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Major depressive disorder (MDD) is a serious and often chronic illness that requires early and urgent treatment. Failing to provide effective treatment of MDD can worsen the illness trajectory, negatively impact physical health, and even alter brain structure. Early optimized treatment (EOT) of MDD, with a measurement-based approach to diagnosis, rapid treatment initiation with medication dosage optimization, frequent monitoring, and prompt adjustments in treatment planning when indicated, should proceed with a sense of urgency. In this article, we describe common barriers to providing an EOT approach to treating MDD at each phase of care, along with strategies for navigating these obstacles. Approaching the treatment of MDD with a greater sense of urgency increases the likelihood of symptom reduction in MDD, facilitating full functional recovery and a return to life engagement.
Conversation Analysis (CA) is one of the predominant methods for the detailed study of human social interaction. Bringing together thirty-four chapters written by a team of world-renowned experts, this Handbook represents the first comprehensive overview of conversation-analytic methods. Topics include how to collect, manage, and transcribe data; how to explore data in search of possible phenomena; how to form and develop collections of phenomena; how to use different types of evidence to analyze data; how to code and quantify interaction; and how to apply, publish, and communicate findings to those who stand to benefit from them. Each method is introduced clearly and systematically, and examples of CA in different languages and cultures are included, to show how it can be applied in multiple settings. Comprehensive yet accessible, it is essential reading for researchers and advanced students in disciplines such as Linguistics, Sociology, Anthropology, Communication and Psychology.
This chapter discusses different types of evidence that conversation analysts use to ground their claims about social action. We begin by reviewing the epistemological perspective of CA, which demands that evidence reflect participants’ orientations; as a critical part of understanding the terms ‘participant orientation’ and ‘relevance,’ here we also discuss two ways in which CA’s position and emphasis on them are commonly misunderstood. The bulk of this chapter then reviews and illustrates a range of types of participant-orientation evidence. We organize our presentation of types of evidence roughly by sequential position vis-à-vis the focal action about which the analyst is making claims, including evidence to be found in: (i) next-turn, (ii) same-turn (e.g., same-TCU self-repair, accounts), (iii) prior turn or sequence, (iv) third turn/position (e.g., repair after next turn, courses of action/activity), (v) fourth turn/position, and (vi) more distal positions. We also discuss other forms of evidence that are not necessarily defined by sequential position, including: (i) third-party conduct, (ii) reported conduct, (iii) deviant cases, and (iv) distributional evidence. We conclude by offering some brief reflections on bringing different types and positions of evidence together toward the construction of an argument.
While the preceding chapters of the Handbook have focused on practical skills in CA research methods, this chapter looks towards the path ahead. A diverse group of conversation analysts were asked to outline possible projects, point readers toward un- or under-described interactional phenomena, and discuss persistent issues in the field. The contributions address future advances in data collection, specific interactional practices, the complex interplay between language and the body, and cross-cultural and crosslinguistic comparisons, among other issues. The chapter concludes with a concise reiteration of the bedrock principle that underpins all CA research methods.
This chapter is written for conversation analysts and is methodological. It discusses, in a step-by-step fashion, how to code practices of action (e.g., particles, gaze orientation) and/or social actions (e.g., inviting, information seeking) for purposes of their statistical association in ways that respect conversation-analytic (CA) principles (e.g., the prioritization of social action, the importance of sequential position, order at all points, the relevance of codes to participants). As such, this chapter focuses on coding as part of engaging in basic CA and advancing its findings, for example as a tool of both discovery and proof (e.g., regarding action formation and sequential implicature). While not its main focus, this chapter should also be useful to analysts seeking to associate interactional variables with demographic, social-psychological, and/or institutional-outcome variables. The chapter’s advice is grounded in case studies of published CA research utilizing coding and statistics (e.g., those of Gail Jefferson, Charles Goodwin, and the present author). These case studies are elaborated by discussions of cautions when creating code categories, inter-rater reliability, the maintenance of a codebook, and the validity of statistical association itself. Both misperceptions and limitations of coding are addressed.
Conversation-analytic (CA) research projects have begun to involve the collection of interaction data in laboratory settings, as opposed to field settings, not for the purpose of experimentation, but in order to systematically analyze interactional phenomena that are elusive, not in the sense of being rare (i.e., ‘seldom occurring’), but in the sense of not being reliably or validly detected by analysts in the field using relatively standard recording equipment. This chapter (1) describes two, CA, methodological mandates – ‘maintaining mundane realism’ and ‘capturing the entirety of settings’ features’ – and their tensions; (2) provides four examples of elusive phenomena that expose these tensions, including gaze orientation, blinking, phonetic features during overlapping talk, and inhaling; and (3) discusses analytic ramifications of elusive phenomena, and provides a resultant series of data collection recommendations for both field and lab settings.