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CBT for depression: a pilot RCT comparing mobile phone vs. computer

CBT for depression: a pilot RCT comparing mobile phone vs. computer Background: This paper reports the results of a pilot randomized controlled trial comparing the delivery modality (mobile phone/tablet or fixed computer) of a cognitive behavioural therapy intervention for the treatment of depression. The aim was to establish whether a previously validated computerized program (The Sadness Program) remained efficacious when delivered via a mobile application. Method: 35 participants were recruited with Major Depression (80% female) and randomly allocated to access the program using a mobile app (on either a mobile phone or iPad) or a computer. Participants completed 6 lessons, weekly homework assignments, and received weekly email contact from a clinical psychologist or psychiatrist until completion of lesson 2. After lesson 2 email contact was only provided in response to participant request, or in response to a deterioration in psychological distress scores. The primary outcome measure was the Patient Health Questionnaire 9 (PHQ-9). Of the 35 participants recruited, 68.6% completed 6 lessons and 65.7% completed the 3-months follow up. Attrition was handled using mixed-model repeated-measures ANOVA. Results: Both the Mobile and Computer Groups were associated with statistically significantly benefits in the PHQ-9 at post-test. At 3 months follow up, the reduction seen for both groups remained significant. Conclusions: These results provide evidence to indicate that delivering a CBT program using a mobile application, can result in clinically significant improvements in outcomes for patients with depression. Trial registration: Australian New Zealand Clinical Trials Registry ACTRN 12611001257954 Keywords: Cognitive behavioural therapy, Major depressive disorder, Mobile app, Internet treatment, Treatment Background Disorder (MDD) and more cost effective [9,10]. Johanssen Depression is a commonly occurring, disabling mental and Andersson (2012) reviewed 25 controlled trials of disorder [1-3]. Worldwide it is currently the fourth lead- iCBT for MDD [11]. Effect size (ES) superiority of the ing cause of disability and is expected to become the intervention over the control group ranged between 0.1 second leading cause of disease burden by the year 2020 and 1.2, but there were six studies in which the effect size [4]. Cognitive behavior therapy (CBT) has been shown superiority was greater than 0.85 (mean = 1.0, NNT=2). to be effective in the treatment of depression [5,6]. How- The intervention in one of these [12,13](ES=1.2) was the ever, a number of barriers prevent patients from acces- basis of the present work. sing treatment. For example, three–quarters of people in Delivery of CBT using the internet has increased the the UK with depression received no treatment, with cost options available for patients with depression to access being the major barrier [7,8]. Treatments that are more evidenced based effective treatment. For some, using a affordable and accessible are necessary. fixed computer may mean little or no privacy, or it may CBT via the internet (iCBT) has been shown to be as simply be inconvenient. Moreover, a patient may want effective as face to face treatment for Major Depressive to review the treatment lesson material in context, for example, re-reading material on a computer just prior to entering a challenging situation may not be feasible. For * Correspondence: [email protected] others, access to the internet may be unreliable and this Clinical Research Unit for Anxiety and Depression, School of Psychiatry, University of New South Wales at St Vincent’s Hospital, 394-404 Victoria may not be a useful alternative. It is for these reasons, Street, Darlinghurst, NSW, Australia © 2013 Watts et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Watts et al. BMC Psychiatry 2013, 13:49 Page 2 of 9 http://www.biomedcentral.com/1471-244X/13/49 that alternative modes of treatment delivery should be ability of the participant to concentrate in this environ- considered. Mobile applications (apps) offer a viable, ment. Adherence towards homework was also measured cost effective and highly accessible solution. Recently using self reported effort and amount of homework mobile apps have been utilized to deliver health treat- completed. ments [14,15] and whilst a plethora of apps are available, evidence based, evaluated apps remain sparse. With al- Method most 6 billion mobile phone subscriptions worldwide in Design 2011, it is anticipated that this mode of health delivery A CONSORT-2010 compliant, registered RCT compared will rise [16]. To our knowledge, there are no published two modes of delivery, a mobile versus computer group. RCTs using a mobile app to deliver treatment for MDD. Both groups were followed through 3-months follow-up. Using a mobile app may enable greater choice in pre- ferred treatment options, increased convenience, greater Participants, randomisation, and recruitment accessibility and enhanced privacy. Applicants applied to www.virtualclinic.org.au after Bang and colleagues (2007) have described the advan- reading details about the study. Details of the applicant tages of using a mobile phone over other delivery meth- and participant flow are in Figure 1. During recruitment ods for some of the elements of CBT, explaining a between March and May 2012, 176 individuals applied mobile phone has the functionality to record, scale and for this program and 52 applicants met the inclusion cri- label anxiety-provoking situations when and where the teria: (i) aged over 18, (ii) self identified as suffering from need arises [17]. These advantages were evidenced in a mild or moderate depression, and have PHQ-9 scores recent study that showed people’s everyday mood, stres- and results of telephone diagnostic interview (MINI) ses, responses and general functioning, can be helpfully consistent with this, (iii) prepared to provide name, communicated to primary care practitioners by tracking phone number and address, and (iv) to provide written and capturing data in context [18]. Furthermore, partici- informed consent, (v) had access to a mobile phone or pants from this study reported this method of data col- iPad, and a computer with a printer and, (iv) had previ- lection as convenient and acceptable. This positive ous experience with downloading a mobile app. Appli- sentiment was echoed in a study exploring community cants were excluded if they: (i) had psychosis, bipolar attitudes towards the use of mobile phones for mental disorder, substance abuse or dependence, (ii) severe de- health monitoring and self management. Proudfoot and pression (with a PHQ-9 score greater than 24) and (iii) colleagues found attitudes were positive towards using a or current suicidality, as assessed by Question 9 on the mobile phone for mental health monitoring, however, PHQ-9: “how frequently over the last two weeks have participants identified the importance of privacy, secur- you been bothered by thoughts that you would be better ity provisions and an easy to use program [19]. off dead or of hurting yourself in some way?” If the ap- On this basis, we revised our previously evaluated 6- plicant answered 2 (= more than half the days), with a lesson clinician assisted treatment program for depres- history of previous suicide attempts or answered 3 (= sion (The Sadness Program) [11,12] into a mobile app nearly every day), with or without previous suicide version, complete with security settings. The name of attempts, they were excluded, and contacted by the the program was changed from The Sadness Program to study clinicians (CT, AG) and advised as to an appropri- The Get Happy Program to convey a sense of optimism ate course of action. and empowerment. In order to demonstrate the efficacy 115 applicants met selection criteria and of these 101 of the program using a mobile app, we decided to com- were able to be contacted by phone. The content of the pare the delivery mode of the same program between a call included a review of the study and confirmation that mobile vs. computer group. It was hypothesized that all the applicant had read and understood the information participants would show significant improvement on and consent form. Following this, the Mini International measures of depression, a reduction of psychological dis- Neuropsychiatric Interview Version 5.0.0 (MINI) [21] tress, and participants would find the treatment modes was used to confirm the applicant met DSM-IV criteria equally acceptable. Given the transportable nature and for a Major Depressive Disorder (MDD). 