Study designs and statistical approaches to suicide and prevention research in real-world data.

<bold>Objective: </bold>To provide researchers, clinicians and policy makers with a primer to study designs, statistical approaches and graphical reporting methods for suicide research in real world data (RWD).<bold>Methods: </bold>Study designs, statistical method and graphical reporting standards...

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Publicado en:Suicide & Life-Threatening Behavior Vol. 51; no. 1; pp. 127 - 137
Autores principales: Lavigne, Jill E., Lagerberg, Tyra, Ambrosi, John W., Chang, Zheng
Formato: journal article
Publicado: Wiley-Blackwell Feb2021
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Feb2021
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      pub: Wiley-Blackwell
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        148928418
        10.1111/sltb.12677
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        atl: Study designs and statistical approaches to suicide and prevention research in real-world data.
      aug:
        au:
          Lavigne, Jill E.
          Lagerberg, Tyra
          Ambrosi, John W.
          Chang, Zheng
        affil:
          Center of Excellence for Suicide Prevention, Department of Veterans Health Affairs, 400 Fort Hill Ave, Canandaigua 14424,, USA
          Wegmans School of Pharmacy, St John Fisher College, 3690 East Ave, Rochester NY, 14618,, USA
          Karolinska Institute, 171 77 Stockholm, Solna, Sweden
      su:
        Suicide prevention
        Suicidal behavior
        Experimental design
        Statistical models
        Sample size (Statistics)
      sug:
        subj:
          Suicide prevention
          Suicidal behavior
          Experimental design
          Statistical models
          Sample size (Statistics)
      ab: <bold>Objective: </bold>To provide researchers, clinicians and policy makers with a primer to study designs, statistical approaches and graphical reporting methods for suicide research in real world data (RWD).<bold>Methods: </bold>Study designs, statistical method and graphical reporting standards are detailed with examples from the recently published literature.<bold>Results: </bold>Data sources and codes for identifying suicidal behavior are described. Study designs are described in detail for post-market surveillance, retrospective cohort studies, case control and nested case-control studies, and self-controlled (within-individual) studies including applications of marginal structural models. Graphical reporting of designs is described using an original research study.<bold>Conclusions: </bold>Compared to RCTs, RWE studies offer larger sample sizes, greater generalizability, and real-world validity. However, these non-experimental data risk uncontrolled confounding and potential introduction of bias unless data, design and statistical approaches are rigorously aligned.
      pubtype: Academic Journal
      doctype: journal article
      src: R
    language: English
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