Model of Post-traumatic Growth in Newly Traumatized vs. Retraumatized Adolescents.

Background: In our analysis of adolescents affected by the 2016 Fort McMurray wildfire, we observed many negative mental health effects in individuals with a prior history of psychological trauma. Elevated rates of depression and markers of post-traumatic stress disorder (PTSD) were observed, consistent with the hypothesis that prior trauma may reduce sensitivity thresholds for later psychopathology (stress sensitization). Surprisingly, levels of anxiety did not differ based on prior trauma history, nor were retraumatized individuals at increased risk for recent (past month) suicidal ideation. These results are more suggestive of inoculation by prior trauma than stress sensitization. This led us to consider whether individuals with a prior trauma history showed evidence of Post-Traumatic Growth (PTG), a condition in which the experience of a previous trauma leads to areas of sparing or even improvement. Method: To investigate this issue, we generated a structural equation model (SEM) exploring the role of anxiety in previously traumatized (n = 295) and wildfire trauma alone (n = 740) groups. Specifically, models were estimated to explore the relationship between hopelessness, anxiety, PTSD symptoms, self-efficacy and potential protective factors such as friend and family support in both groups. The model was tested using a cross-sectional sample of affected youth, comparing effects between the two groups. Results: While both models produced relatively good fit, differences in the effects and chi-squared values led us to conclude that the groups are subject to different causal specifications in a number of areas, although details warrant caution pending additional investigation. Discussion: We found that adolescents with a prior trauma history appear to have a more realistic appraisal of potential difficulties associated with traumatic events, and seem less reactive to potentially unsettling PTSD symptoms. They also seemed less prone to overconfidence as they got older, an effect seen in the adolescents without a history of trauma. Our findings provide preliminary evidence that the construct of anxiety may work differently in newly traumatized and retraumatized individuals, particularly in the context of mass trauma events.

Fusion Validity: Theory-Based Scale Assessment via Causal Structural Equation Modeling.

Fusion validity assessments employ structural equation models to investigate whether an existing scale functions in accordance with theory. Fusion validity parallels criterion validity by depending on correlations with non-scale variables but differs from criterion validity because it requires at least one theorized effect of the scale, and because both the scale and scaled-items are included in the model. Fusion validity, like construct validity, will be most informative if the scale is embedded in as full a substantive context as theory permits. Appropriate scale functioning in a comprehensive theoretical context greatly enhances a scale's validity. Inappropriate scale functioning questions the scale but the scale's theoretical embedding encourages detailed diagnostic investigations potentially challenging specific items, the procedure used to calculate scale values, or aspects of the theory, but also possibly recommends incorporating additional items into the scale. The scaled items should have survived prior content and methodological assessments but the items may or may not reflect a common factor because items having diverse causal backgrounds can sometimes fuse to form a unidimensional entity. Though items reflecting a common cause can be assessed for fusion validity, we illustrate fusion validity in the more challenging context of a scale comprised of diverse items and embedded in a complicated theory. Specifically we consider the Leadership scale from the Alberta Context Tool with care aides working in Canadian long-term care homes.

Improving measurement-invariance assessments: correcting entrenched testing deficiencies.

BACKGROUND: Factor analysis historically focused on measurement while path analysis employed observed variables as though they were error-free. When factor- and path-analysis merged as structural equation modeling, factor analytic notions dominated measurement discussions - including assessments of measurement invariance across groups. The factor analytic tradition fostered disregard of model testing and consequently entrenched this deficiency in measurement invariance assessments. DISCUSSION: Applying contemporary model testing requirements to the so-called configural model initiating invariance assessments will improve future assessments but a substantial backlog of deficient assessments remain to be overcome. This article summarizes the issues, demonstrates the problem using a recent example, illustrates a superior model assessment strategy, and documents disciplinary entrenchment of inadequate testing as exemplified by the journal Organizational Research Methods. Employing the few methodologically and theoretically best, rather than precariously-multiple, indicators of latent variables increases the likelihood of achieving properly causally specified structural equation models capable of displaying measurement invariance. Just as evidence of invalidity trumps reliability, evidence of configural model misspecification trumps invariant estimates of misspecified coefficients.

Measuring Depression-Severity in Critically Ill Patients' Families with the Patient Health Questionnaire (PHQ): Tests for Unidimensionality and Longitudinal Measurement Invariance, with Implications for CONSORT.

