Self Help Apps: Promoting Wellbeing in Young Adults

The topic of mental wellbeing among young individuals is becoming increasingly critical, not only in the UK but globally. Numerous studies have examined the effectiveness of universal interventions aimed at helping young people maintain their mental wellness and prevent mental health issues. Regrettably, current research indicates that these universal interventions have not been successful in enhancing the wellbeing of this demographic. For further insights, refer to Soffia’s recent blog on universal Dialectical Behavior Therapy (DBT) interventions implemented in educational settings.

According to an Ofcom report released in 2023, an alarming 90% of children possess a mobile phone by age 11 and the figure rises to 98% of 16-to-17-year-olds owning a smartphone. This trend raises concerns about the potential link between smartphone usage and the rising rates of anxiety and depression among teenagers (Haidt, 2024). However, could it be possible that smartphones might also offer solutions to these mental health challenges?

Research on smartphone apps designed for mental health has generally been limited to small-scale trials, often involving fewer than 100 participants, which raises questions regarding their reliability. Recently, Watkins et al. (2024a; 2024b) published findings from a comprehensive large-scale randomized controlled trial (RCT) that investigated the preventative effects of the ECoWeB PREVENT app on at-risk youth and the promotive effects of the ECoWeB PROMOTE app on healthy young adults.

Research Design and Methodology for ECoWeB Trials

This study employed an international, multi-center, parallel, open-label randomized controlled trial (RCT) across four locations in the UK, Germany, Spain, and Belgium. This trial utilized a cohort multiple RCT design, wherein participants completed an emotional competence profile at baseline. Those identified as low-risk were assigned to the ECoWeB PROMOTE group, while individuals classified as high-risk were directed to the ECoWeB PREVENT group. Risk was determined based on scores in the lowest quartile for metrics including rumination, worry, achievement appraisals, and rejection sensitivity.

Participants were excluded from the study if they had previously experienced a major depressive disorder or presented with current symptoms. Additional exclusion criteria included:

• Active suicidality
• A self-reported history of severe mental health disorders, including bipolar disorder and psychosis
• Currently undergoing psychological therapy, counseling, or receiving psychiatric medications such as antidepressants
• Demonstrated elevated vulnerability on the emotional competence profile based on the initial assessment of emotional competence skills

Within the scope of each RCT, participants were randomly assigned to receive standard care alongside one of the following:

• An emotional competence app;
• A cognitive-behavioral therapy (CBT) app; or
• A self-monitoring app

All assessors and statisticians were blinded to the treatment allocations. Participants were followed up for a duration of 12 months, with clinical rating scales administered at both 3-month and 12-month intervals.

Clinical Assessment Scales		PROMOTE	PREVENT
Warwick-Edinburgh Mental Well Being Scale (WEMWBS)	Wellbeing	3 and 12 months	12 months
Primary Health Questionnaire-9 (PHQ-9)	Depression	12 months	3 and 12 months
Generalised Anxiety Disorder Scale-7 (GAD-7)	Anxiety	12 months	12 months
Work and Social Adjustment Scale (WSAS)	Social, home, and work or academic functioning	12 months	12 months
EQ-5D-3 Levels (EQ-5D-3L)	Health-related quality of life	12 months	12 months

Key Findings from the ECoWeB Trials

Demographic Overview of Participants

Between October 15th, 2020, and August 3rd, 2021, a total of 21,277 individuals aged between 16 and 22 were screened. Out of these, 10,030 completed the baseline assessment, and 3,794 were identified as eligible for the ECoWeB cohorts.

	ECoWeB PROMOTE	ECOWeB PREVENT
N	2,532	1,264
Mean age	19.2 (SD = 1.8)	18.8 (SD = 2.0)
Gender	1,896 (75%) female, 613 (24%) male	984 (78%) female, 253 (20%) male
Ethnicity	2,203 White (87%) 135 Mixed (5%) 99 Asian (4%) 25 Black (1%) 22 Arab (1%)	1,060 White (84%) 79 Mixed (6%) 63 Asian (5%) 22 Black (2%) 11 Arab (1%)
UK	766 (30%)	418 (33%)
Germany	868 (34%)	229 (18%)
Spain	416 (17%)	437 (35%)
Belgium	482 (19%)	178 (14%)
Emotional Competence app	847	417
CBT app	841	423
Self-monitoring app	844	422

Evaluation of Results for PROMOTE Group

3-month follow-up:

• No significant difference in mental wellbeing was observed between the emotional competence app and the CBT app (mean difference WEMWBS = -0.21 [95% CI –1.08 to 0.66]).
• Mental wellbeing also showed no significant difference between the emotional competence app and the self-monitoring app (0.32 [–0.54 to 1.19]).
• Similarly, no significant difference was found between the CBT app and the self-monitoring app (0.53 [–0.33 to 1.39]).

