Calibration and XGBoost reweighting to reduce coverage and non-response biases in overlapping panel surveys: application to the Healthcare and Social Survey.

BACKGROUND: Surveys have been used worldwide to provide information on the COVID-19 pandemic impact so as to prepare and deliver an effective Public Health response. Overlapping panel surveys allow longitudinal estimates and more accurate cross-sectional estimates to be obtained thanks to the larger sample size. However, the problem of non-response is particularly aggravated in the case of panel surveys due to population fatigue with repeated surveys. OBJECTIVE: To develop a new reweighting method for overlapping panel surveys affected by non-response. METHODS: We chose the Healthcare and Social Survey which has an overlapping panel survey design with measurements throughout 2020 and 2021, and random samplings stratified by province and degree of urbanization. Each measurement comprises two samples: a longitudinal sample taken from previous measurements and a new sample taken at each measurement. RESULTS: Our reweighting methodological approach is the result of a two-step process: the original sampling design weights are corrected by modelling non-response with respect to the longitudinal sample obtained in a previous measurement using machine learning techniques, followed by calibration using the auxiliary information available at the population level. It is applied to the estimation of totals, proportions, ratios, and differences between measurements, and to gender gaps in the variable of self-perceived general health. CONCLUSION: The proposed method produces suitable estimators for both cross-sectional and longitudinal samples. For addressing future health crises such as COVID-19, it is therefore necessary to reduce potential coverage and non-response biases in surveys by means of utilizing reweighting techniques as proposed in this study.

Sex differences in the effectiveness and tolerability of dolutegravir plus rilpivirine as a switch strategy in people living with HIV.

INTRODUCTION: Dolutegravir + rilpivirine (DTG + RPV) is an effective antiretroviral therapy regimen approved in clinical guidelines as a switch therapy for virologically suppressed people with HIV. Our study aimed to compare the effectiveness and tolerability of DTG + RPV in women and men in real-world clinical practice. METHODS: This was a retrospective analysis of treatment-experienced people with HIV from a large HIV unit who switched to DTG + RPV. We analysed treatment effectiveness, rates of adverse events and discontinuation, and metabolic changes after 48 weeks of treatment. HIV-RNA levels <50 copies/mL were analysed at 48 weeks using both intention-to treat analysis (where missing data were interpreted as failures) and per-protocol analysis (excluding those with missing data or changes due to reasons other than virological failure). Outcomes were compared between women and men based on sex at birth. RESULTS: A total of 307 patients were selected (71 women and 236 men). No transgender people were included. At baseline, women had lived with HIV infection and received antiretroviral therapy for longer than men (23.2 vs 17.4 years and 18.9 vs 14.2 years, respectively). In the intention-to-treat analysis, 74.6% (95% confidence interval [CI] 63.4-83.3%) of women and 83.5% (95% CI 78.2-87.7) of men had HIV-RNA <50 copies/mL. In the per-protocol analysis, 96.4% (95% CI 87.7-99) of women and 99% (95% CI 98.9-99.7) of men had HIV-RNA levels <50 copies/mL. Two women and two men had HIV-RNA >50 copies/mL at 48 weeks. Discontinuation due to adverse events was more frequent in women than in men: 12.7% vs 7.2% (p < 0.02). Neuropsychiatric and gastrointestinal events were the most frequently reported. A median (interquartile range) weight gain of 1.9 kg (0-4.2) in women and 1.2 kg (-1-3.1) in men was reported (median of differences between baseline visit and week 48); the remaining changes in metabolic parameters were neutral. CONCLUSIONS: DTG + RPV exhibited good and similar virological effectiveness in women and men in real-world settings. However, poorer tolerability and more treatment interruptions were observed in women.

Use of the Therapy App Prescinde for Increasing Adherence to Smoking Cessation Treatment.

Tobacco use poses major health risks and is a major contributor to causes of death worldwide. Mobile phone-based cessation apps for this substance are gaining popularity, often used as a component of traditional interventions. This study aimed to analyze adherence to an intervention using a mobile phone application (App-therapy Prescinde (v1)) as a function of sociodemographic variables (age, gender, educational level, and profession) as well as the primary activities supported by the app (reducing tobacco or cannabis use and increasing physical exercise). The participants were recruited through the web pages of the Occupational Risk Prevention Service and the Psychology Clinic of the University of Granada during the COVID-19 confinement period. The application's contents include three components (self-report, motivational phrases, and goal setting). Our findings indicate that being male, being aged between 26 and 62, having a high school education, and being unemployed increase the likelihood of adherence to the Prescinde therapy app three months after usage. Our findings highlight the importance of developing new therapeutic approaches and conducting in-depth studies on the factors associated with adherence to tobacco cessation and cannabis cessation treatments via mobile phone applications.

