Emotion-Abstraction Patterns in Verbatim Protocols: A

Journal of Consulting and Clinical Psychology 1996, Vol. 64, No. 6. 1306-1315

Copyright 1996 by the American Psychological Association, Inc 0022-006X/96/$3.00

Emotion-Abstraction Patterns in Verbatim Protocols: A New Way of Describing Psychotherapeutic Processes Erhard Mergenthaler University of Ulm The goal of the study was to develop a computer-aided system that is able to identify key moments in transcripts from psychoanalytic sessions and to provide an adequate theory of change. The term key moment refers to 1 or more sessions of a treatment or to segments of a session that are seen as clinically important and often considered to be a turning point or breakthrough and that mirror points of insight as they occur in the course of the psychotherapeutic process. It will be shown that patterns built of combinations of the content analysis variables "emotion tone" and "abstraction" allow for describing therapeutic cycles including key moments. The method is shown successfully for a single case and for a sample of improved and not improved patients.

The goal of the study presented in this article was to develop a computer-aided system that is able to identify key moments in transcripts from psychoanalytic sessions and to provide an adequate theory of change. The term key moment refers to one or more sessions of a treatment or to segments of a session that are seen as clinically important. "It concerns an experience which, though not frequent, is familiar to all analysts. And it is one welcome to all. I mean 'the good analytic hour' " (Kris, 1956, p. 446). These are moments that may be seen as a turning point or breakthrough, that mirror points of insight as they occur in the course of the psychotherapeutic process, and that are needed in order for some change to occur in the patient's demeanor. Particularly in psychoanalytic therapy, insight is considered to be a central concept. As discussed later, this method also will apply to other psychotherapeutic approaches as long as they are mainly focused on verbal exchange. Development of such a procedure that can be applied across treatments requires a definition explaining what a key moment is and also allowing for a suitable computer-aided approach. Although there are many theories on the development of insight, none of them can be considered to be easy to operationalize and thus to be appropriate for empirical and computer-assisted proof. Therefore, within this study, a viable theory of change with a minimum of variables and no reliance on an elaborate (thus complex) theory is presented. The empirical evidence of

this newly generated model is shown. Given constraints are to use speech only as it appears in transcripts as a source of data.

Selecting Variables The phenomenon of emotion is seen as a central aspect for many or all psychotherapies. Emotion in the course of psychotherapeutic treatment can be experienced physiologically but also mentally, and it can be communicated verbally. This study is restricted to indicators of emotion as they can be observed in transcripts. To comply with this constraint, the concept of emotion is understood as "emotional tone of a text," as it is used also in literary and linguistic research (Anderson & McMaster, 1986). Thus, the observed utterances or words are suitable to express emotion verbally but may not coincide with physiological correlates such as sweating, flushing, or palpitation. Emotional tone, as it is used here, does not reflect the valence of the feeling but measures the density of emotion words within a given text unit. Henceforth, the term emotion tone is used to refer to this concept. It also has to be noted that verbal access to emotional content—which is seen as being located in the symbolic, nonverbal memory—will not always be possible (Bucci, 1993). According to the central importance of emotion in the psychotherapeutic process, it is assumed that the presence of emotion tone is a necessary prerequisite for the emerging of key moments. However, this cannot be seen as being sufficient. One can easily think of moments that may be characterized by high emotionality but lack of insight and, therefore, do not lead to therapeutic change. So far, the concept of high and low emotion tone just will allow to differentiate two states, one of them including key moments. At least another variable is needed, allowing to logically distinguish four states, one of those possibly being a key moment. For the purpose of this study, abstraction, as a construct leading to the development of understanding and perception (Piaget, 1977), was chosen. Schneider (1983) identified the reflecting abstraction as the "central mechanism leading to the construction of new structures" (p. 81).