52 applicants use of mobile phones, we thought it would be important met all inclusion criteria and were randomised via a true to understand the type of environment utilized, and if, randomisation process (www.random.org) generated by any, environmental factors, such as noise, may have an a team member not involved in the study, to either the impact on the efficacy of the program for mobile users. Mobile Group (n=22) or Computer Group (n=30). How- Thus, based on the Experience Sampling Method [20], ever, at baseline we had 15 participants in the Mobile three items were constructed to identify the location of Group and 20 in the Computer Group, due to partici- where the participant was completing the lesson, how pants not starting the first lesson. Concealment of distracting the level of noise was, and the self rated allocation was maintained until the applicant met all Watts et al. BMC Psychiatry 2013, 13:49 Page 3 of 9 http://www.biomedcentral.com/1471-244X/13/49 176 individuals applied for the Get Happy Program within timeframe (06/03/12 – 1/06/12) Unsuccessful Application (n=105) Severe depressive symptoms on PHQ-9 Subclinical depressive symptoms on PHQ-9 7) Non-resident/under 18 years of age (n=8) Taking exclusion criteria medications (n=9) 115 individuals met inclusion criteria Could not contact (n = 14) 101 individuals completed telephone interview with MINI 5.0 Unsuccessful Telephone Interview (n=49) Subclinical (n = 17) Decided not to proceed (n = 10) No appropriate smartphone (n = 10) Recent commencement of CBT (n = 1) Completed similar e course (n=5) Changing medication/using exclusion medication (n = 6) 52 participants met all inclusion criteria and were randomized into T1 or T2 T1 – Mobile group (n = 22) T2 – Computer group (n = 30) Did not complete Pre- Did not complete Pre- Treatment Questionnaires Treatment (n=7) 9) Withdrawn (n=1) 15 completed Pre-Treatment Questionnaires 20 completed Pre-Treatment Questionnaires Eligible for analysis (started lesson 1), n = 15 Eligible for analysis (started lesson 1), n = 20 10 participants completed all lessons 14 participants completed all lessons (1 terminated at lesson 1, 1 at lesson 2, 2 at (2 terminated at lesson 1, 1 at lesson 3, 3 at lesson 4, 1 at lesson 5) lesson 5) 15 Completed Post-Treatment Questionnaires 10 Completed Post-Treatment Questionnaires Completed 3 month Follow Up Completed 3 month Follow Up Questionnaires, n=9 Questionnaires, n=14 Figure 1 Flow of participants through trial. inclusion criteria and an offer of participation made. The Diagnostic measure unsuccessful applicants (n=49) were advised about more Mini international neuropsychiatric interview version 5.0.0 appropriate treatment options. The study was approved (MINI) by the Human Research Ethics Committee (HREC) of St The MINI is a brief diagnostic interview developed to de- Vincent’s Hospital (Sydney, Australia) and the trial was termine the presence of a current and life-time Axis-1 dis- registered as ACTRN 12611001257954. order using DSM-IV diagnostic criteria. It has excellent Watts et al. BMC Psychiatry 2013, 13:49 Page 4 of 9 http://www.biomedcentral.com/1471-244X/13/49 inter-rater reliability (k=.88-1.00) and adequate concurrent validity with the Composite International Diagnostic Interview [22]. Description of treatment The Get Happy Program was based on the principles of CBT and is a version of the previously evaluated Sadness Program [11,12]. The program consisted of 6 lessons conducted over an 8 week period. The lessons read like a comic book and participants follow the story of Jess, a comic character that has depression, and through her story learn how she comes to manage her symptoms, and participants can then apply these principles to their own life. The size of the font was adapted for the mobile version and some minor revisions were made to the con- Figure 3 Screenshot of mobile version of program. tent of the program. On completion of each lesson, par- ticipants were assigned and encouraged to carry out the relevant homework activities and review the lesson. Additional resources, such as information on assertive- Clinician contact ness skills and sleep hygiene, and stories from previous Participants received emails/or phone calls from a clin- participant’s experiences were also available Figure 2, ician, until completion of Lesson 2 because our previous Figure 3. research study has found that additional clinician sup- port does not add any further benefit to participants [13]. Following this, the only clinical contact was when the participant initiated contact, or when a clinician instigated contact due to a deterioration in the K-10 score [23]. The K-10 is a measure of psychological dis- tress and was completed prior to beginning each lesson. Outcome measures The Patient Health Questionnaire-9 (PHQ-9) [24] is a brief 9-item self-report scale that measures each of the DSM-IV criteria for MDD with scores ranging from 0 to 27. Participants rate the frequency of symptoms over the last fortnight on a scale ranging from 0 (not at all) to 3 (nearly every day), where 1 = several days, 2 = more than half of the days. A PHQ-9 score of ≥10 is used as a clin- ical cut-off for probable DSM-IV diagnosis of MDD [25]. The PHQ-9 has been shown to have good sensitivity and specificity [26] and excellent reliability and validity [24]. The Kessler 10-item Psychological Distress scale (K-10) [23] is a measure of non-specific psychological distress over the past 14 days. Scores can range from 10 to 50, with higher scores indicating higher distress. The K-10 has good psychometric properties and can discriminate between cases and non-cases of DSM-IV affective disor- ders [27]. Beck’s Depression Inventory Second Edition (BDI-II) [28] consists of 21 items and is a measure of the presence and severity of a MDD based on the DSM-IV diagnostic cri- Figure 2 Screenshot of mobile program outlining available teria for depression. Scores range from 0 to 63 with higher options for mobile participants to review lesson, open scores indicating a greater severity of depression. The homework, access resources or read stories. BDI-II possesses excellent internal consistency [28]. Watts et al. BMC Psychiatry 2013, 13:49 Page 5 of 9 http://www.biomedcentral.com/1471-244X/13/49 Credibility/Expectancy Questionnaire (CEQ) [29] is a method used to implement marginal models when the scale for measuring treatment credibility and expectancy outcome variable is not normally distributed. The GEN- of improvement. At post treatment, 2 items based on LIN procedure with a repeated statement was implemen- the CEQ were asked including, how satisfied were you ted using SPSS Version 19. A poisson distribution with a with the skills that this program has taught you to man- log link function was specified. An unstructured covari- age your depression from 1 (not at all satisfied) to 9 ance structure was used to model the within-subject de- (very satisfied); how confident would you be in recom- pendencies. Initial models only included measurement mending this treatment to a friend who experiences occasion, study group and their interaction as fixed effects. similar problems from 1 (not at all confident) to 9 (very For each outcome measure, the two homework questions confident). were included separately in subsequent models to investi- Sheehan Disability Scale (SDS) [30] is a measurement gate whether any of the outcomes differed based on self- of functional disability and impairment due to psychi- reported homework effort or homework completion. atric symptoms and is self rated. The 2 items related to