Journal of Consulting and Clinical Psychology
© 1997 by the American Psychological Association Volume 65(6), December 1997, p 970–983
Consider the Simple Screw: Cognitive Science, Quality Improvement, and Psychotherapy
[Special Section: Measuring Cognitive Products in Research and Practice]

Schwartz, Robert M.1,2

1Department of Psychiatry, University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic.
2Correspondence concerning this article should be addressed to Robert M. Schwartz, Department of Psychiatry, University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic, 3811 O'Hara Street, Pittsburgh, Pennsylvania 15213. Electronic mail may be sent via Internet to or via World Wide Web at .
I would like to acknowledge with appreciation the many clients who contributed to the continuous refinement of the personal quality improvement approach. Special thanks to the client who pointed out the connection between tracking states of mind and quality control, and to the client whose data are described in this article. I wish to express gratitude to Larry Glanz and Paul Pilkonis; to Amy Fasiczka, Philip Friedman, Charles Reynolds, and Michael Thase for collecting and analyzing validity data; and to Reuven Hoch for preparing the figures.
Received Date: January 3, 1997; Revised Date: March 17, 1997; Accepted Date: May 28, 1997




Psychological therapy based on cognitive science advances as psychological states can be precisely measured. This article describes a treatment approach, personal quality improvement (PQI), that draws on (a) the states of mind (SOM) model, a mathematical model built on cognitive assessment research on the balance of positive and negative thoughts and feelings; (b) total quality control, a method for improving quality as defined by increased system stability by empowering average workers to reduce variability through process monitoring; and (c) the phase model of psychotherapy, a framework that proposes 3 distinct stages of treatment. In a single-case study, a depressed client used PQI to track emotional, self-image, and optimism balance, achieving an improvement trajectory consistent with the SOM and phase models. PQI emphasizes process, uses a patient focused treatment paradigm that provides tools for autonomous functioning, and allows for calibration of psychological measures.

Producing a quality screw is no simple matter. Consider a few of the things that can go wrong: malformed head, bad drive slot, wrong shank diameter. To ensure a functional product, manufacturers have adopted the quality control methods developed in Japan by American statistician W. Edward Deming (DeVor, Chang, & Sutherland, 1992). The essence of quality is the reduction of variability in a system such that outcomes fall within control limits around the desired goal (Deming, 1982). Because every system exhibits oscillation, the objective is not “zero defects” but acceptable variability (cf. Crosby, 1979). Quality control methods involve defining the process measures, setting improvement goals, gathering baseline data to identify performance gaps, implementing improvements, and evaluating the success of improvement strategies. Control charts track the production process to ensure that outcomes fall within defined limits and to identify causes of deviation. If a screw's shank diameter exceeds acceptable variability, systematic experiments are initiated to discover the changes needed to improve the process (Chang, 1994; Taguchi, 1987).

Given the value of a person relative to a screw, why are sophisticated monitoring technologies widely used for improving screws but not people? A cognitive assessment technology exists for measuring therapeutic progress (Kendall & Hollon, 1981b; Merluzzi, Glass, & Genest, 1981; Peterson, 1993), and Hayes, Nelson, and Jarrett (1987) have encouraged researchers to evaluate the “treatment utility of assessment.” But except for occasional attempts to apply assessment methods with individual clients (e.g., Kazdin, 1993), clinical use of assessment by practitioners remains limited (Cohen, Sargent, & Sechrest, 1986; Haynes, Lemsky, & Sexton-Radek, 1987; McReynolds, 1985). A renewed impetus toward measuring clinical outcomes arises from the need to contain medical costs. Mash and Hunsley (1993) noted that managed mental health care and behavior therapy endorse similar goals such as individual responsibility, focus on wellness, and time-limited interventions. Both favor accountability through clearly defined treatment goals, therapy methods, outcome measures, and the use of assessment to improve clinical practice. Thus, the goals and methods of quality control are consistent with those of both cognitive–behavioral therapy and managed care.

The recent convergence of the following scientific, technological, and socio-economic developments creates a favorable opportunity for integrating cognitive assessment into clinical practice: scientific progress in cognitive assessment, technological advances that allow computerized management of unprecedented amounts of information, economic pressures for a more accountable health care system, and practical application of quality improvement methods in industry, education, and personal life (Chang, 1994). This article presents an approach called personal quality improvement (PQI) that integrates cognitive assessment concepts from the states of mind (SOM) model (R. M. Schwartz, 1993, 1995; R. M. Schwartz & Garamoni, 1986, 1989) with quality control methods (Deming, 1982) and the phase model of psychotherapy (Howard, Lueger, Maling, & Martinovich, 1993). A clinical case study illustrates how PQI incorporates user friendly cognitive assessment procedures to enhance the psychotherapy process, inform treatment decisions, and increase client autonomy.

Quality Control and Human Systems^

Retroduction is an inquiry method whereby concepts from a well-developed domain are transposed to a less understood area (Buchleer, 1955)—for example, retroduction of cybernetic concepts to psychological functioning (Carver & Scheier, 1981). Consider the parallel between the concept of reduced variability in quality control and the need for stability in human physiochemical systems. Cannon (1932) observed that for life to exist, the inherent instability in biological organisms must be overcome through complex regulatory processes. The importance of physiological stability was supported by a recent study reporting that participants in an induced state of deep psychological well-being achieved “internal coherence,” an exceptionally stable pattern of cardiovascular activity, compared to stressed or normally relaxed participants (Tiller, McCraty, & Atkinson, 1996).

A control chart, which specifies a target goal and upper and lower control limits, defines the optimal level and acceptable range of variability in a system. Occasional deviations may be ignored, but sustained, excessive variability indicates a system out of control and in need of improvement. Special causes of variability are sporadic sources such as tool wear that can be corrected by the line worker; common causes are chronic sources within the system that can be corrected through product redesign or training. Control charts help differentiate periods of instability, control, and improvement. Instability is defined as sustained, out of control variability beyond the control limits. Control is the reduction of special causes of variability so the process does what it was originally supposed to do, namely operate stably. Improvement occurs through systemic changes that reduce common causes of variation and yield enhanced levels of functioning.

The retroduction of quality control can be extended to cognitive–affective systems. A scientific, rather than metaphoric, retroduction requires a level of measurement that allows quantitative specification of optimal levels. Previously, I (R. M. Schwartz, 1993) suggested that the quantitative set-points of the SOM model specifying normal and pathological cognitive balances added a component missing from most cybernetic models (cf. Menninger, 1963). Further, I proposed that the goal of maintaining stability may be as fundamental as pursuing pleasure, which may explain the preponderance of unipolar compared to bipolar depression. Thus, the SOM model postulates that level of cognitive–affective balance and stability of these balances are both important to mental health (cf. Kernis & Waschull, 1995).

