Behavior change techniques are not widely marketed in contemporary physical activity apps. Based on the available descriptions and functions of the observed techniques in contemporary health behavior theories, people may need multiple apps to initiate and maintain behavior change. This audit provides a starting point for scientists, developers, clinicians, and consumers to evaluate and enhance apps in this market.

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Objectives:The conceptual models underlying physical activity interventions have been based largely on differences between more and less active people. Yet physical activity is a dynamic behavior, and such models are not sensitive to factors that regulate behavior at a momentary level or how people respond to individual attempts at intervening. We demonstrate how a control systems engineering approach can be applied to develop personalized models of behavioral responses to an intensive text message-based intervention. Design & Method:To establish proof-of-concept for this approach, 10 adults wore activity monitors for 16 weeks and received five text messages daily at random times. Message content was randomly selected from three types of messages designed to target (1) social-cognitive processes associated with increasing physical activity, (2) social-cognitive processes associated with reducing sedentary behavior, or (3) general facts unrelated to either physical activity or

The mapping of resistance toMeloidogyne chitwoodi derived from Solarium bulbocastanum is reported. A population suitable for mapping was developed as follows. A somatic hybrid of nematode-resistant S. bulbocastanum and cultivated tetraploid potato was produced. This was backcrossed to tetraploid potato, and a single resistant BC1 was selected and backcrossed again to the same recurrent tetraploid parent. The mapping population consisted of 64 BC2 progeny scored for restriction fragment length polymorphic (RFLP) markers and 62 of these were evaluated for the reproductive efficiency of race 1 of M. chitwoodi. Forty-eight polymorphic RFLP markers, originally derived from tomato and mapped in diploid cultivated potato, were assigned to 12 chromosomes of S. bulbocastanum. Of the 62 progeny screened for nematode resistance, 18 were non-hosts and four were poor hosts. The rest were highly susceptible (good hosts). Analysis of the resistance (including non-hosts and poor hosts) as both a qualitative trait and as a meristic trait on which QTL analysis was applied supported the same genetic hypothesis. Genetic control was localized solely to factor(s) lying at one end of chromosome 11. The level of expression of resistance in the S. bulbocastanum parent and the resistant portion of the BC2 was essentially the same. This fact, together with the highly significant LOD scores for one end of the chromosome-11 marker array, supports a genetic model equivalent to monogenic dominant control.

The use of intensive sampling methods, such as ecological momentary assessment (EMA), is increasingly prominent in medical research. However, inferences from such data are often limited to the subject-specific mean of the outcome and between-subject variance (i.e., random intercept), despite the capability to examine within-subject variance (i.e., random scale) and associations between covariates and subject-specific mean (i.e., random slope). MixWILD (Mixed model analysis With Intensive Longitudinal Data) is statistical software that tests the effects of subject-level parameters (variance and slope) of time-varying variables, specifically in the context of studies using intensive sampling methods, such as ecological momentary assessment. MixWILD combines estimation of a stage 1 mixed-effects location-scale (MELS) model, including estimation of the subject-specific random effects, with a subsequent stage 2 linear or binary/ordinal logistic regression in which values sampled from each subject's random effect distributions can be used as regressors (and then the results are aggregated across replications). Computations within MixWILD were written in FORTRAN and use maximum likelihood estimation, utilizing both the expectation-maximization (EM) algorithm and a Newton-Raphson solution. The mean and variance of each individual's random effects used in the sampling are estimated using empirical Bayes equations. This manuscript details the underlying procedures and provides examples illustrating standalone usage and features of MixWILD and its GUI. MixWILD is generalizable to a variety of data collection strategies (i.e., EMA, sensors) as a robust and reproducible method to test predictors of variability in level 1 outcomes and the associations between subject-level parameters (variances and slopes) and level 2 outcomes.

Persistent COVID-19 symptoms (long COVID) may bring challenges to long haulers’ social lives. Females may endure more profound impacts given their special social roles and existing structural inequality. This study explores the effects of long COVID on the social life of female long haulers. We conducted semi-structured interviews via Zoom between April and June 2021 with 15 female long haulers in the United States, purposely recruited from Facebook and Slack groups and organization websites related to long COVID. Interviews were audio-recorded and transcribed verbatim with consent. The interview data were managed using MAXQDA and examined by thematic analysis. Long COVID negatively affected female long haulers’ social lives by causing physical limitations, economic issues, altered social relationships, social roles’ conflicts, and social stigma. Long COVID prevented female long haulers’ recovery process. Physical limitations altered their perceptions on body, and family–work conflicts caused tremendous stress. They also experienced internalized stigma and job insecurities. This study provides insights into challenges that COVID-19 female long haulers could face in their return to normal social life, underscoring the vulnerability of females affected by long COVID due to significant alterations in their social lives. Shifting to new methods of communication, especially social media, diminished the adverse effects of long COVID (e.g., social isolation).

The results of this investigation demonstrate a consistent association of A4GALT SNPs rs2143918 and rs5751348 with the P1/P2 phenotypes and suggest that SNP rs5751348 may lead to allelic variations in A4GALT gene expression and consequently leads to the formation of the P1/P2 phenotypes.

Ecological Momentary Assessment data present some new modeling opportunities. Typically, there are sufficient data to explicitly model the within-subject (WS) variance, and in many applications, it is of interest to allow the WS variance to depend on covariates as well as random subject effects. We describe a model that allows multiple random effects per subject in the mean model (eg, random location intercept and slopes), as well as random scale in the error variance model. We present an example of the use of this model on a real dataset and a simulation study that shows the benefit of this model, relative to simpler approaches.