productivity were used for this study. The first item used Outcome measurement to measure absenteeism asked participants how many All participants completed the questionnaire outcome days in the last week their symptoms caused them to measures (BDI-II, PHQ-9, K-10, CEQ, ERS and SDS) at miss studies or work, or leave them unable to do their 1-week post treatment and at 3-months follow up. normal daily responsibilities. The second item used to measure presenteeism asked participants on how many Results days in the last week did they feel so impaired by their Baseline symptoms, that even though they studied, went to work The mean age of participants was 41 years (SD= 12.38, or worked at home, their productivity was reduced. range =18 - 63) and 28/35 were female (80% of the sam- ple). Participants reported on average, moderate depres- Environment rating scale (ERS) sion levels using the PHQ-9, severe levels of depression Three items were constructed to identify the location of on the BDI –II, and severe levels of psychological dis- where Mobile Group participants were completing the tress using the K-10. Participants reported on average lessons with options including: at home, at work, on a 2.14 days of work lost (SD= 2.19) and 4.40 days of work train or a bus, at a park or the beach, a café, or other. that were underproductive (SD= 2.15) due to the pres- The Mobile Group participants were also asked to rate ence of his/her psychiatric symptoms on the SDS (see how distracting the level of noise was from 1 (no dis- Table 1). tracting noise) to 4 (extremely distracting noise). Lastly, the Mobile Group participants were asked to rate their Baseline between-group comparisons ability to concentrate in this environment from 1 (poor) Independent samples t-tests compared the two groups on to 4 (excellent) (adapted from the Experience Sampling baseline demographic characteristics and pre-treatment Method, [20]). symptom questionnaires. There were no differences be- tween the groups on age, the BDI-II, PHQ-9, nor K-10. Homework rating scale (HRS) Two items were constructed to measure the amount of Adherence results effort and homework completion. The participant was 8.6% (3/35) completed only the first lesson, 2.9% (1/35) first asked how much effort they had put into the home- completed two lessons, 2.9% (1/35) completed 3 lessons, work from 0 (no effort) to 4 (complete effort); and how 5.7% (2/35) completed 4 lessons, 11.4% (4/35) completed much of the assigned homework they had finished from 5 lessons and 68.6% (24/35) of participants completed all 0 (none) to 4 (all). six lessons. Refer to Figure 1. When comparing the Mobile Group with the Computer Group on adherence, Statistical analysis there were no significant differences (t (33) = −.242, For the PHQ-9, K-10 and BDI-II analyses were con- P >.05). ducted using linear mixed-model repeated measures (MMRM) ANOVA with measurement occasion as a within-group factor and intervention as a between-groups Disorder-specific and generic outcome measures factor. These analyses were conducted using the MIXED Figure 4 displays mean PHQ-9 scores on each measure- procedure in SPSS Version 19 with an identity covariance ment occasion as a function of the two conditions. matrix. For the SDS generalised estimating equations Statistical tests showed that the benefits of the inter- (GEE) were used to evaluate reductions in absenteeism vention remained significant in both groups at follow up and presenteeism across time. GEE is a semi-parametric when using the PHQ-9 (F [3, 73.6] = 28.4, P=<.001), the Watts et al. BMC Psychiatry 2013, 13:49 Page 6 of 9 http://www.biomedcentral.com/1471-244X/13/49 Table 1 Baseline, mid, post-treatment estimated means, standard deviations, MMRM ANOVA, and effect sizes for outcome measures Pre- Mid- Post- Follow up Statistic Effect Size treatment treatment treatment Measure M (SD) M (SD) M (SD) M (SD) Pre to post Pre to post Pre to follow up Pre to follow up Within-subjects pre- post- Between group post (n=35) (n=30) (n=25) (n=23) within group between group within group between group treatment comparison for treatment (measurement (time by study (measurement (time by study treatment group (95% comparison (95% occasion) group interaction) occasion) group interaction) confidence intervals) confidence intervals) PHQ-9 Mobile 14.65 (1.37) 6.45 (1.51) 6.55 (1.51) 5.28 (1.63) F [2, 51.97] = F [2, 51.97] = 1.09, F [3, 73.6] = F [3, 73.6] = .875, 1.41 (.55-2.26) −0.47 (−0.47- 0.20) 33.22, P=<.001 P=.34 28.4, P=<.001 P=.458 PHQ-9 14.20 (1.62) 8.98 (1.24) 7.21 (1.26) 7.18 (1.32) .92 (.19-1.64) Computer BDI-II Mobile 33.46 (2.95) 12.53 (3.26) 11.66 (3.47) F [1, 25.55] = F [1, 25.55] = .41, F [2, 47.09] = F [2, 47.0] = 1.7, 1.79 (0.92-2.65) −0.37 (−1.05- 0.29) 86.02, P=.<.001 P=.52 60.1, P=.<.001 P=.19 BDI-II Computer 30.90 (2.55) 13.68 (2.79) 16.75 (2.85) 1.88 (1.14-2.62) K-10 Mobile 30.60 (2.06) 22.44 (2.21) 20.03 (2.21) 19.74 (2.31) F [6, 153.9] = F [6, 153.9] = .359, F [7, 1734.5] = F [7,174.91] = .370, 1.05 (.20-1.89) 0.03 (−0.63-0.70) 24.3,P=<.001) P=.90) 28.4, P=<.001) P=.919) K-10 Computer 30.15 (1.78) 24.12 (1.86) 19.95 (1.88) 19.55 (1.93) 1.22 (.52-1.92) SDS days lost 2.20 (.62) .74 (.42) Mobile SDS days lost 2.10 (.44) 1.15 (.37) Computer SDS days 4.13 (.54) 2.23 (.71) underproductive Mobile SDS days 4.25 (.47) 1.89 (.53) underproductive Computer Watts et al. BMC Psychiatry 2013, 13:49 Page 7 of 9 http://www.biomedcentral.com/1471-244X/13/49 to post-treatment. Effect sizes for these measures are Mobile included in Table 1. Computer Productivity outcome measures Statistical tests using the SDS showed a significant re- duction in the number of days lost (absenteeism) (Wald Chi-Square =10.31, P = <.05) and in the number of days underproductive (presenteeism) from pre-treatment to post-treatment (Wald Chi-Square =12.33, P = .001). Fur- ther results indicated that the interaction between ex- perimental group and time was not statistically significant 2 when comparing the SDS on absenteeism (Wald Chi- Square =.86, P = .35) and presenteeism (Wald Chi-Square =.22, P =.63). Pre-test Lesson 4 Post-test 3 month follow- up Figure 4 Estimated marginal means for PHQ-9 scores estimated Environment, distraction, and concentration measure- under occasion x intervention model. mobile group Descriptive data on the environment, level of distraction and ability to concentrate, was collected for participants in the Mobile Group. Over the six lessons, 66.7-92.9% of BDI-II (F [2, 47.09] = 60.1, <.001) and the K-10 (F [7, participants completed the lessons in their home, 46.7- 1734.5] = 28.4, P=<.001). 60% of participants completed these lessons when there Estimated marginal means for PHQ-9 scores estimated was slight distraction, and 30.8-53.3% endorsed an ‘okay’ under occasion x intervention model). ability to concentrate. Please refer to Table 2. Results from the MMRM (ANOVA) indicated that the interaction between experimental group and time was Clinical significance not statistically significant when comparing PHQ-9 At post-treatment, only 16/35 (45%) met criteria for de- scores (F [3, 73.6] = .875, P=.458), BDI-II scores (F [2, pression on the PHQ-9 (see Table 3 for results). 47.0] = 1.7, P=.19), or K-10 scores (F [7, 174.91] = .370, P=.919). Time spent per participant for both the mobile and In order to investigate differences between each occa- computer groups sion of measurement, a series of pair wise comparisons The mean clinician time spent per participant was were conducted. For the PHQ-9 and K-10 the change 4.1 minutes (SD= 4.63) and the mean technician time from baseline to mid-point, post-test, and 3-month follow spent per participant was 6.4 minutes (SD= 5.38). Each up was investigated. Significant reductions were found time a clinician or technician had contact with a partici- between baseline and all other time points for both the pant the amount of time was recorded to monitor the Mobile Group and Computer Group. This pattern was time required to deliver the program. repeated using the BDI-II, when investigating changes from baseline to post-test and 3-months follow up. Participant satisfaction Upon completion of the program 54% of Mobile Group Homework completion and effort and 64% of the Computer Group were very satisfied with The aggregated mean score for homework effort for the the program; with the remaining participants endorsing Mobile Group was 11.25 (range, 6–17) and 14.46 (range ‘somewhat satisfied’. 