Selecting, implementing and evaluating control and placebo conditions in light therapy and light-based interventions

Introduction: Light profoundly influences human physiology, behaviour and cognition by affecting various functions through light-sensitive cells in the retina. Light therapy has proven effective in treating seasonal depression and other disorders. However, designing appropriate control conditions for light-based interventions remains a challenge.Materials and methods: This article presents a novel framework for selecting, implementing and evaluating control conditions in light studies, offering theoretical foundations and practical guidance. It reviews the fundamentals of photoreception and discusses control strategies such as dim light, darkness, different wavelengths, spectral composition and metameric conditions. Special cases like dynamic lighting, simulated dawn and dusk, complex interventions and studies involving blind or visually impaired patients are also considered.Results: The practical guide outlines steps for selection, implementation, evaluation and reporting, emphasizing the importance of α-opic calculations and physiological validation.Conclusion: In conclusion, constructing effective control conditions is crucial for demonstrating the efficacy of light interventions in various research scenarios.

Preventing type 2 diabetes among Indigenous youth: A systematic review of community-based interventions

A systematic review was conducted to assess evidence on effectiveness of community-based interventions promoting wellbeing and prevention of type 2 diabetes (T2D) among Indigenous youth. A convergent, segregated, mixed methods approach was used, with six databases and four grey literature sites searched from inception to May 2022. Articles selected for inclusion were about community-based interventions related to T2D prevention with Indigenous youth that evaluated effectiveness or youth experience published in English. Reference lists were also searched for relevant sources. Seven quantitative research articles met the inclusion and quality assessment criteria. No qualitative articles were identified. The results were synthesised through narrative analysis, while meta-analysis was not possible due to heterogenous study designs. Common foci across interventions included promoting physical wellness, improving physical activity and healthy eating patterns, enhancing knowledge, and psychosocial wellness. Interventions deemed effective addressed multiple areas, were school-based, and operated for at least a year. Findings support multi-strategy, community-based interventions implemented over longer periods of time. However, gaps in research and reporting included the extent to which interventions are culturally informed and based on community-driven priorities. Future research should include Indigenous, mixed and qualitative methods and Indigenous-driven measures of success to better understand effectiveness in alignment with Indigenous worldviews.

Democratising the design and delivery of large-scale randomised, controlled clinical trials in primary care: A personal view

BACKGROUND

Rapid identification of effective treatments for use in the community during a pandemic is vital for the well-being of individuals and the sustainability of healthcare systems and society. Furthermore, identifying treatments that do not work reduces research wastage, spares people unnecessary side effects, rationalises the cost of purchasing and stockpiling medication, and reduces inappropriate medication use. Nevertheless, only a small minority of therapeutic trials for SARS-CoV-2 infections have been in primary care: most opened too late, struggled to recruit, and few produced actionable results. Participation in research is often limited by where one lives or receives health care, and trial participants may not represent those for whom the treatments are intended.

INNOVATIVE TRIALS

The ALIC4E, PRINCIPLE and the ongoing PANORAMIC trial have randomised over 40,500 people with COVID-19. This personal view describes how these trials have innovated in: trial design (by using novel adaptive platform designs); trial delivery (by complementing traditional site-based recruitment ('the patient comes to the research') with mechanisms to enable sick, infectious people to participate without having to leave home ('taking research to the people'), and by addressing the 'inverse research participation law,' which highlights disproportionate barriers faced by those who have the most to contribute, and benefit from, research, and; in transforming the evidence base by evaluating nine medicines to support guidelines and care decisions world-wide for COVID-19 and contribute to antimicrobial stewardship.

CONCLUSION

The PRINCIPLE and PANORAMIC trials represent models of innovation and inclusivity, and exemplify the potential of primary care to lead the way in addressing pressing global health challenges.

Understanding adaptive tasks in cardiac rehabilitation among patients with acute myocardial infarction: a qualitative study

BACKGROUND

While Cardiac Rehabilitation (CR) programs have shown effectiveness in improving cardiac outcomes, there is limited understanding of how patients perceive and adapt to these interventions. Furthermore, alternative modes of delivering CR that have received positive evaluations from participants remain underexplored, yet they have the potential to enhance CR uptake.

OBJECTIVES

To explore the patient experience in CR programmes following Acute Myocardial Infarction (AMI) and describe their adaptive processing.

PATIENTS AND METHODS

This qualitative study was conducted at a nationally certified centre in China between July 2021 and September 2022, encompassing three stages: in-hospital, centre-based, and home-based CR programs. Purposive sampling was used to select eligible AMI patients for in-depth semi-structured interviews. The interview outline and analytical framework were aligned with the key concepts derived from the middle-range theory of adaptation to chronic illness and the normalization process theory. The findings were reported following the Consolidated Criteria for Reporting Qualitative Research checklist.

RESULTS

Forty AMI patients were recruited. Four main themes describing the process of AMI patients normalizing CR intervention were identified, including (1) experiencing CR service driving by role's responsibilities, (2) engaging in collaborative relationship based on interpersonal trust, (3) exploring a personalized rehabilitation plan by complex integration, and (4) expecting a promised outcome to shape decision-making.

CONCLUSION

Integrated care interventions for AMI patients could benefit from a collaborative co-designed approach to ensure that CR interventions are normalized and fit into patients' daily lives. Organizational-level CR services should align with the rehabilitation needs and expectations of patients.

A scoping review on the operationalization of intersectional health research methods in studies related to the COVID-19 pandemic

PURPOSE

The COVID-19 pandemic began in early 2020 and became a global health crisis with devastating impacts. This scoping review maps the key findings of research about the pandemic that has operationalized intersectional research methods around the world. It also tracks how these studies have engaged with methodological tenets of oppression, comparison, relationality, complexity, and deconstruction.

METHODS

Our search resulted in 14,487 articles, 5164 of which were duplicates, and 9297 studies that did not meet the inclusion criteria were excluded. In total, 14 articles were included in this review. We used thematic analysis to analyse themes within this work and Misra et al. (2021) intersectional research framework to analyse the uptake of intersectional methods within such studies.

RESULTS

The research related to the COVID-19 pandemic globally is paying attention to issues around the financial impacts of the pandemic, discrimination, gendered impacts, impacts of and on social ties, and implications for mental health. We also found strong uptake of centring research in the context of oppression, but less attention is being paid to comparison, relationality, complexity, and deconstruction.

CONCLUSIONS

Our findings show the importance of intersectional research within public health policy formation, as well as room for greater rigour in the use of intersectional methods.

The intersection between logical empiricism and qualitative nursing research: a post-structuralist analysis

PURPOSE

To shed light on and analyse the intersection between logical empiricism and qualitative nursing research, and to emphasize a post-structuralist critique to traditional methodological constraints.

METHODS

In this study, a critical examination is conducted through a post-structuralist lens, evaluating entrenched methodologies within nursing research. This approach facilitates a nuanced exploration of the intersection between logical empiricism and qualitative nursing research, challenging traditional methodological paradigms.

RESULTS

The article focusing on the "what abouts" of sample size, analytic framework, data source, data analysis, and rigour and methodological considerations, challenging the predominance of semi-structured interviews and the reliance on spoken voice as primary data sources, and re-evaluating the conventional notion of "rigour".

CONCLUSIONS

I advocate for a shift from qualitative positivism towards more interpretive and post-qualitative inquiries, this work proposes new trajectories through interpretive, critical, post-qualitative, and artistic turns in nursing research, aiming to transcend positivist limitations and foster a plurality of perspectives and research as praxis. Implications emphasize the need for nursing researchers to expand methodological horizons, incorporating visual and artistic methods to enrich understanding and representation of health experiences, moving beyond positivist norms towards a more inclusive and ethically sound research paradigm.