Scoping review of the methodology of large health surveys conducted in Spain early on in the COVID-19 pandemic.

Background: The use of health surveys has been key in the scientific community to promptly communicate results about the health impact of COVID-19. But what information was collected, where, when and how, and who was the study population? Objective: To describe the methodological characteristics used in large health surveys conducted in Spain early on in the COVID-19 pandemic. Methods: Scoping review. Inclusion criteria: observational studies published between January 2020 and December 2021, with sample sizes of over 2,000 persons resident in Spain. Databases consulted: PubMed, CINAHL, Literatura Latinoamericana y del Caribe en CC de la Salud, Scopus, PsycINFO, Embase, Sociological Abstracts, Dialnet and Web of Science Core Collection. We analyzed the characteristics of the literature references, methodologies and information gathered in the surveys selected. Fifty five studies were included. Results: Sixty percentage of the studies included had mental health as their main topic and 75% were conducted on the general adult population. Thirteen percentage had a longitudinal design, 93% used the internet to gather information and the same percentage used non-probability sampling. Thirty percentage made some type of sampling correction to reduce coverage or non-response biases, but not selection biases. Sixty seven percentage did not state the availability of their data. Conclusions: Consistent with the extensive use of non-probability sampling without any bias correction in the extraordinary setting created by COVID-19, quality population frameworks are required so that probability and representative samples can be extracted quickly to promptly address other health crises, as well as to reduce potential coverage, non-response and particularly selection biases by utilizing reweighting techniques. The low data accessibility despite the huge opportunity that COVID-19 provided for Open Science-based research is striking.

A unified approach based on multidimensional scaling for calibration estimation in survey sampling with qualitative auxiliary information.

Survey calibration is a widely used method to estimate the population mean or total score of a target variable, particularly in medical research. In this procedure, auxiliary information related to the variable of interest is used to recalibrate the estimation weights. However, when the auxiliary information includes qualitative variables, traditional calibration techniques may be not feasible or the optimisation procedure may fail. In this article, we propose the use of linear calibration in conjunction with a multidimensional scaling-based set of continuous, uncorrelated auxiliary variables along with a suitable metric in a distance-based regression framework. The calibration weights are estimated using a projection of the auxiliary information on a low-dimensional Euclidean space. The approach becomes one of the linear calibration with quantitative variables avoiding the usual computational problems in the presence of qualitative auxiliary information. The new variables preserve the underlying assumption in linear calibration of a linear relationship between the auxiliary and target variables, and therefore the optimal properties of the linear calibration method remain true. The behaviour of this approach is examined using a Monte Carlo procedure and its value is illustrated by analysing real data sets and by comparing its performance with that of traditional calibration procedures.

Enhancing estimation methods for integrating probability and nonprobability survey samples with machine-learning techniques. An application to a Survey on the impact of the COVID-19 pandemic in Spain.

Web surveys have replaced Face-to-Face and computer assisted telephone interviewing (CATI) as the main mode of data collection in most countries. This trend was reinforced as a consequence of COVID-19 pandemic-related restrictions. However, this mode still faces significant limitations in obtaining probability-based samples of the general population. For this reason, most web surveys rely on nonprobability survey designs. Whereas probability-based designs continue to be the gold standard in survey sampling, nonprobability web surveys may still prove useful in some situations. For instance, when small subpopulations are the group under study and probability sampling is unlikely to meet sample size requirements, complementing a small probability sample with a larger nonprobability one may improve the efficiency of the estimates. Nonprobability samples may also be designed as a mean for compensating for known biases in probability-based web survey samples by purposely targeting respondent profiles that tend to be underrepresented in these surveys. This is the case in the Survey on the impact of the COVID-19 pandemic in Spain (ESPACOV) that motivates this paper. In this paper, we propose a methodology for combining probability and nonprobability web-based survey samples with the help of machine-learning techniques. We then assess the efficiency of the resulting estimates by comparing them with other strategies that have been used before. Our simulation study and the application of the proposed estimation method to the second wave of the ESPACOV Survey allow us to conclude that this is the best option for reducing the biases observed in our data.

