Questionable prospective effects on burnout and exhaustion: Simulated reanalyses of cross-lagged panel models DOI Open Access
Kimmo Sorjonen, Bo Melin, Filippa Folke

и другие.

Опубликована: Авг. 23, 2024

Burnout and exhaustion has been extensively studied in organizational work psychology. Studies using the cross-lagged panel models have tended to conclude, explicitly or implicitly (e.g., form of policy recommendations), causal prospective effects of, for example, demands, job insecurity, depression on burnout exhaustion. However, it is well established that model may be spurious, e.g., due correlations with residuals regression mean. Here, we scrutinized 23 previously reported burnout/exhaustion by fitting complementary data were simulated resemble evaluated studies. With one possible exception, did not withstand scrutiny, i.e., they appeared spurious. It important researchers bear mind correlations, including models, do prove causality order overinterpret findings. We recommend scrutinize findings from their data. If converge, conclusions are corroborated. If, other hand, diverge, caution advised claims causality, explicit implicit, should probably avoided.

Язык: Английский

Questionable prospective effects on burnout and exhaustion: Simulated reanalyses of cross-lagged panel models DOI Open Access
Kimmo Sorjonen, Bo Melin, Filippa Folke

и другие.

Опубликована: Авг. 23, 2024

Burnout and exhaustion has been extensively studied in organizational work psychology. Studies using the cross-lagged panel models have tended to conclude, explicitly or implicitly (e.g., form of policy recommendations), causal prospective effects of, for example, demands, job insecurity, depression on burnout exhaustion. However, it is well established that model may be spurious, e.g., due correlations with residuals regression mean. Here, we scrutinized 23 previously reported burnout/exhaustion by fitting complementary data were simulated resemble evaluated studies. With one possible exception, did not withstand scrutiny, i.e., they appeared spurious. It important researchers bear mind correlations, including models, do prove causality order overinterpret findings. We recommend scrutinize findings from their data. If converge, conclusions are corroborated. If, other hand, diverge, caution advised claims causality, explicit implicit, should probably avoided.

Язык: Английский

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