Psychology experiment design and data collection planning. Use when designing questionnaire studies, laboratory experiments, or online surveys; selecting validated Chinese scales; planning participant recruitment; preparing IRB/ethics applications; or designing attention checks and data quality controls.
This skill guides the design of psychology experiments and data collection procedures.
Best for: attitudes, traits, self-reported behaviors, retrospective data
Key design decisions:
Best for: causal inference, reaction time, physiological measures, behavior observation
Key elements:
sample() for condition assignment)Best for: large samples quickly, remote participants
Qualtrics-specific considerations:
| Scale | Chinese Version | Source | Items |
|---|---|---|---|
| Big Five (NEO-PI-R) | 中文修订版 | Costa & McCrae; Wang et al. (2004) | 240 items |
| Big Five (BFI-44) | 中文版 | John et al.; Schmitt et al. (2007) | 44 items |
| Conscientiousness (BFAS) | — | DeYoung et al. (2007) | 10 items/facet |
| Self-control (Brief) | 中文版 | Tangney et al.; Ent et al. | 13 items |
| Scale | Chinese Version | Source | Items |
|---|---|---|---|
| PANAS | 中文版 | Watson et al.; Huang et al. (2003) | 20 items |
| DASS-21 | 中文版 | Lovibond & Lovibond; Antony et al. | 21 items |
| SWLS (Life Satisfaction) | 中文版 | Diener et al.; Luo et al. | 5 items |
| PHQ-9 (Depression) | 中文版 (Patient Health Q.) | Spitzer et al.; He et al. | 9 items |
| Scale | Chinese Version | Source | Items |
|---|---|---|---|
| SES (Self-esteem, Rosenberg) | 中文版 | Rosenberg; Wang et al. | 10 items |
| Attributional Style Q. | — | Peterson et al. | varies |
| Need for Cognition (NFC) | 中文版 | Cacioppo & Petty | 18 items |
Note: Always verify the Chinese validation study before using. Search via 工部 using:
python3 lit_search.py search "Chinese validation [scale name]" --source pm
When preparing an IRB/ethics application, ensure all items are addressed:
# IRB Pre-submission Checklist
## Study Information
- [ ] Study title and PI information
- [ ] Study duration and timeline
- [ ] Funding source (if any)
## Participants
- [ ] Target population and inclusion/exclusion criteria
- [ ] Recruitment method (poster/online/subject pool)
- [ ] Compensation details (amount, form, timing)
- [ ] Estimated number of participants
- [ ] Vulnerable populations? (children, patients, students of PI — needs extra justification)
## Procedures
- [ ] Complete description of all procedures
- [ ] Duration of each session
- [ ] Any deception used? → Requires justification + debrief plan
- [ ] Any physical procedures (blood draw, physiological measures)?
## Risks and Benefits
- [ ] Potential psychological distress? (e.g., trauma-related content)
- [ ] Privacy risks?
- [ ] Direct benefits to participants?
- [ ] Benefits to society/science?
## Data Privacy
- [ ] Data de-identification plan
- [ ] Data storage location and duration (typically 5-10 years)
- [ ] Who has access to identifiable data?
- [ ] Data sharing plan (OSF? upon request?)
## Informed Consent
- [ ] Consent form includes: study purpose, procedures, risks, benefits, confidentiality, voluntariness, withdrawal rights, contact info
- [ ] Consent is obtained before ANY data collection
- [ ] Online study: digital consent (clicking "agree") acceptable at most institutions
Participants will be excluded from analysis if they:
1. Complete the survey in less than [X] minutes (< 50% of pilot median)
2. Fail [≥ 2 / ≥ 1] attention check item(s)
3. Provide non-sensical responses to open-ended items
4. Have [X]% or more missing data on key measures
Sample size was determined a priori using G*Power 3.1 (Faul et al., 2009).
For [test type], assuming an effect size of [d/f/r] = [value] (based on [citation / meta-analytic estimate]),
α = .05 (two-tailed), and power = .80, a minimum of N = [number] participants per group
([number] total) was required. We targeted N = [number + buffer] to account for
anticipated data exclusions.