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Conducting user research: interview guides, usability test plans, qualitative analysis, persona creation, journey mapping. Use when research design or analysis is needed; complements Echo.

Use this Skill: https://skilld.dev/gh/simota/agent-skills/field

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referencediary-longitudinal-study.md

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Diary Study & Longitudinal Research Reference

Purpose: Design diary / longitudinal behavioral studies that capture in-context behavior unfolding over days or weeks. Covers study-length trade-offs, prompt frequency, self-report bias mitigation, Experience Sampling Method (ESM), participant fatigue management, and multi-modal capture (photo, video, voice).

Scope Boundary

  • Field diary: Longitudinal self-report study design — diary protocols, ESM schedule, prompt authoring, fatigue thresholds, media-capture instructions, analysis of time-series qualitative data.
  • vs Echo: Echo simulates personas walking through a UI in a single session; it does not observe real behavior over time. In-situ longitudinal observation → diary; synthetic single-session walkthrough → Echo.
  • vs Pulse: Pulse captures passive behavioral telemetry via in-product events. Passive telemetry at scale → Pulse; prompted self-report with reflection → diary. Best paired: telemetry gives "what", diary gives "why".
  • vs Voice: Voice collects feedback after the fact (reviews, support tickets, post-hoc NPS). Retrospective feedback → Voice; real-time or near-real-time in-context capture → diary.

Study-Length Trade-Offs

Length Captures Fatigue risk Use when
3–5 days Acute decisions, weekly rhythms Low Purchase journeys, onboarding, habit trials
1–2 weeks Weekly cycles, novelty decay Medium Feature adoption, learning curves
3–4 weeks Habit formation, month-end patterns High Retention, behavior change studies
6–12 weeks Habit stabilization, life-event triggers Very high Long-term behavior shifts, chronic contexts

Default: 2 weeks — long enough to see novelty effects fade, short enough to retain 80%+ participants with adequate incentive.

Prompt Frequency & ESM Schedule

Experience Sampling Method (ESM) prompts participants at semi-random intervals to capture in-the-moment state without recall bias.

Cadence Prompts/day Fatigue Use when
Event-contingent Variable (triggered by event) Low Behavior is discrete and self-reportable
Signal-contingent (ESM) 3–6 randomized Medium Mood, context, in-situ usage patterns
Interval-contingent 1–2 fixed Low End-of-day reflection, summary diary
Combined (ESM + EoD) 3–5 ESM + 1 summary Medium Rich multi-granularity picture

Cap ESM at 6 prompts/day. Response window per prompt: 15–30 minutes. Quiet hours (no prompts): typically 22:00–08:00 local.

Self-Report Bias Mitigation

Bias Mechanism Mitigation
Recall Gaps between event and report distort detail ESM within 30 min of event; end-of-day diary same day
Social desirability Participant reports the "right" answer Emphasize anonymized reporting, no right/wrong framing
Hawthorne Being observed changes behavior Baseline first 1–2 days as "settling"; analyze from day 3
Demand characteristics Participant guesses study hypothesis Cover story; multiple plausible purposes in brief
Selection Who agrees to diary ≠ population Screen for diverse contexts; over-recruit marginal segments
Attrition Dropouts differ from completers Report dropout rate; analyze sensitivity by days-completed

Participant Fatigue Management

Fatigue manifests as declining response length, straight-line answers, missed prompts, and dropout.

  • Front-load key prompts: days 1–3 typically have highest engagement.
  • Rotate prompt types: alternate short (2 items) and medium (5 items) days.
  • Incentive structure: completion bonus (e.g. +50% for ≥80% of prompts answered) outperforms flat payment.
  • Check-in touchpoint: researcher message at day 3 and day 7 reduces dropout by 15–25%.
  • Completion threshold: accept data from participants who answered ≥70% of prompts; flag below for sensitivity analysis.
  • Target 10–15 participants per segment to survive 20–30% attrition and still analyze ≥8 complete logs.

Media Capture

Modality Strength Limit Prompt design
Text Fastest, lowest friction Shallow on emotion 1–3 items, ≤60 words expected
Photo Context, environment, object-of-use PII risk "Show the thing you just used / the space you're in"
Short video (15–30s) Behavior + verbal reflection Upload friction on mobile data "Record what happened, why it mattered"
Voice note (30–60s) Emotion, tone, richer than text Transcription cost "Talk for 30 seconds about how that went"
Screenshot In-app moment Needs OS permission guidance "Capture the screen where you got stuck"

Always include a "no-response" option with reason code (busy / forgot / not applicable). Silence is data.

Tool Selection

Tool Strength Use when
Indeemo Mobile-first, media-rich, ESM Consumer mobile behavior
dscout Strong panel + diary workflow Need recruitment bundled
Ethnio + custom form Flexible, low cost Internal panel, simple text/photo
Gmail/SMS + Airtable DIY, zero tool cost Tiny study (n<10), text-only
Day One / private Notion Participant-preferred journaling Sensitive / personal topics

Anti-Patterns

  • Running a 4-week diary when 1 week would answer the question — attrition wastes data.
  • ESM with >6 prompts/day — dropout after day 3 exceeds 40%.
  • Asking participants to re-explain context every prompt — use short-form checkboxes for recurring context.
  • Treating diary entries as interview substitutes — diaries give breadth over time; interviews give depth at a moment. Use both.
  • Skipping the baseline settling period — Hawthorne effect inflates early-day data.
  • No dropout reporting — readers cannot assess bias.
  • Requiring desktop uploads for mobile behavior — forces context-switch that kills in-the-moment capture.
  • Analyzing as aggregated means — lose the within-person trajectory that is the point of longitudinal data.

Analysis Approach

Diary data is multi-level (observations nested within participants nested within time).

  • Within-person: chart each participant's trajectory; identify turning points and triggers.
  • Cross-person: cluster trajectories (e.g. steady adopters vs. frustrated dropouts).
  • Temporal patterns: day-of-week effects, novelty decay curves, habit-formation thresholds (typically 21–66 days for new habits).
  • Triangulate with telemetry from Pulse where available — diary "why" plus telemetry "what" is the strongest combination.

Handoff

  • To Pulse: telemetry instrumentation needs derived from observed moments (e.g. "add event for the stuck-step participants described on day 4").
  • To Cast: behavior-trajectory clusters for persona refinement.
  • To Echo: specific stuck moments to run cognitive walkthroughs on.
  • To Voice: recurring pain themes that should enter the operational feedback loop.
  • Always include in handoff: participant count, completion rate, dropout pattern, media-capture gaps, within-person variance notes, confidence limitations.

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub13d

    The skill provides a comprehensive and professional framework for user research operations. It emphasizes ethical data handling, participant privacy, and systematic analysis methodologies. While the skill processes external data, which is an inherent surface for indirect prompt injection in LLMs, it lacks high-risk capabilities like code execution or file system modification, and includes multiple human-in-the-loop guardrails to ensure output integrity.

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