An earlier version of this article was presented at the Society for Psychotherapy Research meetings in June 1992, in Berkeley, California, and in June 1993, in Pittsburgh, Pennsylvania. This work was partly conducted within the Program on Conscious and Unconscious Mental Processes funded by the John D. and Catherine T. MacArthur Foundation at the University of California, San Francisco. I gratefully acknowledge the thoughtful consultation of Wilrna Bucci and also of Mardi J. Horowitz, Dan Pokorny, and Charles H. Stinson. Also thanks to Lester Luborsky for providing access to the Penn Psychotherapy Study data. Correspondence concerning this article should be addressed to Erhard Mergenthaler, Universitat Ulm—Klinikum, Sektion Informatik in der Psychotherapie, Am Hochstrafi 8, 89081 Ulm, Germany. 1306

EMOTION-ABSTRACTION PATTERNS

Relaxing

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Pattern B—Reflecting: Little Emotion Tone and Much Abstraction

Reflecting

Patients present topics with a high amount of abstraction and without intervening emotions. This may be an expression of defense known as intellectualizing. B

Experiencing

Connecting

Pattern C—Experiencing: Much Emotion and Little Abstraction Patients find themselves in a state of emotional experiencing. Patients may be raising conflictual themes and experiencing them emotionally.

•

Emotion Tone

C3 Abstraction

Figure 1. The four emotion-abstraction patterns as z scores.

Abstraction can easily be measured within a text. Besides being a rich resource of abstract nouns, natural language provides the unlimited possibility to build abstract terms out of concrete concepts by performing a morphological transformation on single word forms. The "toolbox" provides a set of suffixes that can be used to build abstract nouns. Thus taking "being tender," one can easily build "tender-ness"; or, using the word "we" allows for the neologism "we-ness." As for emotion tone, it is assumed that abstraction as an expression of reflection varies in intensity and that this flow can be measured. The possible combinations of emotion tone and abstraction as expressed in language have clinical significance. This leads to the following general hypothesis: For a "good hour" (key session) to emerge, the temporal coincidence of abstraction and emotion tone is a necessary condition. The same is true for a "good moment" (key moment) within a session. Emotion-Abstraction Patterns

The quantitative dimension of emotion tone and abstraction allows the differentiation of at least four classes that are henceforth referred to as emotion-abstraction patterns. They are the constituents of the method to be developed. Graphically they are represented as a combination of the z-scored relative frequencies for emotion tone and abstraction words (see Figure 1). The four patterns are defined, labeled, and interpreted as follows.

Pattern A—Relaxing: Little Emotion Tone and Little Abstraction Patients talk about material that is not manifestly connected to their central symptoms or issues. They describe rather than reflect. Furthermore, it is a state that patients return to as often as they feel the need to, thus regenerating both physis and psyche to prepare themselves for the next step of their "talking cure."

Pattern D—Connecting: Much Emotion Tone and Much Abstraction Patients have found emotional access to conflictual themes and they can reflect on them. This state marks a clinically important moment: This is the instant that was introduced as key moment earlier.

On Dependency of Emotion Tone and Abstraction Using the constructs of emotion tone and abstraction, four clinically relevant states can be differentiated. In developing them into a measurement, it is important, however, that these measures are designed as statistically independent from one another. The construct of emotion in psychologically oriented research has frequently been dealt with in relation to the construct of concreteness. As one of the major results from the many works on rating word forms for emotion and concreteness, it is known that these two concepts are correlated. This becomes immediately obvious in the metaphoric use of language when reporting emotional experience (Lakoff, 1987). A metaphor such as "I went through the roof" is a concrete way to express anger. Interestingly, few empirical findings have been reported so far concerning the correlation of emotion with abstractness. However, Vikis-Freibergs (1976) in a study on the emotionality and abstractness of French verbs, has stated that the two variables are independent. This becomes also evident as the metaphoric use of language is barely possible with abstract terms. In regard of the method to be developed here, therefore, the theoretical constructs of emotion tone and abstraction are considered as suitable for building the four classes of emotionabstraction patterns.

The Therapeutic Cycle Model During recent years in psychotherapy research, one could observe a change in thinking toward cyclical models based on iteration and recursion. Among the more well-known ones are Wilma Bucci's referential cycle (Bucci, 1993), the states of mind model by Mardi Horowitz (1987, 1991), and the assimilation model by William Stiles et al. (1990). The model that is

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view over the course of a treatment and a microanalytic view describing the flow within a session.

