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As a consequence of lockdowns due to the coronavirus disease (COVID-19) and the resulting restricted social mobility, several billion people worldwide have recently had to replace physical face-to-face communication with computer-mediated interaction. Notably, the adoption rates of videoconferencing increased significantly in 2020, predominantly because videoconferencing resembles face-to-face interaction. Tools such as Zoom, Microsoft Teams, and Cisco Webex are used by hundreds of millions of people today. Videoconferencing may bring benefits (e.g., saving of travel costs, preservation of environment). However, prolonged and inappropriate use of videoconferencing may also have an enormous stress potential. A new phenomenon and term emerged, Zoom fatigue, a synonym for videoconference fatigue. This paper develops a definition for Zoom fatigue and presents a conceptual framework that explores the major root causes of videoconferencing fatigue and stress. The development of the framework draws upon media naturalness theory and its underlying theorizing is based on research published across various scientific fields, including the disciplines of both behavioral science and neuroscience. Based on this theoretical foundation, hypotheses are outlined. Moreover, implications for research and practice are discussed.

Antimicrobial resistance is one of the most serious threats to global health, but little progress has been made in reversing its spread. Inappropriate use of antibiotics in humans is a major driver of antimicrobial resistance, and rates are high and growing in lower- and middle-income countries. Antibiotics are thought to be subject to supplier-induced demand, whereby providers prescribe them to patients who do not know they are unnecessary. We conducted a randomized field experiment in 227 private health facilities in Tanzania, with standardized patients presenting uncomplicated upper respiratory tract infection symptoms. Standardized patients were randomly assigned to express knowledge (informed) or not (uninformed) that antibiotics were not required to treat them. There was a very high rate of inappropriate antibiotic prescription, with 86.0 percent of informed standardized patients and 94.8 percent of uninformed standardized patients prescribed an antibiotic, for an adjusted difference of 7.8 percentage points between the groups. This small effect suggests that broader health systems factors are at play and that interventions should be aimed at systems, health facilities, and providers.

Benzodiazepine (BZD) inappropriate use (i.e., misuse and overuse) is a worldwide public health problem. Despite current knowledge about increased sensitivity to side effects in the elderly, that should lead to more caution, only a third of BZD prescriptions in this age group are considered appropriate. The most frequent inadequate situations are excessive duration and/or dosage of a medical prescription or self-medication, especially in a context where it would be contraindicated, e.g., long-acting BZD in the elderly. Polypharmacy and comorbidities are major risk factors. Consequences of BZD inappropriate use are falls, delirium and other cognitive dysfunction, acute respiratory failure, car accidents, dependence, and withdrawal symptoms. An emerging concern is a potentially increased risk of dementia. Contrary to most clinicians’ belief, discontinuation of chronic BZD use in elderly patients is feasible, with adequate psychotherapeutic or pharmacological strategies, and can lead to long-term abstinence. Brief cognitive therapy mostly relies on psychoeducation and motivational enhancement and is particularly useful in this context. Further research is needed, notably in three areas: (1) assessing the impact of public health programs to prevent BZD inappropriate use in the elderly, (2) developing alternative strategies to treat anxiety and insomnia in elderly patients, and (3) exploring the association between chronic BZD use and dementia.

