Be Consistent

Be Consistent

Be Consistent
One of the best aids to clear thinking is a consistent world view that you can use in all modes of thought, with all of your worldly knowledge, and all of your memories. With a consistent world view it is easier for the various parts of your brain to function in unison, leading to more powerful thinking. A consistent world view helps you to gather information about the world in an objective manner so that all parts of your brain can utilize the same input.
In practice we tend to develop a variety of mental models to cope with particular situations, as we encounter them. The challenge is then to review the characteristics of those models and try to modify them so that they are consistent with each other. I can remember as a child struggling with the concepts that anything lighter than water, such as wood, will float and anything heavier than water, such as steel, will sink – and yet battleships and ocean liners are made of steel and seem to float very well. These mental models of flotation were inconsistent with each other and inspired a lot of pondering and quests for more information. A version of Archimedes’ principle was required to bring these two models of reality into agreement.
Note that inconsistent behaviour involves using one set of guiding principles in one situation, and a conflicting set of principles in a different situation, without you necessarily being aware of any contradiction.
Here are a few examples of inconsistent mental models:
1. While the ancient Romans created disciplined and well-equipped armies, they often relied on augury to determine a good day for battle. Their training and weapons were based on logic and proven battle tactics, but examining a sheep’s liver for favourable signs before going to battle was completely arbitrary.
2. In democratic countries, special interest groups often organize large public protests in efforts to influence government policy. In effect, such public protests are intended to subvert the activities of elected officials – and thus make a democratic government responsive to their group rather than to the entire electorate.
3. Someone who uses a computer to prepare an essay on the ‘evils of technology’ may not be thinking in a consistent manner.
4. The concept of an all-powerful and loving god appears to be inconsistent with the abundant suffering of innocents that such a god could easily prevent.
Working with a consistent mental model is analogous to working with a universal system of measures and weights, such as the metric system. A common set of weights and measures facilitates trade and technical communications between countries.
Tools manufactured in one country can be used to repair a machine manufactured in another. A consistent world view facilitates communication among various mental models. Solutions to problems in one realm can be adapted for use in other realms.
A consistent world view also helps you to understand the past, predict the future, and deal with various individuals and groups of people.

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Approaches to Clear Thinking

Approaches to Clear Thinking

Approaches to Clear Thinking
This last section of the chapter presents a few practical approaches to clear thinking.

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Reality Anchors in the Physical Universe

Reality Anchors in the Physical Universe

Reality Anchors in the Physical Universe
How do you know that any of the three physical zones are real? For that matter, how do you know anything is real? How can you decide between two opposing views of reality?
According to the German philosopher, George Hegel (1770 – 1831), the gradual evolution of the history of ideas leads to the perception of reality. The American philosopher, John Dewey (1859 – 1952), claimed that truth and reality were based on distillations of the rules for action that had proved to be successful.
A more pragmatic approach is that you should be able to detect reality, directly or indirectly, through your senses. On a fundamental level you can touch reality, smell it, and taste it. More precisely, you can measure the properties of reality and you can measure how those properties vary over time.
The use of ‘reality anchors’, analogous to mental anchors, provides a very practical means for establishing your model of reality. A reality anchor is a particular concept in which you have a high degree of confidence. A set of such anchors can help you to maintain a dependable interpretation of reality and provide a framework for reasonable interpolations and extrapolations.
Reality anchors in the everyday realm
The simplest and most reliable anchors are based on direct experience. Your kitchen table is real. You can touch it. You can pile stuff on it. You can measure it. You can leave the room, come back ten minutes later, and there it is again – the same table.
The kitchen table may be one of your first and best anchors in reality. You can expand your realm of reality, and experience your entire home in a similar fashion.
Outside of your home, you can also experience your neighbourhood as a firsthand reality. However, a number of practical difficulties soon become apparent. Your neighbours may not be supportive of your efforts to experience their kitchen tables.
And very soon there would be too many tables, buildings, roads, blades of grass, trees, and fields for you to experience firsthand in a reasonable amount of time. Even if you spent your whole life at it you would never get more than a few kilometres from home.
There are at least two standard procedures for extending a system of reality anchors:
1. The first is to construct a mental model of an aspect of reality that you can use in lieu of firsthand experience. (See section 5.3 for a more complete discussion of models.) After visiting a few buildings you begin to acquire knowledge of their typical properties such as room size, ceiling height, stairs, doors, windows, desks, chairs, and appliances. Soon you can predict, with a reasonable degree of accuracy, the basic structure of the inside of a building after a brief view of its exterior and its surroundings. Similarly, you can soon predict the basic nature of the soil in a whole field just by holding a handful of dirt (sand, loam, pebbles) and glancing at the plants growing in the field.
2. The second way to extend your reality anchors is to rely on the experience of others. Travellers can tell you what they experienced in the next town down the road. They might tell you directly, or you might be able to review recorded versions of their observations.
How can you decide if travellers’ accounts are true and accurate? Continuing the analogy, you can apply one or more of the following criteria:
1. The accounts are reasonable extensions of your own experience in your own neighbourhood.
2. You know some of the travellers personally and trust their ability to observe and report accurately.
3. Some of the travellers are recognized by your neighbours as experienced and truthful observers and reporters.
4. A number of travellers, unknown to each other and coming from different directions, all report similar observations.
5. The traveller explains how to visit the same places he did, so if you wanted to devote the time and energy to do so you could travel down the road to observe the next town for yourself.
Not all reality anchors are equivalent. An anchor that has met several of the above tests is probably more secure than one that has not. If you spend considerable time and effort in expanding your range of anchors and securing them well, then you will probably have a better grip on reality than someone who just checks the kitchen table every now and then.
Reality anchors in the realm of the very large
Around the world, thousands of astronomers spend their professional lives collecting and analyzing astronomical data obtained with sophisticated telescopes and satellites.
All such information gathered during the past three centuries has been used to build a systematic, and consistent model of the cosmos. With ever larger and more complex astronomical instruments new discoveries and clarifications are still being made on a regular basis.
How could you as an individual verify the claims about the properties of this realm? You could use a clock and a protractor to make systematic observations of the positions and apparent motions of the Sun, Moon, and stars. This data could then be used to verify at least a portion of those claims. You could check your position on Earth with a Global-Positioning-System device and verify that all the orbital theories and instrumentation work as advertised. You could read magazines, journals, and texts on astronomy. You could join an association of amateur astronomers. With a few thousand dollars-worth of equipment, and the determination to develop the skills to use that equipment properly, you could observe the moons of Jupiter, the rings of Saturn, comets, multiple star systems, globular clusters, nebulae, and galaxies. You could study astronomy at a university; you could become a professional astronomer.
With accurate and systematic observations spanning months, years, and decades; you could determine the orbits of our planets about the Sun; you could determine the orbits, sizes, and masses of binary stars; you could determine the periods of stars that oscillate in brightness. With more sophisticated equipment and mathematical analyzes you could measure the velocities of stars and galaxies, and determine their distances.
None of this information is secret. If you are willing to spend the time and effort, you could make all the observations and deductions yourself. If you discovered something substantially new or different, the attention of thousands of amateur and professional astronomers would be diverted to explore your claims. And if your discovery were confirmed, existing knowledge would be adjusted and updated to include it.
Reality anchors in the realm of the very small
The realm of the very small is studied by microbiologists, material scientists, biochemists, organic and physical chemists, quantum physicists, and electronic engineers. In the past few centuries they have developed sophisticated instruments to explore the properties of microscopic materials. With this knowledge they have developed new materials, new medicines, and the whole field of electronics. The Internet, e-mails, cell phones, digital TV, iPods, penicillin, and digital cameras all exist because scientists have developed and successfully applied theories of the very small.
How could you verify descriptions and claims about the properties of the realm of the very small? An inexpensive microscope and some basic skills in sample preparation would provide the means for you to observe amoebae, paramecia, plant cells, and animal cells. The structures of crystals such as table salt, ice, and diamonds are reflections of the properties of their constituent atoms. Any working device using transistors supplies a verification of the quantum properties of material at the very small level. Turn on your television set, or your computer, and you have evidence that engineers can manipulate the flow of electrons to transfer energy and information. You could also read technical journals and texts; you could study appropriate courses at university. You could ask experts in the field: a microbiologist could provide details of living organisms as small as the structures within cells, a chemist could provide details of atomic structure, a particle physicist could provide descriptions of subatomic particles.
An expanded world view helps you to appreciate that the universe is an integrated system of physical events. Every day, humanity is applying its talent, tenacity, and curiosity to expand our knowledge of the universe.

