Frontiers in Psychiatry is proud to present our Psychometrics series in Aging Psychiatry. This series of Article Collections will deal with the definition and measurement of clinical constructs. The Psychometrics in Aging Psychiatry Article Collection aims to collect original research and review articles on new developments and applications of psychometrics and psychiatric assessment in Aging Psychiatry and the related areas. Articles can include, but are not limited to, the following topics: Clinical psychometrics The challenge of quantitative psychiatry and measurement Application, validity, and reliability of psychiatric scales Measuring and modelling Psychometrics as predictive model

Pro Chancellor, Biotechnology, KL University, Guntur, India

Agostino Gemelli University Polyclinic (IRCCS)

Koç University school of medicine

Chang Gung Memorial Hospital

Western Sydney University

Frontiers in Psychiatry

Aging Psychiatry

Psychometrics in Psychiatry 2022: Aging Psychiatry

The field of aging psychiatry is undergoing a significant transformation, propelled by the rigorous application of psychometric principles to better define and measure clinical constructs. This Editorial provides a comprehensive overview of the contributions made by four original papers within the &#x201c;Psychometrics in Aging Psychiatry&#x201d; series. These articles collectively describe the advancements and challenges in the measurement and assessment of psychiatric symptoms and cognitive functions in older adults, highlighting the importance of robust psychometric tools in clinical practice and dictate the need for continuous innovation in assessment methodologies.Psychometrics, the scientific discipline concerned with the theory and technique of psychological measurement, traces its origins back to the late 19th century (<a href="#B1">1</a>). The foundations of psychometrics were laid in late 1880s at the University of Cambridge, where the first laboratory dedicated to this science was established. This pioneering effort marked the beginning of a systematic approach to measuring cognitive abilities, personality traits, and other psychological attributes (<a href="#B2">2</a>). By the turn of the century and over time, up to the modern era, measurement approaches have evolved and perfected with the aim to construct reliable and valid tests, inspired by theoretical principles which could be applied to different clinical settings and research protocols (<a href="#B3">3</a>).In psychiatry, psychometrics has established a key role by providing reliable and valid tools for defining mental health conditions, ensuring accurate diagnosis, and guiding suitable treatments (<a href="#B4">4</a>). Administering standardized tests to measure psychological functioning and describe personality characteristics of patients diagnosed with psychiatric diseases supports evidence-based assessment and contributes to tailored care and better evaluation of the efficacy of both psychological and pharmacological interventions (<a href="#B5">5</a>).The introduction of psychometric methods revolutionized the field, allowing for the quantification of complex psychological phenomena and facilitating large-scale epidemiological studies (<a href="#B6">6</a>–<a href="#B8">8</a>). In the context of aging psychiatry, psychometrics is particularly vital due to the multifaceted nature of psychiatric disorders in older adults, which often involve overlapping symptoms of cognitive decline and mood disturbances. In this context, psychometrics not only facilitates the identification of specific pathologies and favors differential diagnosis, but also permits to monitor functional consequences of diseases (<a href="#B9">9</a>). By employing sophisticated measurement techniques, psychometrics can support and enhance our understanding and management of disorders, which consequentially is likely to improve patient outcomes.<a href="https://doi.org/10.3389/fpsyt.2023.1154519">Vaccarino et&nbsp;al.</a> present a critical evaluation of the Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) within populations suffering from neurodegenerative disorders (ND) compared to those with major depressive disorder (MDD). Applying Rasch Measurement Theory, the study confirms the QIDS-SR’s suitability for both cohorts, demonstrating unidimensionality and satisfactory category ordering. However, it also reveals gaps in item targeting, suggesting that the QIDS-SR may not effectively delineate levels of depressive severity in ND patients. These gaps suggest that while the QIDS-SR is effective for general depressive symptom screening, it requires refinement to capture the specific depressive conditions in ND. This paper reinforces the call for specialized tools to better serve the diagnostic needs of individuals with neurodegenerative conditions.<a href="https://doi.org/10.3389/fpsyt.2023.1209745">Samtani et&nbsp;al.</a> provide a thorough review of social cognition assessments in individuals with neurocognitive impairments. They emphasize the critical role of social cognition in clinical decision-making and treatment planning. Their paper advocates for the adoption of validated, multicomponent and multidimensional measures that can accurately capture the social cognitive deficits in this population cohort. By establishing reliable tools, clinicians can better predict and monitor changes, ultimately improving patient care. This review urges the need for a standardized approach to social cognition assessment, which will be vital for comprehensive neuropsychiatric evaluations.<a href="https://doi.org/10.3389/fpsyt.2024.1284559">Yang et&nbsp;al.</a> explore the factors influencing insight and treatment attitudes among hospitalized older patients with major depression. Their study identifies cognitive function, type of admission (e.g., involuntary), dependence on a caregiver, social functionality, and length of hospital stay as significant predictors. Their findings suggest that improving cognitive function and social support systems, alongside careful consideration of admission types, could enhance treatment outcomes. This research further describes the associations that exist between cognitive and social factors in managing depression in older hospitalized adults, highlighting areas for targeted interventions.<a href="https://doi.org/10.3389/fpsyt.2023.1203590">Saldivia et&nbsp;al.</a> establish the relationships between life satisfaction, positive affect, depression, and anxiety among older adults in Chile. The study identifies multiple variables, including geographical area, sex, age, education level, household composition, partner status, employment status, caregiver status, economic satisfaction, chronic disease presence, medication use, and alcohol consumption as significant predictors. The research team found that satisfaction with health emerged as the most influential predictor for positive affect and depressive and anxiety symptoms. This research highlights the multifaceted nature of well-being in older adults, emphasizing the importance of addressing both positive and negative dimensions to improve mental health outcomes.Our &#x201c;Psychometrics in Aging Psychiatry&#x201d; series provides new insights into the application of psychometric principles to aging populations. Together, these studies highlight the critical role of psychometrics in enhancing the assessment and treatment of psychiatric conditions in older adults. They also raise important questions about the need for tailored measurement tools that can accurately capture the complex and overlapping clinical symptoms experienced by this population. By advancing our understanding of these issues, this Research Topic contributes to the ongoing effort to improve mental health outcomes for older adults through more precise and effective psychometric assessments.JS: Writing &#x2013; review &amp; editing, Writing &#x2013; original draft. MM:&#xa0;Writing &#x2013; review &amp; editing.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Editorial: Psychometrics in psychiatry 2022: aging psychiatry

