General Psychiatric Symptomatology, Mindfulness and Meditation Practice
as Predictors of the Effectiveness of a Mindfulness-Based Mobile
Application
Masterthesis M.D. van der Wel Student number: 10190066
Supervisor: A. A. P. van Emmerik Date: 14 – 03 – 2017
University of Amsterdam
Faculty of Social and Behavioural Sciences Psychology department
1 Index Page Abstract 2 Introduction 3 Methodology 9 Results 13 Discussion 15 References 18
2
Abstract
Interventions based on mindfulness are becoming increasingly popular, which is reflected by an increasing amount of mobile applications claiming to promote mindfulness. Although not many of these apps have been tested for effectiveness, Van Emmerik, Berings and Lancee (under review) showed the beneficial effect of such an app (the VGZ Mindfulness Coach) on mindfulness in a randomised waitlist-controlled trial. In this study, a secondary analysis was conducted to investigate the baseline levels of general psychiatric symptomatology and mindfulness and the current practice of (mindfulness) meditation as possible predictors of (1) the effect of the app on mindfulness and (2) dropout. The 191 participants in the experimental condition were offered to use the VGZ Mindfulness Coach, an app that includes 40 different mindfulness exercises without any therapeutic guidance. Eighty participants (41.9%) completed the post-test measurements and 111 participants (58.1%) dropped out of the study. The baseline levels of general psychiatric symptomatology and mindfulness and the current practice of (mindfulness) meditation did not predict the effect of the app on mindfulness nor the dropout rate. It was concluded that an app such as the VGZ Mindfulness Coach has the potential to train mindfulness in a broad non-clinical population, regardless of the levels of general psychiatric symptomatology or mindfulness or the current (mindfulness) meditation practice of the user.
3
Introduction
Originally the core of Buddhist meditation practices in the East, mindfulness has made its way to the West (Kabat-Zinn, 2003). Mindfulness-based interventions (MBIs) are growing in popularity in the clinical field as well as the field of research. Since Jon Kabat-Zinn demonstrated the beneficial effects of an MBI called the “Stress Reduction and Relaxation Program” on the psychological well-being and experience of pain of a group of chronic pain patients (1982), the amount of research on MBIs has grown exponentially (Segal, Teasdale, & Williams, 2013).
Mindfulness refers to an awareness that emerges through purposefully and non-judgmentally paying attention to the present moment (Kabat-Zinn, 2003). Examples of techniques used to train mindfulness in MBIs include meditation, visualisation and hatha yoga (Baer, 2003). MBIs seem to be effective in increasing mindfulness in various studies. Khoury, Sharma, Rush, and Fournier (2015) and Eberth and Sedlmeier (2012) showed moderate effect sizes of g = 0.60 and r = 0.34, respectively, for increases in mindfulness after an MBI.
MBIs have also been shown to have a significant beneficial effect on mental as well as physical health. Reductions in stress, anxiety, and depression have been found, as well as increases in quality of life and positive affect (Baer, 2003; Bohlmeijer, Prenger, Taal, & Cuijpers, 2010; Carmody & Baer, 2008; Eberth & Sedlmeier, 2012; Hofmann, Sawyer, Witt, & Oh, 2010; Khoury et al., 2013; Khoury et al., 2015). Although not every review shows similarly promising results (Toneatto & Nguyen, 2007), these findings seem quite robust for clinical as well as non-clinical samples. Proposed mechanisms underlying the effects of MBIs include changes in cognitive and emotional reactivity, self-compassion, rumination, worry, body awareness and, predictably, mindfulness (Gu, Strauss, Bond, & Cavanagh, 2015; Hölzel et al., 2011). Furthermore, Carmody and Baer (2008) showed that the time spent on home practice of formal mindfulness exercises, such as the body scan and sitting meditation, is
4 positively related to the extent of improvement in mindfulness and psychological functioning after an MBI.
Interestingly, Hofmann and colleagues (2010) showed in a meta-analysis that some of the effects of MBIs are particularly large in certain clinical populations. Specifically, they found that MBIs were associated with large effect sizes for anxiety (g = 0.97) and depression (g = 0.95) in patient samples, while effect sizes for anxiety and depression were smaller in the general population (g = 0.63 and g = 0.59, respectively). An explanation for this could lie in the mechanisms underlying the effect of MBIs, as depression is characterized by rumination and feelings of worthlessness, and anxiety by worry and emotional reactivity in general (Comer, 2011). If the effectivity of MBIs is partially explained by these mechanisms, they actually target what people with depression and anxiety are dealing with, potentially leading to higher outcomes in patient samples. Alternatively, this finding might be due to a floor effect, i.e., participants with a higher level of anxiety or depression at baseline have more room for improvement than participants with lower levels.