The effect of education given to hemodialysis patients based on the Roy Adaptation Model on fluid management, symptom control, and quality of life

This study aimed to determine the effect of fluid management, symptom control, and quality of life on education based on the Roy Adaptation Model. This randomized controlled study was conducted with the participation of 107 patients (53 intervention, 54 control). Data were collected using the "Patient Data Collection Form," "Fluid Control in Hemodialysis Patients Scale," "Dialysis Symptom Index," and "Nottingham Health Profile." The forms were filled out through face-to-face interviews with the patients in the intervention and control groups at the 0th (onset), 1st, and 3rd months. The patients in the intervention group were trained with an education booklet based on the Roy Adaptation Model. The results revealed that the education given according to the Roy Adaptation Model improved the compliance with fluid control, quality of life, and symptom control of hemodialysis patients. It is recommended that education based on the Roy Adaptation Model be systematically used by hemodialysis nurses. The results are limited to the population included in the study, and further research on hemodialysis populations is needed.

Could nudges reduce health literacy disparities in CVD prevention? An experiment using alternative messages for CVD risk assessment screening

OBJECTIVE

To explore the effect of SMS nudge messages amongst people with varying health literacy on their intention to get a Heart Health Check.

METHODS

A 3 (Initial SMS: scarcity, regret, or control nudge) x 2 (Reminder SMS: social norm or control nudge) factorial design was used in a hypothetical online experiment. 705 participants eligible for Heart Health Checks were recruited. Outcomes included intention to attend a Heart Health Check and psychological responses.

RESULTS

In the control condition, people with lower health literacy had lower behavioural intentions compared to those with higher health literacy (p = .011). Scarcity and regret nudges closed this gap, resulting in similar intention levels for lower and higher health literacy. There was no interactive effect of the reminder nudge and health literacy (p = .724).

CONCLUSION

Scarcity and regret nudge messages closed the health literacy gap in behavioural intentions compared to a control message, while a reminder nudge had limited additional benefit. Health literacy should be considered in behavioural intervention evaluations to ensure health equity is addressed.

PRACTICE IMPLICATIONS

Results informed a national screening program using a universal precautions approach, where messages with higher engagement for lower health literacy groups were used in clinical practice.

Analysis of early childhood development according to the nurturing care framework, by wealth quintiles and regions of Argentina (2019-2020)

Introduction. One of the main challenges for early childhood is to provide adequate care to reduce inequalities and promote an early childhood development (ECD). The objective of this study was to describe the relationship between the care provided to children aged 3 and 4 years according to the nurturing care (NC) framework and their ECD levels in Argentina, considering the region and wealth quintiles. Population and methods. This was an observational, cross-sectional analytical study based on data from the National Survey of Children and Adolescents (MICS) of Argentina 2019-2020. A total of 11 NC indicators were selected; the level of ECD was estimated using the Early Childhood Development Index (ECDI) for a descriptive, statistical analysis. Results. In 2638 children aged 3 and 4 years assessed, the average access to care indicators was 79.1%; access was high for 7 indicators (between 84.2% and 97.9%) and middle for 4 indicators (between 46.9% and 65.1%); the highest and lowest frequency corresponded to having a birth certificate (97.9%) and health insurance coverage (46.9%), respectively. Adequate ECDI levels were observed in 87.9%. Results show differences by wealth quintile and region. Conclusions. The results evidence inequalities in terms of access to care and an adequate ECD of children aged 3 and 4 years from urban areas of Argentina, depending on the region where they live and their household wealth level.

Factor Analysis With Unusual Sexual Interests: A Replication Study in a Representative Population Sample

A previous study found a variety of unusual sexual interests to cluster in a five-factor structure, namely submission/masochism, forbidden sexual activities, dominance/sadism, mysophilia, and fetishism (Schippers et al., 2021). The current study was an empirical replication to examine whether these findings generalized to a representative population sample. An online, anonymous sample (N = 256) representative of the Dutch adult male population rated 32 unusual sexual interests on a scale from 1 (very unappealing) to 7 (very appealing). An exploratory factor analysis assessed whether similar factors would emerge as in the original study. A subsequent confirmatory factor analysis served to confirm the factor structure. Four slightly different factors of sexual interest were found: extreme, illegal and mysophilic sexual activities; light BDSM without real pain or suffering; heavy BDSM that may include pain or suffering; and illegal but lower-sentenced and fetishistic sexual activities. The model fit was acceptable. The representative replication sample was more sexually conservative and showed less sexual engagement than the original convenience sample. On a fundamental level, sexual interest in light BDSM activities and extreme, forbidden, and mysophilic activities seem to be relatively separate constructs.

Advancing urban traffic accident forecasting through sparse spatio-temporal dynamic learning

Traffic accidents have emerged as one of the most public health safety matters, raising concerns from both the public and urban administrators. The ability to accurately predict traffic accident not only supports the governmental decision-making in advance but also enhances public confidence in safety measures. However, the efficacy of traditional spatio-temporal prediction models are compromised by the skewed distributions and sparse labeling of accident data. To this end, we propose a Sparse Spatio-Temporal Dynamic Hypergraph Learning (SST-DHL) framework that captures higher-order dependencies in sparse traffic accidents by combining hypergraph learning and self-supervised learning. The SST-DHL model incorporates a multi-view spatiotemporal convolution block to capture local correlations and semantics of traffic accidents, a cross-regional dynamic hypergraph learning model to identify global spatiotemporal dependencies, and a two-supervised self-learning paradigm to capture both local and global spatiotemporal patterns. Through experimentation on New York City and London accident datasets, we demonstrate that our proposed SST-DHL exhibits significant improvements compared to optimal baseline models at different sparsity levels. Additionally, it offers enhanced interpretability of results by elucidating complex spatio-temporal dependencies among various traffic accident instances. Our study demonstrates the effectiveness of the SST-DHL framework in accurately predicting traffic accidents, thereby enhancing public safety and trust.

Effectiveness of a health communication intervention on health literacy in the first year following kidney transplantation - A randomized controlled study

OBJECTIVE

This study aimed to evaluate the effect of a new health communication intervention focusing on knowledge management skills on health literacy and medication adherence during the first year following kidney transplantation.

METHODS

We randomized 195 patients during 2020-2021, to either intervention- or control group. Questionnaires were completed at baseline and at 12 months post-transplantation with a 12-month response rate of 84%. Health literacy was measured by the multidimensional Health Literacy Questionnaire (HLQ) instrument. Medication adherence was measured by the self-reported questionnaire (BAASIS©).

RESULTS

Results showed that the intervention group had a significant increase in 2 HLQ domains compared to the control group capturing the "ability to appraise health information" Domain 5, (p-value = 0.002) and the "ability to navigate the healthcare system" Domain 7, (p-value <0.04). The effect sizes of SRM were 0.49 (Domain 5) and 0.33 (Domain 7). Medication adherence was comparable in the groups at any measure points.

CONCLUSIONS

This study contributes to important knowledge about how a health communication intervention focusing on knowledge translation using motivational interviewing techniques positively strengthens health literacy in kidney transplant recipients.

PRACTICAL IMPLICATIONS

Current patient education practice may benefit from focusing on knowledge translation in combination with motivational interview technique.

Effectiveness of designing a knowledge-based artificial intelligence chatbot system into a nursing training program: A quasi-experimental design

BACKGROUND

Chatbots have gained popularity in the healthcare industry due to their ability to provide prompt and accurate responses to a wide range of inquiries. This has been particularly beneficial for nurses who often require quick access to information and may have questions related to patient care.