64% of the Mobile Group and 64% 9–20) for the Computer Group. An aggregated mean of the Computer Group would be very confident in score for homework completion for the Mobile Group recommending this treatment to a friend; and the re- was 11 (range, 8–16) and 12.4 (range 6–18) for the mainder endorsed ‘somewhat confident’. Computer Group. Results from the MMRM (ANOVA) indicated that there were no significant differences in Discussion homework completion or homework effort between the These results indicate that reductions in PHQ-9, the groups on the PHQ-9, the BDI-II, or the K-10. BDI-II and K-10 pre- to post-intervention and pre to follow up, were significant, regardless of experimental Effect sizes group. This provides preliminary support for the efficacy Large (>.8) within-group effect sizes were found on the of a CBT program delivered using a mobile phone. The BDI-II, PHQ-9 and K-10 measures from pre-treatment results, including the effect size, shown in this study are Watts et al. BMC Psychiatry 2013, 13:49 Page 8 of 9 http://www.biomedcentral.com/1471-244X/13/49 Table 2 Environment, levels of distraction, and levels of concentration for the Mobile Group Lesson 1 Lesson 2 Lesson 3 Lesson 4 Lesson 5 Lesson 6 Environment Home 13/ 15 (86.7%) 13/14 (92.9%) 9/13 (69.2%) 9/12 (75%) 9/11 (81.8%) 6/9 (66.7%) Work 0 0 2/13 (13.3%) 3/12 (25%) 1/11 (9.1%) 0 Train/bus 0 0 1/13 (6.7%) 0 0 2/9 (22.2%) Other 2/15 (13.3%) 1/14 (7.1%) 1/13 (6.7%) 0 1/11 (9.1%) 1 (11.1%) Missing data 0 1 2346 Level of distraction No distraction 5/15 (33.3%) 6/14 (42.9%) 5/13 (38.5%) 5/12 (41.7%) 4/11 (36.4%) 4/10 (40%) Slightly distraction) 7/15 (46.7%) 7/14 (50%) 7/13 (53.8) 5/12 (41.7%) 6/11 (54.5%) 6/10 (60%) Moderately distracting) 3/15 (20%) 1/14 (7.1%) 0 2/12 (16.6%) 1/11 (9.1%) 0 Extremely distracting 0 0 1/13 (7.7) 0 0 0 Missing data 0 1 2345 Ability to concentrate Poor 0 0 0000 Okay 8/15 (53.3%) 6/14 (42.9%) 4/13 (30.8%) 6/12 (50%) 5/11 (45.4%) 2/10 (20%) Good 4/15 (26.7%) 7/14 (50%) 5/13 (38.4%) 2/12 (16.6%) 4/11 (36.4%) 7/10 (70%) Excellent 3/15 (20%) 1/14 (7.1)% 4/13 (30.8%) 4/12 (33.4%) 2/11 (18.2%) 1/10 (10%) Missing data 0 1 2345 commensurate with our previous RCT’s [12,13], indicat- research could explore and compare this data to inform ing that using a mobile phone to offer this program recommendations as to the best placed environment for shows similar promise. patients to complete the program in order to obtain the There were a number of limitations to this study. Firstly, most optimal results. the small sample size necessitates replication, in order to The results of this pilot study indicate the usefulness reproduce the benefits identified in this study of delivering of replicating this study in the future research with a lar- a CBT program via a mobile phone or computer. Other ger sample size and control group. Minor additions to possible limitations include the self-selecting nature of the utilise the functionality available on a mobile phone/tab- sample. Those applying to complete treatment programs let are planned, for example, including the ability for using technology must be motivated; however, this does participants to set automated reminders in their calen- not make the results of this study invalid. A further limita- dar, and complete the homework on their phone/tablet. tion is the absence of a control group. A control group Data on the time of day and amount of usage for the would have provided the additional advantage of ensuring mobile users is also intended to be collected to under- the effects observed were able to be explained by the treat- stand if the increased proximity of the mobile, does lead ment. However, due to the small sample size of this study, to increased use, and greater benefits over time. Very lit- a control group was not included. Lastly, this study did tle is currently known about the possible benefits of not collect data on the environment, level of concentra- offering patient’s treatment programs using a mobile app tion and distractibility in the Computer Group. Future on their mobile phone, however, the ubiquity of mobile Table 3 PHQ-9 scores according to clinical cut-off ranges at pre- and post- treatment Pre treatment Post treatment PHQ-9 Severity Status Mobile (n=14) Computer (n=20) Mobile (n= 11) Computer (n= 16) None (0–9) 2/14 (14%) 2/20 (10%) 8/11 (73%) 10/16 (62%) Mild (10–14) 6/14 (43%) 11/20 (55%) 2/11 (18%) 4/16 (25%) Moderate (15–19) 4/14 (29%) 4/20 (20%) 1/11 (9%) 1/16 (6.5%) Severe (20+) 2/14 (14%) 3/20 (15%) 0 1/16 (6.5%) Missing Data 1 0 4 4 Meet criteria for MDD 12/14 (89%) 18/20 (90%) 3/11 (27%) 6/16 (37.5%) NB. Due to the time lag between recruitment and upon commencement of the program four participants did not meet criteria for MDD. Watts et al. BMC Psychiatry 2013, 13:49 Page 9 of 9 http://www.biomedcentral.com/1471-244X/13/49 apps, the growing community uptake and interest in this borderline personality disorder and substance Use of disorder. 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Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SL, approved the final manuscript. Zaslavsky AM: Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med 2002, Received: 18 December 2012 Accepted: 31 January 2013 32:959–976. Published: 7 February 2013 24. Kroenke K, Spitzer RL, Williams J: The PHQ-9. Validity of a brief depression severity measure. JGIM: Journal of General Internal Medicine 2001, 16:606– References 613. doi:10.1046/j.1525-1497.2001.016009606.x. 1. Andrews G, Titov N: Depression is very disabling. Lancet 2007, 25. Zuithoff N, Vergouwe Y, King M, Nazareth I, van Wezep M, Moons K, 370:808–809. Geerlings M: The Patient Health Questionnaire-9 for detection of major 2. Cuijpers P, Smit F: Excess mortality in depression: a meta-analysis of depressive disorder in primary care: consequences of current thresholds community studies. J Affect Disord 2002, 72:227–236. in a crosssectional study. 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Kessler RC: The costs of depression. Psychiatr Clin North Am 2012, 35:1–14. 9. Cuijpers P, Donker T, van Straten A, Li J, Andersson G: Is guided self-help doi:10.1186/1471-244X-13-49 as effective as face-to-face psychotherapy for depression and anxiety Cite this article as: Watts et al.: CBT for depression: a pilot RCT disorders? A systematic review and meta-analysis of comparative comparing mobile phone vs. computer. BMC Psychiatry 2013 13:49. outcome studies. Psychol Med 2010, 40:14. 10. Hedman E, Andersson G, Ljótsson B, Andersson E, Rück C, Mörtberg E, Lindefors N: Internet-based cognitive behaviour therapy vs. Cognitive behavioural group therapy for social anxiety disorder: a randomized controlled Non-inferiority trial. PLoS One 2011, 6(3):e18001. doi:10.1371/ journal.pone.0018001. 11. Johansson R, Andersson G: Internet-based psychological treatments for depression. Expert Rev Neurother 2012, 12(7):861–870. doi:10.1586/ERN.12.63. 12. Perini S, Titov N, Andrews G: Clinician-assisted Internet-based treatment is effective for depression: Randomized controlled trial. The Royal Australian and New Zealand College of Psychiatrists 2009, 43:7. 13. Titov N, Andrews G, Johnston L, Robinson E, Spence J: Transdiagnostic internet treatment for anxiety disorders: a randomized controlled trial. Behav Res Ther 2010, 48:890–899. doi:10.1016/j.brat.2010.05.014. 14. Rizvi SL, Dimeff LA, Skutch J, Carroll D, Linehan MM: A pilot study of the DBT coach: an interactive mobile phone application for individuals with http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png BMC Psychiatry Springer Journals

CBT for depression: a pilot RCT comparing mobile phone vs. computer

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Springer Journals
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Copyright © 2013 by Watts et al.; licensee BioMed Central Ltd.
