Abdominal circumference growth velocity as a predictor of adverse perinatal outcomes in small-for-gestational-age fetuses.

OBJECTIVE: To assess the predictive value of abdominal circumference growth velocity (ACGV) between the second and third trimesters to predict adverse perinatal outcomes in a cohort of small-for-gestational-age fetuses without evidence of placental insufficiency (i.e. fetal growth restriction). MATERIAL AND METHODS: This is a single-center retrospective cohort study of all singleton pregnancies with small-for-gestational-age fetuses diagnosed and delivered at a quaternary institution. Crude and adjusted odds ratios (ORs) and corresponding confidence intervals (CIs) were calculated via logistic regression models to assess the potential association between abnormal ACGV (i.e. ≤10th centile) and adverse perinatal outcomes defined as a composite outcome (i.e. umbilical artery pH <7.1, 5-min Apgar score <7, admission to the neonatal intensive care unit, hypoglycemia, intrapartum fetal distress requiring expedited delivery, and perinatal death). Furthermore, the area under the receiver-operating characteristic curve (AUC) of three logistic regression models based on estimated fetal weight and ACGV for predicting the composite outcome is also reported. RESULTS: A total of 154 pregnancies were included for analysis. The median birthweight for the cohort was 2,437 g (interquartile range [IQR] 2280, 2635). Overall, the primary composite outcome was relatively common (29.2%). In addition, there was a significant association between abnormal ACGV and adverse perinatal outcomes (OR 3.37, 95% CI 1.60, 7.13; adjusted OR 4.30, 95% CI 1.77, 10.49). Likewise, the AUC for the ACGV was marginally higher (0.64) than the estimated fetal weight (0.54) and ACGV + estimated fetal weight (0.54). Still, no significant difference was detected between the curves (p = 0.297). CONCLUSIONS: Our results suggest that an ACGV below the 10th centile is a risk factor for adverse perinatal outcomes among small-for-gestational-age fetuses.

Geospatial vaccine misinformation risk on social media: Online insights from an English/Spanish natural language processing (NLP) analysis of vaccine-related tweets.

BACKGROUND: Misinformation is known to affect norms, attitudes, and intentions to engage with healthy behaviors. Evidence strongly supports that Spanish speakers may be particularly affected by misinformation and its outcomes, yet current insights into the scope and scale of misinformation is primarily ethnocentric, with greater emphasis on English-language design. OBJECTIVE: This study applies Natural Language Processing (NLP) to analyze a corpus of English/Spanish tweets about vaccines, broadly defined, for misinformation indicators. METHODS: We analyzed NEnglish = 247,140 and NSpanish = 104,445 tweets using Latent Dirichlet Allocation (LDA) topic models with Coherence score calculation (model fit) with a Mallet adjustment (topic optimization). We used informal coding to name computer-identified topics and compare misinformation scope and scale between languages. RESULTS: The LDA analysis yielded a 12-topic solution for English and a 14-topic solution for Spanish. Both corpora contained overlapping misinformation, including uncertainty of research guiding policy recommendations or standing in support of antivax movements. However, the Spanish data were positioned in a global context, where misinformation was directed at government equity and disparate vaccine distribution. CONCLUSION: Our findings support that misinformation is a global issue. However, misinformation may vary depending on culture and language. As such, tailored strategies to combat misinformation in digital planes are strongly encouraged.

Identifying accurate pro-choice and pro-life identity labels in Spanish: Social media insights and implications for comparative survey research.

