Background: Previous studies have assessed the prevalence and characteristics of self-medication in COVID-19. However, no systematic review has summarized their findings.Objective: We conducted a systematic review to assess the prevalence of self-medication to prevent or manage COVID-19.Methods: We used different keywords and searched studies published in PubMed, Scopus, Web of Science, Embase, two preprint repositories, Google, and Google Scholar. We included studies that reported original data and assessed self-medication to prevent or manage COVID-19. The risk of bias was assessed using the Newcastle–Ottawa Scale (NOS) modified for cross-sectional studies.Results: We identified eight studies, all studies were cross-sectional, and only one detailed the question used to assess self-medication. The recall period was heterogeneous across studies. Of the eight studies, seven assessed self-medication without focusing on a specific symptom: four performed in the general population (self-medication prevalence ranged between <4% to 88.3%) and three in specific populations (range: 33.9% to 51.3%). In these seven studies, the most used medications varied widely, including antibiotics, chloroquine or hydroxychloroquine, acetaminophen, vitamins or supplements, ivermectin, and ibuprofen. The last study only assessed self-medication for fever due to COVID-19. Most studies had a risk of bias in the “representativeness of the sample” and “assessment of outcome” items of the NOS.Conclusions: Studies that assessed self-medication for COVID-19 found heterogeneous results regarding self-medication prevalence and medications used. More well-designed and adequately reported studies are warranted to assess this topic.

Dog-assisted therapy (DAT) is a non-pharmacological intervention based on the interaction between patients and dogs, which has been proposed to help adults with dementia. However, evidence to support it is lacking. Thus, we aim to evaluate the effects of DAT on this population and to assess the certainty of the evidence of the RCTs estimates. A systematic search was performed. We included randomized controlled trials (RCTs) and quasi-experimental (QE) controlled studies published up to March 2018, which evaluated the beneficial and deleterious effects of DAT in adults with dementia. Mean differences (MD) or standardized mean differences (SMD) and their 95% confidence intervals (95% CI) were calculated and random effects meta-analyses were performed. Certainty of evidence was assessed for RCTs estimates using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology. The study protocol has been registered in PROSPERO (CRD42018090434). Ten studies (six RCTs and four QE controlled studies) were eligible for inclusion. Meta-analysis of RCTs showed no effect of DAT in daily life activities (SMD: 0.16; 95% CI: -0.80 to 1.12), depression (SMD: -0.45; 95% CI: -2.81 to 1.91), agitation (SDM: -1.12; 95% CI: -2.67 to 0.43), quality of life (SDM: 0.16; 95% CI: -0.41 to 0.73), and cognitive impairment (SDM: -0.52; 95% CI: -1.33 to 0.30), but it found a beneficial effect in apathy (1 study, n = 37, MD: 1.81; 95% CI: 1.26 to 2.36). All outcomes had a very low certainty of evidence according to GRADE methodology. RCTs evidence of very low certainty suggests that, in adults with dementia, DAT has no effect in daily life activities, depression, agitation, quality of life, and cognitive impairment, although one small study found an apparent beneficial effect in apathy. More well-designed and correctly reported studies are needed in order to provide a conclusion. CRD42018090434 (PROSPERO).

Background: ChatGPT has shown impressive performance in national medical licensing examinations, such as the United States Medical Licensing Examination (USMLE), even passing it with expert-level performance. However, there is a lack of research on its performance in low-income countries’ national licensing medical examinations. In Peru, where almost one out of three examinees fails the national licensing medical examination, ChatGPT has the potential to enhance medical education. Objective: We aimed to assess the accuracy of ChatGPT using GPT-3.5 and GPT-4 on the Peruvian National Licensing Medical Examination (Examen Nacional de Medicina [ENAM]). Additionally, we sought to identify factors associated with incorrect answers provided by ChatGPT. Methods: We used the ENAM 2022 data set, which consisted of 180 multiple-choice questions, to evaluate the performance of ChatGPT. Various prompts were used, and accuracy was evaluated. The performance of ChatGPT was compared to that of a sample of 1025 examinees. Factors such as question type, Peruvian-specific knowledge, discrimination, difficulty, quality of questions, and subject were analyzed to determine their influence on incorrect answers. Questions that received incorrect answers underwent a three-step process involving different prompts to explore the potential impact of adding roles and context on ChatGPT’s accuracy. Results: GPT-4 achieved an accuracy of 86% on the ENAM, followed by GPT-3.5 with 77%. The accuracy obtained by the 1025 examinees was 55%. There was a fair agreement (κ=0.38) between GPT-3.5 and GPT-4. Moderate-to-high-difficulty questions were associated with incorrect answers in the crude and adjusted model for GPT-3.5 (odds ratio [OR] 6.6, 95% CI 2.73-15.95) and GPT-4 (OR 33.23, 95% CI 4.3-257.12). After reinputting questions that received incorrect answers, GPT-3.5 went from 41 (100%) to 12 (29%) incorrect answers, and GPT-4 from 25 (100%) to 4 (16%). Conclusions: Our study found that ChatGPT (GPT-3.5 and GPT-4) can achieve expert-level performance on the ENAM, outperforming most of our examinees. We found fair agreement between both GPT-3.5 and GPT-4. Incorrect answers were associated with the difficulty of questions, which may resemble human performance. Furthermore, by reinputting questions that initially received incorrect answers with different prompts containing additional roles and context, ChatGPT achieved improved accuracy.

