 0.62 0.63
Items deleted during factor analysis b 50. How do you feel about the way you spend your spare time? 51. How do you feel about the amount of time you have to do the things you want to do? 52. How do you feel about the chance you have to enjoy pleasant or beautiful things? 53. How do you feel about the amount of fun you have? 54. How do you feel about the amount of relaxation you have in your life? 55. How do you feel about the pleasure you get from the television or radio? 56. In general, how do you feel about your life as a whole? a b c
Item scores range from 1 to 5. Item scores range from 1 to 7. Item scores range from 1 to 4.
jective items using the first data set. In order to create a hypothesized model, we conducted another exploratory principal components analysis on the identified factors. Then, to test the model, we used the second data set. We conducted a confirmatory factor analysis to test the model (SAS Institute Inc., 1989). Using the modification indices from the confirmatory factor analysis, we made one alteration in the model, which we then retested using confirmatory factor analysis on the first dataset.
3. Results The first principal components analysis on the first data set yielded 14 factors. Six items were deleted at this stage: one item because it was the only item
loading on a factor (item 56), four items from the satisfaction with leisure QOL subscale that had factor loadings less than 0.40, and the last item because it was originally part of the satisfaction with leisure subscale and had a factor loading only slightly higher than 0.40 (items 50–55). We then repeated the principal components analysis. This yielded an 11factor solution with all items unambiguously loading on 1 factor, all but 1 factor loading greater than 0.40, and factors that were conceptually meaningful. Table 2 lists the included items, factor names and factor loadings for this solution. We then calculated factor scores by averaging Zscores of the appropriate items. Using these factor scores and the same dataset, we conducted a principal components analysis, yielding a superordinate threefactor solution (Table 3). We tentatively labeled these
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Table 3 Second-order exploratory factor analysis First order factor
Factor loading
Factor 1. Hope and optimism Current mental health Optimism Factor 2. Life satisfaction Satisfaction with family Satisfaction with social network Satisfaction with living arrangements Satisfaction with community Satisfaction with safety Factor 3. Empowerment Knowledge of mental health and services Knowledge of PSR services Empowerment—self-agency Empowerment—mental health services
0.76 0.84 0.66 0.67 0.75 0.80 0.71 0.76 0.65 0.75 0.69
three factors as empowerment, hope and optimism, and life satisfaction. The next step was to conduct a confirmatory factor analysis of the hypothesized three-factor model using the second data set. The Comparative Fit Index for the
model was 0.83 and the root mean square residual was 0.072. Inspection of the modification indices suggested that dividing the empowerment factor into two factors, knowledge and empowerment, would improve the fit indices. Repeating the confirmatory factor analysis using this four-factor superordinate model, the fit indices improved, yielding a Comparative Fit Index of 0.92 and a root mean square residual of 0.054. As a final test of the four-factor model, we repeated the confirmatory factor analyses on the first data set, and the same pattern emerged, in which the fit for the four-factor model (CFI=0.94, root mean square residual=0.066) was superior to the three-factor model. The final model, including path coefficients and error terms, is displayed in Fig. 1. The psychometric properties of the model were good. Although statistically significant ( pb0.0001), intercorrelations between the domains were small to modest in magnitude (r’s ranging from 0.14 to 0.38), suggesting that these dimensions are approximately orthogonal (Table 4). Internal consistency (Cronba-
Fig. 1. Confirmatory factor analysis: components of recovery.
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Table 4 Intercorrelations (and Chronbach’s a) of recovery domains Knowledge Empowerment Hope and optimism Life satisfaction
Knowledge
Empowerment
Hope and optimism
Life satisfaction
(0.86)
0.35 (0.90)
0.25 0.26 (0.75)
0.14 0.38 0.21 (0.92)
All correlations are significant at pb0.0001.
ch’s a) for these four dimensions was good: 0.90 for empowerment, 0.75 for hope and optimism, 0.86 for knowledge and 0.92 for life satisfaction.
