“I know it's bad but I have been pressured into it”: Questionable research practices among psychology students in Canada
Bibliographic record
Abstract
Questionable research practices (QRPs) have been identified as a driving force of the replication crisis in the field of psychological science. The aim of this study was to assess the frequency and reasons for QRP use among psychology students in Canadian universities. Participants were psychology students attending Canadian universities recruited via online advertising and email invitations. Respondents were asked how often they and others engaged in seven QRPs, to estimate the proportion of psychology research impacted by each QRP and how acceptable they found each QRP. Data were collected through Likert-scale survey items and open-ended text responses between May 2020 and January 2021, and analyzed using descriptive statistics and thematic analysis. 425 psychology students completed the survey (40% undergraduate, 59% graduate, 1% post-doctoral fellows). Overall, 64% of participants reported using at least one QRP, while 79% reported having observed others engaging in at least one QRP. The most frequently reported QRPs were p-hacking (46%), not submitting null results for publication (31%) and excluding outcome measures (30%). These QRPs were also the most frequently observed in others, estimated to be the most prevalent in the field, and rated as the most acceptable. Qualitative findings revealed that students are aware of external pressures that promote QRP use and offered several ideas for alternatives and solutions. The results of this study highlight the need to examine the pedagogical standards and cultural norms in academia that may promote or normalize QRPs in psychological science.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchResearch integrity Domain: Methods · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Observational | low |
| gpt | MetaresearchResearch integrity Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.018 | 0.016 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".