mindfulness, health symptoms and healthcare utilization: active facets and possible affective...

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Mindfulness, health symptoms, and healthcare utilization:

active facets and possible affective pathways

Journal: AIDS Care - Psychology, Health & Medicine - Vulnerable Children and Youth

Studies

Manuscript ID: PHM-2013-02-0131.R2

Journal Selection: Psychology, Health & Medicine

Keywords: symptoms, health utilization, mindfulness, emotion, mindfulness facets

http://mc.manuscriptcentral.com/ac-phm-vcy

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Mindfulness facets and health 1

Mindfulness, health symptoms, and healthcare utilization: active facets and possible affective

mediators

RUNNING HEAD: MINDFULNESS FACETS AND HEALTH

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Abstract

Prior work has linked mindfulness with superior physical and psychological health

outcomes. However, studies to date have infrequently tested the unique contributions of individual

mindfulness facets, inadequately tested links between facets and healthcare utilization, and have not

tested whether depression or anxiety may influence these links. In the current report, 40 young,

middle aged and older adults (N = 121) completed measures of dispositional mindfulness, health,

healthcare utilization and depression/anxiety. As expected, global trait mindfulness did not predict

outcomes while individual mindfulness facets predicted both objective and subjective health as well

as healthcare utilization. Across models, observe scores – the tendency to attend to thoughts,

sensations and feelings – predicted poorer, and non-reactivity scores better, outcomes even when

controlling for demographic and health confounds. Depressed and anxious emotion reduced some

but not all mindfulness-health links. Results are discussed in terms of the mechanisms by which

greater mindfulness may facilitate better health and health behaviour.

Key words: mindfulness; mindfulness facets; health; symptom reporting; healthcare utilization;

anxiety; depression

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Mindfulness – the ability or tendency towards bringing attention to present experiences in a

nonjudgmental or accepting way (Baer, Smith, Hopkins, Krietemeyer, & Toney, 2006) – predicts

better health. Trait mindfulness predicts better health and health behaviour (Greeson, 2009), fewer

symptoms (Brown & Ryan, 2003), better perceived health (Zvolensky et al., 2006) and lower

healthcare utilization (Brown & Ryan, 2003). Mindfulness also predicts fewer psychological

symptoms, lower anxiety and less depression (McCracken, Gauntlett-Gilbert, & Vowles, 2007).

However, aspects of these links remain unclear. First, the most relevant facets of

mindfulness are unknown (Schneider, Hough, & Dunnette, 1996). Describing, awareness, non-

judging, and non-reactivity facets predict fewer, but observe greater, symptoms (Baer et al., 2008).

Specifically relevant to physical health, observe scores index the tendency to attend to internal

stimuli such as thoughts, sensations and feelings, while non-reactivity reflects a considered approach

to these phenomena and responding with purposeful behaviour (Reynolds, Consedine, &

McCambridge, 2013).

Second, data have primarily linked mindfulness facets to subjective rather than objective

metrics. We contrast the ability of mindfulness facets to predict objective versus subjective

outcomes. Three, while total mindfulness predicts health behaviour (Brown & Ryan, 2003), how

specific facets predict utilization is unclear. This report evaluates which facets predict utilization for

chronic and psychological issues.

Finally, the mechanisms by which mindfulness predicts health remain unclear (Coffey,

Hartman, & Fredrickson, 2010). Although mindfulness may bolster disease resistance (Davidson et

al., 2003) or reduce symptom sensitivity (Zeidan et al., 2011), it may also predict better health

indirectly by lowering anxiety and depression (Zvolensky et al., 2006). Mindfulness predicts lower

anxiety and depression (Williams, Ciarrochi, & Deane, 2010) and negative affect (Giluk, 2009).

Commensurately, depressed affects predict greater symptoms (Consedine, 2008) and utilization

(Callahan, Kesterson, & Tierney, 1997), while anxiety has weaker links to symptoms but predicts

greater utilization (Consedine & Moskowitz, 2007). Effects on subjective outcomes persist even

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when controlling objective disease metrics (Cohen et al., 1995), implying affect may be more

heavily implicated in subjective symptomology.

