Christina Ralph-Nearman | University of Louisville (original) (raw)

Talks by Christina Ralph-Nearman

ICED2020 Body Image & Prevention SIG, 2020

International Conference on Eating Disorders (ICED2019), New York City, United States., 2019

Institute of Philosophy, School of Advanced Study UCL, Aegina Summer School 2017 “The Social Brai... more Institute of Philosophy, School of Advanced Study UCL, Aegina Summer School 2017 “The Social Brain: Embodiment and Culture”, Aegina, Greece

MBS/MFBS:
Christina Ralph-Nearman & Ruth Filik

Somatomap:
Christina Ralph-Nearman (Christina.Ralph-Nearman@Nottingham.ac.uk),
Armen Arevian, Sahib Khalsa, & Jamie Feusner

Institute of Philosophy, School of Advanced Study UCL, Aegina Summer School 2017 “The Social Bra... more Institute of Philosophy, School of Advanced Study UCL, Aegina Summer School 2017 “The Social Brain: Embodiment and Culture”, Aegina, Greece

International Conference on Eating Disorders 2017. Young Investigators Award for Interventions a... more International Conference on Eating Disorders 2017. Young Investigators Award for Interventions and Assessments SIG talk. Prague, Czech Republic.

Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, England.

ICED2016 San Francisco, California Conference

EPS London 2016 Conference

Conference Presentations by Christina Ralph-Nearman

International Conference on Eating Disorders 2020, virtual, 2020

Experimental Psychology Society London 2020, 2020

Cognitive factors underlying the development of disordered eating behavior are currently not well... more Cognitive factors underlying the development of disordered eating behavior are currently not well understood, but perfectionism may play a role. In the current study, preadolescents’ (aged 4-11, N=124) evaluations of body sizes and types of foods were measured, in relationship to their perfectionism, using a “good” or “bad” judgement game. During the task, children decided whether thin/obese body figures or healthy/unhealthy food pictures or words were “good” or “bad”, and to what extent. Results showed that positive attitudes toward thin bodies and ‘healthy’ foods, and negative evaluations of large bodies and ‘unhealthy’ foods were observed in children as young as 4-6 years old. In contrast, older children expressed negative attitudes towards thin bodies. Positive attitudes toward ‘healthy’ food dramatically increased in older compared to younger preadolescents, with over 97% of older children agreeing that high perfectionism-related materials (e.g., a gold medal) and healthy food-related materials (e.g., salad) were good, and large body-related materials were bad. Generalized perfectionism in children and body-specific perfectionism in mothers (as determined by questionnaires) were associated with children’s body- and food-related attitudes. In conclusion, relationships between perfectionism and body- and food-related attitudes may manifest as young as 4-6 years old, and are related to mothers’ perfectionism.

Eating Disorder Research Society (EDRS2019), Chicago, United States., 2019

Introduction: Body image is a subjective construct usually assessed via questionnaire and current... more Introduction:
Body image is a subjective construct usually assessed via questionnaire and currently lacking objective behavioral markers. We created Somatomap 2D, a novel assessment using a visual mapping interface to capture body image concerns. This study examined the feasibility of Somatomap 2D to measure body image disturbance in anorexia nervosa (AN).

Methods:
AN inpatients (n=25) and non-clinical comparisons (NC; n=25) sequentially outlined individual body concerns on an avatar and rated the associated concern intensity and affective valence. Regional differences in body image disturbance were evaluated via statistical body maps using proportional z-scores.

Results:
A higher proportion in the AN group had concerns about the chest, lower abdomen, and legs (p<.05). AN exhibited greater body concerns, higher concern intensities, and more negative emotional valence compared to NC (p<.001). The number of body concerns explained a large proportion of the variability in eating disorder severity (EDE-Q), controlling for age and BMI (R2=.30, p=.009, 95% CI [0.07, 0.43]).

Conclusions:
Somatomap 2D demonstrated feasibility in identifying body image disturbances in inpatients with AN, showing regional differences in body concerns. Moreover, the number of concerns predicted eating disorder severity, suggesting that it might serve as an objective behavioral marker for AN. We are currently examining the utility of this measure in longitudinally tracking recovery following treatment.

