Behavioral cues to expand a pain model of the cognitively impaired elderly in long-term care

Figures & data

Table 1 Theoretical construct definitions^38,63

Term	Definition
Need-driven behaviors	Expressions of unmet needs or goals
Need-driven dementia compromised behaviors (NDB)	The most meaningful response a dementia-compromised person can give with the limitations of the disease process; disruptive behaviors could be the only and base mechanisms of communication; reflect the interaction of background and proximal factors
Consequences of need-driven dementia-compromised behavior (C-NDB)	Explains the consequences of behavioral symptoms of individuals with dementia; needs are expressed behaviorally and unmet needs influence additional behavioral cues
Antecedent	A preceding cause
Consequence	Events/actions that result from inaction of the need or failing to respond appropriately to the primary need
Proximal factor	More changing aspect of a person’s physical status or social/physical environment. Proximal factors are more likely to precipitate NDBs; ie, emotions, light level, noise, staff stability
Background factor	Neurological, cognitive, general health or psychosocial factors that produce NDBs; ie, regional brain involvement, memory/language skills, functional ability, affective state, behavioral response to stress
Primary need	Immediate need
Secondary need	Needs that may arise from primary needs not being met

Figure 1 Sample method.

Figure 2 Latent construct pain.

Table 2 Demographic table of resident characteristics

(n = 52,996)	Mean ± SD N (percent)	Range
Age	83.7 ± 8.1	65–112
Gender
Male	10,798 (20.4%)
Female	42,198 (79.6%)
Cognitive status
Mean CPS score	2.9 ± 1.9	0–6
Mean MMSE	14.4 ± 8.0	0.4–24.5
Intact	7,428 (14.0%)
Mild	13,928 (26.3%)
Moderate	15,216 (28.7%)
Severe	16,424 (31.0%)
Marital status
Never married	12.7%
Married	15.5%
Widowed	62.3%
Separated	2.2%
Divorced	7.3%
Ethnicity
American Indian/Alaskan natives	0.3%
Asian/Pacific islander	1.2%
Black, not of Hispanic origin	11.4%
Hispanic	2.9%
White, not of Hispanic origin	84.2%
Language
English	94.6%
Spanish	2.4%
French	0.2%
Other	2.8%
Education level
No schooling	3.0%
8th grade/less	30.8%
9–11 grade	14.2%
High school	33.2%
Technical or trade school	4.2%
Some college	7.2%
Bachelor’s degree	4.2%
Graduate degree	1.8%
Not coded/missing	1.5%

Abbreviations: CPS, Cognitive performance scale; MMPE, Folstein mini mental status examination.

Table 3 Diseases/events with potential pain symptoms

Diseases	Number from total (n = 52, 996)	Percent of total
Diabetes	11,063	20.9%
Peripheral vascular disease	6,128	11.6%
*Arthritis	18,110	34.2%
Complaint of joint pain	7,703	14.5%
*Hip fracture	2,113	4.0%
Multiple sclerosis	440	0.8%
Emphysema/COPD	6,423	12.1%
*Cancer	2,844	5.4%
Renal failure	1,327	2.5%
*Pneumonia	472	0.9%
Respiratory infection	1,213	2.3%
Septicemia	28	0.1%
*Urinary tract infection (UTI)	2,737	5.2%
Wound infection	285	0.5%

Note:

* Key diagnoses used for pain diagnosis scoring.

