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Purpose To ensure clarity in communication in the field of quality of life research, and meaningful use of ‘quality of life’ as a research outcome, requires two things: awareness that there is a range of conceptualisations and definitions of ‘quality of life’, and for any particular study, consistency between the way the term is defined and operationalised in that setting. We aimed to identify how frequently research articles described (HR)QOL as a construct of interest, how frequently they referred to “patient-reported outcome (measures)”, which patient-reported outcome measures were used, and how (HR)QOL was defined. Methods We reviewed all Quality of Life Research articles published in 2017 and recorded whether they described health-related quality of life or quality of life as constructs of interest, and/or mentioned the term(s) patient-reported outcome ( measures ). We recorded definitions of (HR)QOL stated and questionnaires used. We classified articles according to constructs assessed and instruments used, and examined whether articles citing the same definition used the same questionnaires. Results We reviewed 300 articles; 65% stated that (HR)QOL was a construct of interest, 27% mentioned patient-reported outcome (measures), and 20% mentioned neither. Fifty-one articles provided definitions of (HR)QOL, citing 66 sources, with 11 definitions cited more than once. PROMIS, SF, EQ-5D, and EORTC instruments were the most commonly used. The only definition and questionnaire consistently used together were the WHO definitions/instruments. Conclusion These results demonstrate considerable heterogeneity in the definition and operationalisation of (HR)QOL, between and within studies. This limits meaningful interpretation of (HR)QOL scores and complicates literature searches. Investigators should define constructs and select instruments aligned with their definitions.

An important challenge in mental health research is to translate findings from cognitive neuroscience and neuroimaging research into effective treatments that target the neurobiological alterations involved in psychiatric symptoms. To address this challenge, in this review we propose a heuristic neurocircuit-based taxonomy to guide the treatment of obsessive–compulsive disorder (OCD). We do this by integrating information from several sources. First, we provide case vignettes in which patients with OCD describe their symptoms and discuss different clinical profiles in the phenotypic expression of the condition. Second, we link variations in these clinical profiles to underlying neurocircuit dysfunctions, drawing on findings from neuropsychological and neuroimaging studies in OCD. Third, we consider behavioral, pharmacological, and neuromodulatory treatments that could target those specific neurocircuit dysfunctions. Finally, we suggest methods of testing this neurocircuit-based taxonomy as well as important limitations to this approach that should be considered in future research.

The QUEST Initiative is a large prospective multicenter study of patients with any chronic health condition newly prescribed medicinal cannabis between November 2020 and December 2021. Eligible patients were identified by 120 clinicians at medical centers across six Australian states. Consenting participants completed the EuroQol Group EQ-5D-5L health status questionnaire; European Organization for Research & Treatment of Cancer Quality of Life questionnaire (QLQ-C30); Patient-Reported Outcomes Measurement Information System (PROMIS) Short Forms in Fatigue and Sleep Disturbance, and the Depression Anxiety Stress Scale (DASS-21) before starting therapy, at 2-weeks titration, then monthly for 3-months. Of the 2762 consenting participants, 2327 completed baseline and at least one follow-up questionnaire. Ages ranged between 18-97 years (mean 51y; SD = 15.4), 62.8% were female. The most commonly treated conditions were chronic pain (n = 1598/2327; 68.7%), insomnia (n = 534/2327; 22.9%), generalized anxiety (n = 508/2327; 21.5%), and mixed anxiety and depression (n = 259/2327; 11%). Across the whole cohort both EQ-5D-5L utility scores and QLQ-C30 summary scores showed clinically meaningful improvement in HRQL from baseline to mean follow-up with d = 0.54 (95%CI:0.47 to 0.59) and d = 0.64 (95%CI:0.58 to 0.70) respectively; and clinically meaningful improvement in fatigue (d = 0.54; 95%CI:0.48 to 0.59). There was clinically meaningful reduction of pain for those with chronic pain (d = 0.65; 95%CI:0.57 to 0.72); significant improvements for those with moderate to extremely severe anxiety (X.sup.2 = 383; df = 4; p<0.001) and depression (X.sup.2 = 395; df = 4; p<0.001); and no changes in sleep disturbance. We observed statistically significant, clinically meaningful improvements in overall HRQL and fatigue over the first 3-months in patients with chronic health conditions accessing prescribed medical cannabis. Anxiety, depression, and pain also improved over time, particularly for those with corresponding health conditions. The study continues to follow-up patients until 12-months to determine whether improvements in PROs are maintained long-term.