Considerable research supports the notion of normal versus dysfunctional balance levels (R. M. Schwartz & Garamoni, 1989). Although stability has not been directly tested within the SOM model, indirect support exists in many studies showing that normal and posttreatment participants maintain relatively stable balances across multiple assessments (e.g., Michelson, Schwartz, & Marchione, 1991). In an elegant research program, Kernis and associates used multiple measures to show that stability in self-esteem relates to a variety of mental health indices independent of level of self-esteem (Kernis & Waschull, 1995). In a study of therapist effectiveness, Blatt, Sanislow, Zuroff, and Pilkonis (1996) found that more effective therapists produced greater stability in the therapeutic outcomes of their patients. Quality in both biological and cognitive–affective systems may thus be defined by optimal level and stability. Prior to cognitive–behavioral research, clinical measurement lacked the precision of biomedical sciences. The past 25 years of clinical cognitive science has yielded precise assessment strategies (documented in this special issue) that now permit a scientific retroduction of quality control methods to human functioning.

Cognitive–Affective Assessment and the SOM Model^

Cognitive assessment reveals positive and negative dimensions as orthogonal factors that account for up to 75% of the variance in studies including these variables (Osgood, Suci, & Tannenbaum, 1957; Watson & Tellegen, 1985). Researchers have adopted a bidimensional assessment approach that reports both positive and negative cognitions–affects (Ingram & Wisnicki, 1988) or computes a positive minus negative difference score (Scheier & Carver, 1985). Recent balance approaches contend that the mind regulates the frequency of positive and negative cognitions and affects; thus, a single ratio reflecting the balance of positive (P) and negative (N) elements, P/(P + N), adds important information beyond reporting each dimension separately (Benjafield & Adams-Webber, 1976; Lefebvre, 1990).

An earlier version of the SOM model incorporating this ratio drew on information processing theory (Adams-Webber, 1982) to propose that a balance of 62% positive cognitions–affects was optimal for coping with stress and general psychological adaptation (R. M. Schwartz, 1986; R. M. Schwartz & Garamoni, 1986). Although supported in many respects by empirical research (e.g., Kendall, Howard, & Hays, 1989; for review see R. M. Schwartz & Garamoni, 1989), the model could not account for anomalous findings that optimal functioning (in contrast to coping with stress) was characterized by higher SOMs ranging from positive balances of 70% to 85% (Davison, Haaga, Rosenbaum, Dolezal, & Weinstein, 1991; Fichten, Amsel, Robillard, & Tagalakis, 1991; Haaga, Davison, McDermut, Hillis, & Twomey, 1993).

Examination of studies including normal participants revealed that a 62% balance was associated with successful coping in negative, stressful situations or adequate (but not optimal) psychotherapy outcomes. For example, stressful situations such as asserting oneself against unreasonable requests yielded SOMs for normal participants of about 62% (e.g., Bruch, 1981; SOM = .63; Heimberg, Chiauzzi, Becker, & Madrazo-Peterson, 1983; SOM = .64; Pitcher & Meikle, 1980; SOM = .60; R. M. Schwartz & Gottman, 1976; SOM = .63). In contrast, higher SOMs were evident in studies involving more positive situations such as high functioning, posttreatment agoraphobics taking a walk (Michelson et al., 1991), or normal participants helping others in positive interactions (Fichten et al., 1991; see also Treadwell & Kendall, 1996).

Reformulated Balanced States of Mind (BSOM) Model^

To handle these findings, the SOM model was reformulated (R. M. Schwartz, 1995) to quantitatively differentiate between SOMs associated with coping with stress and more general psychological well-being.1 Because the original information–theoretic approach did not specify balance values above 62%, the reformulation drew on a theory of consciousness developed by mathematician–psychologist Vladimir Lefebvre (1985, 1990, 1992). Lefebvre has maintained that humans have an “inner computer” that models self and other at increasing levels of reflexive awareness. This computer regulates the ratio of positive and negative thoughts and feelings according to how individuals evaluate themselves and others within various social contexts. Lefebvre's mathematical modeling of interpersonal situations (elaborated below) generates additional balance points that redefine the value of 62% as a subnormal (coping) SOM and designates new balances for normal (72%) and optimal (81%) functioning.

Reflexion is the capacity of humans to see themselves (and others) and to observe themselves seeing themselves (and others). Lefebvre (1990) depicted the structure of consciousness as a reflexive hierarchy in which individuals have an image of themselves and an image of the other, with these images also having images. The first level of reflexion is the sensory experience without conscious awareness of the experience. In order to have awareness, a second level of reflexion is needed so the individual has an image of the experience. A third level of reflexion provides an image of the image or “cognizant image” such that the individual knows that he or she has the particular experience. Linguistically, this might be expressed by a person seated before a mirror (sensory level) saying “I see myself in the mirror” (natural image) and “I know that I am seeing myself” (cognizant image). Both the sensory impressions and the natural image are determined by physical reality; only the cognizant image can be freely changed through consciousness. These reflexive levels are sufficient to model most interpersonal situations.

The positive–negative regulatory process can be functionally described by a Boolean algebra used for bipolar situations such as 1 and 0, happy and sad, good and bad. An individual's SOM can be structurally represented by a formula that models his or her reflexive process in social situations. By assigning 1s for positive (e.g., happy, calm) and 0s for negative (e.g., sad, tense) states of the individual at higher levels of self-reflexion, a ratio can be computed using rules of Boolean algebra, which, depending on situational demands and internal responses of the person, represents the outcome probability of the individual making a positive response to the environment. Thus, stressful, neutral, or pleasant encounters can be modeled; 1s and 0s can be assigned on the basis of assumptions about the positive and negative inner states of the individual; and, through Boolean computations, a single score from 0–100% representing the predicted positivity of responses to environmental demands can be calculated. Theoretically derived predictions can then be compared to actual scores derived from cognitive–affective assessment instruments.2

Lefebvre, Lefebvre, and Adams-Webber (1986) used this theory to model and empirically replicate existing experimental results (Adams-Webber & Rodney, 1983). Thirty-eight Canadian undergraduates evaluated themselves and others three times on 12 bipolar constructs (e.g., generous–stingy) with role-playing instructions that induced deep-positive, positive, neutral, negative, and deep-negative mood states. For example, induced negative mood involved participants imagining themselves sad and deep-negative mood as imagining themselves depressed. To model this experiment, each individual was represented as a three-tiered character indicating the three levels of reflexion noted above. Each character contains an image of the self and the other, and cognizant images of himself or herself from both his or her own and the other's point of view. Because the experimental instructions are assumed to influence a character's cognizant (as opposed to natural) image, the cognizant image was assigned a 1 when the person's self-evaluation was positive, zero when the self-evaluation was negative, and ½ when the self-evaluation was neutral. Modeling the negative (sad) mood, the person was assumed to evaluate him or herself negatively (0) from his or her point of view, but neutrally from the point of view of the other (½). When in a deep-negative mood (depressed), the person's self-evaluation would be negative from both his or her (0) and the other's (0) point of view.