Table 4 Behavioral index

Cognitive status	Intact (n = 7,428)	Mild (n = 13,928)	Moderate (n = 15,216)	Severe (n = 16,424)
Change in behavioral symptoms	101 Improved (1.4%)	348 (2.5%)	645 (4.2%)	821 (5.0%)
	110 Deteriorated (1.5%)	357 (2.6%)	792 (5.2%)	792 (4.8%)
Pain behavior
Affect/nonverbal cues
(E1D) Persistent anger	751 (10.1%)	1,840 (13.2%)	2,839 (18.6%)	2,033 (12.4%)
(E1K) Insomsnia	197 (2.6%)	378 (2.7%)	595 (3.9%)	560 (3.4%)
(E1L) Sad facial expressions	173 (10%)	2,197 (15.8%)	3,558 (23.4%)	3,647 (22.2%)
(E1M) Crying	245 (3.3%)	715 (5.2%)	1,158 (7.6%)	1,452 (8.9%)
(E1O) Withdrawal	107 (1.4%)	394 (2.8%)	574 (3.8%)	659 (4.1%)
(E1P) Reduced social interaction	196 (2.6%)	546 (3.9%)	744 (4.9%)	813 (4.9%)
(E2) Persistence	1,742 (23.4%)	4,514 (32.4%)	6,895 (45.3%)	6,726 (40.9%)
Verbal cues
(E1A) Negative statements	181 (2.4%)	489 (3.6%)	711 (4.6%)	307 (1.9%)
(E1B) Repetitive questions	34 (0.4%)	426 (3.1%)	1,949 (12.8%)	1,085 (6.6%)
(E1C) Repetitive verbalizations	68 (0.9%)	355 (2.5%)	1,306 (8.6%)	1,631 (9.9%)
(E1E) Self deprecation	79 (1.1%)	277 (2.0%)	312 (2.1%)	115 (.7%)
(E1H) Health complaints	776 (10.5%)	1,572 (11.3%)	1,386 (9.1%)	380 (2.3%)
(E1I) Anxious complaints	693 (9.3%)	1,853 (13.3%)	2,524 (16.6%)	960 (5.9%)
(E4BA) Verbally abusive frequency	304 (4.1%)	943 (6.7%)	2,194 (14.4%)	1,915 (11.7%)
Physical cues
(E4DA) Inappropriate behavior frequency; disruptive sounds, noisiness, screaming, self-abuse acts, sexual behavior or disrobing in public, smeared/threw feces, hoarding, rummaging through other’s belongings	178 (2.5%)	857 (6.2%)	2,273 (14.9%)	3,344 (20.4%)
(E4DB) Inappropriate behavior alterability	108 (1.5%)	505 (3.6%)	1,420 (9.3%)	2, 326 (14.2%)
(B5D) Restlessness	65 (0.9%)	689 (4.9%)	3,023 (19.8%)	5,772 (35.1%)
(E1N) Repetitive physical movements; pacing, hand wringing, restlessness, fidgeting, picking	100 (1.4%)	621 (4.4%)	2,158 (14.2%)	3.855 (23.5%)
(E4AA) Wandering frequency	5 (0.1%)	187 (1.4%)	1,874 (12.3%)	2,755 (16.8%)
(E4AB) Wandering alterability	2	68 (0.5%)	900 (5.9%)	1,699 (10.3%)
(E4CA) Physically abusive frequency	37 (0.5%)	223 (1.7%)	1,068 (7.1%)	2,094 (12.7%)
(E4CB) Physically abusive alterability	23 (0.3%)	97 (0.7)	617 (4.1%)	1,368 (8.3%)
(E4EA) Resists care frequency	387 (5.1%)	1,417 (10.3%)	3,375 (22.2%)	4,934 (30.0%)
(E4EB) Resists care alterability	287 (3.9%)	972 (7.0%)	2,244 (14.7%)	3,392 (20.7%)

Table 5 Fries pain scale (PS) ratings

Fries pain indicators	Total population (n = 52,996)	Intact (n = 7,428)	Mild (n = 13,928)	Moderate (n = 15,216)	Severe (n = 16,424)
Pain frequency (J2a)
No pain	36,470 (68.8%)	3,887 (52.3%)	8,411 (60.4%)	10,737 (70.6%)	13,435 (81.8%)
Pain less than daily	9,731 (18.4%)	1,869 (25.2%)	3,144 (22.6%)	2,796 (18.4%)	1,922 (11.7%)
Pain daily	6,795 (12.8%)	1,672 (22.5%)	2,373 (17.0%)	1,683 (11.0%)	1,067 (6.5%)
Pain totals	16,526 (31.2%)	3,541 (47.7%)	5,517 (39.6%)	4,479(29.4%)	2,989 (18.2%)
Pain intensity (J2b)
Mild pain	8, 046 (15.2% of total, or 49% within reported pain)	1,514 (20.4%/42.8%)	2,608 (18.7%/47.3%)	2,295 (15.1%/51.2%)	1,629 (9.9%/54.5%)
Moderate pain	7,946 (15%/48%)	1,873 (25.2%/52.9%)	2,731 (19.6%/49.5%)	2,065 (13.6%/46.1%)	1,277 (7.8%/42.7%)
Horrible/excruciating	534 (1%/3%)	154 (2.1%/4.3%)	178(1.3%/3.2%)	119 (.8%/2.7%)	83 (0.5%/2.8%)
Total	16,526	3,541	5,517	4,479	2,989