Macroanalysis

I

II

III

IV

V

Relaxing

Experiencing

Connecting

Reflecting

Relaxing

Figure 2. Prototypical cycle of emotion-abstraction patterns within the course of a psychotherapy session.

presented here (see Figure 2) is derived from a specific temporal sequence of the four emotion-abstraction patterns. This is introduced as the therapeutic cycle model, consisting of five phases. It is based on the assumption that, in the course of a psychotherapy or within a psychotherapy session, emotion-abstraction patterns do not occur by chance; rather, a periodic process for the underlying variables emotion tone and abstraction is assumed. In explaining this, not only psychic but also biological factors may be taken into account (e.g., endorphins).

Phase I The starting point is Pattern A (relaxing), moments where patients do not show much emotion nor abstraction. They find themselves in a "relaxed" state, in a transitional state from one theme to another, or they are associating freely.

Phase II After a while, emotion increases and Pattern C (experiencing) shows up. This shift can be initiated by having reported a narrative (dream, early memory, episode) or by reporting on the symptoms they are suffering from. Patients at this time are in a state of emotional experience.

Phase III Ideally here, the amount of reflecting increases, either by patients' own impetus or guided by the therapist. Patients reflect on their recent emotional experience and thus reach emotional insight. They are in a state of connecting emotion tone and abstraction, showing up as Pattern D (connecting).

Phase IV As a consequence of the insight processes, the emotional tension decreases. Patients can reflect on their new experience without being bound to emotional constraints. Pattern B (reflecting) shows up.

Phase V Finally, reflection fades out. The cycle ends with the state of relaxing (Pattern A), which can lead to the emergence of a new cycle. The therapeutic cycle model allows for both a macroanalytic

If the emotion-abstraction patterns are computed for complete therapy sessions, a therapy can be characterized by the given sequence of these patterns. Turning points are given by the session immediately before a shift into a new pattern. Key sessions will show up with Pattern D (Connecting). For shortterm therapies, no more than one cycle is expected to occur. However, one is able to locate turning points and key sessions. In long-term therapies, the Therapeutic Cycle can be expected to occur several times. From clinical experience, it is known that at least in successful therapies there are phases in which the patient is "productive," which means processes of insight occur more frequently. However, there are also periods in which defense mechanisms dominate or patients are occupied by emotional states. This experience is what the therapeutic cycle model puts into an ideal order. Depending on the intensity and duration of a therapy (e.g., psychotherapy vs. psychoanalysis), the various phases of the model can become repeated (repetition), cycles can be repeated (iteration), or one or more cycles can occur within a cycle (recursion). This constitutes the descriptive power of the therapeutic cycle model.

Microanalysis The therapeutic cycle model describes the very moments of genesis, effect, and end of therapeutic progress, a movement toward which patient and therapist aim. The therapeutic cycle is not expected to occur frequently or repeatedly within a session, or even in every session. It is more likely that patients will pass through a therapeutic cycle only partially within a session. There are at least two reasons for this. First, many patients have to learn "verbalization" as a typical therapeutic tool. Not all patients intuitively will be able to "work" verbally on themselves. Second, defense processes may prevent a coincidence of emotion tone and abstraction. Thus, patients as "apprentices" may in the early stages of their therapy more often shift from relaxing to experiencing or reflecting and back. This should change, however, in favor of the therapeutic cycle model with increasing experience in "doing" psychotherapy. Patients who do not succeed in connecting emotion tone with abstraction during their therapy are likely not to improve. With the therapeutic cycle model as proposed here, it is the first time that the clinical concept of emotion is brought together with the phenomenon of abstraction and seen to be functional and productive for the therapeutic process. It is expected to allow one to operationalize and to measure the most important concept of psychoanalysis, emotional insight, in a transparent way. After almost 100 years of psychoanalysis, this seems astonishing. However, there may also be some explanation for this because another important concept of psychoanalysis— namely, defense—is strongly connected with abstraction. It is only in psychologically oriented writings that attempts can be found to describe the change in levels of abstraction as a therapeutic sine qua non (Schneider, 1983), without postulating the coincidence of emotion and abstraction however.

