Investigating the Role of Individual Differences in Adherence to Cognitive Training

Consistent with research across several domains, intervention adherence is associated with desired outcomes. Our study investigates adherence, defined by participants’ commitment to, persistence with, and compliance with an intervention’s regimen, as a key mechanism underlying cognitive training effectiveness. We examine this relationship in a large and diverse sample comprising 4,775 adults between the ages of 18 and 93. We test the predictive validity of individual difference factors, such as age, gender, cognitive capability (i.e., fluid reasoning and working memory), grit, ambition, personality, self-perceived cognitive failures, socioeconomic status, exercise, and education on commitment to and persistence with a 20-session cognitive training regimen, as measured by the number of sessions completed. Additionally, we test the relationship between compliance measures: (i) spacing between training sessions, as measured by the average time between training sessions, and (ii) consistency in the training schedule, as measured by the variance in time between training sessions, with performance trajectories on the training task. Our data suggest that none of these factors reliably predict commitment to, persistence with, or compliance with cognitive training. Nevertheless, the lack of evidence from the large and representative sample extends the knowledge from previous research exploring limited, heterogenous samples, characterized by older adult populations. The absence of reliable predictors for commitment, persistence, and compliance in cognitive training suggests that nomothetic factors may affect program adherence. Future research will be well served to examine diverse approaches to increasing motivation in cognitive training to improve program evaluation and reconcile the inconsistency in findings across the field.

[1]  N. Charness,et al.  A Machine-Learning Based Approach for Predicting Older Adults' Adherence to Technology-Based Cognitive Training , 2022, Inf. Process. Manag..

[2]  F. Gobet,et al.  Cognitive Training: A Field in Search of a Phenomenon , 2022, Perspectives on psychological science : a journal of the Association for Psychological Science.

[3]  John W. Schwieter,et al.  The Cambridge Handbook of Working Memory and Language , 2022 .

[4]  Aaron R. Seitz,et al.  Near transfer to an unrelated N-back task mediates the effect of N-back working memory training on matrix reasoning , 2022, Nature Human Behaviour.

[5]  N. Charness,et al.  Investigating message framing to improve adherence to technology-based cognitive interventions. , 2021, Psychology and aging.

[6]  Patrick A. LaCount,et al.  Building a Theoretical Model for Supporting Teens' Autonomy Daily (STAND): A Network Analysis of Family-Perceived Changes. , 2021, The Behavior Therapist.

[7]  Susanne M. Jaeggi,et al.  Exploring Individual Differences as Predictors of Performance Change During Dual-N-Back Training , 2021, Journal of Cognitive Enhancement.

[8]  S. Jaeggi,et al.  Exploring Individual Differences as Predictors of Performance Change During Dual-N-Back Training , 2021, Journal of Cognitive Enhancement.

[9]  Y. Munakata,et al.  Why Does Cognitive Training Yield Inconsistent Benefits? A Meta-Analysis of Individual Differences in Baseline Cognitive Abilities and Training Outcomes , 2021, Frontiers in Psychology.

[10]  D. Collado-Mateo,et al.  Key Factors Associated with Adherence to Physical Exercise in Patients with Chronic Diseases and Older Adults: An Umbrella Review , 2021, International journal of environmental research and public health.

[11]  S. Faraone,et al.  Further evidence of low adherence to stimulant treatment in adult ADHD: an electronic medical record study examining timely renewal of a stimulant prescription , 2020, Psychopharmacology.

[12]  Susanne M. Jaeggi,et al.  Investigating the effects of spacing on working memory training outcome - a randomized controlled multi-site trial in older adults. , 2019, The journals of gerontology. Series B, Psychological sciences and social sciences.

[13]  H. Soininen,et al.  Computer-based cognitive training for older adults: Determinants of adherence , 2019, PloS one.