Table 6 Preliminary model factoring loadings

	Est	SE	CR	P	Label
Pain
(Cum) Pain score 2001	1.000
(J2B) Pain intensity	1.034	0.003	311.057	***	k
(J2A) Pain frequency	0.943	0.003	313.011	***	j
(J1N) Unsteady gait	0.046	0.003	15.931	***	i
(E1A) Neg state	0.019	0.001	15.045	***	h
(E3) Mood change	0.046	0.003	16.511	***	g
(E1M) Crying	0.035	0.002	21.770	***	f
(E1L) Worried face	0.085	0.003	27.922	***	e
(E1C) Repeat verb	0.016	0.001	11.887	***	d
(E4CA) Phys abusive	−0.001	0.001	−1.062	0.288	c
(E1N) Repeat moves	0.009	0.002	5.090	***	b
(E4DA) Dis behavior	0.008	0.003	2.794	0.005	a

Note:

*** Significantly different from zero at the 0.001 level (two-tailed).

Abbreviations: SE, standard error; CR, critical ratio.

Table 7 Definitions of the indicators

Indicators
Variable	Description
Inferred/reported pain
(J2A) Pain frequency	Frequency resident complains or shows evidence of pain
(J2B) Pain intensity	Intensity of pain described or displayed by the resident
Pain sites score	Cumulative pain site index, items J2a-J3j, K1c; higher scores indicates more pain sites
(J1N) Unsteady gait	Problem present in last 7 days; Resident appears unbalanced, uncoordinated, jerking movements, careless movements, slow gait, shuffling steps or wide-based gait with halting steps
Affect
(E1L) Sad facial expressions	Sad, pained, worried facial expressions, ie furrowed brows
(E1M) Crying	Indicator of distress. Behavior is recorded by frequency in the last 30 days irrespective of the cause of the behavior (indicator)
(E3) Change in mood	Refers to status of any symptoms described in section E (mood); snapshot of current observation period, not just a point in time
(E1A) Negative statements	Resident made negative statements, eg, “Nothing matters, would rather be dead, what’s the use, regrets having lived so long”
Behavioral
(E1C) Repetitive verbalizations	Calling out for help, repeated statements
(E4DA) Inappropriate behavior frequency	Disruptive sounds, noisiness, screaming, self-abuse acts, sexual behavior or disrobing in public, smeared/threw feces, hoarding, rummaging through other’s belongings
(E1N) Repetitive physical movements	Pacing, hand wringing, restlessness, fidgeting, picking
(E4CA) Physically abusive frequency	Others are hit, shoved, scratched, sexually abused
Cognition	Grouping variable of the comparative models; cognitive performance algorithm scale 0 = Intact 1 = Mild 2 = Moderate 3 = Severe

Table 8 Correlation matrix of the indicators of pain

Indicators	1	2	3	4	5	6	7	8	9	10	11	12
1. Sad facial expressions	1.000
2. Crying	0.339	1.0
3. Change in mood	0.167	0.131	1.0
4. Negative statements	0.199	0.150	0.115	1.0
5. Repetitive verbalizations	0.213	0.154	0.086	0.153	1.0
6. Inappropriate behavior	0.151	0.114	0.064	0.086	0.316	1.0
7. Repetitive physical movements	0.254	0.145	0.092	0.059	0.239	0.292	1.0
8. Physically abusive	0.109	0.074	0.045	0.062	0.124	0.281	0.188	1.0
9. Unsteady gait	0.054	0.024	0.036	0.031	0.014	0.021	0.057	0.031	1.0
10. Pain frequency	0.090	0.073	0.060	0.067	0.032	−0.025	−0.027	−0.042	0.075	1.0
11. Pain intensity	0.095	0.079	0.063	0.068	0.035	−0.026	−0.026	−0.042	0.073	0.977	1.0
12. Cumulative pain site score	0.095	0.078	0.061	0.072	0.035	−0.024	−0.025	−0.042	0.082	0.965	0.964	1.0

Note: All correlation coefficients are significant at the 0.01 level (one-tailed).