PURPOSE

To evaluate the effectiveness of designing a knowledge-based artificial intelligence chatbot system for a nursing training program.

METHODS

The study utilized a Quasi-experimental design and collected data from a purposive sample of 73 nurses using Google Forms. The tools used in the study included 1) a structured questionnaire for nurses (a) Demographic data (b) Nurses' knowledge regarding chatbots, 2) Nurses' knowledge about artificial intelligence, 3) Nurses' perception of the application of chatbots in nursing, and 4) Nurses' opinions about the use of nursing chatbots or traditional methods of education.

RESULTS

There was a highly statistically significant improvement in nurses' knowledge-based chatbot systems post-intervention (p = 0.001).

CONCLUSION

Integrating an artificial intelligence chatbot system into a nursing training program provides nurses with easy access to reliable and evidence-based knowledge. The chatbot offers immediate answers, explanations, and up-to-date resources, empowering nurses to make informed decisions, stay updated, and served as a communication platform connecting nurses through a common language and enhance their practice.

RECOMMENDATION

Incorporating a knowledge-based chatbot system into a nursing training program. Furthermore, further research should be conducted to explore the long-term impact of chatbot systems on nursing practices and education.

Characteristics and circumstances of rail suicides in England 2019-2021: A cluster analysis and autopsy study

BACKGROUND

Around 4 % of all suicide deaths in Great Britain occur on the railways. This exploratory study was designed to increase understanding of the individuals that take their lives in this way, and the circumstances of their death.

METHOD

Data were obtained from fatality investigation files compiled by the British Transport Police (BTP) relating to suspected suicides on the mainline railway in England from April 2019 to March 2021. Cluster analysis was carried out to identify grouped associations of characteristics and circumstances relating to rail suicide.

RESULTS

A total of 436 files were analysed, representing 93 % of all suspected railway suicides during this period. Cluster analysis identified four groups of almost equal size, distinguished principally by age, living arrangements, employment status and location of death. The study is novel in the way it integrates individual characteristics and circumstances of death. The identified clusters may provide a multidimensional way of conceptualising suicide risk that could inform more targeted interventions at rail locations.

LIMITATIONS

A high proportion of missing data means that the findings need to be interpreted with caution. It also restricted the multivariate analysis to those categories of information for which sufficient information was available.

CONCLUSION

The characteristics and circumstances of suicide deaths on the railways are complex and multifaceted. The typology identified in this study may help to target preventative strategies prior to the incident as well as at different location types.

Explanatory and modifying factors of the association between sex and depression onset during adolescence: An exploratory study

BACKGROUND

The prevalence of Major Depressive Disorder (MDD) is twice as high in women as in men and this difference already emerges during adolescence. Because the mechanisms underlying this sex-difference remain poorly understood, we took a bottom-up approach to identify factors explaining the sex-MDD relationship.

METHODS

Data came from the TRacking Adolescents' Individual Lives Survey (TRAILS), a population study investigating youths' development from age 11 into adulthood. We assessed multiple baseline covariates (e.g., demographic, social and psychological) at ages 11-13 years and MDD onset at ages 19 and 25 years. In regression analyses, each covariate's role in the sex-MDD association as an effect modifier or confounder/explanatory variable was investigated. Replicability was evaluated in an independent sample.

RESULTS

The analyses identified no effect-modifiers. Baseline internalizing problems, behavioral inhibition, dizziness, comfort in classroom, physical complaints, attention problems, cooperation, self/effortful control, interpersonal life events and computer use partially explained the association between sex and MDD at age 19. The association between sex and MDD at age 25 was explained by largely the same variables, but also by shyness, acne, antisocial behavior, aggression, affection from peers and time spent shopping. The explanatory roles of internalizing problems, behavioral inhibition, negative events involving gossip/rumors and leisure-time spending (computer-use/shopping) were replicated.

LIMITATIONS

Potentially important baseline variables were not included or had low response rates. Gender roles or identification were not considered. Baseline MDD was not adjusted for.

CONCLUSION

The sex-MDD association is partially explained by sex differences in symptoms and vulnerability factors already present in early adolescence.

Does the use of surgical face masks reduce postoperative infections in traumatic wounds sutured outside hospital? A randomized study at a Norwegian casualty center

OBJECTIVE

To investigate if wearing surgical face mask by doctors and nurses during suturing of traumatic wounds has any impact on postoperative infection rate.

DESIGN

Randomized controlled study with masked or unmasked health personnel groups.

SETTING

A Norwegian Minor Injury Department.

SUBJECTS

Adult patients with traumatic wounds sutured at the clinic between 7 October 2019 and 28 May 2020.

MAIN OUTCOME MEASURES

Postoperative infections of sutured wounds.

RESULTS

One hundred and sixty-five patients with 176 wounds were included in the study. Nine out of 88 wounds (10.2%) in the masked group and 11 out of 88 wounds in the unmasked group (12.5%) had a wound infection.

CONCLUSIONS

Despite a higher percentage of postoperative infections in the unmasked than in the masked group (12.5% versus 10.2%), the difference was not statistically significant (p = .6). This might imply that the use of facemasks during suture of traumatic wounds in an outpatient setting does not significantly reduce the number of infections. However, due to the covid pandemic, the study had to be prematurely stopped before the planned number of participants had been recruited (n = 594). This increases the risk of type II error.

How Mixed-Methods Research Can Improve the Policy Relevance of Impact Evaluations

This paper describes how mixed methods can improve the value and policy relevance of impact evaluations, paying particular attention to how mixed methods can be used to address external validity and generalization issues. We briefly review the literature on the rationales for using mixed methods; provide documentation of the extent to which mixed methods have been used in impact evaluations in recent years; describe how we developed a list of recent impact evaluations using mixed methods and the process used to conduct full-text reviews of these articles; summarize the findings from our analysis of the articles; discuss three exemplars of using mixed methods in impact evaluations; and discuss how mixed methods have been used for studying and improving external validity and potential improvements that could be made in this area. We find that mixed methods are rarely used in impact evaluations, and we believe that increased use of mixed methods would be useful because they can reinforce findings from the quantitative analysis (triangulation), and they can also help us understand the mechanism by which programs have their impacts and the reasons why programs fail.

A comprehensive and critical review of the unstandardized Folin-Ciocalteu assay to determine the total content of polyphenols: The conundrum of the experimental factors and method validation

The Folin-Ciocalteu method can be considered to be the most widely used in laboratories around the world, to quantify the total polyphenols content. Many different variations found in this assay have been reported in the scientific literature. In this review, the full experimental conditions influencing the Folin-Ciocalteu assay have been comparatively assessed and discussed. Furthermore, few studies relating to the method validation have been evaluated according to the results of selectivity, linearity, precision, trueness, limit of determination, limit of quantification and robustness. In general, the results derived from the reviewed literature are widely variable according to both, the experimental factors selected and the performance parameters reported, making difficult the comparison of the overall results published.

Gender ideology and fertility: evidence for a curvilinear hypothesis

Research on the relationship between fertility and gender ideology revealed inconsistent results. In the present study, we argue that inconsistencies may be due to the fact that such a relationship may be nonlinear. We hypothesize a U-shaped relationship between two dimensions of gender ideology (i.e., primacy of breadwinner role and acceptance of male privilege) and fertility rates. We conducted a cross-national analysis of 60 countries using data from the World Values Survey as well as the World Population Prospects 2019. Controlling for gross domestic product, we found support for a U-shaped relationship between gender ideology and fertility. Higher levels of fertility rates were found at lower and especially higher levels of traditional gender ideology, while a medium level of gender ideology was associated with the lowest fertility rate. This curvilinear relationship is in agreement with the phase of the gender revolution in which the country is located.

