Item Wording Research Articles

Keywords and Semantic Domains in Annual Global Risks Reports through the Past Decade

Incorporating keyword analysis and semantic domain analysis, the present study linguistically investigated ten Global Risks Reports published by the World Economic Forum (WEF) from 2013 to 2024. The corpus comprised 174,800 word types and 405,366 word tokens. Using the features of Wmatrix and the concordance and collocation tools in Sketch Engine, the study identified the top themes, semantic domains, and patterns prevalent in the ten reports. The semantic domain analysis revealed deep insights into the details of these themes, patterns, and the types of language used compared to the keyword analysis. The results showed the obvious interplay between politics, the economy, technology, and the environment, with minimal attention given to humanitarian and social dynamics. Economic risks appear to be the most pressing risks according to these reports, with every theme ultimately boiling down to the economic situation. Additionally, the reports discussed governments’ economics without addressing their impact on citizens and their socioeconomic conditions. This study could be a valuable contribution to the literature that could aid in the tracking of long-term linguistic choices found in risk reports using corpus linguistics. It could also serve as a valuable reference for governments, institutions, or corporations that seek to interpret and analyze global risk reports.

Cognitive testing in 19 countries to refine WHO's Sexual Health Assessment of Practices and Experiences.

To refine a standard questionnaire on sexual practices, experiences and health-related outcomes to improve its cross-cultural applicability and interpretability. We aimed to explore participants' willingness and ability to answer the draft questionnaire items, and determine whether items were interpreted as intended across diverse geographic and cultural environments. We conducted cognitive interviews (n = 645) in three iterative waves of data collection across 19 countries during March 2022-March 2023, with participants of diverse sex, gender, age and geography. Interviewers used a semi-structured field guide to elicit narratives from participants about their questionnaire item interpretation and response processes. Local study teams completed data analysis frameworks, and we conducted joint analysis meetings between data collection waves to identify question failures. Overall, we observed that participants were willing to respond to even the most sensitive questionnaire items on sexual biography and practices. We identified issues with the original questionnaire that (i)affected the willingness (acceptability) and ability (knowledge barriers) of participants to respond fully; and/or (ii)prevented participants from interpreting the questions as intended, including poor wording (source question error), cultural portability and very rarely translation error. Our revisions included adjusting item order and wording, adding preambles and implementation guidance, and removing items with limited cultural portability. We have demonstrated that a questionnaire exploring sexual practices, experiences and health-related outcomes can be comprehensible and acceptable by the general population in diverse global contexts, and have highlighted the importance of rigorous processes for the translation and cognitive testing of such a questionnaire.

Measuring Stakeholder Engagement in Statewide Primary Care Cardiovascular Health Improvement Cooperatives.

Cardiovascular disease (CVD) remains a major national health challenge with significant disparities linked to socioeconomic status, race, ethnicity, sex, and geography, prompting federal efforts to build statewide primary care quality improvement (QI) cooperatives to improve heart health. To be effective, cooperatives require high levels of member engagement and leaders need ways to assess engagement. The objective of this study was to develop and validate a novel Cooperative Member Survey to assess cooperative member engagement and assess the value of the cooperative to members across three statewide heart health QI cooperatives. The 14-item survey included fixed-response and open-ended questions and was developed through multiple iterative rounds across the three cooperatives to gain consensus on the wording of final items using a Delphi process. The survey then was administered to the key stakeholders in the three cooperatives. Findings from both the quantitative and qualitative items were analyzed and reported based on frequencies and emerging themes. The survey was then analyzed to determine factor structure and validity. Analysis revealed a two-factor structure which the research team identified as: (1) Cooperative Engagement, consisting of 11 items that measured how well the cooperative functioned overall, and (2) Cooperative Value, consisting of two items that assessed the perceived value of mutual learning and respect within the cooperative. This two-factor structure indicated that the Cooperative Member Survey successfully captured both the practical aspects of how the cooperative operates and the members' perceived benefits of their involvement. Successful QI cooperatives not only require efficient operations but also a sense of shared value among members. These findings suggest that cooperatives designed to improve public health outcomes may benefit from focusing not only on practical aspects of engagement but also on cultivating mutual respect and collective learning.

An Easily Accessible, Semi-Automated Approach to Creating Personalized Normative Feedback and Risk Feedback Graphics.

