Can you tell people's cognitive ability level from their response patterns in questionnaires?

Questionnaires are ever present in survey research. In this study, we examined whether an indirect indicator of general cognitive ability could be developed based on response patterns in questionnaires. We drew on two established phenomena characterizing connections between cognitive ability and people's performance on basic cognitive tasks, and examined whether they apply to questionnaires responses. (1) The worst performance rule (WPR) states that people's worst performance on multiple sequential tasks is more indicative of their cognitive ability than their average or best performance. (2) The task complexity hypothesis (TCH) suggests that relationships between cognitive ability and performance increase with task complexity. We conceptualized items of a questionnaire as a series of cognitively demanding tasks. A graded response model was used to estimate respondents' performance for each item based on the difference between the observed and model-predicted response ("response error" scores). Analyzing data from 102 items (21 questionnaires) collected from a large-scale nationally representative sample of people aged 50+ years, we found robust associations of cognitive ability with a person's largest but not with their smallest response error scores (supporting the WPR), and stronger associations of cognitive ability with response errors for more complex than for less complex questions (supporting the TCH). Results replicated across two independent samples and six assessment waves. A latent variable of response errors estimated for the most complex items correlated .50 with a latent cognitive ability factor, suggesting that response patterns can be utilized to extract a rough indicator of general cognitive ability in survey research.

Cost-Effectiveness of a Technology-Facilitated Depression Care Management Adoption Model in Safety-Net Primary Care Patients with Type 2 Diabetes.

BACKGROUND: The Diabetes-Depression Care-Management Adoption Trial is a translational study of safety-net primary care predominantly Hispanic/Latino patients with type 2 diabetes in collaboration with the Los Angeles County Department of Health Services. OBJECTIVES: To evaluate the cost-effectiveness of an information and communication technology (ICT)-facilitated depression care management program. METHODS: Cost-effectiveness of the ICT-facilitated care (TC) delivery model was evaluated relative to a usual care (UC) and a supported care (SC) model. TC added automated low-intensity periodic depression assessment calls to patients. Patient-reported outcomes included the 12-Item Short Form Health Survey converted into quality-adjusted life-years (QALYs) and the 9-Item Patient Health Questionnaire-calculated depression-free days (DFDs). Costs and outcomes data were collected over a 24-month period (-6 to 0 months baseline, 0 to 18 months study intervention). RESULTS: A sample of 1406 patients (484 in UC, 480 in SC, and 442 in TC) was enrolled in the nonrandomized trial. TC had a significant improvement in DFDs (17.3; P = 0.011) and significantly greater 12-Item Short Form Health Survey utility improvement (2.1%; P = 0.031) compared with UC. Medical costs were statistically significantly lower for TC (-$2328; P = 0.001) relative to UC but not significantly lower than for SC. TC had more than a 50% probability of being cost-effective relative to SC at willingness-to-pay thresholds of more than $50,000/QALY. CONCLUSIONS: An ICT-facilitated depression care (TC) delivery model improved QALYs, DFDs, and medical costs. It was cost-effective compared with SC and dominant compared with UC.

Comparative Effectiveness of a Technology-Facilitated Depression Care Management Model in Safety-Net Primary Care Patients With Type 2 Diabetes: 6-Month Outcomes of a Large Clinical Trial.