A Description of Missing Data in Single-Case Experimental Designs Studies and an Evaluation of Single Imputation Methods

Missing data is inevitable in single-case experimental designs (SCEDs) studies due to repeated measures over a period of time. Despite this fact, SCEDs implementers such as researchers, teachers, clinicians, and school psychologists usually ignore missing data in their studies. Performing analyses without considering missing data in an intervention study using SCEDs or a meta-analysis study including SCEDs studies in a topic can lead to biased results and affect the validity of individual or overall results. In addition, missingness can undermine the generalizability of SCEDs studies. Considering these drawbacks, this study aims to give descriptive and advisory information to SCEDs practitioners and researchers about missing data in single-case data. To accomplish this task, the study presents information about missing data mechanisms, item level and unit level missing data, planned missing data designs, drawbacks of ignoring missing data in SCEDs, and missing data handling methods. Since single imputation methods among missing data handling methods do not require complicated statistical knowledge, are easy to use, and hence are more likely to be used by practitioners and researchers, the present study evaluates single imputation methods in terms of intervention effect sizes and missing data rates by using a real and hypothetical data sample. This study encourages SCEDs implementers, and also meta-analysts to use some of the single imputation methods to increase the generalizability and validity of the study results in case they encounter missing data in their studies.

Impact of green space and built environment on metabolic syndrome: A systematic review with meta-analysis

Metabolic Syndrome presents a significant public health challenge associated with an increased risk of noncommunicable diseases such as cardiovascular conditions. Evidence shows that green spaces and the built environment may influence metabolic syndrome. We conducted a systematic review and meta-analysis of observational studies published through August 30, 2023, examining the association of green space and built environment with metabolic syndrome. A quality assessment of the included studies was conducted using the Office of Health Assessment and Translation (OHAT) tool. The Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) assessment was used to evaluate the overall quality of evidence. Our search retrieved 18 studies that met the inclusion criteria and were included in our review. Most were from China (n = 5) and the USA (n = 5), and most used a cross-sectional study design (n = 8). Nine studies (50 %) reported only green space exposures, seven (39 %) reported only built environment exposures, and two (11 %) reported both built environment and green space exposures. Studies reported diverse definitions of green space and the built environment, such as availability, accessibility, and quality, particularly around participants' homes. The outcomes focused on metabolic syndrome; however, studies applied different definitions of metabolic syndrome. Meta-analysis results showed that an increase in normalized difference vegetation index (NDVI) within a 500-m buffer was associated with a lower risk of metabolic syndrome (odds ratio [OR] = 0.90, 95%CI = 0.87-0.93, I2 = 22.3 %, n = 4). A substantial number of studies detected bias for exposure classification and residual confounding. Overall, the extant literature shows a 'limited' strength of evidence for green space protecting against metabolic syndrome and an 'inadequate' strength of evidence for the built environment associated with metabolic syndrome. Studies with more robust study designs, better controlled confounding factors, and stronger exposure measures are needed to understand better what types of green spaces and built environment features influence metabolic syndrome.

Updated recommendations on measures for clinical trials in pediatric chronic pain: a multiphase approach from the Core Outcomes in Pediatric Persistent Pain (Core-OPPP) Workgroup

ABSTRACT

Many gaps remain in finding effective, safe, and equitable treatments for children and adolescents with chronic pain and in accessing treatments in different settings. A major goal of the field is to improve assessment of pain and related experience. Valid and reliable patient-reported outcome measures are critical for advancing knowledge of clinical interventions for pediatric chronic pain. Building on the work of the Ped-IMMPACT group, we previously updated a core outcome set (COS) for pediatric chronic pain clinical trials using stakeholder feedback from providers, youth, and parents. The new COS includes 3 mandatory domains: pain severity, pain-related interference with daily living, and adverse events and 4 optional domains: overall well-being, emotional functioning, physical functioning, and sleep quality. The aim of this study was to use a multiphased approach to recommend specific measures for each of the 7 domains identified in our new COS for pediatric chronic pain. We synthesized evidence through conducting the following: (1) a Delphi study of experts to identify candidate measures for the new COS domains, (2) a review phase to gather evidence for measurement properties for candidate measures, and (3) an expert consensus conference to reach agreement on measurement recommendations. Final recommendations included 9 patient-reported measures. Important contextual considerations are discussed, and guidance is provided regarding strengths and limitations of the recommendations. Implementation of these recommendations may be enhanced by widespread dissemination and ease of access to measurement tools.

Investigation of Two Preliminary Analysis-Altering Elements: Ordinate Scaling and DPPXYR

The purpose of this pre-registered study (Peltier & McKenna) was to conceptually replicate if the truncation of the ordinate and DPPXYR increased analysts' estimation of a functional relation and magnitude of treatment effect. Visual analysts (n = 27) evaluated eight data sets reporting null (n = 2), small (n = 2), moderate (n = 2), and large (n = 2) effects. Each data set was graphed six times with manipulations of the ordinate and DPPXYR, resulting in 48 ABAB graphs. We estimated two separate three-level mixed effect models with variations nested in datasets and nested in participants to evaluate the impact of graph characteristics for (1) confidence in determining a functional relation and (2) the estimated magnitude of the treatment effect. We included ordinate scaling and DPPXYR at level 1 and graph effect size at level 2, including all interactions. Overall, graph manipulation consistently did not impact confidence in a functional relation. Results suggest mixed findings for graph manipulation on the estimated magnitude of the treatment effect. Findings will be couched in current literature and recommendations for graph construction and future research will be discussed.

Understanding experiences of 'Gig Buddies': A befriending scheme for people with intellectual disabilities

BACKGROUND

Research into befriending for people with intellectual disabilities is limited. This study aimed to explore the impact, mechanisms of change, and limitations of a befriending scheme for adults with intellectual disabilities and/or autism.

METHODS

Participants were recruited using convenience sampling. Thirteen individuals with intellectual disabilities and/or autism were interviewed and data thematically analysed.

RESULTS

Four themes were generated: 'Something fun for me'; 'A good connection'; 'Increasing independence'; and 'A life less quiet'. Befriending had direct benefits through the activities undertaken and the befriending relationships themselves being fun and reducing isolation. Befriending facilitated belonging, improved access to mainstream activities, and fostered independence by providing safety and support. The importance of shared interests and external support for the relationship was highlighted.

CONCLUSIONS

Positive outcomes of befriending were found, supporting existing literature and revealing new information from the voices of participants with intellectual disabilities themselves.

Modeling occupant injury severities for electric-vehicle-involved crashes using a vehicle-accident bi-layered correlative framework with matched-pair sampling

This study seeks to investigate occupant injury severities for electric-vehicle-involved crashes and inspect if electric vehicles lead to more serious injuries than fuel-powered vehicles, which have commonly been neglected in past studies. A Bayesian random slope model is proposed aiming to capture interactions between occupant injury severity levels and electric vehicle variable. The random slope model is developed under a vehicle-accident bi-layered correlative framework, which can account for the interactive effects of vehicles in the same accident. Based on the crash report sampling system (CRSS) 2020 and 2021 database, the extracted observations are formed into inherently matched pairs under certain matching variables including restraint system use, air bag deployed, ejection and rollover. The introduced data structure is able to ensure the standard error of the modeling parameters are not affected by these matching variables. Meanwhile, a comprehensive modeling performance comparison is conducted between the Bayesian random slope model and the Bayesian random intercept model, the Bayesian basic model. According to the empirical results, the bi-layered Bayesian random slope model presents a strong ability in model fitting and analysis, even when the sample size is small and the error structure is complex. Most importantly, occupants in electric vehicles are more likely to suffer serious injuries, especially incapacitating and fatal injuries, in the event of an accident compared to fuel-powered vehicles, which disproving the long-held misconception that green and safety are related.

