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Trajectories of Recovery Among Formerly Homeless Adults With Serious Mental Illness

Published Online:https://doi.org/10.1176/appi.ps.201500126

Abstract

Objective:

Recovery from mental illness is possible, but individuals with co-occurring disorders and homelessness face challenges. Although a nonlinear recovery course is assumed, few studies have analyzed recovery over time. This mixed-methods study examined recovery trajectories over 18 months after enrollment in supportive housing programs of 38 participants with DSM axis I diagnoses.

Methods:

Qualitative interview data were quantified through consensual ratings to generate a recovery score for four waves of data collection based on eight recovery domains culled from the literature. Case study analyses were conducted of participants whose scores varied by one standard deviation or more between baseline and 18 months to identify which domains were important.

Results:

Most of the 38 participants (N=23) had no significant change in recovery; seven had a negative trajectory, and eight had a positive trajectory. Case studies of these 15 participants indicated domains that contributed to change: significant-other relationships (N=9), engagement in meaningful activities (N=9), mental health (N=7), family relationships (N=6), general medical health (N=5), housing satisfaction (N=5), employment (N=2), and substance use (N=1). Except for mental health and substance use (which contributed only to negative trajectories), the influence of domains was both positive and negative. Domains were intertwined; for example, variation in relationships was linked to changes in meaningful activities.

Conclusions:

This study showed little change in recovery over time for most participants and a decline in mental health for a small minority. Findings underscore the importance of social relationships and meaningful activities among individuals with serious mental illness, who experience complex challenges.

Research has shown that recovery from mental illness is possible for many affected individuals (15). However, those with complex problems such as substance abuse and homelessness face additional challenges. Few studies have examined changes in recovery from mental illness over time, even though a nonlinear course is assumed (6). In a two-year study of recovery in a well-insured predominantly white population, Green and colleagues (7) identified four trajectories of recovery among individuals with a diagnosis of mental illness: two stable (high and low levels of recovery) and two fluctuating (trending higher and lower). Bobes and colleagues (8) found that recovery was associated with illness-related factors previously found in other studies, including shorter duration of untreated psychosis (9), better premorbid adjustment (1013), and use of antipsychotic pharmacotherapy (11,14,15).

Recovery has been defined as “a vision, a philosophy, a process, an attitude, a life orientation, an outcome and a set of outcomes” (16). A primary difficulty in defining and measuring recovery is its idiosyncratic and subjective nature. In a narrative systematic review, 97 studies were identified and analyzed to produce a three-part conceptualization of the phenomenon of recovery (17). These three dimensions were characteristics of the journey (for example, unique, nonlinear, and active), recovery processes (connectedness, hope, identity, meaning, and empowerment, or CHIME), and recovery stages of change (based on the transtheoretical model) (18).

An operational view of recovery was adopted by Whitley and Drake (19), who outlined five types: clinical recovery (reduction in symptoms and in substance dependence), existential recovery (hope, empowerment, and spirituality), functional recovery (employment, education, and housing), physical recovery (health and well-being), and social recovery (social connections to family, friends, and the wider community). These dimensions are more directly linked to the challenges of recovery among persons with coexisting morbidities and other problems, the population of interest in our study. Thus we drew on Whitley and Drake’s recovery dimensions to address the following research questions: Are there changes in participants’ recovery trajectories over time? What is the lived experience of recovery over time?

In this mixed-methods study, a sample of formerly homeless study participants was followed over an 18-month period after entering supportive housing. Our overall goal was to understand the patterned ways that recovery changed over time, as well as individual experiences. Persons with serious mental illness who also have histories of homelessness and substance abuse have received less attention in the burgeoning literature on mental health recovery, and changes over time have seldom been documented.

Methods

Participants and Procedures

The study sample was part of a prospective (18-month follow-up) qualitative study conducted from 2011 to 2014. Participants were recruited as they entered two supportive housing programs in New York City. Written informed consent was obtained from participants prior to enrollment; 53 participants were enrolled during the accrual period. Eligible individuals had to meet the following inclusion criteria: history of homelessness and substance abuse, newly housed in the program (less than a month at the time of the initial interview), a DSM axis I diagnosis, and 18 years of age or older.