Most MBIs are delivered face-to-face by an experienced instructor or therapist who practices mindfulness him- or herself (Kabat-Zinn, 2003). However, not enough instructors are available to meet the increasing demand in a number of countries (Crane et al., 2012). In addition to that, MBIs are – at least in the Netherlands – usually not covered by health insurance plans. The emergence of mobile health technology (m-health) may help to overcome this by providing smartphone- or tablet-based MBIs. Such applications (or hereafter: ‘apps’) that are designed to train mindfulness are potentially cost-effective, flexible, and easily accessible for large numbers of people – patients and non-patients alike.
Over the past few years, MBIs have indeed become popular in m-health and e-health (i.e. online interventions). Although not many of these interventions have been researched to investigate their effectiveness, preliminary results of a meta-analysis on the effectiveness of
e-5 health MBIs show reductions in stress, anxiety, and depression and increases in mindfulness (Fish, Brimson, & Lynch, 2016). Recently, the development of these interventions seems to be directed more and more towards m-health, with more than 200 apps related to mindfulness available for Google Android smartphones alone (Plaza, Demarzo, Herrera-Mercadal, & Garcia-Campayo, 2013). Only two of these apps have been researched to investigate their effectiveness, showing promising results confirming the potential of MBI apps to increase mental health (Ly et al., 2014; Howells, Itzvan, & Eiroa-Orosa, 2014).
Van Emmerik, Berings and Lancee (under review) also investigated the effects of an MBI app (the VGZ Mindfulness Coach, see Operationalisation) in a randomised waitlist-controlled trial. They found that, compared to a waitlist control group, the app was effective in increasing mindfulness (d = 0.77). Furthermore, they found that the app significantly reduced general psychiatric symptoms (d = -0.68) and significantly increased psychological, social, and environmental quality of life (d = 0.38, d = 0.38 and d = 0.36, respectively). Although the study sample had rather high scores for general psychiatric symptomatology at baseline, the presence of such symptoms was not an inclusion criterion and the sample was essentially non-clinical.
Now that the effectiveness of the VGZ Mindfulness Coach has been demonstrated in a non-clinical population, a useful next step is to obtain a more fine-grained picture of the app’s effectiveness in specific sub-populations. For this purpose, two possible predictors of the effectiveness of the app were investigated in this study. First, study populations are often labelled as clinical or non-clinical, but underlying such dichotomous labels is the severity of general psychiatric symptomatology as a continuous variable. One possibility is therefore that even in ‘non-clinical’ populations, the effectiveness of apps such as the VGZ Mindfulness Coach is related to the general psychiatric symptomatology of its users. Face-to-face MBIs have been shown to be effective in increasing mindfulness and psychological well-being in
6 clinical as well as non-clinical samples (Carmody & Baer, 2008; Eberth & Sedlmeier, 2012; Khoury et al., 2013; Khoury et al., 2015; Sedlmeier et al., 2012), with notably higher decreases in depression and anxiety in clinical samples than in non-clinical samples (Hofmann et al., 2010). This study investigated whether general psychiatric symptomatology predicted the effectiveness of an MBI app in increasing mindfulness. In addition, it was investigated if general psychiatric symptomatology predicts dropout.
A second possible predictor of the effectiveness of MBI apps is the level of mindfulness and whether the user is currently practicing mindfulness or other forms of meditation. In a study on the effects of a face-to-face MBI in a non-clinical sample, Shapiro, Brown, Thoresen, and Plante (2011) found that participants with higher levels of mindfulness showed a larger increase in mindfulness and subjective wellbeing. They theorised that participants with higher levels of mindfulness might find the exercises easier than people with lower levels of mindfulness, and therefore would practice more and longer. Carmody and Baer (2008), however, found no relationship between the level of mindfulness at baseline and the extent of home practice with a face-to-face MBI in a semi-clinical sample. The question therefore remains if current practice of mindfulness or other forms of meditation predicts dropout and the effectiveness of an MBI app in increasing mindfulness. Furthermore, as an exploratory analysis, we investigated the relationship between the frequency of use of the VGZ Mindfulness Coach and the baseline level of mindfulness and the association between the frequency of use of the app and current practice of (mindfulness) meditation.