CONTEXT: Families of intensive care unit patients are at risk for depression and are important targets for depression-reducing interventions. Multi-item scores for evaluating such interventions should meet criteria for unidimensionality and longitudinal measurement invariance. The Patient Health Questionnaire (PHQ), widely used for measuring depression severity, provides standard nine-, eight-, and two-item scores. However, published studies often report no (or weak) evidence of these scores' unidimensionality/invariance, and no tests have evaluated them as measures of depression severity in intensive care unit patients' families. OBJECTIVES: To identify multi-item PHQ constructs with promise for evaluating change in depression severity among family members of critically ill patients. METHODS: Structural equation models with rigorous fit criterion (χ(2), P ≥ 0.05) tested the standard nine-, eight-, and two-item PHQ, and other item subsets, for unidimensionality and longitudinal invariance, using data from a trial evaluating an intervention to reduce depressive symptoms in family members. RESULTS: Neither the standard nine-item nor the eight-item PHQ construct showed longitudinal invariance, although the standard two-item construct and other item subsets did. CONCLUSION: The longer eight- and nine-item PHQ scores appear inappropriate for assessing depression severity in this population, with constructs based on smaller subsets of items being more promising targets for future trials. The Consolidated Standards of Reporting Trials requirement for prespecified trial outcomes is problematic because unidimensionality/invariance testing must occur after trial completion. Consolidated Standards of Reporting Trials could be strengthened by endorsing rigorous assessment of composite scores and encouraging use of the most appropriate substitute, should trial-based evidence challenge the legitimacy of prespecified multi-item scores.

Rural Caregivers for a Family Member With Dementia: Models of Burden and Distress Differ for Women and Men.

Forecasts of increasing prevalence of dementia in rural settings, coupled with reliance on family caregiver support, indicate that a greater understanding of caregiver distress in these contexts is necessary. The purpose of this study was to examine family caregiver burden and severity of distress on the day that a family member was diagnosed with dementia at a memory clinic that serves a rural population. Participants in this retrospective study were 231 primary family caregivers of a rural community-dwelling person with dementia. On the diagnostic day, women reported more burden and severity of distress than men and spouses reported more severity of distress than adult children. A structural equation model was not supported for the entire sample, but was supported for women caregivers only (n = 161). Caregiver distress related to dementia-specific behaviors explained both global distress and burden. Patients' functional decline was related to caregiver burden.

Shame for disrespecting evidence: the personal consequences of insufficient respect for structural equation model testing.

BACKGROUND: Inappropriate and unacceptable disregard for structural equation model (SEM) testing can be traced back to: factor-analytic inattention to model testing, misapplication of the Wilkinson task force's [Am Psychol 54:594-604, 1999] critique of tests, exaggeration of test biases, and uncomfortably-numerous model failures. DISCUSSION: The arguments for disregarding structural equation model testing are reviewed and found to be misguided or flawed. The fundamental test-supporting observations are: a) that the null hypothesis of the χ2 structural equation model test is not nil, but notable because it contains substantive theory claims and consequences; and b) that the amount of covariance ill fit cannot be trusted to report the seriousness of model misspecifications. All covariance-based fit indices risk failing to expose model problems because the extent of model misspecification does not reliably correspond to the magnitude of covariance ill fit - seriously causally misspecified models can fit, or almost fit. SUMMARY: The only reasonable research response to evidence of non-chance structural equation model failure is to diagnostically investigate the reasons for failure. Unfortunately, many SEM-based theories and measurement scales will require reassessment if we are to clear the backlogged consequences of previous deficient model testing. Fortunately, it will be easier for researchers to respect evidence pointing toward required reassessments, than to suffer manuscript rejection and shame for disrespecting evidence potentially signaling serious model misspecifications.

Should researchers use single indicators, best indicators, or multiple indicators in structural equation models?

BACKGROUND: Structural equation modeling developed as a statistical melding of path analysis and factor analysis that obscured a fundamental tension between a factor preference for multiple indicators and path modeling's openness to fewer indicators. DISCUSSION: Multiple indicators hamper theory by unnecessarily restricting the number of modeled latents. Using the few best indicators - possibly even the single best indicator of each latent - encourages development of theoretically sophisticated models. Additional latent variables permit stronger statistical control of potential confounders, and encourage detailed investigation of mediating causal mechanisms. SUMMARY: We recommend the use of the few best indicators. One or two indicators are often sufficient, but three indicators may occasionally be helpful. More than three indicators are rarely warranted because additional redundant indicators provide less research benefit than single indicators of additional latent variables. Scales created from multiple indicators can introduce additional problems, and are prone to being less desirable than either single or multiple indicators.

Contributions of environment, comorbidity, and stage of dementia to the onset of walking and eating disability in long-term care residents.