INTRODUCTION: Although debate remains about the saliency and relevance of pro-choice and pro-life labels (as abortion belief indicators), they have been consistently used for decades to broadly designate abortion identity. However, clear labels are less apparent in other languages (e.g., Spanish). Social media, as an exploratory data science tool, can be leveraged to identify the presence and popularity of online abortion identity labels and how they are contextualized online. PURPOSE: This study aims to determine how popularly used Spanish-language pro-choice and pro-life identity labels are contextualized online. METHOD: We used Latent Dirichlet Allocation (LDA) topic models, an unsupervised natural language processing (NLP) application, to generate themes about Spanish language tweets categorized by Spanish abortion identity labels: (1) proelección (pro-choice); (2) derecho a decidir (right to choose); (3) proaborto (pro-abortion); (4) provida (pro-life); (5) antiaborto (anti-abortion); and (6) derecho a vivir (right to life). We manually reviewed themes for each identity label to assess scope. RESULTS: All six identity labels included in our analysis contained some references to abortion. However, several labels were not exclusive to abortion. Proelección (pro-choice), for example, contained several themes related to ongoing presidential elections. DISCUSSION AND CONCLUSION: No singular Spanish abortion identity label encapsulates abortion beliefs; however, there are several viable options. Just as the debate remains ongoing about pro-choice and pro-life as accurate indicators of abortion beliefs in English, we must also consider that identity is more complex than binary labels in Spanish.

Assessing rigid modes of thinking in self-declared abortion ideology: natural language processing insights from an online pilot qualitative study on abortion attitudes.

INTRODUCTION: Although much work has been done on US abortion ideology, less is known relative to the psychological processes that distinguish personal abortion beliefs or how those beliefs are communicated to others. As part of a forthcoming probability-based sampling designed study on US abortion climate, we piloted a study with a controlled sample to determine whether psychological indicators guiding abortion beliefs can be meaningfully extracted from qualitative interviews using natural language processing (NLP) substring matching. Of particular interest to this study is the presence of cognitive distortions-markers of rigid thinking-spoken during interviews and how cognitive distortion frequency may be tied to rigid, or firm, abortion beliefs. METHODS: We ran qualitative interview transcripts against two lexicons. The first lexicon, the cognitive distortion schemata (CDS), was applied to identify cognitive distortion n-grams (a series of words) embedded within the qualitative interviews. The second lexicon, the Linguistic Inquiry Word Count (LIWC), was applied to extract other psychological indicators, including the degrees of (1) analytic thinking, (2) emotional reasoning, (3) authenticity, and (4) clout. RESULTS: People with polarized abortion views (i.e., strongly supportive of or opposed to abortion) had the highest observed usage of CDS n-grams, scored highest on authenticity, and lowest on analytic thinking. By contrast, people with moderate or uncertain abortion views (i.e., people holding more complex or nuanced views of abortion) spoke with the least CDS n-grams and scored slightly higher on analytic thinking. DISCUSSION AND CONCLUSION: Our findings suggest people communicate about abortion differently depending on their personal abortion ideology. Those with strong abortion views may be more likely to communicate with authoritative words and patterns of words indicative of cognitive distortions-or limited complexity in belief systems. Those with moderate views are more likely to speak in conflicting terms and patterns of words that are flexible and open to change-or high complexity in belief systems. These findings suggest it is possible to extract psychological indicators with NLP from qualitative interviews about abortion. Findings from this study will help refine our protocol ahead of full-study launch.

Translation frameworks and questionnaire design approaches as a component of health research and practice: A discussion and taxonomy of popular translation frameworks and questionnaire design approaches.

Multilanguage surveys are a vital component of comparative public health science. And, with dozens of tools available to guide the translation and design process, an open dialogue about key translation frameworks and design approaches and their strengths and limitations is needed. Herein, we briefly summarize the application and use of several popular translation frameworks and questionnaire design approaches. Our purpose is to draw attention to the complexities of multilanguage surveys by noting how the most appropriate framework or approach is entirely dependent on the context of a specific study. We conclude with a call encouraging the adoption of frameworks and approaches that value high degrees of cultural input, ideally among a large team of culture, language, and subject matter experts. And, as the implemented translation framework or questionnaire design approach may hold implications for the quality and validity of data, we also call on editors to create recommendations that encourage disclosure of the translation framework(s) and/or questionnaire design approaches guiding multilanguage surveys.