Adaptive Multiple Comparison Sequential Design (AMCSD) for clinical trials

We propose an adaptive sequential testing procedure for clinical trials that test the efficacy of multiple treatment options, such as dose/regimen, different drugs, sub-populations, endpoints, or a mixture of them in one trial. At any interim analyses, sample size re-estimation can be conducted, and any option can be dropped for lack of efficacy or unsatisfactory safety profile. Inference after the trial, including p-value, conservative point estimate and confidence intervals, are provided.

Mindfulness-based Interventions Across the Cancer Continuum in the United States: A Scoping Review

OBJECTIVE

To review mindfulness-based interventions (MBIs) tested in randomized controlled trials (RCT) across the cancer continuum.

DATA SOURCE

Articles identified in PubMed, CINAHL, Web of Science, PsycINFO, and Embase.

STUDY INCLUSION AND EXCLUSION CRITERIA

Two independent reviewers screened articles for: (1) topic relevance; (2) RCT study design; (3) mindfulness activity; (4) text availability; (5) country (United States); and (6) mindfulness as the primary intervention component.

DATA EXTRACTION

Twenty-eight RCTs met the inclusion criteria. Data was extracted on the following variables: publication year, population, study arms, cancer site, stage of cancer continuum, participant demographic characteristics, mindfulness definition, mindfulness measures, mindfulness delivery, and behavioral theory.

DATA SYNTHESIS

We used descriptive statistics and preliminary content analysis to characterize the data and identify emerging themes.

RESULTS

A definition of mindfulness was reported in 46% of studies and 43% measured mindfulness. Almost all MBIs were tested in survivorship (50%) or treatment (46%) stages of the cancer continuum. Breast cancer was the focus of 73% of cancer-site specific studies, and most participants were non-Hispanic white females.

CONCLUSION

The scoping review identified 5 themes: (1) inconsistency in defining mindfulness; (2) differences in measuring mindfulness; (3) underrepresentation of racial/ethnic minorities; (4) underrepresentation of males and cancer sites other than breast; and (5) the lack of behavioral theory in the design, implementation, and evaluation of the MBI.

Clinical outcomes, medical costs, and medication usage patterns of different somatic symptom disorders and functional somatic syndromes: a population-based study in Taiwan

BACKGROUND

Somatic symptom disorders (SSD) and functional somatic syndromes (FSS) are often regarded as similar diagnostic constructs; however, whether they exhibit similar clinical outcomes, medical costs, and medication usage patterns has not been examined in nationwide data. Therefore, this study focused on analyzing SSD and four types of FSS (fibromyalgia, chronic fatigue syndrome, irritable bowel syndrome, functional dyspepsia).

METHODS

This population-based matched cohort study utilized Taiwan's National Health Insurance (NHI) claims database to investigate the impact of SSD/FSS. The study included 2 615 477 newly diagnosed patients with SSD/FSS and matched comparisons from the NHI beneficiary registry. Healthcare utilization, mortality, medical expenditure, and medication usage were assessed as outcome measures. Statistical analysis involved Cox regression models for hazard ratios, generalized linear models for comparing differences, and adjustment for covariates.

RESULTS

All SSD/FSS showed significantly higher adjusted hazard ratios for psychiatric hospitalization and all-cause hospitalization compared to the control group. All SSD/FSS exhibited significantly higher adjusted hazard ratios for suicide, and SSD was particularly high. All-cause mortality was significantly higher in all SSD/FSS. Medical costs were significantly higher for all SSD/FSS compared to controls. The usage duration of all psychiatric medications and analgesics was significantly higher in SSD/FSS compared to the control group.

CONCLUSION

All SSD/FSS shared similar clinical outcomes and medical costs. The high hazard ratio for suicide in SSD deserves clinical attention.

Use of Sequential Hot-Deck Imputation for Missing Health Care Systems Data for Population Health Research

Electronic medical record (EMR) data present many opportunities for population health research. The use of EMR data for population risk models can be impeded by the high proportion of missingness in key patient variables. Common approaches like complete case analysis and multiple imputation may not be appropriate for some population health initiatives that require a single, complete analytic data set. In this study, we demonstrate a sequential hot-deck imputation (HDI) procedure to address missingness in a set of cardiometabolic measures in an EMR data set. We assessed the performance of sequential HDI within the individual variables and a commonly used composite risk score. A data set of cardiometabolic measures based on EMR data from 2 large urban hospitals was used to create a benchmark data set with simulated missingness. Sequential HDI was applied, and the resulting data were used to calculate atherosclerotic cardiovascular disease risk scores. The performance of the imputation approach was assessed using a set of metrics to evaluate the distribution and validity of the imputed data. Of the 567,841 patients, 65% had at least 1 missing cardiometabolic measure. Sequential HDI resulted in the distribution of variables and risk scores that reflected those in the simulated data while retaining correlation. When stratified by age and sex, risk scores were plausible and captured patterns expected in the general population. The use of sequential HDI was shown to be a suitable approach to multivariate missingness in EMR data. Sequential HDI could benefit population health research by providing a straightforward, computationally nonintensive approach to missing EMR data that results in a single analytic data set.

Development of a whole spinal MRI-based tumor burden scoring method in participants with multiple myeloma: a pilot study of prognostic significance

The aim of the study was to develop a new whole spinal MRI-based tumor burden scoring method in participants with newly diagnosed multiple myeloma (MM) and to explore its prognostic significance. We prospectively recruited participants with newly diagnosed MM; performed whole spinal MRI (sagittal FSE T1WI, sagittal IDEAL T2WI, and axial FLAIR T2WI) on them; and collected their clinical data, early treatment response, progression-free survival (PFS), and overall survival (OS). We developed a new tumor burden scoring method according to the extent of bone marrow infiltration in five MRI patterns. All participants were divided into good response and poor response groups after four treatment cycles. Univariate, multivariate analyses, and ROC were used to determine the performance of independent predictors. Thresholds for PFS and OS were calculated using X-tile, and their prognostic significance were assessed by Kaplan-Meier. The Kruskal-Wallis H test was used to compare the differences of tumor burden score between the revised International Staging System (R-ISS) stages. The new tumor burden scoring method was used in 62 participants (median score, 12; range, 0-18). The tumor burden score (OR 1.266, p = 0.002) was an independent predictor of poor response and the AUC was 0.838. Higher tumor burden scores were associated with shorter PFS (p = 0.002) and OS (p = 0.011). The tumor burden score was higher in R-ISS-III than in R-ISS-I and R-ISS-II (p = 0.016 and p = 0.006, respectively). The tumor burden score was an excellent predictor of prognosis and may serve as a supplemental marker for R-ISS.

