An exploratory application of machine learning methods to optimize prediction of responsiveness to digital interventions for eating disorder symptoms
- Authors: Linardon, Jake , Fuller-Tyszkiewicz, Matthew , Shatte, Adrian , Greenwood, Christopher
- Date: 2022
- Type: Text , Journal article
- Relation: International Journal of Eating Disorders Vol. 55, no. 6 (2022), p. 845-850
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- Description: Objective: Digital interventions show promise to address eating disorder (ED) symptoms. However, response rates are variable, and the ability to predict responsiveness to digital interventions has been poor. We tested whether machine learning (ML) techniques can enhance outcome predictions from digital interventions for ED symptoms. Method: Data were aggregated from three RCTs (n = 826) of self-guided digital interventions for EDs. Predictive models were developed for four key outcomes: uptake, adherence, drop-out, and symptom-level change. Seven ML techniques for classification were tested and compared against the generalized linear model (GLM). Results: The seven ML methods used to predict outcomes from 36 baseline variables were poor for the three engagement outcomes (AUCs = 0.48–0.52), but adequate for symptom-level change (R2 =.15–.40). ML did not offer an added benefit to the GLM. Incorporating intervention usage pattern data improved ML prediction accuracy for drop-out (AUC = 0.75–0.93) and adherence (AUC = 0.92–0.99). Age, motivation, symptom severity, and anxiety emerged as influential outcome predictors. Conclusion: A limited set of routinely measured baseline variables was not sufficient to detect a performance benefit of ML over traditional approaches. The benefits of ML may emerge when numerous usage pattern variables are modeled, although this validation in larger datasets before stronger conclusions can be made. © 2022 The Authors. International Journal of Eating Disorders published by Wiley Periodicals LLC.
Critical measurement issues in the assessment of social media influence on body image
- Authors: Jarman, Hannah , McLean, Sian , Griffiths, Scott , Teague, Samantha , Rodgers, Rachel , Paxton, Susan , Austen, Emma , Harris, Emily , Steward, Trevor , Shatte, Adrian , Khanh-Dao Le, Long , Anwar, Tarique , Mihalopoulos, Cathrine , Parker, Alexandra , Yager, Zali , Fuller-Tyszkiewicz, Matthew
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Body Image Vol. 40, no. (2022), p. 225-236
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- Description: Progress towards understanding how social media impacts body image hinges on the use of appropriate measurement tools and methodologies. This review provides an overview of common (qualitative, self-report survey, lab-based experiments) and emerging (momentary assessment, computational) methodological approaches to the exploration of the impact of social media on body image. The potential of these methodologies is detailed, with examples illustrating current use as well as opportunities for expansion. A key theme from our review is that each methodology has provided insights for the body image research field, yet is insufficient in isolation to fully capture the nuance and complexity of social media experiences. Thus, in consideration of gaps in methodology, we emphasise the need for big picture thinking that leverages and combines the strengths of each of these methodologies to yield a more comprehensive, nuanced, and robust picture of the positive and negative impacts of social media. © 2022 Elsevier Ltd
Understanding the role of positive body image during digital interventions for eating disorders : secondary analyses of a randomized controlled trial
- Authors: Linardon, Jake , Tylka, Tracy , Burnette, C. , Shatte, Adrian , Fuller-Tyszkiewicz, Matthew
- Date: 2022
- Type: Text , Journal article
- Relation: Body Image Vol. 43, no. (2022), p. 1-7
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- Description: Despite growing interest in the possible link between positive body image and eating disorder (ED) symptoms, little is known about what role this adaptive construct plays in ED treatment. This study investigated whether: (1) interventions principally designed to target ED psychopathology also lead to improvements in positive body image indices (i.e., body appreciation, functionality appreciation, and body image flexibility); (2) changes in ED symptoms correlate with changes in positive body image, both concurrently and prospectively; and (3) baseline positive body image levels moderate the degree of symptom improvement. Secondary analyses from a randomized controlled trial on digital interventions for EDs (n=600) were conducted. Intervention participants reported greater increases in the three positive body image constructs than the control group (ds=0.15-0.41). Greater pre-post reductions in ED psychopathology and binge eating were associated with greater pre-post improvements in positive body image indices. However, earlier reductions in ED psychopathology and binge eating did not predict later improvements in positive body image at follow-up. None of the positive body image constructs at baseline moderated degree of symptom change. Standard ED interventions can cultivate a more positive body image, although this is not explained by earlier symptom reduction. Understanding the mechanisms through which ED interventions enhance positive body image is needed. © 2022 Elsevier Ltd
“You are not alone”: A big data and qualitative analysis of men's unintended fatherhood
- Authors: Smith, Imogene , Youssef, George , Shatte, Adrian , Teague, Samantha , Knight, Tess , Macdonald, Jacqui
- Date: 2022
- Type: Text , Journal article
- Relation: SSM. Qualitative research in health Vol. 2, no. (2022), p. 100085
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- Description: Becoming a father is a profound change in a man's life that is not always planned or wanted. Little is known about the subjective experiences of men who become fathers unintentionally or reluctantly. The aim of this research was to explore how men who did not intend to have children discuss their feelings about becoming a father in an online, anonymous environment. We sought insights into emotional responses, appraisals of family functioning, and relationships with infants. Data were collected from two Reddit forums for new and expectant fathers, r/Daddit and r/Predaddit. Approximately 2600 posts and 21,000 comments were extracted from the period between January 2019 and March 2020. We employed a two-stage methodology, blending big data techniques and qualitative analyses. Stage One included extraction and data preparation for topic modelling Stage Two was an adapted approach to thematic qualitative analysis. Topic modelling revealed 49 topics of which 6 were relevant thematically to unintended fatherhood. Men's communication in these were then classified within three domains: 1) Men's Concerns included their mental health, problems bonding with baby, their relationships with family and partner, and finances 2) Men's Affective Experiences existed on a spectrum of complex emotions including regret, resignation, ambivalence, acceptance, and excitement and 3) the Purpose of Communication included asking for and offering advice, normalisation, and perspective. Online forums like Reddit provide a unique opportunity for fathers who did not intend to have children to normalize their experience by expressing concerns and emotions in a pseudonymous environment. This study highlights the supportive environment that online discussions offer to fathers, and particularly unexpected fathers who may face stigma or barriers in other settings.