The SCCAP was initially developed as a paper and pencil instrument. Once this version was completed and tested, a computerized application was developed. The SCCAP application can be used across computer operating systems (Windows, Macintosh, and Linux). The program functions with a user-friendly point and click interface with drop down menus, text boxes, or counters.
SCCAP is an application designed to accomplish coding of verbal conversations from audio. The audio portion is not integrated into the SCCAP; the researcher listens to and uses his or her audio data directly from his or her own audio equipment. This is advantageous because transcription is costly and time consuming. Nevertheless, researchers can choose to transcribe and use the written transcription to aid in the coding process if they so choose. The SCCAP program is designed for audio only, rather than audio and video. Although nonverbal communication presents a multitude of observable cues audio retains nonverbal vocal inflections that impart meaning to the spoken words. Some researchers have argued that inclusion of kinesic information does not necessarily add significant explanatory power to coding only vocalic information (Dent et al., 2005
) and that vocal cues are a more reliable and valid channel for coding nonverbal cues (DePaulo, Rosenthal, Eisenstat, Rogers, & Finkelstein, 1978
; Haskard, DiMatteo, & Heritage, 2009
). Other recent work (Penner et al., 2007
; Riddle et al., 2002
) has indicated that nonverbal, observable behaviors have much to add to an understanding of a particular communication. However, recording of nonverbal data requires videotaping, which is often expensive or impracticable. Therefore, to maximize feasibility, reliability, and coding parsimony, our version of SCCAP is audio only. The flexibility of the program is such that future versions could include additional nonverbal coding sections (e.g., kinesics).
The program opens and runs from a main menu that offers several coder activities. These reflect three general sets of data. The first set, content themes, includes those activities that constitute the task or instrumental aspect of most medical transactions (e.g., providing treatment information). Content themes are delineated into general categories and then further refined into discrete communication behaviors or events (e.g., discuss treatment, side effects). Coders click each event or activity as it occurs in the interaction and the program automatically records speaker, topic, message form (statement or question) and sequence. The unit of analysis that the SCCAP developers have used to test the program is an utterance, that is, the smallest definable unit of meaning. We trained all coders to identify an utterance with accuracy and calculated reliability scores on that basis. However, the idea of the SCCAP was to provide researchers with as much flexibility as possible. Researchers need to choose their own unit of speech analysis as dictated by their theoretical framework and research questions. A highly focused research question examining specific content might only code every instance of a specific content item. Conversely, a study taking a holistic or linguistic approach might need to code every utterance. Researchers can decide how much communication data they need and use the program to obtain their desired level of detail as long as the coding unit of analysis is clearly defined and the coding is consistent.
The second set consists of communication types. These are the aspects of communication that indicate relational information or influence attempts. Within this group are nested additional menus for recording question types. Content themes and communication types are coded at the same time. As the coder assigns a specific content theme to an utterance, she toggles to another coding screen that offers a menu of various communication types. After coding, communication types can be analyzed as discrete entities or by how they are associated with the content codes.
The third set consists of observer speech and affect ratings, including emotions (e.g., anger, sadness) and more composite affect (e.g., composure). Coders are trained to observe nonverbal vocalic cues likely to indicate affective qualities of interaction (Frijda, 1989
). Speech ratings include those cues associated with the immediacy construct, such as speech rate and timber (Bradac, Bowers, & Courtright, 1979
; Kearney, 1994
). Coders rate each participant after listening to and coding content aspects of the interaction. Each of these primary data sets—content themes, communication types, and speech/affect ratings—are subsequently described in more detail.
Content themes reflect commonly occurring communication functions in most health interactions (Cole & Bird, 2000
). The underlying assumption is that information exchange is a primary function of the interaction between providers and patients. Therefore, the utility of the program lies in being able to code exactly who exchanges what information, how frequently, and in what sequence. The content themes include introduction, purpose of visit, medical history, disease information, prognosis information, treatment information, clinical trials, logistics, preferences and values, psychosocial information, emotional, procedural directives, and closing. The program allows the researcher to add as many or as few sub-themes as desired under each content heading. Researchers may use all or only some of the content themes in the SCCAP program, depending on the health care context under study, the level of detail required or theoretical predictions. defines each major content theme domain.
Siminoff Communication Content & Affect Program content themes
As the content themes are coded, the program logs each categorized utterance as it occurs in a real time sequence. Because of this ongoing sequencing, content themes are coded at the same time as the second primary group of variables, communication and question types. This approach is consistent with a transactional view of communication that recognizes simultaneous streams of content and relational communication during interactions.
The second coding group, communication types, encompasses those utterances that fulfill relational and social-influence functions of provider–patient communication. As the coder clicks content subtheme codes, he or she can also access a communication types menu from a sidebar on the screen. This menu offers options for confirming and disconfirming messages, arguments and refutations, and compliance strategies. defines these relational message types.
Definitions of communication types
Question forms are also embedded within the communication types section of the SCCAP. Questioning is a fundamental mode of active information seeking and is particularly important in health care conversations (Berger & Calabrese, 1975
). Therefore, several question descriptors are available to indicate the function of a question (e.g., seek understanding, service), topic (e.g., economic, spiritual concerns), and whether the question was open- or closed ended. Questions can also be entered verbatim into a space provided for further analysis. Similar to other elements of the program, frequency and sequencing data for questioning is automatically calculated for each speaker during the course of the interview.
The third SCCAP coding group is the observer ratings section. These include third party observations of primarily nonverbal communication behaviors, such as vocal immediacy, composure, and expressed affect. Ratings are completed for as many health care providers, patients or others who contribute to the conversation. Immediacy cues include vocal expressiveness, speech rate, extemporaneous tone, vocal clarity, vocal encouragement, and inclusive pronoun use (e.g., we, our). Each item is rated on a scale of 1 to 7, with higher scores indicating optimum quantities.
Although research has identified a variety of communication skills specific to health transactions (e.g., questioning, listening, empathy), few focus on the qualitative features of communication that indicate closeness, warmth, and connection. These cues are fundamental to relationship development and have been associated with building rapport and increased patient disclosure and participation (Duggan & Parrott, 2001
; Street et al., 2005
; Zandbelt, Smets, Oort, Godried, & de Haies, 2007
). Positive (i.e., compassionate, involved, sincere, friendly, animated, expressive) and negative (i.e., sadness, anger) emotion items relevant to health contexts were scaled 0–6, with high scores representing higher quantities of that emotion.
The observer rating section of the main menu concludes with menus that enable description of decisions made during the interaction. For each decision discussed, the coder provides verbatim transcription and indication of decision options, option clarity, chosen option, and option discussed most.