ObjectiveTo explore the insight, treatment attitude, and related influencing factors of hospitalized elderly patients suffering from major depression.</sec>MethodsA total of 141 hospitalized elderly patients with depression were selected as the research objects. Insight was evaluated by the total score of the Insight and Treatment Attitude questionnaire (ITAQ). The data collected included sociodemographic characteristics, psychiatric symptoms, delirium status, social functioning, social support, suicide risk, and cognitive function.</sec>ResultsThe sample included 74.5% of female patients, and the mean age was 67.53 (sd=7.19) years. The influencing factors of inpatients with depression included alcohol consumption, length of hospitalization, admission types, and the main caregivers (P<0.05). The various factors were further analyzed by linear regression, revealing that the insight and treatment attitude of elderly depressed hospitalized patients were mainly related to the Mini-Mental State Examination (MMSE) (β= 0.225, 95% CI 0.055–0.395, P=0.01), dependent on a caregiver (β=-5.810, 95% CI -8.086~-3.535, P<0.001), the type of admission (involuntary admission) (β=-3.365, 95% CI -5.448~-1.283, P=0.002), Functional Activities Questionnaire (FAQ) (β=-0.156, 95% CI -0.303~-0.010, P=0.037), and length of stay (≤28 days) (β=2.272, 95% CI 0.055~-4.489, P=0.045).</sec>ConclusionThe level of insight was affected by cognitive function, involuntary admission, dependent on a caregiver, social function and length of stay. Future studies should focus on cognitive function recovery, observation of admission mode, and self-care ability in elderly patients with depression.</sec>