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Medicine & Public Health; Psychiatry; Psychotherapy
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1471-244X
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10.1186/1471-244X-13-49
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Abstract

Background: This paper reports the results of a pilot randomized controlled trial comparing the delivery modality (mobile phone/tablet or fixed computer) of a cognitive behavioural therapy intervention for the treatment of depression. The aim was to establish whether a previously validated computerized program (The Sadness Program) remained efficacious when delivered via a mobile application. Method: 35 participants were recruited with Major Depression (80% female) and randomly allocated to access the program using a mobile app (on either a mobile phone or iPad) or a computer. Participants completed 6 lessons, weekly homework assignments, and received weekly email contact from a clinical psychologist or psychiatrist until completion of lesson 2. After lesson 2 email contact was only provided in response to participant request, or in response to a deterioration in psychological distress scores. The primary outcome measure was the Patient Health Questionnaire 9 (PHQ-9). Of the 35 participants recruited, 68.6% completed 6 lessons and 65.7% completed the 3-months follow up. Attrition was handled using mixed-model repeated-measures ANOVA. Results: Both the Mobile and Computer Groups were associated with statistically significantly benefits in the PHQ-9 at post-test. At 3 months follow up, the reduction seen for both groups remained significant. Conclusions: These results provide evidence to indicate that delivering a CBT program using a mobile application, can result in clinically significant improvements in outcomes for patients with depression. Trial registration: Australian New Zealand Clinical Trials Registry ACTRN 12611001257954 Keywords: Cognitive behavioural therapy, Major depressive disorder, Mobile app, Internet treatment, Treatment Background Disorder (MDD) and more cost effective [9,10]. Johanssen Depression is a commonly occurring, disabling mental and Andersson (2012) reviewed 25 controlled trials of disorder [1-3]. Worldwide it is currently the fourth lead- iCBT for MDD [11]. Effect size (ES) superiority of the ing cause of disability and is expected to become the intervention over the control group ranged between 0.1 second leading cause of disease burden by the year 2020 and 1.2, but there were six studies in which the effect size [4]. Cognitive behavior therapy (CBT) has been shown superiority was greater than 0.85 (mean = 1.0, NNT=2). to be effective in the treatment of depression [5,6]. How- The intervention in one of these [12,13](ES=1.2) was the ever, a number of barriers prevent patients from acces- basis of the present work. sing treatment. For example, three–quarters of people in Delivery of CBT using the internet has increased the the UK with depression received no treatment, with cost options available for patients with depression to access being the major barrier [7,8]. Treatments that are more evidenced based effective treatment. For some, using a affordable and accessible are necessary. fixed computer may mean little or no privacy, or it may CBT via the internet (iCBT) has been shown to be as simply be inconvenient. Moreover, a patient may want effective as face to face treatment for Major Depressive to review the treatment lesson material in context, for example, re-reading material on a computer just prior to entering a challenging situation may not be feasible. For * Correspondence: [email protected] others, access to the internet may be unreliable and this Clinical Research Unit for Anxiety and Depression, School of Psychiatry, University of New South Wales at St Vincent’s Hospital, 394-404 Victoria may not be a useful alternative. It is for these reasons, Street, Darlinghurst, NSW, Australia © 2013 Watts et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Watts et al. BMC Psychiatry 2013, 13:49 Page 2 of 9 http://www.biomedcentral.com/1471-244X/13/49 that alternative modes of treatment delivery should be ability of the participant to concentrate in this environ- considered. Mobile applications (apps) offer a viable, ment. Adherence towards homework was also measured cost effective and highly accessible solution. Recently using self reported effort and amount of homework mobile apps have been utilized to deliver health treat- completed. ments [14,15] and whilst a plethora of apps are available, evidence based, evaluated apps remain sparse. With al- Method most 6 billion mobile phone subscriptions worldwide in Design 2011, it is anticipated that this mode of health delivery A CONSORT-2010 compliant, registered RCT compared will rise [16]. To our knowledge, there are no published two modes of delivery, a mobile versus computer group. RCTs using a mobile app to deliver treatment for MDD. Both groups were followed through 3-months follow-up. Using a mobile app may enable greater choice in pre- ferred treatment options, increased convenience, greater Participants, randomisation, and recruitment accessibility and enhanced privacy. Applicants applied to www.virtualclinic.org.au after Bang and colleagues (2007) have described the advan- reading details about the study. Details of the applicant tages of using a mobile phone over other delivery meth- and participant flow are in Figure 1. During recruitment ods for some of the elements of CBT, explaining a between March and May 2012, 176 individuals applied mobile phone has the functionality to record, scale and for this program and 52 applicants met the inclusion cri- label anxiety-provoking situations when and where the teria: (i) aged over 18, (ii) self identified as suffering from need arises [17]. These advantages were evidenced in a mild or moderate depression, and have PHQ-9 scores recent study that showed people’s everyday mood, stres- and results of telephone diagnostic interview (MINI) ses, responses and general functioning, can be helpfully consistent with this, (iii) prepared to provide name, communicated to primary care practitioners by tracking phone number and address, and (iv) to provide written and capturing data in context [18]. Furthermore, partici- informed consent, (v) had access to a mobile phone or pants from this study reported this method of data col- iPad, and a computer with a printer and, (iv) had previ- lection as convenient and acceptable. This positive ous experience with downloading a mobile app. Appli- sentiment was echoed in a study exploring community cants were excluded if they: (i) had psychosis, bipolar attitudes towards the use of mobile phones for mental disorder, substance abuse or dependence, (ii) severe de- health monitoring and self management. Proudfoot and pression (with a PHQ-9 score greater than 24) and (iii) colleagues found attitudes were positive towards using a or current suicidality, as assessed by Question 9 on the mobile phone for mental health monitoring, however, PHQ-9: “how frequently over the last two weeks have participants identified the importance of privacy, secur- you been bothered by thoughts that you would be better ity provisions and an easy to use program [19]. off dead or of hurting yourself in some way?” If the ap- On this basis, we revised our previously evaluated 6- plicant answered 2 (= more than half the days), with a lesson