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Objectives: The Hypoglycemia During Hospitalization (HyDHo) score predicts hypoglycemia in a population of Canadian inpatients by assigning various weightings to 5 key clinical criteria known at the time of admission, in particular age, recent presentation to an emergency department, insulin use, use of oral hypoglycemic agents, and chronic kidney disease. Our aim in this study was to externally validate the HyDHo score by applying this risk calculator to an Australian population of inpatients with diabetes., Methods: This study was a retrospective data analysis of a subset of the Diabetes IN-hospital: Glucose & Outcomes (DINGO) cohort. The HyDHo score was applied based on clinical information known at the time of admission to stratify risk of inpatient hypoglycemia., Results: The HyDHo score was applied to 1,015 patients, generating a receiver-operating characteristic c-statistic of 0.607. A threshold of ≥9, as per the original study, generated a sensitivity of 83% and a specificity of 20%. A threshold of ≥10, to better suit this Australian population, generated a sensitivity of 90% and a specificity of 34%. The HyDHo score has been externally valid in a geographically different population; in fact, it outperformed the original study after accounting for local hypoglycemia rates., Conclusions: Our findings support the external validity of the HyDHo score in a geographically different population. Application of this simple and accessible tool can serve as an adjunct to predict an inpatient's risk of hypoglycemia and guide more appropriate glucose monitoring and diabetes management., (Copyright © 2024 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.)

Psychological research frequently encounters criticism regarding the representativeness of the samples under study, highlighting concerns about the external validity of the obtained results. Here, we conducted a comprehensive survey of all the quantitative samples from the journal Body Image for 2021 (n = 149 samples). Our primary objective was to examine the extent to which the sampled populations deviated from the population at large, which could potentially compromise the generalizability of findings. We identified that a substantial number of these samples came from student populations (n = 44) and the majority were from the United States, United Kingdom, and Australia. Only a small number of samples (n = 9) employed direct measurements of body mass index (BMI), while the majority relied on self-reported data (n = 93). For a subset of samples in the journal, which were drawn from the general population, we compared whether these differed from population reference values in terms of age and BMI. Using Monte Carlo simulations, we found that samples tended to be younger and score lower on BMI than reference values obtained from the broader population. Samples drawn from female university students also tended to be lower on BMI than age-matched reference samples. We discuss the implications of our findings and make recommendations on sampling and inference. We conclude that a clearer specification of the parameters or conditions under which findings are expected to generalise has the potential to enhance the overall rigor and validity of this field of research., Competing Interests: Declaration of Competing Interest No conflict of interests are known to the authors., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: The external validity, or generalizability, of trials and guidelines has been considered poor in the context of multiple morbidity. How multiple morbidity might affect the magnitude of benefit of a given treatment, and thereby external validity, has had little study. Objective: To provide a method of decision analysis to quantify the effects of age and comorbidity on the probability of deriving a given magnitude of treatment benefit. Design: We developed a method to calculate probabilistically the effect of all of a patient's comorbidities on their underlying utility, or well-being, at a future time point. From this, we derived a distribution of possible magnitudes of treatment benefit at that future time point. We then expressed this distribution as the probability of deriving at least a given magnitude of treatment benefit. To demonstrate the applicability of this method of decision analysis, we applied it to the treatment of hypercholesterolaemia in a geriatric population of 50 individuals. We highlighted the results of four of these individuals. Results: This method of analysis provided individualized quantifications of the effect of age and comorbidity on the probability of treatment benefit. The average probability of deriving a benefit, of at least 50% of the magnitude of benefit available to an individual without comorbidity, was only 0.8%. Conclusion: The effects of age and comorbidity on the probability of deriving significant treatment benefits can be quantified for any individual. Even without consideration of other factors affecting external validity, these effects may be sufficient to guide decision-making. [ABSTRACT FROM AUTHOR]

Objectives: For the Center for Epidemiologic Studies Depression Scale (CES-D) ratings, the study examined support for a bifactor model, and also the internal consistency reliability and external validity of the factors in this model. Method: Participants (N = 1,178) were older adults from the general community who completed the CES-D. Results: Confirmatory factor analysis of their ratings indicated support for the bifactor model. For this model, the general factor explained most of the covariance in the scores of the CES-D items for Depressed Affect, Somatic Symptoms and Retarded Activity, and Interpersonal Difficulties items. Most of the covariance in the scores of the Positive Affect (PA) scale was explained by its own specific factor. Additional analyses showed support for internal consistencies and external validities of general factors based on all the CES-D items, and when PA items were excluded, and also the PA-specific factor. Discussion: The findings support the use of a total CES-D score without the PA items and also the concurrent use of the PA scale score. [ABSTRACT FROM PUBLISHER]

Abstract: This paper tests both the internal and external validity of the brand equity framework using two measurement modelling approaches, namely the relatively new Best-Worst scaling (BWS) method () and the more traditional confirmatory factor analysis (CFA) method. Data were collected from the Australian banking and mobile services sectors. We find the measurement models derived from BWS outperformed the models based on CFA of the rating data in predicting both stated and real brand choices. The findings have implications for both academics and practitioners in brand equity measurement and management. [Copyright &y& Elsevier]

