Not provided
| ID | Type | Description | Link |
|---|---|---|---|
| 1R21AG069428-01A1 | U.S. NIH Grant/Contract | View source | |
| 5R21AG069428-02 | U.S. NIH Grant/Contract | View source |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| University of California, Riverside | OTHER |
| National Institute on Aging (NIA) | NIH |
Not provided
Not provided
Not provided
The present study investigates how individual differences in cognitive processing contribute to the efficacy of working memory training programs in an older adult population. In a randomized crossover design, different types of working memory training interventions will be evaluated within the same participants.
Adding game-like elements to working memory training programs can increase motivation and engagement, which can increase learning. However this process, termed gamification, adds sensory complexity that can lead to increased mental load and/or distraction in older adults. Investigators hypothesize that gamification of training tasks will be beneficial to some and counterproductive to other participants. The investigators will test two models; the first assumes that participants with difficulty inhibiting distracting information will show better learning and transfer when assigned to non-gamified training, whereas those with more distractor tolerance will show better learning and transfer when assigned to gamified training. The second model states that the outcomes of the intervention will be better predicted by performance on measures of general cognitive ability.
In a separate study, the investigators will compare working memory training that contains rich, multisensory information with a training program that contains only visual information. Here they will also test two models; the first assumes that participants with difficulty binding two stimulus streams will show better learning and transfer when assigned to visual-only working memory training, whereas participants who do not have this difficulty will show better learning and transfer when assigned to multisensory working memory training. The second model states that the outcomes of the intervention will be better predicted by performance on measures of general cognitive ability.
Three randomized cross-over trials will be conducted to obtain within-subject comparisons of training with enriched (game-like) versions of working memory training tasks compared to basic (non-gamified) versions of these tasks. In the N-back trial, participants will be assigned to Non-Gamified N-back training and Gamified N-back training. In the Span trial, they will be assigned to Non-Gamified Span training and Gamified Span training and in the Multisensory trial, they will be assigned to Non-gamified Unisensory N-back training and Non-gamified Multisensory N-back training.
Each trial involves a total of 50 sessions per participant: the first few sessions consist of completing questionnaires and computerized cognitive assessments (pre-test). Participants then complete 20 sessions of working memory training. After a mid-test, they complete 20 sessions of a different type of working memory training. Post-test is administered upon training completion, and at least a month later, participants complete 3 follow-up sessions. The study can be administered either in person or remotely; however, the investigators anticipate that most participants will complete the study remotely.
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Condition 1 | Active Comparator | Training type 1 will be administered in the first part of the crossover trial and Training type 2 will be administered in the second part of the trial. Each training part consists of 20 twenty-minute long sessions with the recommended frequency of 2 sessions per work day. Thus each training part can be completed in 10 work days (2 weeks). |
|
| Condition 2 | Active Comparator | Training type 2 will be administered in the first part of the crossover trial and Training type 1 will be administered in the second part of the trial. Each training part consists of 20 twenty-minute long sessions with the recommended frequency of 2 sessions per work day. Thus each training part can be completed in 10 work days (2 weeks). |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| N-back | Behavioral | The training program is a personal device-based adaptive version of a visual N-back task, either devoid of game elements or embedded in a gamified platform game |
| Measure | Description | Time Frame |
|---|---|---|
| Change in N-level | N-back is a tablet-based updating working memory task. Participants see a consecutive stream of pictures and are asked to tap the pictures that match those presented N items earlier. All participants will complete 1-back and 2-back, progression to 3-back and beyond is based on performance on the previous level (no more than 4 errors). The outcome measure is the change in the highest N-level reached on the task compared to baseline at Day 2. | Day 24, Day 46, Day 78 |
| Change in Corsi span | Corsi is a tabled-based measure of spatial working memory. Participants see characters emerge one at a time from twelve possible locations and are asked to repeat the sequence by tapping on the locations in the correct order. The task starts with set size two and increases in difficulty using an adaptive algorithm. Participants first play Simple Corsi (without a distractor task), followed by Complex Corsi (with a distractor task). The outcome measure is change in overall span, calculated as the sum of the two highest set sizes that can be recalled in Simple and Complex Corsi tasks, at the point of measurement compared to baseline at Day 3. | Day 25, Day 47, Day 79 |
| Change in Inhibitory Control Composite Score | The score is the mean of standardized dependent variables on tablet-based inhibitory control tasks. The outcome measure is the change in the composite score at the point of measurement compared to baseline at Day 2. | Day 24, Day 46, Day 78 |