Overall, we expected mindfulness facets would better predict outcomes than a global

mindfulness score. We expected the observe facet to predict greater symptomology and other facets

to predict less; neither facet nor total scores should predict objective health (number of diagnosed

conditions). Finally, depression and anxiety should weaken links between mindfulness and

subjective outcomes but leave the objective outcome models essentially unchanged.

Methods

Participants

40 community-dwelling adults aged 18+ years in each of 18-34, 35-59, and 60+ year

brackets (Total N = 121) were recruited. Two thirds were female, 54.5% married/living with

partner, and 86% of majority ethnicity; 16 years education was average.

Procedures

Recruitment used advertisements and flyers, with electronic advertisements sent via e-mail

and Facebook. Interested participants contacted the coordinator who posted paper questionnaires

and return envelopes. No exclusions or incentives were used and no drop outs were recorded.

Measures

Demographics and confounds. Self-reported gender, age (years), weight (kg), height (cm)

smoking history (ever/never), and current exercise frequency (using a 0 “never” to 7 “daily”) scale.

Dispositional mindfulness. Five Facet Mindfulness Questionnaire (FFMQ) (Baer et al.,

2006). The FFMQ assesses five facets and has good psychometric properties (Baer et al., 2008). In

this report reliabilities were .78 (observe), .91 (describe), .88 (awareness), .87 (non-judge), and .83

(non-react).

Objective health conditions. Participants reported formal diagnoses of physical or mental

health conditions. Condition counts were aggregated.

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Subjective symptomology. The 42-item Wahler Physical Symptom Inventory (WPSI)

(Wahler, 1968) has respondents indicate how often they are bothered by symptoms including

backaches, difficulty breathing, pain, and bowel trouble (Frezza, Wachtel, & Gordhamer, 2008).

The WPSI has good internal consistency and is widely used (Consedine et al., 2006). Reliability

was .87.

Healthcare utilisation. Participants reported the frequency of doctor/health professional

visits for chronic conditions and psychological issues in the past year.

Anxious and depressed affect. Hospital Anxiety and Depression Scale (HADS) (Zigmond &

Snaith, 1983). The scale excludes somatic symptoms (Bjelland, Dahl, Haug, & Neckelmann, 2002)

and has good internal consistency (Bjelland et al., 2002), convergent validity, and test retest

reliability. Reliabilities were .77 (anxiety) and .65 (depression).

Analytic strategy

Data were analyzed in two phases. First, we characterized our sample (Table 1). Second,

step-wise linear regressions regressed outcomes on demographics/confounds, mindfulness facets,

and possible affect. Confounds and mindfulness were entered in Step 1 and depression/anxiety at

Step 2.

Results

Characteristics of the sample are displayed in Table 1. Health problems afflicted 57% of the

sample and 47% had been diagnosed with a condition (ranging from hayfever to CHD); 10.7% had

been diagnosed with a mental condition.

Multivariate prediction of objective and subjective health

After checking univariate correlations (Table 2), we assessed whether facets versus total

mindfulness better predicted objective conditions. Total mindfulness was a poor predictor (Table 3);

the initial model was marginal, F (6, 114) = 1.90, p = .09, with no mindfulness effect. Adding

depression and anxiety in Step 2 did not improve fit, F∆ (2, 112) = 1.27, n. s. The model using

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facets was slightly better. Although neither Step 1 nor Step 2 models were significant, non-

reactivity predicted fewer conditions (see Table 3).

Given this pattern, hypotheses regarding subjective symptoms were tested using facets

alone. Symptomology was predicted at Step 1 by being female, greater observe, and lower non-

reactivity scores. After adding depression and anxiety at Step 2 symptomology remained greater

among females but observe and non-reactivity effects were eliminated while greater depression and,

marginally, anxiety were now predictors (Table 4).