Nomophobia is the discomfort caused by not being in contact with a cell phone. Few studies have addressed nomophobia in university students. The study aimed to evaluate nomophobia and its associated factors in Peruvian medical students. We conducted an analytical cross-sectional study on Peruvian medical students between June 2020 and March 2021, using an online survey disseminated through social networks. We analyzed 3139 responses (females: 61.1%, median age: 22 years): 25.7% presented moderate nomophobia and 7.4% severe nomophobia. In the adjusted model, the nomophobia score was lower in students ≥24 years (β: −4.1, 95% CI: −7.2 to −1.0) and was higher in those who had a mobile internet data plan (β: 2.9, 0.8 to 5.0), used the cell phone >4 h (β: 4.5, 2.3 to 6.7), used a smartphone mainly for education (β: 2.5, 0.2 to 4.8), social networks (β: 8.2, 5.8 to 10.6) and entertainment (β: 3.3, 0.5 to 6.1), and those who presented possible anxious (β: 6.6, 4.3 to 8.9) or depressive (β: 19.5, 5.2 to 9.6) symptomatology. In conclusion, nomophobia in university students is a frequent and emerging problem, present mainly at younger ages and associated with symptoms of anxiety or depression. Implementing evaluation and early intervention strategies would favor the mental health of university students.

Research suggested that waiting time and consultation time are associated with overall patient satisfaction concerning health services. However, there is a lack of information regarding this subject in Latin American countries, where particular aspects of health systems and population characteristics could modify this association. Our aim was to evaluate the association of waiting time and consultation time with patient satisfaction, in Peruvian ambulatory care facilities and propose a cut-off points of waiting and consultation time based on patient satisfaction. Cross-sectional secondary data analysis of the National Survey on User Satisfaction of Health Services (ENSUSALUD-2015), a national-wide survey with a probabilistic sample of 181 Peruvian ambulatory care facilities. Patient satisfaction, waiting time, consultation time, and sociodemographic variables were collected from the ENSUSALUD-2015. All variables were collected by survey directly to patients, from the selected ambulatory care facilities, after their consultation. Complex survey sampling was considered for data analysis. In the association analysis, we grouped the waiting time and consultation time variables, every 10 min, because for it is more relevant and helpful in the statistical and practical interpretation of the results, instead of the every-minute unit. The survey was performed in 13,360 participants. Response rate were 99.8 to 100% in the main variables. Waiting time (for every 10 min) was inversely associated with patient satisfaction (aOR: 0.98, 95% CI: 0.97–0.99), although the aOR was lower among those who reported a waiting time ≤ 90 min (aOR: 0.92, 95% CI: 0.89–0.96). Consultation time (for every 10 min) was directly associated with patient satisfaction (aOR: 1.59, 95% CI: 1.26–2.01), although the aOR was higher among those who reported a consultation time ≤ 15 min (aOR: 2.31, 95% CI: 1.66–3.21). In Peruvian ambulatory care facilities, both waiting time and consultation time showed an association with overall patient satisfaction, which was stronger in the first 90 min of waiting time and in the first 15 min of consultation time. This should be taken into consideration when designing interventions to improve waiting times and consultation times in ambulatory care facilities from Peru or from similar contexts.