Personalized normative feedback interventions show efficacy in reducing health risk behaviors (e.g., alcohol use, sexual aggression). However, complex personalized normative feedback interventions may require manual methods of inputting participant data into graphics, which introduces error, and automated approaches require substantial technical costs and funding and may limit the types of feedback that can be provided. To make personalized normative feedback more accessible, we outline a method of using easily accessible software programs including IBM Statistical Package for the Social Sciences (SPSS), Microsoft Excel, and Microsoft PowerPoint, to create and display complex personalized normative feedback graphics. We also describe methods through which personalized normative feedback graphics can be created within a larger preventive intervention for alcohol and sexual assault in college men. We first provide step-by-step instructions for collecting data and then creating semi-automated syntax files within SPSS and Excel to merge participant data into complex personalized normative feedback graphics in Excel. To do so, we append annotated syntax in text and in supplemental material. Next, we outline the process of creating risk feedback graphics, whereby individual items or exact wording of items are displayed back to the participant. Finally, we provide guidance regarding the process of translating graphics from Excel for viewing via PowerPoint without having to manually update PowerPoint slides for each presentation. Via the described syntax and graphic generation, researchers are then able to create semi-automated personalized normative feedback and risk feedback graphics. This tutorial may help in increasing the dissemination of complex personalized normative feedback interventions.

Voices of Hope: Leveraging Think-Aloud Cognitive Interviews to Develop a Hope Assessment Tool for Young People Living with Chronic Health Conditions.

Hope is a universal, multidimensional, and nuanced concept that may have specific meaning for young people living with chronic health conditions anticipated to last into adulthood. We previously identified definitions of hope for youth living with chronic health conditions derived from young people's and their caregivers' own words. Here, we aimed to develop a hope assessment tool to facilitate the future evaluation of interventions to support wellness and health for young people growing up with chronic health conditions; Methods: We developed Likert-type scale questions using the young people's and caregivers' definitions of hope and applied the think-aloud cognitive interview method to assess understanding and to inform sequential iteration. Interviews were recorded and insights from participant interviews were analyzed thematically. In total, 11 youth (age 12-16 years) with various chronic health conditions completed surveys and interviews over three iteration cycles. Responses to the six-point Likert-scale questions ranged from 1 (none of the time) to 6 (all of the time) (median 5). All of the young people (n = 11) reported that they do things they enjoy, either all of the time or most of the time. In contrast, only 36% felt energetic, either all or most of the time. Three themes were identified: my body and hope; my identity, self-image, and hope; and my world and hope. In addition to gaining important feedback that allowed us to improve item word choice to maximize assessment tool understanding, we gained valuable insights into the multidimensional construct of hope. Thematic analysis revealed the importance of physical symptoms and identity to the meaning of hope in the context of a young person's life. Our new hope assessment tool derived from the young people's own definition of hope has face and content validity for use in clinical and research settings to evaluate hope among pediatric patients living with chronic health conditions.

Approach to Complementary Feeding and Infant Language Use: An Observational Study.

Emerging research suggests that a more infant-led approach to complementary feeding may confer benefits for child language, but these findings are based on parent report studies. Using an observational approach this study examines whether different complementary feeding experiences relate to infant language exposure and language use. Fifty-eight parents recorded a typical infant mealtime in the home (mean infant age = 14 months, SD = 4.15). Observations were coded to measure the prevalence of infant-led and parent-led feeding using the Family Mealtime Coding Scheme. Caregiver language use (word types and token directed at the child, mean length of utterances in child-directed speech, responsiveness and initiations) and the number of infant vocalisations were coded in ELAN using CHAT conventions and parents completed the MacArthur Communicative Development Inventory short form as a measure of child language. Greater observed infant self-feeding was significantly associated with greater observed exposure to language from caregivers (r = 0.312 percentage of infant self-feeding correlated with caregiver word types directed at the child) and a greater number of infant vocalisations (r = 0.320 percentage of infant self-feeding correlated with number of child vocalisations produced). Structural Equation Modelling showed the relationship between infant self-feeding and infant vocalisations to be significantly mediated by enhanced quality and quantity of caregiver child-directed speech (model fit: χ2 [5] = 5.01, p = 0.415, CFI = 1.00 [NF = 0.98], RMSEA = 0.006). Differences in the approach to complementary feeding may shape infant's experiences in ways that support language exposure and use. Autonomy associated with infant self-feeding may enhance opportunities for social interaction.

