Jennifer Tackett

@jnfrltackett.bsky.social

Psychology professor into kid personality and its various manifestations. Also entrepreneurship, leadership, construct validity, and nachos.

@syeducation.bsky.socialReposted by @jnfrltackett.bsky.social

New diamond open access outlet for developmental psych. Free to publish, free to read, and led by a great team. One more step away from for-profit publishers.

@jnfrltackett.bsky.social

I learned a lot in writing this piece & came away convinced that we are missing a huge opportunity to understand youth personality development across multiple levels, including how they find their place in the world - and the need to contextualize impairment within normative personality development

@jnfrltackett.bsky.social

3. We highlight several current areas of research on adolescent development that could benefit from integration with personality science - particularly social media, internet use, and activism (and I would add leadership here!)

@jnfrltackett.bsky.social

2. We argue for expanding our view of impairment beyond self & close relationships to civic engagement, sense of purpose, and meaning - there is almost no research looking at how teenage personality development shapes their emerging sense of how they fit into and contribute to the world around them

@jnfrltackett.bsky.social

There are a few important things we tried to do with this piece: 1. We make the case that personality pathology develops through the same processes as normative personality developmental that can, at times, go awry

@dsquintana.bsky.socialReposted by @jnfrltackett.bsky.social

New preprint! πŸŽ‰ I analysed 1660 papers from 4 psychology journals and found materials sharing went from 9% of papers in 2015 to 82% in 2025, and these materials *do* get downloaded β€” a median of 135 times each. BUT shared code is often hard to run. doi.org/10.31234/osf...

Let's walk through it 🧡

Two-panel figure. Panel a is a flow diagram tracking 1,611 empirical psychology articles from publication year (545 in 2015, 552 in 2020, 514 in 2025) to repository-link type: 785 link an OSF project, 85 link another platform, and 741 link no repository. Of those with an OSF link, download counts were retrieved for 670 and not retrieved for 115. Panel b is a line chart of the share of empirical papers linking OSF across 2015, 2020 and 2025. The overall rate, shown as a dashed black line, rises from 9% to 57% to 82%. All four journals rise steeply and end close together: Psychological Science 92%, JESP 89%, JML 83%, Cognition 76%, with Psychological Science highest throughout.Three-panel figure. Panel a: ridgeline plot of downloads per file by material type on a log scale, with the percentage never downloaded labelled for each β€” archive 16% of 545 files, documents 20% of 2,970, code 12% of 3,471, other 17% of 1,646, data 21% of 10,051, media 35% of 2,120, images 35% of 4,102. Most files cluster between 1 and 10 downloads, with long right tails past 100. Panel b: ridgeline plot of downloads per paper by journal, log scale, with dashed median lines; Psychological Science is highest, then JESP, JML and Cognition. Panel c: stacked bars showing, for documents, data and code separately, the share of papers by download band (0, 1–10, 11–100, more than 100) in 2015, 2020 and 2025. The share exceeding 100 downloads falls sharply over time in all three types, from roughly two-thirds in 2015 to a quarter or less in 2025, as the 1–10 band grows.Four-panel figure. Panel a: statistical languages detected among 333 papers with retrievable code β€” R 88%, SPSS 12%, Stata 4%, SAS 1%. Panel b: code red flags among those 333 papers β€” 34% hard-code an absolute path, 40% reference a missing file β€” above documentation among 672 OSF-linked papers β€” 21% have a README, 30% are documented by README, description or wiki. Panel c: among 562 Elsevier papers with no repository link, 44% (245) host at least one journal supplementary file but only 14% (77) host data, code or an archive. Panel d: composition of those 448 hosted files β€” documents 52%, data 21%, media 9%, other 7%, archive 6%, code 3%, images 1%. The code panels are green, the journal-supplement panels blue.Coefficient plot (download predictors) Dot-and-whisker plot of three standardised predictors of OSF download volume, each with a 95% confidence interval. Repository size (number of files) has the largest effect at about 0.76, citations about 0.38, and altmetric attention about 0.12. All three intervals sit entirely above zero, so each predicts more downloads, with repository size roughly twice the effect of citations and six times that of attention. X-axis: standardised effect, βˆ’0.2 to 1.0.
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