Experimental Psychology Society, EPS2019LONDON, University College London, London, England., 2019

Eating disorder prevalence rates are increasing in males, perhaps more rapidly than in females. C... more Eating disorder prevalence rates are increasing in males, perhaps more rapidly than in females. Current theories debate whether it is the way in which body-, food-, or perfectionism-related information is processed that is primarily associated with eating disorder symptomatology. In two experiments, males had their eye movements monitored while they read body-, food-, or perfectionism-related texts, which ended with a sentence containing a critical emotion-based word that either ‘matched’ or ‘mismatched’ one’s expectations concerning how the character might react. Participants read scenarios that were written from either a third-person perspective (Experiment 1, N = 90), or a second-person perspective (Experiment 2, N = 90). Following the reading task, participants completed the Eating Disorder Examination Questionnaire (EDE-Q 6.0) and their body mass index (BMI) was calculated. EDE-Q 6.0 scores were associated with the size of the mismatch effect (reading times for mismatch minus match conditions) for body- and perfectionism-related materials for third-person scenarios. BMI was associated with the size of the mismatch effect for perfectionism-related materials for third-person scenarios, and with the size of the mismatch effect for body-related materials for second-person scenarios. Results support theories proposing that body and perfectionism-related cognitive mechanisms may be key contributors to eating disorder symptomatology.

Technology in Psychiatry Summit (TIPS), Harvard Medical School, Boston, United States., 2018

Introduction: Disturbances in self-perceptions are key features of mood, anxiety and eating disor... more Introduction:
Disturbances in self-perceptions are key features of mood, anxiety and eating disorders, with prognostic and therapeutic relevance, but they are difficult to measure. To better assess these self-perceptions, we developed Somatomap, a cross-platform mobile application which facilitates the assessment of appearance-based visual perceptual and interoceptive experiences, as well as related cognitive, affective, and behavioral symptoms using a graphical interface involving two-dimensional (2D) and three-dimensional (3D) avatars.

Method:
To examine the initial utility of this technology, we collected emotion- and appearance-based concerns (2D) and body-size perception (3D) data in a convenience sample of working female fashion models (n=65, age=23.4+/-5.5yrs) and non-model reference females (n=38, age=25.4+/-5.2yrs), using objective body measurements as perceptual anchors.

Results:
We observed significant relationships between objectively measured and subjectively perceived body parts including bust (r’s≥.3, ps≤.017, models and non-models), and biceps (r = .4, p = .001, models only), but not shoulders, waist, hips, thighs, or calves (Somatomap 3D). Also, models were disproportionately concerned with their thighs compared to non-models, χ2(df=1)=10.56, p=0.001, whereas non-models were disproportionately concerned with their abdomen χ2(df=1)=4.13, p=0.042 (Somatomap 2D). However, both groups reported similar intensities of emotional concern for both regions (ps≥.6), suggesting that spatial topography rather than emotional concern differentiated the groups.

Conclusion:
Our initial results suggest that Somatomap identifies distinct perceptual aspects of body image related to physical proportions as well as affective and appearance-based concerns. Current applications of this tool are focused on assessment and prediction of body-related perceptual distortions in eating and other psychiatric disorders.

APA’s 126th Annual Conference, San Francisco, California, United States., 2018

Body-related disturbances are key features of many psychiatric illnesses, with prognostic and the... more Body-related disturbances are key features of many psychiatric illnesses, with prognostic and therapeutic relevance. Reliance upon word-based self-report provides limited, verbal clinical evaluation of patients’ body-related experiences. To address this gap, we created Somatomap, a mobile tool that graphically assesses affective, interoceptive, and appearance based concerns across smartphone, tablet, and computer platforms. A visually based entry allows individuals to indicate areas of body concern by drawing on a two-dimensional (2D) manikin, and specifying the concern type, intensity, as well as associated moods, feelings, compulsions, behaviors, and perceptions surrounding isolated areas. A report interface provides real-time snapshots of topographical distributions (‘Somatomaps’), allowing graphical exploration of body concern characteristics and their interaction with affective, behavioral, and cognitive symptom intensity over time. We have acquired 2D cohort data, which reveal distinctive body-related concern patterns. Additionally, we developed three-dimensional (3D) avatars, allowing individuals to manipulate individual body parts. This provides clinically-relevant, quantitative assessments of body-related perceptual distortions. Avatars were reported to be easy to use (M=8.47 of 10), and to closely resemble individuals’ actual body (>70%). Somatomap 2D and 3D may be used together or individually to explore novel, objective, and clinically-relevant measures of body-related perceptual distortions across psychiatric disorders.

13th International Conference for Cognitive Neuroscience, 2017

19th European Conference on Eye Movements Bergische Universität, Wuppertal, Germany

13th International Conference for Cognitive Neuroscience (ICON2017). Amsterdam, Netherlands. Wie... more 13th International Conference for Cognitive Neuroscience (ICON2017). Amsterdam, Netherlands.

Wiebking, C., Ralph-Nearman, C., Herbert, C.

International Conference on Eating Disorders, ICED 2017, Prague Congress Centre, Prague, Czech Re... more International Conference on Eating Disorders, ICED 2017, Prague Congress Centre, Prague, Czech Republic.