These research questions may inform the optimal dissemination of MBI apps in sub-populations that vary in the presence and severity of psychiatric symptomatology, level of mindfulness and current practice of (mindfulness) meditation. To answer the first question, it was investigated if baseline general psychiatric symptomatology predicts (1) the effect of the app on mindfulness, and (2) dropout. Regarding the effect of the app on mindfulness, no
7 hypothesis was established because the predictive value of baseline general psychiatric symptomatology could go both ways. On the one hand, face to face MBIs have been shown to have a larger effect on decreasing anxiety and depression in a clinical sample compared to a non-clinical sample (Hofmann et al., 2010) and higher mindfulness has been shown to be related to lower general psychiatric symptomatology (Brown & Ryan, 2003; Khoury et al., 2015). This would suggest that people with high levels of general psychiatric symptomatology have lower levels of mindfulness, and therefore more room for improvement in mindfulness. On the other hand, one could argue that a higher level of general psychiatric symptomatology interferes with the development of mindfulness skills, especially since users of the app receive no therapist guidance. While practicing mindfulness, one observes whatever comes to mind, including unpleasant experiences such as emotional turbulence and stress (Kabat-Zinn, 2003). Users with higher levels of general psychiatric symptomatology might come across more unpleasant feelings, which could impede the development of mindfulness skills.
Regarding the relationship between baseline psychiatric symptomatology and dropout, no hypothesis was formulated either. Cavanagh and colleagues (2013) and Glück and Maercker (2011) found no predictive value of baseline distress, anxiety and depression for dropout in their studies of e-health MBIs. However, both of these studies had very small sample sizes and only two weeks between the baseline and post-test measurements, which might have given the participants less time or reason to quit using the MBI. One could also argue that higher general psychiatric symptomatology predicts higher dropout rates. Crane and Williams (2010) showed that participants with a history of depression were more likely to drop out of a face-to-face MBI when they had high levels of depressive rumination, brooding and increased reactivity to sad mood. Added to this is again the fact that there is no guidance from a therapist while using the VGZ Mindfulness Coach, possibly posing a bigger challenge
8 for people with higher levels of general psychiatric symptomatology in practising mindfulness and persisting use of the app.
In sum, we expected that baseline general psychiatric symptomatology would predict the effect of the app on mindfulness and dropout. However, no a priori hypotheses were established regarding the direction of these relationships, given the different possibilities outlined above.
Second, to investigate if the app is differentially effective for people with higher baseline levels of mindfulness or for people who are currently practicing mindfulness or other forms of meditation, it was investigated if (1) current practice of (mindfulness) meditation predicted the effect of the app on mindfulness and (2) baseline mindfulness and current practice of (mindfulness) meditation predicted dropout rates. As noted earlier, participants with higher levels of mindfulness at baseline in a non-clinical sample showed a larger increase in mindfulness after a face-to-face MBI (Shapiro et al., 2011), but no relationship between baseline mindfulness and home practice time was found in a semi-clinical sample (Carmody & Baer, 2008). However, the use of the VGZ Mindfulness Coach does not come with any personal guidance, in contrast to the MBI in the study by Carmody and Baer (2008). We expected that people who were already quite mindful before using the app, or who were currently practising mindfulness or other forms of meditation, would find it easier to follow the instructions of the app and practice regularly. It was therefore hypothesised that participants with higher levels of mindfulness at baseline, or who were currently practising (mindfulness) meditation, would show greater increases in mindfulness after using the app and would be less likely to drop out.
9
Methodology Participants
To investigate the possible predictors of the effectiveness of the app, a secondary analysis was conducted on the data obtained by Van Emmerik and colleagues (under review). They recruited participants by using a Facebook advertisement for the VGZ Mindfulness Coach. The advertisement was directed away from people who had already liked the VGZ Mindfulness Coach page on Facebook, to avoid the inclusion of participants who were already familiar with the app. Participants who were 18 years or older, sufficiently fluent in Dutch to use the app and complete the research procedures, and willing to provide written informed consent, were included in the study. This resulted in a total of 337 participants. The participants received no compensation.
Of the 337 participants who were included in the study, 191 (50.7%) were allocated to the experimental condition and 186 (49.3%) were allocated to the WLC condition. For the purpose of this study, only the 191 participants in the experimental condition were included in the analyses. This group consisted of 183 women (95.8%) and 8 men (4.2%). The average age of the participants in this group was 45.63 years (SD = 9.09) and ranged between 19.42 and 67.14.