Applying Boolean calculations to the characters,3 Lefebvre et al. (1986) derived ratios representing the likelihood that individuals will evaluate themselves positively under five mood states: positive evaluations of self in deep-positive mood = .875, positive evaluations of self in positive mood = .813, positive evaluations of self in neutral mood = .719, positive evaluations of self in negative mood = .625, and positive evaluations of self in deep-negative mood = .500. The BSOM model defined five primary set-points corresponding to the psychological states enumerated above. As with the original SOM model (R. M. Schwartz & Garamoni, 1986), a preference of the mind for certain balances (good forms) presumes a preference for their inverse (Garner, 1974; Weyl, 1952). This provides the following negative, derivative set-points: 1 - .875 = .125; 1 - .813 = .187; 1 - .719 = .281; 1 - .625 = .375. Accordingly, nine quantitatively distinct set-points were generated, including four normal set-points above the .500 midpoint, four psychopathological set-points below .500, and one intermediate set-point at .500 (see Table 1).

Table 1 The Balanced States of Mind Model Showing Quantitative Range and Set-Points (in %) and Associated Qualitative Features

The BSOM model organizes the nine mathematically derived set-points into seven qualitatively distinct SOM categories that differentiate pathological, subnormal, normal, and optimal balances of positive and negative cognitions–affects. These SOMs include three positive SOM categories 4 greater than .50: positive monologue, positive dialogue, and successful coping dialogue; one conflicted SOM at the .50 midpoint: conflicted dialogue; and three negative SOM categories less than .50: failed coping dialogue, negative dialogue, and negative monologue (see Table 1). The middle three SOM categories (successful coping dialogue, conflicted dialogue, and failed coping dialogue) contain a single set-point at the midpoint of its SOM range. Three set-points (normal, optimal, and superoptimal) were grouped together within the newly defined positive dialogue SOM category. Although these are distinct, mathematically generated set-points with some qualitative differences, they were not sufficiently divergent to establish separate SOM categories. This procedure applies also to the three negative set-points (high negative, moderate negative, and low negative), which were grouped together in the newly defined negative dialogue SOM category. The positive and negative monologues lack set-points and are considered inherently unstable (see Table 1).

These new SOM categories contain important qualitative differences from the original model that alter the conception of normal and optimal balance. The previously defined positive dialogue set-point of 62% is redefined as a successful coping dialogue associated with adaptive (but not optimal) coping under environmental conditions of stress or failure. This SOM is termed subnormal because it avoids the mildly pathological status of the conflicted dialogue, but is still a lower ratio than the newly defined normal and optimal balances. The normal dialogue is associated with healthy persons in neutral, rather than specifically positive (e.g., success) or negative (e.g., failure) situations. The optimal dialogue characterizes healthy persons in a positive mood and represents the standard for cheerful, optimistic SOMs associated with optimal well-being. The superoptimal dialogue is associated with healthy persons in a deep-positive mood who are experiencing a more pervasive feeling of well-being associated with less frequent peak experiences (see Table 1). The new positive monologue, more circumscribed in range, remains hypothetically related to excessive positivity associated with denial, grandiosity, and mania. The conflicted dialogue, increased in range, remains an SOM of doubt and ambivalence associated with mild levels of anxiety and depression. The more differentiated negative SOMs remain consistent in distinguishing degrees of psychopathology including mild (conflicted dialogue), moderate (failed coping dialogue), severe (negative dialogue), and profound (negative monologue) (see Table 1).

The original SOM model has considerable empirical support (R. M. Schwartz & Garamoni, 1989); the reformulated model subsumes the original set-points and offers new values to account for anomalous findings that could not be explained by the original model. Nevertheless, the reformulated norms have not yet been extensively validated. In one exception, R. M. Schwartz, Reynolds, Thase, Frank, and Fasiczka (1996) found that depressed men undergoing cognitive therapy progressed to a normal emotional balance at posttreatment (.71), whereas those undergoing pharmacotherapy achieved an optimal balance (.82). Posttreatment patients, regardless of treatment, were independently classified as achieving an average or superior level of functioning using Global Assessment Scale and Hamilton Rating Scale for Depression scores. Patients classified as average functioning achieved a balance near the normal dialogue set-point of .72, and those with superior functioning were close to the optimal dialogue set-point of .81.

PQI and Psychotherapy^

The parallels between quality improvement, psychotherapy (especially cognitive therapy), and the SOM model are apparent.5 The client is likened to an operator working on-line to reduce excess variability in a cognitive–affective system; the therapist assumes the role of supervisor assisting the client off-line to improve the process at the systemic level. Psychotherapy becomes a discipline of “continual process improvement” (Chang, 1994) that provides clients with tools they can use independently to pursue enhanced personal quality. Personal quality is defined as a state of mind and life functioning characterized by processes that yield well-being (i.e., optimal levels) with increasing efficiency (i.e., minimal variability). Quality is conceptualized within a balance framework, with health defined as quantitatively defined states of optimal balance in physio-cognitive–affective systems, illness as sustained states of imbalance, and therapy a process of restoring stable, optimal balance (R. M. Schwartz, 1993). Personal quality in human systems can be depicted visually by a control chart showing oscillations (as opposed to erratic fluctuations) around normal and optimal set-points.

PQI's emphasis on stability as a criterion of quality requires clarification. Although minimal variability is the goal in manufacturing, within physical systems different degrees of variability exist in context-sensitive systems (e.g., blood pressure) compared to context-independent systems (e.g., body temperature). Regarding cognitive–affective systems, Kernis, Cornell, Sun, Berry, and Harlow (1993) found that instability in self-esteem is related to greater neuroticism, anger in response to threat, and decreased preference for challenge. In contrast, persons with stable high self-esteem are less reactive to external events and exhibit genuine self-acceptance (Kernis & Waschull, 1995).

Although cognitive–affective stability over the course of life is a reasonable goal, periodic instability may also be adaptive. Recall that the PQI approach does not equate health with zero variability (an impossible goal), but with minimal variability within acceptable ranges. The original SOM model noted that a transitory conflicted dialogue, “with periodic alternations between positive and negative thought,” may stimulate personal growth during problem solving or creative dilemmas (R. M. Schwartz & Garamoni, 1986, pp. 25–26). More generally, the relationship between stability and quality of life may vary as a function of the construct being assessed, the phase of the process, and the type of personality style.6 For example, the idea that self-image is a more stable construct than emotion is clinically plausible and supported by initial data (R. M. Schwartz et al., 1996). Regarding phase differences, increased variability in self-image during adolescence or larger fluctuations in mood during early stages of mourning may be adaptive. Finally, personality types such as thrill seekers craving intense positive affect may be uncomfortable with too much stability.7 Despite these qualifications, PQI maintains a particular model of mental health that hypothesizes adaptive advantages to cognitive–affective stability while allowing for periods of variability under special circumstances. Additional assessment research must define how much variability is acceptable for optimal functioning, taking into account type of construct, stage of coping, and personality style.