Objective: To explore the insight, treatment attitude, and related influencing factors of hospitalized elderly patients suffering from major depression.Methods: A total of 141 hospitalized elderly patients with depression were selected as the research objects. Insight was evaluated by the total score of the Insight and Treatment Attitude questionnaire (ITAQ). The data collected included sociodemographic characteristics, psychiatric symptoms, delirium status, social functioning, social support, suicide risk, and cognitive function.Results: The sample included 74.5% of female patients, and the mean age was 67.53 (sd=7.19) years. The influencing factors of inpatients with depression included alcohol consumption, length of hospitalization, admission types, and the main caregivers (P&lt;0.05). The various factors were further analyzed by linear regression, revealing that the insight and treatment attitude of elderly depressed hospitalized patients were mainly related to the Mini-Mental State Examination (MMSE) (β= 0.225, 95% CI 0.055–0.395, P=0.01), dependent on a caregiver (β=-5.810, 95% CI -8.086~-3.535, P&lt;0.001), the type of admission (involuntary admission) (β=-3.365, 95% CI -5.448~-1.283, P=0.002), Functional Activities Questionnaire (FAQ) (β=-0.156, 95% CI -0.303~-0.010, P=0.037), and length of stay (≤28 days) (β=2.272, 95% CI 0.055~-4.489, P=0.045).Conclusion: The level of insight was affected by cognitive function, involuntary admission, dependent on a caregiver, social function and length of stay. Future studies should focus on cognitive function recovery, observation of admission mode, and self-care ability in elderly patients with depression.

Factors influencing the level of insight and treatment attitude: a cross-sectional study of 141 elderly patients of major depression in Guangzhou, China

Neurocognitive disorders involves progressive decline in cognition, function, behavior and needs. Recent developments have identified the need to characterize social cognition in individuals with neurocognitive impairments to support uncertainty in clinical decision making, treatment plans and monitoring individual change. Routine social cognition assessments have thus been more recently used and adopted in persons with dementia or mild cognitive impairment. This work serves to summarize current assessments and provide a discourse on the practicality of available social cognition tools, its implication in clinical practice and key future directions. We highlight advantages in establishing validated, multicomponent measures of social cognition for people with neurocognitive disorders.

Neurocognitive disorders involves progressive decline in cognition, function, behavior and needs. Recent developments have identified the need to characterize social cognition in individuals with neurocognitive impairments to support uncertainty in clinical decision making, treatment plans and monitoring individual change. Routine social cognition assessments have thus been more recently used and adopted in persons with dementia or mild cognitive impairment. This work serves to summarize current assessments and provide a discourse on the practicality of available social cognition tools, its implication in clinical practice and key future directions. We highlight advantages in establishing validated, multicomponent measures of social cognition for people with neurocognitive disorders.

Beyond memory: exploring the value of social cognition for older adults with neurocognitive disorders

BackgroundThis study aims to describe the relationship between life satisfaction, positive affect, depression and anxiety symptoms with sociodemographic, psychosocial and clinical variables, and to identify the relative importance of these predictor groups.</sec>MethodsWe evaluated life satisfaction (SWLS), positive affect (PANAS), depressive (PHQ-9), and anxiety (GAI) symptoms and their association with sociodemographic, psychosocial and clinical variables in a multistage, random general population sample of fully functioning individuals aged 60–80 years from the Concepción province and Gran Santiago, Chile (n = 396). We performed weighted multiple regression analysis, considering the complex sample structure with age group, sex, and geographical area, complemented with general and conditional dominance analyses to estimate the relevance of the predictor groups.</sec>ResultsWe found significant associations with the geographical area, sex, age, education level, household members, having a partner, employment status, caregiver status, economic satisfaction, presence of chronic diseases, medication use, and alcohol use. Satisfaction with health was the most important predictor for positive affect (p < 0.001), depressive (p < 0.001), and anxiety (p < 0.001) symptoms, while alcohol use was the most significant predictor for life satisfaction (p < 0.001).</sec>ConclusionSimultaneously studying the positive and negative dimensions of wellbeing and mental health in older adults allows for a more comprehensive perspective on the challenges faced during this stage of life. This study accounts for previously unknown associations and contributes to the identification of common and specific predictors in both dimensions.</sec>

Background: This study aims to describe the relationship between life satisfaction, positive affect, depression and anxiety symptoms with sociodemographic, psychosocial and clinical variables, and to identify the relative importance of these predictor groups.Methods: We evaluated life satisfaction (SWLS), positive affect (PANAS), depressive (PHQ-9), and anxiety (GAI) symptoms and their association with sociodemographic, psychosocial and clinical variables in a multistage, random general population sample of fully functioning individuals aged 60–80 years from the Concepción province and Gran Santiago, Chile (n = 396). We performed weighted multiple regression analysis, considering the complex sample structure with age group, sex, and geographical area, complemented with general and conditional dominance analyses to estimate the relevance of the predictor groups.Results: We found significant associations with the geographical area, sex, age, education level, household members, having a partner, employment status, caregiver status, economic satisfaction, presence of chronic diseases, medication use, and alcohol use. Satisfaction with health was the most important predictor for positive affect (p &lt; 0.001), depressive (p &lt; 0.001), and anxiety (p &lt; 0.001) symptoms, while alcohol use was the most significant predictor for life satisfaction (p &lt; 0.001).Conclusion: Simultaneously studying the positive and negative dimensions of wellbeing and mental health in older adults allows for a more comprehensive perspective on the challenges faced during this stage of life. This study accounts for previously unknown associations and contributes to the identification of common and specific predictors in both dimensions.

