Deskly: A Privacy-First Desktop Digital Wellbeing System for Windows Using Behavioral Nudges and Gamification

Digital wellbeing tools are widely available on mobile platforms — Google Digital Wellbeing for Android and Apple Screen Time for iOS — yet no equivalent native, intervention-capable system exists for Windows desktops, the primary work device for students and knowledge workers. This paper presents Deskly, a desktop-native digital wellbeing system for Microsoft Windows that integrates:(1) Real-time application and browser-level activity tracking via Windows UI Automation APIs(2) Evidence-based behavioral nudge interventions including graduated app limits with conscious-extension checkpoints(3) Gamified habit formation with streaks, achievements, and daily goals(4) Privacy-first local data storage using an Obsidian-inspired vault architecture Technical Highlights:• Built on Electron 31 + React 18 + Vite 5• PowerShell–C# interop for sub-second foreground detection including UWP apps• Browser title-bar parsing for website-level tracking across 58 browsers — no extension required• Heuristic app categorization (88 keyword rules, 7 intent labels, weighted F1 = 0.83)• Local-only JSON vault with auto-repair and 60-second write-behind caching Evaluation Results (N = 12, within-subjects pilot):• 23% reduction in daily screen time (p = 0.008, Cohen's d = 0.93)• 17% improvement in WHO-5 Well-Being Index (p = 0.036, d = 0.69)• System Usability Scale: 81.3/100 ("Excellent")• 100% adoption of graduated extension model• 22% reduction in app switches per hour (d = 0.76) The paper includes 10 TikZ-rendered figures (architecture, data pipeline, UI wireframes, study protocol, satisfaction chart), 8 tables (tool comparison, tech stack, ML classification, demographics, results), and 28 references. Developed at the Department of Computer Science and Engineering, Parul University, Vadodara, Gujarat, India, under the guidance of Prof. Alok Singh Kushwaha. Website: https://deskly.in