Literature DB >> 32683886

How Do Older Adults Recruited Using MTurk Differ From Those in a National Probability Sample?

Aaron M Ogletree1, Benjamin Katz2.   

Abstract

A growing number of studies within the field of gerontology have included samples recruited from Amazon's Mechanical Turk (MTurk), an online crowdsourcing portal. While some research has examined how younger adult participants recruited through other means may differ from those recruited using MTurk, little work has addressed this question with older adults specifically. In the present study, we examined how older adults recruited via MTurk might differ from those recruited via a national probability sample, the Health and Retirement Study (HRS), on a battery of outcomes related to health and cognition. Using a Latin-square design, we examined the relationship between recruitment time, remuneration amount, and measures of cognitive functioning. We found substantial differences between our MTurk sample and the participants within the HRS, most notably within measures of verbal fluency and analogical reasoning. Additionally, remuneration amount was related to differences in time to complete recruitment, particularly at the lowest remuneration level, where recruitment completion required between 138 and 485 additional hours. While the general consensus has been that MTurk samples are a reasonable proxy for the larger population, this work suggests that researchers should be wary of overgeneralizing research conducted with older adults recruited through this portal.

Entities:  

Keywords:  HRS; MTurk; cognition; depression; feasibility; online participants

Year:  2020        PMID: 32683886     DOI: 10.1177/0091415020940197

Source DB:  PubMed          Journal:  Int J Aging Hum Dev        ISSN: 0091-4150


  8 in total

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2.  Bridging the Technological Divide: Stigmas and Challenges With Technology in Digital Brain Health Studies of Older Adults.

Authors:  Jessica Nicosia; Andrew J Aschenbrenner; Sarah L Adams; Marisol Tahan; Sarah H Stout; Hannah Wilks; Joyce E Balls-Berry; John C Morris; Jason Hassenstab
Journal:  Front Digit Health       Date:  2022-04-29

3.  Understanding Psychological Distress and Protective Factors Amongst Older Adults During the COVID-19 Pandemic.

Authors:  Nichole Sams; Dylan M Fisher; Felicia Mata-Greve; Morgan Johnson; Michael D Pullmann; Patrick J Raue; Brenna N Renn; Jaden Duffy; Doyanne Darnell; Isabell Griffith Fillipo; Ryan Allred; Kathy Huynh; Emily Friedman; Patricia A Areán
Journal:  Am J Geriatr Psychiatry       Date:  2021-03-20       Impact factor: 7.996

4.  Older Adults' Emotion Recognition Ability Is Unaffected by Stereotype Threat.

Authors:  Lianne Atkinson; Janice E Murray; Jamin Halberstadt
Journal:  Front Psychol       Date:  2021-01-07

5.  Measurement Invariance of Social Media Use in Younger and Older Adults and Links to Socioemotional Health.

Authors:  Neika Sharifian; A Zarina Kraal; Afsara B Zaheed; Ketlyne Sol; Emily P Morris; Laura B Zahodne
Journal:  Innov Aging       Date:  2021-03-11

6.  An investigation of COVID-19 related worry in a United States population sample.

Authors:  Jack Samuels; Calliope Holingue; Paul S Nestadt; O Joseph Bienvenu; Phillip Phan; Gerald Nestadt
Journal:  J Psychiatr Res       Date:  2021-10-22       Impact factor: 5.250

7.  Story stimuli for instantiating true and false beliefs about the world.

Authors:  Nikita A Salovich; Megan N Imundo; David N Rapp
Journal:  Behav Res Methods       Date:  2022-07-05

8.  Predicting Decisional Determinants of Physical Activity Among Older Adults: An Integrated Behavior Approach.

Authors:  Christian E Preissner; Kathleen Charles; Bärbel Knäuper; Navin Kaushal
Journal:  J Aging Health       Date:  2021-10-18
  8 in total

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