4.Burton P, Gurrin L, Sly P. Extending the simple linear regression model to account for correlated responses: an introduction to generalized estimating equations and multi-level mixed modelling. Stat Med. 1998;17(11):1261-1291 In Reply: Drs Wang and Gao assert that social desirability is a response bias that can confound relationships among the variables of interest. This claim is nonspecific and belied by the evidence. First, a wide body of psychometric data suggests that the putative social desirability response bias is not a response bias at all, but a misnomer for a personality trait related to conventionality.1 Second, even if social desirability resulted in a response bias, there is no psychometric consensus on how it should be measured. Third, even if its measurement were attempted, including the results of this measurement in models may reduce rather than enhance the validity of associations.2,3 For instance, in the legally perilous and financially high-stakes world of personnel selection, meta-analytic evidence weighs heavily against the claims that social desirability is a response bias and confounds associations of interest; efforts to measure and adjust for it are discouraged. Fourth, even if a social desirability bias exists, measurement is endeavored, and adjustment attempted, social desirability responsiveness could bias treatment effect estimates only if it were associated with both the outcome and treatment.Even if all of the preceding conditions prevailed, data on the effects of mindfulness suggest that this putative bias would likely work in the opposite direction of the study's findings. The magnitude of the treatment effect would be underestimated because mindfulness treatments reduce, rather than increase, the reactivity to social norms and closemindedness characteristic of the social desirability bias. 4 Therefore, social desirability responding would operate prior to treatment, inflating pretreatment reports of adjustment. Because treatment reduces attributes giving rise to this putative response bias, posttreatment reports of adjustment would not benefit from the same inflation as pretreatment reports, thereby spuriously reducing the difference between pretreatment and posttreatment scores.Wang and Gao also raise concerns regarding the possible organizational effects among individuals, suggesting that the group effect should also be disaggregated and that modeling of both within-and between-individual effects can be used. First, we note that there were no other group effects to be disaggregated. Second, the linear mixed models used already model between-and within-individual effects. Third, even if clustering on a variable is observed, specification of a random effect is only appropriate if the clustering can be traced to the data generating process.5 A nonzero intraclass correlation is necessary but not sufficient evidence of such a data generating process. The sufficient condition is that measurements are random variables arising from a probability space in which their expected probabi...
Mindfulness interventions aim to foster greater attention to and awareness of present moment experience. There has been a dramatic increase in randomized controlled trials (RCTs) of mindfulness interventions over the past two decades. This article evaluates the growing evidence of mindfulness intervention RCTs by reviewing and discussing (a) the effects of mindfulness interventions on health, cognitive, affective, and interpersonal outcomes; (b) evidence-based applications of mindfulness interventions to new settings and populations (e.g., the workplace, military, schools); (c) psychological and neurobiological mechanisms of mindfulness interventions; (d) mindfulness intervention dosing considerations; and (e) potential risks of mindfulness interventions. Methodologically rigorous RCTs have demonstrated that mindfulness interventions improve outcomes in multiple domains (e.g., chronic pain, depression relapse, addiction). Discussion focuses on opportunities and challenges for mindfulness intervention research and on community applications.
Pawlowski, who assisted in identifying and locating published mixed methods studies.
Despite evidence linking trait mindfulness and mindfulness training with a broad range of effects, still little is known about its underlying active mechanisms. Mindfulness is commonly defined as (1) the ongoing monitoring of present-moment experience (2) with an orientation of acceptance. Building on conceptual, clinical, and empirical work, we describe a testable theoretical account to help explain mindfulness effects on cognition, affect, stress, and health outcomes. Specifically, Monitor and Acceptance Theory (MAT) posits that (1), by enhancing awareness of one’s experiences, the skill of attention monitoring explains how mindfulness improves cognitive functioning outcomes, yet this same skill can increase affective reactivity. Second (2), by modifying one’s relation to monitored experience, acceptance is necessary for reducing affective reactivity, such that attention monitoring and acceptance skills together explain how mindfulness improves negative affectivity, stress, and stress-related health outcomes. We discuss how MAT contributes to mindfulness science, suggest plausible alternatives to the account, and offer specific predictions for future research.
Objective: Mindfulness is a process whereby one is aware and receptive to present moment experiences. Although mindfulnessenhancing interventions reduce pathological mental and physical health symptoms across a wide variety of conditions and diseases, the mechanisms underlying these effects remain unknown. Converging evidence from the mindfulness and neuroscience literature suggests that labeling affect may be one mechanism for these effects. Methods: Participants (n ϭ 27) indicated trait levels of mindfulness and then completed an affect labeling task while undergoing functional magnetic resonance imaging. The labeling task consisted of matching facial expressions to appropriate affect words (affect labeling) or to gender-appropriate names (gender labeling control task). Results: After controlling for multiple individual difference measures, dispositional mindfulness was associated with greater widespread prefrontal cortical activation, and reduced bilateral amygdala activity during affect labeling, compared with the gender labeling control task. Further, strong negative associations were found between areas of prefrontal cortex and right amygdala responses in participants high in mindfulness but not in participants low in mindfulness. Conclusions: The present findings with a dispositional measure of mindfulness suggest one potential neurocognitive mechanism for understanding how mindfulness meditation interventions reduce negative affect and improve health outcomes, showing that mindfulness is associated with enhanced prefrontal cortical regulation of affect through labeling of negative affective stimuli.
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