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Stages of Recovery Instrument

Stages of Recovery Instrument
The final consumer-oriented measure of recovery described in this section is the Stages of Recovery Instrument (STORI: Andresen, Caputi and Oades, 2006). 

The STORI is a 50-item self-report measure that yields five subscales corresponding to the five stages of recovery, Moratorium, Awareness, Preparation, Rebuilding and Growth. The development of the STORI is grounded in the stage model of recovery (Andresen, Caputi and Oades, 2003). As outlined in Andresen, Caputi and Oades (2006), item generation was significantly influenced by five key studies that identified stages or phases of recovery (Davidson and Strauss, 1992; Baxter and Diehl, 1998; Pettie and Triolo, 1999; Young and Ensing, 1999; Spaniol et al, 2002).
In particular, these studies provided evidence for the four component processes associated with recovery – finding and maintaining hope, re-establishing a positive identity, finding meaning in life and taking responsibility for one’s life (Andresen, Caputi andOades, 2006, p. 974). Conceptually, the STORI has a complex structure reflecting the four component processes that are assumed to vary across five stages of recovery.
Recently, the STORI has received growing attention in the psychological and psychiatric literature. For instance, Deane and Andresen (2006) have used the STORI in a review of a volunteer programme to increase and support social contact and friendships with people with mental illness. Puschner et al. (2010) have included a 30 item version of the STORI in an international study of the outcomes of clinical decision making with individuals with serious mental illness. Given its increased use in research and practice, what can be said about the psychometric properties of the STORI? We provided initial support for the internal consistency of the subscales representing the stages of recovery with alpha coefficients ranging from 0.88 to 0.94 (Andresen, Caputi and Oades, 2006). Weeks, Slade and Hayward (2010) also reported strong alpha coefficients for these subscales with Cronbach’s alpha coefficients between 0.81 and 0.87. They also found strong evidence for the temporal stability of the subscales with re-test reliability coefficients of at least 0.90 for each stage subscale.
There is also evidence for the concurrent validity of the STORI. In our original paper (Andresen, Caputi and Oades, 2006) we correlated the STORI subscales with a set of measures that included the Mental Health Inventory – five item version (Stewart, Hays and Ware, 1988) – the RAS, the Psychological Well-Being Scales (Ryff and Keyes, 1995), the Adult State Hope Scale (Snyder et al., 1996) and the Connor–Davidson Resilience Scale (Connor and Davidson, 2003). A distinct pattern of relationships emerged from this analysis. We found negative correlations between the subscale for Moratorium (stage 1) and the other measures (ranging from 0.44 to 0.68); on the other hand significant positive associations were observed between the subscale for Growth (stage 5) and the other measures (ranging from 0.53 to 0.79) (Andresen, Caputi and Oades, 2006). There were no significant associations observed between stage 3 subscale and the other measures. There were only some negative associations found for the stage 2 subscale, and some significant positive correlations between the stage 4 subscale and the other measures. The pattern of correlations, increasing from negative in stage 1 through to highly positive at stage 5, lend some support to the ordinal nature of the stages of the model.
Moreover, we concluded that these patterns of findings suggest that stages 2, 3 and 4 subscales may be measuring variables not detectable by the other measures used in their study (Andresen, Caputi and Oades, 2006).
Weeks, Slade and Hayward (2010) observed a similar pattern of relationships between the subscales of the STORI and the RAS, finding a strong negative association between the RAS and the Stage 1 subscale and moderate to strong positive associations between the RAS and the subscales of Stages 3, 4 and 5, with the correlations in increasing size from Stage 3 (r¼.458) to Stage 5 (r¼.735). Weeks,Slade and Hayward (2010) argued that these findings suggest the sequential or ordinal nature of stages. We also found evidence for ordinality when examining the inter-correlation of stage subscales (Andresen, Caputi and Oades, 2006). Stage 1 scores were positively correlated with stage 2 and 3 scores (r¼.33 and .22, respectively), but negatively correlated with stage 5 scores (r¼ .05). There was no correlation between stage 1 and stage 4 scores. Stage 2 scores were positively correlated with stage 3 and 4 scores (r¼.88 and .66, respectively), and stage 3 scores were positively correlated with stage 4 and 5 scores (r¼.82 and .29, respectively).
Stage 4 and 5 scores were also correlated (r¼.52). We argued that this pattern of correlations provided support for the validity of the subscales of the STORI – proximal stages were positively correlated, while distal stages had weak association, with the most distal stages being negatively correlated.