EMOTION-ABSTRACTION PATTERNS

Method The method for measuring the emotion-abstraction patterns originates from a technique called automated content analysis, which was introduced by Stone, Dunphy, Smith, and Ogilvie in 1966 within the realm of the social sciences. Within the field of psychotherapy research, Spence (1970) was the first to use this technique. Computer-aided content analysis can be seen as a mechanized variant of the classical content analysis. The method uses lists of words thematically ordered into categories. These lists are referred to as dictionaries. They are compared with the text under analysis, and the frequency of occurrence of each single word is counted yielding a frequency distribution for the associated categories. As a basic assumption of content analysis, we expect a theme to be the more prominent in a text, the more references we can find to it. This, however, was the subject of a controversy, which was raised by Berelson (1952) and Kracauer (1952) and which focused on aspects of quantitative versus qualitative content analysis. Although this controversy never was resolved, its importance decreased in the subsequent years, thus a pragmatic stance was taken. Kracauer (1972), and later on Howe (1988), pointed out that the two approaches overlap, with quantitative analyses ending up with qualitative considerations, and qualitative analyses often requiring quantification. Also, this controversy became less critical as more results were produced through quantitative methods, particularly computer-aided content analyses that addressed qualitative issues (Oxman et al., 1988a, 1988b; Rosenberg, Schnurr, & Oxman, 1990). The technique developed and used within this article is called computer-aided text analysis. This is to make clear that in contrast to the aforementioned approach, it is not intended to quantify the various meanings or contents of a text but rather to identify more general thematic aspects. An entry from the dictionary that matches a word in the analyzed text is seen as a "marker" indicating the presence of a thematic construct. Given this approach, the controversy about qualitative and quantitative aspects again is made obsolete by interpreting quantitative findings thematically and with regard to their significance. Computeraided text analysis as proposed here provides the following information: Are the phenomena of interest in the text, and if so, where are they located?

Software Realization The application of this scientific approach depends on development of suitable software. The analysis of the text material, as discussed here, was conducted using the text analysis program TAS/C (Mergenthaler, 1993). This software was specifically conceived for applications in the field of psychotherapy research and offers many different ways to investigate verbatim transcripts. Thus, analyses can be performed separating patient's and therapist's speech but also as a total text without this distinction. Furthermore, analyses can be done for any selected segments marked within the text, as for example, units given by time markers, blocks of an equal number of words, or the identification of dreams, early memories, or other episodes. TAS/C is designed to handle large amounts of text; thus, for example, it would be able to analyze all the transcripts from a complete treatment in one run. The TAS/C software requires a Unix environment at the time being. A version running on Macintosh and personal computers using Windows is now being developed. TAS/C supports a data interface to transfer its results to other software products. Within this study, these have been SYSTAT for Macintosh for the statistical analyses and DeltaGraph Pro for Macintosh for the graphical representation of the findings.

The Development of the Dictionaries The dictionaries were developed for the English language. Applications to other languages are being prepared.

