1/27/2024 0 Comments Assessing coherence in writingThus, LSA may provide a related but distinct operationalization of memory organization compared to other methods. As an extreme example of the contrast between approaches, in LSA two consecutive identical sentences are considered perfectly correlated, contributing to high coherence, whereas in a commonly-used narrative coding system, repetition of thought is “the most direct index of fragmentation” ( Foa et al., 1995, p. Coherence is operationalized as the average semantic relationship between each consecutive sentence thus there is no holistic evaluation of the organization of the narrative, nor any assessment of the quality of thought within individual sentences. LSA’s approach to coherence is very different than approaches that involve expert-coded ratings of fragmentation, or self-reported ratings of organized thoughts. Coherence in this study is defined as the mean of the correlations between each successive sentence, which represents how well each sentence flows into the next to support the overall meaning of a text. Both of these applications involve LSA’s approach to computing coherence, which is to calculate the semantic similarity (expressed as a correlation) between each successive pair of sentences (e.g., the first and second, the second and third, etc.) in a document ( Dennis, 2007). LSA has been used to summarize and grade student essays ( Landauer, 2007), as well as discriminate between people with and without schizophrenia based on the coherence of answers to interview questions ( Foltz, 2007). Once LSA is “trained” on enough texts to extract meaning from words, then texts of any length-from a single word to long passage-can be compared for their semantic similarity. By deriving the meaning of a word as a function of its relationships to other words occurring across a large body of texts, LSA builds a network of meanings in which the meaning of each word is characterized by loadings on a set of dimensions. LSA is a computational method for modeling semantic meaning from text ( Landauer, 2007). The current study introduces Latent Semantic Analysis (LSA) as a method to examine the coherence of expressive writing. Reviewers attribute this in part to “limitations in how disorganization or fragmentation are conceptualized and operationalized” and recommend as a “priority for future PTSD narrative research…to develop measures of narrative organization that are valid but less transparent than the present ones” ( O’Kearney & Perrott, 2006, p. However, despite clinical and theoretical accounts that describe trauma memory in PTSD as lacking coherence, the literature on narrative coherence and related constructs in trauma memories is inconclusive ( Crespo & Fernández-Lansac, 2016 O’Kearney & Perrott, 2006). In order to study the structure and content of trauma narratives, researchers have relied on self-report of memory disorganization ( O’Kearney, Hunt, & Wallace, 2011), rater-coding of trauma narratives for variables such as fragmentation and organization ( Foa, Molnar, & Cashman, 1995), or computer-assisted counting of words in different content categories that appear in the narratives ( Jaeger, Lindblom, Parker-Guilbert, & Zoellner, 2014).Īn important distinction in this literature has been between cohesion, which typically involves surface features like specific word choice and reflects connectedness of temporal and causal relationships, and coherence, which involves deeper conceptual organization throughout the entire document ( Foltz, 2007 Crespo & Fernández-Lansac, 2016 O’Kearney & Perrott, 2006). Several hypotheses about the effects of expressive writing suggest that it is beneficial because it helps create a more coherent and meaningful memory out of a disorganized and incomprehensible experience ( Pennebaker & Seagal, 1999 Smyth, True, & Souto, 2001). Expressive writing about a personally traumatic event over time can have positive mental and physical health effects ( Lepore, Greenberg, Bruno, & Smyth, 2002).
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