clinician assisted treatment program for depres- history of previous suicide attempts or answered 3 (= sion (The Sadness Program) [11,12] into a mobile app nearly every day), with or without previous suicide version, complete with security settings. The name of attempts, they were excluded, and contacted by the the program was changed from The Sadness Program to study clinicians (CT, AG) and advised as to an appropri- The Get Happy Program to convey a sense of optimism ate course of action. and empowerment. In order to demonstrate the efficacy 115 applicants met selection criteria and of these 101 of the program using a mobile app, we decided to com- were able to be contacted by phone. The content of the pare the delivery mode of the same program between a call included a review of the study and confirmation that mobile vs. computer group. It was hypothesized that all the applicant had read and understood the information participants would show significant improvement on and consent form. Following this, the Mini International measures of depression, a reduction of psychological dis- Neuropsychiatric Interview Version 5.0.0 (MINI) [21] tress, and participants would find the treatment modes was used to confirm the applicant met DSM-IV criteria equally acceptable. Given the transportable nature and for a Major Depressive Disorder (MDD). 52 applicants use of mobile phones, we thought it would be important met all inclusion criteria and were randomised via a true to understand the type of environment utilized, and if, randomisation process (www.random.org) generated by any, environmental factors, such as noise, may have an a team member not involved in the study, to either the impact on the efficacy of the program for mobile users. Mobile Group (n=22) or Computer Group (n=30). How- Thus, based on the Experience Sampling Method [20], ever, at baseline we had 15 participants in the Mobile three items were constructed to identify the location of Group and 20 in the Computer Group, due to partici- where the participant was completing the lesson, how pants not starting the first lesson. Concealment of distracting the level of noise was, and the self rated allocation was maintained until the applicant met all Watts et al. BMC Psychiatry 2013, 13:49 Page 3 of 9 http://www.biomedcentral.com/1471-244X/13/49 176 individuals applied for the Get Happy Program within timeframe (06/03/12 – 1/06/12) Unsuccessful Application (n=105) Severe depressive symptoms on PHQ-9 Subclinical depressive symptoms on PHQ-9 7) Non-resident/under 18 years of age (n=8) Taking exclusion criteria medications (n=9) 115 individuals met inclusion criteria Could not contact (n = 14) 101 individuals completed telephone interview with MINI 5.0 Unsuccessful Telephone Interview (n=49) Subclinical (n = 17) Decided not to proceed (n = 10) No appropriate smartphone (n = 10) Recent commencement of CBT (n = 1) Completed similar e course (n=5) Changing medication/using exclusion medication (n = 6) 52 participants met all inclusion criteria and were randomized into T1 or T2 T1 – Mobile group (n = 22) T2 – Computer group (n = 30) Did not complete Pre- Did not complete Pre- Treatment Questionnaires Treatment (n=7) 9) Withdrawn (n=1) 15 completed Pre-Treatment Questionnaires 20 completed Pre-Treatment Questionnaires Eligible for analysis (started lesson 1), n = 15 Eligible for analysis (started lesson 1), n = 20 10 participants completed all lessons 14 participants completed all lessons (1 terminated at lesson 1, 1 at lesson 2, 2 at (2 terminated at lesson 1, 1 at lesson 3, 3 at lesson 4, 1 at lesson 5) lesson 5) 15 Completed Post-Treatment Questionnaires 10 Completed Post-Treatment Questionnaires Completed 3 month Follow Up Completed 3 month Follow Up Questionnaires, n=9 Questionnaires, n=14 Figure 1 Flow of participants through trial. inclusion criteria and an offer of participation made. The Diagnostic measure unsuccessful applicants (n=49) were advised about more Mini international neuropsychiatric interview version 5.0.0 appropriate treatment options. The study was approved (MINI) by the Human Research Ethics Committee (HREC) of St The MINI is a brief diagnostic interview developed to de- Vincent’s Hospital (Sydney, Australia) and the trial was termine the presence of a current and life-time Axis-1 dis- registered as ACTRN 12611001257954. order using DSM-IV diagnostic criteria. It has excellent Watts et al. BMC Psychiatry 2013, 13:49 Page 4 of 9 http://www.biomedcentral.com/1471-244X/13/49 inter-rater reliability (k=.88-1.00) and adequate concurrent validity with the Composite International Diagnostic Interview [22]. Description of treatment The Get Happy Program was based on the principles of CBT and is a version of the previously evaluated Sadness Program [11,12]. The program consisted of 6 lessons conducted over an 8 week period. The lessons read like a comic book and participants follow the story of Jess, a comic character that has depression, and through her story learn how she comes to manage her symptoms, and participants can then apply these principles to their own life. The size of the font was adapted for the mobile version and some minor revisions were made to the con- Figure 3 Screenshot of mobile version of program. tent of the program. On completion of each lesson, par- ticipants were assigned and encouraged to carry out the relevant homework activities and review the lesson. Additional resources, such as information on assertive- Clinician contact ness skills and sleep hygiene, and stories from previous Participants received emails/or phone calls from a clin- participant’s experiences were also available Figure 2, ician, until completion of Lesson 2 because our previous Figure 3. research study has found that additional clinician sup- port does not add any further benefit to participants [13]. Following this, the only clinical contact was when the participant initiated contact, or when a clinician instigated contact due to a deterioration in the K-10 score [23]. The K-10 is a measure of psychological dis- tress and was completed prior to beginning each lesson. Outcome measures The Patient Health Questionnaire-9 (PHQ-9) [24] is a brief 9-item self-report scale that measures each of the DSM-IV criteria for MDD with scores ranging from 0 to 27. Participants rate the frequency of symptoms over the last fortnight on a scale ranging from 0 (not at all) to 3 (nearly every day), where 1 = several days, 2 = more than half of the days. A PHQ-9 score of ≥10 is used as a clin- ical cut-off for probable DSM-IV diagnosis of MDD [25]. The PHQ-9 has been shown to have good sensitivity and specificity [26] and excellent reliability and validity [24]. The Kessler 10-item Psychological Distress scale (K-10) [23] is a measure of non-specific psychological distress over the past 14 days. Scores can range from 10 to 50, with higher scores indicating higher distress. The K-10 has good psychometric properties and can discriminate between cases and non-cases of DSM-IV affective disor- ders [27]. Beck’s Depression Inventory Second Edition (BDI-II) [28] consists of 21 items and is a measure of the presence and severity of a MDD based on the DSM-IV diagnostic cri- Figure 2 Screenshot of mobile program outlining available teria for depression. Scores range from 0 to 63 with higher options for mobile participants to review lesson, open scores indicating a greater severity of depression. The homework, access resources or read stories. BDI-II