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The emotion tone dictionary. In the first step, the emotion tone dictionary was compiled from various word lists taken from literature. In particular, there was the input of the emotion category from the Regressive Imagery Dictionary (Martindale, 1975). In the second step, a body of approximately 1 million words of running text, taken from English texts stored in the Ulm Textbank, were examined for emotionally tinged words. The developed word list was revised in such a way that words meeting certain exclusion criteria were deleted from the dictionary. 1. Words with concrete aspects of sensory reference are excluded; for example, "heart" or "warm." Within the scope of this work, emotion should be viewed as a narrowly defined construct. By excluding concrete words, one can avoid the metaphorical expression of emotions, which would be hard to distinguish from the denotative usage of these words, without emotional reference, using automated procedures. Another reason for this exclusion is the desired independence of the variables emotion tone and abstraction. Because emotion and concreteness are correlated, and also concreteness and abstractness are negatively correlated, with the addition of the concrete words, used in an emotional context, a negative correlation between the variables emotion tone and abstraction could indirectly be created. 2. Only words that can be classified into at least one of the following dimensions, are included in the dictionary: pleasure-displeasure, approval-disapproval, attachment-disattachment, and surprise. These four scales go back to the work of Sandhofer-Sixel (1988) and represent, borrowing from Kleinginna and Kleinginna (1981), the convergence of current emotion theories. As just two examples, the "Basic Emotions" by Paul Ekman, as well as the categories of De Rivera, which are based on a binary decision tree (De Rivera, 1977), can both be placed on these dimensions. The schema of Sandhofer-Sixel allows the fixation of an emotion on a continuum of all four dimensions at the same time, whereas Ekman and De Rivera exclusively reflect emotions in single categories. Sandhofer-Sixel's dimensions are used for a quick, reliable, and simple selection of emotion tone words. The dictionary developed on this basis comprises only a single category with the common term emotion tone and does not use any further divisions. 3. Words that have multiple meanings in their language usage and occur frequently (e.g., like, mean, kind, well) were also removed from the dictionary. With this procedure, the effort of an important and timeconsuming step of the text analysis was reduced. In this step, the transcripts that had to be analyzed were examined, and word forms with multiple meanings were "disambiguated" by inserting appropriate markers. Even today, automated procedures in a practical form are available only for chosen domains, although considerable progress in linguistic data processing, especially for the written language, has been made in recent years (Jacobs & Rau, 1993). Because in psychotherapy any imaginable theme could be addressed in spoken language form, procedures with thematic constraints or constraints concerning the form of the script cannot be applied. In its current form, the emotion tone dictionary consists of 2,305 items, including inflected forms. In a sample of 80 sessions from 20 patients (as discussed in detail later) emotion tone covers an average of 5.4% of the text, with a standard deviation of .62%. The abstraction dictionary. The abstraction dictionary was obtained primarily through a suffix analysis of all the words in English texts that were available in the Ulm Textbank. This technique goes back to the study of Gillie (1957), who showed that the use of specific endings (e.g., -ness, -ity), which is typical for abstract word forms, correlates significantly with the classification of texts by observers regarding the construct of abstraction. The suffix analyses use the TAS/C program with instructions that are capable of examining each word of a text for the following endings: -ity, -ness, -nee, -ment, -any, -ncy, -ship, -dom, -ing, -ion, and their plural forms. The abstraction dictionary includes a total of 3,900 entries. In a sample of 80 sessions from 20 patients,

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(discussed later) it covers an average of 4.0% text with a standard deviation of .53%. The interplay of the two dictionaries. In the existing version of both dictionaries, a word form was permitted to be in either the emotion tone or the abstraction dictionary but not both. Given this constraint, when the uncoded words are added as a third category, 100% text coverage is achieved. Thus, the statistical analysis of the text becomes easier and more transparent. In fact, however, there are many instances in which emotion tone words are changed by suffixes into abstract word forms (e.g., hesitancy, tenderness). The coincidence of emotion tone and abstraction in its linguistic realization on a word level is, in fact, expressed exactly in this phenomenon. The impact of this phenomenon has not been investigated in the present work. Instead, the question of classification of such word forms was decided pragmatically in the present study for purposes of a more straightforward methodology. Because abstraction was shown in pilot work to have 1% to 2% less text coverage than emotion tone, abstracted emotion tone words were included in the abstraction dictionary, thus increasing its text coverage and, hence, allowing for smaller scoring units. If these word forms were included as a linguistic realization of the coincident expression of emotion tone and abstraction, this would be expected to strengthen the findings of this study, on the grounds of the redundancy that is characteristic of human expression. This will be investigated in further work.

