Previous plant-based diet (PBD) adoption strategies have primarily focused on health rather than environmental rationale and meat reduction rather than plant-based protein promotion. In this study, we explored the effect of a theory-informed text-message intervention on dietary intentions and behaviors in young adult omnivores and the potential explanatory role of PBD beliefs, subjective norm, self-efficacy, moral norm, and health and environmental values. Participants completed baseline questionnaires and reported dietary intake before being randomly assigned to receive 2–3 health- or environment-focused text messages per week for eight weeks and then repeated baseline assessments. Although we did not see significant changes in meat or plant protein intake, we did observe a marked decrease in intentions to consume animal protein and a marginal increase in fruit and vegetable consumption intention. We identified subjective norms, self-efficacy, and moral satisfaction as the strongest predictors of changes in intention to consume animal or plant protein. Although few group differences were observed, those receiving environment-focused text messages experienced a greater change in values and were more likely to increase vegetable intake. Messages that improve sustainability awareness and provide practical adoption strategies may be part of an effective strategy to influence PBD intake among young adults.

In this article, we consider a time-varying-stress accelerated life testing (ALT) under aWiener decay process. The failure time of products follows a time-transformed inverse Gaussian dis-tribution. We outline some interesting properties of this highly flexible distribution, present the classical maximum likelihood estimation method, and propose a new Bayesian approach for inference. Simulation studies are carried out to assess the performance of the methods under various settings of parameter values and sample sizes. Real data are analyzed for illustrative purposes to demonstrate the efficiency and accuracy of the proposed Bayesian method over the likelihood-based procedure.