One participant was withdrawn from the study because of cognitive impairment, and 14 were lost to follow-up because of relapse or incarceration. No significant differences were found in average age, gender, or racial-ethnic composition of this group compared with the 38 who were retained in the study. Data from the 38 participants were included in this analysis (33 completed all four waves of interviews at baseline and at six, 12, and 18 months, and the remaining five completed the baseline plus the 18-month interview and either the six- or the 12-month interview).

In the qualitative interviews, participants were asked to speak about their experiences across eight domains of recovery adapted from Whitley and Drake (19). These included mental health, general medical health, work and employment, family relationships, substance use, significant-other (friend or partner) relationships, housing satisfaction, and engagement in meaningful activities. Interviews lasted 90 minutes on average and were audio-recorded and transcribed verbatim. Participants were provided $30 cash plus a round-trip subway voucher. All study procedures were approved by the New York University Human Subjects Committee.

Data Analysis

Recovery Ratings and Change Over Time

Qualitative interview data were quantified to generate a recovery score for each participant at each wave of data collection. This “quantitizing” technique was used in order to make systematic comparisons across individuals (20). The original interviewer (BTS, MC-B, or ET) and a second team member (DKP, BTS,MC-B, or ET) independently completed ratings of each transcript across the eight common recovery domains. Each domain was rated on a scale from 1 to 3 for low, mixed, and high recovery, respectively, and participants were given an overall recovery score ranging from 8 to 24 for each of the four waves. Ratings of transcripts (N=147; approximately 4,500 pages of text, 30 pages per transcript on average) resulted in 1,176 observations and 147 scores. Consensus was used to resolve any discrepancies between the raters. We graphically plotted these scores with trend lines and calculated the trend in the trajectories as being positive or negative (defined as an increase or decrease of more than 1 standard deviation from the mean score at baseline versus 18 months) or no change.

Qualitative Analyses Using Case Studies

Following a sequential mixed-methods design, the trajectories were used to guide qualitative data analyses of domains associated with positive and negative trajectories. Individual trajectories that showed upward or downward movement were identified for additional analyses of the individual domains and their contribution to (or hindrance of) recovery. Our approach echoed earlier work by Singer and colleagues (21) in which individual trajectories are kept intact (person centered) as much as possible despite being dependent on quantitative measures (variable centered). Following Stake’s (22) guidelines on case study analysis, we assembled sources of data for each case, including all interview transcripts and interviewer observation forms (filled out after each interview). One research team member (BTS) independently read all the documents while linking the narratives to changes in the trajectory. Another team member (DKP) independently reviewed the case files, and consensus was reached on how positive or negative changes were voiced by the participants.

Results

Quantitative Findings

Most participants were male (N=31, 82%) and African American (N=32, 84%), followed by Hispanic (N=3, 8%) and Caucasian (N=3, 8%). Participants were between 22 and 63 years of age, with a mean±SD age of 42.7±7.0 years. Most (N=23, 61%) had no change in recovery, seven (18%) had a negative trajectory, and eight (21%) had a positive trajectory. Table 1 shows the mean recovery scores at each wave. There were only modest differences, with a slight drop at the 12-month wave.

TABLE 1. Recovery scores over time among study participantsa

Time pointParticipantsMSD
Baseline3816.552.18
6 months3416.381.92
12 months3715.922.54
18 months3816.323.09

aPossible scores range from 8 to 24, with higher scores indicating greater recovery.

TABLE 1. Recovery scores over time among study participantsa

Enlarge table

We used our criterion of more than one standard deviation in change to construct a 15×8 matrix, with participants who met the criterion (N=15) arranged in the rows and the domains arrayed across the columns. A valence—positive, negative, or no change—was noted in each cell.

Case Studies of Recovery Domains Over Time

In rank order, beginning with the most frequent, the domains that contributed to change in the overall recovery score and the numbers of individuals affected were significant-other relationships (N=9), meaningful activities (N=9), mental health (N=7), family relationships (N=6), general medical health (N=5), housing satisfaction (N=5), employment (N=2), and substance use (N=1). The lack of salience for the last two of these domains reflects the absence of work opportunities for persons with psychiatric disabilities and the relatively stable state of substance use recovery in participants’ lives. To provide context for this observation: one of the supportive housing programs mandated abstinence, but several participants in both programs reported occasional use of marijuana, and only one participant reported significantly increased substance use during the study.

