Discussion: Generalizability (21)
The items from STROBE state that you should report:
- Discuss the generalizability (external validity) of the study results
Explanation
Generalizability, also called external validity or applicability, is the extent to which the results of a study can be applied to other circumstances.(Campbell, 1957) There is no external validity per se; the term is meaningful only with regard to clearly specified conditions.(Justice, 1999) Can results be applied to an individual, groups or populations that differ from those enrolled in the study with regard to age, sex, ethnicity, severity of disease, and co-morbid conditions? Are the nature and level of exposures comparable, and the definitions of outcomes relevant to another setting or population? Are data that were collected in longitudinal studies many years ago still relevant today? Are results from health services research in one country applicable to health systems in other countries?
The question of whether the results of a study have external validity is often a matter of judgment that depends on the study setting, the characteristics of the participants, the exposures examined, and the outcomes assessed. Thus, it is crucial that authors provide readers with adequate information about the setting and locations, eligibility criteria, the exposures and how they were measured, the definition of outcomes, and the period of recruitment and follow-up. The degree of nonparticipation and the proportion of unexposed participants in whom the outcome develops are also relevant. Knowledge of the absolute risk and prevalence of the exposure, which will often vary across populations, are helpful when applying results to other settings and populations (see Box 7). (Vandenbroucke et al., 2007).
Example
- “How applicable are our estimates to other HIV-1-infected patients? This is an important question because the accuracy of prognostic models tends to be lower when applied to data other than those used to develop them. We addressed this issue by penalising model complexity, and by choosing models that generalized best to cohorts omitted from the estimation procedure. Our database included patients from many countries from Europe and North America, who were treated in different settings. The range of patients was broad: men and women, from teenagers to elderly people were included, and the major exposure categories were well represented. The severity of immunodeficiency at baseline ranged from not measureable to very severe, and viral load from undetectable to extremely high.” (Egger et al., 2002; Vandenbroucke et al., 2007)
Field-specific guidance
Anti-microbial stewardship programs (Tacconelli et al., 2016)
- Discuss study setting, type of hospital, local epidemiology for the generalisability
Simulation-based research (Cheng et al., 2016)
- Describe generalizability of simulation-based outcomes to patient-based outcomes (if applicable)
References
Campbell, D. T. (1957). Factors relevant to the validity of experiments in social settings. Psychological Bulletin, 54(4), 297–312. https://doi.org/10.1037/h0040950
Cheng, A., Kessler, D., Mackinnon, R., Chang, T. P., Nadkarni, V. M., Hunt, E. A., Duval-Arnould, J., Lin, Y., Cook, D. A., Pusic, M., Hui, J., Moher, D., Egger, M., & Auerbach, M. (2016). Reporting guidelines for health care simulation research: Extensions to the CONSORT and STROBE statements. Advances in Simulation, 1, 25. https://doi.org/10.1186/s41077-016-0025-y
Egger, M., May, M., Chene, G., Phillips, A. N., Ledergerber, B., Dabis, F., Costagliola, D., D’Arminio Monforte, A., Wolf, F. de, Reiss, P., Lundgren, J. D., Justice, A. C., Staszewski, S., Leport, C., Hogg, R. S., Sabin, C. A., Gill, M. J., Salzberger, B., Sterne, J. A. C., & ART Cohort Collaboration. (2002). Prognosis of hiv 1 infected patients starting highly active antiretroviral therapy: A collaborative analysis of prospective studies. Lancet, 360(9327), 119–129.
Justice, A. C. (1999). Assessing the Generalizability of Prognostic Information. Annals of Internal Medicine, 130(6), 515. https://doi.org/10.7326/0003-4819-130-6-199903160-00016
Tacconelli, E., Cataldo, M. A., Paul, M., Leibovici, L., Kluytmans, J., Schröder, W., Foschi, F., Angelis, G. D., Waure, C. D., Cadeddu, C., Mutters, N. T., Gastmeier, P., & Cookson, B. (2016). STROBE-AMS: Recommendations to optimise reporting of epidemiological studies on antimicrobial resistance and informing improvement in antimicrobial stewardship. BMJ Open, 6(2), e010134. https://doi.org/10.1136/bmjopen-2015-010134
Vandenbroucke, J. P., Elm, E. von, Altman, D. G., Gotzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., & Egger, M. (2007). Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration. Epidemiology, 18(6), 805–835. https://doi.org/10.1097/EDE.0b013e3181577511