Emily Kahumoku-Fessler

Bio: Emily Kahumoku-Fessler is an academic researcher from University of Houston–Clear Lake. The author has contributed to research in topics: Autism & Coping (psychology). The author has an hindex of 3, co-authored 6 publications receiving 29 citations.

Microaggressions and Islamophobia: Experiences of Muslims Across the United States and Clinical Implications.

Abstract: This mixed methods exploratory study illustrates the influence of pervasive misconceptions about Islam on the experiences of 314 adult Muslims across the United States. Quantitative results suggest that Muslim stress levels are comparable to the stress levels of other marginalized groups in the United States. Qualitative analysis revealed four themes that highlight the challenges faced by Muslims as well as their resiliency in the face of microaggressions and marginalization. Family therapists may utilize these personal accounts to expand their understanding of Muslim experiences, and to reflect on their own implicit biases toward Muslims in order to reduce chances of premature termination. Clinical implications include using resiliency-based models and creating collaborative partnerships with community leaders when working with this religious minority group.

Understanding Infidelity: How Perceptions of Infidelity Behaviors Vary by Sex and One's Own Infidelity Experiences

Abstract: This study examines (1) how previous history with infidelity influences perceptions of cheating behaviors, and (2) sex's impact on ratings of cheating behaviors. A total of 83 undergraduate students enrolled in psychology courses volunteered to participate through an anonymous online survey. Participants rated sexual and emotional behaviors on a scale that ranged from “always” to “never,” indicating if the behavior was perceived as cheating. Individuals that had previous experience with infidelity either as the involved or non-involved partner rated sexual behaviors higher than those with no experience with infidelity, while non-involved partners rated emotional behaviors higher than the rest. Overall, females rated sexual and emotional behaviors higher than males. Non-involved males rated sexual behaviors higher than non-involved female partners. However, males who have not committed an infidelity rated sexual behaviors lower than any other group. The results provide further evidence that percept...

A Summative Content Analysis of Stress and Coping among Parents of Children with Autism

Abstract: Sixty-nine married couples who had a child with autism spectrum disorder (ASD) described their experiences in an online survey. Using Grounded theory thematic analysis and summative content analysi...

Links Between Parenting and Internalizing and Externalizing Problems: Cross-Cultural Evidence from Ten Countries

Abstract: The present study tested the links between perceived maternal and paternal parenting and internalizing and externalizing problems across ten cultures (China, Czech Republic, Hungary, the Netherlands, Slovenia, Spain, Switzerland, Taiwan, Turkey, and the United States). Self-report data were collected from N = 12,757 adolescents (Mage = 17.13 years, 48.4% female). Multigroup confirmatory factor analyses and structural equation models tested whether: (1) the six parenting processes (closeness, support, monitoring, communication, peer approval, and conflict; Adolescent Family Process, Short Form (AFP-SF, 18 items) varied across cultures, and (2) the links between parenting processes and measures of internalizing and externalizing problems varied across cultures. Study findings indicated measurement invariance (configural and metric) of both maternal and paternal parenting processes and that the parenting—internalizing/externalizing problems links did not vary across cultures. Findings underscore the ubiquitous importance of parenting processes for internalizing and externalizing problems across diverse Asian, European, Eurasian, and North American cultures.

Detecting weak and strong Islamophobic hate speech on social media

Abstract: Islamophobic hate speech on social media is a growing concern in contemporary Western politics and society. It can inflict considerable harm on any victims who are targeted, create a sense of fear ...

Developing a Measure of the Impact of COVID-19 Social Distancing on Household Conflict and Cohesion.

Abstract: This report introduces the COVID-19 Family Environment Scale (CHES), which aims to measure the impact of social distancing due to COVID-19 on household conflict and cohesion Existing measures do not capture household experiences relevant to the pandemic, in which families are largely confined to their homes while sharing a life-threatening situation Using best practice guidelines, we developed a pool of items and revised them with review by a panel of experts, and cognitive interviewing with community respondents We administered the CHES by online survey to 3,965 adults The CHES consists of 15 items for each of two subscales, household conflict (α = 847) and household cohesion (α = 887) Exploratory factor analysis yielded two factors, corresponding to the intended conflict and cohesion items, which accounted for 29% of variance Confirmatory factor analysis partially supported the 2-factor model (RMSEA = 057; CFI = 729, TLI = 708, and SRMR = 098) The CHES also contains 25 optional items to describe respondent and household characteristics, and household-level COVID-19 exposure The CHES, publicly available at https://elcentrosonhsmiamiedu/research/measures-library/covid-19/indexhtml, provides a tool for measuring the impact of the COVID-19 pandemic on important determinants of resilience in the face of major stressful events Further work is needed to address the factor structure and establish validity of the CHES

Detecting weak and strong Islamophobic hate speech on social media.

Abstract: Islamophobic hate speech on social media inflicts considerable harm on both targeted individuals and wider society, and also risks reputational damage for the host platforms. Accordingly, there is a pressing need for robust tools to detect and classify Islamophobic hate speech at scale. Previous research has largely approached the detection of Islamophobic hate speech on social media as a binary task. However, the varied nature of Islamophobia means that this is often inappropriate for both theoretically-informed social science and effectively monitoring social media. Drawing on in-depth conceptual work we build a multi-class classifier which distinguishes between non-Islamophobic, weak Islamophobic and strong Islamophobic content. Accuracy is 77.6% and balanced accuracy is 83%. We apply the classifier to a dataset of 109,488 tweets produced by far right Twitter accounts during 2017. Whilst most tweets are not Islamophobic, weak Islamophobia is considerably more prevalent (36,963 tweets) than strong (14,895 tweets). Our main input feature is a gloVe word embeddings model trained on a newly collected corpus of 140 million tweets. It outperforms a generic word embeddings model by 5.9 percentage points, demonstrating the importan4ce of context. Unexpectedly, we also find that a one-against-one multi class SVM outperforms a deep learning algorithm.

"Yes We Can!" The Mental Health Significance for U.S. Black Adults of Barack Obama's 2008 Presidential Election.

Abstract: This study examines the mental health significance of Barack Obama’s 2008 presidential election for black adults. His election was a milestone moment. Hence, we expect black adults would experience...