The PANAS positive data was analysed using a mixed-measures ANOVA, with a within-subjects factor of time (each of the 14 days) and between-subject factor of group (condition and control) (see Figure 6.11). Mauchly’s test indicated that the assumption of sphericity had been met. The main effect of time was not significant, F(13,728) = 1.17, p=.300, η2= .020. However, the main effect of group was significant, F(1, 56) = 47.13, p<.001, η2= .457. The interaction of time and group was also significant where, F(13, 728) = 3.28, p < .001, η2= .0.55.
.00 .04 .08 .12 .16
Baseline Week One Week Two
Treatment Control 0. 4.5 9. 13.5 18. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Condition Control
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Figure 6.11 Mean positive PANAS scores per day. N=58.
The PANAS negative data was analysed using a mixed-measures ANOVA, with a within- subjects factor of time (each of the 14 days) and between-subject factor of group (condition and control) (see Figure 6.11). Mauchly’s test indicated that the assumption of sphericity had been met. The main effect of time was significant, F(13,728) = 2.78, p<.01, η2= .047. The main effect of group was also significant where, F(1, 56) = 10.47, p<.01, η2= .157. The interaction of time and group significant where, F(13, 728) = 5.37, p < .001, η2= .087.
Figure 6.12 Mean negative PANAS scores per day. N=58.
0. 3.75 7.5 11.25 15. 18.75 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Condition Control
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6.4 Discussion
The UoR:C was created to test whether a community sample, trained to reduce and prevent catastrophising, would experience reduced levels of catastrophising, increased mood and less distress than a control group. The interaction between time and group established the effectiveness of the treatment between groups and over time. There was a significant interaction between groups and over time for total catastrophizing scores. The post-hoc tests for CQ total scores demonstrated a significant difference between groups at week two. These results support the first hypothesis, that the application would reduce the rate of catastrophising. Once the CQ was broken down into its two subscales, the General Catastrophising subscale retained a significant interaction. However, the Health and Safety subscale did not. This difference validates the original distinction made between subscales in Chapter Five. It also suggests that the application targeted General Catastrophising.
As the first hypothesis was confirmed (the UoR:C would significantly reduce catastrophising), further analysis into distress and mood was conducted. The interactions for each subscale (depression, anxiety and stress) were significant. However, the post-hoc tests at week 2 were only significant for depression and stress, not anxiety. These results indicate that training individuals in ways to dealing with catastrophising reduced general distress. Causality can be strongly indicated but not explicitly proven by self-reported scores that do not perfectly represent ‘true’ values. However, the results suggest that the application did cause a general reduction in depression, anxiety and stress scores as predicted. A measurable impact of the application at week two for depression and stress but anxiety was not expected. As there was a significant interaction for all three subscales, it would appear that the application had a smaller impact on anxiety scores. However, at this stage it is not possible to decipher if this is due to peculiarities in the sample, specificity of the application or a feature in the relationship
181 between anxiety, depression and stress concerning catastrophising. To ensure that this non- significance is worth consideration, it should first be replicated by a future study.
The third hypothesis, that the intervention would increase positive mood and decrease negative mood was upheld. Interestingly, the between group main effect for positive mood is very pronounced. However, for negative mood, participants in the condition only narrowly outperformed their control counterparts. Additionally, positive mood appears to be considerably more stable over time than negative mood. This suggests that the effect for positive mood will be easier to replicate and more indicative of a true effect. In the Broaden and Build Theory proposed by Fredrickson (2004) negative emotions are specific action tendencies, as they prime specific behaviours (e.g. escape, expel or attack). In threatening situations, these specific action tendencies narrow thought-action repertoires to promote quick and decisive action. Therefore, negative emotions are reactionary and specific. However, positive emotions rarely occur in threatening situations, which means that positive emotions do not need to narrow an individual’s thought-action repertoire for quick and decisive action. Instead positive emotions increase an individual’s thought-action repertoire, such as encouraging play and curiosity. The consequence of this is that positive emotions frequently build upon one another, whereas negative emotions are more situation specific. This effect is one possible explanation of the highly variable daily negative emotion, compared to the relatively stable positive emotion scores.