Since 2016, more than one million new patients with chronic health conditions have been prescribed medicinal cannabis in Australia. We aimed to assess overall health-related quality of life (HRQL), pain, fatigue, sleep, anxiety, depression, and motor function in a large real-world sample of patients prescribed medicinal cannabis. We previously found all patient-reported outcomes improved in the first 3-months and hypothesised that improvements would be maintained to 12-months. The QUEST Initiative, a multicentre prospective study, recruited adult patients with any chronic health condition newly prescribed medicinal cannabis oil between November 2020 and December 2021. Participants identified by 114 clinicians across Australia completed validated questionnaires at baseline, then 2-weeks titration, and 1-,2-,3-,5-,7-,9- and 12-months follow-up. Of 2744 consenting participants who completed baseline assessments, 2353 also completed at least one follow-up questionnaire and were included in analyses, with completion rates declining to 778/2353 (38%) at 12-months. Ages ranged between 18-97 years (mean 50.4y; SD = 15.4), 62.8% were female. Chronic conditions commonly treated included musculoskeletal pain (n = 896/2353; 38.1%), neuropathic pain (n = 547/2353; 23.2%), insomnia (n = 546/2353; 23.2%), anxiety (n = 520/2353; 22.1%), and mixed depressive and anxiety disorder (n = 263/2353; 11.2%). Clinically meaningful improvements were observed in HRQL: EQ-5D-5L index (d = 0.52) and QLQ-C30 summary scores (d = 0.91), PROMIS fatigue (d = 0.51) and sleep disturbance (d = 0.76). Participants diagnosed with chronic pain experienced clinically meaningful improvement in scores on QLQ-C30 pain (d = 0.5), PROMIS pain intensity (d = 0.76), and PROMIS pain interference (d = 0.76). There was significant improvement in DASS anxiety (d = 0.69) and DASS depression (d = 0.65) for those with anxiety or depressive conditions, but no motor function improvements observed for participants with movement disorders. All observed improvements were statistically significant. Statistically significant and clinically meaningful improvements in overall HRQL, fatigue, and sleep disturbance were maintained over 12-months in patients prescribed medical cannabis for chronic health conditions. Anxiety, depression, insomnia, and pain also improved over time for those with corresponding health conditions. Australian New Zealand Clinical Trials Registry: ACTRN12621000063819.

During the early months of the COVID-19 pandemic, there was an unusually high submission rate of scholarly articles. Given that most academics were forced to work from home, the competing demands for familial duties may have penalized the scientific productivity of women. To test this hypothesis, we looked at submitted manuscripts and peer review activities for all Elsevier journals between February and May 2018-2020, including data on over 5 million authors and referees. Results showed that during the first wave of the pandemic, women submitted proportionally fewer manuscripts than men. This deficit was especially pronounced among more junior cohorts of women academics. The rate of the peer-review invitation acceptance showed a less pronounced gender pattern with women taking on a greater service responsibility for journals, except for health & medicine, the field where the impact of COVID-19 research has been more prominent. Our findings suggest that the first wave of the pandemic has created potentially cumulative advantages for men.

Lung cancer is the leading cause of cancer-related death. The identification of epidermal growth factor receptor (EGFR) somatic mutations defined a new, molecularly classified subgroup of non-small-cell lung cancer (NSCLC). Classic EGFR activating mutations, such as inframe deletions in exon 19 or the Leu858Arg (L858R) point mutation in exon 21 are associated with sensitivity to first generation quinazoline reversible EGFR tyrosine kinase inhibitors (TKIs). EGFR exon 20 insertion mutations, which are typically located after the C-helix of the tyrosine kinase domain of EGFR, may account for up to 4% of all EGFR mutations. Preclinical models have shown that the most prevalent EGFR exon 20 insertion mutated proteins are resistant to clinically achievable doses of reversible (gefitinib, erlotinib) and irreversible (neratinib, afatinib, PF00299804) EGFR TKIs. Growing clinical experience with patients whose tumours harbour EGFR exon 20 insertions corresponds with the preclinical data; very few patients have had responses to EGFR TKIs. Despite the prevalence and biological importance of EEGFR exon 20 insertions, few reports have summarised all preclinical and clinical data on these mutations. Here, we review the literature and provide an update with an emphasis on the structural, molecular, and clinical implications of EGFR exon 20 insertions.

Obsessive–compulsive disorder (OCD) is a highly prevalent and chronic condition that is associated with substantial global disability. OCD is the key example of the ‘obsessive–compulsive and related disorders’, a group of conditions which are now classified together in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and the International Classification of Diseases, 11th Revision, and which are often underdiagnosed and undertreated. In addition, OCD is an important example of a neuropsychiatric disorder in which rigorous research on phenomenology, psychobiology, pharmacotherapy and psychotherapy has contributed to better recognition, assessment and outcomes. Although OCD is a relatively homogenous disorder with similar symptom dimensions globally, individualized assessment of symptoms, the degree of insight, and the extent of comorbidity is needed. Several neurobiological mechanisms underlying OCD have been identified, including specific brain circuits that underpin OCD. In addition, laboratory models have demonstrated how cellular and molecular dysfunction underpins repetitive stereotyped behaviours, and the genetic architecture of OCD is increasingly understood. Effective treatments for OCD include serotonin reuptake inhibitors and cognitive–behavioural therapy, and neurosurgery for those with intractable symptoms. Integration of global mental health and translational neuroscience approaches could further advance knowledge on OCD and improve clinical outcomes. This Primer by Stein and colleagues discusses the epidemiology, mechanisms, diagnosis and treatment of obsessive–compulsive disorder, which is a psychiatric disorder that is characterized by the presence of obsessions and compulsions.