BACKGROUND: Comorbid depression is a significant challenge for safety-net primary care systems. Team-based collaborative depression care is effective, but complex system factors in safety-net organizations impede adoption and result in persistent disparities in outcomes. Diabetes-Depression Care-management Adoption Trial (DCAT) evaluated whether depression care could be significantly improved by harnessing information and communication technologies to automate routine screening and monitoring of patient symptoms and treatment adherence and allow timely communication with providers. OBJECTIVE: The aim of this study was to compare 6-month outcomes of a technology-facilitated care model with a usual care model and a supported care model that involved team-based collaborative depression care for safety-net primary care adult patients with type 2 diabetes. METHODS: DCAT is a translational study in collaboration with Los Angeles County Department of Health Services, the second largest safety-net care system in the United States. A comparative effectiveness study with quasi-experimental design was conducted in three groups of adult patients with type 2 diabetes to compare three delivery models: usual care, supported care, and technology-facilitated care. Six-month outcomes included depression and diabetes care measures and patient-reported outcomes. Comparative treatment effects were estimated by linear or logistic regression models that used generalized propensity scores to adjust for sampling bias inherent in the nonrandomized design. RESULTS: DCAT enrolled 1406 patients (484 in usual care, 480 in supported care, and 442 in technology-facilitated care), most of whom were Hispanic or Latino and female. Compared with usual care, both the supported care and technology-facilitated care groups were associated with significant reduction in depressive symptoms measured by scores on the 9-item Patient Health Questionnaire (least squares estimate, LSE: usual care=6.35, supported care=5.05, technology-facilitated care=5.16; P value: supported care vs usual care=.02, technology-facilitated care vs usual care=.02); decreased prevalence of major depression (odds ratio, OR: supported care vs usual care=0.45, technology-facilitated care vs usual care=0.33; P value: supported care vs usual care=.02, technology-facilitated care vs usual care=.007); and reduced functional disability as measured by Sheehan Disability Scale scores (LSE: usual care=3.21, supported care=2.61, technology-facilitated care=2.59; P value: supported care vs usual care=.04, technology-facilitated care vs usual care=.03). Technology-facilitated care was significantly associated with depression remission (technology-facilitated care vs usual care: OR=2.98, P=.04); increased satisfaction with care for emotional problems among depressed patients (LSE: usual care=3.20, technology-facilitated care=3.70; P=.05); reduced total cholesterol level (LSE: usual care=176.40, technology-facilitated care=160.46; P=.01); improved satisfaction with diabetes care (LSE: usual care=4.01, technology-facilitated care=4.20; P=.05); and increased odds of taking an glycated hemoglobin test (technology-facilitated care vs usual care: OR=3.40, P<.001). CONCLUSIONS: Both the technology-facilitated care and supported care delivery models showed potential to improve 6-month depression and functional disability outcomes. The technology-facilitated care model has a greater likelihood to improve depression remission, patient satisfaction, and diabetes care quality.

Collaborative health literate depression care among predominantly Hispanic patients with coronary heart disease in safety net care.

OBJECTIVE: To determine whether evidence-based socioculturally health literate-adapted collaborative depression care improves depression care, depressive symptoms, and quality of life among predominantly Hispanic patients with coronary heart disease. METHODS: The 12-month trial included 97 patients with coronary heart disease (79% of eligible patients) who met the depression criteria assessed by the Patient Health Questionnaire-9. Patients were recruited from 3 safety net clinics and offered depression team care by a bilingual clinical social worker and community patient navigator, a consulting psychiatrist, and a primary care physician. The team provided problem-solving therapy (PST) or pharmacotherapy or both, telephone symptom monitoring and behavioral activation, and patient resource navigation support. Recruited patients were given patient and family member health literacy-adapted educational and community resource materials in Spanish or English. RESULTS: Overall, depression treatment was 74% (PST, 55%; PST plus antidepressant medications, 18%; and antidepressant medications alone, 2%). Nearly half of the patients showed a 50% reduction of the Symptom Checklist-20 (49% at 6 mo and 48% at 12 mo) and of Patient Health Questionnaire-9 score with 47% of patients at 6 months and 43% at 12 months. The 50% improvement in Patient Health Questionnaire and Symptom Checklist-20 score reduction did not vary significantly between patients who received PST or antidepressant only or those who received PST plus antidepressant. The quality of life Short-Form Health Survey SF-12, the Minnesota Living with Heart Failure questionnaire, and the Sheehan Disability Scale outcomes also improved significantly. CONCLUSIONS: Socioculturally literacy-adapted collaborative depression care was accepted by patients with coronary heart disease and improved depression care and symptoms, quality of life, and functional outcomes among predominantly Hispanic patients with heart disease.

Collaborative depression care among Latino patients in diabetes disease management, Los Angeles, 2011-2013.

INTRODUCTION: The prevalence of comorbid diabetes and depression is high, especially in low-income Hispanic or Latino patients. The complex mix of factors in safety-net care systems impedes the adoption of evidence-based collaborative depression care and results in persistent disparities in depression outcomes. The Diabetes-Depression Care-Management Adoption Trial examined whether the collaborative depression care model is an effective approach in safety-net clinics to improve clinical care outcomes of depression and diabetes. METHODS: A sample of 964 patients with diabetes from 5 safety-net clinics were enrolled in a quasi-experimental study that included 2 arms: usual care, in which primary medical providers and staff translated and adopted evidence-based depression care; and supportive care, in which providers of a disease management program delivered protocol-driven depression care. Because the study design established individual treatment centers as separate arms, we calculated propensity scores that interpreted the probability of treatment assignment conditional on observed baseline characteristics. Primary outcomes were 5 depression care outcomes and 7 diabetes care measures. Regression models with propensity score covariate adjustment were applied to analyze 6-month outcomes. RESULTS: Compared with usual care, supportive care significantly decreased Patient Health Questionnaire-9 scores, reduced the number of patients with moderate or severe depression, improved depression remission, increased satisfaction in care for patients with emotional problems, and significantly reduced functional impairment. CONCLUSION: Implementing collaborative depression care in a diabetes disease management program is a scalable approach to improve depression outcomes and patient care satisfaction among patients with diabetes in a safety-net care system.