The therapist must present PQI methods to clients in a way that conveys enthusiasm and harmonizes with the client's belief system (Frank, 1961). The SOM model defines health as a vital, dynamic balance and therapy as self-improvement using rebalancing strategies. Once the client adopts the language of balance, the idea of measuring quality can be gently introduced with Socratic questioning: “How will we know when you are in balance?”; “What vital signs does the nurse measure when you go for a checkup?”; “Wouldn't it be helpful if we could take your ‘mental temperature’ to see if your mind is optimally balanced?”. To increase compliance, the therapist must motivate the client to make quality improvement and self-monitoring top priorities. For resistant clients, measurement should begin with less frequent assessments of one domain of experience (e.g., emotion). If necessary, the client can initially complete the inventory before or during the session (Kazdin, 1993). Consistent with the balance model, the therapist exercises clinical judgment to discover the optimal blend for a given client of technical versus metaphoric aspects of rebalancing.

Improving personal quality involves restoring balance by increasing positive states, decreasing negative states, or both. Beyond the quantitative positive–negative balance of the SOM model, other “vital balances” that currently lack quantitative norms also define mental health. Thinking and feeling cannot be construed as positive and negative. However, a healthy balance between these modes of processing information is critical and can in principle be quantified. Many people are imbalanced towards either too much thinking with deficient feeling (e.g., obsessionals) or the obverse (e.g., hysterics; cf. Jung, 1968). Other “vital balances” important in mental health are self–other, active–passive, introverted–extroverted, independent–dependent, secular–spiritual, and work–play (cf. Millon, 1981). Therapy enhances personal quality by bringing individuals into better balance along multiple life dimensions. The PQI approach, grounded in cognitive science, provides a technology to operationalize balance and quantitatively evaluate the therapeutic impact of rebalancing strategies.

Clinical Illustration of PQI^

Despite the complexity of people, psychological research suggests three cognitive–affective domains consistently related to well-being and thus worthy of systematic improvement: emotion (Derogatis, 1975; Goleman, 1995; Gottman, 1997), self-image (Gough & Heilbrun, 1983; Rosenberg, 1979), and optimism (Scheier & Carver, 1985; Seligman, 1991). Although research has only begun to address the issue of balance within self-image and optimism (R. M. Schwartz et al., 1996), existing evidence indicates that emotional and other cognitive (e.g., coping self-statements) balances relate to normal functioning (R. M. Schwartz & Garamoni, 1989). Thus, it is a reasonable hypothesis that an individual with optimal emotional balance, self-image balance, and optimism balance will function well.

Because no existing instruments have assessed emotional, self-image, and optimism balance as defined by the SOM model, balance measures were constructed. Clients also completed the Beck Depression Inventory (BDI; Beck, Ward, Mendelson, Mock, & Erbaugh, 1961), the Beck Anxiety Inventory (BAI; Beck, Epstein, Brown, & Steer, 1988), and the Marlowe–Crowne Social Desirability Scale (MCSD; Crowne & Marlowe, 1960), the latter to assess a construct that might bias self-report measures yielding an “illusion of mental health” (Shedler, Mayman, & Manis, 1993). The inventory method of cognitive assessment was adopted for empirical and practical reasons. Researchers have more widely used and validated self-statement and mood inventories compared to thought listing or talking aloud methods (Glass & Arnkoff, 1997; Kendall & Hollon, 1981a; Merluzzi et al., 1981). Given the labor intensive demands of self-monitoring, the most cost-effective method of collecting data is indicated (Achenbach, 1993).


The BDI, a 21-item self-report inventory for assessing severity of depressive symptoms, is widely used in research and clinical practice. Each item is rated on a 4-point scale (0 to 3) indicating increasing degrees of severity, yielding a range from 0 to 63.


The BAI, a 21-item self-report inventory for assessing severity of anxiety symptoms, is a companion to the BDI with demonstrated psychometric properties. Each item is rated on a 4-point scale (0 to 3), yielding a range from 0 to 63.


The MCSD is a 33-item scale measuring self-deception or repressive coping style (Weinberger, 1990). Individuals with high positive mood and high MCSD scores have poorer health status as compared to low MCSD scorers, consistent with theories linking repression to dysfunctional somatic status (G. Schwartz, 1990). The median score of the MCSD is 11, with higher scores indicating a repressive coping style.

Emotional Balance Inventory (EBI).^

The EBI is a 24-item inventory consisting of 12 positive (e.g., happy) and 12 negative (e.g., angry) mood terms categorized into 3 positive (happy, vital, friendly) and 3 negative (fearful, sad, angry) subscales. A factor analytic study (Derogatis, 1982) of a related measure with four positive and four negative subscales (Affect Balance Scale; Derogatis, 1975) failed to distinguish statistically between joy and contentment subscales. Drawing on this research, I created the EBI so that a single factor (Happy) would contain moods of both happiness and contentment. Participants indicate on a 5-point Likert scale (0 = never, 4 = almost always) how often during the past day or week they experienced each feeling. Earlier scale development (R. M. Schwartz & Gottman, 1976) suggested that although the term never accurately portrays a total absence of an event, the opposite term always is unlikely to be literally accurate, even for obsessional states. Because of this asymmetry, the extreme score of 4 was anchored with the term almost always.

Previous measures including mood terms have scored positive and negative items separately (e.g., Gough & Heilbrun, 1983) or calculated a positive minus negative difference score (Derogatis, 1975). Because the SOM model defines balance as a ratio of positive to total cognitions–affects, the EBI generates a unique emotional balance score by dividing the sum of the positive items by the sum of the positive plus negative items, P/(P + N). The resulting P/(P + N) scores are interpreted using the theoretical values posited by the SOM model.

Data on 33 heterogeneous psychotherapy clients (Friedman, 1997) assessed during treatment indicated that EBI ratio scores correlated highly with Watson, Clark, and Tellegen's (1988) Positive and Negative Affect Scale (PANAS), total affect balance score (r = .80, p < .0001), total positive affect (r = .72, p < .0001), and total negative affect (r = .72, p < .0001); and with Friedman's (1993, 1995) Well-Being Scale composite score (r = .73, p < .0001), Emotional Stability subscale (r = .76, p < .0001), and Happiness subscale (r = .73, p < .0001). The EBI correlated moderately with Snyder et al.'s (1991) Hope Scale (r = .60, p < .02) and with Friedman's (1995) jovial subscale (r = .58, p < .001). The EBI did not correlate with Friedman's self-esteem (r = .28, p > .05) and social subscales (r = .27, p > .05) or Scheier and Carver's (1985) Life Orientation Test (optimism; r = .47, p > .05; N = 15), although the .47 correlation may prove significant with a larger N.

Self-Image Balance Inventory (SBI).^

The SBI is a 50-item inventory consisting of 25 positive (e.g., sincere, attractive face) and 25 negative (e.g., weak, egotistical) self-descriptive terms categorized into 5 positive (adjustment, self-confidence, self-control, nurturance, body image—positive) and 5 negative (self-centered, aggressive, self-critical, self-pitying, body image—negative) subscales. Participants indicate on a 5-point Likert scale how well each trait described them (0 = not at all, 4 = extremely).