In our original investigation, we conducted a cluster analysis of the items of the STORI to determine whether they clustered into the five theoretically determined stages of recovery (Andresen, Caputi and Oades, 2006). Interestingly, the most interpretable solution contained only three clusters. The first cluster comprised stage 1 items; the second cluster consisted of stage 2 and 3 items as well as four stage 4 items; the third cluster consisted of the stage 5 items and six stage 4 items. Similarly, Weeks, Slade and Hayward (2010) also found a three-cluster solution for the items of STORI. These findings point to further research focusing on whether the STORI items discriminate between the stages (Andresen, Caputi and Oades, 2006). However, at a more fundamental level it does raise the question (as noted by Weeks, Slade and Hayward, 2010) of whether recovery is best described by a three or five stage model. Conceptually, we have argued for a five-stage model of recovery (Andresen, Caputi and Oades, 2003). However, empirically, the evidence points to a three-stage model. We addressed this anomaly by considering a general issue with psychological change models (Andresen, Caputi and Oades, 2006) and drew on Smedslund (1997), who argued the stage models of change, such as the Transtheoretical Model, would describe the behavioural outcome for smoking cessation as either smoking or non-smoking. However, there are processes that described the intermediate stages between smoking and non-smoking. Similarly, a three-stage model of recovery may represent a distinction between stages hopelessness, loss of identity and meaning in life; transition; and finally growth.
However, such a conceptualization may not explain the complex nature of recovery from serious mental illness. Perhaps further effort should be directed to testing the ability of the STORI to discriminate between the five stages of the model. 

The absence of empirical evidence for a five-stage model may be a measurement issue rather than a conceptual one.

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Short Interview to Assess Stages of Recovery

Short Interview to Assess Stages of Recovery
The Short Interview to assess Stages of Recovery (SIST-R: Wolstencroft et al., 2010) is a brief interview-based measure that identifies an individuals’ stage of recovery from mental illness. Our motivation for developing the SIST-R was twofold: We wanted to develop a recovery measure that would (i) be feasible and acceptable for clinicians to use in various service settings, and (ii) facilitate collaborative discussion between consumer and clinician, therefore allowing the possibility to explore ‘something more’ in terms of understanding the process of recovery. The SISTR encompasses the elements of feasibility espoused by Slade, Thornicroft and Glover (1999). Consequently, the SIST-R is brief, easy to use, adopts language that is relevant, and seen as a valuable tool in supporting consumers and practitioners within recovery-oriented services.
The interview schedule consists of five questions. Each question is read out to the respondent who is then asked to make a choice between two options, A or B in each question. If the respondent chooses option A then his or her stage is identified at that point. If option B is chosen then the respondent proceeds to the next question with options A or B. To illustrate, consider the first question from the interview schedule: A) Do you find it difficult to feel hopeful about your future or in control of what is happening to you?
OR
B) Do you think that there are things that you could possibly do, or will be doing in the future, that will help you to recover and take you beyond how you feel today? Choosing option A would suggest the respondent is in the Moratorium stage of recovery, while choosing B would suggest the respondent may be in the Awareness stage of recovery. The interview continues through the questions until the respondent chooses option A. If the respondent arrives at question 5, he or she will finish by choosing option A, which will indicate the stage of Growth.
A description of the development of the SIST-R is provided by Wolstencroft et al (2010). We report some preliminary psychometric findings for the SIST-R, although some caution is needed in interpreting these findings given they are based on a sample of 18 consumers (Wolstencroft et al., 2010). Initially, the concordance in the stage of recovery as identified by the SIST-R and the Stages of Recovery Instrument (STORI – see the next section for a description; Andresen, Caputi and Oades, 2006) was assessed. We found substantial concordance between the two measures, thus providing preliminary evidence for the validity of the SIST-R as a measure of recovery (Wolstencroft et al., 2010).
We also examined the construct validity of the SIST-R. Participants’ scores on the Kessler-10 and the subscales of the RAS were correlated with those of the SIST-R (Wolstencroft et al., 2010). Low to moderate correlations were observed between the RAS subscales and the SIST-R.Asmall negative correlation was observed between the Kessler-10 and the SIST-R. However, given the small sample size there is a need for further research to examine whether these relationships are present in a larger sample .