Assessing the Parenting Stress Index-Short Form (PSI-SF) for Latinx Parents of Children with Intellectual and Developmental Disabilities Within Exploratory Structural Equation Modeling and Structural Equation Modeling-Based Generalizability Theory Frameworks

Although the Parenting Stress Index-Short Form (PSI-SF) is widely applicable, there has been a dearth of research on the psychometric properties and item wording effects associated with the cultural sensitivity of the instrument. This study investigated the psychometric properties, the factor structure, and the negative and positive item wording effects of PSI-SF for 96 Latinx parents of children with intellectual and developmental disabilities in the United States within exploratory structural equation modeling, and structural equation modeling-based generalizability theory frameworks. This study produces the following noteworthy findings. First, the ESEM bifactor model with negatively and positively phrased items best captured the theoretical frameworks underlying the structure of the PSI-SF. Second, adding method factors enhanced the model fits of all the factor models. Third, this study discovered several items with great proportions of method factors. This study recommended that the items with high proportions of method factors, which may likely be culturally insensitive to Latinx parents, be examined further and refined. With the use of accurately assessed PSI-SF scores, practitioners will be better able to support and empower Latinx parents of children with IDD and better meet their needs through the FIRME program, a parent advocacy initiative.

Arabic word tokenization system using the maximum matching model

Word tokenization is the first stage for higher-order Natural Language Processing (NLP) tasks like Part-of-Speech (PoS) tagging, parsing, and named entity recognition. The amount of text on the World Wide Web is growing daily in the present era of technology, necessitating the use of advanced instruments. Since more and more people speak Arabic around the world, Arabic language processing systems must be improved. Due to the writing style of Arabic with a lack of support for capitalization features and the use of compound words, it is difficult to perform word tokenization. This research paper proposes a novel Arabic word tokenization system based on the knowledge. To develop this system, a maximum matching model with its two variations, namely forward and reverse maximum matching is used. The proposed system is implemented in Python. The results produced during system evaluation report high performance.

Development of Digital Health Gender and Sexual Health Literacy scale

Abstract Introduction Health literacy, as the ability to obtain, process and understand health information, including gender and sexuality awareness, appears to be underdeveloped in terms of measurement tools and thematic materials. The literature indicates the existence of serious deficits in gender and sexual health literacy at all levels, with implications for relationships with citizens and patients. Methods Delphi study agreement was conducted and a pool of potential scale items was generated, reflecting a range of skills and abilities within each domain. Items were carefully worded to ensure clarity, cultural sensitivity and relevance to different gender identities and sexual orientations. Expert review and cognitive pre-testing were employed to refine item wording, assess content validity, and ensure that the 10-item scale was comprehensible and relevant to the target population. Results The theoretical development of the 10-item Digital Health Gender and Sexual Health Literacy Scale was successfully completed. The scale items were designed to provide a comprehensive measure of an individual’s ability to navigate the digital landscape for gender and sexual health information. Conclusions The theoretical validation of the Digital Health Gender and Sexual Health Literacy Scale (DiGeSHeL) provides the community with a promising tool to assess individuals’ confidence and ability to use digital technologies for sexual health information and resources. However, further research is needed to validate the scale and test its reliability with a diverse group of participants. Once validated, this scale could be a valuable tool for sexual health promotion programmes to identify gaps and evaluate the impact of digital literacy interventions. Key messages • Gender and sexual literacy are crucial for health. • Health literacy as six vital sign.

A default mode network subsystem supports both item and associative word encoding: Insights from a meta-analysis

Abstract Recent meta-analytic evidence has underscored the significant role of the default mode network (DMN) in facilitating item word encoding. This study builds on this finding through a comprehensive meta-analysis of fMRI-based subsequent memory studies that use words as stimuli. The results highlight several key functions within the DMN. Firstly, the dorsomedial prefrontal cortex (dmPFC) subsystem of the DMN plays a pivotal role in enhancing successful word encoding, suggesting its vital involvement in the semantic processing of incoming verbal information. Secondly, the utility of the dmPFC subsystem extends beyond item word encoding to associative word encoding tasks, demonstrating its broad applicability in verbal information encoding. Thirdly, regions within the left inferior frontal cortex, a core component of the dmPFC subsystem, show increased activity during associative compared to item word encoding, emphasizing their role in integrating verbal information with contextual details. Contrary to previous research that linked the DMN with encoding interference—often attributed to the core subsystem’s tendency for mind-wandering—this study highlights the facilitative role of the dmPFC subsystem in memory encoding. The contrasting roles of the DMN subsystems, both interfering and facilitating, challenge traditional views and advocate for a more nuanced understanding of the network’s role in memory encoding.