Inappropriate use of antibiotics in humans and agriculture is one of the drivers1 of the emergence of antimicrobial resistance. The prevalence of penicillinresistant pneumococci, macrolideresistant Streptococcus pneumoniae and S.pyogenes strongly correlates with total antibiotic use in outpatients.2 Such inappropriate use is the result of complex interactions between demand for and supply of antibiotics. The use of antibiotics in the retail sector, for example in pharmacies and drugstores, the healthcare sector and in farms involves both professional and unqualified personnel from various sectors. These personnel operate within their country-specific regulatory environments and have different economic incentives.In the retail sector, there are several challenges on the demand for antibiotics. Prevalence of non-prescription antibiotics is high in some countries, such as in Bangladesh, Brazil and Sudan. In these countries, the prevalence of antimicrobial resistance is higher in communities who use non-prescription antibiotics more frequently.3 Among Hispanic households in New York, United States of America (USA), self-medication with antibiotics is a common choice for fever, respiratory and gastrointestinal conditions.4 A systematic review of adult individuals in households of low- and middle-income countries covering 34 studies shows high prevalence (39%) of antimicrobial self-medication.5 Half of these studies focus on non-prescription antibiotics while the remainder is about the use of anti-malarial and other medicines. Main sources of self-medication antibiotics were found to be pharmacies, drugstores and leftover or borrowed drugs. Antibiotics sold in drugstores and provided by non-qualified personnel exacerbate inappropriate use. Common inappropriate use by households includes not completing the course or taking an insufficient dose, taking antibiotics for the wrong indications, such as viral infection and inflammation, and sharing antibiotics. The antibiotics most commonly used inappropriately to treat flu or common cold symptoms are ampicillin, tetracycline, metronidazole, ceftriaxone, kanamycin and cotrimoxazole.

ABSTRACTBackgroundThis study explores the appropriateness of psychotropic drug (PD) use for neuropsychiatric symptoms (NPS) in nursing home patients with dementia. MethodsA cross-sectional study on 559 patients with dementia residing on dementia special care units in Dutch nursing homes was conducted. Appropriateness of PD use was assessed using the Appropriate Psychotropic drug use In Dementia (APID) index. The APID index score is calculated using information about individual PDs from patients’ medical records. The index encompasses seven (different) domains of appropriateness, i.e. indication, evaluation, dosage, drug-drug interactions, drug-disease interactions, duplications, and therapy duration. ResultsA total of 578 PDs were used for NPS by 60% of the nursing home patients. Indication, evaluation, and therapy duration contributed the most to inappropriate use. Ten per cent of the PDs scored fully appropriate according to the APID index sum score, 36% scored fully appropriate for indication, 46% scored fully appropriate for evaluation, and 58% scored fully appropriate for therapy duration. Antidepressants were used the most appropriately, and antiepileptics the most inappropriately. ConclusionsThe minority of the PD use was fully appropriate. The results imply that PD use for NPS in dementia can be improved; the appropriateness should be optimized with a clinical focus on the appropriate indications, evaluations, and therapy duration.

Mental ill-health is the leading cause of disability worldwide. Moreover, 75% of mental health conditions emerge between the ages of 12 and 25 years. Unfortunately, due to lack of resources and limited engagement with services, a majority of young people affected by mental ill-health do not access evidence-based support. To address this gap, our team has developed a multimodal, scalable digital mental health service (Enhanced Moderated Online Social Therapy [MOST+]) merging real-time, clinician-delivered web chat counseling; interactive user-directed online therapy; expert and peer moderation; and peer-to-peer social networking. The primary aim of this study is to ascertain the feasibility, acceptability, and safety of MOST+. The secondary aims are to assess pre-post changes in clinical, psychosocial, and well-being outcomes and to explore the correlations between system use, perceived helpfulness, and secondary outcome variables. Overall, 157 young people seeking help from a national youth e-mental health service were recruited over 5 weeks. MOST+ was active for 9 weeks. All participants had access to interactive online therapy and integrated web chat counseling. Additional access to peer-to-peer social networking was granted to 73 participants (46.5%) for whom it was deemed safe. The intervention was evaluated via an uncontrolled single-group study. Overall, 93 participants completed the follow-up assessment. Most participants had moderate (52/157, 33%) to severe (96/157, 61%) mental health conditions. All a priori feasibility, acceptability, and safety criteria were met. Participants provided mean scores of ≥3.5 (out of 5) on ease of use (mean 3.7, SD 1.1), relevancy (mean 3.9, SD 1.0), helpfulness (mean 3.5, SD 0.9), and overall experience (mean 3.9, SD 0.8). Moreover, 98% (91/93) of participants reported a positive experience using MOST+, 82% (70/93) reported that using MOST+ helped them feel better, 86% (76/93) felt more socially connected using it, and 92% (86/93) said they would recommend it to others. No serious adverse events or inappropriate use were detected, and 97% (90/93) of participants reported feeling safe. There were statistically significant improvements in 8 of the 11 secondary outcomes assessed: psychological distress (d=-0.39; P<.001), perceived stress (d=-0.44; P<.001), psychological well-being (d=0.51; P<.001), depression (d=-0.29; P<.001), loneliness (d=-0.23; P=.04), social support (d=0.30; P<.001), autonomy (d=0.36; P=.001), and self-competence (d=0.30; P<.001). There were significant correlations between system use, perceived helpfulness, and a number of secondary outcome variables. MOST+ is a feasible, acceptable, and safe online clinical service for young people with mental ill-health. The high level of perceived helpfulness, the significant improvements in secondary outcomes, and the correlations between indicators of system use and secondary outcome variables provide initial support for the therapeutic potential of MOST+. MOST+ is a promising and scalable platform to deliver standalone e-mental health services as well as enhance the growing international network of face-to-face youth mental health services.