Figure 3 Preliminary indicators in model.

Table 9 Final model factor loadings

	Est	SE	CR	P	Label
Pain
(Cum) pain site 2001	1.000
(J2B) Pain intensity	1.024	0.030	34.198	***	i
(J2A) Pain frequency	0.879	0.026	33.856	***	h
(E1A) Neg state	0.373	0.022	16.645	***	g
(E3) Mood change	0.808	0.051	15.860	***	f
(E1M) Crying	0.951	0.056	17.117	***	e
(E1L) Worried face	2.718	0.152	17.913	***	d
(E1C) Repeat verb	2.137	0.117	18.289	***	c
(E1N) Repeat moves	2.216	0.121	18.277	***	b
(E4DA) Dis behavior	2.961	0.160	18.532	***	a

Note:

*** Significantly different from zero at the 0.001 level (two-tailed).

Abbreviations: CR, critical ratio; SE, standard error.

Figure 4 Final model.

Table 10 Goodness of fit statistics for the measurement models

Goodness of fit statistics	Stacked original model	Stacked revised model
χ^2	30589.3	4933.4
Degrees of freedom (df)	249	143
P	0.000	0.000
Number of free parameters	63	77
χ^2/df	122.849	34.45
RMR	0.024	0.011
GFI	0.887	0.981
TLI	0.820	0.965
AGFI	0.859	0.970
RMSEA	0.048	0.025
Hoelter (0.05)	500	1850

Abbreviations: AGFI, Adjusted Goodness of Fit Index; RMR, Root Mean Square Residual; GFI, Goodness of Fit Index; TLI, Tucker-Lewis Index.

Table 11 Goodness of fit statistical terms

Goodness of fit statistics	Terms and understanding statistical output
χ^2 (chi-square)	Best for models with sample sizes between 75–100; for n > 100 chi-square is almost always significant since the magnitude is affected by the sample size; also affected by the size of correlations in the model, the larger the correlations the poorer the fit
Degrees of freedom (df)	The number of degrees of freedom and equals p-q (the # of sample moments subtract the # of parameters estimated)
P	The probability is ideally non-significant; however, significant models can still yield valuable theoretical construct information
Number of free parameters	Multiple times 5–10 to estimate required sample size for the study
χ^2/df	Use to compare models; this number should decrease from model to model; <5 is good, but must have P > 0.05; close to 1.0 means it is a correct model
RMR	Root mean square residual is the square root of the average amount that the sample variances and covariances differ from their estimates, smaller values are better
GFI (also GOF)	Slightly less than or equal (0–1) to 1 indicates a perfect fit; acceptable values are above 0.90; affected by sample size and can be large for poorly specified models
TLI	The Tucker-Lewis coefficient should be between 0–1, values close to 1 indicate a very good fit
AGFI (also AGOF)	Adjusted goodness of fit index, takes into account the df available for testing the model; AGFI is bound by 1, which indicates a perfect fit; however is not bound by 0
RMSEA	Should be less than 0.05; score of less than 0.05 indicates a close fit of the model in relation to the df. Not definitive but the rule of thumb is an RMSEA of 0.01 is an exact fit, a score of 0.08 or less indicates a reasonable error of approximation. A model with an RMSEA of greater than 0.1 should not be used – indicates a poor fit
Hoelter (0.05)	The largest sample size for which one would accept the hypothesis that the model is correct; the index should only be calculated if the chi-square is statistically significant. How small one’s sample size would have to be for chi-square to no longer be significant. Hoelter recommends values of at least 200, values ≤75 indicate a poor fit

Abbreviations: AGFI, adjusted goodness of fit index; AGOF, adjusted goodness of fit; GFI, goodness of fit index; GOF, goodness of fit; RMR, root mean square residual; RMSEA, root mean square error of approximation; TLI, tucker-lewis index.

Figure 5 Measurement models by cognitive status with correlations and shared error.

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