12-month follow-up:

• At this stage, mental wellbeing was lower for the emotional competence app compared to the CBT app (mean difference WEMWBS = 1.17 [95% CI –2.11 to –0.24]), although this difference was not clinically significant.
• No significant difference in mental wellbeing emerged between the emotional competence app and the self-monitoring app (–0.76 [–1.69 to 0.18]).
• Likewise, no significant difference was found between the CBT app and the self-monitoring app (0.42 [–0.51 to 1.34]).

The outcomes for secondary evaluations closely mirrored those of the primary outcome, indicating no significant global differences among the three groups at either the 3-month or 12-month follow-up.

Evaluation of Results for PREVENT Group

3-month follow-up:

• Depression symptoms displayed a significant decrease when comparing the CBT app to the self-monitoring app (mean difference in PHQ-9 = –1.18 [95% CI –2.01 to –0.34]; p = .006).
• No significant difference in depression symptoms was found between the emotional competence app and the CBT app (0.63 [–0.22 to 1.49]; p = .15).
• Similarly, no significant differences were found between the emotional competence app and the self-monitoring app (–0.54 [–1.39 to 0.31]; p = .21).
• PHQ-9 scores indicated a lower incidence of symptoms with the CBT app (59 [31%] of 191) compared to the self-monitoring app (85 [43%] of 199; odds ratio [OR] = 0.50 [95% CI 0.31 to 0.81]).
• Interestingly, PHQ-9 scores were higher with the emotional competence app (69 [39%] of 178) compared to the CBT app (1.63 [1.01 to 2.64]; number needed to treat [NNT] = 8.33). Depression scores did not differ significantly between the emotional competence app and the self-monitoring app (0.82 [0.52 to 1.30]).
• Moreover, work and academic/social functioning and health-related quality of life were found to be superior in the CBT app group compared to the self-monitoring group.
• Lastly, no notable benefits were observed with the emotional competence app in relation to the self-monitoring app.

Throughout both the 3-month and 12-month follow-ups, no significant differences were detected among the groups regarding anxiety (GAD-7) or wellbeing (WEMWBS). At the 12-month mark, no significant differences were noted among any of the groups.

Key Insights from the ECoWeB Studies

The findings from the ECoWeB PROMOTE trial indicated that there was no added advantage of using the emotional competence app or the CBT app compared to the self-monitoring app for promoting mental wellbeing.

On the other hand, the ECoWeB PREVENT trial highlighted that a generic CBT self-help app showed protective benefits for depression symptoms, functionality, and quality of life among young individuals who are at increased risk for developing depression.

Importantly, the emotional competence app did not prove to be more effective than either the CBT app or the self-monitoring app.

Strengths, Limitations, and Future Directions

The strengths of this study are evident in its utilization of a robust RCT model. Additionally, recruitment from various European nations enhances the generalizability of the findings. The targeted age group of 16-22 years is particularly relevant for practical applications of the results. Furthermore, the blinding of all assessors and statisticians minimizes bias, contributing to the study’s reliability.

However, the absence of a ‘usual care’ control intervention is a noted limitation, which is often a standard element in RCTs. Yet, employing a self-monitoring control may have mitigated some of the variability and inconsistencies that a ‘usual care’ condition could introduce. While the authors consider this a limitation, it might actually represent a strength.

Despite the initial large sample sizes, a significant limitation arose from the declining compliance rates with the app and substantial attrition rates during follow-up. Approximately 80% of participants signed up for the app, yet the overall follow-up attrition rate was 47.8% [95% CI 35.8 to 60.0]. The authors noted that such attrition is common in app-based studies, maintaining that sufficient participants remained for ‘conservative estimates.’ However, this speaks volumes about the acceptability of the intervention.

The generalizability of these results is further constrained by the demographic composition of the study population, which was predominantly White, female, and enrolled in university education. The selection process incorporated various recruitment strategies, including online advertising, social media campaigns, newsletters, and campus noticeboards, to maximize participant engagement. However, the final follow-up demographics were not reported, which could have been insightful, especially if there were notable differences.

This study focused on self-help apps, and while the suggestion of increased human involvement could enhance uptake is valid, such a change would substantially alter the study’s design, costs, and logistical capacity.

Practical Implications and Future Research Directions

The findings from this research contribute to a growing body of evidence suggesting that efforts to mitigate the global burden of poor mental health among young people may be more effectively directed towards prevention strategies aimed at selective and indicated at-risk populations, rather than relying solely on universal initiatives to promote mental wellbeing.

One significant takeaway from this study is the emphasis on the advantages of the CBT app. The app is characterized as being automated, scalable, non-consumable, and cost-effective – which raises the possibility of transforming it into a public mental health intervention to reach a wider audience.

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