Experimental Psychology Society, EPS2017LONDON, University of Central London, London, England.

ICED2020 Body Image & Prevention SIG, 2020

International Conference on Eating Disorders (ICED2019), New York City, United States., 2019

MBS/MFBS:
Christina Ralph-Nearman & Ruth Filik

Somatomap:
Christina Ralph-Nearman (Christina.Ralph-Nearman@Nottingham.ac.uk),
Armen Arevian, Sahib Khalsa, & Jamie Feusner

Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, England.

ICED2016 San Francisco, California Conference

EPS London 2016 Conference

International Conference on Eating Disorders 2020, virtual, 2020

Experimental Psychology Society London 2020, 2020

Eating Disorder Research Society (EDRS2019), Chicago, United States., 2019

Experimental Psychology Society, EPS2019LONDON, University College London, London, England., 2019

Technology in Psychiatry Summit (TIPS), Harvard Medical School, Boston, United States., 2018

APA’s 126th Annual Conference, San Francisco, California, United States., 2018

13th International Conference for Cognitive Neuroscience, 2017

19th European Conference on Eye Movements Bergische Universität, Wuppertal, Germany

13th International Conference for Cognitive Neuroscience (ICON2017). Amsterdam, Netherlands. Wie... more 13th International Conference for Cognitive Neuroscience (ICON2017). Amsterdam, Netherlands.

Wiebking, C., Ralph-Nearman, C., Herbert, C.

Experimental Psychology Society, EPS2017LONDON, University of Central London, London, England.

2016 Figurative Language Workshop, University of Nottingham, Nottingham, England.

The International journal of eating disorders/International journal of eating disorders, Feb 14, 2024

Objective: Body mass index (BMI) is the primary criterion differentiating anorexia nervosa (AN) a... more Objective: Body mass index (BMI) is the primary criterion differentiating anorexia nervosa (AN) and atypical anorexia nervosa despite prior literature indicating few differences between disorders. Machine learning (ML) classification provides us an efficient means of accurately distinguishing between two meaningful classes given any number of features. The aim of the present study was to determine if ML algorithms can accurately distinguish AN and atypical AN given an ensemble of features excluding BMI, and if not, if the inclusion of BMI enables ML to accurately classify between the two. Methods: Using an aggregate sample from seven studies consisting of individuals with AN and atypical AN who completed baseline questionnaires (N = 448), we used logistic regression, decision tree, and random forest ML classification models each trained on two datasets, one containing demographic, eating disorder, and comorbid features without BMI, and one retaining all features and BMI. Results: Model performance for all algorithms trained with BMI as a feature was deemed acceptable (mean accuracy = 74.98%, mean area under the receiving operating characteristics curve [AUC] = 74.75%), whereas model performance diminished without BMI (mean accuracy = 59.37%, mean AUC = 59.98%). Discussion: Model performance was acceptable, but not strong, if BMI was included as a feature; no other features meaningfully improved classification. When BMI was excluded, ML algorithms performed poorly at classifying cases of AN and atypical AN when considering other demographic and clinical characteristics. Results suggest a reconceptualization of atypical AN should be considered.

Appetite, Dec 31, 2023

Feeling fat and fear of weight gain are key cognitive-affective symptoms that are theorized to ma... more Feeling fat and fear of weight gain are key cognitive-affective symptoms that are theorized to maintain eating disorders (EDs). Little research has examined the dynamic relationships among feeling fat, fear of weight gain, emotions, cognitions, and ED behaviors. Furthermore, it is unknown if these relations vary by ED diagnosis (e.g., anorexia nervosa (AN) vs other ED). The current study (N = 94 ED participants; AN n = 64) utilized ecological momentary assessments collected four times a day for 18 days (72 timepoints) asking about feeling fat, fear of weight gain, emotions (i.e., anxiety, guilt), cognitions (i.e., feelings of having overeaten, thoughts about dieting), and ED behaviors (i.e., vomiting, diuretic/laxative use, excessive exercise, body checking, self-weighing, binge-eating, restriction) at stressful timepoints (contemporaneous [mealtime], and prospective/temporal [next-meal]). Multilevel modeling was used to test for between and within-person associations. Higher feeling fat and fear of weight gain independently predicted higher next-meal emotions (i.e., anxiety, guilt), cognitions (i.e., feelings of having overeaten, thoughts about dieting, fear of weight gain, feeling fat), and ED behaviors (i.e., body checking, self-weighing [feeling fat]). There were relationships in the opposite direction, such that some emotions, cognitions, and ED behaviors prospectively predicted feeling fat and fear of weight gain, suggesting existence of a reciprocal cycle. Some differences were found via diagnosis. Findings pinpoint specific dynamic and cyclical relationships among feeling fat, fear of weight gain, and specific ED symptoms, and suggest the need for more research on how feeling fat, fear of weight gain and cognitive-affective-behavioral aspects of ED operate. Future research can test if treatment interventions targeted at feeling fat and fear of weight gain may disrupt these cycles.