Impact of COVID-19 on the Health of the General and More Vulnerable Population and Its Determinants: Health Care and Social Survey-ESSOC, Study Protocol.

This manuscript describes the rationale and protocol of a real-world data (RWD) study entitled Health Care and Social Survey (ESSOC, Encuesta Sanitaria y Social). The study's objective is to determine the magnitude, characteristics, and evolution of the COVID-19 impact on overall health as well as the socioeconomic, psychosocial, behavioural, occupational, environmental, and clinical determinants of both the general and more vulnerable population. The study integrates observational data collected through a survey using a probabilistic, overlapping panel design, and data from clinical, epidemiological, demographic, and environmental registries. The data will be analysed using advanced statistical, sampling, and machine learning techniques. The study is based on several measurements obtained from three random samples of the Andalusian (Spain) population: general population aged 16 years and over, residents in disadvantaged areas, and people over the age of 55. Given the current characteristics of this pandemic and its future repercussions, this project will generate relevant information on a regular basis, commencing from the beginning of the State of Alarm. It will also establish institutional alliances of great social value, explore and apply powerful and novel methodologies, and produce large, integrated, high-quality and open-access databases. The information described here will be vital for health systems in order to design tailor-made interventions aimed at improving the health care, health, and quality of life of the populations most affected by the COVID-19 pandemic.

Indirect questioning methods for sensitive survey questions: Modelling criminal behaviours among a prison population.

Information such as the prevalence and frequency of criminal behaviour is difficult to estimate using standard survey techniques because of the tendency of respondents to withhold or misrepresent information. Social desirability bias is a significant threat to the validity of self-reported data, especially when supplied by persons such as sexual offenders or those convicted of theft or substance abuse. The randomized response approach is an alternative to the standard interview method and offers great potential for researchers in the field of criminal justice. By means of a survey of 792 prison inmates, incorporating both indirect and direct response techniques, we investigate if the prison population also has problems recognizing their participation in criminal acts such as theft, illicit drug use, violence against property, reckless driving and arson. Our research findings suggest that self-reported criminal behaviour among a prison population is affected by social desirability bias and that the behaviour considered is significantly associated with the severity of obsessive-compulsive symptoms. The results also demonstrate the inadequacy of traditional, yet widely used, direct questioning methods, and the great potential for indirect questioning techniques to advance policy formation and evaluation in the field of criminal behaviour.

Pacientes con hepatitis C perdidos en el sistema: aspectos éticos-legales y resultados de su búsqueda / No disponible

INTRODUCCIÓN: se conoce la existencia de pacientes con hepatitis C perdidos en el sistema, pero se desconocen su prevalencia y características. Además, su identificación colisiona con la barrera de la protección de datos. MÉTODOS: se presentó un protocolo de identificación y contacto al Comité de Ética Asistencial. Se obtendrían las serologías anti-VHC+ de Microbiología entre 2010-18. Se analizaría su situación en la base de datos hospitalaria y regional. Se clasificarían: a) hepatitis C crónica, si última determinación de ARN-VHC+; b) hepatitis C curada, si última determinación de ARN-VHC- tras 12 semanas de tratamiento; c) hepatitis C posible, si anti-VHC+ sin determinación de ARN-VHC. Se considerarían perdidos aquellos con hepatitis C crónica o posible sin seguimiento en Digestivo o Medicina Interna. Se contactaría con ellos mediante correo postal y, posteriormente, por teléfono para ofrecerles tratamiento. RESULTADOS: el Comité de Ética consideró que el protocolo cumplía los principios bioéticos de autonomía, beneficencia, no maleficencia y justicia, y que el contacto era éticamente deseable. Sobre 4.816 serologías anti-VHC+ identificamos 677 pacientes perdidos (14,06 %; IC 95 %: 13,2-15,2): edad 54 años, 61 % hombres, 12 % extranjeros y 95 % monoinfectados. Se consumieron 1,3 minutos en el estudio de cada serología. Un 25 % de las perdidas habían sido solicitadas por Digestivo o Medicina Interna. De los 677 perdidos, 228 (33,7 %) tenían también ARN-VHC+ y 449 (66,3 %) solo tenían solicitada la serología. CONCLUSIÓN: un número importante de pacientes con hepatitis C se encuentran perdidos en el sistema. Su búsqueda y contacto es posible desde el punto de vista ético-legal

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Patients with hepatitis C lost to follow-up: ethical-legal aspects and search results.