Only self-descriptive terms with clear positive or negative valence were included in the SBI. A study of 97 undergraduate students had them rate 300 personality traits from the Adjective Check List as favorable and unfavorable, resulting in lists of the 75 most positive and 75 most negative traits (Gough & Heilbrun, 1983). In a similar study, Anderson (1968) had 100 students rate 555 personality trait words on likableness. Items for the SBI were selected if they appeared on Gough and Heilbrun's favorable–unfavorable lists and were in the upper and lower 1/3 of Anderson's likableness rank ordering (e.g., positive items: alert, independent, understanding, practical; negative items: conceited, self-centered, cowardly, complaining). The SBI generates a self-image balance score by dividing the sum of the positive items by the sum of the positive plus negative items, P/(P + N). The resulting scores are interpreted using the theoretical SOM values.

Data on 33 heterogeneous psychotherapy clients (Friedman, 1997) indicated that SBI ratio scores correlated moderately with Watson et al.'s (1988) PANAS total affect balance score (r = .67, p < .0001), total positive affect (r = .64, p < .0001), and total negative affect (r = -.57, p < .0004), and with Snyder et al.'s (1991) Hope Scale (r = .73, p < .001; N = 15) and Friedman's (1995) Well-Being Scale composite score (r = .62, p < .0001) and all subscales. Separate data on 64 depressed clients (Thase, Schwartz, Reynolds, & Fasiczka, 1997) assessed at pre- and posttreatment indicated that the SBI correlated moderately with Hollon and Kendall's (1980) Automatic Thoughts Questionnaire (r = .46, p < .001), Derogatis's (1975) Affect Balance Scale (r = .36, p < .004), the BDI (r = -.49, p < .0001), and the Hamilton Rating Scale for Depression (Hamilton, 1960; r = -.29, p < .02).

Optimism Balance Inventory (OBI).^

The OBI is a 14-item modified version of Scheier & Carver's (1985) Life Orientation Test (LOT), differing in two respects. The LOT is a 13-item inventory of dispositional optimism focused specifically on optimistic (“In uncertain times, I usually expect the best”) and pessimistic (“If something can go wrong for me it will”) outcome expectancies.8 (Four neutral filler items minimize the obvious nature of the items, leaving five optimism and four pessimism items). Participants indicate on a 5-point Likert scale the extent to which they agree with each statement (0 = strongly disagree, 4 = strongly agree). An additional item was added with Scheier's permission (Scheier, personal communication, June 17, 1990), to equalize the number of positive and negative items (“Looking into the future, things can only get worse, not better”).

An optimism balance score was calculated by dividing the sum of the positive items by the sum of the positive plus negative items, P/(P + N), allowing the scores to be interpreted using the SOM model. Data on 64 depressed clients (Thase et al., 1997) indicated that the OBI correlated moderately with Hollon and Kendall's (1980) Automatic Thoughts Questionnaire (r = .66, p < .0001), Derogatis's (1975) Affect Balance Scale (r = .40, p < .001), the BDI (r = -.50, p < .0001), and the Hamilton Rating Scale for Depression (r = -.25, p = .05).

Method of analysis.^

Kazdin (1993) noted that single-case methods in clinical practice rely on repeated observations of performance over time that allow comparison of baseline levels to changes during treatment. Clinician and client can examine the data using visual inspection, a nonstatistical (but systematic) method to evaluate the reliability of change, including changes in mean level and slope across phases, shifts in performance when treatment begins, and latency of change after treatment modifications (Kazdin, 1992). The case study used visual inspection to evaluate changes in balance throughout phases of treatment by ascertaining their fit with the quantitative norms of the BSOM model.

Jon: Running to Keep Beyond the Shadow of Father's Greatness^

Therapy with Jon will illustrate an approach to quality improvement using cognitive–dynamic therapy that balances cognitive and psychodynamic strategies depending on the client's needs (Wachtel, 1977). Employed as a high level professional in a technical field involving computers, Jon chose to work with me because I have an Internet web page and would “understand his language.” Jon presented as a bright, anxious, compulsive, overideational, 41-year-old man, married with three children, and the son of a renowned scientist. He exhibited a sense of time urgency, tense facial expression, and impatience with others. Because intellectual efficiency was central to his self-esteem, he felt distressed by his ruminating and indecisive cognitive style. His productivity at work was suffering, raising fears of failure and helplessness. Interpersonally, an intense, perfectionist style left little room for sensitivity when expressing criticism.

Quantitative PQI Analysis^

Jon responded favorably to the idea of balance as a criterion of health and welcomed a result-oriented method of quantitatively tracking personal quality. He conscientiously self-monitored his SOM and used quality control charts to find opportunities for personal improvement (see Figure 1). Jon completed the BDI, BAI, and MCSD at pre- and posttreatment and at follow-up. The PQI balance measures (EBI, SBI, OBI) were taken three times per week for the first 3 weeks to detect trends early (e.g., instability) and weekly thereafter as part of systematic “quality reviews.” His pretreatment BDI score of 26 and BAI score of 11 indicated moderate symptoms of depression and mild anxiety. The MCSD scores of 10 at pretreatment and 6 at final follow-up were close to the median score for this test, suggesting a normal degree of self-deception.

Figure 1. Personal quality improvement (PQI) chart of client's emotional balance, self-image balance, and optimism balance trajectories across phases of treatment. Horizontal grid marks on the y axis on the right side indicate the set-point(s) associated with each state of mind category. BDI = Beck Depression Inventory; BAI = Beck Anxiety Inventory.

Self-deception was construed as a general trait and Jon's pre–post data were consistent with this view. In other cases, self-deception may fluctuate throughout treatment as a phase-dependent variable or may be heightened because clients are self-scoring the measures. Future studies might include multiple MCSD measures to directly explore this issue. When clients have extremely high balance (e.g., 90%) and high SCSD scores, the first therapeutic goal is to teach them to accept negative states with the goal of (paradoxically) lowering their mood to a more realistic level.

Visual inspection of the PQI repeated measures were analyzed at three levels: (a) balance analysis—overall balance was charted and evaluated using the norms of the BSOM model. (b) Subscale analysis—subscales were examined to compare the relative scores on positive and negative subscales for the client within a given assessment. Because rebalancing is achieved by increasing positives or decreasing negatives, the therapist and client collaboratively identify improvement goals by noting negative subscales with relatively higher scores (e.g., angry; self-critical) and positive subscales with relatively lower scores (happy, confident). (c) Item analysis—inventory items were examined to identify specific traits for quality (character) improvement (e.g., cowardly, independent). Negative items endorsed with high scores (3 or 4) and positive items with low scores (0 or 1) indicated likely qualities for rebalancing. Note that the balance analyses (i.e., EBI, SBI, & OBI) are based on normative research, whereas the subscale and item analyses are evaluated relative to the client's overall balance and his or her own subscore profile (cf. Kazdin, 1993).

Emotional balance (EB).^

Jon's pretreatment EB score of 34% (see Figure 1, 1/15) placed him near the failed coping dialogue set-point, consistent with his moderate level of depression on the BDI. An in-session analysis of the EB subscales revealed excesses in sadness and fear (relative to anger), and deficiencies in happiness and vitality (relative to friendliness). Item analysis revealed that although Jon was less angry, he reported heightened irritability.

