Prosodic Phrasing and Syllable Prominence in Spoken Prose. A Validated Coding Manual

Current systems for predicting prosodic prominence and boundaries in texts focus on syntax/semantic-based automatic decoding of sentences that need to be annotated syntactically (Atterer & Klein 2002; Windmann et al. 2011). However, to date, there is no phonetically validated replicable system for manually coding prosodic boundaries and syllable prominence in longer sentences or texts. Based on work in the fields of metrical phonology (Liberman & Prince 1977), phrase formation (Hayes 1989) and existing pause coding systems (Gee and Grosjean 1983), we developed a manual for coding prosodic boundaries (with 6 degrees of juncture) and syllable prominence (8 degrees). Three independent annotators applied the coding system to the beginning pages of four German novels and to four short stories (20 058 syllables, Fleiss kappa .82). For the phonetic validation, eight professional speakers read the excerpts of the novels aloud. We annotated the speech signal automatically with MAUS (Schiel 1999). Using PRAAT (Boersma & Weenink 2019), we extracted pitch, duration, and intensity for each syllable, as well as several phonetic parameters for pauses, and compared all measures obtained to the theoretically predicted levels of syllable prominence and prosodic boundary strength. The validation with the speech signal shows that our annotation system reliably predicts syllable prominence and prosodic boundaries. Since our annotation works with plain text, there are many potential applications of the coding system, covering research on prose rhythm, synthetic speech and (psycho)linguistic research on prosody.

Evaluating Implementation Contexts, Mechanisms, and Outcomes: A Normalization Process Theory Coding Manual for Qualitative Research and Instrument Development

Background. Qualitative studies, especially those conducted by teams of researchers, may benefit from clearly structured, parsimonious, coding manuals. The process of creating rigorous and robust coding manuals for individual studies is rarely described, and generalizable coding manuals are rare. Normalization Process Theory (NPT) provides conceptual tools to facilitate understanding of the dynamics of adoption, implementation, and sustainment of socio-technical and organizational innovations. As a widely used theory, a generalizable coding manual would be of utility to implementation researchersObjectives. To make the application of NPT simple for the user, to describe the development of a coding manual for qualitative content analytic studies using NPT, and present this for wider use.Method. Concept Selection and Structuring. Qualitative Content Analysis of selected published papers and interview transcripts. Results. All identifiable theoretical concepts (n=149) embedded in papers and chapters that developed NPT between 2006 and 2020 were identified and extracted from their texts. Overlapping, ambiguous, and duplicate versions of concepts were eliminated, as were concepts derived from other theories. This left 38 core concept definitions. These were piloted in coding of qualitative transcripts collected in two implementation studies, and by collaboratively coding papers collected for a systematic review of implementation studies. At the end of this process, a further process of elimination of overlapping or ambiguous concepts was undertaken leaving 12 primary NPT concepts. Conclusion. The process of coding manual resulted in the presentation of NPT concepts according to the Context-Mechanism-Outcomes configuration of realist evaluation research. A coding manual for NPT that is in accordance with realistic evaluation research was successfully produced and is now freely available to researchers who wish to use NPT in primary and secondary research that employs qualitative methods.

Seeing the Woods for the Trees Again: Analyzing Evolutionary Diagrams in German and US University-Level Textbooks

Phylogenetic trees are important tools for teaching and understanding evolution, yet students struggle to read and interpret them correctly. In this study, we extend a study conducted by Catley and Novick (2008) by investigating depictions of evolutionary trees in US textbooks. We investigated 1197 diagrams from 11 German and 11 United States university textbooks, conducting a cross-country comparison and comparing the results with data from the 2008 study. A coding manual was developed based on the 2008 study, with extensions focused on additional important aspects of evolutionary trees. The US and German books showed only a low number of significant differences, typically with very small impacts. In both samples, some characteristics that can render reading trees more difficult or foster misconceptions were found to be prevalent in various portions of the diagrams. Furthermore, US textbooks showed fewer problematic properties in our sample than in the 2008 sample. We conclude that evolutionary trees in US and German textbooks are represented comparably and that depictions in US textbooks have improved over the past 12 years. As students are confronted with comparable depictions of evolutionary relatedness, we argue that findings and materials from one country should easily be transferable to the other.

Exploring the extent of digital food and beverage related content associated with a family-friendly event: a case study

Background Exposure to unhealthy food and beverage content is a contributing factor to the obesity epidemic. Youth are susceptible to unhealthy digital food marketing including content shared by their peers, which can be as influential as commercial marketing. Current Canadian regulations do not consider the threat digital food marketing poses to health. No research to date has examined the prevalence of food related posts on social media surrounding family-friendly events. The aim of this study was to explore the frequency of food related content (including food marketing) and the marketing techniques employed in social media posts related to a family-friendly event in Canada. Methods In this case study, a content analysis of social media posts related to a family-friendly event on Facebook, Twitter, and Instagram was conducted between January to February 2019. Each post containing food related content was identified and categorized by source and food category using a coding manual. Marketing techniques found in each food related post were also assessed. Results A total of 732 food and beverage related posts were assessed. These posts were most commonly promoted through Instagram (n = 561, 76.6%) with significantly more individual users (61.5%; p < 0.05) generating food and beverage related content (n = 198, 27%) than other post sources. The top most featured food category was fast food (n = 328, 44.8%) followed by dine-in restaurants (n = 126, 17.2%). The most frequently observed marketing techniques included predominantly featuring a child in the post (n = 124, 16.9%; p < 0.0001), followed by products intended for children (n = 118, 16.1%; p < 0.05), and the presence of family (n = 57, 7.8%; p < 0.0001). Conclusions The present study highlights the proliferation of unhealthy food and beverage content by individuals at a family-friendly event as well as the presence of food marketing. Due to the unfettered advertising found in digital spaces, and that they are largely unregulated, it is important for future policies looking to combat childhood obesity to consider incorporating social media into their regulations to safeguard family-friendly events. General awareness on the implications of peer to peer sharing of unhealthy food and beverage posts should also be considered.