Multivariate prediction of chronic condition and psychological visit frequency

The initial model predicting chronic visit frequency was significant (Table 5). Visits were

predicted by health conditions and greater observe scores. Adding depression and anxiety changed

nothing in this model. The initial model predicting psychological visits explained 43% variance;

having a psychological diagnosis, greater BMI, lower age, greater observe, lower non-reactivity,

and, marginally, lower describe scores predicted more visits. Adding depression and anxiety did not

alter these effects; the model remained significant but was not improved.

Discussion

The current report makes several contributions. First, relative to mindfulness facets, total

mindfulness failed to predict outcome; effects held even when controlling for confounds. Second,

mindfulness facets were better predicts of subjective versus objective health indices. Finally,

depressed or anxious affect may influence some but not all mindfulness-health links.

Operationalizing mindfulness in health and health behaviour research

Specific mindfulness facets appear more useful than global scores in predicting health. As

expected, observe scores predicted greater symptomology but non-reactivity scores predicted less.

Similarly, higher observe scores predicted more frequent chronic conditions and psychological

visits while non-reactivity scores predicted less frequent psychological visits. High observe

individuals may not have objectively worse health but experience health as poorer while non-

reactivity may index the ability to manage health issues without responding with anxiety or

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impulsiveness (Baer, 2009). Overall, notwithstanding whether symptoms, conditions, or behaviours

were considered, modelling mindfulness facets was consistently more informative. Importantly, it

was not just that mindfulness predicted more conditions (Table 3). Even when condition counts

(and other confounds) were covaried, persons with greater observe scores consumed more

healthcare while those with greater non-react scores consumed less (see Tables 4-5).

The mechanism question – depression and anxiety as possible mediators

As expected, the link between non-reactivity and objective conditions did not change (Table

4), but effects for observe and non-react facets in predicting subjective symptoms were eliminated

after controlling for HADS scores (Table 5). Although low reliability in the HADS-D in this

healthy sample is important (see Mykletun, Stordal, & Dahl, 2001), negative affect mediates

mindfulness-sleep links (Caldwell, Harrison, Adams, Quin, & Greeson, 2010). Because

mindfulness predicts less depression/anxiety and negative affects predict greater symptoms and

utilization, adding such variables might weaken mindfulness-health links. In our study, however,

observe scores (associated with an internal focus) did not predict depressive symptoms (Table 2),

but predicted greater utilization even when controlling for depression. This pattern suggests the link

between mindfulness facets and utilization is not merely a function of a depressogenic internal

focus or affect more broadly (Table 5). Indeed, the role of negative affect in mindfulness-health

links may be most prominent when assessing subjective symptoms. Behaviourally, persons with

greater non-reactivity have more flexible cognitive control (Anicha, Ode, Moeller, & Robinson,

2012) and persons who are less reactive may be less prone to reflexively seek care when confronted

with symptoms or health anxiety.

Obviously, interpretations are constrained by design. Although using distinct metrics to

assess mindfulness, symptoms, and behaviour should ameliorate method bias (Podsakoff,

MacKenzie, & Podsakoff, 2012), only the diagnosis count is objective and our sample relatively

young and healthy. Objective measures of disease are obvious next steps as are designs among older

groups or those in poorer health; links between mindfulness and outcome might vary in less healthy

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groups. We assessed trait mindfulness not meditation experience; measurement may vary with

experience (Veehof, ten Klooster, Taal, Westerhof, & Bohlmeijer, 2011). Most interventions

include formal training/practice that is supplemented by informal use. In theory, living mindfully

rather than training should produce benefits (Dimidjian & Linehan, 2006). Our data do not enable

commentary on this issue.

Despite such limitations, the present work extends data linking mindful functioning to

health. Tendencies to observe and/or react predicted outcomes, for both objective and subjective

symptomology, as well as for utilization. While depressed and anxious affect reduced the effects on

subjective symptomology, objective health and healthcare utilization models remained unchanged.

Providing participants are prepared for initial increases in symptomatic awareness, mindfulness

interventions aimed at health might thus profitably target non-reactivity.

