Capítulo 3 Materiales y métodos
3.3 Validación de datos y depuración de la información
This experiment tested a potential mechanism mediating negative mood and increased worrying (Buhr & Dugas, 2009; Johnston & Davey, 1997; Startup & Davey, 2001). Experimentally-induced negative mood significantly increased scores on a composite systematic processing facilitator measure, and the endorsement of accountability. However, negative mood did not affect responsibility, desire for control or NFC, although the composite systematic processing facilitator measure (encompassing all four cognitive appraisals) better predicted worry levels than the individual cognitive appraisal ratings. Negative mood positively correlated with NFC, despite no between-group differences being identified. Additionally, negative mood increased (1) the endorsement of deploying AMA stop rules for worrying, and (2) scores on a validated measure of worrying (PSWQ). The CI scores showed a trend that was consistent with the prediction that negative mood would facilitate behavioural worry measures, and negative mood significantly positively correlated with the number of catastrophising steps that an individual generated. The experiment utilized a control condition for priming which indicated that the negative mood effects could not be accounted for simply by priming. Meditational analyses confirmed that the composite systematic processing facilitator measure and AMA stop rule deployment fully mediate negative mood and increased worrying.
These findings confirm the prediction that negative mood facilitates the endorsement of cognitive appraisals that increase sufficiency thresholds and trigger the systematic processing of information, and this analysis suggests a mechanism by which negative mood causes increases in worrying. Many negative moods are known to facilitate the use of an analytic processing style (Ambady & Gray, 2002), especially those associated with uncertainty, not understanding what is happening, and feeling unsure about what will happen
next (Tiedens & Linton, 2001). In this experiment, the negative mood vignette significantly increased sadness (associated with uncertainty) and decreased happiness (associated with certainty), circumstances which facilitate systematic processing (Bodenhausen, et al., 1994). This provides an empirical rationale for predicting that negative mood influences worrying through its effect on systematic processing.
It is interesting to note that in terms of the individual cognitive appraisals only the accountability measure was significantly different between the mood groups. Examination of what these appraisals measure suggests that the need to justify one’s worries (accountability) may be much more heavily implicated in appraising worry, as is seen in the psychopathology- relevant Type 2 worry (see Wells, 1995). This provides further support to the notion that negative mood states can increase perseverative pathological worrying. As reported in the literature on heuristic and systematic processing literature (Chen, et al., 1996; Erb, et al., 2007; Livingston & Sinclair, 2008; Tetlock, 1983; Tetlock & Boettger, 1989) when individuals feel high levels of accountability, they feel a greater need to process their thoughts in great detail, possess higher sufficiency thresholds, and are more likely to deploy systematic processing. Thus, the accountability measure may reflect appraisals associated with Type 2 worry; the other VAS measures may better reflect Type 1 worry appraisals. While a greater endorsement of a negative mood was associated with significantly higher self-reported NFC, there were no significant between-group differences. This may reflect that NFC is typically considered a dispositional characteristic (e.g. Cacioppo, et al., 1986), and may be less affected by short-term experimental manipulations.
The relationship between negative mood and PSWQ scores was also mediated by intention to use AMA stop rules. This was independent of the mediating effect of systematic processing appraisals as both represented independent sources of PSWQ variance. This may reflect a separate effect of negative mood inducing higher performance standards (Scott & Cervone, 2002), causing individuals to become relatively dissatisfied with any given level of performance (Cervone, et al., 1994). This may lead to deployment of AMA stop rules (‘I must continue with the task till I am sure I have met all my specific goals for the task’) rather than ‘feel like continuing’ (FLC) stop rules (‘I will continue with the task until I no longer feel like doing it any more’). One interpretation is that the sufficiency threshold measure indicates the extent that appraisals are triggering systematic processing through a raised processing threshold, whereas AMA deployment represents a more generic measure of an individual’s
goals for their worrying (e.g., ‘I must worry until I have resolved this problem/feel less anxious’). To some extent these two factors are inter-related, in that systematic processing may be necessary to achieve stringently-defined goals for worrying, but systematic processing is a means to an end and not an end in itself, so the deployment of stop rules will inevitably be affected by a wider range of variables than those that trigger systematic processing.
However, as shown by the alternative mediation models, this is not the only model consistent with the data obtained. Worry also mediated the relationship between negative mood and the AMA stop rule. Worrying may lead to the deployment of the AMA rule, as the task is rationalized to be problematic, and therefore a large amount of cognitive expenditure is warranted. However, mediation models cannot test causation, and therefore the statistical significance of the indirect effects of these alternative models is not evidence in itself that the directional relationship exists (Preacher & Hayes, 2004). The alternative models need to be examined in future experiments that involve experimental manipulations. However, while evidence exists demonstrating a causal effect of AMA stop rules on worrying (Davey, 2006b; Davey, et al., 2005; Startup & Davey, 2001), there is no evidence indicative of a causal effect of worrying on AMA stop rule deployment. Indeed, evidence indicates the opposite effect: as worry persists, worriers turn to deploying FLC rather than AMA stop rules (Davey, Eldridge, Drost, & MacDonald, 2007), supporting the first mediation model over the second, and guiding the predictions of future studies. Furthermore, the experimental procedure involved measuring AMA deployment and the sufficiency threshold, before measuring worry levels, and as such these proposed mediators were activated prior to measuring worry. Additionally, the alternative mediation model, with worry as the mediator and AMA stop rule use as the outcome variable, only indicated partial mediation, compared with full mediation when AMA stop rule use and the composite systematic processing facilitator measure were included as mediators between negative mood and worry.
One potential limitation is that no direct measure of systematic processing was used in the present experiment, and there was a reliance on self-report measures. This is perhaps not surprising because – to the authors’ knowledge – there is currently no validated measure of systematic processing as such (see Chapter 3 for a discussion of measures of systematic processing). This issue is addressed in the General Discussion (see Chapter 9).
Although two worry measures were utilized, only the questionnaire measure (PSWQ) exhibited a significant between-group mood effect. The PSWQ is typically considered a trait
measure but is used frequently in clinical research contexts to demonstrate changes in self- perceived levels of worry (Borkovec & Costello, 1993; Goldman, et al., 2007; Treanor, et al., 2011). These results, somewhat surprisingly, indicate that short-term laboratory manipulations, such as mood inductions, can affect participants’ responses to supposedly trait measures. Metacognitive theory proposes that appraising worry levels as problematic is a key component of GAD (Type 2 worry, Wells, 1995), and this memory and appraisal bias for worry frequency may act as a mechanism for the onset of Type 2 worry/meta-worry. The behavioural measure (CI steps) showed trends in the predicted directions, with a significant positive correlation obtained between negative mood and CI steps. But differences in the number of CI steps across mood induction groups failed to reach statistical significance. This is probably due to the temporal distance between the mood induction and the CI, which was greater than in previous studies (e.g. Johnston & Davey, 1997). This result does not dispute that negative mood facilitates worrying, which has now been reported in a series of studies (Buhr & Dugas, 2009; Johnston & Davey, 1997; Startup & Davey, 2001), but emphasizes the importance of utilizing a range of worry measures in future studies to allow a more thorough analysis of the factors mediating causal variables and subsequent worrying.