[14]  Michèle Allard,et al.  Adherence to multidomain interventions for dementia prevention: Data from the FINGER and MAPT trials , 2019, Alzheimer's & Dementia.

[15]  Thomas S. Redick The Hype Cycle of Working Memory Training , 2019, Current directions in psychological science.

[16]  Aaron R. Seitz,et al.  Divergent Research Methods Limit Understanding of Working Memory Training , 2019, Journal of Cognitive Enhancement.

[17]  J. Hadwin,et al.  A Growth Mixture Modeling Study of Learning Trajectories in an Extended Computerized Working Memory Training Programme Developed for Young Children Diagnosed With Attention-Deficit/Hyperactivity Disorder , 2019, Front. Educ..

[18]  Aaron R. Seitz,et al.  Improving Methodological Standards in Behavioral Interventions for Cognitive Enhancement , 2019, Journal of Cognitive Enhancement.

[19]  Thomas S. Redick,et al.  The Influence of Individual Differences in Cognitive Ability on Working Memory Training Gains , 2018, Journal of cognitive enhancement : towards the integration of theory and practice.

[20]  Aaron R. Seitz,et al.  Validation of a matrix reasoning task for mobile devices , 2018, Behavior Research Methods.

[21]  P. Shah,et al.  How to play 20 questions with nature and lose: Reflections on 100 years of brain-training research , 2018, Proceedings of the National Academy of Sciences.

[22]  Susanne M. Jaeggi,et al.  The effect of monetary compensation on cognitive training outcomes , 2018, Learning and Motivation.

[23]  Susanne M. Jaeggi,et al.  Exploring N-Back Cognitive Training for Children With ADHD , 2018, Journal of attention disorders.

[24]  Evelyn H. Kroesbergen,et al.  Coaching positively influences the effects of working memory training on visual working memory as well as mathematical ability , 2018, Neuropsychologia.

[25]  Carla De Simoni,et al.  Do Individual Differences Predict Change in Cognitive Training Performance? A Latent Growth Curve Modeling Approach , 2017 .

[26]  Victor B. Zordan,et al.  The Benefits and Challenges of Implementing Motivational Features to Boost Cognitive Training Outcome , 2017, Journal of Cognitive Enhancement.

[27]  J. Karbach,et al.  Who Benefits the Most? Individual Differences in the Transfer of Executive Control Training Across the Lifespan , 2017 .

[28]  A. V. Leij,et al.  Individual Differences in Training Gains and Transfer Measures: An Investigation of Training Curves in Children with Attention-Deficit/Hyperactivity Disorder , 2017 .

[29]  Rashmita S. Mistry,et al.  Subjective Social Status and Self-Reported Health Among US-born and Immigrant Latinos , 2017, Journal of Immigrant and Minority Health.

[30]  Damian P. Birney,et al.  The effects of personality and metacognitive beliefs on cognitive training adherence and performance , 2016 .

[31]  Elizabeth A. L. Stine-Morrow,et al.  Do “Brain-Training” Programs Work? , 2016, Psychological science in the public interest : a journal of the American Psychological Society.

[32]  Monica Melby-Lervåg,et al.  There is no convincing evidence that working memory training is effective: A reply to Au et al. (2014) and Karbach and Verhaeghen (2014) , 2015, Psychonomic Bulletin & Review.

[33]  Aaron R. Seitz,et al.  The Impacts of Video Games on Cognition (and How the Government Can Guide the Industry) , 2015 .

[34]  G. Andersson,et al.  Experiences of non-adherence to Internet-delivered cognitive behavior therapy: A qualitative study , 2015 .

[35]  F. Fischer,et al.  Does Working Memory Training Transfer? A Meta-Analysis Including Training Conditions as Moderators , 2015 .

[36]  Tony Leung,et al.  Would Older Adults with Mild Cognitive Impairment Adhere to and Benefit from a Structured Lifestyle Activity Intervention to Enhance Cognition?: A Cluster Randomized Controlled Trial , 2015, PloS one.