Cognitive Functioning and the Quality of Survey Responses: An Individual Participant Data Meta-Analysis of 10 Epidemiological Studies of Aging.

OBJECTIVES: Self-reported survey data are essential for monitoring the health and well-being of the population as it ages. For studies of aging to provide precise and unbiased results, it is necessary that the self-reported information meets high psychometric standards. In this study, we examined whether the quality of survey responses in panel studies of aging depends on respondents' cognitive abilities. METHODS: Over 17 million survey responses from 157,844 participants aged 50 years and older in 10 epidemiological studies of aging were analyzed. We derived 6 common statistical indicators of response quality from each participant's data and estimated the correlations with participants' cognitive test scores at each study wave. Effect sizes (correlations) were synthesized across studies, cognitive tests, and waves using individual participant data meta-analysis methods. RESULTS: Respondents with lower cognitive scores showed significantly more missing item responses (overall effect size ρ^ = -0.144), random measurement error (ρ^ = -0.192), Guttman errors (ρ^ = -0.233), multivariate outliers (ρ^ = -0.254), and acquiescent responses (ρ^ = -0.078); the overall effect for extreme responses (ρ^ = -0.045) was not significant. Effect sizes were consistent across studies, modes of survey administsration, and different cognitive functioning domains, although some cognitive domain specificity was also observed. DISCUSSION: Lower-quality responses among respondents with lower cognitive abilities add random and systematic errors to survey measures, reducing the reliability, validity, and reproducibility of survey study results in aging research.

Attrition from longitudinal ageing studies and performance across domains of cognitive functioning: an individual participant data meta-analysis.

OBJECTIVES: This paper examined the magnitude of differences in performance across domains of cognitive functioning between participants who attrited from studies and those who did not, using data from longitudinal ageing studies where multiple cognitive tests were administered. DESIGN: Individual participant data meta-analysis. PARTICIPANTS: Data are from 10 epidemiological longitudinal studies on ageing (total n=209 518) from several Western countries (UK, USA, Mexico, etc). Each study had multiple waves of data (range of 2-17 waves), with multiple cognitive tests administered at each wave (range of 4-17 tests). Only waves with cognitive tests and information on participant dropout at the immediate next wave for adults aged 50 years or older were used in the meta-analysis. MEASURES: For each pair of consecutive study waves, we compared the difference in cognitive scores (Cohen's d) between participants who dropped out at the next study wave and those who remained. Note that our operationalisation of dropout was inclusive of all causes (eg, mortality). The proportion of participant dropout at each wave was also computed. RESULTS: The average proportion of dropouts between consecutive study waves was 0.26 (0.18 to 0.34). People who attrited were found to have significantly lower levels of cognitive functioning in all domains (at the wave 2-3 years before attrition) compared with those who did not attrit, with small-to-medium effect sizes (overall d=0.37 (0.30 to 0.43)). CONCLUSIONS: Older adults who attrited from longitudinal ageing studies had lower cognitive functioning (assessed at the timepoint before attrition) across all domains as compared with individuals who remained. Cognitive functioning differences may contribute to selection bias in longitudinal ageing studies, impeding accurate conclusions in developmental research. In addition, examining the functional capabilities of attriters may be valuable for determining whether attriters experience functional limitations requiring healthcare attention.

Developing Early Markers of Cognitive Decline and Dementia Derived From Survey Response Behaviors: Protocol for Analyses of Preexisting Large-scale Longitudinal Data.

