Alliance With an Unguided Smartphone App: Validation of the Digital Working Alliance Inventory

Goldberg, Simon B.; Baldwin, Scott A.; Riordan, Kevin M.; Torous, John; Dahl, Cortland J.; Davidson, Richard J.; Hirshberg, Matthew J.

doi:10.1177/10731911211015310

Cited by 33 publications

(36 citation statements)

References 70 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, we hope our results sensitize both clinical trialists and meta-analysts to the importance of considering the comparison condition (for an exemplary meta-analytic treatment of comparison type, see Linardon et al [21]). This literature would be strengthened through more studies including active and ideally specific active controls which are capable of identifying key intervention ingredients and disentangling intervention-specific elements from the effect of expectancy and other non-specific factors alone (although these non-specific elements are likely an important component worthy of study in their own right [64,65]). The quality of the primary study literature would be improved through the use of objective measures (to reduce bias due to unblinded outcome assessors), use of intention-to-treat analyses (to reduce bias due to incomplete outcome data), and preregistration of outcomes (to reduce selective reporting bias).…”

Section: Plos Digital Healthmentioning

confidence: 99%

Mobile phone-based interventions for mental health: A systematic meta-review of 14 meta-analyses of randomized controlled trials

et al. 2022

Self Cite

View full text Add to dashboard Cite

Mobile phone-based interventions have been proposed as a means for reducing the burden of disease associated with mental illness. While numerous randomized controlled trials and meta-analyses have investigated this possibility, evidence remains unclear. We conducted a systematic meta-review of meta-analyses examining mobile phone-based interventions tested in randomized controlled trials. We synthesized results from 14 meta-analyses representing 145 randomized controlled trials and 47,940 participants. We identified 34 effect sizes representing unique pairings of participants, intervention, comparisons, and outcome (PICO) and graded the strength of the evidence as using umbrella review methodology. We failed to find convincing evidence of efficacy (i.e., n > 1000, p < 10−6, I2 < 50%, absence of publication bias); publication bias was rarely assessed for the representative effect sizes. Eight effect sizes provided highly suggestive evidence (i.e., n > 1000, p < 10−6), including smartphone interventions outperforming inactive controls on measures of psychological symptoms and quality of life (ds = 0.32 to 0.47) and text message-based interventions outperforming non-specific controls and active controls for smoking cessation (ds = 0.31 and 0.19, respectively). The magnitude of effects and strength of evidence tended to diminish as comparison conditions became more rigorous (i.e., inactive to active, non-specific to specific). Four effect sizes provided suggestive evidence, 14 effect sizes provided weak evidence, and eight effect sizes were non-significant. Despite substantial heterogeneity, no moderators were identified. Adverse effects were not reported. Taken together, results support the potential of mobile phone-based interventions and highlight key directions to guide providers, policy makers, clinical trialists, and meta-analysts working in this area.

show abstract

Section: Plos Digital Healthmentioning

confidence: 99%

Mobile phone-based interventions for mental health: A systematic meta-review of 14 meta-analyses of randomized controlled trials

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…Two studies measured the DTA using the WAI short form and one study measured DTA using the ARM. In addition, two measurements, the Mobile Agnew Relationship Measure (mARM) ( 48 ) and the Digital Working Alliance Inventory (DWAI) ( 49 ) have been proposed to measure the DTA in fully automated mental health apps. The mARM was created by replacing the word “therapist” with “app,” and adding, deleting, and rewording some questions based on qualitative feedback from both clients and healthcare professionals ( 48 ).…”

Section: Resultsmentioning

confidence: 99%

“…Only two identified studies examined the relationships between the DTA and clinical outcomes in the context of fully automated mental health apps, with mixed findings. Goldberg et al ( 49 ) assessed the DTA by using the DWAI in fully automated meditation apps and found that DWAI scores at weeks 3 or 4 only correlated with reductions in psychological distress (βs = −0.17 and −0.13). However, Clarke et al ( 14 ) examined the relationship between the DTA (measured by the ARM) and clinical outcomes with a fully automated mental health app, comprising educational modules and multiple other functions, and found no statistically significant correlation.…”