4. Discussion We propose here four domains to serve as an initial approach to the conceptualization of the recovery orientation: the capacity to feel empowered in one’s life; self-perceptions of knowledge about mental illness and available treatments; satisfaction with quality of life; and hope and optimism for the future. We also propose a preliminary instrument with good psychometric properties and face validity for measuring these four domains of the recovery orientation. While it is understood that the recovery orientation has individual variations and is influenced by many factors, we propose that these four domains are of central importance. Many questions related to the recovery orientation can now begin to be explored with this preliminary instrument. Which sociodemographic, clinical and social characteristics are associated with a strong experience of the recovery orientation? Which interventions are most effective at inducing the recovery orientation? Is it possible to have graduated levels of the recovery orientation, or is there a threshold at which a person may be said to be bin recoveryQ? If recovery is a process, how can a measure of recovery be used as an outcome? The measurement of clinical significance is related to these last two questions. This concept, used primarily in longitudinal studies and psychotherapy research, suggests that meaningful cutoff points can be identified for various symptom measures. These cutoff points are then used to determine, among other things, the percentage of individuals who have returned to a normative range of symptoms, substance
use, etc., and who may be considered brecoveredQ (Jacobson et al., 1999; Roberts et al., 2000), using the traditional, symptom-oriented usage of recovery. Clinical significance, thus defined, has not been adopted in the research on treatment for individuals with severe mental illness, partly due to difficulties in determining normative comparison groups and the varied course of mental illness (Bond et al., 2001b). In recognizing that symptoms and functioning are often independent, others have suggested an expanded definition of clinical significance, in which the impact of interventions upon functioning, quality of life and society are considered (Gladis et al., 1999; Kazdin, 1999). This definition of clinical significance bears much similarity to the conceptualization of the recovery orientation we describe here. We thus propose that for those with severe mental illness, clinical significance is analogous to our conceptualization of recovery, but as an outcome, rather than an orientation. Our measure of the recovery orientation can thus serve as a tool for assessing interventions for their ability to assist practitioners and consumers in fostering recovery. The evidence-based practice (EBP) movement, another influential movement in the mental health field, provides a model for this type of assessment. The EBP movement, which promotes treatments supported by clinical trials, originates in the evidence-based movement in general medicine (Muir Gray, 1997; Sakett et al., 1996) and has become a primary force in the scientific community. The movement to support EBPs for the treatment of individuals with severe mental illness is most visible in the recent adoption and promotion of EBPs by several state mental health systems (Torrey et al., 2001). The EBP movement has been described as a polar opposite of the recovery movement, specifically in the conflict between the EBP movement’s emphasis on
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empirical and experimental evidence versus the recovery movement’s focus on internal, subjective experience (Frese et al., 2001). This dichotomization is not justifiable and is counter-productive. EBPs have the potential to provide the missing bhowQ-how states, mental health agencies and professionals can cultivate a recovery orientation, and equally importantly, assist consumers to achieve important objective goals that we hypothesize are critical to recovery, including participation in meaningful activity such as employment, access to stable and safe housing, and an adequate social support network, among others. The four main domains of the recovery orientation that emerged from our analyses, empowerment, hope and optimism, knowledge and life satisfaction, should be evaluated and carefully considered when designing services, and service systems, for people with severe mental illness. Additionally, we suggest that current EBPs may promote development of these four domains. 4.1. Empowerment The empowerment domain explained the greatest amount of variance in our model of the recovery orientation. Empowerment, as conceptualized here, refers to feeling empowered to take responsibility to make one’s own decisions and take responsibility for treatment, as well the feeling that one’s treatment and treatment providers are in concordance with one’s own treatment goals. Thus, our results suggest that promoting self-esteem and helping individuals discover and reach their goals will be especially helpful in the promotion of the recovery orientation. Supported employment may be a framework in which professionals can help consumers to clarify their goals and develop meaningful activity that promotes selfesteem (Bond et al., 2001b).
ment of hope and optimism among people. Peer provided services, in which consumers serve as role models for other consumers, may help to foster hope for those who are still learning to manage the symptoms of their mental illness (Mead et al., 2001; Solomon and Draine, 2001). 4.3. Knowledge Knowledge about one’s illness, the range of available treatments and ways to navigate the service system is another area of importance identified by our model. It is notable that the items do not measure objective knowledge, but instead reflect the individual’s perception of their knowledge, perhaps also reflecting their confidence in coping with mental illness. Interventions such as Illness Management and Recovery may be useful in helping consumers attend to their own personal experiences, manage symptoms, and achieve greater independence and less dependence on the mental health system (Mueser et al., 2002). 4.4. Life satisfaction Life satisfaction is increasingly included in empirical research, and as such, is probably the most frequently addressed domain of recovery attitudes. The subdomains included here—satisfaction with family, social network, living arrangements, community and safety—are centered on two main themes— relationships with others, and affordable, safe housing. Family psychoeducation may be a helpful tool for consumers who would like to improve communication with family members (Dixon et al., 2001), and case management services such as assertive community treatment may help consumers maximize their housing opportunities and create housing stability (Bond et al., 2001a).