Optimism balance (OB).^

Jon's pretreatment OB score of 37% (see Figure 1, 1/15), also within the failed coping dialogue, was achieved by relative excesses in pessimistic cognitions such as “Things never work out the way I want them to” and “I rarely count on good things happening to me,” and relative deficiencies in optimistic cognitions such as “I always look on the bright side of things” and “I'm always optimistic about my future.”

Self-image balance (SB).^

Jon's pretreatment SB score of 56% (see Figure 1, 1/15) placed him within the conflicted dialogue category, one SOM category above his EB and OB scores. This slightly elevated SB score relative to emotional and non-self-relevant cognitive balance is frequently observed in my clinical work and was seen in recent experimental data (R. M. Schwartz et al., 1996). The comparative stability of self-schemata relative to mood and optimism may yield less of a downward shift in self-image from premorbid levels of adjustment. Alternatively, the higher SB may be understood in terms of self-serving cognitive biases that provide a buffering, if illusory, inflation in one's image of the self (Taylor, 1989).

Subscale analysis revealed moderate excesses in aggression, self-criticism, and self-pity, and mild excesses in self-centeredness and negative body image. Moderate deficiencies occurred in self-confidence, adjustment, self-control, and positive body image. Item analysis indicated that quality improvement processes could most profitably focus on decreasing more extremely elevated negative traits (e.g., argumentative, weak, self-punishing, dependent, egotistical, plain looking) and increasing more extremely deficient positive characteristics (e.g., self-confident, initiating, enthusiastic). Note that some personal traits such as height cannot be directly modified. As a general rule, improvement can be accomplished either by changes in the self or world when possible, or by modifying the subjective meaning of immutable realities.

PQI and Phase Model of Therapy^

Visual inspection of Figure 1 reveals three distinct, progressive stages of the SOM balance scores (excluding follow-up) that are consistent with Howard et al.'s (1993) phase model of psychotherapy. The first phase, remoralization, is characterized by failure to cope, painful symptoms, pessimism, and powerlessness to change, with therapy focused on using the healing relationship to clarify symptoms, promote mastery, and enhance well-being. These positive changes occur quickly in response to setting an appointment, receiving advice, and so on. Remediation, the middle phase, involves resolving symptoms and life problems by mobilizing coping skills through cognitive strategies to reduce negative thoughts, interpersonal strategies to increase assertiveness, empathic strategies to enhance self-esteem, and interpretative strategies to deepen adaptive understanding. The third phase, rehabilitation, focuses on unlearning long-standing, maladaptive patterns involving self and others. Although many patients will terminate once symptoms have abated, others recognize that the repetitive nature of their problem requires more time to consolidate new coping skills acquired during the remediation phase and to integrate enhanced cognitive–affective structures into stable life roles.

Remoralization phase.^

Jon's process of remoralization is reflected in the progression of balance scores during the first week of treatment (see Figure 1, 1/15 through 1/21). He expressed hope (cf. Synder et al., 1991) regarding PQI's goal-oriented approach with measurable outcomes. His initial drop in EB (24%) and OB (29%) into the negative dialogue from 1/15 to 1/18 (together with normal MCSD scores) suggests he was not faking well or engaged in excess self-deception. The lack of a comparable change in SB (56% to 54%) supports the noted stability of the self-schema compared to mood. Jon became more actively involved in systematically analyzing and discovering the sources of his problems, rather than helplessly ruminating about them. During this period, his EB increased rapidly to 69% (less sadness; more happiness and vitality), his OB rose to 60% (less convinced things never work out and more able to look on the bright side), and his SB increased to 69% (less self-critical and self-pitying; more self-confident and nurturing). Note that this rapid improvement in balance increased only to the subnormal, successful coping dialogue, signifying adequate (but not optimal) struggling under stressful conditions. These remoralization phase improvements may be attributed to other factors, including denial or desire to please the therapist. Although inconsistent with the initial drop in mood, this explanation can be definitively ruled out only with repeated applications of the MCSD or noninventory methods of measuring defensiveness (Shedler et al., 1993).

Remediation phase.^

Jon's remediation phase shows relatively steady oscillations of all balance measures around the successful coping dialogue set-point (see Figure 1, 1/22 through 3/11), with the exception of the more variable EB drifting into the conflicted dialogue (2/8). Although Jon reduced variability, he did not achieve the mean quality level for normal (SOM = 71%) or optimal (SOM = 81%) balance. The greater variability and decreased level in EB indicated an individual with mood disorder struggling unsuccessfully at this treatment phase to maintain positive affect. Jon's drop in mood was attributed to growing work pressure, interpersonal conflicts with a coworker, and stress of the change process itself as he explored new modes of thinking and behaving. This phase can be characterized by reestablishing control (i.e., stability) in cognitive–affective systems rather than producing improvements per se, as defined by increased balance scores.

Subscale analysis of EB indicated that compared to earlier assessments, vitality and friendliness increased and sadness decreased. Overall balance remained subnormal because happiness remained relatively low, tension and nervousness remained high, and hostility fluctuated in direct response to confrontations with a colleague. SB subscales showed continued deficiencies in self-confidence and moderate excesses in self-criticism, argumentativeness, fault finding, and sarcasm.

The remediation phase focused on learning anxiety management techniques (e.g., relaxation training), and cognitive strategies to reduce worry and self-punitive attributions for failure. Assertiveness and communication skills enhanced interpersonal functioning at work, primarily with his collaborator. Clinical observation revealed that Jon's cognitive–affective style was imbalanced by excessive ideation and deficient emotional awareness.9 He achieved a better thinking–feeling balance through emotive exercises, including music and vocalization therapy to access deeper, intuitive sources of tacit knowledge, which reduced rumination during decision making.

Jon developed greater self-confidence by working through childhood conflicts about living in the shadow of a demanding, critical father and overcoming injuries from competitive peers who envied his intellectual powers. As Jon separated from his father, he began to shift from the role of a precocious student striving to verbally outsmart others (including me) into a mature professional with a balanced perspective on his assets and limitations. After negative thoughts and feelings reduced, Jon cultivated realistic, positive cognitions about himself and others resulting in an affirmative, enthusiastic mode of self-presentation and increased pleasure in work.


By week 12 of treatment (4/7), Jon experienced a dramatic improvement in personal quality. His EB rose rapidly from a conflicted dialogue to an optimal dialogue and his OB rose from a coping dialogue to a superoptimal dialogue (see Figure 1). Because the SB, as hypothesized, remained relatively stable, Jon decided to make the assessment process more efficient by temporarily eliminating this inventory. His optimal levels of mood and optimism reflected enthusiasm about his newly acquired coping skills, actual breakthroughs on work projects, improved handling of interpersonal conflicts, and an increased sense of mastery and self-confidence. He feared this improvement might be transitory because he attributed it to situational factors related to hopeful signs about funding for a major project (i.e., temporary special causes).

