Additional evidence that valence does not affect serial recall

Abstract

In immediate serial recall, a canonical short-term memory task, it is well established that performance is affected by several sublexical, lexical and semantic factors. One factor that receives a growing interest is valence, whether a word is categorized as positive (e.g., happy) or as negative (e.g., pain). However, contradictory findings have recently emerged. Tse and Altarriba (2022) in two experiments with one set of stimuli and fixed lists concluded that valence affects serial recall performance while Bireta et al. (2021) in three experiments with three sets of stimuli and randomized lists concluded that valence does not affect serial recall performance. Two experiments assessed the experimental discrepancy between Tse and Altarriba and Bireta et al. For both experiments, in one block every participant saw the exact same lists as those used in Tse and Altarriba and in the other block, each list was randomly constructed for each participant, as was done in Bireta et al. In Experiment 1, with concrete words varying in valence, we replicated the results of Tse and Altarriba with fixed lists and the results of Bireta et al. with randomized lists. In Experiment 2, with abstract words with both fixed and randomized lists we replicate the absence of effect valence like Tse and Altarriba and Bireta et al. Overall, we conclude that valence does not affect serial recall and the discrepancy was attributed to the peculiarity of the fixed lists used by Tse and Altarriba.

Set size and the orthographic/phonological neighbourhood size effect in serial recognition: The importance of randomization.

“…In Experiment 3, for each subject, 12 words were randomly selected from the large neighbourhood pool and 12 from the small neighbourhood pool used in Experiment 1. The pools formed can be determined by examining the raw data at the Open Science Foundation (Guitard et al, 2023).…”

“…Whereas Bireta et al (2021) randomly generated each list for each subject, Tse and Altarriba (2022) created five concrete positive and five concrete negative lists, and all subjects experienced the same lists. Guitard et al (2023) noted that when the concrete positive and concrete negative lists were ranked by mean frequency, four of the five highest frequency lists were positive, and four of the five lowest frequency lists were negative. Although the larger pools were equated for frequency, the individual lists turned out to differ.…”

“…These were the 47 large and 47 small neighbourhood size words from Clarkson et al (2017) and two words added by Greeno et al (2022): NUT in the large neighbourhood pool and RIB in the small neighbourhood pool. Large neighbourhood : bark, bead, bin, boot, buzz, cone, cop, cork, cull, duck, fade, fizz, ham, haze, hike, hood, kite, lag, lard, lice, lick, maim, meek, mole, node, nut, peach, pearl, pod, poise, poke, pun, rake, rim, ripe, robe, sane, sap, shack, siege, sock, tan, tart, thorn, tile, vine, weep, weird Small neighbourhood : badge, beige, carve, chase, chef, chime, churn, couch, dab, dodge, fang, fog, forge, geese, germ, gig, gown, gush, herb, ledge, loaf, lurch, merge, mesh, morgue, moth, noose, notch, nudge, peg, pierce, rib, shove, sieve, soothe, thatch, thief, thud, torch, turf, verse, vogue, void, web, wharf, yarn, zip, zoomIn Experiment 2, the stimuli were the same as in Experiment 4 of Greeno et al (2022). Large neighbourhood : bark, boot, cone, cop, cork, cull, pearl, pod, tan, tart, thorn, tile Small neighbourhood : badge, beige, chase, chef, chime, couch, peg, pierce, thatch, thief, torch, turfIn Experiment 3, for each subject, 12 words were randomly selected from the large neighbourhood pool and 12 from the small neighbourhood pool used in Experiment 1. The pools formed can be determined by examining the raw data at the Open Science Foundation (Guitard et al, 2023).…”

“…Although the larger pools were equated for frequency, the individual lists turned out to differ. Guitard et al (2023) then reran Tse and Altarriba’s (2022) experiment using their stimuli but randomly constructed each list for each subject. The effect of valence disappeared replicating the null effect of valence reported by Bireta et al (2021).…”