Optimal biological dose selection in dose-finding trials with model-assisted designs based on efficacy and toxicity: a simulation study

With the emergence of molecular targeted agents and immunotherapies in anti-cancer treatment, a concept of optimal biological dose (OBD), accounting for efficacy and toxicity in the framework of dose-finding, has been widely introduced into phase I oncology clinical trials. Various model-assisted designs with dose-escalation rules based jointly on toxicity and efficacy are now available to establish the OBD, where the OBD is generally selected at the end of the trial using all toxicity and efficacy data obtained from the entire cohort. Several measures to select the OBD and multiple methods to estimate the efficacy probability have been developed for the OBD selection, leading to many options in practice; however, their comparative performance is still uncertain, and practitioners need to take special care of which approaches would be the best for their applications. Therefore, we conducted a comprehensive simulation study to demonstrate the operating characteristics of the OBD selection approaches. The simulation study revealed key features of utility functions measuring the toxicity-efficacy trade-off and suggested that the measure used to select the OBD could vary depending on the choice of the dose-escalation procedure. Modelling the efficacy probability might lead to limited gains in OBD selection.

Disentangling potential causal effects of educational duration on well-being, and mental and physical health outcomes

BACKGROUND

Extensive research has focused on the potential benefits of education on various mental and physical health outcomes. However, whether the associations reflect a causal effect is harder to establish.

METHODS

To examine associations between educational duration and specific aspects of well-being, anxiety and mood disorders, and cardiovascular health in a sample of European Ancestry UK Biobank participants born in England and Wales, we apply four different causal inference methods (a natural policy experiment leveraging the minimum school-leaving age, a sibling-control design, Mendelian randomization [MR], and within-family MR), and assess if the methods converge on the same conclusion.

RESULTS

A comparison of results across the four methods reveals that associations between educational duration and these outcomes appears predominantly to be the result of confounding or bias rather than a true causal effect of education on well-being and health outcomes. Although we do consistently find no associations between educational duration and happiness, family satisfaction, work satisfaction, meaning in life, anxiety, and bipolar disorder, we do not find consistent significant associations across all methods for the other phenotypes (health satisfaction, depression, financial satisfaction, friendship satisfaction, neuroticism, and cardiovascular outcomes).

CONCLUSIONS

We discuss inconsistencies in results across methods considering their respective limitations and biases, and additionally discuss the generalizability of our findings in light of the sample and phenotype limitations. Overall, this study strengthens the idea that triangulation across different methods is necessary to enhance our understanding of the causal consequences of educational duration.

Using cross-validation methods to select time series models: Promises and pitfalls

Vector autoregressive (VAR) modelling is widely employed in psychology for time series analyses of dynamic processes. However, the typically short time series in psychological studies can lead to overfitting of VAR models, impairing their predictive ability on unseen samples. Cross-validation (CV) methods are commonly recommended for assessing the predictive ability of statistical models. However, it is unclear how the performance of CV is affected by characteristics of time series data and the fitted models. In this simulation study, we examine the ability of two CV methods, namely,10-fold CV and blocked CV, in estimating the prediction errors of three time series models with increasing complexity (person-mean, AR, and VAR), and evaluate how their performance is affected by data characteristics. We then compare these CV methods to the traditional methods using the Akaike (AIC) and Bayesian (BIC) information criteria in their accuracy of selecting the most predictive models. We find that CV methods tend to underestimate prediction errors of simpler models, but overestimate prediction errors of VAR models, particularly when the number of observations is small. Nonetheless, CV methods, especially blocked CV, generally outperform the AIC and BIC. We conclude our study with a discussion on the implications of the findings and provide helpful guidelines for practice.

Applications of Grounded Theory Methodology to Investigate Hearing Loss: A Methodological Qualitative Systematic Review With Developed Guidelines

OBJECTIVES

Qualitative methodologies are commonly adopted in hearing loss research. Grounded theory methodology is increasingly used to establish novel theories explaining experiences related to hearing loss. Establishing and improving the quality of grounded theory studies has been emphasized as critical to ensuring theoretical trustworthiness. Thus, the primary aim of the present study was to systematically review hearing loss research studies that have applied grounded theory methodology and assess the methodological quality of those grounded theory applications. Secondarily aims were to (i) explore how grounded theory methodology has been applied to investigate hearing loss, and (ii) use the findings of the review to develop a set of guidelines to aid the future high-quality application of grounded theory methodology to hearing loss research.

DESIGN

Original peer-reviewed studies applying grounded theory methodology and published in English were identified through systematic searches in 10 databases; Applied Social Sciences Index and Abstracts, British Nursing Index, Cumulative Index to Nursing and Allied Health Literature, EBSCO, Global Health, MEDLINE (OvidSP), PsycINFO, PubMed, Scopus, and Web of Science. The quality of studies was assessed according to 12 grounded theory principles using the Guideline for Reporting, Evaluating, and applying the core principles of Grounded Theory studies (GUREGT) tool. Data were analyzed using qualitative inductive thematic analysis.

RESULTS

After the removal of duplicates, 155 articles were retrieved. Of those, 39 met the criteria for inclusion in the systematic review. An increase in the adoption of grounded theory methodology to investigate hearing loss was identified with the number of published studies tripling in the last 5 years. Critical appraisal using the GUREGT tool identified four studies as high-quality. Most included studies were of moderate study quality (n = 25), and 10 were classified as being of low study quality. Using inductive thematic analysis, the included studies investigated one of four areas relating to hearing loss: (a) Living with hearing loss, (b) Identity and hearing loss, (c) Coping strategies for hearing loss, and (d) Audiological counseling and rehabilitation. Analysis also identified four main grounded theory factors frequently overlooked in hearing loss research: the different schools of grounded theory, sampling strategy, sample size, and the depth of grounded theory application.

CONCLUSIONS

Use of grounded theory methodology is increasing at a rapid rate in hearing loss research. Despite this, studies conducted in the field to date do not meet and apply the full spectrum of grounded theory principles, as outlined by the GUREGT tool. To improve methodological rigor in future studies using grounded theory, we propose a set of guidelines that address the most commonly overlooked methodological considerations in hearing loss studies to date. The guidelines are designed to aid researchers to achieve high methodological quality in any field, improve qualitative rigor, and promote theoretical credibility.

Employing graph attention networks to decode psycho-metabolic interactions in Schizophrenia

Schizophrenia is a severe mental disorder characterized by intricate and underexplored interactions between psychological symptoms and metabolic health, presenting challenges in understanding the disease mechanisms and designing effective treatment strategies. To delve deeply into the complex interactions between mental and metabolic health in patients with schizophrenia, this study constructed a psycho-metabolic interaction network and optimized the Graph Attention Network (GAT). This approach reveals complex data patterns that traditional statistical analyses fail to capture. The results show that weight management and medication management play a central role in the interplay between psychiatric disorders and metabolic health. Furthermore, additional analysis revealed significant correlations between the history of psychiatric symptoms and physical health indicators, as well as the key roles of biochemical markers(e.g., triglycerides and low-density lipoprotein cholesterol), which have not been sufficiently emphasized in previous studies. This highlights the importance of medication management approaches, weight management, psychological treatment, and biomarker monitoring in comprehensive treatment and underscores the significance of the biopsychosocial model. This study is the first to utilize a GNN to explore the interactions between schizophrenia symptoms and metabolic features, providing new insights into understanding psychiatric disorders and guiding the development of more comprehensive treatment strategies for schizophrenia.

Epistemic uncertainty in Bayesian predictive probabilities

Bayesian predictive probabilities have become a ubiquitous tool for design and monitoring of clinical trials. The typical procedure is to average predictive probabilities over the prior or posterior distributions. In this paper, we highlight the limitations of relying solely on averaging, and propose the reporting of intervals or quantiles for the predictive probabilities. These intervals formalize the intuition that uncertainty decreases with more information. We present four different applications (Phase 1 dose escalation, early stopping for futility, sample size re-estimation, and assurance/probability of success) to demonstrate the practicality and generality of the proposed approach.