Subscale analysis showed that his optimal EB was a function of high vitality, increased happiness and friendliness, and decreased anger and sadness. Item analysis revealed that tension and nervousness remained moderately high. At 4/25 his EB dropped to a normal balance, with moderate variability around the normal dialogue set-point through posttreatment. This variability was attributed to situational factors that increased his anxiety, sadness, and nervousness.

After an unstable period rising into the positive monologue (4/7, 4/18), Jon's OB re-equilibrated and continued to oscillate around the optimal balance set-point with minimal variability through posttreatment. This optimal balance level and relative stability indicated a high-quality, optimistic SOM. By posttreatment (see Figure 1, 6/13), Jon's SB reached a new height precisely at the normal dialogue set-point (.72). This reflected major improvement in self-confidence and nurturance of others, smaller increases in adjustment and self-control, and reductions in aggression, self-criticism, and self-pity. The final Beck scores (BDI = 6, BAI = 5) were consistent with these normal-to-optimal SOMs. Jon had learned that a “key lesson is that it's my choice how to interpret events.”

Because Jon had previous therapy for recurrent affective disorder, we continued treatment to see if these improvements would remain stable. This phase of treatment focused primarily on consolidating the gains in personal quality made during the remediation phase and on improving dysfunctional interpersonal patterns. He continued to work on what we called the “systematic cultivation of joy” (cf. James, 1902/1961), gradually internalizing a more relaxed, playful, enthusiastic style. Jon reported a more satisfying work–leisure balance with more quality time with his family.

One month into this stable period (5/25), Jon said with a smile (but pointedly) that he was not sure why he was still in treatment—except to fund my upcoming lake vacation. “A vacation at the lake is fine,” I replied, “but it would also be fun to rent maybe a small boat.” Repartee aside, I interpreted his manner of introducing termination as a residual of his admittedly abrasive interpersonal style that apparently we hadn't fully modified. He used sarcasm to defend against separation fears and conflicts expressing gratitude characteristic of obsessive styles (Shapiro, 1965). We agreed to meet for several more sessions to explore this aspect of our relationship because it might improve the quality of his professional interactions, and to resolve other termination issues.

Termination and follow-up.^

The optimal level and relative stability of Jon's PQI measures provided a rational basis for decision making regarding termination. A potential limitation of the treatment was suggested by relatively larger variability in EB that fell during several recent assessments in the subnormal, coping dialogue. Responding to this observation, Jon said that his previous therapist used a dental checkup model of scheduled “booster” sessions. I agreed in principle, but noted that PQI allowed greater autonomy. In dental situations, patients lack technical knowledge and practical tools for self-examination. Because a goal of therapy is to have clients “become their own therapist” and PQI provides simple tools for self-examination, planned sessions may unnecessarily promote dependency and higher treatment cost. I suggested that Jon conduct periodic PQI assessments to identify variability, locate its cause, and initiate self-improvement strategies. We could rely on e-mail communications as needed, reserving face-to-face booster sessions only if PQI assessments indicated necessity.

The 3-month follow-up (see Figure 1, 9/2) showed further gains in OB, SB, and EB, with EB elevated to its highest level (superoptimal balance). The BDI of 4 and BAI of 3 showed normal range scores on these measures of depressive and anxious symptoms. The 4-month follow-up (10/3) showed OB at an optimal balance and SB stabilizing at a normal balance. Because EB dropped to a borderline positive–successful coping dialogue, I e-mailed Jon to pose several questions regarding possible causes of variability (special vs. common) and options for rebalancing (self-directed or booster session). He responded by e-mail stating that the temporary drop in EB was because his project did not get funded. This situationally appropriate variability may be adaptive as a form of minigrieving, especially when high levels of optimism and positive self-image are preserved. Jon's PQI profile thus reflected appropriate sadness about loss without negatively affecting self-esteem.

At 5-month follow-up (see Figure 1, 11/2), EB increased to a superoptimal balance; SB and OB oscillated around a normal and optimal balance, respectively. Although EB continued to show relatively greater variability than the other domains, this variation remained in the positive dialogue and thus within acceptable control limits.


A special issue of the American Psychologist (1996, 51 (10), October) on assessment in psychotherapy identified critical steps to make research relevant to clinicians and policy makers. Before exploring whether PQI satisfies these criteria, limitations must be noted. PQI is an innovative cognitive assessment approach, but several assumptions require further research including the optimal level and stability hypotheses and the role of balance in a model of well-being. Although the original SOM model has empirical support and the reformulated BSOM model accounts for anomalous data, the new set-points need further evaluation. Research must determine whether set-point stability (i.e., oscillation around a theoretical value) relates to optimal functioning, the degree of acceptable variability, and the conditions under which variability may be adaptive.

The current model of mental health, emphasizing balance and stability, is conditional on one's vision of life. Alternative models should be articulated and evaluated empirically. Although it has been hypothesized that a healthy balance in emotion, self-image, and optimism underlie well-being, PQI could be improved by also assessing interpersonal relationships and global well-being. Future PQI studies might include measures of self–other balance and quality of life (cf. Frisch, Cornell, Villanueva, & Retzlaff, 1992).

Goldfried and Wolfe (1996) stressed the need for intensive study of single-case designs to elucidate the link between therapeutic intervention and patient change. Single-case research has been hampered because studies have lacked theory-based, clearly formulated, and disconfirmable hypotheses. PQI generates disconfirmable hypotheses about the process of cognitive and affective improvement in therapy. For example, future research may attempt to disconfirm the quantitative parameters of the BSOM model, investigate pathological or adaptive implications of variability versus stability in cognitive–affective systems, or test treatment phase hypotheses such as whether optimal outcomes result from rapid acquisition of stability versus a period of variability during the remediation phase as clients experiment with new adaptive strategies.

Therapy research has focused primarily on evaluating efficacy (does treatment work experimentally?) and effectiveness (does it work in clinical settings?). Rarely have studies posed the vital question of practicing clinicians: Does it work for my patient? Howard, Moras, Brill, Martinovich, and Lutz (1996) proposed a clinical research paradigm called patient-focused research that monitors an individual's progress during treatment and provides feedback “to the practitioner, supervisor, or case manager” (p. 1059). The clinician needs information about the patient's condition throughout therapy, not only when treatment ends. Quality improvement approaches devise simple measurement systems so average workers can actively monitor and correct the processes for which they are responsible. PQI assessment measures are client focused, face valid, and easy to complete and interpret. The trajectory of change in balance reported in this study is consistent with Howard et al.'s (1993) phase model, but extends it by including the client as a participant in the data analysis, treatment planning, and follow-up. Future studies using PQI methods might include Howard et al.'s measures of life functioning to delineate relationships between these indices and PQI balance measures.