Assessment

Eating disorders are severe and often chronic mental illnesses that are associated with high impa... more Eating disorders are severe and often chronic mental illnesses that are associated with high impairment and mortality rates. Recent estimates suggest that eating disorder prevalence rates are on the rise, indicating an increased need for accurate assessment and detection. The current review provides an overview of transdiagnostic eating disorder assessments, including interview, self-report, health and primary care screeners, and technology-based and objective assessments. We focused on assessments that are transdiagnostic in nature and exhibit high impact in the field. We provide recommendations for how these assessments should be used in research and clinical settings. We also discuss considerations that are crucial for assessment, including the use of a categorical versus dimensional diagnostic framework, assessment of eating disorders in related fields (i.e., anxiety and depression), and measurement-based care for eating disorders. Finally, we provide suggestions for future rese...

Psychological Medicine

Background Eating disorders (ED) are serious psychiatric disorders, taking a life every 52 minute... more Background Eating disorders (ED) are serious psychiatric disorders, taking a life every 52 minutes, with high relapse. There are currently no support or effective intervention therapeutics for individuals with an ED in their everyday life. The aim of this study is to build idiographic machine learning (ML) models to evaluate the performance of physiological recordings to detect individual ED behaviors in naturalistic settings. Methods From an ongoing study (Final N = 120), we piloted the ability for ML to detect an individual's ED behavioral episodes (e.g. purging) from physiological data in six individuals diagnosed with an ED, all of whom endorsed purging. Participants wore an ambulatory monitor for 30 days and tapped a button to denote ED behavioral episodes. We built idiographic (N = 1) logistic regression classifiers (LRC) ML trained models to identify onset of episodes (~600 windows) v. baseline (~571 windows) physiology (Heart Rate, Electrodermal Activity, and Temperature...

International Journal of Eating Disorders , 2024

Appetite, 2024

New Ideas in Psychology, 2024

Assessment, 2023

Psychological Medicine, 2023

medRxiv (Cold Spring Harbor Laboratory), Jun 20, 2023

Journal of Consulting and Clinical Psychology, 2023

Eating disorders are serious psychiatric illnesses with treatments ineffective for about 50% of i... more Eating disorders are serious psychiatric illnesses with treatments ineffective for about 50% of individuals due to 1) high heterogeneity of symptom presentation even within the same diagnoses, 2) a lack of personalized treatments to address this heterogeneity, and 3) the fact that clinicians are left to rely upon their own judgment to decide how to personalize treatment. Idiographic (personalized) networks can be estimated from ecological momentary assessment data, and have been used to investigate central symptoms, which are theorized to be fruitful treatment targets. However, both efficacy of treatment target selection and implementation with ‘real world’ clinicians could be maximized if clinician input is integrated into such networks. An emerging line of research is therefore proposing to integrate case conceptualizations and statistical routines, tying together the benefits from clinical expertise as well as patient experience and idiographic networks. The current pilot compare...

New Ideas in Psychology, 2022

Supplemental material, supplement_material for Disturbed Eating and Body Dysmorphic Symptoms in a... more Supplemental material, supplement_material for Disturbed Eating and Body Dysmorphic Symptoms in a Young Adult Sample Are Separable Constructs That Each Show a Mixture of Distributions by Majed Samad, Christina Ralph-Nearman, Gerhard Hellemann, Sahib S. Khalsa, Ladan Shams and Jamie D. Feusner in Assessment

Journal of Abnormal Psychology, 2021

Many cognitive theories point to key factors underlying the development and maintenance of eating... more Many cognitive theories point to key factors underlying the development and maintenance of eating disorders, such as: unhealthy food-related cognitive biases, negative body attitude, and perfectionism. The present research utilised eye-tracking during reading as a novel implicit measure of how these factors may relate to eating disorder tendencies in females and males, followed by the development of two new male body dissatisfaction scales. In four experiments female and male (N = 360) participants’ eye movements were monitored while they read third- and second-person perspective texts in which the characters’ emotional responses to food-, body image-, and perfectionism-related scenarios were described. Overall, results from these studies suggest that on-line processing of characters’ emotional responses to perfectionism-, and to a lesser extent, body image-related information is predictive of participants’ disordered eating tendencies, thus supporting theories in which these two un...