Speech-Language Pathologists' Knowledge and Consideration of Factors That May Predict, Moderate, and Mediate AAC Outcomes.

Sievers et al. (2020) sent an online survey to 187 speech-language pathologists around the world. They asked which child, family, and device factors shape AAC success for kids with autism.

The survey listed research-backed predictors like joint attention and fine motor skills. It also left blank boxes so clinicians could add any extra factors they watch for in real life.

SLPs agreed with most published predictors, but they also wrote in 20 new ones. These ranged from the child’s frustration level to the family’s daily routine.

No single factor dominated. Instead, clinicians described a web of small details that stack together to help or hinder AAC use.

Mason et al. (2021) zoomed in on the same question but for spoken language. Their SLPs named tiny vocal behaviors—like consonant babbles—that forecast speech gains. Together, the two studies show clinicians value both broad AAC ingredients and micro speech markers.

Maingi et al. (2025) surveyed Indian SLPs about AAC barriers. They cited scarce devices and scant training, echoing the 2020 call for more practical know-how. The pair links Western predictor lists to real-world resource gaps in low-income settings.

Alhuzimi (2026) asked Saudi teachers, not SLPs, what drives AAC uptake. Teachers flagged “easy to use” and “clear benefit” as core. Their classroom view adds a new layer: even perfect child predictors fail if the teacher sees the tool as too hard or pointless.

Use the 20 clinician factors as a quick checklist during AAC evals. Ask about sleep, sensory triggers, and sibling involvement—items research reviews still miss. Then pair that lens with David’s micro speech signs and Bhavya’s resource reality. Your plan will cover child skills, family life, and service barriers in one shot.