Textual Data Used The method of measuring emotion-abstraction patterns will be presented using two different types of clinical text corpora. The material has been chosen in such a way that the validity of the method can be demonstrated as well. This became possible because independent clinical evaluations and results from psychological tests are available for both corpora, which can be interpreted in relation to the hypotheses that one may want to test. The first corpus is a sample of 80 sessions taken from the Penn Psychotherapy Study (Luborsky, Crits-Christoph, Mintz, & Auerbach, 1988). It consists of four sessions from each of 20 treatments. The second corpus is the case of "Patricia," covering all 28 sessions of a psychodynamically oriented short term psychotherapy provided by the Project on Conscious and Unconscious Mental Processes (Horowitz et al., 1993). It is known from independent clinical studies of this treatment that it had a clear key session and two key moments within this session. All patients were informed of the nature of the respective study and consented to the intensive research on their therapy.

differences in terms of age, gender, marital status, and religion. According to the second edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-II), none of the patients was psychotic. The most frequent diagnoses included adaptation disorder, compulsive personality, depressive reaction, and schizoid personality. The mean length of treatment was 61 weeks for the improved patients and 43 weeks for the nonimproved ones. For each patient, a sample of two sessions from the beginning and another two from the end were chosen. Transcription was conducted for the first 20 min of these selected sessions. It was an assumption of the Penn Psychotherapy Project group that those phenomena that are examined within the project occur sufficiently often within the first third of a therapy session. This assumption is accepted with respect to the goals of the study presented here.

The Case of Patricia The data used for the single-case study were recordings of a participant who was given the pseudonym "Patricia." At the age of 40, she had a pathological grief syndrome after the death of her husband. She was selected from a pool of individuals who had lost an important person in their lives. She was treated in the research setting with a 28-session brief psychodynamic therapy 18 months after the traumatic event, with substantial subjective and objective improvement (for more details, see Horowitz etal., 1993). In the case of Patricia, Session 12 is a breakthrough, or key session. A group of reviewing clinicians decided that this session was exemplary in containing in clear form a prototype of her key conflicts. Furthermore, Session 12 has two 5-min segments showing signs of defensive control that are seen as being key moments (Horowitz, Milbrath, & Stinson, 1995). To allow a better understanding, I summarize the first 11 sessions as follows: The patient was describing the good properties of her late husband James throughout the first 10 sessions. He was being idealized. Gradually, however, she brought in more and more comparisons with her new friend Sidney. While at the beginning, she barely admitted that Sidney had properties as good as her husband's, this changed until finally in the 11th session she described both men as being equally valuable. She mentioned how lucky she was to have found two such wonderful men. After this session, she decided to marry Sidney. This event initiated more working through on the topic of "self as being married with James" and "self as being married with Sidney" in the following 12th session.

Transcription The Penn Sample In the Penn Psychotherapy Study (Luborsky et al., 1988), 73 treatments were examined and rated for outcome. For subsequent studies, a sample was chosen consisting of 10 patients each with the best and worst outcome and with the additional condition that each of these treatments must have at least 25 therapy sessions. Outcome was measured based on "residual gain" and "rated benefits" scores. Residual gain was calculated on the basis of ratings by the patients themselves and by clinical observers at the beginning and at the end of the treatment using a battery of accepted measures. Rated benefits was rated immediately after the end of the treatment by both patient and therapist independently. Because of the fact that the rated benefits and residual gain measures showed a high significant correlation (r = .76), those cases were selected for the most and least improved samples based on extreme scores for at least one of the two measures. Fifteen cases were selected due to residual gain, 5 due to rated benefits. The 20 patients were treated by 18 psychodynamically oriented male therapists including eight experienced therapists and 10 who had 2 or 3 years experience as a therapist and were still under supervision. The improved and nonimproved samples did not show significant

The transcription of the Penn corpus was done without using a specific transcription standard. When entering these data into the archive of the Dim Textbank, these transcripts were adapted to the set of rules in use there (Mergenthaler, 1985). The case of Patricia was transcribed according to the Psychotherapy Transcription Standards by Mergenthaler and Stinson (Mergenthaler & Stinson, 1992), which is basically an adaption of the aforementioned rules of Mergenthaler for American English. Therefore, the results that will be received for both corpora are considered to be comparable.