| Change in Everyday Memory Questionnaire Revised | The Everyday Memory Questionnaire Revised (Royle & Lincoln, 2008) consists of 13 items that describe everyday events that might involve forgetting. Participants are asked how often on average they think each one has happened to them over the past month on a 5-point scale (0-4) and the total score is calculated as the sum of all responses. The minimum total score is 0 and the maximum is 52, with higher scores indicative of greater presence of memory difficulties. The outcome measure is the change in total score at the point of measurement compared to baseline at Day 1. |
| Measure | Description | Time Frame |
|---|---|---|
| Training Experience Enjoyment Subscale I | Scores range from 1 to 5, with higher scores indicative of greater enjoyment of the training task. | Day 24 |
| Training Experience Enjoyment Subscale II | Scores range from 1 to 5, with higher scores indicative of greater enjoyment of the training task. |
| Measure | Description | Time Frame |
|---|---|---|
| Change in General Cognitive Ability Composite Score | A composite score will be generated by taking the average of standardized outcome measures on tasks in the Standard Older Adult Cognitive Battery (SOACB), which consists of word list learning, complex figure copy, object naming, trail making, a vocabulary task, and matrix reasoning. The outcome measure is the change in the composite score reached on the task compared to baseline at Day 1. |
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Affiliation | Role |
|---|---|---|
| Aaron R Seitz, Phd | University of California, Riverside | Principal Investigator |
| Susanne M Jaeggi, Phd | University of California, Irvine | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of California, Irvine | Irvine | California | 92697 | United States | ||
| University of California, Riverside |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 35106729 | Background | Pahor A, Mester RE, Carrillo AA, Ghil E, Reimer JF, Jaeggi SM, Seitz AR. UCancellation: A new mobile measure of selective attention and concentration. Behav Res Methods. 2022 Oct;54(5):2602-2617. doi: 10.3758/s13428-021-01765-5. Epub 2022 Feb 1. | |
| 30367386 | Background | Pahor A, Stavropoulos T, Jaeggi SM, Seitz AR. Validation of a matrix reasoning task for mobile devices. Behav Res Methods. 2019 Oct;51(5):2256-2267. doi: 10.3758/s13428-018-1152-2. |
Not provided
Not provided
All individual participant data (anonymized).
Data will be available persistently at the conclusion of the study.
There are no access criteria.
Not provided
Not provided
Not provided
| Release Date | Unrelease Date | Unrelease Date Unknown | Reset Date | MCP Release Number |
|---|---|---|---|---|
| Jun 25, 2026 |
Three randomized crossover trials (N-back, Span and Multisensory) will be conducted and in each trial, participants will be randomly assigned to 1 of 2 conditions: Condition 1 consists of training type 1 followed by training type 2, whereas Condition 2 consists of training type 2 followed by training type 1. In the N-back trial, participants will be assigned to Non-Gamified N-back training and Gamified N-back training. In the Span trial, they will be assigned to Non-Gamified Span training and Gamified Span training and in the Multisensory trial, they will be assigned to Non-gamified Unisensory N-back training and Non-gamified Multisensory N-back training.
Not provided
Not provided
Not provided
| Span | Behavioral | The training program is a personal device-based adaptive version of a visual working memory span task, either devoid of game elements or embedded in a gamified platform game |
|
| Multisensory | Behavioral | The training program is a personal device-based adaptive version of an N-back task that features visual stimuli (Unisensory) or visual stimuli paired with unique sounds (Multisensory) and is devoid of game elements |
|
| Day 24, Day 46, Day 77 |
| Day 46 |
| Training Experience Difficulty Subscale I | Score range from 1 to 10, with scores 1-3 indicating that the training was too easy, scores 4-7 indicating that the training was of appropriate difficulty, and scores 8-10 indicating that it was too difficult. | Day 24 |
| Training Experience Difficulty Subscale II | Score range from 1 to 10, with scores 1-3 indicating that the training was too easy, scores 4-7 indicating that the training was of appropriate difficulty, and scores 8-10 indicating that it was too difficult. | Day 46 |
| Training Experience Subjective Progress Subscale I | Scores range from 1 to 5, with higher scores indicative of greater subjective progress on the training task. | Day 24 |
| Training Experience Subjective Progress Subscale II | Scores range from 1 to 5, with higher scores indicative of greater subjective progress on the training task. | Day 46 |
| Training Experience Interface Subscale I | Scores range from 1 to 5, with higher scores indicative of greater satisfaction with the interface (software). | Day 24 |
| Training Experience Interface Subscale II | Scores range from 1 to 5, with higher scores indicative of greater satisfaction with the interface (software). | Day 46 |
| Exit Survey | Participants are asked 5 open-ended questions about their subjective experience of participating in the study. | Day 79 |
| Day 77 |
| Riverside |
| California |
| 92521 |
| United States |
| 17852284 | Background | Royle J, Lincoln NB. The Everyday Memory Questionnaire-revised: development of a 13-item scale. Disabil Rehabil. 2008;30(2):114-21. doi: 10.1080/09638280701223876. |
| 34485810 | Background | Pahor A, Collins C, Smith RN, Moon A, Stavropoulos T, Silva I, Peng E, Jaeggi SM, Seitz AR. Multisensory Facilitation of Working Memory Training. J Cogn Enhanc. 2021 Sep;5(3):386-395. doi: 10.1007/s41465-020-00196-y. Epub 2020 Nov 27. |
| 32793032 | Background | Sandeep S, Shelton CR, Pahor A, Jaeggi SM, Seitz AR. Application of Machine Learning Models for Tracking Participant Skills in Cognitive Training. Front Psychol. 2020 Jul 22;11:1532. doi: 10.3389/fpsyg.2020.01532. eCollection 2020. |