Programa de Movilización de los Recursos Forestales (2014-2022)

The hypothesis was that higher CAT would predict higher pain self-report ratings and lower observed pain tolerance. For self-report, outcome variables were maximum pain intensity and maximum pain unpleasantness from the pre-intervention pain tasks; these two variables were tested with a MANCOVA approach. Using a multivariate approach takes into account the expected correlation between the intensity rating and

unpleasantness rating each individual gave for a given pain task, allowing for a more reliable test of a variable‘s predictive utility on the entire set of outcomes (i.e., the omnibus test) before additional exploration of its association with individual outcome variables through univariate tests. For pain tolerance, a single outcome variable, time elapsed in the task, was used in a survival analysis approach. This approach was necessary given the nature of the outcome variable; because the amount of time before quitting for a participant who tolerated the full task only is known to be greater than 3 minutes, the variable is ―right censored,‖ potentially leading to erroneous conclusions if an individual‘s pain tolerance is said to be only the 180 seconds that were observed.

59

Analyses were conducted on the pre-intervention pain tasks (pressure 1 and 2, cold pressor 1) given the expected influence of intervention on pain report.

Self-reported pain. Results of the MANCOVA are summarized in Tables 10 and 11. Omnibus tests evaluated whether variables significantly predict self-reported pain

outcomes (intensity and unpleasantness) as a set. The MANCOVA, which included all of the above predictors, accounted for 54%-56% of the total variance in intensity and unpleasantness for pressure tasks 1 and 2 and 38-43% of the variance in intensity and unpleasantness for cold pressor task 1. The omnibus tests indicated that, when all predictors were included in the model, only CAT-VAS slope (all p < .0001) and CAT- VAS intercept (all p < .05) significantly predicted subjective pain report; no other predictors returned statistically significant results. In all cases, the estimated regression coefficients for CAT-VAS slope and intercept were positive, indicating that higher levels of CAT as determined by the CAT-VAS were associated with higher pain self-report.

Observed pain tolerance. To determine the predictive value of CAT-VAS slope and intercept for determining how much time would elapse before a participant would terminate the pre-intervention pain tasks, survival analyses were conducted in SAS using PROC LIFEREG. The approach used, an accelerated time to failure model, aims to estimate the likelihood of a participant‘s terminating the task at a given time point by fitting the log of failure times into a parametric regression model using an iterative, maximum likelihood estimation approach. The regression coefficients generated by PROC LIFEREG indicate whether the time to failure is accelerated or decelerated by the predictor variable; positive coefficients indicate that positive values on the variable are associated with longer times before failure, whereas negative values indicate that higher

60

values of the predictor are associated with shorter times before failure. In other words, these values can be interpreted in the same way as conventional multiple regression coefficients for predictors.

For example, the model constructed to test for differences in failure times using CAT- VAS slopes, CAT-VAS intercepts and male gender as predictors of failure time on a pain task would be:

log(Time To Failure) = β1(CAT-VAS Slope) + β2(CAT-VAS Intercept) + β3(Male) + ε Inspection of the observed frequency distributions of time elapsed (e.g., Figure 3) suggested that the likelihood of terminating a pain task varied over time; for example, for pre-intervention cold pressor pain, participants appeared to be most likely to quit the task within the first 10 to 60 seconds of the task and much less likely after that point. Thus, when possible, a generalized gamma distribution was used to estimate the underlying probability distribution function (odds at any time that a participant would quit), in an effort to avoid the assumption that the likelihood of participants quitting was always increasing or decreasing. Inspection of fit statistics (e.g., -2 log likelihood and AIC) indicated that using a generalized gamma distribution provided the best fit to the data for cold tasks. However, because the failure rate for pressure tasks was generally very low (a maximum of 16% of participants asked to stop or removed their hand for any pressure pain task), a solution frequently could not be estimated for pressure tasks using the generalized gamma distribution. This difficulty necessitated some restriction of the model, namely that some aspects of the shape of the underlying probability distribution would be assumed rather than estimated from the data, to reach a solution. Thus, for

61

pressure tasks, a Weibull probability distribution function (i.e., a specific case of the gamma distribution) was assumed.

For all three pre-intervention pain tasks, when entered as the sole predictor, higher CAT-VAS slopes predicted significantly shorter times before quitting the pain task at hand (pressure 1: β = -8.08, X2_{(1) = 13.19, p = .0003; pressure 2: β = -2.97, X}2

(1) = 54.22, p < .0001; cold 1: β = -4.02, X2

(1) = 49.32, p < .0001). Similarly, higher CAT- VAS intercepts were associated with significantly shorter times before termination of the task (pressure 1: β = -0.508, X2_{(1) = 4.66, p = .0308; pressure 2: β = -0.04, X}2

(1) = 6.25, p = .0124; cold 1: β = -0.02, X2

(1) = 28.57, p < .0001). However, tests of the interaction between CAT-VAS slope and intercept did not significantly predict pain tolerance for any of the three pre-intervention pain tasks.

When gender and race were included as covariates, higher CAT-VAS slope remained a significant predictor of lower pain tolerance for all three pre-intervention pain tasks (pressure 1: β = -2.79, X2_{(1) = 16.07, p < .0001; pressure 2: β = -4.32, X}2

(1) = 46.06, p < .0001; cold 1: β = -4.32, X2

(1) = 63.65, p < .0001). CAT-VAS intercept again had a similar negative association with pain tolerance times, but this association was not statistically significant for pressure task 2 (pressure 1: β = -0.03, X2

(1) = 4.70, p = .0302; pressure 2: β = -0.01, X2_{(1) = 1.55, p = .2139; cold 1: β = -0.04, X}2

(1) = 26.79, p < .0001). Race significantly predicted pain tolerance only for cold pressor 1, with White participants showing higher pain tolerance than other groups (β = 0.59, X2

(1) = 7.04, p = .0080). Gender did not predict pain tolerance for any pre-intervention pain task.