Segmenting of Transcripts To describe the flow of a variable within a session, a segmentation into scoring units is needed. The measurement then can be done for each segment independently, and the course of the respective variable can be observed or further analyzed using the sequence of the measured values. For statistical reasons, there should not be less than 7 to 10 scoring units. On the other hand, the upper bound is also limited otherwise a single segment would become too small in terms of number of words included. In fact, computer-aided text analysis needs a minimum

EMOTION-ABSTRACTION PATTERNS amount of words per scoring unit as well, otherwise the results would have to be considered to be the result of chance (Mergenthaler, 1985, pp. 77-81 and pp. 172-173). This estimate has to be based on the variable with the least text coverage. As is shown in the results, this will be abstraction with about 4%, which needs a minimum of 129 words (see table in Mergenthaler, 1985, p. 173). Thus, the often used "idea units" or "thought units" (Butterworth, 1980) are not suitable, because they normally just comprise little more than one sentence. Therefore, transcripts were segmented into word blocks of 150 words each. However, this arbitrary segmentation procedure does not take the thematic flow within the session into account. To compensate for this, the data were smoothed using a weighted mean ( 1 -2-1) spanning over three word blocks. In a pilot study, meaning-determined thematic units, scored using procedures developed by Stinson, Milbrath, Reidbord, and Bucci (1994), were found to map adequately onto units developed using this segmentation and smoothing procedure. The text analysis within this study except for parts of the single-case evaluation are presented without separating patient's and therapist's speech. From a text-linguistic stance, as it is taken here every word uttered by a patient is determined not only by his or her own preceding words but also by those of the therapist and vice versa. Text-analytic techniques that take care of how to analyze patient and therapist separately and related aspects are currently being developed and will be presented elsewhere.

Hypotheses The usefulness of the emotion-abstraction patterns was evaluated by testing two hypotheses (H1-H2) and by investigating three exploratory hypotheses (E1-E3): H1: Successful patients differ from patients that did not change in a positive way or got worse by having a higher percentage of the emotionabstraction pattern D(connecting). H2: The use of emotion-abstraction patterns in the course of a therapy will be different for successful patients or patients that did not change in a positive way or got worse. The former ones will have the Pattern D (connecting) more frequently at the end of their treatment, compared with the beginning. E1: Being applied to a sequence of therapy sessions, clinically important (good hour) sessions can be identified by an outstanding Pattern D (connecting). E2: Being applied to a sequence of contiguous segments within a therapy session, clinically important moments (key moments) show up as therapeutic cycle. E3: Successful patients compared with patients that did not change in a positive way or got worse will have a higher percentage of emotion tone and abstraction. Justification: It is expected that both groups of patients do not differ statistically with regard to reflecting and experiencing. For the successful patients, however, it is expected that they additionally have or acquire the capacity of connecting. As a consequence, this results in a higher proportion of both variables for them.

Results The Penn Sample The variables emotion tone and abstraction. The proportion of the variables emotion tone and abstraction was calculated for each session (« = 4 X 20). As each of the 20 patients had four sessions in the sample, first the mean for each patient was computed and then the overall patient mean was derived. The same was done when differentiating early and late sessions. Overall emotion tone has a mean proportion of M = 5.4%, SD = 0.62% and abstraction has M = 4.0%, SD = 0.53% (« = 20).

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Table 1 Distribution of Text Variables by Outcome Early and Late in Therapy Early (n = 10)

Late(» = 10)

Not

Variable

Improved

improved

5.6 0.7

5.4 0.5

4.2* 0.7

3.8 0.5

Not Improved

improved

5.5*

4.9 0.7

Emotion tone

M SD

0.8

Abstraction

M SD

4.4**

0.7

3.8 0.4

Note. The values represent mean percentage. *p < .10, one-tailed for unpaired samples. **p < .05, one-tailed for unpaired samples.