6.4.1 Limitations
While this study sought to develop upon previous interventions developed as mobile applications, it is not without limitations. One such limitation is the absence of data on how frequently individuals accessed the application. This includes, which aspects were most frequently accessed. While this is unlikely to invalidate the results of the study, it is likely to be its largest weakness for two reasons. Firstly, beyond completing questionnaires, it is unknown
182 whether participants read or applied any of the information or tasks provided. This may have had a dampening effect on the strength of the findings, particularly in distinguishing between groups. As undergraduates, completing the application for course credit, may have sought to do the minimum. However, it is equally likely that as participants knew the application was collecting data, they engaged with the application to ensure course credit. This problem cannot be answered, except that in future studies some measure of use would prevent it occurring again. This also reveals the potential of technology, if fully exploited.
A second issue to arise is if the application was engaged in constructively, there is no record of what aspects individuals found most helpful. The application was designed to measure this as part of the exit questionnaire. But due to technical limitations these questions did not appear, and this did not come to the attention of the experimenter until the completion of the study. As a consequence, it is difficult to bring these results back to the wider literature in regards of what is the best way to tackle catastrophising. This application drew various aspects from a variety of interventions and theories. But without self-report measures on what was useful (and not useful) it is not possible to relate the findings to specific literature. However, this did not undermine the main aim, which was a test of whether catastrophising training is beneficial.
The sample of the study was confined in two ways. The majority of participants that completed the study were undergraduates and the application was limited to Apple devices. As shown in Chapter Two, the undergraduate population demonstrated abnormally high levels of depression. Secondly, Apple users tend to represent higher socioeconomic status. For example, during December 2013 Android users spent an average of $48.10 per order compared to $93.94 by Apple users (Yarow, 2013). The sample for this experiment was restricted to Apple users due to time constraints. This is because Android applications have no standardisation (such as screen size) and consequently require more testing. However, a
183 future study could build on this application and include Android and Windows users as well. A simpler method of widening the sample would be to allow considerably more time for the experiment to be downloaded by a greater number of the public until they form a pre- specified proportion of the sample.
Another restriction imposed by the design of this study is the absence of any measure of long-term change for the participants. It is impossible to determine if the improvements demonstrated by the condition group are enduring. As the concept, has now been tested, future studies could simply prompt users (who still have the application installed) after one and then six months to complete the DASS and CQ measures. Based on the findings of the current study it could be predicted that after one month and six months the effects will be maintained but somewhat reduced over time. However, there is likely to be a high dropout rate, based upon the rate within the sample and from users uninstalling the application.
While the aim of this experiment was to test the potential of catastrophising in a therapeutic setting, it is also testing the potential effectiveness of application-based treatment. This study intended to develop upon the weaknesses of previous application based interventions. Potentially, these lessons facilitated UoR:C’s effectiveness. And in reflection I make some key recommendations, which could further benefit future therapeutic interventions. Applications are unlike standard psychological experiments or psychological interventions. As with almost all psychology experiments UoR:C was designed from a
psychology first perspective, where the concept was developed and the technology followed it
like a script. This one-way influence had two repercussions. Firstly, the programming lacked ambition, as it was simply following a pre-set structure. However, if the technological aspect was explored for its own sake, and allowed to build upon the theory, its potential would drastically increase. Secondly, in a psychology first perspective the implication is that one is designed followed by the other. This results in poor project management issues never
184 normally encountered or considered in developing psychological tools. These include a variety technical issues that were not foreseen and a lack of product testing due to the mind-set of following a concrete programming script. Both results in delays and a less effective product. Any application based psychological intervention should have their theory and programing developed in tandem. From a software industry perspective, this would be using an agile project management style, where the application is gradually developed and continuously tested over different phases (alpha, beta and release). This flexibility should never compromise psychological validity, but focus on exploiting it.