The top two contributors to recovery operated in both positive and negative ways. Thus a change in significant-other relationships affected six participants positively (finding a romantic partner or close friend) and three participants negatively. Engaging in meaningful activities increased for six participants and decreased for three. Participants who experienced a positive change in significant-other relationships (N=5) or family relationships (N=2) also showed a positive change in engagement in meaningful activities. The mental health domain was only negatively influential, adversely affecting the recovery of seven individuals. Valences for the family relationships domain were evenly split between positive and negative. Housing satisfaction was a negative influence for four of the five participants, and general medical health was negative for three participants and positive for two. With regard to housing satisfaction, this negative influence was attributed to financial problems experienced by one of the programs, leading to fears of eviction among four study participants.

For 13 of the 15 participants, the valence of domains matched their overall recovery trajectory valence. Only two had a mix of both positive and negative change across the domains. For both, the mental health domain was negative and family relationships or significant-other relationships and meaningful activities were positive.

In returning to the person-centered aspects of individual trajectories, we used the case study analyses to trace the contexts of these domains. Not surprisingly, these were intertwined in individuals’ lives. For example, Darren (all names are pseudonyms) became close friends with a client and her boyfriend at a resource center he attended. This friendship paved the way for engagement in meaningful activities together, where before he had kept to himself and stayed in his apartment. In describing this relationship, he stated, “We talk, we get along. . . . I go visit them . . . they’ll cook for me. . . . We watch TV. She does a lot of talking about different things just going on in her life or what she has to do, or sometimes she asks me questions about me, and I answer her [to] the best of my knowledge. I call her sometimes for advice and she calls me up for advice sometimes.”

Similarly, Fay became friends with some of her neighbors and reconnected with her sisters. These relationships also contributed to an increase in participation in meaningful activities. She described “go[ing] to the movies with my friends or clubs . . . Manhattan [clubs] with my sister. . . . We have fun. . . . Me and my sisters are getting along now.”

Conversely, relationship troubles contributed to a reduction in meaningful activities. Yolanda used to see her now-adult children on a routine basis. However, she noted, “My family’s really not giving me that much support nowadays. They really have given up on me.” During the study, she came to spend more time alone in her apartment. “I don’t have any activities. . . . All activity is really just focused in this apartment. . . . My children stopped coming here to see me. . . . They used to come see me every—very often. For some reason they just backed up. . . . I really wish they were part of my life, so much involved in my life.”

New friendships and activities were not always positive. Anthony became involved with a woman who was using drugs and would accompany her to a local park where drug dealing as well as substance use was common. “I was down here at [local park]. . . . I went along with it at first, but then things that she did I didn’t want. . . . She’s out there at all hours in the night trying to get drugs. . . . I’m trying to tell her, ‘You cannot be doing this every day because sooner or later that’s going to catch up to you.’”

During one evening at the park an altercation broke out, and Anthony was concerned about getting caught up in it. He elaborated, “They was getting loud. They was also drinking. The police rolled up . . . asked us politely to all please take a walk. . . . I don’t know because I was not trying to get wound up into this situation and stuff because I’ve got my own problems. . . . Since I came into [supportive housing agency], I have not messed up. I’m about to be three years clean, straight.”

Anthony explained that it was not until he met a more positive female friend that he “started hanging out with her instead of coming down . . . to the [local] park because all the nonsense that goes on.” Developing multiple social relationships enabled participants like Anthony to be more selective about the people they chose to associate with and the activities that they took part in.

Mental deterioration was attributed to isolation, depression, and stigma rather than psychotic symptoms. Sylvester checked himself into a hospital psychiatric ward, saying he felt extremely depressed and lonely. Although desiring relationships with others, he thought that his medications would provoke stigma and further isolate him. “I’m tired of all these pills. If you went into my apartment, into my room, it’s the whole dresser. . . . I can’t put them away, I don’t know where to put them. I got to put them somewhere. I am trying to see if I can get some company. Get some guts and see if I can find a friend. But . . . too many bottles. . . . I don’t want them to see them and say, ‘Why you taking all these pills. What’s wrong with you?’”

For Judith, the increasing toll of diabetic complications was further exacerbated by partner abuse and a decline in mental health, leading to heavier use of marijuana. “I’m struggling with my health. Physically and mentally. So that’s two things right now that are so far against me. . . . I got a therapist and a clinic that doesn’t even really want to talk to me or hear me. I don’t have no family here. It’s supposed to be him [husband]. . . . Not only am I lonely, I feel alone . . . and then when he’s here, all he does is badmouth me. Calling me names.”

