心理学研究通常仅依靠线性相关（r）或类似的统计数据，而不包括其他关联度量（例如相对风险，它检查了受影响人数的差异)。例如,如果只检查线性r，吸烟和肺癌(r=0.06)之间的关联可以被认为是“小”，即使吸烟者比不吸烟者多30倍得肺癌。许多研究得出的结论是，技术使用和福祉之间的关联太小而不具有实际重要性，仅依赖于线性r。我们表明，跨越五个数据集，技术使用与心理健康之间的“小”相关性与实际上重要的风险关联同时存在。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r2）来表征关联可能会产生误导。
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.