4.2. Hope and optimism 4.5. Limitations and future directions An often-cited component of the recovery orientation is the fostering of hope-hope for the future, hope for achieving one’s goals and the importance of being surrounded by treaters, peers and family members who share realistic optimism and hope. Our results suggest that interventions for people with severe mental illness should seek to promote the develop-
Because the PORT survey was not originally designed to investigate the recovery orientation, we were limited in the concepts that we could include in our exploration. Future empirical efforts that focus on the measurement of recovery would benefit from first identifying recovery domains, and selecting items
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based on these domains. It will be necessary to continue to examine the structure of the recovery orientation with the addition of recovery dimensions such as those discussed in our introduction, and begin to develop a measure that adequately captures these domains. 4.6. Conclusions We began this paper with the assertion that recovery should be conceptualized as an orientation, reflecting the belief that recovery is a fluid process and an attitude, not an endpoint. We conclude that an empirical measure based on recovery attitudes may be used to measure recovery as a type of outcome, as well as a process. This duality allows for a full examination of the relationship between the recovery orientation and interventions, which we hypothesize is bi-directional. Those with a strong recovery attitude may benefit more from treatment and rehabilitation than those with a weaker orientation, underscoring the importance of promoting the recovery philosophy among professionals and treatment settings. Some interventions may be more helpful than others in promoting recovery attitudes, and as such, evaluations of interventions should include measurement of this type of clinical significance. Thus, the relationship between interventions and recovery may take the form of a virtuous cycle, in which the promotion of the recovery attitude becomes a critical process and a desired outcome.
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An empirical conceptualization of the recovery orientation Sandra G. Resnicka,*, Alan Fontanaa, Anthony F. Lehmanb, Robert A. Rosenhecka a
Northeast Program Evaluation Center and Yale University School of Medicine, NEPEC 182, 950 Campbell Avenue, West Haven, CT 06516, United States b VA Maryland Healthcare System and University of Maryland School of Medicine, United States Received 18 February 2004; received in revised form 18 May 2004; accepted 21 May 2004 Available online 10 July 2004
Abstract Objective: The recovery movement is having a growing impact on policy for people with severe mental illness. The empirical literature on the recovery orientation, however, is scant, and no empirical conceptualization of recovery has been published. Method: We identified items reflecting recovery themes and measuring aspects of subjective experience, and used principle components and confirmatory factor analyses to develop an empirical conceptualization of the recovery orientation, using data from a large, systematic study of schizophrenia. Results: We identified four domains of the recovery orientation: empowerment, hope and optimism, knowledge and life satisfaction. Conclusions: We propose here an initial approach to measuring and conceptualizing recovery attitudes. We also suggest that the evidence-based practice (EBP) movement may help to identify interventions that promote the recovery orientation and help to advance recovery attitudes. We suggest that there is a bidirectional relationship between recovery attitudes and the positive clinical outcomes that are the goals of EBPs. Through the use of empirically derived conceptualizations of recovery, EBPs can provide a mechanism for identifying treatments that promote the recovery orientation. The conceptualization proposed here can, thus, serve as a tool to assess changes in recovery attitudes during participation in specific EBPs. D 2004 Elsevier B.V. All rights reserved. Keywords: Recovery; Hope; Knowledge; Empowerment; Life satisfaction; Attitudes
1. Introduction The recovery concept has gained increasing prominence among those delivering services to people with * Corresponding author. Tel.: +1 203 932 5711x5106; fax: +1 203 937 3433. E-mail address: [email protected] (S.G. Resnick). 0920-9964/$ - see front matter D 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.schres.2004.05.009
severe mental illness. Traditionally, recovery has been narrowly defined as an outcome occurring at a discrete point in time after an illness when one’s health is entirely regained. Beginning in the 1980s, a new and broader definition of recovery began to emerge in mental health (Anthony, 2000). In this expanded usage, recovery is a process representing the belief that all individuals, even those with severe