Lexical frequency and target language input in the primary languages classroom

ABSTRACT This paper presents an exploratory study of L2 input in the primary languages classroom. Teacher talk in 33 videorecorded lessons taught to Year 3 French beginners by a specialist teacher of French was analysed, in order to document the extent and nature of L2 vocabulary input. Further analyses compared the lexis of teacher talk in this primary setting with high-frequency wordlists derived from two reference corpora designed to support the teaching of L2 French. Results showed that children were exposed to c 45,000 words (tokens) of French, reflecting a teacher vocabulary of c 650 lemmas. Intentionally taught lexis such as foods or animal names typically received massed practice, not always supplemented by distributed practice. The teachers’ partial but consistent use of French for classroom management contributed to a well-balanced distribution of word classes. There was considerable overlap with both reference wordlists, and divergence could largely be explained by the teacher’s choice of topics, and incidental use of French to personalise and engage childrens’ individual interests, as well as for classroom management purposes. In discussion, the need for careful planning and management of vocabulary instruction is highlighted, as well as the significant potential of L2 classroom management to enrich lexical input.

Development of the Compassionate Technology Scale for Professionals (CTS-P): value driven evaluation of digital mental health interventions

BackgroundCompassion is an essential and beneficial value in mental healthcare. However, how digital mental health interventions influence compassion in treatment has not been systematically investigated, due to the lack of appropriate measurement instruments. To address this gap, we developed the Compassionate Technology Scale for Professionals (CTS-P), aimed at mental health professionals.MethodsWe used Q-methodology, a method that combines quantitative and qualitative analysis to explore shared viewpoints on a particular topic, to select and refine items. Participants were 15 professionals from different areas of mental healthcare. In individual sessions, while thinking aloud, they sorted 35 statements on relevance for evaluating technology use on compassion. The statements were based on a scientific conceptualization of compassion with five elements. The sorting task was followed by a short interview to explore participants’ associations with compassion and technology.ResultsWith by-person factor analysis, we found three different viewpoints among participants, all with eigenvalues > 1 and with a total explained variance of 63.02%. We selected prioritized items of each viewpoint and for each theoretical element of compassion, resulting in a full scale (15 items) and a short scale (3 items). Based on qualitative input from participants, the scale was adapted to clarify its focus and the wording of items. While thinking aloud, participants shared benefits and critical notes regarding technology and compassion.DiscussionTogether with key stakeholders, we developed the CTS-P. Most participants prioritized the potential of technology to obtain more information and be closer to their client in facilitating compassion. The main critical note participants had was that technology is not necessary to support compassion at the therapist’s experiential level. This emphasizes the need to further explore how mental health professionals and technology can complement each other in a system of compassionate care. Future research should explore the factor structure, validity, and reliability of the scale through psychometric validation.ConclusionsThe CTS-P can make the extent to which technology for mental healthcare influences elements of compassion measurable and comparable. The scale can prove useful for prioritizing the value of compassion in both the development and use of digital mental health interventions.

Assessing Jealousy: Factor Analyses, Measurement Invariance, Nomological Validity, and Longitudinal APIM Analyses of the Multidimensional Jealousy Scale.

The Multidimensional Jealousy Scale is the standard instrument to assess cognitive, emotional, and behavioral jealousy. We examined competing factor models and external correlations with broad and narrow traits. Across two studies, we analyzed four samples (Ntotal = 2,117). Confirmatory factor analysis supported the measurement model of three correlated factors in comparison to unidimensional, second-order, and bifactor models. Thus, speaking against the use of a total score. Furthermore, we found measurement invariance between romantic partners. We extended the Multidimensional Jealousy Scale (MJS)' nomological net to personality pathology and replicated prior findings of associations with broad and narrow traits. Study 2 examined longitudinal data (5- to 9-month lag) from couples. Actor-Partner Interdependence Model analyses showed that the MJS predicts facets of relationship satisfaction in actors and partners. We discuss potential avenues for revising the MJS (e.g., heteronormative item wordings).