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Self-Identified Stage of Recovery

Self-Identified Stage of Recovery
The Self-Identified Stage of Recovery (originally named the Stage of Recovery Measure) is a brief, two-part measure of recovery. Part A of the Self-identified Stage of Recovery (SISR-A) consists of five statements (each statement consisting of two sentences) that reflect the five stages of recovery. Respondents select the statement that best reflects their current experience of recovery. For example, a respondent may chose the statement ‘I don’t think people can recover from mental illness. I feel my life is out of control, and there is nothing I can do to help myself’ reflecting the Moratorium stage.
Part B of the SISR (SISR-B) consists of four statements reflecting the four processes of recovery: Hope, Responsibility, Identity and Meaning. Respondents rate each statement on a six-point scale from 1¼‘Strongly disagree’ to 6¼‘Strongly agree’. For instance, the process of Meaning is reflected in the statement ‘The things I do in my life are meaningful and valuable’. A respondent would rate the extent to which he or she agrees or disagrees with this statement.
There is some evidence that the psychometric properties of the SISR are sound. Chiba, Kawakami, Miyamoto, and Andresen (2010) have developed a Japanese version of the SISR. They evaluated the psychometric properties of this version of the SISR using a sample of 223 participants with long-term mental illness drawn from both community and inpatient settings. Chiba et al. (2010) reported acceptable levels of internal consistency (Cronbach alpha coefficient greater than 0.70) for the total score of the SISR-B in both the community and inpatient samples. Further, Chiba et al. (2010) also tested the temporal stability for the SISR-A and the SISR-B, and found some evidence that these measures were stable over time. The reported statistics were modest, but acceptable, prompting the need for further research around the stability of the measure over time.
Chiba et al. (2010) also examined the concurrent validity of the SISR-A and SISR-B. Total scores for the SISR-A and SISR-B were significantly correlated with the RAS, the Japanese version of the Herth Hope Index (Hirano et al., 2007; as cited in Chiba et al., 2010), the Japanese versions of theEmpowermentScale(YamadaandSuzuki, 2007; as cited in Chiba et al., 2010) and the Resilience Scale (Oshio et al, 2002; as cited in Chiba et al., 2010). These findings provide support for the validity of the SISR-A and SISR-B. We compared the relationship between the SISR and two other measures of recovery, the Recovery Assessment Scale (RAS: Corrigan et al., 1999b) and the Mental Health Recovery Measure (MHRM; Young and Ensing, 1999; Ralph, Kidder and Phillips, 2000) in a sample of adults with a diagnosis of a psychiatric disorder and high support needs (Andresen, Caputi and Oades, 2010). We found high correlations between the SISR-B and the MHRM and RAS, and lower correlations between the SISR-A and the other recovery measures. We then compared the SISRA and the individual SISR-B items of Hope, Identity, Meaning and Responsibility to the subscales of the RAS and MHRM, and found low to moderate correlations. The findings not only provided further support for the validity of these measures, but they highlighted that the SISR-A, being a stage measure, is assessing unique aspects of recovery not assessed by contunuous recovery measures.
We also looked at whether the RAS and MHRM scores differed across stages assessed by the SISR-A (Andresen, Caputi and Oades, 2010). One would anticipate lower scores on the RAS and MHRM in the Moratorium stage than at later stages, and highest scores in the Growth stage. Standardized total scores for the RAS and MHRM differed significantly across stages, and as anticipated, scores increased steadily across the stages of recovery. Significant differences were also observed in some of the subscales of the RAS (Personal confidence and hope, Goal success orientation and Not dominated by symptoms) and all subscales of the MHRM except Overcoming stuckness. These findings provide useful insight into what might be important in recovery, and demonstrate the theoretical utility of the SISR. For example, we found that scores on Reliance on others and Willingness to ask for help (subscales of the RAS) were higher at Moratorium than at Awareness. Given the conceptual association between these two subscales, this result suggests that, while asking for help is important in recovery, it may not be sufficient for higher levels of recovery (Andresen, Caputi and Oades, 2010, p. 315).
Notably, we also found evidence that recovery measures such as the RAS,MHRM and SISR assess aspects of recovery that are not detected by traditional clinical measures (Andresen, Caputi and Oades, 2010). We examined the relationship between four clinical measures, the Health of the Nation Outcome Scales (Wing et al., 1998), the Life Skills Profile-16 (Rosen, Hadzi-Pavlovic and Parker, 1989), the Global Assessment of Functioning (American Psychiatric Association, 1994) and the Kessler-10 (Andrews and Slade, 2001), and the RAS, MHRM, SISR-A and SISR-B. There was little relationship between recovery and clinical measures. Only the Kessler-10 was found to be correlated with the recovery measures. These findings support the position held by consumers that traditional approaches to outcome measurement overlook things that are important to them in their recovery process.

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Measures Based on the Stage Model of Psychological Recovery

Measures Based on the Stage Model of Psychological Recovery

Measures Based on the Stage Model of Psychological Recovery
The model of psychological recovery we presented in Chapter 2 provides a framework for operationalizing the subjective experience of recovery. It describes the psychological process of recovery from the trauma of the illness, and focuses on positive outcomes. To recap, the model identifies four key psychological processes:
finding and maintaining hope; taking responsibility for one’s life; the re-establishment of a positive identity; and finding meaning and purpose in life. These processes take place over five stages of recovery: Moratorium, Awareness, Preparation, Rebuilding and Growth (Andresen, Oades and Caputi, 2003). Due to the highly personal nature of recovery, the model is purposely flexible in terms of the means by which the person moves through this process. That is, each individual finds his or her own sources of hope, ways of finding meaning and building a positive identity.
We have developed three measures based on the model. The measures are both subjective and non-prescriptive, focusing on positive psychological health .

