Resilience, Well-being, and Empathy Among Private Practice Physicians and Advanced Practice Providers in Texas: A Structural Equation Model Study

Objective

To investigate structural relationships of latent constructs such as occupational wellbeing, resilience, work meaningfulness, and psychological empowerment with affective and cognitive clinical empathy among a community of physicians and advanced practice providers.

Methods

We conducted a cross-sectional observational study. We gathered data by an anonymous self-administered multidimensional questionnaire disseminated electronically between March and May 2016. Participants were physicians and advanced practice providers belonging to the Health Texas Provider Network, a group private practice affiliated with the Baylor Scott and White Health system. We excluded allied health care staff (eg, nurses) and trainees (eg, residents, medical students). We pursued a 3-step strategy: (1) confirmatory factor analysis of a theory-driven measurement model, (2) a modified structural equation model from which pathways with nonsignificant path coefficients were deleted, and (3) multigroup analyses of the modified model.

Results

Cognitive empathy was the strongest predictor of affective empathy. We observed modest positive associations of resilience with cognitive and affective empathy and of well-being and meaning with affective but not with cognitive empathy. Resilience, meaning, and psychological empowerment were surprisingly negatively associated with well-being, suggesting diminished self-care among practitioners. Effects of psychological empowerment on empathy and well-being were mediated by resilience and meaning.

Conclusion

Cognitive empathy directly influenced affective empathy; well-being and meaningfulness exerted direct positive effects on affective but not on cognitive empathy, whereas resilience had direct positive associations with both empathy dimensions. Resilience and meaning manifested direct, negative associations with well-being, revealing clinicians’ disproportionate focus on patient care at the expense of self-care.

Discovering different profiles in the dynamics of depression based on real-time monitoring of mood: a first exploration

BACKGROUND

Although depression is typically characterized by a persistent depressed mood, mood dynamics do seem to vary across a depressed population. Heterogeneity of mood variability (magnitude of changes) and emotional inertia (speed at which mood shifts) is seen in clinical practice. However, studies investigating the heterogeneity of these mood dynamics are still scarce. The aim of the present study is to explore different distinctive profiles in real-time monitored mood dynamics among depressed persons.

METHODS

After completing baseline measures, mildly-to-moderately depressed persons (n = 37) were prompted to rate their current mood (1-10 scale) on their smartphones, 3 times a day for 7 consecutive days. Latent profile analyses were applied to identify profiles based on average mood, variability of mood and emotional inertia as reported by the participants.

RESULTS

Two profiles were identified in this sample. The overwhelming majority of the sample belonged to profile 1 (n = 31). Persons in profile 1 were characterized by a mood just above the cutoff for positive mood (M = 6.27), with smaller mood shifts (lower variability [SD = 1.05]) than those in profile 2 (n = 6), who displayed an overall negative mood (M = 4.72) and larger mood shifts (higher variability [SD = 1.95]) but at similar speed (emotional inertia) (AC = 0.19, AC = 0.26, respectively).

CONCLUSIONS

The present study provides preliminary indications for patterns of average mood and mood variability, but not emotional inertia, among mildly-to-moderately depressed persons.

Goal Attainment: A Clinically Meaningful Measure of Success of Botulinum Toxin-A Treatment for Lower Limb Spasticity in Ambulatory Patients

Objectives

The objectives of this study were to evaluate whether botulinum toxin type A (BoNT-A) treatment for lower limb spasticity leads to patient goal attainment and identify factors associated with positive goal attainment and to assess the effect of BoNT-A treatment on patients’ gait.

Design

Retrospective cohort study between June 2014 and February 2019.

Setting

Public outpatient spasticity clinic in a tertiary hospital.

Participants

Thirty patients (N=30; 50% female; average age, 50.5y) with lower limb spasticity of heterogenous etiologies (96.7% cerebral±spinal origin and 3.3% isolated spinal origin); 73.3% (N=22) of patients had previously received BoNT-A treatment.

Interventions

BoNT-A injection to lower limb muscles.

Main Outcome Measures

The primary outcome measure was goal attainment measured using Goal Attainment Scaling. The Modified Ashworth Scale (MAS) was used to assess spasticity. Gait was characterized by spatiotemporal parameters.

Results

Fifty-six treatment episodes were analyzed and showed that BoNT-A treatment resulted in a significant reduction in spasticity (pretreatment MAS=3.18±0.73; posttreatment MAS=2.27±0.89; P<.001) with no associated change in gait parameters. Logistic regression revealed that most patients (74.1%) achieved all of their goals, with younger patients having a high likelihood of goal attainment regardless of their gait profile identified by latent profile analysis of the gait parameters. Patients considered to have a low functioning gait profile demonstrated a significantly greater likelihood of goal attainment than patients with the other gait profiles combined (odds ratio, 45.6; 95% confidence interval, 1.3-1602.1; P=.036). Chronic spasticity and pretreatment severity of spasticity (MAS) and its reduction were not associated with likelihood of goal attainment.

Conclusions

The success and efficacy of BoNT-A treatment in improving patient perceived gait quality and reducing the negative symptoms of spasticity were best measured using Goal Attainment Scaling. The study emphasizes the importance of measuring patient goals as a clinical outcome. Gait parameters were most informative when used collectively to classify patients based on their overall gait profile, which assisted in identifying differences between patients’ likelihood of goal attainment after treatment.