BACKGROUND: Accumulating evidence shows that subtle alterations in daily functioning are among the earliest and strongest signals that predict cognitive decline and dementia. A survey is a small slice of everyday functioning; nevertheless, completing a survey is a complex and cognitively demanding task that requires attention, working memory, executive functioning, and short- and long-term memory. Examining older people's survey response behaviors, which focus on how respondents complete surveys irrespective of the content being sought by the questions, may represent a valuable but often neglected resource that can be leveraged to develop behavior-based early markers of cognitive decline and dementia that are cost-effective, unobtrusive, and scalable for use in large population samples. OBJECTIVE: This paper describes the protocol of a multiyear research project funded by the US National Institute on Aging to develop early markers of cognitive decline and dementia derived from survey response behaviors at older ages. METHODS: Two types of indices summarizing different aspects of older adults' survey response behaviors are created. Indices of subtle reporting mistakes are derived from questionnaire answer patterns in a number of population-based longitudinal aging studies. In parallel, para-data indices are generated from computer use behaviors recorded on the backend server of a large web-based panel study known as the Understanding America Study (UAS). In-depth examinations of the properties of the created questionnaire answer pattern and para-data indices will be conducted for the purpose of evaluating their concurrent validity, sensitivity to change, and predictive validity. We will synthesize the indices using individual participant data meta-analysis and conduct feature selection to identify the optimal combination of indices for predicting cognitive decline and dementia. RESULTS: As of October 2022, we have identified 15 longitudinal ageing studies as eligible data sources for creating questionnaire answer pattern indices and obtained para-data from 15 UAS surveys that were fielded from mid-2014 to 2015. A total of 20 questionnaire answer pattern indices and 20 para-data indices have also been identified. We have conducted a preliminary investigation to test the utility of the questionnaire answer patterns and para-data indices for the prediction of cognitive decline and dementia. These early results are based on only a subset of indices but are suggestive of the findings that we anticipate will emerge from the planned analyses of multiple behavioral indices derived from many diverse studies. CONCLUSIONS: Survey response behaviors are a relatively inexpensive data source, but they are seldom used directly for epidemiological research on cognitive impairment at older ages. This study is anticipated to develop an innovative yet unconventional approach that may complement existing approaches aimed at the early detection of cognitive decline and dementia. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/44627.

Within-person Relationships of Sleep Duration with Next-Day Stress and Affect in the Daily Life of Adults with Type-1 Diabetes.

Objective: The objective of this study is to examine the within-person relationships between sleep duration and next-day stress and affect in the daily life of individuals with T1D. Methods: Study participants were recruited in the Function and Emotion in Everyday Life with Type 1 Diabetes (FEEL-T1D) study. Sleep duration was derived by synthesizing objective (actigraphy) and self-report measures. General and diabetes-specific stress and positive and negative affect were measured using ecological momentary assessment. Multilevel regression was used to examine the within-person relationships between sleep duration and next-day stress and affect. Cross-level interactions were used to explore whether gender and baseline depression and anxiety moderated these within-person relationships. Results: Adults with T1D (n=166) completed measurements for 14 days. The average age was 40.99 years, and 91 participants (54.82%) were female. The average sleep duration was 7.29 hours (SD=1.18 hours). Longer sleep was significantly associated with lower general stress (p<0.001) but not diabetes-specific stress (p=0.18) on the next day. There were significant within-person associations of longer sleep with lower levels on next-day negative affect (overall, p=0.002, disappoint, p=0.05; sad, p=0.05; tense, p<0.001; upset, p=0.008; anxious, p=0.04). There were no significant associations with positive affect. Examination of the interaction effects did not reveal significant differential relationships for men and women and for individuals with and without depression or anxiety at baseline. Conclusion: Findings from this study suggest optimizing sleep duration as an important interventional target for better managing general stress and improving daily emotional wellbeing of individuals with T1D.

Using Item Response Times in Online Questionnaires to Detect Mild Cognitive Impairment.

OBJECTIVES: With the increase in web-based data collection, response times (RTs) for survey items have become a readily available byproduct in most online studies. We examined whether RTs in online questionnaires can prospectively discriminate between cognitively normal respondents and those with cognitive impairment, no dementia (CIND). METHOD: Participants were 943 members of a nationally representative internet panel, aged 50 and older. We analyzed RTs that were passively recorded as paradata for 37 surveys (1,053 items) administered online over 6.5 years. A multilevel location-scale model derived 3 RT parameters for each survey: (1) a respondent's average RT and 2 components of intraindividual RT variability addressing (2) systematic RT adjustments and (3) unsystematic RT fluctuations. CIND status was determined at the end of the 6.5-year period. RESULTS: All 3 RT parameters were significantly associated with CIND, with a combined predictive accuracy of area under the receiver-operating characteristic curve = 0.74. Slower average RTs, smaller systematic RT adjustments, and greater unsystematic RT fluctuations prospectively predicted a greater likelihood of CIND over periods of up to 6.5, 4.5, and 1.5 years, respectively. DISCUSSION: RTs for survey items are a potential early indicator of CIND, which may enhance analyses of predictors, correlates, and consequences of cognitive impairment in online survey research.