Robust time selection for interim analysis in the Bayesian phase 2 exploratory clinical trial

In phase 2 clinical trials, we expect to make a right Go or No-Go decision during the interim analysis (IA) and make this decision at the right time. The optimal time for IA is usually determined based on a utility function. In most previous research, utility functions aim to minimize the expected sample size or total cost in confirmatory trials. However, the selected time can vary depending on different alternative hypotheses. This paper proposes a new utility function for Bayesian phase 2 exploratory clinical trials. It evaluates the predictability and robustness of the Go and No-Go decision made during the IA. We can make a robust time selection for the IA based on the function regardless of the treatment effect assumptions.

Justice perceptions and well-being: Belief in a just world is a personal resource and a coping resource

Although the perception of justice is a core need of all individuals, the adaptive value of belief in a just world (BJW)-in everyday life and when facing severe distress-has been typically investigated in separate studies. In this article, we tested, in only one study, the possibility that BJW can be a personal resource and a coping resource. We analysed data from the European Social Survey comprised of random representative samples of 27 European countries (N = 24,776 participants). We considered distressing circumstances both at an individual level (health impairment and financial difficulty) and at a macroeconomic contextual level. The results showed that for people both facing and not facing financial or health-related distress, BJW was positively associated with well-being, supporting BJW as a personal resource. Furthermore, we found that the decrease of well-being of people facing distress, both at an individual level and at a contextual level, compared to people not facing distress, was lower for individuals with higher BJW than for individuals with lower BJW, supporting BJW as a coping resource.

Local Level Economic Evaluation: What is it? What is its Value? Is it Sustainable?

In Australia, local health services with allocated budgets manage public hospital services for defined geographical areas. The authors were embedded in a local health service for around 2 years and undertook a range of local level economic evaluations for which three decision contexts were defined: intervention development, post-implementation and prioritisation. Despite difficulties in estimating opportunity costs and in the relevance of portfolio-based prioritisation approaches, economic evaluation added value to local decision-making. Development-focused (ex ante) economic evaluations used expert elicitation and calibration methods to synthesise published evidence with local health systems data to evaluate interventions to prevent hospital acquired complications. The use of economic evaluation facilitated the implementation of interventions with additional resource requirements. Decision analytic models were used alongside the implementation of larger scale, more complex service interventions to estimate counterfactual patient pathways, costs and outcomes, providing a transparent alternative to the statistical analyses of intervention effects, which were subject to high risk of bias. Economic evaluations of more established services had less impact due to data limitations and lesser executive interest. Prioritisation-focused economic evaluations compared costs, outcomes and processes of care for defined patient populations across alternative local health services to identify, understand and quantify the effects of unwarranted variation to inform priority areas for improvement within individual local health services. The sustained use of local level economic evaluation could be supported by embedding health economists in local continuous improvement units, perhaps with an initial focus on supporting the development and evaluation of prioritised new service interventions. Shared resources and critical mass are important, which could be facilitated through groups of embedded economists with joint appointments between different local health services and the same academic institution.

Ultra-brief acceptance & commitment therapy for inpatients with psychosis - a single-case experimental design investigating processes of change

People with primary psychosis are among the most seen in inpatient psychiatry. Treatment guidelines recommend both pharmacological and psychological treatments. However, psychological treatments are not routinely offered in many settings. There is also a lack of research on psychological treatments for this vulnerable population in the inpatient setting. The first aim of the current study was to examine treatment effects of a brief form of Acceptance and Commitment Therapy on outcomes valued by the treatment recipients. The second aim was to explore hypothetical processes of change in relation to outcomes over time. Three people with primary psychosis were treated for two to four sessions. A replicated single-case experimental design with multiple baselines across subjects (Clinical Trials registration number ID NCT04704973) was employed to examine treatment effects. The Personal Questionnaire (PQ) was used as primary outcome, symptom believability and preoccupation as proposed processes of change. Data were analyzed using visual inspection, calculation of Tau-U values, and cross-lagged correlation. All participants improved significantly on PQ and the symptom preoccupation measure. Two improved significantly on the symptom believability measure. Cross-lagged correlation analyses showed no clear mediation. Change in proposed processes of change and primary outcome predominantly happened concomitantly, although patterns of results reflected individual differences.

STCGRU: A hybrid model based on CNN and BiGRU for mild cognitive impairment diagnosis

BACKGROUND AND OBJECTIVE

Early diagnosis of mild cognitive impairment (MCI) is one of the essential measures to prevent its further development into Alzheimer's disease (AD). In this paper, we propose a hybrid deep learning model for early diagnosis of MCI, called spatio-temporal convolutional gated recurrent unit network (STCGRU).

METHODS

The STCGRU comprises three bespoke convolutional neural network (CNN) modules and a bi-directional gated recurrent unit (BiGRU) module, which can effectively extract the spatial and temporal features of EEG and obtain excellent diagnostic results. We use a publicly available EEG dataset that has not undergone pre-processing to verify the robustness and accuracy of the model. Ablation experiments on STCGRU are conducted to showcase the individual performance improvement of each module.

RESULTS

Compared with other state-of-the-art approaches using the same publicly available EEG dataset, the results show that STCGRU is more suitable for early diagnosis of MCI. After 10-fold cross-validation, the average classification accuracy of the hybrid model reached 99.95 %, while the average kappa value reached 0.9989.

CONCLUSIONS

The experimental results show that the hybrid model proposed in this paper can directly extract compelling spatio-temporal features from the raw EEG data for classification. The STCGRU allows for accurate diagnosis of patients with MCI and has a high practical value.

Association between visual impairment and suicide: A systematic review and meta-analysis

Visual impairment severely impacts the life of the patients. In this study, we systematically reviewed studies on the potential relationship between visual impairment and suicidal behaviour, and conducted meta-analyses on the risk estimates. We searched 11 literature databases on 20 October 2022 and identified a total of 10 eligible studies with 5.8 million participants. Suicide behaviour was investigated according to three domains: suicide ideation, suicide attempt and suicide death. In the 10 eligible studies, seven reported data on suicide ideation, five reported data on suicide attempt, and three reported data on suicide death. All summary estimates extracted for use in the meta-analyses were adjusted estimates of association since we acknowledged that depression as well as other confounding factors may play an important role. We found that visual impairment was a significant risk factor of suicide ideation (OR 1.83; 95% CI: 1.40-2.40; p = 0.000012), suicide attempt (OR 2.62; 95% CI: 1.29-5.31; p = 0.0077) and suicide death (OR 7.00; 95% CI: 2.30-21.4; p = 0.000063). These high increases in risk of suicide from visual impairment underscore the importance of eye health on the overall mental health, and the potential devastating consequences of insufficient access to eye care, lack of treatment possibilities for any reason or low political priority of eye care.

Bayesian cell therapy process optimization

Optimizing complex bioprocesses poses a significant challenge in several fields, particularly in cell therapy manufacturing. The development of customized, closed, and automated processes is crucial for their industrial translation and for addressing large patient populations at a sustainable price. Limited understanding of the underlying biological mechanisms, coupled with highly resource-intensive experimentation, are two contributing factors that make the development of these next-generation processes challenging. Bayesian optimization (BO) is an iterative experimental design methodology that addresses these challenges, but has not been extensively tested in situations that require parallel experimentation with significant experimental variability. In this study, we present an evaluation of noisy, parallel BO for increasing noise levels and parallel batch sizes on two in silico bioprocesses, and compare it to the industry state-of-the-art. As an in vitro showcase, we apply the method to the optimization of a monocyte purification unit operation. The in silico results show that BO significantly outperforms the state-of-the-art, requiring approximately 50% fewer experiments on average. This study highlights the potential of noisy, parallel BO as valuable tool for cell therapy process development and optimization.

