Research Development Using REDCap Software

Garcia, Klauss Kleydmann Sabino; Abrahão, Amanda Amaral

doi:10.4258/hir.2021.27.4.341

Cited by 28 publications

(24 citation statements)

References 17 publications

(32 reference statements)

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“…This platform allows one to create questionnaire links, consent terms, and store the data collected in a secure web system. The utilization of electronic data capture (EDC) systems is recommended to optimize research data through proper management (Garcia & Abrahão, 2021). REDCap is a web application that can facilitate clinical research development, mainly in the health field, and reduce the costs of conducting research (Garcia & Abrahão, 2021;Walther et al, 2011).…”

Section: Study Design and Settingmentioning

confidence: 99%

“…The utilization of electronic data capture (EDC) systems is recommended to optimize research data through proper management (Garcia & Abrahão, 2021). REDCap is a web application that can facilitate clinical research development, mainly in the health field, and reduce the costs of conducting research (Garcia & Abrahão, 2021;Walther et al, 2011). Its tools allow researchers to make the best use of EDC components such as data storage.…”

Section: Study Design and Settingmentioning

confidence: 99%

See 1 more Smart Citation

Cognitive and psychological factors associated with severe insomnia in Brazilian women: a cross-sectional study

Rafihi‐Ferreira

Carmo

Bassolli

et al. 2022

Psicol. Refl. Crít.

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Insomnia is the most prevalent sleep disorder in women. Sociodemographic, cognitive, and psychological factors may contribute to its severity. This study evaluated factors associated with severe insomnia in women with insomnia complaints. We evaluated 530 women aged 18–59 (mean = 40.5, SD = 10.2), who experienced insomnia complaints, using self-report instruments. Severe insomnia was defined as a score above 21 on the Insomnia Severity Index. Age, marital status, educational level, depression and anxiety, psychological inflexibility, and beliefs about sleep were assessed as potential factors associated with severe insomnia. Simple and multivariate analyses were conducted using binary logistic regression. Low education level (odds ratio; OR = 1.85 [1.27–2.69]), depression (OR = 2.17 [1.27–3.81]), psychological inflexibility (OR = 1.05 [1.02–1.08]), and dysfunctional beliefs about sleep (OR = 1.04 [1.02–1.06]) were factors associated with severe insomnia scores in the multiple logistic regression model. These findings are important from a public health perspective, because behavioral strategies designed to treat insomnia with a focus on cognitive and psychological factors are low-cost treatments and may help improve sleep quality in women, which also influences mental health.

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Section: Study Design and Settingmentioning

confidence: 99%

Section: Study Design and Settingmentioning

confidence: 99%

Cognitive and psychological factors associated with severe insomnia in Brazilian women: a cross-sectional study

Rafihi‐Ferreira

Carmo

Bassolli

et al. 2022

Psicol. Refl. Crít.

View full text Add to dashboard Cite

show abstract

“…Clinical data collected will be those in the paper medical record. With the consent of the patient or his/her family member/caregiver/legal guardian, the data will be entered anonymously into a computerized database using REDCap (Research Electronic Data Capture) ( 38 ), a web application for building and managing research databases. The use of a dedicated tool allows for robust data collection, data quality checks, and the reduction of missing data.…”

Section: Methodsmentioning

confidence: 99%

Design and implementation of a Stroke Rehabilitation Registry for the systematic assessment of processes and outcomes and the development of data-driven prediction models: The STRATEGY study protocol

et al. 2022

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BackgroundStroke represents the second preventable cause of death after cardiovascular disease and the third global cause of disability. In countries where national registries of the clinical quality of stroke care have been established, the publication and sharing of the collected data have led to an improvement in the quality of care and survival of patients. However, information on rehabilitation processes and outcomes is often lacking, and predictors of functional outcomes remain poorly explored. This paper describes a multicenter study protocol to implement a Stroke rehabilitation Registry, mainly based on a multidimensional assessment proposed by the Italian Society of Physical and Rehabilitation Medicine (PMIC2020), in a pilot Italian cohort of stroke survivors undergoing post-acute inpatient rehabilitation, to provide a systematic assessment of processes and outcomes and develop data-driven prediction models of functional outcomes.MethodsAll patients with a diagnosis of ischemic or haemorrhagic stroke confirmed by clinical assessment, admitted to intensive rehabilitation units within 30 days from the acute event, aged 18+, and providing informed consent will be enrolled. Measures will be taken at admission (T0), at discharge (T1), and at follow-up, 3 months (T2) and 6 months (T3) after the stroke. Assessment variables include anamnestic data, clinical and nursing complexity information and measures of body structures and function, activity and participation (PMIC2020), rehabilitation interventions, adverse events and discharge data. The modified Barthel Index will be our primary outcome. In addition to classical biostatistical analysis, learning algorithms will be cross-validated to achieve data-driven prognosis prediction models.ConclusionsThis study will test the feasibility of a stroke rehabilitation registry in the Italian health context and provide a systematic assessment of processes and outcomes for quality assessment and benchmarking. By the development of data-driven prediction models in stroke rehabilitation, this study will pave the way for the development of decision support tools for patient-oriented therapy planning and rehabilitation outcomes maximization.Clinical tial registrationThe registration on ClinicalTrials.gov is ongoing and under review. The identification number will be provided when the review process will be completed.

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“…We did not have any polyclinical follow up for the neonates that were discharged prior to day 7 of life. Data were subsequently transferred from the case report forms into an electronic database (RedCap, Vanderbilt, USA) by a trained research assistant 20 .…”

Section: Methodsmentioning

confidence: 99%

Endotracheal intubation performance at a large obstetric hospital delivery room, Hanoi, Vietnam

Dempsey

Nguyen²,

Nguyen³

et al. 2022

Resuscitation Plus

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Research Development Using REDCap Software

Cited by 28 publications

References 17 publications

Cognitive and psychological factors associated with severe insomnia in Brazilian women: a cross-sectional study

Cognitive and psychological factors associated with severe insomnia in Brazilian women: a cross-sectional study

Design and implementation of a Stroke Rehabilitation Registry for the systematic assessment of processes and outcomes and the development of data-driven prediction models: The STRATEGY study protocol

Endotracheal intubation performance at a large obstetric hospital delivery room, Hanoi, Vietnam

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