OBJECTIVES: To estimate the relative effects of environment, comorbidities, stage of dementia and other variables on disability onset. DESIGN: A 1-year prospective cohort study was conducted in which the walking and eating abilities of long-term care residents were observed fortnightly. Structural equation modeling was used to assess the contributions of individual and environmental factors to the onset of disability. SETTING: Fifteen nursing homes in western Canada. PARTICIPANTS: One hundred twenty residents with middle-stage Alzheimer disease or related dementia. MEASUREMENTS: Environmental quality was assessed using the Professional Environmental Assessment Protocol, comorbidity using the Charlson Comorbidity Index, and stage of dementia using the Global Deterioration Scale. RESULTS: More-advanced baseline dementia had a direct effect on onset of walking and eating disability (standardized maximum likelihood estimate (SMLE) = 0.24, P = .006). Resident environment (SMLE = -0.25, P = .007) and comorbidities (SMLE = 0.32, P < .001) influenced disability onset approximately as strongly as stage of dementia. Smaller and publicly owned facilities provided superior environmental quality, which indirectly contributed to a delay in onset of walking and eating disability. CONCLUSION: Environmental quality and extent of comorbidity are at least as important as progression of dementia in initiating or delaying the onset of disability.

Advancing the argument for validity of the Alberta Context Tool with healthcare aides in residential long-term care.

BACKGROUND: Organizational context has the potential to influence the use of new knowledge. However, despite advances in understanding the theoretical base of organizational context, its measurement has not been adequately addressed, limiting our ability to quantify and assess context in healthcare settings and thus, advance development of contextual interventions to improve patient care. We developed the Alberta Context Tool (the ACT) to address this concern. It consists of 58 items representing 10 modifiable contextual concepts. We reported the initial validation of the ACT in 2009. This paper presents the second stage of the psychometric validation of the ACT. METHODS: We used the Standards for Educational and Psychological Testing to frame our validity assessment. Data from 645 English speaking healthcare aides from 25 urban residential long-term care facilities (nursing homes) in the three Canadian Prairie Provinces were used for this stage of validation. In this stage we focused on: (1) advanced aspects of internal structure (e.g., confirmatory factor analysis) and (2) relations with other variables validity evidence. To assess reliability and validity of scores obtained using the ACT we conducted: Cronbach's alpha, confirmatory factor analysis, analysis of variance, and tests of association. We also assessed the performance of the ACT when individual responses were aggregated to the care unit level, because the instrument was developed to obtain unit-level scores of context. RESULTS: Item-total correlations exceeded acceptable standards (> 0.3) for the majority of items (51 of 58). We ran three confirmatory factor models. Model 1 (all ACT items) displayed unacceptable fit overall and for five specific items (1 item on adequate space for resident care in the Organizational Slack-Space ACT concept and 4 items on use of electronic resources in the Structural and Electronic Resources ACT concept). This prompted specification of two additional models. Model 2 used the 7 scaled ACT concepts while Model 3 used the 3 count-based ACT concepts. Both models displayed substantially improved fit in comparison to Model 1. Cronbach's alpha for the 10 ACT concepts ranged from 0.37 to 0.92 with 2 concepts performing below the commonly accepted standard of 0.70. Bivariate associations between the ACT concepts and instrumental research utilization levels (which the ACT should predict) were statistically significant at the 5% level for 8 of the 10 ACT concepts. The majority (8/10) of the ACT concepts also showed a statistically significant trend of increasing mean scores when arrayed across the lowest to the highest levels of instrumental research use. CONCLUSIONS: The validation process in this study demonstrated additional empirical support for construct validity of the ACT, when completed by healthcare aides in nursing homes. The overall pattern of the data was consistent with the structure hypothesized in the development of the ACT and supports the ACT as an appropriate measure for assessing organizational context in nursing homes. Caution should be applied in using the one space and four electronic resource items that displayed misfit in this study with healthcare aides until further assessments are made.

Structural equation model testing and the quality of natural killer cell activity measurements.

BACKGROUND: Browne et al. [Browne, MacCallum, Kim, Andersen, Glaser: When fit indices and residuals are incompatible. Psychol Methods 2002] employed a structural equation model of measurements of target cell lysing by natural killer cells as an example purportedly demonstrating that small but statistically significant ill model fit can be dismissed as "negligible from a practical point of view". METHODS: Reanalysis of the natural killer cell data reveals that the supposedly negligible ill fit obscured important, systematic, and substantial causal misspecifications. RESULTS: A clean-fitting structural equation model indicates that measurements employing higher natural-killer-cell to target-cell ratios are more strongly influenced by a progressively intrusive factor, whether or not the natural killer cell activity is activated by recombinant interferon gamma (rIFN gamma). The progressive influence may reflect independent rate limiting steps in cell recognition and attachment, spatial competition for cell attachment points, or the simultaneous lysings of single target cells by multiple natural killer cells. CONCLUSIONS: If the progressively influential factor is ultimately identified as a mere procedural impediment, the substantive conclusion will be that measurements of natural killer cell activity made at lower effector to target ratios are more valid. Alternatively, if the individual variations in the progressively influential factor are modifiable, this may presage a new therapeutic route to enhancing natural killer cell activity. The methodological conclusion is that, when using structural equation models, researchers should attend to significant model ill fit even if the degree of covariance ill fit is small, because small covariance residuals do not imply that the underlying model misspecifications are correspondingly small or inconsequential.