Within-person relationships of sleep duration with next-day stress and affect in the daily life of adults with Type-1 diabetes.

OBJECTIVE: The objective of this study is to examine the within-person relationships between sleep duration and next-day stress and affect in the daily life of individuals with T1D. METHODS: Study participants were recruited in the Function and Emotion in Everyday Life with Type 1 Diabetes (FEEL-T1D) study. Sleep duration was derived by synthesizing objective (actigraphy) and self-report measures. General and diabetes-specific stress and positive and negative affect were measured using ecological momentary assessment. Multilevel regression was used to examine the within-person relationships between sleep duration and next-day stress and affect. Cross-level interactions were used to explore whether gender and baseline depression and anxiety moderated these within-person relationships. RESULTS: Adults with T1D (n = 166) completed measurements for 14 days. The average age was 41.0 years, and 91 participants (54.8%) were female. The average sleep duration was 7.3 h (SD = 1.2 h). Longer sleep was significantly associated with lower general stress (p < 0.001) but not diabetes-specific stress (p = 0.18) on the next day. There were significant within-person associations of longer sleep with lower levels on next-day negative affect (overall, p = 0.002, disappoint, p = 0.05; sad, p = 0.05; tense, p < 0.001; upset, p = 0.008; anxious, p = 0.04). There were no significant associations with positive affect. Examination of the interaction effects did not reveal significant differential relationships for men and women and for individuals with and without depression or anxiety at baseline. CONCLUSION: Findings from this study suggest optimizing sleep duration as an important interventional target for better managing general stress and improving daily emotional wellbeing of individuals with T1D.

Reliability and Validity of Noncognitive Ecological Momentary Assessment Survey Response Times as an Indicator of Cognitive Processing Speed in People's Natural Environment: Intensive Longitudinal Study.

BACKGROUND: Various populations with chronic conditions are at risk for decreased cognitive performance, making assessment of their cognition important. Formal mobile cognitive assessments measure cognitive performance with greater ecological validity than traditional laboratory-based testing but add to participant task demands. Given that responding to a survey is considered a cognitively demanding task itself, information that is passively collected as a by-product of ecological momentary assessment (EMA) may be a means through which people's cognitive performance in their natural environment can be estimated when formal ambulatory cognitive assessment is not feasible. We specifically examined whether the item response times (RTs) to EMA questions (eg, mood) can serve as approximations of cognitive processing speed. OBJECTIVE: This study aims to investigate whether the RTs from noncognitive EMA surveys can serve as approximate indicators of between-person (BP) differences and momentary within-person (WP) variability in cognitive processing speed. METHODS: Data from a 2-week EMA study investigating the relationships among glucose, emotion, and functioning in adults with type 1 diabetes were analyzed. Validated mobile cognitive tests assessing processing speed (Symbol Search task) and sustained attention (Go-No Go task) were administered together with noncognitive EMA surveys 5 to 6 times per day via smartphones. Multilevel modeling was used to examine the reliability of EMA RTs, their convergent validity with the Symbol Search task, and their divergent validity with the Go-No Go task. Other tests of the validity of EMA RTs included the examination of their associations with age, depression, fatigue, and the time of day. RESULTS: Overall, in BP analyses, evidence was found supporting the reliability and convergent validity of EMA question RTs from even a single repeatedly administered EMA item as a measure of average processing speed. BP correlations between the Symbol Search task and EMA RTs ranged from 0.43 to 0.58 (P<.001). EMA RTs had significant BP associations with age (P<.001), as expected, but not with depression (P=.20) or average fatigue (P=.18). In WP analyses, the RTs to 16 slider items and all 22 EMA items (including the 16 slider items) had acceptable (>0.70) WP reliability. After correcting for unreliability in multilevel models, EMA RTs from most combinations of items showed moderate WP correlations with the Symbol Search task (ranged from 0.29 to 0.58; P<.001) and demonstrated theoretically expected relationships with momentary fatigue and the time of day. The associations between EMA RTs and the Symbol Search task were greater than those between EMA RTs and the Go-No Go task at both the BP and WP levels, providing evidence of divergent validity. CONCLUSIONS: Assessing the RTs to EMA items (eg, mood) may be a method of approximating people's average levels of and momentary fluctuations in processing speed without adding tasks beyond the survey questions.

Impact of Overnight Glucose on Next-Day Functioning in Adults With Type 1 Diabetes: An Exploratory Intensive Longitudinal Study.