Background: Randomized controlled trials (RCTs) with vigorous study designs are vital for determining the efficacy of treatments. Despite the high internal validity attributed to RCTs, external validity concerns limit the generalizability of results to the general population. Bias can be introduced, for example, when study participants who self-select into a trial are more motivated to comply with study conditions than are other individuals. These external validity considerations extend to e-mental health (eMH) research, especially when eMH tools are designed for public access and provide minimal or no supervision., Objective: Clustering techniques were employed to identify engagement profiles of RCT participants and community users of a self-guided eMH program. This exploratory approach inspected actual, not theorized, RCT participant and community user engagement patterns. Both samples had access to the eMH program over the same time period and received identical usage recommendations on the eMH program website. The aim of this study is to help gauge expectations of similarities and differences in usage behaviors of an eMH tool across evaluation and naturalistic contexts., Methods: Australian adults signed up to myCompass, a self-guided online treatment program created to reduce mild to moderate symptoms of negative emotions. They did so either by being part of an RCT onboarding (160/231, 69.6% female) or by accessing the program freely on the internet (5563/8391, 66.30% female) between October 2011 and October 2012. During registration, RCT participants and community users provided basic demographic information. Usage metrics (number of logins, trackings, and learning activities) were recorded by the system., Results: Samples at sign-up differed significantly in age (P=.003), with community users being on average 3 years older (mean 41.78, SD 13.64) than RCT participants (mean 38.79, SD 10.73). Furthermore, frequency of program use was higher for RCT participants on all usage metrics compared to community users through the first 49 days after registration (all P values <.001). Two-step cluster analyses revealed 3 user groups in the RCT sample (Nonstarters, 10-Timers, and 30+-Timers) and 2 user groups in the community samples (2-Timers and 20-Timers). Groups seemed comparable in patterns of use but differed in magnitude, with RCT participant usage groups showing more frequent engagement than community usage groups. Only the high-usage group among RCT participants approached myCompass usage recommendations., Conclusions: Findings suggested that external validity concerns of RCT designs may arise with regards to the predicted magnitude of eMH program use rather than overall usage styles. Following up RCT nonstarters may help provide unique insights into why individuals choose not to engage with an eMH program despite generally being willing to participate in an eMH evaluation study. Overestimating frequency of engagement with eMH tools may have theoretical implications and potentially impact economic considerations for plans to disseminate these tools to the general public., (©Samineh Sanatkar, Peter Baldwin, Kit Huckvale, Helen Christensen, Samuel Harvey. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 11.03.2021.)

Objective: To describe the challenges in recruitment of a national sample of young Australian women for a study of their physical and psychological wellbeing., Methods: Women, aged 18 to 39 years, were invited by email to complete an online questionnaire and, if not using systemic hormones, pregnant or breast feeding, to provide a blood sample., Results: A total of 94,546 email invitations were sent. Follow-up of 1,000 randomly selected non-responders by text message recruited 15 additional women. Direct telephoning resulted in another 516 completed questionnaires from a further 3,614 randomly selected non-responders. In all, 6,986 women completed the questionnaire and blood samples were provided by 761 (20.6%) of 3,689 eligible participants. The study sample is similar to women within the target age range captured by the Australian Census for their state of residence in terms of age distribution, education, relationship status, employment and occupation., Conclusions: Recruitment, by predominantly electronic means, has achieved a large, representative study sample of young women recruited from the eastern states of Australia. Implications for public health: Recruitment of a representative study sample can be achieved in the absence of a high response rate., (© 2019 The Authors.)

Background: Younger adults are difficult to engage in preventive health, yet in Australia they are gaining more weight and increasing in waist circumference faster than middle-to-older adults. A further challenge to engaging 18- to 35-year-olds in interventions is the limited reporting of outcomes of recruitment strategies. Objective: This paper describes the outcomes of strategies used to recruit young adults to a randomized controlled trial (RCT), healthy lifestyle mHealth program, TXT2BFiT, for prevention of weight gain. The progression from enquiry through eligibility check to randomization into the trial and the costs of recruitment strategies are reported. Factors associated with nonparticipation are explored. Methods: Participants were recruited either via letters of invitation from general practitioners (GPs) or via electronic or print advertisements, including Facebook and Google -- social media and advertising -- university electronic newsletters, printed posters, mailbox drops, and newspapers. Participants recruited from GP invitation letters had an appointment booked with their GP for eligibility screening. Those recruited from other methods were sent an information pack to seek approval to participate from their own GP. The total number and source of enquiries were categorized according to eligibility and subsequent completion of steps to enrolment. Cost data and details of recruitment strategies were recorded. Results: From 1181 enquiries in total from all strategies, 250 (21.17%) participants were randomized. A total of 5311 invitation letters were sent from 12 GP practices -- 16 participating GPs. A total of 131 patients enquired with 68 participants randomized (68/74 of those eligible, 92%). The other recruitment methods yielded the remaining 182 randomized participants. Enrolment from print media was 26% of enquiries, from electronic media was 20%, and from other methods was 3%. Across all strategies the average cost of recruitment was Australian Dollar (AUD) $139 per person. The least expensive modality was electronic (AUD $37), largely due to a free feature story on one university Web home page, despite Facebook advertising costing AUD $945 per enrolment. The most expensive was print media at AUD $213 and GP letters at AUD $145 per enrolment. Conclusions: The research indicated that free electronic media was the most cost-effective strategy, with GP letters the least expensive of the paid strategies in comparison to the other strategies. This study is an important contribution for future research into efficacy, translation, and implementation of cost-effective programs for the prevention of weight gain in young adults. Procedural frameworks for recruitment protocols are required, along with systematic reporting of recruitment strategies to reduce unnecessary expenditure and allow for valuable public health prevention programs to go beyond the research setting. [ABSTRACT FROM AUTHOR]