It is common for psychology studies to rely solely on linear correlation (r) or similar statistics and not include other measures of association (such as relative risk, which examines differences in the number of people affected). For example, the association between smoking and lung cancer (r = 0.06) could be dismissed as “small” if only linear r is examined, even though 30 times more smokers than non-smokers get lung cancer. Many studies concluding that associations between technology use and well-being as too small to be of practical importance relied solely on linear r. We show that, across five datasets, “small” correlations between technology use and mental health exist alongside practically important risk associations. As there are several valid types of association, and characterizing an association based on a single type of a measure – such as linear r or r² – can be misleading.

心理学研究通常仅依赖线性相关 ( r ) 或类似统计数据，而不包括其他关联度量（例如相对风险，它检查受影响人数的差异）。例如，如果只检查线性r，吸烟与肺癌之间的关联 ( r  = 0.06) 可能会被视为“小” ，即使吸烟者患肺癌的人数是不吸烟者的 30 倍。许多研究得出结论，技术使用与幸福感之间的关联太小而没有实际意义，仅依赖于线性r. 我们表明，在五个数据集中，技术使用与心理健康之间的“小”相关性​​与实际重要的风险关联并存。由于有几种有效的关联类型，并且基于单一类型的度量（例如线性r或r ²）来表征关联可能会产生误导。