possesses excellent internal consistency [28]. Watts et al. BMC Psychiatry 2013, 13:49 Page 5 of 9 http://www.biomedcentral.com/1471-244X/13/49 Credibility/Expectancy Questionnaire (CEQ) [29] is a method used to implement marginal models when the scale for measuring treatment credibility and expectancy outcome variable is not normally distributed. The GEN- of improvement. At post treatment, 2 items based on LIN procedure with a repeated statement was implemen- the CEQ were asked including, how satisfied were you ted using SPSS Version 19. A poisson distribution with a with the skills that this program has taught you to man- log link function was specified. An unstructured covari- age your depression from 1 (not at all satisfied) to 9 ance structure was used to model the within-subject de- (very satisfied); how confident would you be in recom- pendencies. Initial models only included measurement mending this treatment to a friend who experiences occasion, study group and their interaction as fixed effects. similar problems from 1 (not at all confident) to 9 (very For each outcome measure, the two homework questions confident). were included separately in subsequent models to investi- Sheehan Disability Scale (SDS) [30] is a measurement gate whether any of the outcomes differed based on self- of functional disability and impairment due to psychi- reported homework effort or homework completion. atric symptoms and is self rated. The 2 items related to productivity were used for this study. The first item used Outcome measurement to measure absenteeism asked participants how many All participants completed the questionnaire outcome days in the last week their symptoms caused them to measures (BDI-II, PHQ-9, K-10, CEQ, ERS and SDS) at miss studies or work, or leave them unable to do their 1-week post treatment and at 3-months follow up. normal daily responsibilities. The second item used to measure presenteeism asked participants on how many Results days in the last week did they feel so impaired by their Baseline symptoms, that even though they studied, went to work The mean age of participants was 41 years (SD= 12.38, or worked at home, their productivity was reduced. range =18 - 63) and 28/35 were female (80% of the sam- ple). Participants reported on average, moderate depres- Environment rating scale (ERS) sion levels using the PHQ-9, severe levels of depression Three items were constructed to identify the location of on the BDI –II, and severe levels of psychological dis- where Mobile Group participants were completing the tress using the K-10. Participants reported on average lessons with options including: at home, at work, on a 2.14 days of work lost (SD= 2.19) and 4.40 days of work train or a bus, at a park or the beach, a café, or other. that were underproductive (SD= 2.15) due to the pres- The Mobile Group participants were also asked to rate ence of his/her psychiatric symptoms on the SDS (see how distracting the level of noise was from 1 (no dis- Table 1). tracting noise) to 4 (extremely distracting noise). Lastly, the Mobile Group participants were asked to rate their Baseline between-group comparisons ability to concentrate in this environment from 1 (poor) Independent samples t-tests compared the two groups on to 4 (excellent) (adapted from the Experience Sampling baseline demographic characteristics and pre-treatment Method, [20]). symptom questionnaires. There were no differences be- tween the groups on age, the BDI-II, PHQ-9, nor K-10. Homework rating scale (HRS) Two items were constructed to measure the amount of Adherence results effort and homework completion. The participant was 8.6% (3/35) completed only the first lesson, 2.9% (1/35) first asked how much effort they had put into the home- completed two lessons, 2.9% (1/35) completed 3 lessons, work from 0 (no effort) to 4 (complete effort); and how 5.7% (2/35) completed 4 lessons, 11.4% (4/35) completed much of the assigned homework they had finished from 5 lessons and 68.6% (24/35) of participants completed all 0 (none) to 4 (all). six lessons. Refer to Figure 1. When comparing the Mobile Group with the Computer Group on adherence, Statistical analysis there were no significant differences (t (33) = −.242, For the PHQ-9, K-10 and BDI-II analyses were con- P >.05). ducted using linear mixed-model repeated measures (MMRM) ANOVA with measurement occasion as a within-group factor and intervention as a between-groups Disorder-specific and generic outcome measures factor. These analyses were conducted using the MIXED Figure 4 displays mean PHQ-9 scores on each measure- procedure in SPSS Version 19 with an identity covariance ment occasion as a function of the two conditions. matrix. For the SDS generalised estimating equations Statistical tests showed that the benefits of the inter- (GEE) were used to evaluate reductions in absenteeism vention remained significant in both groups at follow up and presenteeism across time. GEE is a semi-parametric when using the PHQ-9 (F [3, 73.6] = 28.4, P=<.001), the Watts et al. BMC Psychiatry 2013, 13:49 Page 6 of 9 http://www.biomedcentral.com/1471-244X/13/49 Table 1 Baseline, mid, post-treatment estimated means, standard deviations, MMRM ANOVA, and effect sizes for outcome measures Pre- Mid- Post- Follow up Statistic Effect Size treatment treatment treatment Measure M (SD) M (SD) M (SD) M (SD) Pre to post Pre to post Pre to follow up Pre to follow up Within-subjects pre- post- Between group post (n=35) (n=30) (n=25) (n=23) within group between group within group between group treatment comparison for treatment (measurement (time by study (measurement (time by study treatment group (95% comparison (95% occasion) group interaction) occasion) group interaction) confidence intervals) confidence intervals) PHQ-9 Mobile 14.65 (1.37) 6.45 (1.51) 6.55 (1.51) 5.28 (1.63) F [2, 51.97] = F [2, 51.97] = 1.09, F [3, 73.6] = F [3, 73.6] = .875, 1.41 (.55-2.26) −0.47 (−0.47- 0.20) 33.22, P=<.001 P=.34 28.4, P=<.001 P=.458 PHQ-9 14.20 (1.62) 8.98 (1.24) 7.21 (1.26) 7.18 (1.32) .92 (.19-1.64) Computer BDI-II Mobile 33.46 (2.95) 12.53 (3.26) 11.66 (3.47) F [1, 25.55] = F [1, 25.55] = .41, F [2, 47.09] = F [2, 47.0] = 1.7, 1.79 (0.92-2.65) −0.37 (−1.05- 0.29) 86.02, P=.<.001 P=.52 60.1, P=.<.001 P=.19 BDI-II Computer 30.90 (2.55) 13.68 (2.79) 16.75 (2.85) 1.88 (1.14-2.62) K-10 Mobile 30.60 (2.06) 22.44 (2.21) 20.03 (2.21) 19.74 (2.31) F [6, 153.9] = F [6, 153.9] = .359, F [7, 1734.5] = F [7,174.91] = .370, 1.05 (.20-1.89) 0.03 (−0.63-0.70) 24.3,P=<.001) P=.90) 28.4, P=<.001) P=.919) K-10 Computer 30.15 (1.78) 24.12 (1.86) 19.95 (1.88) 19.55 (1.93) 1.22 (.52-1.92) SDS days lost 2.20 (.62) .74 (.42) Mobile SDS days lost 2.10 (.44) 1.15 (.37) Computer SDS days 4.13 (.54) 2.23 (.71) underproductive Mobile SDS days 4.25 (.47) 1.89 (.53) underproductive Computer Watts et al. BMC Psychiatry 2013, 13:49 Page 7 of 9 http://www.biomedcentral.com/1471-244X/13/49 to post-treatment. Effect sizes for these measures are Mobile included in Table 1. Computer Productivity outcome measures Statistical tests using the SDS showed a significant re- duction in the number of days lost (absenteeism) (Wald Chi-Square =10.31, P = <.05) and in the number of days underproductive (presenteeism) from pre-treatment to post-treatment (Wald Chi-Square =12.33, P = .001). Fur- ther results indicated that the interaction between ex- perimental group and time was not statistically significant 2 when comparing the SDS on absenteeism (Wald Chi- Square =.86, P = .35) and presenteeism (Wald Chi-Square =.22, P =.63). Pre-test Lesson 4 Post-test 3 month follow- up Figure 4 Estimated marginal means for PHQ-9 scores estimated Environment, distraction, and concentration measure- under occasion x intervention model. mobile group Descriptive data on the environment, level of distraction and ability to concentrate, was collected for participants in the Mobile Group. Over the six lessons, 66.7-92.9% of BDI-II (F [2, 47.09] = 60.1, <.001) and the K-10 (F [7, participants completed the lessons in their home, 46.7- 1734.5] = 28.4, P=<.001). 