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Table 1 – Means and standard deviations of demographic, health and mindfulness variables across gender and age group

Variable

Male Female

Young Middle Older Young Middle Older

Age (years) 25.13 (3.23) 49.78 (8.41) 66.33 (7.00) 25.97 (3.44) 49.84 (6.17) 64.94 (6.73)

% Ever smoked 62.5 33.3 50.0 39.4 54.8 62.5

Exercise 3.38 (1.77) 4.00 (1.58) 2.67 (1.27) 4.56 (1.50) 4.90 (1.38) 4.44 (1.71)

Height (cm) 180.75 (9.87) 179.21 (8.43) 173.55 (8.21) 165.42 (6.14) 164.22 (6.26) 164.84 (4.23)

Weight (kg) 76.88 (8.32) 99.44 (28.59) 79.25 (10.56) 64.10 (19.32) 65.67 (11.42) 70.05 (14.22)

BMI (kg/m2) 23.48 (1.22) 31.32 (10.57 26.41 (3.85) 23.37 (6.73) 24.28 (3.53) 25.70 (4.40)

Symptoms (WPSI) 32.38 (12.09) 22.67 (15.45) 25.54 (18.60) 36.64 (17.42) 34.42 (17.42) 32.19 (24.06)

Past year psych visits .00 (.00) .00 (.00) .21 (.83) .97 (2.93) .16 (.74) .31 (1.01)

Past year chronic visits 1.50 (4.24) .11 (.33) 1.75 (5.30) .52 (1.03) .55 (1.52) 1.31 (1.78)

# Diagnosed conditions .50 (.76) .22 (.44) 1.00 (.86) .45 (.62) .32 (.48) 1.00 (.73)

Total mindfulness 122.00 (16.14) 132.44 (12.49) 140.78 (13.90) 129.67 (17.43) 135.33 (19.71) 145.04 (17.33)

Observe facet 3.02 (.73) 2.94 (.73) 3.55 (.52) 3.15 (.45) 3.45 (.76) 3.61 (.62)

Describe facet 3.17 (.58) 3.43 (.63) 3.66 (.59) 3.67 (.84) 3.72 (.82) 3.94 (.57)

Aware facet 2.75 (.54) 3.61 (.42) 3.65 (.61) 3.25 (.61) 3.25 (.70) 3.67 (.66)

Non-judge facet 3.48 (.54) 3.69 (.42) 3.70 (.59) 3.40 (.80) 3.65 (.65) 3.94 (.82)

Non-react facet 3.23 (.60) 3.29 (.61) 3.48 (.56) 3.13 (.57) 3.24 (.61) 3.39 (.86)

HADS Anxiety 7.88 (2.23) 5.56 (2.51) 5.25 (4.00) 7.24 (3.69) 6.34 (2.72) 4.63 (2.55)

HADS Depression 4.75 (2.82) 2.00 (2.06) 3.04 (2.29) 2.91 (2.71) 3.00 (2.07) 2.83 (2.19)

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Table 2 – Zero-order correlations between total mindfulness, mindfulness facets, depression,

anxiety, demographics and health outcomes

Mindfulness facet or affect

Total Observe Describe Aware Non-

judge

Non-

react Anxiety Depress

Demographic

Age (years) .34** .29** .08 .36** .23* .18* -.32** -.06

Sex -.00 .02 .17ŧ -.09 .04 -.10 .08 -.04

Ever smoke? .03 .12 .06 -.08 -.05 .09 .13 .17ŧ

Exercise .23* .20* .19* .08 .16ŧ .12 -.13 -.12

BMI (kg/m2) .06 -.01 -.07 .17

ŧ .20* -.10 -.11 .09

Health

# Diagnosed

conditions .05 .09 -.01 .08 .10 -.10 -.13 .08

Symptoms

(WPSI) -.22** .04 -.13 -.25** -.16

ŧ -.27** .36** .43**

Mental

condition? -.15 -.06 -.04 -.15 -.15 -.14 .29** .29**

Past year

psych visits .10 .23* .12 .00 .00 -.03 -.06 .11

Past year

chronic visits -.20* .03 -.18* -.09 -.17

ŧ -.29** .23* .28**

HADS

Anxiety -.51** -.12 -.23* -.46** -.57** -.34** - .16**

HADS

Depression -.44** -.09 -.42** -.36** -.31** -.26** .46** -

*p < .05, **p < .01, ŧ p < .10

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Table 3:

