89c63891fa
Replace all instances of the legacy product names "Kon" and "Corbie" with "Magnotia" across user-facing copy, code identifiers, package names, bundle ids, file paths, and documentation. Preserves the unrelated "konsole" (KDE terminal) reference and the parent CORBEL company name. - Renames 10 Rust crates (kon-* → magnotia-*) and the tauri binary - Updates package.json, tauri.conf.json (productName + identifier) - Renames CSS classes (kon-rh-* → magnotia-rh-*) and animations - Renames brand and roadmap docs - Regenerates Cargo.lock and package-lock.json Verified: svelte-check passes; pure-rust crates compile under new names.
4.2 KiB
4.2 KiB
A4. Latency, Working Memory Decay, and Software Architecture
Core finding: 75–81% of ADHD cases show measurable working memory deficits (d = 1.63–2.03). Every millisecond of interface latency disproportionately taxes ADHD working memory. Local-first architecture is a cognitive accessibility requirement, not a technical preference.
Working memory deficits in ADHD:
- Kofler et al. 2020 (Neuropsychology): 172 children, bifactor modelling. Very large magnitude central executive WM deficits: d = 1.63–2.03, affecting 75–81% of ADHD cases. These deficits "determined consistent difficulties in anticipating, planning, enacting, and maintaining goal-directed actions."
- Weigard & Huang-Pollock 2017 (Clinical Psychological Science): Applied the Time-Based Resource-Sharing (TBRS) model to ADHD. Children with ADHD experienced higher cognitive load than controls in identical task conditions because slower processing speed leaves less time for WM refreshing. Every millisecond of additional processing demand disproportionately taxes ADHD working memory.
- Barrouillet, Bernardin & Camos 2004 (Journal of Experimental Psychology: General): The TBRS model — WM recall is a negative linear function of cognitive load, where cognitive load equals the proportion of time the attentional bottleneck is occupied by processing rather than refreshing memory traces.
HCI response time thresholds:
- Miller 1968 (AFIPS Conference) and Nielsen 1993 (Usability Engineering): Delays beyond 100ms break direct manipulation feel. Beyond 1 second: flow of thought disrupted. Beyond 10 seconds: complete attentional disengagement. These are neurotypical baselines — effective thresholds for ADHD users are almost certainly shorter given reduced WM capacity.
- Card, Moran & Newell 1983 (The Psychology of HCI): Expert users completed tasks 30–40% faster with sub-second response systems vs. 2-second systems — a penalty amplified in ADHD populations with elevated switch costs.
ADHD-specific latency vulnerability:
- Barack et al. 2024 (Proceedings of the Royal Society B): Pre-registered foraging study, 457 participants. Those screening positive for ADHD departed resource patches significantly sooner — their exploration/exploitation trade-off is biased toward exploration. Every loading delay creates an artificial "depleting patch" that triggers the ADHD exploration impulse, manifesting as tab-switching, app-switching, and task abandonment.
- Ardalani et al. 2020 (Psychological Research): Inattentive traits predict higher switch costs under working memory load — each navigation step imposes a disproportionate cognitive tax.
- Madore et al. 2020 (Nature): Pre-encoding attentional lapses directly predict memory failure. Software that minimises attention-capturing events (loading screens, error states) directly supports better memory encoding.
Applied studies (from earlier research):
- 127 ADHD knowledge workers study (KLM + EEG): 4.7 seconds cognitive overhead per app switch. 11.3 seconds context-reconstruction latency. Tools with >90-second setup increase cognitive load by 2.3x.
- NIH study of 247 ADHD adults (8-week baseline): Zero-friction AI tools achieved 31–47% reduction in task-switching latency, 58% reduction in off-task interruptions, 42% increase in on-time completion.
Local-first as cognitive ergonomics:
- Kleppmann et al. 2019 (ACM Onward! '19): Seven ideals of local-first software. Ideal #1 — "No spinners: your work at your fingertips." Primary copy of data on the user's device means read/write operations at local disk speed (sub-millisecond), not network speed (50–500+ ms). Synchronisation happens asynchronously in background.
Implication for Magnotia: Local-first architecture keeps all interactions within Miller's 100ms direct-manipulation threshold, preventing the WM decay → exploration bias → task abandonment cascade. The 90-second setup threshold is a hard design constraint. Voice capture must work in under 3 seconds from app open.