60% of participants completed these lessons when there Estimated marginal means for PHQ-9 scores estimated was slight distraction, and 30.8-53.3% endorsed an ‘okay’ under occasion x intervention model). ability to concentrate. Please refer to Table 2. Results from the MMRM (ANOVA) indicated that the interaction between experimental group and time was Clinical significance not statistically significant when comparing PHQ-9 At post-treatment, only 16/35 (45%) met criteria for de- scores (F [3, 73.6] = .875, P=.458), BDI-II scores (F [2, pression on the PHQ-9 (see Table 3 for results). 47.0] = 1.7, P=.19), or K-10 scores (F [7, 174.91] = .370, P=.919). Time spent per participant for both the mobile and In order to investigate differences between each occa- computer groups sion of measurement, a series of pair wise comparisons The mean clinician time spent per participant was were conducted. For the PHQ-9 and K-10 the change 4.1 minutes (SD= 4.63) and the mean technician time from baseline to mid-point, post-test, and 3-month follow spent per participant was 6.4 minutes (SD= 5.38). Each up was investigated. Significant reductions were found time a clinician or technician had contact with a partici- between baseline and all other time points for both the pant the amount of time was recorded to monitor the Mobile Group and Computer Group. This pattern was time required to deliver the program. repeated using the BDI-II, when investigating changes from baseline to post-test and 3-months follow up. Participant satisfaction Upon completion of the program 54% of Mobile Group Homework completion and effort and 64% of the Computer Group were very satisfied with The aggregated mean score for homework effort for the the program; with the remaining participants endorsing Mobile Group was 11.25 (range, 6–17) and 14.46 (range ‘somewhat satisfied’. 64% of the Mobile Group and 64% 9–20) for the Computer Group. An aggregated mean of the Computer Group would be very confident in score for homework completion for the Mobile Group recommending this treatment to a friend; and the re- was 11 (range, 8–16) and 12.4 (range 6–18) for the mainder endorsed ‘somewhat confident’. Computer Group. Results from the MMRM (ANOVA) indicated that there were no significant differences in Discussion homework completion or homework effort between the These results indicate that reductions in PHQ-9, the groups on the PHQ-9, the BDI-II, or the K-10. BDI-II and K-10 pre- to post-intervention and pre to follow up, were significant, regardless of experimental Effect sizes group. This provides preliminary support for the efficacy Large (>.8) within-group effect sizes were found on the of a CBT program delivered using a mobile phone. The BDI-II, PHQ-9 and K-10 measures from pre-treatment results, including the effect size, shown in this study are Watts et al. BMC Psychiatry 2013, 13:49 Page 8 of 9 http://www.biomedcentral.com/1471-244X/13/49 Table 2 Environment, levels of distraction, and levels of concentration for the Mobile Group Lesson 1 Lesson 2 Lesson 3 Lesson 4 Lesson 5 Lesson 6 Environment Home 13/ 15 (86.7%) 13/14 (92.9%) 9/13 (69.2%) 9/12 (75%) 9/11 (81.8%) 6/9 (66.7%) Work 0 0 2/13 (13.3%) 3/12 (25%) 1/11 (9.1%) 0 Train/bus 0 0 1/13 (6.7%) 0 0 2/9 (22.2%) Other 2/15 (13.3%) 1/14 (7.1%) 1/13 (6.7%) 0 1/11 (9.1%) 1 (11.1%) Missing data 0 1 2346 Level of distraction No distraction 5/15 (33.3%) 6/14 (42.9%) 5/13 (38.5%) 5/12 (41.7%) 4/11 (36.4%) 4/10 (40%) Slightly distraction) 7/15 (46.7%) 7/14 (50%) 7/13 (53.8) 5/12 (41.7%) 6/11 (54.5%) 6/10 (60%) Moderately distracting) 3/15 (20%) 1/14 (7.1%) 0 2/12 (16.6%) 1/11 (9.1%) 0 Extremely distracting 0 0 1/13 (7.7) 0 0 0 Missing data 0 1 2345 Ability to concentrate Poor 0 0 0000 Okay 8/15 (53.3%) 6/14 (42.9%) 4/13 (30.8%) 6/12 (50%) 5/11 (45.4%) 2/10 (20%) Good 4/15 (26.7%) 7/14 (50%) 5/13 (38.4%) 2/12 (16.6%) 4/11 (36.4%) 7/10 (70%) Excellent 3/15 (20%) 1/14 (7.1)% 4/13 (30.8%) 4/12 (33.4%) 2/11 (18.2%) 1/10 (10%) Missing data 0 1 2345 commensurate with our previous RCT’s [12,13], indicat- research could explore and compare this data to inform ing that using a mobile phone to offer this program recommendations as to the best placed environment for shows similar promise. patients to complete the program in order to obtain the There were a number of limitations to this study. Firstly, most optimal results. the small sample size necessitates replication, in order to The results of this pilot study indicate the usefulness reproduce the benefits identified in this study of delivering of replicating this study in the future research with a lar- a CBT program via a mobile phone or computer. Other ger sample size and control group. Minor additions to possible limitations include the self-selecting nature of the utilise the functionality available on a mobile phone/tab- sample. Those applying to complete treatment programs let are planned, for example, including the ability for using technology must be motivated; however, this does participants to set automated reminders in their calen- not make the results of this study invalid. A further limita- dar, and complete the homework on their phone/tablet. tion is the absence of a control group. A control group Data on the time of day and amount of usage for the would have provided the additional advantage of ensuring mobile users is also intended to be collected to under- the effects observed were able to be explained by the treat- stand if the increased proximity of the mobile, does lead ment. However, due to the small sample size of this study, to increased use, and greater benefits over time. Very lit- a control group was not included. Lastly, this study did tle is currently known about the possible benefits of not collect data on the environment, level of concentra- offering patient’s treatment programs using a mobile app tion and distractibility in the Computer Group. Future on their mobile phone, however, the ubiquity of mobile Table 3 PHQ-9 scores according to clinical cut-off ranges at pre- and post- treatment Pre treatment Post treatment PHQ-9 Severity Status Mobile (n=14) Computer (n=20) Mobile (n= 11) Computer (n= 16) None (0–9) 2/14 (14%) 2/20 (10%) 8/11 (73%) 10/16 (62%) Mild (10–14) 6/14 (43%) 11/20 (55%) 2/11 (18%) 4/16 (25%) Moderate (15–19) 4/14 (29%) 4/20 (20%) 1/11 (9%) 1/16 (6.5%) Severe (20+) 2/14 (14%) 3/20 (15%) 0 1/16 (6.5%) Missing Data 1 0 4 4 Meet criteria for MDD 12/14 (89%) 18/20 (90%) 3/11 (27%) 6/16 (37.5%) NB. Due to the time lag between recruitment and upon commencement of the program four participants did not meet criteria for MDD. Watts et al. BMC Psychiatry 2013, 13:49 Page 9 of 9 http://www.biomedcentral.com/1471-244X/13/49 apps, the growing community uptake and interest in this borderline personality disorder and substance Use of disorder. 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