Self-reported Survey Questions Research Articles

Predicting Self-Reported Social Risk in Medically Complex Adults Using Electronic Health Data.

Social barriers to health care, such as food insecurity, financial distress, and housing instability, may impede effective clinical management for individuals with chronic illness. Systematic strategies are needed to more efficiently identify at-risk individuals who may benefit from proactive outreach by health care systems for screening and referral to available social resources. To create a predictive model to identify a higher likelihood of food insecurity, financial distress, and/or housing instability among adults with multiple chronic medical conditions. We developed and validated a predictive model in adults with 2 or more chronic conditions who were receiving care within Kaiser Permanente Northern California (KPNC) between January 2017 and February 2020. The model was developed to predict the likelihood of a "yes" response to any of 3 validated self-reported survey questions related to current concerns about food insecurity, financial distress, and/or housing instability. External model validation was conducted in a separate cohort of adult non-Medicaid KPNC members aged 35-85 who completed a survey administered to a random sample of health plan members between April and June 2021 (n = 2820). We examined the performance of multiple model iterations by comparing areas under the receiver operating characteristic curves (AUCs). We also assessed algorithmic bias related to race/ethnicity and calculated model performance at defined risk thresholds for screening implementation. Patients in the primary modeling cohort (n = 11,999) had a mean age of 53.8 (±19.3) years, 64.7% were women, and 63.9% were of non-White race/ethnicity. The final, simplified model with 30 predictors (including utilization, diagnosis, behavior, insurance, neighborhood, and pharmacy-based variables) had an AUC of 0.68. The model remained robust within different race/ethnic strata. Our results demonstrated that a predictive model developed using information gleaned from the medical record and from public census tract data can be used to identify patients who may benefit from proactive social needs assessment. Depending on the prevalence of social needs in the target population, different risk output thresholds could be set to optimize positive predictive value for successful outreach. This predictive model-based strategy provides a pathway for prioritizing more intensive social risk outreach and screening efforts to the patients who may be in greatest need.

Trust in and Use of COVID-19 Information Sources Differs by Health Literacy among College Students.

People's health information-seeking behaviors differ by their health literacy levels. This study assessed the relationship between health literacy and college students' levels of trust in and use of a range of health information sources of COVID-19. We collected data from August to December 2020 among college students (n = 763) through an online survey. We used a health literacy measure containing three self-reported survey questions, developed by the CDC. We assessed the extent to which participants trusted and used any of the sixteen different sources of information about COVID-19. Respondents reported high levels of trusting and using COVID-19 information from the CDC, health care providers, the WHO, state/county/city health departments, and official government websites when compared to other sources. After controlling for demographic characteristics (i.e., gender, age, race, ethnicity, and income), those who reported having lower health literacy were significantly less likely to trust and use COVID-19 information from these health authorities when compared to participants who reported having higher health literacy. Students with lower self-reported health literacy indicated not trusting or using official health authority sources for COVID-19 information. Relying on low-quality information sources could create and reinforce people's misperceptions regarding the virus, leading to low compliance with COVID-19-related public health measures and poor health outcomes.

A practical risk calculator for suicidal behavior among transitioning U.S. Army soldiers: results from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS).

Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions. We revised the original model in a sample of n = 8335 observations from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in one of three Army STARRS 2011-2014 baseline surveys while in service and in one or more subsequent panel surveys (LS1: 2016-2018, LS2: 2018-2019) after leaving service. We trained ensemble machine learning models with constrained numbers of item-level survey predictors in a 70% training sample. The outcome was self-reported post-transition suicide attempts (SA). The models were validated in the 30% test sample. Twelve-month post-transition SA prevalence was 1.0% (s.e. = 0.1). The best constrained model, with only 17 predictors, had a test sample ROC-AUC of 0.85 (s.e. = 0.03). The 10-30% of respondents with the highest predicted risk included 44.9-92.5% of 12-month SAs. An accurate SA risk calculator based on a short self-report survey can target transitioning soldiers shortly before leaving service for intervention to prevent post-transition SA.

Systematic Bias in Self-Reported Social Media Use in the Age of Platform Swinging: Implications for Studying Social Media Use in Relation to Adolescent Health Behavior.

