. BACKGROUND
. Personas, based on customer or population data, are widely used to inform design decisions in the commercial sector. The variety of methods available means that personas can be produced from projects of different types and scale.
.
.
. OBJECTIVE
. This study aims to experiment with the use of personas that bring together data from a survey, household air measurements and electricity usage sensors, and an interview within a research and innovation project, with the aim of supporting eHealth and eWell-being product, process, and service development through broadening the engagement with and understanding of the data about the local community.
.
.
. METHODS
. The project participants were social housing residents (adults only) living in central Cornwall, a rural unitary authority in the United Kingdom. A total of 329 households were recruited between September 2017 and November 2018, with 235 (71.4%) providing complete baseline survey data on demographics, socioeconomic position, household composition, home environment, technology ownership, pet ownership, smoking, social cohesion, volunteering, caring, mental well-being, physical and mental health–related quality of life, and activity. K-prototype cluster analysis was used to identify 8 clusters among the baseline survey responses. The sensor and interview data were subsequently analyzed by cluster and the insights from all 3 data sources were brought together to produce the personas, known as the Smartline Archetypes.
.
.
. RESULTS
. The Smartline Archetypes proved to be an engaging way of presenting data, accessible to a broader group of stakeholders than those who accessed the raw anonymized data, thereby providing a vehicle for greater research engagement, innovation, and impact.
.
.
. CONCLUSIONS
. Through the adoption of a tool widely used in practice, research projects could generate greater policy and practical impact, while also becoming more transparent and open to the public.
.

In response to the COVID-19 outbreak, the UK Government provided public health advice to stay at home from 16 March 2020, followed by instruction to stay at home (full lockdown) from 24 March 2020. We use data with high temporal resolution from utility sensors installed in 280 homes across social housing in Cornwall, UK, to test for changes in domestic electricity, gas and water usage in response to government guidance. Gas usage increased by 20% following advice to stay at home, the week before full lockdown, although no difference was seen during full lockdown itself. During full lockdown, morning electricity usage shifted to later in the day, decreasing at 6 a.m. and increasing at midday. These changes in energy were echoed in water usage, with a 17% increase and a one-hour delay in peak morning usage. Changes were consistent with people getting up later, spending more time at home and washing more during full lockdown. Evidence for these changes was also observed in later lockdowns, but not between lockdowns. Our findings suggest more compliance with an enforced stay-at-home message than with advice. We discuss implications for socioeconomically disadvantaged households given the indication of inability to achieve increased energy needs during the pandemic.

. Background
. Personas, based on customer or population data, are widely used to inform design decisions in the commercial sector. The variety of methods available means that personas can be produced from projects of different types and scale.
.
.
. Objective
. This study aims to experiment with the use of personas that bring together data from a survey, household air measurements and electricity usage sensors, and an interview within a research and innovation project, with the aim of supporting eHealth and eWell-being product, process, and service development through broadening the engagement with and understanding of the data about the local community.
.
.
. Methods
. The project participants were social housing residents (adults only) living in central Cornwall, a rural unitary authority in the United Kingdom. A total of 329 households were recruited between September 2017 and November 2018, with 235 (71.4%) providing complete baseline survey data on demographics, socioeconomic position, household composition, home environment, technology ownership, pet ownership, smoking, social cohesion, volunteering, caring, mental well-being, physical and mental health–related quality of life, and activity. K-prototype cluster analysis was used to identify 8 clusters among the baseline survey responses. The sensor and interview data were subsequently analyzed by cluster and the insights from all 3 data sources were brought together to produce the personas, known as the Smartline Archetypes.
.
.
. Results
. The Smartline Archetypes proved to be an engaging way of presenting data, accessible to a broader group of stakeholders than those who accessed the raw anonymized data, thereby providing a vehicle for greater research engagement, innovation, and impact.
.
.
. Conclusions
. Through the adoption of a tool widely used in practice, research projects could generate greater policy and practical impact, while also becoming more transparent and open to the public.
.

Photodynamic therapy (PDT) is a light activated drug therapy that can be used to treat a number of dermatological cancers and precancers. Improvement of efficacy is required to widen its application. Clinical protoporphyrin IX (PpIX) fluorescence data were obtained using a pre-validated, non-invasive imaging system during routine methyl aminolevulinate (MAL)-PDT treatment of 172 patients with licensed dermatological indications (37.2% actinic keratosis, 27.3% superficial basal cell carcinoma and 35.5% Bowen's disease). Linear and logistic regressions were employed to model any relationships between variables that may have affected PpIX accumulation and/or PpIX photobleaching during irradiation and thus clinical outcome at three months. Patient age was found to be associated with lower PpIX accumulation/photobleaching, however only a reduction in PpIX photobleaching appeared to consistently adversely affect treatment efficacy. Clinical clearance was reduced in lesions located on the limbs, hands and feet with lower PpIX accumulation and subsequent photobleaching adversely affecting the outcome achieved. If air cooling pain relief was employed during light irradiation, PpIX photobleaching was lower and this resulted in an approximate three-fold reduction in the likelihood of achieving clinical clearance. PpIX photobleaching during the first treatment was concluded to be an excellent predictor of clinical outcome across all lesion types.