Life satisfaction, positive affect, depression and anxiety symptoms, and their relationship with sociodemographic, psychosocial, and clinical variables in a general elderly population sample from Chile

BackgroundSymptoms of depression are present in neurodegenerative disorders (ND). It is important that depression-related symptoms be adequately screened and monitored in persons living with ND. The Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) is a widely-used self-report measure to assess and monitor depressive severity across different patient populations. However, the measurement properties of the QIDS-SR have not been assessed in ND.</sec>AimTo use Rasch Measurement Theory to assess the measurement properties of the Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) in ND and in comparison to major depressive disorder (MDD).</sec>MethodsDe-identified data from the Ontario Neurodegenerative Disease Research Initiative (NCT04104373) and Canadian Biomarker Integration Network in Depression (NCT01655706) were used in the analyses. Five hundred and twenty participants with ND (Alzheimer’s disease or mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia and Parkinson’s disease) and 117 participants with major depressive disorder (MDD) were administered the QIDS-SR. Rasch Measurement Theory was used to assess measurement properties of the QIDS-SR, including unidimensionality and item-level fit, category ordering, item targeting, person separation index and reliability and differential item functioning.</sec>ResultsThe QIDS-SR fit well to the Rasch model in ND and MDD, including unidimensionality, satisfactory category ordering and goodness-of-fit. Item-person measures (Wright maps) showed gaps in item difficulties, suggesting poor precision for persons falling between those severity levels. Differences between mean person and item measures in the ND cohort logits suggest that QIDS-SR items target more severe depression than experienced by the ND cohort. Some items showed differential item functioning between cohorts.</sec>ConclusionThe present study supports the use of the QIDS-SR in MDD and suggest that the QIDS-SR can be also used to screen for depressive symptoms in persons with ND. However, gaps in item targeting were noted that suggests that the QIDS-SR cannot differentiate participants falling within certain severity levels. Future studies would benefit from examination in a more severely depressed ND cohort, including those with diagnosed clinical depression.</sec>

Background: Symptoms of depression are present in neurodegenerative disorders (ND). It is important that depression-related symptoms be adequately screened and monitored in persons living with ND. The Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) is a widely-used self-report measure to assess and monitor depressive severity across different patient populations. However, the measurement properties of the QIDS-SR have not been assessed in ND.Aim: To use Rasch Measurement Theory to assess the measurement properties of the Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) in ND and in comparison to major depressive disorder (MDD).Methods: De-identified data from the Ontario Neurodegenerative Disease Research Initiative (NCT04104373) and Canadian Biomarker Integration Network in Depression (NCT01655706) were used in the analyses. Five hundred and twenty participants with ND (Alzheimer’s disease or mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia and Parkinson’s disease) and 117 participants with major depressive disorder (MDD) were administered the QIDS-SR. Rasch Measurement Theory was used to assess measurement properties of the QIDS-SR, including unidimensionality and item-level fit, category ordering, item targeting, person separation index and reliability and differential item functioning.Results: The QIDS-SR fit well to the Rasch model in ND and MDD, including unidimensionality, satisfactory category ordering and goodness-of-fit. Item-person measures (Wright maps) showed gaps in item difficulties, suggesting poor precision for persons falling between those severity levels. Differences between mean person and item measures in the ND cohort logits suggest that QIDS-SR items target more severe depression than experienced by the ND cohort. Some items showed differential item functioning between cohorts.Conclusion: The present study supports the use of the QIDS-SR in MDD and suggest that the QIDS-SR can be also used to screen for depressive symptoms in persons with ND. However, gaps in item targeting were noted that suggests that the QIDS-SR cannot differentiate participants falling within certain severity levels. Future studies would benefit from examination in a more severely depressed ND cohort, including those with diagnosed clinical depression.