Aspect Based Feature Extraction in Sentiment Analysis using Bi-GRU-LSTM Model

In Natural Language Processing (NLP), Sentiment Analysis (SA) is a fundamental process which predicts the sentiment expressed in sentences. In contrast to conventional sentiment analysis, Aspect-Based Sentiment Analysis (ABSA) employs a more nuanced approach to assess the sentiment of individual aspects or components within a document or sentence. Its objective is to identify the sentiment polarity, such as positive, neutral, or negative, associated with particular elements disclosed within a sentence. This research introduces a novel sentiment analysis technique that proves to be more efficient in sentiment analysis compared to current methods. The suggested sentiment analysis method undergoes three key phases: 1. Pre-processing 2. Extraction of aspect sentiment and 3. Sentiment analysis classification. The input text data undergoes pre-processing through the implementation of four typical text normalization techniques, which include stemming, stop word elimination, lemmatization, and tokenization. By employing these methods, the provided text data is prepared and fed into the aspect sentiment extraction phase. During the aspect sentiment extraction phase, features are obtained through a series of steps, including enhanced ATE (Aspect Term Extraction), assessment of word length, and determination of cosine similarity. By following these steps, the relevant features are extracted on the basis of aspects and sentiments involved in the text data. Further, a hybrid classification model is proposed to classify sentiments. In this work, two of the Deep Learning (DL) classifiers, Bi-directional Gated Recurrent Unit (Bi-GRU) and Long Short-Term memory (LSTM) are used in proposing a hybrid classification model which classifies the sentiments effectively and provides accurate final predicted results. Moreover, the performance of proposed sentiment analysis technique is analyzed experimentally to show its efficacy over other models.

Fake News Detection Using Optimized Convolutional Neural Network and Bidirectional Long Short-Term Memory

The spread of fake news in the digital age threatens the integrity of online information, influences public opinion, and creates confusion. This study developed and tested a fake news detection model using an enhanced CNN-BiLSTM architecture with GloVe word embedding techniques. The WELFake dataset comprising 72,000 samples was used, with training and testing data ratios of 90:10, 80:20, and 70:30. Preprocessing involved GloVe 100-dimensional word embedding, tokenization, and stopword removal. The CNN-BiLSTM model was optimized with hyperparameter tuning, achieving an accuracy of 96%. A larger training data ratio demonstrated better performance. Results indicate the effectiveness of this model in distinguishing fake news from real news. This study shows that the CNN-BiLSTM architecture with GloVe embedding can achieve high accuracy in fake news detection, with recommendations for further research to explore preprocessing techniques and alternative model architectures for further improvement.

Routine Language Intervention: Supporting Spanish-Speaking Mothers’ Talk to Toddlers During Everyday Routines

SYNOPSIS Objective. Toddlers learn language as they participate in everyday routines in the home environment. The Routine Language Intervention encourages caregivers to infuse language in everyday routines to support toddlers’ language development. Design. Researchers collaborated with a Spanish-speaking, immigrant community in New York City to develop an intervention that is grounded in the routines that mothers commonly engage in with their toddlers. Altogether, 51 mothers participated in 6 months of group workshops and home visits. To test the efficacy of the intervention, mothers were videorecorded interacting with their toddlers at home before and after participating in the intervention. A comparison group of 12 families drawn from the same community was also videorecorded in their homes. Results. Mothers who participated in the Routine Language Intervention increased their speech to toddlers, nearly doubling word tokens and word types, and used more types and tokens than mothers in the matched comparison group. Increases in maternal speech were seen for words referring to targeted daily routines (e.g., mealtime, grooming, play and literacy) and extended to other words (e.g., unrelated household objects). Conclusions. Routine Language offers a culturally sensitive, easy-to-implement intervention that builds on families’ everyday routines and yields benefits for toddlers’ early language exposure.

The Inventory of Callous-Unemotional Traits (ICU) self-report version: Factor structure, measurement invariance, and predictive validity in justice-involved male adolescents.

