ABSTRACT
The objective of this scoping review was to examine the breadth of the existing literature on the relation between meat consumption or meat abstention and positive psychological functioning. In April 2022, we conducted a systematic search of online databases (PubMed, PsycINFO, CINAHL Plus, Medline, Cochrane Library, and Web of Science) for primary research examining positive psychological functioning in meat consumers and those who abstain from meat. Thirteen studies met the inclusion/exclusion criteria, representing 89,138 participants (54,413 females and 33,863 males) with 78,562 meat consumers and 10,148 meat abstainers (13-102 years) from multiple geographic regions. The primary outcomes were life satisfaction, "positive mental health", self-esteem, and vigor. The secondary outcomes were "meaning in life", optimism, positive emotions, and psychological well-being. Eight of the 13 studies demonstrated no differences between the groups on positive psychological functioning, three studies showed mixed results, and two studies showed that compared to meat abstainers, meat consumers had greater self-esteem, "positive mental health", and "meaning in life". Studies varied substantially in methods and outcomes. Although a small minority of studies showed that meat consumers had more positive psychological functioning, no studies suggested that meat abstainers did. There was mixed evidence for temporal relations, but study designs precluded causal inferences. Our review demonstrates the need for future research given the equivocal nature of the extant literature on the relation between meat consumption and meat abstention and positive psychological functioning.
ABSTRACT
BACKGROUND: For many years, clinicians have been seeking for objective pain assessment solutions via neuroimaging techniques, focusing on the brain to detect human pain. Unfortunately, most of those techniques are not applicable in the clinical environment or lack accuracy. OBJECTIVE: This study aimed to test the feasibility of a mobile neuroimaging-based clinical augmented reality (AR) and artificial intelligence (AI) framework, CLARAi, for objective pain detection and also localization direct from the patient's brain in real time. METHODS: Clinical dental pain was triggered in 21 patients by hypersensitive tooth stimulation with 20 consecutive descending cold stimulations (32°C-0°C). We used a portable optical neuroimaging technology, functional near-infrared spectroscopy, to gauge their cortical activity during evoked acute clinical pain. The data were decoded using a neural network (NN)-based AI algorithm to classify hemodynamic response data into pain and no-pain brain states in real time. We tested the performance of several networks (NN with 7 layers, 6 layers, 5 layers, 3 layers, recurrent NN, and long short-term memory network) upon reorganized data features on pain diction and localization in a simulated real-time environment. In addition, we also tested the feasibility of transmitting the neuroimaging data to an AR device, HoloLens, in the same simulated environment, allowing visualization of the ongoing cortical activity on a 3-dimensional brain template virtually plotted on the patients' head during clinical consult. RESULTS: The artificial neutral network (3-layer NN) achieved an optimal classification accuracy at 80.37% (126,000/156,680) for pain and no pain discrimination, with positive likelihood ratio (PLR) at 2.35. We further explored a 3-class localization task of left/right side pain and no-pain states, and convolutional NN-6 (6-layer NN) achieved highest classification accuracy at 74.23% (1040/1401) with PLR at 2.02. CONCLUSIONS: Additional studies are needed to optimize and validate our prototype CLARAi framework for other pains and neurologic disorders. However, we presented an innovative and feasible neuroimaging-based AR/AI concept that can potentially transform the human brain into an objective target to visualize and precisely measure and localize pain in real time where it is most needed: in the doctor's office. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/13594.