Public health researchers are increasingly interested in the potential relationships between social media (SM) use, well-being, and health behavior among adolescents. However, most research has assessed daily SM time via self-report survey questions, despite a lack of clarity around the accuracy of such reports given the current tendency of youth to access SM on multiple electronic devices and cycle between multiple SM platforms on a daily basis (i.e., platform swinging). The current study investigates the potential for systematic reporting biases to skew findings. Three hundred and twenty incoming college students downloaded software on their computers, tablets, and smartphones to track their active use of Facebook, Twitter, Instagram, and Snapchat over a 2-week surveillance period and then self-reported their average daily minutes on each platform immediately after. Larger proportions of students over-estimated than under-estimated their use, with the largest overestimations found on the most heavily used platforms. Females logged significantly more SM time and were less accurate in reporting than were males and, independently, the likelihood of substantial inaccuracies in reporting total SM time and time on most individual platforms increased with each additional SM platform participants reported using. Findings demonstrate that self-reported estimates of SM time among adolescents in the age of SM platform swinging are prone to substantial error and may lead to biased conclusions about relationships between variables. Alternative measurement approaches are suggested to improve the validity of future research in this area.

Associations between Street-View Perceptions and Housing Prices: Subjective vs. Objective Measures Using Computer Vision and Machine Learning Techniques

This study investigated the extent to which subjectively and objectively measured street-level perceptions complement or conflict with each other in explaining property value. Street-scene perceptions can be subjectively assessed from self-reported survey questions, or objectively quantified from land use data or pixel ratios of physical features extracted from street-view imagery. Prior studies mainly relied on objective indicators to describe perceptions and found that a better street environment is associated with a price premium. While very few studies have addressed the impact of subjectively-assessed perceptions. We hypothesized that human perceptions have a subtle relationship to physical features that cannot be comprehensively captured with objective indicators. Subjective measures could be more effective to describe human perceptions, thus might explain more housing price variations. To test the hypothesis, we both subjectively and objectively measured six pairwise eye-level perceptions (i.e., Greenness, Walkability, Safety, Imageability, Enclosure, and Complexity). We then investigated their coherence and divergence for each perception respectively. Moreover, we revealed their similar or opposite effects in explaining house prices in Shanghai using the hedonic price model (HPM). Our intention was not to make causal statements. Instead, we set to address the coherent and conflicting effects of the two measures in explaining people’s behaviors and preferences. Our method is high-throughput by extending classical urban design measurement protocols with current artificial intelligence (AI) frameworks for urban-scene understanding. First, we found the percentage increases in housing prices attributable to street-view perceptions were significant for both subjective and objective measures. While subjective scores explained more variance over objective scores. Second, the two measures exhibited opposite signs in explaining house prices for Greenness and Imageability perceptions. Our results indicated that objective measures which simply extract or recombine individual streetscape pixels cannot fully capture human perceptions. For perceptual qualities that were not familiar to the average person (e.g., Imageability), a subjective framework exhibits better performance. Conversely, for perceptions whose connotation are self-evident (e.g., Greenness), objective measures could outperform the subjective counterparts. This study demonstrates a more holistic understanding for street-scene perceptions and their relations to property values. It also sheds light on future studies where the coherence and divergence of the two measures could be further stressed.

Using externally collected vignettes to account for reporting heterogeneity in survey self-assessment

The anchoring vignette approach has grown in popularity as a method to adjust for reporting heterogeneity in self-reported survey questions, removing bias due to systematic variation in reporting styles across study respondents. The use of anchoring vignettes, however, has been limited to surveys where both self-reports and vignette questions have been included. This diminishes their wider application. We illustrate, using an application to self-reported health in a large household survey, how externally collected vignettes can be used to adjust for reporting heterogeneity in datasets that have not included anchoring vignettes. Given that self-reported measures are an important facet of social, health and economic research, we anticipate the approach described will lead to new applications of the anchoring vignette methodology.

Racial discrimination, John Henryism coping, and behavioral health conditions among predominantly poor, urban African Americans: Implications for community‐level opioid problems and mental health services

The current study examined the relationship between John Henryism Active Coping (JHAC), experiences of racial discrimination, and behavioral health outcomes in a community sample of 319 Black adults. Assessments included primary health care screenings as well as self-reported survey questions to assess JHAC, experiences of discrimination, and self-reported behavioral health. Logistic regression models, adjusted for control variables, found a significant relationship between JHAC and having an opioid problem (odds ratio [OR] = 0.95, p = 0.003) and needing mental health services (OR = 0.95, p < 0.001), such that higher levels of coping were associated with lower odds of reporting an opioid problem and needing mental health services. Notably, racial discrimination was not significantly independently associated with behavioral health. Implications for interventions and community programming are discussed.

Sleep Mediates the Relationship Between Depression and Cognitive Impairment in Older Men.