The Inventory of Callous-Unemotional Traits (ICU) is a widely used measure of callous-unemotional (CU) traits that may aid in the assessment of the diagnostic specifier "with limited prosocial emotions," which has been added to diagnostic criteria for conduct disorder. Though there is substantial support for use of the ICU total score, the scale's factor structure has been highly debated. Inconsistencies in past factor analyses may be largely attributed to failure to control for method variance due to item wording (i.e., half of the items being worded in the callous direction and half worded in the prosocial direction). Thus, the present study used a multitrait-multimethod confirmatory factor analytic approach that models both trait and method variance to test the factor structure of the ICU self-report in a clinically relevant, high-risk sample of justice-involved male adolescents (N = 1,216). When comparing the fit of empirical and theoretical models, goodness of fit indices (χ² = 1105.877, df = 190, root-mean-square error of approximation = .063, comparative fit index = .916, Tucker-Lewis index = .878, standardized root-mean-square residual = .051) provided support for a hierarchical four-factor model (i.e., one overarching callous-unemotional factor, four latent trait factors) when accounting for method variance (i.e., covarying positively worded items). This factor structure is consistent with the way the ICU was constructed and with criteria for the limited prosocial emotions specifier. In addition, measurement invariance of this factor structure across age, race, and ethnicity was supported, and the predictive validity of the ICU was supported across these demographic groups in predicting self-reported antisocial behavior and rearrests over a 5-year period following an adolescent's first arrest. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

German translation and cross-cultural adaptation of the Vestibular Schwannoma Quality of Life Index (VSQOL)

BackgroundVestibular schwannomas (VSs) are benign tumors of the vestibulocochlear nerve that often cause significant neurological and functional impairment. Patient-reported outcomes, including quality of life (QoL), are essential for understanding the overall impact of VS and its treatment. This study aimed to translate and culturally adapt the Vestibular Schwannoma Quality of Life (VSQOL) Index into German to expand its relevance to German-speaking populations.MethodsWe used a qualitative approach including translation and cognitive interviews with 10 patients who underwent VS surgery. The translation process followed the TRAPD protocol to ensure linguistic and conceptual accuracy. Cognitive interviews assessed the comprehensibility and relevance of the translated questionnaire.ResultsThe translation showed remarkable consistency between translators, with minor discrepancies resolved by consensus. Cognitive interviews provided valuable insights that led to refinements in item wording. Participants emphasized the importance of an additional item on physician referrals, reflecting differences in health care systems between the United States and Germany.ConclusionsThe German VSQOL provides a comprehensive tool for assessing QoL in patients with VS that integrates patient-centered dimensions. A Validation study is underway to establish its reliability and validity.

Factor Structure and Reliability of the Lithuanian Version of the Public Speaking Anxiety Scale

Social Anxiety Disorder (SAD) is especially prevalent among young individuals aged 18–25 and significantly affects daily social activities and interpersonal relationships. Public Speaking Anxiety (PSA), a subtype of SAD, is a widespread concern that affects one in five individuals. The study focuses on the Public Speaking Anxiety Scale (PSAS), with the aim of assessing the factor structure and reliability of the Lithuanian version (PSAS-LT). The PSAS-LT, administered to 227 participants aged 18–25, comprises 17 Likert-scaled items, evaluating cognitive, behavioral, and physiological aspects of PSA. Three models were tested: a single-factor model, a three-factor model and a single factor model with positive and negative item wording factors model. Results indicate less than desirable fit for the single, and three-factor models, suggesting the need for alternative structures. The model that included a single factor as well as positive and negative item wording factors demonstrated a reasonably good fit. The diagnostic validity confirmed that the PSAS-LT effectively differentiated between participants with and without history of anxiety disorders. The total score of the PSAS-LT had excellent internal consistency. Despite limitations, including convenience sampling and nonrepresentative sample, the study contributes valuable insights into refining the understanding of PSA assessment features, emphasizing the importance of considering response patterns. Future research should validate these findings with larger and more diverse samples of the Lithuanian population.

Long-term cognitive and affective consequences of mild traumatic brain injury: comparison with older adults

ABSTRACT Objective Memory and affective processing were compared in young adults with a remote mild traumatic brain injury (mTBI), to healthy younger and older adults. We evaluated memory performance when encoding was done under multi-tasking (divided attention) conditions, likely to exacerbate cognitive and psychological symptoms in mTBI. Methods Participants studied pairs of unrelated words under either full or divided attention conditions. Memory for single words (item memory) and for pairs of words (associative memory) was then assessed in sequential independent recognition tests, under full attention. Results Associative memory was poorer than item memory, and worse when encoding was done under divided than full attention. The decline in recognition accuracy from full to divided attention conditions on the associative memory test was significantly greater in mTBI compared to young adults and was similar in magnitude to that observed in older adults under full attention. Self-reported mental and total fatigue increased significantly as performance on the memory tests, following the divided attention condition, decreased, but only in the mTBI group. Conclusions Results show lingering memory deficits, and suggest that cognitive tasks may be experienced as psychologically more demanding in those with a mTBI, even months or years after injury.