16 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
Early goal-directed nutrition in ICU patients (EAT-ICU): protocol for a randomised trial
No full textINTRODUCTION: Extensive weight loss has been documented in intensive care unit (ICU) survivors, primarily as the result of muscle loss, leading to impaired physical function and reduced quality of life. The aim of the EAT-ICU trial is to test the effect of early goal-directed protein-energy nutrition based on measured requirements on short-term clinical outcomes and long-term physical quality of life in ICU patients. METHODS: The EAT-ICU trial is a single-centre, randomised, parallel-group trial with concealed allocation and blinded outcome assessment. A total of 200 consecutive, acutely admitted, mechanically ventilated intensive care patients will be randomised 1: 1 to early goal-directed nutrition versus standard of care to show a potential 15% relative risk reduction in the primary outcome measure (physical function) at six months (two-sided significance level alpha = 0.05; power beta = 80%). Secondary outcomes include energy-and protein balances, metabolic control, new organ failure, use of life support, nosocomial infections, ICU- and hospital length of stay, mortality and cost analyses. CONCLUSION : The optimal nutrition strategy for ICU patients remains unsettled. The EAT-ICU trial will provide important data on the effects of early goal-directed proteinenergy nutrition based on measured requirements in these patients.Copenhagen University Hospital; Rigshospitalet; Fresenius Kabi A/S; European Society for Clinical Nutrition and Metabolism (ESPEN)SCI(E)[email protected]
Early goal-directed nutrition versus standard of care in adult intensive care patients: the single-centre, randomised, outcome assessor-blinded EAT-ICU trial
No full textPurpose: We assessed the effects of early goal-directed nutrition (EGDN) vs. standard nutritional care in adult intensive care unit (ICU) patients. Methods: We randomised acutely admitted, mechanically ventilated ICU patients expected to stay longer than 3 days in the ICU. In the EGDN group we estimated nutritional requirements by indirect calorimetry and 24-h urinary urea aiming at covering 100% of requirements from the first full trial day using enteral and parenteral nutrition. In the standard of care group we aimed at providing 25 kcal/kg/day by enteral nutrition. If this was not met by day 7, patients were supplemented with parenteral nutrition. The primary outcome was physical component summary (PCS) score of SF-36 at 6 months. We performed multiple imputation for data of the non-responders. Results: We randomised 203 patients and included 199 in the intention-to-treat analyses; baseline variables were reasonably balanced between the two groups. The EGDN group had less negative energy (p < 0.001) and protein (p < 0.001) balances in the ICU as compared to the standard of care group. The PCS score at 6 months did not differ between the two groups (mean difference 0.0, 95% CI -5.9 to 5.8, p = 0.99); neither did mortality, rates of organ failures, serious adverse reactions or infections in the ICU, length of ICU or hospital stay, or days alive without life support at 90 days. Conclusions: EGDN did not appear to affect physical quality of life at 6 months or other important outcomes as compared to standard nutrition care in acutely admitted, mechanically ventilated, adult ICU patients.Rigshospitalet; Fresenius Kabi; European Society for Clinical Nutrition and Metabolism (ESPEN); COSMED; Medinor/MedGraphics; CSL Behring; Ferring PharmaceuticalsSCI(E)ARTICLE111637-16474
A measurement of material in the ATLAS tracker using secondary hadronic interactions in 7 TeV pp collisions
No full textSee paper for full list of authors, 28 pages plus author list + cover pages (45 pages total),14 figures, 8 tables, submitted to Journal of Instrum., All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/PERF-2015-06/International audienceKnowledge of the material in the ATLAS inner tracking detector is crucial in understanding the reconstruction of charged-particle tracks, the performance of algorithms that identify jets containing b-hadrons and is also essential to reduce background in searches for exotic particles that can decay within the inner detector volume. Interactions of primary hadrons produced in pp collisions with the material in the inner detector are used to map the location and amount of this material. The hadronic interactions of primary particles may result in secondary vertices, which in this analysis are reconstructed by an inclusive vertex-finding algorithm. Data were collected using minimum-bias triggers by the ATLAS detector operating at the LHC during 2010 at centre-of-mass energy = 7 TeV, and correspond to an integrated luminosity of nb. Kinematic properties of these secondary vertices are used to study the validity of the modelling of hadronic interactions in simulation. Secondary-vertex yields are compared between data and simulation over a volume of about 0.7 m around the interaction point, and agreement is found within overall uncertainties