Although the current case study suggests the clinical utility of PQI, one cannot conclusively attribute the improvements to PQI methods as opposed to cognitive–dynamic therapy itself (Hayes et al., 1987). To determine effectiveness, future single-case research might use a reversal design with a single-patient or multiple-baseline design across clients to investigate effects of completing versus not completing PQI measures and exploring the effect of revealing scores to client, therapist, or both. Although SOM studies cited earlier have shown improvements in cognitive–affective balance during treatment, these involved traditional therapies and merely assessed balance as a dependent measure (e.g., Bruch, Heimberg, & Hope 1991; Garamoni, Reynolds, Thase, Frank, & Fasiczka, 1992). Only randomized group studies with and without PQI methods can demonstrate its unique contribution to treatment.

According to Sechrest, McKnight, and McKnight (1996), the greatest challenge to therapy research is that assessment measures are not intuitive and have no meaningful metric. Measures with inherent meaning must be calibrated against life events and each other to allow transformations of values and substitutions of measures. What does it mean to an individual client, for example, that a BDI score decreased from 26 to 17? Not much, say Sechrest et al., except that depression lessened to some extent. We are interested in what a reduction in score means regarding real issues such as work performance or improvements noted by family members. Contrast this vague formulation as a basis for decision making with the quantitatively precise and experientially meaningful rise in body temperature of 3 °F. Health decisions should be based on measures that communicate something specific about functional status (what people can do) and quality of life (well-being). Sechrest et al. recommended that for therapy to further its scientific status, “in some manner as yet unclear to us, the field should settle on single standard measures for constructs of central interest, and researchers should be expected to use these standard measures in all their projects … the use of standard measures would provide a basis on which calibration could proceed if calibration is possible” (1996, pp. 1070–1071). Adopting standard measures, they conclude, need not preclude the creative development of new measures.

The ratio variable of the SOM model and PQI approach offers a standard metric that may satisfy these requirements. The balance ratio was conceived to allow comparison of cognition measures across diverse content domains (e.g., assertiveness and depression) and modes of information processing (e.g., self-statements and memory) that would otherwise have been incomparable (R. M. Schwartz & Garamoni, 1989). Self-statement inventory derived cognition scores in an assertiveness study (e.g., positive thoughts = 70; negative thoughts = 30) would be difficult to compare to thought listing generated scores in a depression study (e.g., positive thoughts = 7; negative thoughts = 3). However, the ratios 70/100 and 7/10 = 70% would be readily comparable, theoretically related to normal functioning, and easier to map against real life events.

Ratio scores also facilitate statistical analyses and the transformation of values (cf. Amsel & Fichten, 1996; Kendall, 1983). Further, the balance variable allows creative generation of new measures because most constructs can be organized in binary opposition (Kelly, 1955) and represented in ratio form. A research program extending beyond positive–negative balance can define a set of psychological constructs, formulate them as ratios and calibrate them against life events. Although theorists may emphasize different dimensions, the field may reach sufficient consensus on variables such as attachment balance (independence–dependence), assertiveness balance (self–other), self-efficacy balance (competence–incompetence), sociability balance (extraversion–introversion), and trust balance (trust–mistrust) (cf. Amsel & Fichten, 1990; Bandura, 1977; Haaga et al., 1993; Millon, 1981).

Although the reformulated set-points require further research, initial calibration of original SOM ratios exists. Each SOM category relates to different levels of functionality and to qualitative features such as conflict, coping, or optimality. For example, Bruch, Hamer, and Kaflowitz-Lindner (1992) tested the construct validity of the SOM model and found that individuals in a conflicted dialogue demonstrated greater indecisiveness and ambivalence in an assertiveness task. As noted earlier, R. M. Schwartz et al. (1996) showed that successfully treated depressed men who achieved an optimal dialogue (81%) exhibited independently defined optimal functioning compared to those who achieved a normal dialogue (72%) and whose functioning was healthy, but not optimal. Clients and practitioners using PQI can develop an inherently meaningful calibration of balance scores. A client with an emotional balance of 72% feels and acts healthy (“72 degrees and sunny”); one with 60% expresses feeling O.K., but stressed (“good, but not great”); and one with 50% feels mildly anxious, depressed, or conflicted. The balanced SOM model not only differentiates dysfunctional and functional status, but also permits finer calibration of clinically significant improvement, including coping, normal, optimal, and superoptimal states (cf. Tingey, Lambert, Burlingame, & Hansen, 1996).


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1The reformulated model is hereafter referred to as the BSOM model to differentiate it from the original SOM model. [Context Link]

2Readers interested in more mathematical details should see Lefebvre (1990) and his related articles in the Journal of Mathematical Psychology. [Context Link]

3Lefebvre, Lefebvre, & Adams-Webber (1986) delineated the character for the participant evaluating himself or herself under neutral mood conditions as

Equation (Uncited)

Variables a1, a2, and b2 automatically take on value1/2, and because the mood condition is neutral, the variables a3 and a4 take on the value 1 with probability1/2. Using gamma algebra as described by Lefebvre (1990), the status of the character A1 is calculated as follows:

Equation (Uncited)

Thus, modeling the experimental conditions of self-evaluation under neutral mood indicates that the participant will assign himself or herself to the positive pole with a frequency of .719 (Lefebvre et al., 1986). The other mood conditions were modeled in a similar fashion. [Context Link]

4SOMs are conceptualized as inner dialogues in which varying proportions of positive and negative thoughts and feelings dialectically interact. When either positive or negative elements predominate to the extent that the dialectical process is essentially lost, these SOMs are considered inner monologues. The concepts of internal dialogue and monologue are used heuristically, not literally. Although much thought takes the form of inner dialogues with oneself, cognition also occurs in other modes such as imagery, affective information, or tacit knowledge. The BSOM model applies generally to cognitive and affective states, regardless of whether they are verbally expressed in dialogic form (cf. R. M. Schwartz & Garamoni, 1986). [Context Link]

5The link between quality control charts and states of mind records was made by one of my clients who uses quality control methods to investigate health care delivery systems. [Context Link]

6I wish to thank an anonymous reviewer for conceptualizing this point. [Context Link]

7Although such individuals may be viewed as simply alternative types, research on subjective well-being suggests problems with this style. Diener, Sandvik, and Pavot (1991) found that happiness is a function of many moderate positive experiences rather than few intense positive experiences. The latter are typically followed by longer lasting, intense negative experiences, thus lowering the overall level of well-being. This effect, which can be explained in terms of opponent-process theory, raises questions about whether extreme instability can promote well-being. [Context Link]

8These data were collected using an earlier version of the LOT. Scheier, Carver, and Bridges's (1994) revision reduced the inventory to 12 items, equalizing the number of positive and negative items to four optimistic and four pessimistic items. The authors reported a correlation between the original and revised LOT to be “in the .90's” leading them to expect minimal differences in findings (Scheier et al., 1994, p. 1073). [Context Link]

9Clinical evaluation of many imbalances is somewhat arbitrarily based in personal and cultural values. A clinician makes judgments about quantity in the absence of empirical data by drawing on experience. How much grief is optimal for the death of a loved one versus the end of marriage? How much cognitive activity is required to qualify as “overideational”? [Context Link]

Accession Number: 00004730-199712000-00007