8 research outputs found
Pursuing clarity of purpose and generalizable research practices for mental health apps and recommendations
No full textMental health issues are a diverse and widespread problem. Whilst effective treatments and solutions exist, numerous obstacles make it difficult to deliver them to the people who need them. One promising way to lower access barriers is through mental health apps, a ubiquitous, often inexpensive solution. Furthermore, through the existence of recommender systems, delivery of content within the app can be personalized, allowing for the personal tailoring of a widely available resource. Yet whilst there have been some promising results in the field regarding their efficacy, commercial deployment is outpacing the supporting science. Many apps are untested, there are very few unifying methodological frameworks in place and a shallow understanding of mechanisms of change. The research that does exist is comprised mostly of exploration and testing of novel algorithms or solutions leading to little coherence between studies and generalizability of findings is largely unknown. Whilst, to some extent, this is to be expected in early-stage research, it would be far more beneficial in the long run to pursue foundational improvements now rather than later.
This thesis aims to address these issues, to shore up the foundations of research into mental health apps and recommender systems, to identify generalizable practices and pursue a deeper understanding of how we can enable positive mental health change. The current work focuses on establishing the link between engagement and mental health outcomes, as research in the field has a tendency to make assumptions regarding the beneficial effects of increased engagement. Through a systematic review of recommender systems in the mental health context and three studies, we evaluate how recommendations can be tailored towards both outcomes, how we can increase congruence in research by clear, goal-oriented definition of variables, and whether academic research translates to real world effects. The current work investigates the influence of financial incentivization on engagement and mental health outcomes, analyzes a commercial dataset gathered over several years and explores the relationship between different character traits, behaviors, facets of engagement and short-term and long-term mental health outcomes across a number of domains. In the final chapter the disparate threads will be brought together, presenting broadly applicable recommendations for how researchers can structure individual research to generate more cohesive value in the field as a whole, and suggest how future research may continue to pursue a stronger foundational understanding of mental health change
Generalizability Theory Dissertation
No full textA dissertation project using secondary data analysis to explore the applications of Generalizability Theory within the field of anxiety. Will include pre-registration and coding done through Rstudi
Generalizability Theory Dissertation
No full textA dissertation project using secondary data analysis to explore the applications of Generalizability Theory within the field of anxiety. Will include pre-registration and coding done through Rstudi
Generalizability Theory Dissertation
No full textA dissertation project using secondary data analysis to explore the applications of Generalizability Theory within the field of anxiety. Will include pre-registration and coding done through Rstudi
Assessing COVID-19 distress and eustress across multiple time points using the Situated Assessment Method (SAM2) – Full study
No full textIn the summer of 2020, we piloted the study preregistered here with 40 participants. Because the pilot constituted exploratory work, it was not preregistered. The current study is a much better powered version of the same study that attempts to replicate and verify its results with 300 participants (funded by the University of Glasgow Exchange Fund). In this file here, we formalise hypotheses and analyses for a preregistration of the full study
Using Polarized Spectroscopy to Investigate Order in Thin-Films of Ionic Self-Assembled Materials Based on Azo-Dyes
No full textThree series of ionic self-assembled materials based on anionic azo-dyes and cationic benzalkonium surfactants were synthesized and thin films were prepared by spin-casting. These thin films appear isotropic when investigated with polarized optical microscopy, although they are highly anisotropic. Here, three series of homologous materials were studied to rationalize this observation. Investigating thin films of ordered molecular materials relies to a large extent on advanced experimental methods and large research infrastructure. A statement that in particular is true for thin films with nanoscopic order, where X-ray reflectometry, X-ray and neutron scattering, electron microscopy and atom force microscopy (AFM) has to be used to elucidate film morphology and the underlying molecular structure. Here, the thin films were investigated using AFM, optical microscopy and polarized absorption spectroscopy. It was shown that by using numerical method for treating the polarized absorption spectroscopy data, the molecular structure can be elucidated. Further, it was shown that polarized optical spectroscopy is a general tool that allows determination of the molecular order in thin films. Finally, it was found that full control of thermal history and rigorous control of the ionic self-assembly conditions are required to reproducibly make these materials of high nanoscopic order. Similarly, the conditions for spin-casting are shown to be determining for the overall thin film morphology, while molecular order is maintained