[37]  Victor B. Zordan,et al.  How to build better memory training games , 2015, Front. Syst. Neurosci..

[38]  Aaron R. Seitz,et al.  Broad-based visual benefits from training with an integrated perceptual-learning video game , 2014, Vision Research.

[39]  H. Christensen,et al.  Predictors of Adherence and Outcome in Internet-Based Cognitive Behavior Therapy Delivered in a Telephone Counseling Setting , 2014, Cognitive Therapy and Research.

[40]  Virgílio F. Bento,et al.  Web-Based Cognitive Training: Patient Adherence and Intensity of Treatment in an Outpatient Memory Clinic , 2014, Journal of medical Internet research.

[41]  P. Shah,et al.  Spaced cognitive training promotes training transfer , 2014, Front. Hum. Neurosci..

[42]  Susanne M. Jaeggi,et al.  The role of individual differences in cognitive training and transfer , 2014, Memory & cognition.

[43]  J. Uderman,et al.  A randomized clinical trial of Cogmed Working Memory Training in school-age children with ADHD: a replication in a diverse sample using a control condition. , 2014, Journal of child psychology and psychiatry, and allied disciplines.

[44]  J. Jonides,et al.  Cognitive training for ADHD: The importance of individual differences , 2012 .

[45]  Yves Rosseel,et al.  lavaan: An R Package for Structural Equation Modeling , 2012 .

[46]  Susanne M. Jaeggi,et al.  Short- and long-term benefits of cognitive training , 2011, Proceedings of the National Academy of Sciences.

[47]  Pier J. M. Prins,et al.  Does Computerized Working Memory Training with Game Elements Enhance Motivation and Training Efficacy in Children with ADHD? , 2011, Cyberpsychology Behav. Soc. Netw..

[48]  J. Uderman,et al.  Improving medication adherence in chronic pediatric health conditions: a focus on ADHD in youth. , 2010, Current pharmaceutical design.

[49]  V. Entwistle,et al.  Supporting Patient Autonomy: The Importance of Clinician-patient Relationships , 2010, Journal of General Internal Medicine.

[50]  Kathleen M Griffiths,et al.  Predictors of Adherence by Adolescents to a Cognitive Behavior Therapy Website in School and Community-Based Settings , 2009, Journal of medical Internet research.

[51]  P. Quinn,et al.  Please Scroll down for Article Journal of Personality Assessment Development and Validation of the Short Grit Scale (grit-s) , 2022 .

[52]  R. West,et al.  Assessing compliance: Active versus inactive trainees in a memory intervention , 2008, Clinical interventions in aging.

[53]  S. Gau,et al.  National survey of adherence, efficacy, and side effects of methylphenidate in children with attention-deficit/hyperactivity disorder in Taiwan. , 2008, The Journal of clinical psychiatry.

[54]  Angela L. Duckworth,et al.  Grit: perseverance and passion for long-term goals. , 2007, Journal of personality and social psychology.

[55]  N. Adler,et al.  Does Subjective Social Status Predict Health and Change in Health Status Better Than Objective Status? , 2005, Psychosomatic medicine.

[56]  E. Epel,et al.  Relationship of subjective and objective social status with psychological and physiological functioning: preliminary data in healthy white women. , 2000, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[57]  E. Deci,et al.  Autonomous regulation and long-term medication adherence in adult outpatients. , 1998, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[58]  G. Saucier Mini-markers: a brief version of Goldberg's unipolar big-five markers. , 1994, Journal of personality assessment.

[59]  D. Broadbent,et al.  The Cognitive Failures Questionnaire (CFQ) and its correlates. , 1982, The British journal of clinical psychology.

[60]  Susanne M. Jaeggi,et al.  Individual Differences in Cognitive Training Research , 2020 .

[61]  Susanne M. Jaeggi,et al.  Individual differences and motivational effects , 2016 .