In the following, the results of both approaches to dream report analysis will be compared with respect to several selected criteria (Table 2).
Table 2 Comparison criteria of the three approaches (HVCCS, GRS, ZDPCS)Theoretical presuppositionsThe ZDPCS is based on a dream-generation theory. Following French [6], dreams are viewed as attempts to deal with unresolved problems (complexes) such as neurotic conflicts or traumatic experiences. The dream process aims to find a solution or the currently best possible adaptation to the reenacted complex. To achieve this objective, a set of cognitive-affective procedures termed dream organization simulates, positions, and regulates cognitive elements. By transforming affective information from the dream complex into a simulated interactional experience, the dream receives its problem-solving potential; the dream ego can strive for better solutions in terms of interactive outcomes. In contrast, dream content analysis abstains from assumptions on how dreams are generated and what function they serve, resulting in its descriptive, inductive approach.
Coding materialBoth approaches use the transcribed dream report. However, the ZDPCS refers to the actual content of the dream report and deletes specific narrative artifacts such as comments. Likewise, the order of the dream plot is restored if, for example, information about the beginning of the dream is reported at the end. The analysis is then based solely on this edited version. Thus, information such as comments from the dreamer is lost. Dream content analysis works with the unaltered dream report including comments of the dreamer which can help external raters to, e.g., clarify complicated narratives or the intensity of emotions. A trade-off between loss of information and merging dream and waking experience is revealed.
Evaluation categoriesTwo main categories of evaluation in HVCCS and ZDPCS focus on dream characters and social interactions; thus, both approaches capture the two characters that feature. HVCCS captures the male gender and categorizes the connection to the dreamer (familiar and husband). In the ZDPCS, the familiar quality is also captured but not gender, unless it is explicitly stated as an attribute. Moreover, in the ZDPCS, persons are coded in each segment in which they appear, whereas in the dream content analysis, they are coded once, regardless of the duration/number of appearance(s).
Both social interactions in the dream, the kiss and the verbal interaction are captured from both systems. HVCCS captures their intensity based on content aspects; sexual intercourse is more intense than a kiss, as a verbal threat is less intense than physical harm. The intensity of interactions is captured in the ZDPCS based on formal characteristics (affective involvement of dream ego and complexity of simulated relationship model). A kiss or sexual intercourse results in the same code, which marks mutually regulated interaction with physical contact between a dream ego and a human person. Playing soccer is less intense than watching others play soccer and a soccer match on TV reflects even more distance.
Economic considerationsWhereas dream content analysis can be applied relatively easily, the ZDPCS requires intensive training. Likewise, the effort required to assess a single dream is much higher. Studies using dream content analysis require the selection of relevant scales. If scales on specific content aspects are not available, new scales need to be developed, leading to problems related to reliability and validity [19]. Parameters of interest can be constructed for statistical analysis, e.g., by the ratio of positive to negative emotions. The ZDPCS, on the other hand, does not directly provide global ratings for a single dream but offers a broader range of options for creating additional categories.
Empirical findings illustrate these differences. For example, when examining the dreams of veterans with respect to trauma-related psychopathology, analysis of dream content reveals that, among others, more “weapons,” “aggression,” “death,” “threat,” and “combat,” and fewer “friendly interactions” are characteristic [2].
In comparison, an analysis of patterns of affect regulation dynamics in dreams of trauma survivors reveals that “an abrupt overwhelming beginning, passivity of the dream ego, absence of or failing of trials to leave this passive position by means of interactions or locomotion, absence of or failing of metacognitions and metarelations, as well as a sudden ending and resulting on-off-character of the dreams” [22, p. 1] are characteristic.
Norm dataExtensive normative data on dream content are available for the HVCCS. However, Hall and Van de Castle [7] collected their data in the middle of the last century from mainly white students at universities in the USA. Accordingly, dreams of men more often take place in an outdoor setting, whereas explicit emotions are more frequently found in dream reports of women. On the one hand, one could thus assume that heteronormative gender roles from the 1950s are reflected in the results. However, surprisingly, these norms have been replicated several times (e.g. [4]). On the other hand, even though gender is a relatively simple trait factor, matching the dreamer’s gender from a single dream report is difficult [18]. Especially for associations between clinical trait factors and dream content, large samples are necessary. Regarding the ZDPCS, no norm data are available thus far.
Time course of dream contentDream content analysis assigns selections of content to categories or rates the intensity of overall impressions without considering the development of the dream plot. This may be comparable to the substitution of a movie by a photograph. However, the order of events carries more information than their presence alone. For instance, whether the dream ego confronts an enemy and then runs away or instead at first runs away but then turns to confront makes a significant difference from the perspective of dream regulation. Analyzing the transformations that lead from each segment to the next over the time course of the dream plot is a central advantage of the ZDPCS. Transformations from each segment to the next can be systematized according to whether the result is an increase or decrease in the level of affectualization of the dream [12].
Sample size considerationsDream content analysis is usually performed to examine a rather large number of dreams due to its advantages in quantifying and identifying patterns within different samples. For instance, Rimsh and Pietrowsky [13] showed by using the HVCCS that dreams of anxiety patients contain, among other things, more characters, higher numbers of aggressive interactions, lower numbers of friendly interactions, and higher frequencies of misfortunes and negative emotions. Due to its descriptive character, dream content analysis for single dreams—as illustrated here—offers limited information.
The analysis of affect regulation by the ZDPCS focuses primarily on the dynamics of a single dream. However, the ZDPCS offers a wide range of options for quantifying specific aspects of dynamic affect regulation in dreams [3, 5, 22]. Capacities for affect regulation can be quantified, e.g., by the number of alternations between involvement and safety processes.
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