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Measuring Consumer-defined Recovery

Measuring Consumer-defined Recovery

Measuring Consumer-defined Recovery
Measures of consumer-oriented outcomes go only part of the way to the goal of ensuring that services promote recovery. What is required are measures of recovery as it has been defined by consumers (Davidson et al., 2006). However, given that recovery is represented as a unique, personal journey, there has been a reluctance to define it as an outcome, as this is seen as prescribing what recovery should be for all consumers (Torrey et al., 2005). Torrey and colleagues noted that the outcome goals identified by consumers are usually those things commonly sought by everyone, such as a home, a partner or work. While this is true, measures based on a specified set of goal domains would be contrary to the recovery movement’s drive for empowerment and self-determination (Torrey et al., 2005). One approach to clinical work that incorporates individualized goal setting and measurement can be found in the Collaborative Recovery Model (CRM; Oades et al., 2005). The CRM enables clients to identify their personal, values-based goals, and to monitor and measure progress towards these goals (Clarke et al., 2006).
In the past decade or so, researchers have been working to develop outcome measures that reflect the consumer definition of recovery. Some of these utilize existing subjective outcome measures which assess aspects of the recovery process.
Writing from the perspective of psychopharmacologists wishing to work within the recovery model, Noordsy and colleagues (Noordsy et al., 2000, 2002), moved towards a consumer definition of recovery by identifying three intrapersonal criteria for recovery from the literature – hope, taking responsibility and ‘getting on with life’ – consisting of four components: identity through life roles, relationships, work or structured activity and recreation. They offered examples of eight existing assessment tools to cover various components of these three aspects, embracing spirituality, illness management, healthy lifestyle, identity, relationships, work and recreation. Importantly, Noordsy and colleagues (2002) suggested that these quantitative measures would need to be augmented by the subjective experience of recovery, and stressed that objective measures should be coupled with measures of the value and meaningfulness of the item to the consumer.
A number of other measures of specific aspects of recovery have been used, including hope, resilience, self-efficacy, empowerment and wellbeing (Ralph, Kidder and Phillips, 2000). Resnick et al. (Resnick et al., 2005) conducted a study aimed at identifying aspects of existing outcome measures which could be used to measure a ‘recovery orientation’. Using data from the Schizophrenia Patient  Outcomes Research Team (PORT) Client Survey (Lehman et al., 1998), they factor analysed items which assessed subjective aspects of recovery, and identified four aspects of a recovery orientation: Knowledge, Empowerment, Hope and Optimism, and Life Satisfaction. They suggested that, although recovery is described as a process, an empirical conceptualization could be used to assess recovery as an outcome (Resnick et al., 2005). Resnick and colleagues note that a limitation of their operationalization was its dependence on items from an existing outcomes database, rather than being based in theory. The items, although subjective, focus largely on opinion about services received. For example, the first item in the Empowerment– Self Agency factor is: How much do your opinions and ideas count in which services you get? This does not reflect the sense of personal responsibility for one’s life and wellbeing found in the consumer literature.
The first measure of recovery as a psychological construct with published psychometric properties was the Recovery Assessment Scale (RAS; Corrigan et al., 1999b). Items of the RAS were based on qualitative work with consumers, and later factor analysed to reveal five factors: Personal confidence and hope; Willingness to ask for help; Goal and success orientation; Reliance on others and No domination by symptoms (Corrigan et al., 2004). The Mental Health Recovery Measure (MHRM; Young, Ensing and Bullock, 1999), was based on Young and Ensing’s conceptual model of recovery (Young and Ensing, 1999). The original version assessed the six aspects of recovery described in the model: Overcoming Stuckness; Self-Empowerment; Learning and Self-Redefinition; Basic Functioning; Overall Well-Being; and New Potentials. Later, the domains of Spirituality and Advocacy/Enrichment were added.
A collection of recovery and recovery-related measures has been compiled by Campbell-Orde et al. (2005). A distinction is made between measures of ‘individual recovery’ and ‘recovery-promoting environments’. Of the eight measures of individual recovery in the volume that have been tested, only the RAS andMHRMcould be considered measures of psychological recovery. The remainder incorporate ‘external’ factors of recovery, such as satisfaction with service or measure a single aspect such as illness management. Some were designed to evaluate a specific service or programme.

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Outcome Measurement from the Consumer Perspective

Outcome Measurement from the Consumer Perspective

Outcome Measurement from the Consumer Perspective
Before the rise of the recovery movement, there were few self-rated outcome measures. Possibly the earliest and most common were, and still are, measures of psychological distress, such as the Mental Health Inventory (Veit and Ware, 1983) and its derivatives, and the Kessler-10 (Andrews and Slade, 2001). Consumers use a rating scale to report levels of depression and anxiety symptoms. A more consumeroriented approach was realized with the assessment of individual needs. The most used and tested needs measure is the Camberwell Assessment of Need Short Appraisal Schedule (CANSAS; Slade et al., 1999). The CANSAS assesses the client’s met and unmet needs in 22 domains, including accommodation, household skills, relationships, child care, and transport. Each domain can be rated as ‘No Need’, ‘Met Need’ or ‘Unmet Need’ from the perspective of the consumer, clinician and carer.
Potentially closer to a holistic recovery perspective is the assessment of quality of life (QoL). Quality of life has been conceptualized and operationalized in a variety of ways; while some measures are little more than checklists to assess the impact of a specific disease or illness, others assess satisfaction in a number of life domains, either as a questionnaire or in interview format. A number of QoL measures have been developed specifically for people with a mental illness. For example, the Quality of Life Interview (QOLI; Lehman, 1988) assesses satisfaction across eight domains:
living situation, family, social relations, leisure, work, safety, finances and health; the self-rated Quality of Life Inventory (Frisch et al., 1992), assessing satisfaction in 17 life domains including spirituality, creativity, civic action, and community; and the Wisconsin Quality of Life Index (W-QLI; Diamond and Becker, 1999), which assesses nine dimensions including symptoms, activities of daily living, emotional wellbeing, and personal goal attainment. The W-QLI has companion provider and caregiver versions.