Materials
Mindfulness was assessed with a Dutch version of the Five Facet Mindfulness Questionnaire (FFMQ; Baer, Smith, Hopkins, Krietemeyer, & Toney, 2006; De Bruin, Topper, Muskens, Bögels, & Kamphuis, 2012). The FFMQ consists of 39 items that are rated on a 5-point Likert scale from 1 (never or very rarely true) to 5 (very often or always true). The items reflect 5 facets of mindfulness: Observing (8 items, for example: “I remain present with sensations and feelings even when they are unpleasant or painful”), Describing (8 items, for example: “I’m good at finding the words to describe my feelings”), Acting with awareness
10 (8 items, for example: “I rush through activities without being really attentive to them”), Nonjudging (8 items, for example: “I tend to evaluate whether my perceptions are right or wrong”) and Non-reactivity (7 items, for example: “Usually when I have distressing thoughts or images, I step back and am aware of the thought or image without getting taken over by it”) In the present study, Cronbach’s α was .92 for the total scale.
General psychiatric symptomatology was assessed with a Dutch version of the General Health Questionnaire 12 (GHQ-12; Koeter & Ormel, 1991; Goldberg & Williams, 1988). The GHQ-12 consists of 12 items that are rated on a 4-point Likert scale from 1 to 4, with different answer categories tailored to each item. The items in the GHQ-12 reflect general psychiatric symptomatology and (dis)functioning (for example: “Have you recently been able
to enjoy your normal day to day activities?”). The total score ranges from 0 to 36, with higher
scores reflecting higher levels of general psychiatric symptomatology. In the present study, Cronbach’s α was .89 for the total scale.
Current practice of mindfulness meditation was assessed with the question: “Are you currently practising mindfulness meditation or other forms of mindfulness?”. Current practice of other forms of meditation was assessed with the question: “Are you currently practising any other forms of meditation?”. The items were both rated on a dichotomous scale (1 = yes and 0 = no). The frequency of use of the app was assessed with the question: “In what frequency did you use the VGZ Mindfulness Coach?”. The answer categories were rated on a 5-point Likert scale from 1 (daily) to 5 (once in a while).
Procedure
For this study, a secondary analysis was conducted of the existing data set of the study by Van Emmerik and colleagues (under review). In their study, participants were randomly assigned to the experimental or waitlist condition after providing informed consent. The study
11 measures (see Materials) were administered before randomisation (baseline), 8 weeks after baseline (post-test) and 20 weeks after baseline (follow-up).
After randomisation, participants in the experimental condition were directed to a website where they could download the VGZ Mindfulness Coach. This app offers 40 Dutch-spoken mindfulness exercises, including (but not limited to) breathing exercises, body scan exercises, attention exercises and guided meditation exercises. In addition, the app offers a five week program with 25 pre-selected exercises and background information on mindfulness and meditation. Within the 8 week interval between baseline and post-test, participants in the experimental condition could use the VGZ Mindfulness Coach. Participants were gently encouraged to complete the five-week program of the application and received a weekly automated, non-individualised e-mail to promote their use of the app. There was no form of therapist guidance. Participants in the waitlist condition were offered to use the VGZ Mindfulness Coach immediately after completion of the post-test measurements. Therefore, a follow-up test was only conducted in the experimental condition.
Statistical Analyses
Data were analysed using IBM SPSS, version 22 for Windows. Because only limited adherence data were collected, no distinction could be made between study dropouts and intervention dropouts. Participants were identified as dropouts when they did not complete the primary outcome measure (FFMQ) at post-test. All statistical tests were two-tailed.
Before performing the main analysis, the baseline total scores of the GHQ and FFMQ were checked for normality with Kolomogorov-Smirnov tests. The baseline GHQ scores were not normally distributed in the completers sample (D(80) = 0.12, p < 0.05). The data of the FFMQ were normally distributed for both completers and dropouts. Therefore, a Mann-Whitney test was used to evaluate differences in the baseline level of general psychiatric symptomatology between post-test completers and dropouts. An independent sample t-test
12 was used to evaluate differences in the baseline level of mindfulness between post-test completers and dropouts. Second, chi-squares were used to evaluate the association between current practice of mindfulness or other forms of meditation and dropout.