Section: Resultsmentioning

confidence: 99%

Digital Therapeutic Alliance With Fully Automated Mental Health Smartphone Apps: A Narrative Review

et al. 2022

View full text Add to dashboard Cite

Fully automated mental health smartphone apps show strong promise in increasing access to psychological support. Therefore, it is crucial to understand how to make these apps effective. The therapeutic alliance (TA), or the relationship between healthcare professionals and clients, is considered fundamental to successful treatment outcomes in face-to-face therapy. Thus, understanding the TA in the context of fully automated apps would bring us insights into building effective smartphone apps which engage users. However, the concept of a digital therapeutic alliance (DTA) in the context of fully automated mental health smartphone apps is nascent and under-researched, and only a handful of studies have been published in this area. In particular, no published review paper examined the DTA in the context of fully automated apps. The objective of this review was to integrate the extant literature to identify research gaps and future directions in the investigation of DTA in relation to fully automated mental health smartphone apps. Our findings suggest that the DTA in relation to fully automated smartphone apps needs to be conceptualized differently to traditional face-to-face TA. First, the role of bond in the context of fully automated apps is unclear. Second, human components of face-to-face TA, such as empathy, are hard to achieve in the digital context. Third, some users may perceive apps as more non-judgmental and flexible, which may further influence DTA formation. Subdisciplines of computer science, such as affective computing and positive computing, and some human-computer interaction (HCI) theories, such as those of persuasive technology and human-app attachment, can potentially help to foster a sense of empathy, build tasks and goals and develop bond or an attachment between users and apps, which may further contribute to DTA formation in fully automated smartphone apps. Whilst the review produced a relatively limited quantity of literature, this reflects the novelty of the topic and the need for further research.

show abstract

“…While we were not able to explicitly measure the therapeutic alliance construct within this work, the heterogeneity found across coaching modalities may suggest a lack of consensus regarding how to best foster a digital therapeutic alliance [ 48 ] between the patient and clinicians. Recent studies not captured in our sample have employed the Digital Working Alliance Inventory to measure alliance with apps and suggested that such an alliance may predict app engagement [ 49 ], highlighting the significance of future research and standardization around this concept.…”

Section: Discussionmentioning

confidence: 99%

Coaching to Support Mental Health Apps: Exploratory Narrative Review

Meyer¹,

Wisniewski²,

Torous³

2022

JMIR Hum Factors

Self Cite

View full text Add to dashboard Cite

Background The therapeutic alliance is crucial for the success of face-to-face therapies. Little is known about how coaching functions and fosters the therapeutic alliance in asynchronous treatment modalities such as smartphone apps. Objective The aim of this paper was to assess how coaching functions and fosters the therapeutic alliance in asynchronous treatment modalities. Methods We conducted a selected review to gather preliminary data about the role of coaching in mobile technology use for mental health care. We identified 26 trials using a 2019 review by Tønning et al and a 2021 scoping review by Tokgöz et al to assess how coaching is currently being used across different studies. Results Our results showed a high level of heterogeneity as studies used varying types of coaching methods but provided little information about coaching protocols and training. Coaching was feasible by clinicians and nonclinicians, scheduled and on demand, and across all technologies ranging from phone calls to social media. Conclusions Further research is required to better understand the effects of coaching in mobile mental health treatments, but examples offered from reviewed papers suggest several options to implement coaching today. Coaching based on replicable protocols that are verifiable for fidelity will enable the scaling of this model and a better exploration of the digital therapeutic alliance.

show abstract

Alliance With an Unguided Smartphone App: Validation of the Digital Working Alliance Inventory

Cited by 33 publications

References 70 publications

Mobile phone-based interventions for mental health: A systematic meta-review of 14 meta-analyses of randomized controlled trials

Mobile phone-based interventions for mental health: A systematic meta-review of 14 meta-analyses of randomized controlled trials

Digital Therapeutic Alliance With Fully Automated Mental Health Smartphone Apps: A Narrative Review

Coaching to Support Mental Health Apps: Exploratory Narrative Review

Contact Info

Product

Resources

About