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Assessing Outcomes in Routine Clinical Practice

Assessing Outcomes in Routine Clinical Practice
The focus of the definitions of recovery presented so far has been on outcome measurement in research, including longitudinal outcome studies and studies of treatment effectiveness. However, the drive towards evidence-based practice has fuelled demand for the introduction of routine outcome measures for assessing individual outcomes and for the evaluation of services (Slade, Thornicroft and Glover, 1999; Eagar, Trauer and Mellsop, 2005; Slade et al., 2006; Priebe et al., 2007; Valenstein et al., 2009). Outcome measures for routine use have also often failed to embrace a recovery orientation. A number of authors have proposed domains for outcome measurement. In a systematic review of this literature, Slade (2002)
identified seven categories of patient-level outcome domains: wellbeing, cognition/ emotion, behaviour, physical health, interpersonal, society and satisfaction with service (Slade, 2002). The majority of authors took a medical perspective and focused the staff viewpoint on ameliorating disability. The only review that emphasized the client’s subjective experience came from the consumer-oriented literature, and included domains of wellbeing, recovery (defined in terms of cognition, emotion and functioning), self-help and empowerment – representing a recovery-oriented focus (see Slade, 2002, for the full review).
In Australia, which was at the forefront of introducing mandatory routine outcome measures, a number of existing tools were selected for routine use (Stedman et al., 1997). Two clinician-rated adult mental health outcome measures have been introduced into most Australian states, the Health of a Nation Outcome Scales (HoNOS; Wing et al., 1998) and the Life Skills Profile (LSP-16; Rosen, Hadzi-Pavlovic and Parker, 1989). In addition, one client-rated measure is mandatory, and varies between states. In New South Wales the Kessler-10 (K-10; Andrews and Slade, 2001) is used (Department of Health NSW, 2006). The HoNOS consists of 12 items assessing four domains: symptoms, impairment, behaviour and functioning. The LSP-16 consists of five scales: Self-Care, Non-Turbulence, Social Contact, Communication, and Responsibility. The client-rated K-10 assesses depression and anxiety symptoms.
While assessment should, ideally, contribute something to the clinical process, rather than representing a burden on clinicians and consumers, consumers found that these measures – which are typical of those used elsewhere – were not used to initiate change, and moreover do not assess those things important to them (Happell, 2008). Lakeman (2004) cautioned that, rather than informing recoveryoriented practice, such measures ‘have little, if anything, [to] do with or offer to the recovery process. Indeed, they strip the person’s experience of all meaning and reduce it to predetermined categories’ (p. 212). A recent Australian review of outcome measures for ‘chronic’ mental illness has acknowledged the value of subjective assessments such as quality of life, perceived needs and recovery (Trauer, 2010).

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Approaches to Operationalizing Recovery in Research

Approaches to Operationalizing Recovery in Research
Early longitudinal studies of outcome, particularly of schizophrenia, employed definitions of recovery that were broader than the medical definition. As we saw in Chapter 1, most of these studies used both medical outcome measures and assessments of functioning. For example, the Vermont Longitudinal Study (Harding et al., 1987a, 1987b), as well as an interview protocol determining current status on a number of functional and social dimensions, included two measures of functioning, the Global Assessment Scale (Endicott, Spitzer and Fliess, 1976), and the Strauss– Carpenter Level of Functioning Scales, which rate quantity of employment and level of intimate relationships (married/unmarried/dating) on a scale of 0 to 4. Similarly, in a longitudinal follow-up study of schizophrenia, Harrow et al. (2005) added at least half-time work and the absence of poor social functioning to measures of symptoms and hospitalizations. Criteria weremeasured using the Strauss–Carpenter Level of Functioning Scales and the Levenstein–Klein–Pollack Scale (Levenstein, Klein and Pollack, 1966), on which symptoms, hospitalizations, vocational and social functioning, life adjustment and self-support are rated on an eight-point scale. In assessing one-year outcomes of treatment for early psychosis,Whitehorn et al. (2002), in addition to positive and negative symptoms, used two measures of functioning: the Global Assessment of Functioning (GAF; American Psychiatric Association, 1994) and the Social and Occupational Functioning Scale (SOFAS; Goldman, Skodol and Lave, 1992). The SOFAS was derived from the GAF, and uses similar descriptions of social and occupational functioning, but omits references to symptoms. Both of these measures use a scale of 0–100, described in 10 subdivisions, and are based on clinical judgement.
Recognizing the lack of a universal definition of recovery for research, Liberman and colleagues (2002) attempted to introduce consistency by proposing dimensions that reflect the diagnostic criteria for schizophrenia, i.e., symptom remission, vocational functioning, independent living and social relationships. The criteria specified thresholds that were to be attained and maintained for two years. For example, in the case of peer relationships, the criteria specified that the person have a social interaction with a peer outside the family at least once per week. As Liberman and colleagues noted, the thresholds and durations chosen were largely arbitrary, and determined by consensus of professionals. There is a judgemental element to these definitions; assessment of recovery ought not involve moral judgements on a person’s lifestyle. After all, if ‘normality’ is the goal of mental health services, who decides what is ‘normal’ (Ralph and Corrigan, 2005)? We noted earlier that Harding (1994) questioned the definition used in the Vermont study (Harding et al., 1987a1987b), as they found groups of people who, while not meeting all the study criteria for recovery, were nonetheless happy with their way of life. Focus groups made up of researchers, mental health professionals and consumers showed that, although there was broad consensus on the dimensions chosen by Liberman et al.
(2002), the operational definitions gained approval from a greater percentage of researchers than of consumers or practitioners. Consumers preferred to define recovery as an ongoing process, rather than an endpoint or goal.
While acknowledging that there are common elements to recovery, Anthony et al. (2003) pointed out that quantitative approaches do not allow for the diversity of recovery goals among subjects. These authors therefore urge that quantitative approaches be supplemented by the use of subjective, qualitative measures such as narrative analysis and interviews in determining best practices. However, qualitative procedures such as interviews and narratives, and multidimensional batteries such as those described above, are burdensome on consumers, staff and researchers and are often impractical for large-scale studies or routine clinical use – an area in which outcome measurement is becoming more in demand.