OBJECTIVE: While there is evidence that functioning, or ability to perform daily life activities, can be adversely influenced by type 1 diabetes, the impact of acute fluctuations in glucose levels on functioning is poorly understood. RESEARCH DESIGN AND METHODS: Using dynamic structural equation modeling, we examined whether overnight glucose (coefficient of variation[CV], percent time <70 mg/dL, percent time >250 mg/dL) predicted seven next-day functioning outcomes (mobile cognitive tasks, accelerometry-derived physical activity, self-reported activity participation) in adults with type 1 diabetes. We examined mediation, moderation, and whether short-term relationships were predictive of global patient-reported outcomes. RESULTS: Overall next-day functioning was significantly predicted from overnight CV (P = 0.017) and percent time >250 mg/dL (P = 0.037). Pairwise tests indicate that higher CV is associated with poorer sustained attention (P = 0.028) and lower engagement in demanding activities (P = 0.028), time <70 mg/dL is associated with poorer sustained attention (P = 0.007), and time >250 mg/dL is associated with more sedentary time (P = 0.024). The impact of CV on sustained attention is partially mediated by sleep fragmentation. Individual differences in the effect of overnight time <70 mg/dL on sustained attention predict global illness intrusiveness (P = 0.016) and diabetes-related quality of life (P = 0.036). CONCLUSIONS: Overnight glucose predicts problems with objective and self-reported next-day functioning and can adversely impact global patient-reported outcomes. These findings across diverse outcomes highlight the wide-ranging effects of glucose fluctuations on functioning in adults with type 1 diabetes.

Research design and baseline participant characteristics of the Resilient, Empowered, Active Living with Diabetes - Telehealth (REAL-T) Study: A randomized controlled trial for young adults with type 1 diabetes.

BACKGROUND: Type 1 diabetes (T1D) is a chronic condition affecting nearly 1.9 million people in the United States. Young adults (YAs) with T1D face unique challenges in managing their condition, experiencing poorer health and well-being than other age groups. The current study is evaluating the Resilient, Empowered, Active Living (REAL) intervention, previously shown to improve glucose levels and quality of life among YAs with diabetes, using telehealth delivery (REAL-T) to expand reach and accessibility. This paper reports on the methodology and baseline participant characteristics of the REAL-T study. METHODS: REAL-T is a two-arm randomized controlled trial that recruited 18-30 year olds with T1D via clinics and social media advertising. Data collection, which was adapted to be fully remote due to COVID-19, occurs every three months for one year. Participants receive either usual care or a 6-month telehealth occupational therapy intervention. The primary outcome is glycated hemoglobin (A1c); secondary outcomes include diabetes distress, quality of life, and continuous glucose monitor-derived measures. RESULTS: The study enrolled a diverse sample of 209 YAs with T1D. Analysis of baseline data indicates equivalence between the intervention and control groups. Study participants have notably higher diabetes distress and poorer mental well-being than similar populations. CONCLUSION: The REAL-T study successfully adapted to remote implementation during the COVID-19 pandemic. By examining long-term outcomes, mediating pathways, and cost-effectiveness, the study will contribute knowledge of the impact of tailored interventions for YAs with T1D, designed to reduce disparities and improve health and well-being in this population.

Cost-effectiveness analysis of collaborative care management of major depression among low-income, predominantly Hispanics with diabetes.

OBJECTIVE: To evaluate the cost-effectiveness of a socioculturally adapted collaborative depression care program among low-income Hispanics with diabetes. RESEARCH DESIGN AND METHODS: A randomized controlled trial of 387 patients with diabetes (96.5% Hispanic) with clinically significant depression followed over 18 months evaluated the cost-effectiveness of the Multifaceted Diabetes and Depression Program aimed at increasing patient exposure to evidence-based depression psychotherapy and/or pharmacotherapy in two public safety net clinics. Patient medical care costs and utilization were captured from Los Angeles County Department of Health Services claims records. Patient-reported outcomes included Short-Form Health Survey-12 and Patient Health Questionnaire-9-calculated depression-free days. RESULTS: Intervention patients had significantly greater Short-Form Health Survey-12 utility improvement from baseline compared with controls over the 18-month evaluation period (4.8%; P < 0.001) and a corresponding significant improvement in depression-free days (43.0; P < 0.001). Medical cost differences were not statistically significant in ordinary least squares and log-transformed cost regressions. The average costs of the Multifaceted Diabetes and Depression Program study intervention were $515 per patient. The program's cost-effectiveness averaged $4053 per quality-adjusted life-year per MDDP recipient and was more than 90% likely to fall below $12,000 per quality-adjusted life-year. CONCLUSIONS: Socioculturally adapted collaborative depression care improved utility and quality of life in predominantly low-income Hispanic patients with diabetes and was highly cost-effective.