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psychiatric disabilities, can develop hope for the future, participate in meaningful activities, exercise self-determination, and live in a society without stigma and discrimination. The recovery orientation, thus defined, has been at the core of a grass-roots social movement that envisions and advocates for major reform of the mental health service system. The recovery movement has grown considerably since its inception and the expanded recovery philosophy is now widely endorsed and promoted by many, including the National Alliance for the Mentally Ill (2003), several state mental health systems (Anthony et al., 2003) and, most recently, by the President’s New Freedom Commission on Mental Health (2003). The recovery movement has begun to influence policy and advocacy concerning mental illness and mental health services, but it is yet to be addressed through empirical research. There is increasing agreement among mental health researchers that empirical studies are needed to identify correlates of the recovery orientation and to develop recovery-oriented interventions. However, the word brecoveryQ lacks precision (Liberman and Kopelowicz, 2002), and until a clear operational definition of the recovery orientation emerges, this research agenda within the recovery vision cannot advance (Liberman and Kopelowicz, 2002; Noordsy et al., 2002). Confusion around the conceptualization of recovery may be partly responsible for the current paucity of instruments to measure it. One primary source of confusion is over the common use of recovery as both process and outcome—the newer, expanded usage of recovery is often described and defined as a process, but then used as an outcome. Another source of confusion is in the complexity of the recovery concept. Recovery is multifaceted, yet also somewhat self-evident. Individuals who have experienced the recovery process are able to provide firsthand accounts of their experiences and there are many descriptions of the recovery orientation in the literature, drawn from personal narratives and qualitative studies (Jacobsen, 2001; Jacobsen and Greenley, 2001; Ralph, 2000; Young and Ensing, 1999). In these descriptions, many different domains have been suggested to be defining features of the recovery orientation, such as the development of spirituality, a sense of identity (Liberman et al., 2002; Noordsy et al., 2002), hope, choice, social relationships, avail-
ability of peer support, feelings of independence and autonomy, and involvement in meaningful activity (Onken et al., 2002). Despite the many domains suggested in the literature to be critical to recovery, to our knowledge, there are no empirically derived conceptualizations. Our resolution to our confusion around the meaning of recovery is to conceptualize it as an attitude or life orientation. As an orientation, we firmly place the concept of recovery in the domain of process, but like all attitudes, it can also be measured and in some contexts used as an outcome. We then can use empirical methods to begin to further conceptualize domains of the recovery orientation and devise measurement strategies. In the current study, we thus aim to provide an initial approach to the conceptualization and measurement of the recovery orientation. We use data from the Schizophrenia Patient Outcomes Research Team (PORT) Client Survey, the largest systematic survey of the treatment of schizophrenia ever conducted. The PORT surveyed a representative sample of people with schizophrenia on a broad range of measures, including measures of clinical status, community adjustment and an array of attitudinal measures (Lehman et al., 1998). After selecting items that measure aspects of the recovery orientation, we conducted a series of principal components analyses and confirmatory factor analysis to identify recovery dimensions.
2. Methods 2.1. Participants Data for the current study were derived from two sources: the PORT study, which examined usual care in a random sample of people with schizophrenia in Ohio and Georgia (Lehman et al., 1998); and a VA PORT extension, which followed a parallel sampling strategy in order to provide an expanded VA-specific comparison group to the original study (Rosenheck et al., 2000), for a total sample of 1076 participants. All participants were 18 years of age or older, legally competent, English speaking, had a working clinical diagnosis of schizophrenia, and provided written informed consent after a full explanation of
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the study and procedures. Characteristics of the final sample can be seen in Table 1.
originate, all items are enumerated in Table 2 and identified by their item numbers below.
2.2. Measures
2.2.1. Quality of life The PORT Client Survey included portions of the Quality of Life Interview (Lehman, 1983). The Quality of Life Interview is a widely used instrument that measures both objective information and subjective perceptions. We retained subjective items measuring satisfaction with family relationships (items 6–9), relationships with friends (items 10– 14), living arrangements (items 15–18), one’s community (items 19–23), overall safety (items 24–28), satisfaction with leisure (items 50–55) and one item measuring overall quality of life (item 56).