Third, a multiple regression analysis (enter method) was conducted to evaluate the predictive value of baseline general psychiatric symptomatology, current practice of mindfulness meditation and current practice of other forms of meditation (predictor variables) on the difference in mindfulness between baseline and post-test in the completers sample (dependent variable). Before the analysis was conducted, the difference scores of the FFMQ between baseline and post-test were calculated and the assumptions for a multiple regression analysis were checked. An analysis of standard residuals showed that the data contained no outliers (Std. Residual Min = -2.68, Std. Residual Max = 3.16). Tests to see if the data met the assumption of collinearity indicated that multicollinearity was not an issue (Baseline GHQ, Tolerance = 1.00, VIF = 1.00; Mindfulness meditation practice, Tolerance = .96, VIF = 1.05; Other meditation practice, Tolerance = .96, VIF = 1.05). Furthermore, the data met the assumption of independent errors (Durbin-Watson value = 1.57). The histogram of standardised residuals indicated that the data contained approximately normally distributed errors, as well as the normal P-P plot of standardised residuals. The scatterplot of standardised residuals showed that the data met the assumptions of homogeneity of variance and linearity. The data also met the assumption of non-zero variances.
Fourth, Pearson’s correlation was used to exploratively investigate the relationship between baseline mindfulness and the frequency of use of the app in the completers sample. Fifth, chi-squares were used to exploratively evaluate the association between current practice of mindfulness or other forms of meditation and frequency of use of the app in the completers sample.
13
Power
For this study, we wanted to have sufficient power (1 - β = 0.80) for detecting a medium effect size (f 2 = .15). Based on an independent samples T-test, this would require a sample size of at least 51 participants per group. For the independent samples T-test, the experimental condition was analysed, comparing the post-test completers (n = 80) to the dropouts (n = 111). This means that this analysis had sufficient power.
Based on a multiple regression test with three predictors, this would require a sample size of at least 77 participants (p < 0.05, two-tailed). For the multiple regression analysis, the post-test completers sample in the experimental condition (n = 80) was analysed, which means that this analysis too had sufficient power.
The expectation of a medium effect size was based on several studies. First of all, Shapiro and colleagues (2011) found that participants who had a higher level of mindfulness at baseline, showed a larger increase in mindfulness, with a large effect size of η2
= 0.21, p < .01. Furthermore, Carmody and Baer (2008) found that in a population with various psychological problems including anxiety and personal stress, the participants showed a large increase in mindfulness after an MBI, with medium to large effect sizes on the facets of the FFMQ, ranging from d = 0.47, p < .001, to d = 0.91, p < .001.
Results Dropout
Of the 191 participants that were allocated to the experimental condition, 80 (41.9%) completed the post-test measurements and 111 (58.1%) did not complete the post-test measurements. The baseline GHQ-12 scores in dropouts (Mdn = 16.00) did not differ significantly from completers (Mdn = 15.5), U = 4378.00, z = -0.17, p = .87, r = 0.01 (see Table 1 for the mean GHQ-12 scores). Furthermore, there was no significant association between current practice of mindfulness or other forms of meditation and dropout, χ2 (1) =
14 0.00, p = .99 and χ2 (1) = 1.19, p = .28, respectively. The baseline mean FFMQ scores in dropouts did not differ significantly from completers, t = -0.18, p = .86.
Table 1.
Baseline and Post-test scores for the Completers (n = 80) and Dropouts (n = 111).
Study variable Completers Dropouts
FFMQ (M [SD]) Baseline Post-test 118.60 (18.36) 133.13 (2.12) 119.10 (20.08) - GHQ (M [SD]) Baseline Post-test 16.93 (7.06) 11.20 (6.46) 16.53 (6.52) - Current mindfulness meditation (%) yes no 26.3 73.8 26.1 73.9 Current other meditation (%)
yes no 27.5 72.5 20.7 79.3
Note. FFMQ = Five Facet Mindfulness Questionnaire. GHQ = General Health Questionnaire.
Mindfulness
The multiple regression analysis showed that the three predictors, baseline general psychiatric symptomatology, current mindfulness meditation practice and current practice of other forms of meditation, explained 3,6% of the variance in the effect on mindfulness. None of the predictors significantly predicted the effect on mindfulness in the completers sample of the experimental condition (see Table 2).
15 Table 2.
Summary of the Multiple Regression Analysis for Variables Predicting the Effect on Mindfulness in the Completers Sample of the Experimental Condition (n = 80)
Variable B SE(B) β t Sig. (p)
Current mindfulness meditation -4.38 4.17 -.12 -1.05 .30 Current other meditation -1.93 4.23 -.05 -.46 .65 GHQ 0.31 0.26 .14 1.21 .23 R2 = .036, F (3, 76) = 0.99, p = .42
Note. GHQ = General Health Questionnaire.