Raw and standardized coefficients from two steps of two linear regressions in which objective health condition frequency was regressed on

demographics, controls and either global mindfulness or mindfulness facets (Step 1) before adding affective characteristics (Step 2)

Global mindfulness model Mindfulness facets model

Step 1 Step 2 Step 1 Step 2

B SE β sr2 B SE β sr

2 B SE β sr

2 B SE β sr

2

Age .01 .00 .28** .06 .01 .00 .25* .05 .01 .00 .25* .04 .01 .00 .22* .03

Sex -.09 .14 -.06 .00 -.09 .14 -.06 .00 -.18 .15 -.12 .01 -.18 .15 -.12 .01

Smoke -.08 .10 -.07 .00 -.09 .11 -.08 .01 -.06 .10 -.05 .00 -.07 .11 -.07 .00

Exercise -.03 .04 -.06 .00 -.02 .04 -.05 .00 -.03 .04 -.08 .00 -.03 .04 -.07 .00

BMI .00 .01 -.01 .00 .00 .01 -.03 .00 -.01 .01 -.06 .00 -.01 .01 -.08 .01

Global MF .00 .00 -.02 .00 .00 .00 .00 .00 - - - - - - - -

Observe - - - - - - - - .15 .12 .14 .01 .15 .12 .13 .01

Describe - - - - - - - - .00 .10 .00 .00 .05 .11 .05 .00

Aware - - - - - - - - -.03 .12 -.02 .00 -.01 .12 -.01 .00

Non-judge - - - - - - - - .14 .11 .14 .01 .11 .12 .11 .01

Non-react - - - - - - - - -.29 .13 -.25* .04 -.30 .13 -.26* .04

Anxiety - - - - -.03 .02 -.12 .01 - - - - -.03 .03 -.14 .01

Depression - - - - .05 .03 .16 .02 - - - - .05 .03 .16 .02

Constant .43 .58 - - .46 .75 - - 0.61 0.58 - - .73 .77 - -

Model F/R2 F(6,114)=1.90, n.s.; R

2=.09 F(8,112)=1.75, n.s; R

2=.11 F(10,110)=1.76, n.s.; R

2=.14 F(12,108)=1.68, p=.08; R

2=.16

Model F∆ - F∆(2,112)=1.27, n.s F∆(2,108)=1.25, n.s

Notes: * p <.05, ** p < .01, ŧ p < .10, sr

2 = squared part correlation

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Table 4

Raw and standardized coefficients from two steps of a linear regression in which subjective

health symptomology was regressed on demographics, controls and mindfulness facets (Step

1) and affective characteristics (Step 2)