Discussion

In this mixed-methods study, we used longitudinal interview data to generate quantitative and qualitative assessments of recovery in a vulnerable population of formerly homeless men and women with a diagnosis of serious mental illness. Our analyses and findings followed a sequential design in which the quantitative results were used to identify a subsample for further case study analyses iteratively examined by using a matrix of domains arrayed by cases. Each case was examined holistically to understand the interplay of positive and negative changes.

In returning to our research questions, we note that there was modest change in recovery affecting a minority of participants (15 of 38), and for only eight of these participants was the change in a positive direction. The domains most likely to positively affect recovery—having a close friend or partner and engaging in meaningful activities—had a correspondingly negative effect on recovery when they declined. The frequency to which family and significant-other relationships contributed to change in participants’ lives further points to the salience of social relationships in recovery. Meanwhile, some domains—employment and substance use in particular—showed minimal impact on recovery (positive or negative).

As noted by Singer and colleagues (21), the “thinning down” of life histories necessitated by the desire to make comparisons—and the subsequent reliance on quantitative measures—diverts attention from interconnections and dynamic change. Our approach reduced recovery to eight domains in order to compare across individuals over 18 months’ time, but the individuals in our study also led complex lives that transcended these domains.

As with many individuals with a diagnosis of serious mental illness, recovery is a “work in progress” (13). Moreover, the combined impact of homelessness, mental illness, and substance abuse is unlikely to be reversed in a short time. As noted by Henwood and colleagues (23) recovery is not a simple matter of satisfying basic needs before proceeding to other life goals. Our findings point to the central role of social relationships and the pursuit of meaningful activities, such as going to the movies, a library, or the local park, in contributing to a positive recovery trajectory for participants. For the participants with a negative trajectory, the undertow of poor mental health took its toll. Yet even here, their attributions focused more on social isolation and betrayal by family and friends than on an increase in psychotic symptoms.

The recent push toward recovery-oriented services and person-centered care planning (24) highlights the importance of individual trajectories. We were struck by the continued unemployment in our study sample. More positive was the steady control over substance use (one of few domains over which participants felt they had agency or control). Although family relationships could be fulfilling, they could also be problematic. Previous research has shown severe depletion of social networks in this population (25), and assistance in restoring social relationships must take this into account. Finally, we note that general medical problems (in addition to mental problems) hindered recovery by reducing mobility and quality of life.

We acknowledge that the “quantitizing” process, while independently rated and consensual, could be subject to ratings error. Such post hoc ratings have the advantage of drawing on in-depth knowledge of the study participants on which to base ratings. With regard to the domains of recovery, these were consonant with mainstream definitions, but they fell short in assessing hope and future aspirations (18) because these phenomena were difficult to reliably capture from the data. We also acknowledge that our sample may have been biased toward “better scenario” cases given the reasons for attrition (substance abuse relapse and incarceration).

This study had strengths, including the use of strategies for rigor (26), such as prolonged engagement with participants, peer debriefing, and independent ratings of recovery followed by consensus building. Our aim was to draw on subjective reports in the service of objective indices and then return to participants’ accounts via case study analyses to contextualize their meaning. The qualitative case study analyses were not used to corroborate but to expand on the quantitative findings, a common strategy in mixed-methods designs (27). A final strength is the longitudinal design. Studies of changes in recovery over time using mixed methods are relatively rare, and when conducted with this particular population, rarer still.

Conclusions

For individuals struggling with mental illness, homelessness, and substance abuse, the roadblocks to recovery can be daunting. Our study showed salient contributors to recovery over time (improvements in social relationships, engagement in meaningful activities, and maintenance of substance abuse recovery), as well as their interconnectednss. Recovery-oriented research and services can be improved by going beyond the alleviation of psychiatric symptoms to address consumers’ perceptions as well as nonclinical aspects of their lives. Moreover, the interconnectedness of different domains of recovery affects an individual’s recovery journey in patterned yet unpredictable ways.

Dr. Padgett, Ms. Choy-Brown, and Dr. Mercado are with the Silver School of Social Work, New York University, New York City (e-mail: ). Ms. Smith is with the School of Social Service Administration, University of Chicago, Chicago, Illinois. Dr. Tiderington is with the School of Social Work, Rutgers University, New Brunswick, New Jersey.

This project was supported by grant R01-MH084903 from the National Institute of Mental Health.

The authors report no financial relationships with commercial interests.

The authors thank the study participants.

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