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Why the Need for Measures of Recovery?

Why the Need for Measures of Recovery?
Why would one wish to measure outcomes in mental health, and in particular, why would one wish to measure recovery? Trauer (2010, p. 99) pointed out that outcome measurement can be useful for several key stakeholders: good outcome measures can provide useful information that can assist managers to evaluate their services; likewise, clinicians, and importantly, consumers and their carers can benefit from good outcome measurement – outcome measures can be used to monitor consumer progress, while consumers and their carers can engage more fully in that process.
Finally, good outcome measurement can inform policy makers (Trauer, 2010). In Chapter 1 we posited that consumers are increasingly advocating for recoveryoriented mental health services (Acuff, 2000; Crowley, 1997; Curtis, 2001). Internationally, this notion has been incorporated into mental health policy, for example, in the United States (New Freedom Commission on Mental Health, 2003a, 2003b), Australia (Australian Health Ministers, 2003), New Zealand (Minister of Health, 2005), Ireland (Mental Health Commission, 2005), Canada (Mental Health Commission of Canada, 2009), United Kingdom (Cross-Government Strategy: Mental Health Division, 2009) and Israel (Ramon et al., 2009). In our own recovery research, we have fielded enquiries from Eastern and Western Europe, Scandinavia, Central Asia, South-East Asia and the Middle East. Although a number of countries have incorporated a recovery-orientation into policy, there is no definitive description of what this entails. Various policies highlight the need for a consumer orientation, fostering hope, meaning, fulfilment, an active sense of self, personal responsibility and resilience, and for promoting choice, social inclusion and rights (see Slade, 2009). An approach to recovery-focused practice, based on the processes of the stage model of psychological recovery, was provided by Slade (2009). The framework identifies and elucidates four tasks of mental health practitioners: to support hope by fostering relationships and social inclusion; to offer intervention options which foster self-management and personal responsibility; using the assessment process to support the person in finding meaning in their experience; and supporting identity and encouraging personal growth by promoting personal goal-planning and engendering hope (Slade, 2009).
In parallel with the movement towards recovery-oriented services, there is increasing pressure to use only evidence-based practices – those that have demonstrated positive effects on outcomes (Australian Health Ministers, 1992; New Freedom Commission on Mental Health, 2003a, 2003b; Mental Health Commission, 2005; Minister of Health, 2005; Cross-Government Strategy: Mental Health Division, 2009; Mental Health Commission of Canada, 2009). Some hold that the notion of evidence-based practice, as an outgrowth of evidence-based medicine, is incompatible with the recovery vision (Tanenbaum, 2005; Bonney and Stickley, 2008; Fisher and Happell, 2009). Often, treatment effectiveness studies have been conducted in relation to medications, and effectiveness has therefore been determined by measures of symptoms, hospitalizations and functioning. These types of outcomes may not fully represent the individual consumer’s definition of recovery, and do not reflect recovery-oriented approaches to treatment. For example, a self-admission to hospital may be the result of a person’s taking responsibility for his or her treatment, rather than a failure of treatment (Anthony, 2000). Tanenbaum (2005) questioned whether the elimination of symptoms without relieving suffering could be considered effective treatment, and found that consumers are likely to regard treatments – even those found to be effective in research – as merely tools to facilitate person-led recovery (Tanenbaum, 2008).
However, Torrey et al. (2005) and Silverstein and Bellack (2008) have countered that there are many evidence-based practices in use that are in keeping with the principles of recovery-oriented services, and that the two notions are complementary.
The key, according to those authors, is to use recovery-oriented principles in service provision; for example, giving information about treatments to promote informed choice. While this is certainly in keeping with the aims of the recovery movement, much evidence-based practice research has not been conducted within a recovery framework, and has not demonstrated substantial effects on consumeroriented outcomes (Anthony, Rogers and Farkas, 2003). The issue is with how ‘effectiveness’ is defined and what outcomes are measured (Tanenbaum, 2005).
There are two overarching arenas of outcome measurement: research, including investigations of the outcomes of schizophrenia and treatment effectiveness; and clinical assessment, which, in assessing individual outcomes, also informs the evaluation of services. Below we provide a brief overview of approaches to outcome measurement in these domains and how they are changing with the focus on recovery-oriented services.

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Does linking this work with positive psychology overlook the suffering that goes on for people living with illness?