Antipsychotics are widely used for treating patients with psychosis, and target threshold psychotic symptoms. Individuals at clinical high risk (CHR) for psychosis are characterized by subthreshold psychotic symptoms. It is currently unclear who might benefit from antipsychotic treatment. Our objective was to apply a risk calculator (RC) to identify people that would benefit from antipsychotics. Drawing on 400 CHR individuals recruited between 2011 and 2016, 208 individuals who received antipsychotic treatment were included. Clinical and cognitive variables were entered into an individualized RC for psychosis; personal risk was estimated and 4 risk components (negative symptoms-RC-NS, general function-RC-GF, cognitive performance-RC-CP, and positive symptoms-RC-PS) were constructed. The sample was further stratified according to the risk level. Higher risk was defined based on the estimated risk score (20% or higher). In total, 208 CHR individuals received daily antipsychotic treatment of an olanzapine-equivalent dose of 8.7 mg with a mean administration duration of 58.4 weeks. Of these, 39 (18.8%) developed psychosis within 2 years. A new index of factors ratio (FR), which was derived from the ratio of RC-PS plus RC-GF to RC-NS plus RC-CP, was generated. In the higher-risk group, as FR increased, the conversion rate decreased. A small group (15%) of CHR individuals at higher-risk and an FR >1 benefitted from the antipsychotic treatment. Through applying a personal risk assessment, the administration of antipsychotics should be limited to CHR individuals with predominantly positive symptoms and related function decline. A strict antipsychotic prescription strategy should be introduced to reduce inappropriate use.

Machine Learning (ML) has revolutionized various domains, offering predictive capabilities in several areas. However, there is growing evidence in the literature that ML approaches are not always used appropriately, leading to incorrect and sometimes overly optimistic results. One reason for this inappropriate use of ML may be the increasing availability of machine learning tools, leading to what we call the “push the button” approach. While this approach provides convenience, it raises concerns about the reliability of outcomes, leading to challenges such as incorrect performance evaluation. In particular, this paper addresses a critical issue in ML, known as data leakage, where unintended information contaminates the training data, impacting model performance evaluation. Indeed, crucial steps in ML pipeline can be inadvertently overlooked, leading to optimistic performance estimates that may not hold in real-world scenarios. The discrepancy between evaluated and actual performance on new data is a significant concern. In particular, this paper categorizes data leakage in ML, discussing how certain conditions can propagate through the ML approach workflow. Furthermore, it explores the connection between data leakage and the specific task being addressed, investigates its occurrence in Transfer Learning framework, and compares standard inductive ML with transductive ML paradigms. The conclusion summarizes key findings, emphasizing the importance of addressing data leakage for robust and reliable ML applications considering tasks and generalization goals.