The MID5 Dataset, 2011–2014: Procedures, coding rules, and description

This article introduces the latest iteration of the most widely used dataset on interstate conflicts, the Militarized Interstate Dispute (MID) 5 dataset. We begin by outlining the data collection process used in the MID5 project. Next, we discuss some of the most challenging cases that we coded and some updates to the coding manual that resulted. Finally, we provide descriptive statistics for the new years of the MID data.

Ketidaktepatan Kode Sebab Dasar Kematian menjadi Penyebab Kerugian 600 Juta Dana di Unit ICCU RSUD dr Moh Saleh Probolinggo

The coding of the diagnosis is important for patient care, hospital management and research. However, coding accuracy is a major problem in the diagnosis process and has impact on hospital income levels. This study is about the inaccuracy of the underlying cause of death coding toward the level of hospital income. The Methods employed is the Analysis of the accuracy of the diagnosis according to the mortality coding rules compiled in the Instruction Coding Manual of the World Health Organization (WHO). Afterwards, the percentage of losses is calculated using the system of INAcbg’s, in the Diagnosis Based on Indonesian Case system. The result shows that, out of 176 files were studied, 114 files or 65% of the diagnosis codes of the cause of death were incorrect, 57 files or 32% were correct and 5 files or 3% of files were not coded. Further, the study found out that 65% of these inaccuracies contributed to hospital losses which includes 40-75 % loss with the total loss received by the hospital as much as IDR 597,849,006 or nearly 600 million rupiah. The research concludes that the absence of a diagnosis of death increases hospital losses by more than 40% to 75%. Keywords: Accuracy, Code of Basic Cause of Death, ICD 10

Behavior Change Techniques Included in Reports of Social Media Interventions for Promoting Health Behaviors in Adults: Content Analysis Within a Systematic Review

Background Social media are an increasingly commonly used platform for delivering health promotion interventions. Although recent research has focused on the effectiveness of social media interventions for health promotion, very little is known about the optimal content within such interventions, and the active ingredients to promote health behavior change using social media are not clear. Identifying which behavior change techniques (BCTs) are reported may help to clarify the content of interventions using a generalizable terminology that may facilitate future intervention development. Objective This study aimed to identify which BCTs are reported in social media interventions for promoting health behavior change in adults. Methods We included 71 studies conducted with adult participants (aged ≥18 years) and for which social media intervention was considered interactive in a Cochrane review of the effectiveness of such interventions. We developed a coding manual informed by the Behavior Change Technique Taxonomy version 1 (BCTTv1) to identify BCTs in the included studies. We identified BCTs in all study arms (including control) and described BCTs in the group and self-directed components of studies. We characterized the dose of delivery for each BCT by low and high intensity. We used descriptive analyses to characterize the reported BCTs. Results Our data consisted of 71 studies published from 2001 to 2017, mainly conducted in high-income countries (n=65). Most studies (n=31) used tailored, interactive websites to deliver the intervention; Facebook was the most used mainstream platform. In developing our coding manual, we adapted some BCTTv1 instructions to better capture unique nuances of how BCTs were operationalized in social media with respect to likes, retweets, smiles, congratulations, and badges. Social support (unspecified), instruction on how to perform the behavior, and credible source were most frequently identified BCTs in intervention arms of studies and group-delivery settings, whereas instruction on how to perform the behavior was most commonly applied in self-directed components of studies, control arms, and individual participant settings. Instruction on how to perform the behavior was also the most frequently reported BCT in both intervention and control arms simultaneously. Instruction on how to perform the behavior, social support (unspecified), self-monitoring of behavior, information about health consequences, and credible source were identified in the top 5 BCTs delivered with the highest intensity. Conclusions This study within a review provides a detailed description of the BCTs and their dose to promote behavior change in web-based, interactive social media interventions. Clarifying active ingredients in social media interventions and the intensity of their delivery may help to develop future interventions that can more clearly build upon the existing evidence.

Measuring and interpreting cognitive representations of foods and drinks: A procedure for collecting and coding feature listing data

Feature listing is a novel method to study people’s rich, multifaceted cognitive representations of food and drink objects. In other words, it helps researchers understand the content activated in memory when people think about foods or drinks. Feature listing is an easy-to-administer method that has traditionally been used to study the semantic features of conceptual representation in cognitive science. We have recently adapted it for examining the representations of food and alcoholic and non-alcoholic drinks. Here, we describe a procedure for collecting feature listing data for food or drink objects, and for systematically coding the features produced by participants to enable quantitative analyses. First, we provide an overview of the feature listing method along with detailed instructions to participants. Then, we describe a systematic procedure for coding the wide variety of features that participants list in such tasks, using a total of 44 hierarchically-organised feature categories. We first present a general overview of the coding procedure followed by a systematic overview of the categories used, including categories of consumption situation features, non-consumption features, and situation-independent features. We then provide an extensive coding manual describing the categories and subcategories in detail, offering detailed criteria for coding a feature as belonging to a specific category along with examples and disambiguation procedures. This manual should allow researchers to systematically collect and code responses in feature listing tasks for foods and drinks, and increase the reproducibility of research findings involving feature listing.