The emotion tone and abstraction dictionaries together cover a total of 9.4% of the text. The improved patients have significantly higher levels for the variable abstraction (M = 4.3, SD = 0.6 vs. M = 3.8, SD = 0.3, n = 10; / test for unpaired samples, one-tailed, p < .05). Although for emotion tone the difference is not significant, successful patients numerically are in the expected direction. Considering the results from both dictionaries together, the differences become even more clear (p < .01). This supports the exploratory hypothesis E3. The differentiation between early and late sessions for the same data is shown in Table 1. The differences found between patients who were successful and those who were not at the beginning of the treatments are not as clear as toward the end. At both moments, however, the scores for emotion tone and abstraction are higher for the successful patients. The variables emotion tone and abstraction were not correlated for this sample (Spearman r = .001, ns). This was also true when differentiating for outcome or for early or late sessions. A test for differences that were due to gender of patients (therapists were all male), age, and education also did not yield a trend or significant finding. The distribution of emotion-abstraction patterns. All sessions were segmented into word blocks of 150 words each (partial word blocks at the end of a session were omitted if they had fewer than 75 words). The result was a total of 3,346 blocks for all 80 sessions. A total of 1,590 blocks (47.52%) belonged to the improved patients, the other 1,756 (52.48%) constitute the text of the nonimproved patients. This difference is statistically not relevant. Figure 3 shows that, in concordance with the expectations from hypothesis H1, the successful patients have a higher proportion of connecting than those who were not successful (M = 20.9%, SD = 4.1% vs. M = 18.4%, SD = 2.9%, respectively) and a lower one of relaxing (M = 25.7% vs. 27.4%, respectively). Statistically seen, the former is a trend (/ test for independent samples, p < .10). Also, in accordance with the exploratory hypothesis E3, the two groups do not differ with regard to reflecting (M = 26.8%, SD = 3.4% vs. M = 27.2%, SD = 3.4%) and experiencing (M = 26.6%, SD = 3.1% vs. M = 27.0%, SD = 3.1%).

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Improved Patients (N=10)

Not Improved Patients (N=10)

Relaxing Reflecting Experiencing Experiencing Connecting Percent 9

Connecting 5

Improved

20

25

-14 -7 0 7 A Percent

30

14 -14 -7 0 7 A Percent

14

Figure 4. Proportion of change during therapy for emotion-abstraction patterns by outcome.

—O— Not Improved

Figure 3. Distribution of emotion-abstraction patterns by outcome.

In a comparison of the results for the early and late sessions (see Table 2) at the beginning of the therapies, improved and nonimproved patients showed only little differences, whereas these became much clearer toward the end. Using an analysis of variance (ANOVA) model with outcome as a grouping factor and time (early vs. late) as a repeated measurement factor gave the following results: For the dependent variable connecting, the effect of outcome shows a trend (cf. results to hypothesis H I ) . The effect of time was not significant. The interaction of both effects was significant (p < .05, one tailed), with improved patients showing an increase in usage of connecting, whereas the nonimproved patients decreased. This is seen as a confirmation of hypothesis H2. There was no significant interaction for the other three patterns (see also Figure 4). It has to be noted that the design of the Penn Sample uses

Table 2 Distribution of Emotion-Abstraction Patterns by Outcome Early and Late in Therapy Late(«= 10)

Early (n= 10) Pattern

Improved

Not improved

Improved

Not improved

extreme groups, which bears limitations. Thus, the aforementioned results do not necessarily generalize to the full range of outcomes. A study including the middle group will be necessary and is currently being prepared.

The Case of Patricia Emotion tone and abstraction. All 28 therapy sessions have a mean of 5.9% for emotion and 3.4% for abstraction. Thus, Patricia clearly has a higher proportion of emotion tone than the sample of successful patients (5.4%). For abstraction, however, Patricia has even less than the sample of nonimproved patients (4.0%). This becomes very clear when the data become differentiated for patient and therapist (Table 3). It is also obvious that the therapist has much more abstraction than his patient. In addition, there is a significant intrasession correlation for emotion tone between patient and therapist (Spearman r = .44, p < .05, based on word blocks). Abstraction is not correlated for them (Spearman r = .10, ns). On the other hand, the emotion tone scores for the patient are significantly correlated with the abstraction scores for the therapist (Spearman r = .39, p