Depressive symptom deterioration among predominantly Hispanic diabetes patients in safety net care.

OBJECTIVE: This study examines clinical predictors of symptom deterioration (relapse/recurrence) at the completion of a clinical intervention trial of depressed, low-income, predominantly Hispanic diabetes patients who were randomized to socio-culturally adapted collaborative depression treatment or usual care and who no longer met clinically significant depression criteria at 12 months post-trial baseline. METHODS: A sub-cohort of 193 diabetes patients with major depression symptoms at baseline, who were randomized to a 12-month collaborative care intervention (INT) (problem-solving therapy and/or pharmacotherapy, telephone symptom monitoring/relapse prevention, behavioral activation and patient navigation support) or enhanced usual care (EUC), and who did not meet major depression criteria at 12 months were subsequently observed over 18 to 24 months. RESULTS: Post-trial depression symptom deterioration was similar between INT (35.2%) and EUC (35.3%) groups. Among the combined groups, significant predictors of symptom deterioration were baseline history of previous depression and/or dysthymia (odds ratio [OR] = 2.66), 12-month PHQ-9 score (OR = 1.22), antidepressant treatment receipt during the initial 12-months (OR = 2.38), 12-month diabetes symptoms (OR = 2.27), and new ICD-9 medical diagnoses in the initial 12 months (OR = 1.11) (R2 = 27%; max-rescaled R2 = 37%; likelihood ratio test, χ2 = 59.79, df = 5, P < 0.0001). CONCLUSIONS: Among predominantly Hispanic diabetes patients in community safety net primary care clinics whose depression had improved over 1 year, more than one-third experienced symptom deterioration over the following year. A primary care management depression care protocol that includes ongoing depression symptom monitoring, antidepressant adherence, and diabetes and co-morbid illness monitoring plus depression medication adjustment and behavioral activation may reduce and/or effectively treat depression symptom deterioration.

Quality of Survey Responses at Older Ages Predicts Cognitive Decline and Mortality Risk.

Background and Objectives: It is widely recognized that survey satisficing, inattentive, or careless responding in questionnaires reduce the quality of self-report data. In this study, we propose that such low-quality responding (LQR) can carry substantive meaning at older ages. Completing questionnaires is a cognitively demanding task and LQR among older adults may reflect early signals of cognitive deficits and pathological aging. We hypothesized that older people displaying greater LQR would show faster cognitive decline and greater mortality risk. Research Design and Methods: We analyzed data from 9, 288 adults 65 years or older in the Health and Retirement Study. Indicators of LQR were derived from participants' response patterns in 102 psychosocial questionnaire items administered in 2006-2008. Latent growth models examined whether LQR predicted initial status and change in cognitive functioning, assessed with the modified Telephone Interview for Cognitive Status, over the subsequent 10 years. Discrete-time survival models examined whether LQR was associated with mortality risk over the 10 years. We also examined evidence for indirect (mediated) effects in which LQR predicts mortality via cognitive trajectories. Results: After adjusting for age, gender, race, marital status, education, health conditions, smoking status, physical activity, and depressive symptoms, greater LQR was cross-sectionally associated with poorer cognitive functioning, and prospectively associated with faster cognitive decline over the follow-up period. Furthermore, greater LQR was associated with increased mortality risk during follow-up, and this effect was partially accounted for by the associations between LQR and cognitive functioning. Discussion and Implications: Self-report questionnaires are not formally designed as cognitive tasks, but this study shows that LQR indicators derived from self-report measures provide objective, performance-based information about individuals' cognitive functioning and survival. Self-report surveys are ubiquitous in social science, and indicators of LQR may be of broad relevance as predictors of cognitive and health trajectories in older people.

Inferring Cognitive Abilities from Response Times to Web-Administered Survey Items in a Population-Representative Sample.

Monitoring of cognitive abilities in large-scale survey research is receiving increasing attention. Conventional cognitive testing, however, is often impractical on a population level highlighting the need for alternative means of cognitive assessment. We evaluated whether response times (RTs) to online survey items could be useful to infer cognitive abilities. We analyzed >5 million survey item RTs from >6000 individuals administered over 6.5 years in an internet panel together with cognitive tests (numerical reasoning, verbal reasoning, task switching/inhibitory control). We derived measures of mean RT and intraindividual RT variability from a multilevel location-scale model as well as an expanded version that separated intraindividual RT variability into systematic RT adjustments (variation of RTs with item time intensities) and residual intraindividual RT variability (residual error in RTs). RT measures from the location-scale model showed weak associations with cognitive test scores. However, RT measures from the expanded model explained 22−26% of the variance in cognitive scores and had prospective associations with cognitive assessments over lag-periods of at least 6.5 years (mean RTs), 4.5 years (systematic RT adjustments) and 1 year (residual RT variability). Our findings suggest that RTs in online surveys may be useful for gaining information about cognitive abilities in large-scale survey research.

