The psychometric rigor of unsupervised, smartphone-based assessments and factors that impact remote protocol engagement is critical to evaluate prior to the use of such methods in clinical contexts. We evaluated the validity of a high-frequency, smartphone-based cognitive assessment protocol, including examining convergence and divergence with standard cognitive tests, and investigating factors that may impact adherence and performance (i.e., time of day and anticipated receipt of feedback vs. no feedback).

Cognitively unimpaired participants (N = 120, Mage = 68.8, 68.3% female, 87% White, Meducation = 16.5 years) completed 8 consecutive days of the Mobile Monitoring of Cognitive Change (M2C2), a mobile app-based testing platform, with brief morning, afternoon, and evening sessions. Tasks included measures of working memory, processing speed, and episodic memory. Traditional neuropsychological assessments included measures from the Preclinical Alzheimer’s Cognitive Composite battery.

Findings showed overall high compliance (89.3%) across M2C2 sessions. Average compliance by time of day ranged from 90.2% for morning sessions, to 77.9% for afternoon sessions, and 84.4% for evening sessions. There was evidence of faster reaction time and among participants who expected to receive performance feedback. We observed excellent convergent and divergent validity in our comparison of M2C2 tasks and traditional neuropsychological assessments.

This study supports the validity and reliability of self-administered, high-frequency cognitive assessment via smartphones in older adults. Insights into factors affecting adherence, performance, and protocol implementation are discussed.

Cancer health research relies on large-scale cohorts to derive generalizable results for different populations. While traditional epidemiological cohorts often use costly random sampling or self-motivated, preselected groups, a shift toward health system-based cohorts has emerged. However, such cohorts depend on participants remaining within a single system. Recent consumer engagement models using smartphone-based communication, driving projects, and social media have begun to upend these paradigms.

We initiated the Healthy Oregon Project (HOP) to support basic and clinical cancer research. HOP study employs a novel, cost-effective remote recruitment approach to effectively establish a large-scale cohort for population-based studies. The recruitment leverages the unique email account, the HOP website, and social media platforms to direct smartphone users to the study app, which facilitates saliva sample collection and survey administration. Monthly newsletters further facilitate engagement and outreach to broader communities.

By the end of 2022, the HOP has enrolled approximately 35,000 participants aged 18–100 years (median = 44.2 years), comprising more than 1% of the Oregon adult population. Among those who have app access, ∼87% provided consent to genetic screening. The HOP monthly email newsletters have an average open rate of 38%. Efforts continue to be made to improve survey response rates.

This study underscores the efficacy of remote recruitment approaches in establishing large-scale cohorts for population-based cancer studies. The implementation of the study facilitates the collection of extensive survey and biological data into a repository that can be broadly shared and supports collaborative clinical and translational research.

Online supermarkets are increasingly used both by consumers and as a source of data on the food environment. We compared product availability, nutritional information, front-of-pack (FOP) labelling, price and price promotions for food and drink products between physical and online supermarkets.

For physical stores, we collected data on price, price promotions, FOP nutrition labels and nutrition information from a random sample of food and drinks from six UK supermarkets. For online stores, we used foodDB, a research-ready dataset of over 14 million observations of food and drink products available in online supermarkets.

Six large supermarket stores located near Oxford, UK.

General sample with 295 food and drink products, plus boost samples for both fruit and vegetables, and alcohol.

In the general sample, 85 % (95 % CI 80, 90 %) of products found in physical stores could be matched with an online product. Nutritional information found in the two settings was almost identical, for example, concordance correlation coefficient for energy = 0·995 (95 % CI 0·993, 0·996). The presence of FOP labelling and price promotions differed between the two settings (Cohen’s kappa = 0·56 (95 % CI 0·45, 0·66) and 0·40 (95 % CI 0·26, 0·55), respectively). Prices were similar between online and physical supermarkets (concordance correlation coefficient > 0·9 for all samples).

Product availability, nutritional information and prices sourced online for these six retailers are good proxies of those found in physical stores. Price promotions and FOP labelling vary between the two settings. Further research should investigate whether this could impact on health inequalities.

There are concerns that price promotions encourage unhealthy dietary choices. This review aims to answer the following research questions (RQ1) what is the prevalence of price promotions on foods in high-income settings, and (RQ2) are price promotions more likely to be found on unhealthy foods?

Systematic review of articles published in English, in peer-review journals, after 1 January 2000.

Included studies measured the prevalence of price promotions (i.e. percentage of foods carrying a price promotion out of the total number of foods available to purchase) in retail settings, in upper-mid to high-income countries.

‘Price promotion’ was defined as a consumer-facing temporary price reduction or discount available to all customers. The control group/comparator was the equivalent products without promotions. The primary outcome for this review was the prevalence of price promotions, and the secondary outcome was the difference between the proportions of price promotions on healthy and unhealthy foods.

Nine studies (239 344 observations) were included for the meta-analysis for RQ1, the prevalence of price promotions ranged from 6 % (95 % CI 2 %, 15 %) for energy-dense nutrient-poor foods to 15 % (95 % CI 9 %, 25 %) for cereals, grains, breads and other starchy carbohydrates. However, the I-squared statistic was 99 % suggesting a very high level of heterogeneity. Four studies were included for the analysis of RQ2, of which two supported the hypothesis that price promotions were more likely to be found on unhealthy foods.

The prevalence of price promotions is very context specific, and any proposed regulations should be supported by studies conducted within the proposed setting(s).

Poor-quality diet, regarded as an important contributor to health inequalities, is linked to adverse health outcomes. We investigated sociodemographic and lifestyle predictors of poor-quality diet in a population sample.

A cross-sectional analysis of the Survey of Lifestyle, Attitudes and Nutrition (SLÁN). Diet was assessed using an FFQ (n 9223, response rate = 89 %), from which a dietary score (the DASH (Dietary Approaches to Stop Hypertension) score) was constructed.

General population of the Republic of Ireland.

The SLÁN survey is a two-stage clustered sample of 10 364 individuals aged 18 years.

Adjusting for age and gender, a number of sociodemographic, lifestyle and health-related variables were associated with poor-quality diet: social class, education, marital status, social support, food poverty (FP), smoking status, alcohol consumption, underweight and self-perceived general health. These associations persisted when adjusted for age, gender and social class. They were not significantly altered in the multivariate analysis, although the association with social support was attenuated and that with FP was borderline significant (OR = 1·2, 95 % CI 1·03, 1·45). A classical U-shaped relationship between alcohol consumption and dietary quality was observed. Dietary quality was associated with social class, educational attainment, FP and related core determinants of health.

The extent to which social inequalities in health can be explained by socially determined differences in dietary intake is probably underestimated. The use of composite dietary quality scores such as the DASH score to address the issue of confounding by diet in the relationship between alcohol consumption and health merits further study.