We carefully reviewed all measures from the PORT Client Survey, and identified measures that reflected a theme in the existing recovery literature, such as quality of life, hope and empowerment. Because our interest is in recovery as an attitude or orientation, we eliminated all objective items, such as whether a participant was living independently, was working, adequacy of finances, etc. We retained all subjective measures that potentially reflected recovery attitudes. In order to identify the measures from which items
Table 1 Sample characteristics Variable Gender (n=1075) Male Female Ethnicity (n=1070) White Black Other Marital status (n=1072) Currently married Previously married Never married Housing status Independent housing Living with family/friends Supervised in community Institution or other Income from all sources in the prior month 0–US$300 US$301–900 NUS$900 Missing Working for pay No Yes Admitted to the hospital for emotional problems in the past year (n=1017) No Yes Age (M, S.D.) Number years school (M, S.D.)
Current sample, N=1076, n (%) 792 (73.61%) 283 (26.30%) 621 (57.71%) 402 (37.36%) 47 (4.37%) 196 (18.22%) 363 (33.74%) 513 (47.68%) 575 233 209 59
(53.44%) (21.65%) (19.42%) (5.48%)
166 525 297 88
(15.43%) (48.79%) (27.60%) (8.18%)
912 (84.76%) 164 (15.24%)
454 (42.19%) 563 (52.32%) 45.61 (12.61) 11.86 (2.43)
2.2.2. Mastery of mental health treatment Items about participation in treatment and feeling cared about by treaters are from a questionnaire measuring perceptions of mastery with mental health treatment (Rosenfield, 1992). 2.2.3. Perceptions of mental health Perceptions of current, future, and past mental health were adapted from questions used in the Medical Outcomes Study (Ware and Sherbourne, 1992). 2.2.4. Knowledge Items measuring self-perception of knowledge of mental illness and services were developed specifically for the PORT Client Survey (Lehman et al., 1998) and were used as a proxy for objective knowledge. 2.2.5. Background and mental health variables Demographics and other variables used to describe the sample (age, gender, ethnicity, education, income, employment status, history of mental health treatment and housing stability) were obtained via interview. 2.3. Data analysis We used standard psychometric procedures to develop a conceptual model of recovery (Tabachnick and Fidell, 2001). First, we randomly divided our data set into two separate data sets, each with 538 participants. Then, in order to eliminate weak items and identify orthogonal factors, we conducted a principal components analysis on the selected sub-
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Table 2 Exploratory factor analysis: factor solution Item
Factor loading
Current mental health a 1. In general, at the present time, would you say your mental or emotional health is. . . 2. Compared to 12 months ago, would you say your mental or emotional health is. . . 3. Compared to 5 years ago, would you say your mental or emotional health is. . .
0.54 0.78 0.72
Optimism a 4. Thinking ahead to 12 months from now, do you expect your mental or emotional health to be. . . 5. Now thinking about 5 years from now, do you expect your mental or emotional health to be. . .
0.85 0.82
Satisfaction with family b 6. How do you feel about your family in general? 7. How do you feel about how often you have contact with your family? 8. How do you feel about the way you and your family act toward each other? 9. The way things are in general between you and your family?
0.79 0.62 0.85 0.84
Satisfaction with social network b 10. How do you feel about the things you do with other people? 11. How do you feel about the amount of time you spend with other people? 12. How do you feel about the people you see socially? 13. How do you feel about how you get along with other people in general? 14. How do you feel about the chance you have to know people with whom you really feel comfortable?
0.77 0.76 0.70 0.67 0.75
Satisfaction with living arrangements b 15. How do you feel about the living arrangements where you live? 16. How do you feel about the food there? 17. How do you feel about the rules there? 18. How do you feel about the privacy you have there?
0.67 0.45 0.76 0.78
Satisfaction with community b 19. How do you feel about the people who live in the houses, apartments, near yours? 20. How do you feel about people who live in this community? 21. How do you feel about the outdoor space there is for you to use outside your home? 22. How do you feel about the particular neighborhood as a place to live? 23. How do you feel about this community as a place to live?