Establishing an updated consensus on the conceptual and operational definitions of Making Every Contact Count (MECC) across experts within research and practice: an international Delphi Study

OBJECTIVES

The Making Every Contact Count (MECC) initiative is broadly defined as an opportunistic approach to prevention by making use of the thousands of conversations service providers have with service users every day. However, since its conception, the application of MECC has diverged and developed considerably. Thus, the current study aimed to revise the definition according to current research and practice to better describe what is and is not included.

STUDY DESIGN

A consensus building classic Delphi methodology, completed by an expert panel.

METHODS

Round 1 asked open questions around the definition of MECC. Content analysis of round 1 identified statements that were rated for agreement in round 2. Statements achieving ≥80% agreement were included in a short, long, or operational definition of MECC that were rated for agreement in round 3 (the minimum number required). An agreement of ≥80% indicated consensus.

RESULTS

Forty out of 100 contacted experts completed three rounds. Experts in practice and research were recruited internationally although most were from England. From round 1, 274 statements were generated, of which 96 achieved consensus and were included within round 3. The short and long definition received consensus in round 3, the operational definition required four rounds to reach consensus.

CONCLUSIONS

MECC is a person-centred approach to health behaviour change that, provided an individual possesses the relevant skills, can be delivered by anyone and anywhere. The distinguishing feature of MECC is not in its duration, target behaviour, or conditions for delivery, but rather in the approach taken and the mechanisms applied to conversations. Implications for research and practice are discussed, and the limits for applicability acknowledged.

Ageism in Birthday Cards: A Mixed-Method Content Analysis

BACKGROUND AND OBJECTIVES

Ageism is oftentimes sugarcoated within humor. Paper birthday cards are 1 delivery approach in which ageist messages are perpetuated and reinforced through humor.

RESEARCH DESIGN AND METHODS

A convenience sample of birthday cards (k = 227), all indicating a decade of age, were acquired from 7 national retail stores in Colorado Springs, CO. The decades sampled ranged from 21 to 100. With a predeveloped codebook, 3 raters coded the decade birthday cards on various variables, including age group, ageist tone, and humor.

RESULTS

Birthday cards intended for age 30-60 contained significantly more ageist messages compared to cards intended for age 21 and age 70-100, which did not show a significant difference from each other. Additionally, birthday cards with humor showed more ageist messages than cards without humor. Characteristics of decade birthday cards were also explored.

DISCUSSION AND IMPLICATIONS

Consumers need to learn to evaluate these ageist messages in birthday cards to reduce the perpetuation of damaging stereotypes.

Enhancing drug development and clinical studies with patient-centric sampling using microsampling techniques: Opportunities, challenges, and insights into liquid chromatography-mass spectrometry strategies

Microsampling has revolutionized pharmaceutical drug development and clinical research by reducing sample volume requirements, allowing sample collection at home or nontraditional sites, minimizing animal and patient burden, and enabling more flexible study designs. This perspective paper discusses the transformative impact of microsampling and patient-centric sampling (PCS) techniques, emphasizing their advantages in drug development and clinical trials. We highlight the integration of liquid chromatography-mass spectrometry (LC-MS) strategies for analyzing PCS samples, focusing on our research experience and a review of current literatures. The paper reviews commercially available PCS devices, their regulatory status, and their application in clinical trials, underscoring the benefits of PCS in expanding patient enrollment diversity and improving study designs. We also address the operational challenges of implementing PCS, including the need for bridging studies to ensure data comparability between traditional and microsampling methods, and the analytical challenges posed by PCS samples. The paper proposes future directions for PCS, including the development of global regulatory standards, technological advancements to enhance user experience, the increased concern of sustainability and patient data privacy, and the integration of PCS with other technologies for improved performance in drug development and clinical studies. By advancing microsampling and PCS techniques, we aim to foster patient-centric approaches in pharmaceutical sciences, ultimately enhancing patient care and treatment efficacy.

Assessing the Landscape of Lactation Education: Results of a Pilot Survey

BACKGROUND

The field of lactation currently uses breastfeeding rates to measure effectiveness. While monitoring breastfeeding outcomes can provide insight into the successes of lactation consulting as a profession, the improvement of breastfeeding outcomes is a multifactorial issue. In order to facilitate the growth of lactation education processes, understanding experiences during training and perceptions of readiness of current International Board Certified Lactation Consultants (IBCLC) for clinical practice is necessary.

RESEARCH AIM

The aim of this survey was to provide a baseline assessment of the current landscape of the lactation profession through data related to certification, job market, practice confidence after passing the International Board of Lactation Consultant Examiners (IBLCE) certifying examination, and perceptions of specializations.

METHODS

A cross-sectional study design was used to assess the experiences of practicing IBCLCs. Non-probability convenience sampling was implemented from December 2021 through January 2022. A total of 281 unique responses were recorded with complete data on variables of interest.

RESULTS

The majority of respondents were white females under age 50 located in the United States. The majority of respondents were certified through a Pathway 1. The largest barrier to certification was reported to be a lack of clinical/mentorship opportunities. Respondents were significantly more confident in providing entry-level support to dyads when mentored by four or more preceptors.

CONCLUSION

Diversification of the field of lactation is necessary to provide appropriate support to lactating families in the United States. Additionally, addressing the barrier of accessing clinical/mentorship opportunities is essential for continued growth of the field of lactation.

The effect of a stress management program on first-year nursing students' clinical stress: A randomized controlled experimental study

BACKGROUND

Clinical clerkships lie at the core of nursing education and are crucial for developing professional skills. However, nursing students, especially freshmen, often encounter significant stress during their clinical experiences.

OBJECTIVES

This study investigated the effect of a stress management program on first-year nursing students' clinical stress levels.

DESIGN

This randomized controlled experimental study adopted a pretest-posttest-follow-up test research design.

SETTINGS AND PARTICIPANTS

Participants were recruited using simple randomization. The sample consisted of 64 first-year nursing students (intervention = 32; control = 32) from the nursing department of the faculty of health sciences of a university in Türkiye.

METHODS

Participants were randomized into intervention and control groups. The intervention group attended a stress management program, one weekly session for five weeks (intervention). The research was conducted between 21.02.2022 and 20.05.2022. Data were collected using a personal information form, the Perceived Stress Scale, the Physio-Psycho-Social Response Scale, and the Coping Behavior Inventory. The data were collected pretest and posttest the intervention and two months follow-up test. The data were analyzed using the two-way repeated measures analysis of variance (ANOVA).

RESULTS

The changes in the Perceived Stress Scale mean scores, group*time interaction, were statistically significant (p < 0.05). The results showed that the changes in the Coping Behavior Inventory "problem-solving" subscale mean scores, group*time interaction, were statistically significant (p < 0.05). The multiple comparisons showed a statistically significant difference in posttest Physio-Psycho-Social Response Scale "social behavioral symptoms" and "emotional symptoms" subscale scores between the intervention and control groups (p < 0.05). The multiple comparisons showed a statistically significant difference in posttest Coping Behavior Inventory "problem-solving" and "avoidance" subscale scores between the intervention and control groups (p < 0.05).

CONCLUSION

The stress management program helps first-year nursing students experience less stress and develop problem-solving skills before they perform clinical clerkships. It also allows them to suffer from fewer emotional and social behavioral symptoms and exhibit fewer avoidance behaviors.