Sleep and depression are strongly associated with cognitive impairment. The role of sleep disturbances in the adverse effect of depression on cognitive dysfunction in older adults remains unclear. This study explored the mediating effect of self-reported sleep disturbances on the relationship between depression and cognitive impairment in older adults according to sex differences. This study derived data from the 2009 Taiwan National Health Interview Survey and included 2,175 community-dwelling adults aged 65 years and older (men = 991; women = 1,184). Sleep disturbances were measured using self-reported survey questions. The Center for Epidemiological Studies Depression scale was used to assess depression. The Mini-Mental State Examination was used to evaluate cognitive impairment. A higher proportion of female older persons had cognitive impairment and depression than male older persons (cognition: 24.4% vs. 11.5%; depression: 17.0% vs. 10.8%). The meditating effect of sleep was detected in only men. Difficulty in initiating sleep was a complete mediator of the adverse effect of depression on cognitive impairment (Sobel test: p = .03). In summary, difficultly in initiating sleep may be a crucial, treatable mediator of the adverse effect of depression on cognitive impairment in older men.

Development and use of an index for measuring implementation of a weight management program in children in primary care clinics in Texas

BackgroundThe Texas Childhood Obesity Research Demonstration study was an integrated, systems-oriented intervention that incorporated primary and secondary obesity prevention approaches targeting multiple sectors, including primary care clinics, to address childhood obesity. The primary care clinic component included the American Academy of Pediatrics’ Next Steps weight management counseling materials that support brief healthy lifestyle-focused visits. The current study describes the methodology and assesses the implementation of the Next Steps program in the participating primary care clinics, as well as the association of implementation with enrollment of children with overweight and obesity in the secondary prevention intervention.MethodsThe study used a serial cross-sectional study design to collect data from 11 primary care clinics in Houston (n = 5) and Austin (n = 6), Texas, in 2013–2014. Responses of primary care providers on 42 self-reported survey questions assessing acceptability, adoption, appropriateness, and feasibility of the program were utilized to create a mean standardized clinic implementation index score. Provider scores were aggregated to represent Next Steps implementation scores at the clinic level. A mixed effects logistic regression test was conducted to determine the association between program implementation and the enrollment of children in the secondary prevention.ResultsMean implementation index score was lower at Year 2 of implementation (2014) than Year 1 (2013) although the decrease was not significant [63.2% (12.2%) in 2013 vs. 55.3% (16.5%) in 2014]. There were no significant associations between levels of implementation of Next Steps and enrollment into TX CORD secondary prevention study.ConclusionsThe development of an index using process evaluation measures can be used to assess the implementation and evaluation of provider-based obesity prevention tools in primary care clinics.

Prevalence of physical activity and sedentary-related behaviors among adolescents: data from the Qatar National School Survey

ObjectivesTo investigate the prevalence of physical activity (PA) and sedentary behaviors among adolescents in Qatar by selected demographic characteristics. Study designCross-sectional study. MethodsA total of 5862 students (2938 boys and 2924 girls) in the age group 12–17 years were included in the analyses. PA and sedentary-related measures were obtained from the self-reported survey questions. ResultsOnly 35.4% of students were performing 60 min of PA ≥3 days/week. The proportion of students with >2 hr screentime ranged from 43% to 57% (weekdays) and 50% to 62.5% (weekends). Girls had less odds of being physically active than the boys (odds ratio [OR] = 0.61, P < 0.001). Qatari students were less likely to be physically active than non-Qataris (OR = 0.79, P < 0.001). Age was inversely correlated with PA ([r = −0.113, P < 0.001 for participation with sports team] and [r = −0.139, P < 0.001 for school physical education classes]). Participation in sports teams positively correlated with 60 min of PA number of days in a week (r = 0.317, P < 0.001). ConclusionsThe study describes insufficient PA among youth as a public health issue of concern in the State of Qatar that requires multipronged health promotion initiatives.

Informal Leadership Status and Individual Performance

Informal leadership has been a topic of growing interest in recent years, with the recognition that much remains to be known about this phenomenon. In the present study, an integrative social–political conceptualization of informal leadership is proposed and tested. The research question was tested through individual self-report survey questions, a network-based consensus informal leadership measure whereby each employee identified informal leaders in their network, and individual performance provided by the organization. Specifically, the mediated moderation test demonstrated that employees high in political will, as operationalized by power motivation, were more likely to be collectively recognized as informal leaders than those low in political will, and the performance of these informal leaders was found to be contingent on their political skill. By capturing informal leadership using a consensus measure, the results of this study provide a first look at informal leadership in an organizational setting, not team or group. Furthermore, the current research offers a social network—political conceptualization of informal leadership in organizations that contributes to theory, research, and practice.