0.67 0.74 0.59 0.77 0.77
Satisfaction with safety b 24. How do you feel about 25. How do you feel about 26. How do you feel about 27. How do you feel about 28. How do you feel about
0.74 0.74 0.77 0.83 0.58
your personal safety? how safe you are on the streets in your neighborhood? how safe you are where you live? the protection you have against being robbed or attacked? your chance of finding a policeman if you need one?
Knowledge of mental health and mental health services c 29. How much do you feel you know about schizophrenia, including symptoms and illness management? 30. How much do you feel you know about providers of mental health care in your area? 31. How much do you feel you know about the best and worst providers of care in your area? 32. How much do you feel you know about emergency and crisis services in your area? 33. How much do you feel you know about social and recreational activities in your area for people with mental illness? 34. How much do you feel you know about support groups or meeting in your area where you can talk with other people with mental illness? 35. How much do you feel you know about organizations in your area for family members of people with mental illness?
0.38 0.52 0.62 0.57 0.75 0.79 0.73
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Table 2 (continued) Item
Factor loading
Knowledge of procedural assistance c 36. How much do you feel you know about how to find help with housing? 37. How much do you feel you know about how to find help with employment or job training? 38. How much do you feel you know about how to find help with applying for benefits like SSDI or Medicaid?
0.80 0.79 0.72
Empowerment—self agency c 39. How much do your opinions and ideas count in which services you get? 40. How much responsibility do you feel you have for the services you get? 41. How much input do you have into your rehabilitation plan and personal goals? 42. How much do these services help you learn to make your own decisions about your life? 43. How much do you rely on these services to help you through difficult times?
0.57 0.66 0.64 0.66 0.54
Empowerment—mental health services c 44. Do the people at these services care about you? 45. How much do you have the feeling of being cared about at these services? 46. How much does your overall service plan fit what you want? 47. How much do you feel your therapists or counselors really know what you need? 48. How much do these services give you a sense of competence that you have skills you can use? 49. How much do you think people providing these services want to see you get better?
0.77 0.78 0.64 0.67 0.62 0.63
Items deleted during factor analysis b 50. How do you feel about the way you spend your spare time? 51. How do you feel about the amount of time you have to do the things you want to do? 52. How do you feel about the chance you have to enjoy pleasant or beautiful things? 53. How do you feel about the amount of fun you have? 54. How do you feel about the amount of relaxation you have in your life? 55. How do you feel about the pleasure you get from the television or radio? 56. In general, how do you feel about your life as a whole? a b c
Item scores range from 1 to 5. Item scores range from 1 to 7. Item scores range from 1 to 4.
jective items using the first data set. In order to create a hypothesized model, we conducted another exploratory principal components analysis on the identified factors. Then, to test the model, we used the second data set. We conducted a confirmatory factor analysis to test the model (SAS Institute Inc., 1989). Using the modification indices from the confirmatory factor analysis, we made one alteration in the model, which we then retested using confirmatory factor analysis on the first dataset.