Exploratory analyses
The baseline FFMQ scores were not significantly related to the frequency of use of the app, r = -.12, p = .26. Furthermore, there was no significant association between current practice of mindfulness or other forms of meditation and the frequency of use of the app, χ2 (3) = 1.97, p = .58 and χ2 (3) = 0.62, p = .89, respectively.
Discussion
This study had two primary aims. First, it investigated the predictive value of baseline general psychiatric symptomatology on the effectiveness of the VGZ Mindfulness Coach. Second, this study investigated the predictive value of baseline mindfulness and current practice of mindfulness or other forms of meditation on the effectiveness of the app. We first found that baseline general psychiatric symptomatology did not predict study dropout or the effect of the app on mindfulness. It seems that higher general psychiatric symptomatology does not lead to a larger increase in mindfulness, nor does it interfere with the development of mindfulness or perseverance in using the app. This is in line with the findings of Cavanagh and colleagues (2013) and Glück and Maercker (2011), who found that baseline personal distress did not predict dropout for a web-based MBI.
Second, we found that, contradictory to our expectations, nor the baseline level of mindfulness, nor current practice of (mindfulness) meditation predicted study dropout or the
16 effect of the app on mindfulness. Apparently, participants do not benefit more from an MBI app if they are already quite mindful or already practicing (mindfulness) meditation. This is not in line with what was found by Shapiro and colleagues (2011), which was that people with higher baseline levels of mindfulness benefitted more from a face-to-face MBI than people with lower levels. In the exploratory analysis, we found that there was no relationship between frequency of use of the app and the baseline level of mindfulness or current practice of (mindfulness) meditation. This might partially explain why the baseline level of mindfulness or current practice of (mindfulness) meditation did not predict the effectiveness of the app, since the time spent on practice has been shown to be related to the improvement in mindfulness after an MBI (Carmody & Baer, 2008).
Van Emmerik and colleagues (under review) found a within-group post-test effect size for mindfulness of d = 0.79, p < .001. Because research on MBI apps is still in its infancy, we cannot compare these findings directly to other, similar studies. Any comparisons that have been made must therefore be carefully interpreted. However, the results of this study suggest that MBI apps such as the VGZ Mindfulness Coach have the potential to train mindfulness in a broad non-clinical population, regardless of the level of general psychiatric symptomatology or mindfulness or current practice of (mindfulness) meditation of its users. This is a promising finding, because it shows that MBI apps – which are essentially self-help MBIs – could be a useful addition to health care, to meet the increasing demand on mindfulness. There is debate about whether the authenticity and integrity of mindfulness training is warranted when it is not taught by an experienced instructor (Crane et al., 2012). Therefore, because MBI apps do not offer an instructor, it is important that these apps are evidence based, well-designed and stay close to the programs of well-established face-to-face MBIs (see Fish et al., 2016).
That said, there are a number of limitations to this study that have to be taken into consideration when interpreting the findings. First, we have no data on why participants
17 stopped using the app or quit their participation in the study. It might be useful in future research and the development of MBI apps to ask what made people discontinue their use of the app, to know how to motivate them to keep practicing. Second, the question that was used to ask people about their (mindfulness) meditation experience, only asked if the participants were currently practising mindfulness or other forms of meditation. With this phrasing, we do not have any information about prior meditation experience, so we cannot draw conclusions about that in this study. Third, our measurements relied only on self-report questionnaires. Self-report measurements are sensitive to response biases, such as a social desirability bias, that potentially undermine the validity of the measurements. Fourth, although this study aimed to investigate the predictive value of general psychiatric symptomatology, the population in this study was essentially non-clinical. Therefore, we cannot make any inferences about the effect of the app in clinical populations. That said, the fact that we found that the level of general psychiatric symptomatology does not predict the effect of the app, is a promising finding emphasising the potential of the app to train mindfulness in clinical populations. However, this is something that has to be investigated in future research.
In conclusion, despite these limitations, this study shows that regardless of (non-clinical) psychological problems or level of mindfulness, users can develop mindfulness skills with an MBI app such as the VGZ Mindfulness Coach. We suggest that future research focuses on investigating other predictors in order to get a deeper understanding of the effectivity of MBI apps. Furthermore, future research could explore the use of MBI apps in clinical populations, for instance as a complement to face-to-face therapy.
18
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