Does linking this work with positive psychology overlook the suffering that goes on for people living with illness?
This question is similar to many that are put to practitioners and researchers who identify with positive psychology. The stage model of psychological recovery, however, in no way denies suffering, and in fact the first four stages still refer back to illness, and only the final stage truly transcends it. Rather than focusing on the term positive psychology a more useful question may be: Which of the following are relevant to experiences of mental health consumers?
. Wellbeing
. Courage
. Strength
. Wisdom
. Hope
. Goals
. Values
. Resilience.
Any text on positive psychology will include a science of these ideas. In some ways this is a sensible evolution of the recovery movement, using the power of science to validate one’s experience. Recovery is a debate about what constitutes progress and an outcome. Using the science of positive psychology does not deny the negative experience, rather it brings tools to develop optimal functioning in the bad times and the good. The common credo of recovery and positive psychology is to develop a life worth living.

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What about social inclusion, employment, stable housing, poverty, stigma? isn’t the model too intrapersonal?

What about social inclusion, employment, stable housing, poverty, stigma? isn’t the model too intrapersonal?
Stated simply, this is a model of psychological recovery for people living with and beyond mental illness. The focus of the model is intrapersonal, particularly on issues of the self and its development. Social inclusion, employment, housing and poverty are of course important to issues of mental health recovery – however, the focus of this approach is internal resources. The coherence of the model, and the fact that it is proving fertile in terms of measurement is due to the fact that it has been circumscribed about what is being measured. The claim is not that this is a comprehensive model of all things that facilitate recovery, rather, it includes ways of understanding the psychological process of that journey.

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If recovery is a process, does it end at the fifth stage? Does that mean you are recovered?

If recovery is a process, does it end at the fifth stage?
Does that mean you are recovered?
The lived experience of recovery is often emphasized as a process, and views of outcome or endpoint are often less favoured by mental health consumers.
Researchers and managers, however, are often more interested in outcomes. Given that the stage model of psychological recovery has five stages, it could be said that reaching the Growth stage is the endpoint or the outcome. There are two issues to consider here. First, the Growth stage is a dynamic stage, that is, it involves ongoing striving for goals and purpose in line with core values – in the same way psychological well-being is indicated by purpose, growth and autonomy. It is not an endpoint, but an ongoing direction. Qualitatively, however, it is different than
previous stages.

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The recovery process is very complex, so is this an oversimplification?

The recovery process is very complex, so is this an oversimplification?
The recovery process is indeed a complex and dynamic process – which is one of the reasons it is difficult to define, understand, research and experience! The stage model of psychological recovery, is just that – a model. That is, something taken from a better known domain (i.e. a composite of multiple people’s experience) and applied to a lesser known domain (i.e. the experience of an individual). The map, however, is not the territory. The model is parsimonious as feasibility of use has been considered. A four process by five stage model provides 20 possibilities on which to map experience. Any more complex and individuals, teams and systems would find it unwieldy.

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Are there really five stages? What about the evidence that there might be only three?

Are there really five stages? What about the evidence that there might be only three?
The original research from the qualitative literature suggested that there were five stages. Thus far, however, some quantitative research indicates that empirically there may be three factors/clusters of experience rather than five. At the time of writing it is premature to abandon five stages when measurement continues to be developed.
That is, is the model flawed or is the measurement? Interestingly, similar to the TTM, whether there are five stages is a different question to whether it is useful to work with people in terms of five stages. There is a significant amount of evidence that the five stage TTM has been useful in assisting people change their behaviour, yet there is varied evidence as to whether there are five stages. There is much more work to be done until there is a conclusive answer to this question.

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Isn’t this just another example of researchers and professionals colonizing consumers’ experiences?

Isn’t this just another example of researchers and professionals colonizing consumers’ experiences?
Many people who have lived with illness have had multiple injustices and indignities. The aim of the stage model of psychological recovery, however, is to provide a framework for people to have discussions about their personal processes. It provides a comparison point for dialogue. It also provides the opportunity for some structuring of recovery-oriented service provision and for measurement of recovery processes. If consumers were being actively exploited to use this approach or partake in research unwillingly it could be construed as colonization. Rather than colonization, a better analogy may be mutual map making. If over time the model does not fit with people’s experience it will be modified in line with scientific method.
The model is silent on whether the researcher has a mental illness or not.

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If recovery is an individualized process, how can it be put into a model?

If recovery is an individualized process, how can it be put into a model? Doesn’t trying to measure it or model it lose the richness of one’s personal experience?
The stage model of psychological recovery is a conceptual model with the purpose of assisting understanding and sharing of experience; and also generating fruitful research questions. It is a model, therefore it is an abstraction from a collection of experiences, and is not an experience, nor does it claim to be. Whilst the experience of recovery is an individual process, some common factors do exist in terms of the psychological process. For example, most people appear to find hope important and most people address issues regarding identity in relation to illness at some point. By creating a map of a city one does not claim to know the exact experience of the traveller. The map, however, may still be useful for the traveller. The richness of personal experience is definitely lost when one abstracts from the individual situated experience to the general – from the qualitative to the quantitative. This is a reality and not unique to the stage model of psychological recovery. The purpose, however, is not to capture the rich unique experience, but rather provide a broad framework as a reference point for multiple viewpoints and stories – not one single story.

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Isn’t this just another set of standards for consumers to be measured against?

Isn’t this just another set of standards for consumers to be measured against?
Like any tool used incorrectly, it could do harm. However, one practical purpose of the stage model of psychological recovery is to show consumers that there is a pathway towards recovery, based on previous people’s experience. The approach has been developed from stories of people living with illness and refined in consultation with a range of consumers. Many consumers have provided input into this work.
The measures developed to date, as outlined in Chapter 9, are rated by consumers rather than professionals.

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