Abstract
Alexithymia is the inability to identify and describe one’s own emotions. Some research suggests that organic alexithymia may occur after acquired brain injury (ABI). However, the results in the literature are inconsistent, when comparisons are made against healthy controls. Furthermore, a precise estimate of alexithymia prevalence in the ABI population has not yet been reported. Consequently, this meta–analysis aimed to estimate the prevalence and characteristics of alexithymia in ABI, as measured by the Toronto Alexithymia Scale–20 (TAS–20). Based on 22 unique ABI samples, a series of random-effects meta-analyses estimated moderate to large positive effect sizes (i.e., greater alexithymia in ABI samples) for the TAS–20 total scale (Hedges’ g = 1.00, 95% CI [0.75, 1.35]), as well as the subscales: difficulty identifying feelings (Hedges’ g = 0.92, 95% CI [0.66, 1.17]), difficulty describing feelings (Hedges’ g = 0.69, 95% CI [0.50, 0.87]) and externally oriented thinking (Hedges’ g = 0.75, 95% CI [0.64, 0.85]). Furthermore, a meta–regression identified a larger effect size (TAS–20 total scale score) for traumatic brain injury (TBI) samples, in comparison to non–TBI samples. Finally, the prevalence of clinically significant levels of alexithymia (TAS–20 total scale ≥ 68.4; i.e., two SDs above the general population mean) in ABI patients was estimated at 15.2%. We interpreted the results to suggest that ABI may have a substantial negative impact on affective processing abilities and, thus, comprehensive assessment of emotional functioning deficits following ABI should be considered by practitioners.
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Notes
We note that the literature search did not identify empirical studies that utilized other measures of alexithymia and met the inclusion criteria.
We use the term “clinical alexithymia” in this manuscript, not because we believe a particular score from a questionnaire can validly diagnose a psychological condition, but because it is common practice in the literature to use such a term, in this context (i.e., a specified high value on the TAS-20).
Supplementary leave-one-out robustness analyses were conducted and when Wood et al., 2014 was excluded, almost identical effect sizes were yielded for the total scale (g = 0.99, 95% CI [0.73, 1.25]), and subscales: DIF (g = 0.89, 95% CI [0.63, 1.16]), DDF (g = 0.68, 95% CI [0.48, 0.87]) and EOT (g = 0.74, 95% CI [0.63, 0.86]).
Supplementary meta–analyses for DIF, DDF, EOT and TS were conducted with the control sample data reported in the individual papers (see Table S3 supplementary section). However, of the included papers, six did not include any control data. Consequently, Parker et al. (2003) norms (i.e., N = 1933/6) were used for those six papers. Numerically, these supplementary meta–analyses yielded somewhat larger effect sizes for DIF (g = 1.02, p < .001, 95% CI [0.75, 1.23], DDF (g = 0.77, p < .001, 95% CI [0.53, 1.01], and TS (g = 1.16, p < .001, 95% CI [0.74, 1.57], and a numerically smaller effect size for EOT (g = 0.66, p < .001, 95% CI [0.49, 0.84], in comparison to the meta–analyses that used the Parker et al. (2003) control sample norms exclusively. Overall, the effect sizes were comparable across the two series of meta–analyses.
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Fynn, D.M., Gignac, G.E., Becerra, R. et al. The Prevalence and Characteristics of Alexithymia in Adults Following Brain Injury: A Meta-Analysis. Neuropsychol Rev 31, 722–738 (2021). https://doi.org/10.1007/s11065-021-09484-6
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DOI: https://doi.org/10.1007/s11065-021-09484-6