Items (or indicators) that constitute \"quality of life\" instruments can be classified as either reflective (manifestations of some underlying construct), causal (the construct is an effect of the indicators), or composite (the construct is an exact linear combination of the indicators). Psychometric methods based on inter-item associations are only appropriate for reflective indicators, whereas other statistical and non-statistical validation methods can be used for composite or causal indicators. Thus, the distinction has important practical, as well as theoretical, implications. Attempts have been made to empirically identify which items of the EORTC QLQ-C30, a cancer-specific instrument, are causal and which are reflective. Such attempts, however, first require commitment to a particular definition of quality of life, of which there are many. Whether an indicator forms a composite, is causal or reflective of quality of life will depend on the definition adopted, and therefore, the reflective-composite-causal distinction is, arguably, best established on conceptual rather empirical grounds, guided by the \"mental experiments\" suggested by Bollen (Structural equations with latent variables, Wiley, New York, 1989). Conceptual models of health status and quality of life, as well as a cognitive-linguistic approach to quality of life assessment, may make some contribution to this practice. Theoretical consideration of indicator content can guide not only instrument development and validation, but also the selection of an appropriate instrument.

Vehicles are the major source of air pollution in modern cities, emitting excessive levels of CO2 and other noxious gases. Exploiting the OBD-II interface available on most vehicles, the continuous emission of such pollutants can be indirectly measured over time, although accuracy has been an important design issue when performing this task due the nature of the retrieved data. In this scenario, soft-sensor approaches can be adopted to process engine combustion data such as fuel injection and mass air flow, processing them to estimate pollution and transmitting the results for further analyses. Therefore, this article proposes a soft-sensor solution based on an embedded system designed to retrieve data from vehicles through their OBD-II interface, processing different inputs to provide estimated values of CO2 emissions over time. According to the type of data provided by the vehicle, two different algorithms are defined, and each follows a comprehensive mathematical formulation. Moreover, an unsupervised TinyML approach is also derived to remove outliers data when processing the computed data stream, improving the accuracy of the soft sensor as a whole while not requiring any interaction with cloud-based servers to operate. Initial results for an embedded implementation on the Freematics ONE+ board have shown the proposal’s feasibility with an acquisition frequency equal to 1Hz and emission granularity measure of gCO2/km.

Purpose Compare the health-related quality of life (HRQL) of the Australian general population during the COVID-19 pandemic (2020) with pre-pandemic data (2015–2016) and identify pandemic-related and demographic factors associated with poorer HRQL. Methods Participants were quota sampled from an online panel by four regions (defined by active COVID-19 case numbers); then by age and sex. Participants completed an online survey about their HRQL [EORTC QLQ-C30 questionnaire and General Health Question (GHQ)], demographic characteristics, and the impact of the pandemic on daily life. HRQL scores were compared to a 2015–2016 reference sample using independent t-tests, adjusted for multiple testing. Associations between 22 pre-specified factors (pandemic-related and demographic) and 15 QLQ-C30 domains and GHQ, were assessed with multiple regressions. Results Most domains were statistically significantly worse for the 2020 sample ( n  = 1898) compared to the reference sample ( n  = 1979), except fatigue and pain. Differences were largest for the youngest group (18–29 years) for cognitive functioning, nausea, diarrhoea, and financial difficulties. Emotional functioning was worse for 2020 participants aged 18–59, but not for those 60 +. All models were statistically significant at p  < .001; the most variance was explained for emotional functioning, QLQ-C30 global health/QOL, nausea/vomiting, GHQ, and financial difficulties. Generally, increased workload, negative COVID-19 impacts, COVID-19-related worries, and negative attitudes towards public health order compliance were associated with poorer HRQL outcomes. Conclusion During the COVID-19 pandemic, Australians reported poorer HRQL relative to a pre-pandemic sample. Risk factors for poor HRQL outcomes included greater negative pandemic-related impacts, poorer compliance attitudes, and younger age. Trial registration ANZCTR number is: ACTRN12621001240831. Web address of your trial: https://www.anzctr.org.au/ACTRN12621001240831.aspx . Date submitted: 26/08/2021 2:56:53 PM. Date registered: 14/09/2021 9:40:31 AM. Registered by: Margaret-Ann Tait. Principal Investigator: Madeleine King.