INTRODUCTION: data on the prevalence and characteristics of hepatitis C patients lost to follow-up are lacking. In addition, the identification of this population clashes with data protection regulations. METHODS: the identification and contact protocol was submitted to the Health Care Ethics Committee. The protocol was based on anti-HCV serology test results for 2010-2018, which were obtained from the Microbiology Department. In addition, the situation of the patients in the hospital and regional database was analyzed, based on the following classification: a) chronic hepatitis C, if the last HCV RNA determination was positive; b) cured hepatitis C, if the last HCV RNA determination was negative after 12 weeks of treatment; and c) possible hepatitis C, if anti-HCV antibodies were positive with no result for HCV RNA. Lost patients were defined as those with chronic or possible hepatitis C and no follow-up in the Digestive Diseases or Internal Medicine Departments. The patients were contacted by postal mail and then by telephone, so that they could be offered treatment. RESULTS: the Ethics Committee considered that the protocol fulfilled the bioethical principles of autonomy, beneficence, non-maleficence and justice and that contact was ethically desirable. From 4,816 positive anti-HCV serology results, 677 patients were identified who were lost to follow-up (14.06 %; 95 % CI, 13.2-15.2). The mean age was 54 years, 61 % were male, 12 % were foreign born and 95 % were mono-infected. The study of each serology result took 1.3 minutes. One-quarter (25 %) of the losses corresponded to the Digestive Diseases and Internal Medicine Departments. Of the 677 losses, serology testing had only been ordered for 449 patients (66.3 %) and the remaining 228 (33.7 %) also had a positive HCV RNA result. CONCLUSION: a large number of patients with hepatitis C are lost to follow-up. Searching for and contacting these patients is legally and ethically viable.

Bronconeumonía bilateral simulando descompensación cardíaca fácilmente detectada con ecografía multiventana / Bilateral bronchopneumonia simulating cardiac decompensation easily detected with multi-window ultrasound

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Point-of-care ultrasound in early detection of superior vena cava syndrome / Ecografía clínica en el diagnóstico precoz del síndrome de vena cava superior

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Propensity score adjustment using machine learning classification algorithms to control selection bias in online surveys.

Modern survey methods may be subject to non-observable bias, from various sources. Among online surveys, for example, selection bias is prevalent, due to the sampling mechanism commonly used, whereby participants self-select from a subgroup whose characteristics differ from those of the target population. Several techniques have been proposed to tackle this issue. One such is Propensity Score Adjustment (PSA), which is widely used and has been analysed in various studies. The usual method of estimating the propensity score is logistic regression, which requires a reference probability sample in addition to the online nonprobability sample. The predicted propensities can be used for reweighting using various estimators. However, in the online survey context, there are alternatives that might outperform logistic regression regarding propensity estimation. The aim of the present study is to determine the efficiency of some of these alternatives, involving Machine Learning (ML) classification algorithms. PSA is applied in two simulation scenarios, representing situations commonly found in online surveys, using logistic regression and ML models for propensity estimation. The results obtained show that ML algorithms remove selection bias more effectively than logistic regression when used for PSA, but that their efficacy depends largely on the selection mechanism employed and the dimensionality of the data.

La necesidad de contar con sistemas resilientes: A propósito de la creación de una unidad de gestión clínica para la reorganización de un hospital de tercer nivel durante una emergencia sanitaria / The need for resilient structures: on the creation of a clinic management unit for the reorganization of a tertiary hospital during a health emergency

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Temperament and characteristics related to nomophobia.

Nomophobia is defined as the fear of being out of mobile phone contact and is considered to be a phobia of the modern age. The current study set out to establish the relationship between temperament and personality and the development of nomophobia. The sample was composed of 968 participants selected from the Andalusian population, of which there were 182 males and 785 females aged from 23.19 years. The instruments used were the Questionnaire to Assess Nomophobia (QANIP; Olivencia-Carrión et al., 2018) and the Temperament and Character Inventory Revised (TCI-R; Cloninger et al., 1993). We found that cooperation is a characteristic that significantly reduces nomophobic levels, particularly for the two factors of Mobile Phone Addiction and Negative Consequences. Furthermore, Reward Dependence appears to be positively related to two of the factors involved in nomophobia, namely Mobile Phone Addiction and Loss of Control, suggesting a relationship between Nomophobia and personality. These findings are discussed in terms of their usefulness for identifying the personality predictors of nomophobia in order to develop preventive and intervention strategies.