Function and Emotion in Everyday Life With Type 1 Diabetes (FEEL-T1D): Protocol for a Fully Remote Intensive Longitudinal Study.

BACKGROUND: Although short-term blood glucose levels and variability are thought to underlie diminished function and emotional well-being in people with type 1 diabetes (T1D), these relationships are poorly understood. The Function and Emotion in Everyday Life with T1D (FEEL-T1D) study focuses on investigating these short-term dynamic relationships among blood glucose levels, functional ability, and emotional well-being in adults with T1D. OBJECTIVE: The aim of this study is to present the FEEL-T1D study design, methods, and study progress to date, including adaptations necessitated by the COVID-19 pandemic to implement the study fully remotely. METHODS: The FEEL-T1D study will recruit 200 adults with T1D in the age range of 18-75 years. Data collection includes a comprehensive survey battery, along with 14 days of intensive longitudinal data using blinded continuous glucose monitoring, ecological momentary assessments, ambulatory cognitive tasks, and accelerometers. All study procedures are conducted remotely by mailing the study equipment and by using videoconferencing for study visits. RESULTS: The study received institutional review board approval in January 2019 and was funded in April 2019. Data collection began in June 2020 and is projected to end in December 2021. As of June 2021, after 12 months of recruitment, 124 participants have enrolled in the FEEL-T1D study. Approximately 87.6% (7082/8087) of ecological momentary assessment surveys have been completed with minimal missing data, and 82.0% (82/100) of the participants provided concurrent continuous glucose monitoring data, ecological momentary assessment data, and accelerometer data for at least 10 of the 14 days of data collection. CONCLUSIONS: Thus far, our reconfiguration of the FEEL-T1D protocol to be implemented remotely during the COVID-19 pandemic has been a success. The FEEL-T1D study will elucidate the dynamic relationships among blood glucose levels, emotional well-being, cognitive function, and participation in daily activities. In doing so, it will pave the way for innovative just-in-time interventions and produce actionable insights to facilitate tailoring of diabetes treatments to optimize the function and well-being of individuals with T1D. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30901.

Collaborative depression treatment in older and younger adults with physical illness: pooled comparative analysis of three randomized clinical trials.

OBJECTIVE: There have been few comparisons of the effectiveness of collaborative depression care between older versus younger adults with comorbid illness, particularly among low-income populations. DESIGN: Intent-to-treat analyses are conducted on pooled data from three randomized controlled trials that tested collaborative care aimed at improving depression, quality of life, and treatment receipt. SETTINGS: Trials were conducted in oncology and primary care safety net clinics and diverse home healthcare programs. PARTICIPANTS: Thousand eighty-one patients with major depressive symptoms and cancer, diabetes, or other comorbid illness. INTERVENTION: Similar intervention protocols included patient, provider, sociocultural, and organizational adaptations. MEASUREMENTS: The Patient Health Questionnaire (PHQ)-9 depression, Short-Form Health Survey-12/20 quality of life, self-reported hospitalization, ER, intensive care unit utilization, and antidepressant, psychotherapy treatment receipt are assessed at baseline, 6, and 12 months. RESULTS: There are no significant differences in reducing depression symptoms (p ranged 0.18-0.58), improving quality of life (t = 1.86, df = 669, p = 0.07 for physical functioning at 12 months, and p ranged 0.23-0.99 for all others) patients aged between >/=60 years versus 18-59 years. Both age group intervention patients have significantly higher rates of a 50% PHQ-9 reduction (older: Wald chi[df = 1] = 4.82, p = 0.03; younger: Wald chi[df = 1] = 6.47, p = 0.02), greater reduction in major depression rates (older: Wald chi[df = 1] = 7.72, p = 0.01; younger: Wald chi[df = 1] = 4.0, p = 0.05) than enhanced-usual-care patients at 6 months and no significant age group differences in treatment type or intensity. CONCLUSION: Collaborative depression care in individuals with comorbid illness is as effective in reducing depression in older patients as younger patients, including among low-income, minority patients. Patient, provider, and organizational adaptations of depression care management models may contribute to positive outcomes.