Parent/Child Concordance about Bullying Involvement and Family Characteristics Related to Bullying and Peer Victimization

ABSTRACT This study examined parent perspectives on bullying, parent/child concordance about bullying involvement, and family characteristics associated with bullying perpetration and peer victimization. Participants were 205 fifth-grade students and their parents. Students attended an urban, ethnically diverse school district in the Northeast. Youth completed self-report measures about bullying involvement, attitudes toward and responses to bullying, and victimization in the home. Parents responded to self-report survey questions about attitudes toward and responses to bullying, perceptions of their child's involvement in bullying, and family characteristics. Bullying perpetration and victimization rates were higher when reported by students than parents, and parents were particularly unaware of their children bullying others. Family support was related to students telling their parents about peer victimization and youth getting in trouble at home for bullying perpetration. Finally, victims' homes were characterized by higher levels of criticism, fewer rules, and more child maltreatment; bullies' homes were characterized by lack of supervision, child maltreatment, and exposure to domestic violence. Findings highlight the need to increase parental awareness about bullying and to include parents in school-based bullying prevention programs.

Making Sense of Sexual Orientation Measures: Findings from a Cognitive Processing Study with Adolescents on Health Survey Questions

To carry out a study using cognitive processing interview methods to explore ways in which adolescents understand sexual orientation questions currently used on epidemiologic surveys. In-depth, individual interviews were conducted to probe cognitive processes involved in answering four self-report survey questions assessing sexual identity, sexual attraction, and sex of sexual partners.A semi-structured interview guide was used to explore variation in question interpretation, information retrieval patterns and problems, item clarity, valence of reactions to items (positive, negative, neutral), respondent burden, and perceived threat associated with the measures. Thirty adolescents aged 15 to 21 of diverse sexual orientations and race/ethnicities participated in the study, including female, male, and transgender youth. A question on sexual attraction was the most consistently understood and thus was easy for nearly all youth to answer. In contrast, a measure of sexual identity with options heterosexual, bisexual, gay/lesbian, and unsure was the most difficult to answer. Most preferred a sexual identity item that also provided the intermediate options mostly heterosexual and mostly homosexual, which many said reflected their experience of feeling between categories. Participants had varying and inconsistent interpretations of sexual behavior terms, such as sex and sexual intercourse, used in assessing the sex of sexual partners. Differences in understanding could affect interpretation of survey data in important ways. Development of valid measures of sexual orientation will be essential to better monitor health disparities.

Early onset and recent drug use among children of parents with alcohol problems: data from a national epidemiologic survey

There is good evidence that children of parents with alcohol problems have more drug involvement, plus related mental health and behavioral problems. In this study, we sought to estimate the degree to which these children might be more likely to initiate drug use precociously. A sample of 2888 parent–child pairs was identified within public data files of the National Household Survey on Drug Abuse (NHSDA), 1995–1997. Alcohol dependence of one parent was assessed by that parent's report of three or more dependence manifestations. Independently, one randomly selected 12–17 year-old child of the parent answered self-report survey questions on age at first use of tobacco, alcohol, and marijuana. In analyses contrasting 114 children of alcohol dependent parents (AD+) with 2774 other children (AD−), youths with alcohol dependent parents had higher odds than other kids to have used tobacco in the past year (odds ratio, OR=3.2, 95% confidence interval, CI=2.05–4.98), as well as alcohol (OR=1.6, 95% CI=1.05–2.50), and marijuana (OR=2.9, 95% CI=1.71–4.90). Survival analyses were used to clarify excess risk of early-onset drug use. For example, by age 17, an estimated 73% of AD+ children had smoked tobacco cigarettes, 70% had started drinking, and 41% had smoked marijuana, versus 44%, 57%, and 26% of AD− children, respectively. This new evidence helps build a case that children of parents with alcohol problems experience precocious drug use.

The proper use of self-report questions in effective measurement of health outcomes.

Outcomes research often relies on the use of general population survey data. The recent efforts to employ cognitive science theory in the development of data collection instruments has led to the establishment of new questionnaire design research methods. Intensive cognitive techniques are used in laboratory interviews to develop and pretest self-report survey questions with the goal of reducing non-sampling response error. This article presents the theoretical and applied approach used in the cognitive laboratory to study the ways people respond to surveys, and offers guidelines for improving self-report survey questions.