Sleep disorders such as insomnia may occur in old age, potentially leading to z-hypnotic use. However, few studies have explored older adults' self-reported sleep concerns in relation to z-hypnotic use. We aim to examine this relationship. We conducted a cross-sectional study using a web-based questionnaire to assess sleep disturbances and medication use (z-hypnotics, benzodiazepines, and opioid analgesics) among 5,194 older adults through 21 GPs in southeast Norway. The main outcome, inappropriate z-hypnotic use, was defined as self-reported use for ≥4 weeks at ≥ three times per week. We used descriptive statistics and exploratory logistic regression mixed-effects models for data analysis. Among the 687 patients included in the study, 22% (  = 153) reported sleep disturbances. Of these, 84% (  = 575) did not use z-hypnotics, while 16% (  = 112) used z-hypnotics, 63% (  = 71) of these used them inappropriately. (≥4 weeks, ≥ three times per week). Patients with sleep disturbances (OR: 12.1, CI: 6.77 - 21.6,  < 0.001), trouble falling or staying asleep (OR: 14.6, CI: 5.04-42.0,  < 0.001), and multiple reasons for disturbances (pain, overthinking, or a family death) (OR: 3.58, CI: 1.85-6.93,  < 0.001) had higher odds of inappropriate z-hypnotic use compared to those with no or occasional disturbances. Men had lower odds (OR: 0.54, CI: 0.30-0.97,  = 0.039) than women. GP prescribing was not associated with inappropriate use, but men had lower odds (OR: 0.34, CI: 0.14-0.84,  = 0.020) when prescribed by male GPs compared to women prescribed by female GPs. A high proportion of patients used z-hypnotics inappropriately. This inappropriate use was associated with experienced sleep disturbances, particularly trouble falling asleep, trouble staying asleep, and multiple reasons for sleep disturbances. The prescribing GP was not significantly associated with inappropriate use.

Background: The epidemic of medical use and abuse of opioid analgesics is linked to the economic burden of opioid-related abuse and fatalities in the United States. Multiple studies have estimated the extent to which prescription opioid analgesics contribute to the national drug abuse problem; studies also assessing the trends in medical use and abuse of opioid analgesics have confirmed the relationship between increasing medical use of opioids and increasing fatalities. The available data is limited until 2002.. Study Design: Retrospective analysis of data from 2004 to 2011 from 2 databases: Automation of Reports and Consolidated Orders System (ARCOS) for opioid use data and Drug Abuse Warning Network (DAWN) for drug misuse data. Objective: To determine the proportion of drug abuse related to opioid analgesics and the various trends in the medical use and abuse of 8 opioid analgesics commonly used to treat pain: buprenorphine, codeine, fentanyl, hydrocodone, hydromorphone, methadone, morphine, and oxycodone. Methods: The data obtained from DAWN is a nationally representative sample of hospital emergency department admissions resulting from drug abuse. Main outcome measure was the identification of trends in the medical use and misuse of opioid analgesics from 2004 to 2011. Results: From 2004 to 2011, there was an increase in the medical use of all opioids except for a 20% decrease in codeine. The abuse of all opioids including codeine increased during this period. Increases in medical use ranged from 2,318% for buprenorphine to 35% for fentanyl, including 140% for hydromorphone, 117% for oxycodone, 73% for hydrocodone, 64% for morphine, and 37% for methadone. The misuse increased 384% for buprenorphine with available data from 2006 to 2011, whereas from 2004 to 2011, it increased 438% for hydromorphone, 263% for oxycodone, 146% for morphine, 107% for hydrocodone, 104% for fentanyl, 82% for methadone, and 39% for codeine. Comparison of opioid use showed an overall increase of 1,448% from 1996 to 2011, with increases if 690% from 1996 to 2004 and 100% from 2004 to 2011. In contrast, misuse increased more dramatically: 4,680% from 1996 to 2011, with increases of 1,372% from 1996 through 2004 and 245% from 2004 to 2011. The number of patients seeking rehabilitation for substance abuse also increased 187% for opioids, whereas it increased 87% for heroin, 40% for marijuana, and decreased 7% for cocaine. Limitations: Limitations of this assessment include the lack of data from 2003, lack of data available on meperidine, and that the aggregate data systems used in the study did not identify specific formulations or commercial products. Conclusion: The present trend of continued increase in the medical use of opioid analgesics appears to contribute to increases in misuse, resulting in multiple health consequences. Key words: Medical use of opioids, inappropriate use of opioids, abuse of opioids, opioid-related fatalities, Automation of Reports and Consolidated Orders System (ARCOS), Drug Abuse Warning Network (DAWN), International Narcotics Control Board (INCB)