3. Results The first principal components analysis on the first data set yielded 14 factors. Six items were deleted at this stage: one item because it was the only item
loading on a factor (item 56), four items from the satisfaction with leisure QOL subscale that had factor loadings less than 0.40, and the last item because it was originally part of the satisfaction with leisure subscale and had a factor loading only slightly higher than 0.40 (items 50–55). We then repeated the principal components analysis. This yielded an 11factor solution with all items unambiguously loading on 1 factor, all but 1 factor loading greater than 0.40, and factors that were conceptually meaningful. Table 2 lists the included items, factor names and factor loadings for this solution. We then calculated factor scores by averaging Zscores of the appropriate items. Using these factor scores and the same dataset, we conducted a principal components analysis, yielding a superordinate threefactor solution (Table 3). We tentatively labeled these
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Table 3 Second-order exploratory factor analysis First order factor
Factor loading
Factor 1. Hope and optimism Current mental health Optimism Factor 2. Life satisfaction Satisfaction with family Satisfaction with social network Satisfaction with living arrangements Satisfaction with community Satisfaction with safety Factor 3. Empowerment Knowledge of mental health and services Knowledge of PSR services Empowerment—self-agency Empowerment—mental health services
0.76 0.84 0.66 0.67 0.75 0.80 0.71 0.76 0.65 0.75 0.69
three factors as empowerment, hope and optimism, and life satisfaction. The next step was to conduct a confirmatory factor analysis of the hypothesized three-factor model using the second data set. The Comparative Fit Index for the
model was 0.83 and the root mean square residual was 0.072. Inspection of the modification indices suggested that dividing the empowerment factor into two factors, knowledge and empowerment, would improve the fit indices. Repeating the confirmatory factor analysis using this four-factor superordinate model, the fit indices improved, yielding a Comparative Fit Index of 0.92 and a root mean square residual of 0.054. As a final test of the four-factor model, we repeated the confirmatory factor analyses on the first data set, and the same pattern emerged, in which the fit for the four-factor model (CFI=0.94, root mean square residual=0.066) was superior to the three-factor model. The final model, including path coefficients and error terms, is displayed in Fig. 1. The psychometric properties of the model were good. Although statistically significant ( pb0.0001), intercorrelations between the domains were small to modest in magnitude (r’s ranging from 0.14 to 0.38), suggesting that these dimensions are approximately orthogonal (Table 4). Internal consistency (Cronba-
Fig. 1. Confirmatory factor analysis: components of recovery.
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Table 4 Intercorrelations (and Chronbach’s a) of recovery domains Knowledge Empowerment Hope and optimism Life satisfaction
Knowledge
Empowerment
Hope and optimism
Life satisfaction
(0.86)
0.35 (0.90)
0.25 0.26 (0.75)
0.14 0.38 0.21 (0.92)
All correlations are significant at pb0.0001.
ch’s a) for these four dimensions was good: 0.90 for empowerment, 0.75 for hope and optimism, 0.86 for knowledge and 0.92 for life satisfaction.
4. Discussion We propose here four domains to serve as an initial approach to the conceptualization of the recovery orientation: the capacity to feel empowered in one’s life; self-perceptions of knowledge about mental illness and available treatments; satisfaction with quality of life; and hope and optimism for the future. We also propose a preliminary instrument with good psychometric properties and face validity for measuring these four domains of the recovery orientation. While it is understood that the recovery orientation has individual variations and is influenced by many factors, we propose that these four domains are of central importance. Many questions related to the recovery orientation can now begin to be explored with this preliminary instrument. Which sociodemographic, clinical and social characteristics are associated with a strong experience of the recovery orientation? Which interventions are most effective at inducing the recovery orientation? Is it possible to have graduated levels of the recovery orientation, or is there a threshold at which a person may be said to be bin recoveryQ? If recovery is a process, how can a measure of recovery be used as an outcome? The measurement of clinical significance is related to these last two questions. This concept, used primarily in longitudinal studies and psychotherapy research, suggests that meaningful cutoff points can be identified for various symptom measures. These cutoff points are then used to determine, among other things, the percentage of individuals who have returned to a normative range of symptoms, substance
use, etc., and who may be considered brecoveredQ (Jacobson et al., 1999; Roberts et al., 2000), using the traditional, symptom-oriented usage of recovery. Clinical significance, thus defined, has not been adopted in the research on treatment for individuals with severe mental illness, partly due to difficulties in determining normative comparison groups and the varied course of mental illness (Bond et al., 2001b). In recognizing that symptoms and functioning are often independent, others have suggested an expanded definition of clinical significance, in which the impact of interventions upon functioning, quality of life and society are considered (Gladis et al., 1999; Kazdin, 1999). This definition of clinical significance bears much similarity to the conceptualization of the recovery orientation we describe here. We thus propose that for those with severe mental illness, clinical significance is analogous to our conceptualization of recovery, but as an outcome, rather than an orientation. Our measure of the recovery orientation can thus serve as a tool for assessing interventions for their ability to assist practitioners and consumers in fostering recovery. The evidence-based practice (EBP) movement, another influential movement in the mental health field, provides a model for this type of assessment. The EBP movement, which promotes treatments supported by clinical trials, originates in the evidence-based movement in general medicine (Muir Gray, 1997; Sakett et al., 1996) and has become a primary force in the scientific community. The movement to support EBPs for the treatment of individuals with severe mental illness is most visible in the recent adoption and promotion of EBPs by several state mental health systems (Torrey et al., 2001). The EBP movement has been described as a polar opposite of the recovery movement, specifically in the conflict between the EBP movement’s emphasis on