Variables Step 1 Step 2


2

Age -0.08 0.11 -0.08 -0.06 -0.06 0.10 -0.06 -0.05

Sex 8.13 3.69 0.21* 0.18 8.25 3.46 0.21* 0.19

Smoke 3.93 2.56 0.14 0.13 1.91 2.46 0.07 0.06

Exercise -0.53 1.07 -0.05 -0.04 -0.54 1.01 -0.05 -0.04

BMI 0.50 0.30 0.15ŧ 0.14 0.39 0.28 0.12 0.11

# Conditions 3.56 2.34 0.14 0.13 3.10 2.22 0.12 0.11

Observe 5.80 2.98 0.20* 0.16 4.49 2.82 0.16 0.13

Describe -1.99 2.50 -0.08 -0.07 0.51 2.47 0.02 0.02

Aware -4.62 2.91 -0.17 -0.13 -1.96 2.81 -0.07 -0.05

Non-judge -0.64 2.69 -0.02 -0.02 2.51 2.75 0.09 0.07

Non-react -6.47 3.20 -0.22* -0.17 -4.69 3.06 -0.16 -0.12

Anxiety - - - - 1.08 0.61 0.19ŧ 0.14

Depression - - - - 2.28 0.78 0.29** 0.23

Constant 43.10 14.35 - - 1.59 17.79 - -

Model F/R2 F(11,109)=3.06, p<.01; R

2=.24 F(13,107)=4.22, p<.01; R

2=.34

Model F∆ - F∆(2,107)=8.36, p<.01

Notes: * p <.05, ** p < .01, ŧ p < .10, sr


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Mindfulness components and health 17

Table 5

Raw and standardized coefficients from two steps of two linear regression in which the frequency of physician visits for chronic conditions and

psychological issues were regressed on demographics, controls and mindfulness facets (Step 1) before adding affective characteristics (Step 2)

Chronic condition visits model Psychological visits model

Step 1 Step 2 Step 1 Step 2


2 B SE β sr

2 B SE β sr

2

Age -0.02 0.02 -0.12 0.01 -0.02 0.02 -0.15 0.01 -0.02 0.01 -0.18* 0.02 -0.02 0.01 -0.18* 0.02

Sex -0.86 0.58 -0.14 0.02 -0.90 0.58 -0.15 0.02 0.37 0.29 0.10 0.01 0.37 0.29 0.10 0.01

Smoke 0.03 0.41 0.01 0.00 -0.03 0.41 -0.01 0.00 0.30 0.20 0.11 0.01 0.29 0.21 0.11 0.01

Exercise 0.11 0.17 0.06 0.00 0.11 0.17 0.06 0.00 0.05 0.08 0.05 0.00 0.05 0.08 0.05 0.00

BMI 0.02 0.05 0.03 0.00 0.01 0.05 0.01 0.00 0.10 0.02 0.34** 0.09 0.10 0.02 0.34** 0.09

# Conds 1.09 0.37 0.28** 0.07 0.99 0.37 0.25** 0.05 1.69 0.42 0.31** 0.09 1.66 0.44 0.31** 0.08

Observe 1.16 0.47 0.26* 0.05 1.17 0.47 0.27* 0.05 0.59 0.23 0.23* 0.03 0.58 0.24 0.22* 0.03

Describe 0.43 0.40 0.11 0.01 0.63 0.42 0.16 0.02 -0.39 0.20 -0.17* 0.02 -0.38 0.21 -0.17ŧ 0.02

Aware -0.19 0.46 -0.04 0.00 -0.16 0.47 -0.04 0.00 0.21 0.23 0.08 0.00 0.22 0.24 0.09 0.00

Non-judge -0.08 0.43 -0.02 0.00 -0.26 0.46 -0.06 0.00 -0.23 0.21 -0.10 0.01 -0.23 0.23 -0.10 0.01

Non-react -0.62 0.51 -0.14 0.01 -0.70 0.51 -0.15 0.01 -0.59 0.25 -0.22* 0.03 -0.59 0.25 -0.22* 0.03

Anxiety - - - - -0.15 0.10 -0.17 0.01 - - - - 0.00 0.05 0.00 0.00

Depression - - - - 0.21 0.13 0.18 0.02 - - - - 0.02 0.07 0.02 0.00

Constant -1.74 2.28 - - -0.85 2.99 - - -0.60 1.12 - - -0.71 1.51 - -

Model F/R2 F(11,109)=2.09, p<.05; R

2=.17 F(13,107)=2.06, p<.05; R

2=.20 F(11,109)=7.45, p<.01; R

2=.43 F(13,107)=6.20, p<.01; R

2=.43

Model F∆ - F∆(2,107)=1.73, n.s - F∆(2,107)=0.03, n.s

Notes: * p <.05, ** p < .01, ŧ p < .10; # Conds is scored 0 (absent)/1 (present) for psychological visit model; sr


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