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empirical and experimental evidence versus the recovery movement’s focus on internal, subjective experience (Frese et al., 2001). This dichotomization is not justifiable and is counter-productive. EBPs have the potential to provide the missing bhowQ-how states, mental health agencies and professionals can cultivate a recovery orientation, and equally importantly, assist consumers to achieve important objective goals that we hypothesize are critical to recovery, including participation in meaningful activity such as employment, access to stable and safe housing, and an adequate social support network, among others. The four main domains of the recovery orientation that emerged from our analyses, empowerment, hope and optimism, knowledge and life satisfaction, should be evaluated and carefully considered when designing services, and service systems, for people with severe mental illness. Additionally, we suggest that current EBPs may promote development of these four domains. 4.1. Empowerment The empowerment domain explained the greatest amount of variance in our model of the recovery orientation. Empowerment, as conceptualized here, refers to feeling empowered to take responsibility to make one’s own decisions and take responsibility for treatment, as well the feeling that one’s treatment and treatment providers are in concordance with one’s own treatment goals. Thus, our results suggest that promoting self-esteem and helping individuals discover and reach their goals will be especially helpful in the promotion of the recovery orientation. Supported employment may be a framework in which professionals can help consumers to clarify their goals and develop meaningful activity that promotes selfesteem (Bond et al., 2001b).
ment of hope and optimism among people. Peer provided services, in which consumers serve as role models for other consumers, may help to foster hope for those who are still learning to manage the symptoms of their mental illness (Mead et al., 2001; Solomon and Draine, 2001). 4.3. Knowledge Knowledge about one’s illness, the range of available treatments and ways to navigate the service system is another area of importance identified by our model. It is notable that the items do not measure objective knowledge, but instead reflect the individual’s perception of their knowledge, perhaps also reflecting their confidence in coping with mental illness. Interventions such as Illness Management and Recovery may be useful in helping consumers attend to their own personal experiences, manage symptoms, and achieve greater independence and less dependence on the mental health system (Mueser et al., 2002). 4.4. Life satisfaction Life satisfaction is increasingly included in empirical research, and as such, is probably the most frequently addressed domain of recovery attitudes. The subdomains included here—satisfaction with family, social network, living arrangements, community and safety—are centered on two main themes— relationships with others, and affordable, safe housing. Family psychoeducation may be a helpful tool for consumers who would like to improve communication with family members (Dixon et al., 2001), and case management services such as assertive community treatment may help consumers maximize their housing opportunities and create housing stability (Bond et al., 2001a).
4.2. Hope and optimism 4.5. Limitations and future directions An often-cited component of the recovery orientation is the fostering of hope-hope for the future, hope for achieving one’s goals and the importance of being surrounded by treaters, peers and family members who share realistic optimism and hope. Our results suggest that interventions for people with severe mental illness should seek to promote the develop-
Because the PORT survey was not originally designed to investigate the recovery orientation, we were limited in the concepts that we could include in our exploration. Future empirical efforts that focus on the measurement of recovery would benefit from first identifying recovery domains, and selecting items
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based on these domains. It will be necessary to continue to examine the structure of the recovery orientation with the addition of recovery dimensions such as those discussed in our introduction, and begin to develop a measure that adequately captures these domains. 4.6. Conclusions We began this paper with the assertion that recovery should be conceptualized as an orientation, reflecting the belief that recovery is a fluid process and an attitude, not an endpoint. We conclude that an empirical measure based on recovery attitudes may be used to measure recovery as a type of outcome, as well as a process. This duality allows for a full examination of the relationship between the recovery orientation and interventions, which we hypothesize is bi-directional. Those with a strong recovery attitude may benefit more from treatment and rehabilitation than those with a weaker orientation, underscoring the importance of promoting the recovery philosophy among professionals and treatment settings. Some interventions may be more helpful than others in promoting recovery attitudes, and as such, evaluations of interventions should include measurement of this type of clinical significance. Thus, the relationship between interventions and recovery may take the form of a virtuous cycle, in which the promotion of the recovery attitude becomes a critical process and a desired outcome.
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