The Influence of Human Support on Adherence to, and Outcomes of an Online Interdisciplinary Mental Health Promotion Intervention for a Healthy Adult Cohort

Escalating mental health distress has prompted the call for mental health promotion initiatives to improve the mental resilience of the general population and provide a buffer against common mental health disorders. Digital delivery modes offer accessible and scalable opportunities to implement lifestyle-based interventions to enhance mental well-being. However, digital interventions are hampered by sub-optimal adherence, which negatively impacts outcomes. Little is known about the effectiveness of human support to improve adherence to and outcomes of digital interventions amongst general population cohorts. This dissertation documents the rationale for and findings of a randomised comparative study that assessed the influence of adding different types of human support to an online, interdisciplinary mental health promotion intervention. Participants were randomised into three intervention groups: standard intervention with automated emails only (S); standard intervention plus personalised text messages (S+pSMS); and standard intervention plus videoconferencing support (S+VCS). A questionnaire was administered pre- and post-intervention to assess changes in depression, anxiety, stress, mental health, vitality, life satisfaction, and flourishing. Adherence was measured by the number of video lessons viewed, points scored for experiential activities, and the number of weeks that participants logged activity. Inductive, thematic analysis of free-text responses in the post-intervention questionnaire elicited participant perceptions about facilitators and barriers impacting adherence. The study results led to a series of three publications, which addressed the three research questions presented in the dissertation and a fourth publication that consolidated the findings and reviewed them in the context of the current literature. The first publication addressed Research Question 1—What is the influence of different modes of human support on the outcomes of a web and mobile app, lifestyle-based mental health intervention for a healthy adult cohort? This publication found that human support had little influence on the outcomes of the intervention. Significant improvements were recorded from baseline to post-intervention in every outcome measure, irrespective of the types of human support offered (P≤0.001). Between-group differences were not observed for any of the outcome measures: depression (P=0.93), anxiety (P=0.25), stress (P=0.57), mental health (P=0.77), vitality (P=0.65), life satisfaction (P=0.65), and flourishing (P=0.99). The second publication addressed Research Question 2—What is the influence of different modes of human support on attrition and adherence to a web and mobile app, lifestyle-based mental health intervention for a healthy adult cohort, including the influence of participant preference? Early dropout attrition differed between the groups (P=.009), being disproportionally higher in the videoconferencing support group. However, there was no difference in adherence behaviour between the groups (i.e., number of videos viewed, P=0.42; mean challenge points scored, P=0.71; and the number of weeks challenge points were logged, P=0.66), indicating that human support had little effect. The third publication addressed the final research question—What do healthy adult participants perceive as the facilitators of, and barriers to, adherence to a web and mobile app, lifestyle-based mental health intervention? Qualitative thematic analysis revealed that human support did not feature strongly as a facilitator or barrier to intervention adherence. Perceived adherence facilitators included engaging content, time availability, accessibility, enjoyable challenges, valuing the program, and personal motivation. Time scarcity was overwhelmingly perceived as the most dominant adherence barrier. Other barriers included completing and logging experiential activity, content length, technical difficulties, and interindividual personal factors. The study’s findings provided novel insights into an exposed research gap, as little was known about the influence of human support on adherence to and outcomes of a digital mental health promotion intervention when delivered to a general population group. The fourth publication, a review, synthesised the overall findings of this dissertation in conjunction with other recent literature and provided recommendations for future studies

Addressing the COVID-19 Mental Health Crisis: A Perspective on Using Interdisciplinary Universal Interventions

Mental health is reaching a crisis point due to the ramifications of COVID-19. In an attempt to curb the spread of the virus and circumvent health systems from being overwhelmed, governments have imposed regulations such as lockdown restrictions and home confinement. These restrictions, while effective for infection control, have contributed to poorer lifestyle behaviors. Currently, Positive Psychology and Lifestyle Medicine are two distinct but complimentary disciplines that offer an array of evidence-based approaches for promoting mental health and well-being across a universal population. However, these strategies for improving mental health are typically used in isolation. This perspective calls for a new paradigm shift to create and rollout well-designed interdisciplinary universal multicomponent mental health interventions that integrates the benefits of both disciplines, and uses innovative digital mental health solutions to achieve scalability and accessibility within the limitations and beyond the COVID-19 lockdown and restrictions.</jats:p

The Influence of Human Support on the Effectiveness of Digital Mental Health Promotion Interventions for the General Population

Mental wellbeing amongst the general population is languishing—exacerbated by the Coronavirus Disease 2019 (COVID-19) pandemic. Digital mental health promotion interventions, that improve mental health literacy and encourage adoption of evidence-informed practical strategies are essential. However, attrition and non-adherence are problematic in digital interventions. Human support is often applied as an antidote; yet, there is a paucity of randomized trials that compare different human support conditions amongst general population cohorts. Limited trials generally indicate that human support has little influence on adherence or outcomes in DMHPIs. However, providing participants autonomy to self-select automated support options may enhance motivation and adherence.</jats:p

Participant Perceptions of Facilitators and Barriers to Adherence in a Digital Mental Health Intervention for a Nonclinical Cohort: Content Analysis (Preprint)

BACKGROUND Digital mental health promotion interventions (MHPIs) present a scalable opportunity to attenuate the risk of mental health distress among nonclinical cohorts. However, adherence is frequently suboptimal, and little is known about participants’ perspectives concerning facilitators and barriers to adherence in community-based settings. OBJECTIVE This study aimed to examine participants’ perceptions of facilitators and barriers to adherence in a web- and mobile app–based MHPI for a nonclinical cohort. METHODS This qualitative study used inductive, reflexive thematic analysis to explore free-text responses in a postintervention evaluation of a 10-week digital MHPI. The intervention was administered using a web and mobile app from September to December 2018. Participants (N=320) were Australian and New Zealand members of a faith-based organization who self-selected into the study, owned a mobile phone with messaging capability, had an email address and internet access, were fluent in English, provided informed consent, and gave permission for their data to be used for research. The postintervention questionnaire elicited participants’ perceptions of facilitators and barriers to adherence during the intervention period. RESULTS Key factors that facilitated adherence were engaging content, time availability and management, ease of accessibility, easy or enjoyable practical challenges, high perceived value, and personal motivation to complete the intervention. The primary perceived barrier to adherence was the participants’ lack of time. Other barriers included completing and recording practical activities, length of video content, technical difficulties, and a combination of personal factors. CONCLUSIONS Time scarcity was the foremost issue for the nonclinical cohort engaged in this digital MHPI. Program developers should streamline digital interventions to minimize the time investment for participants. This may include condensed content, optimization of intuitive web and app design, simplified recording of activities, and greater participant autonomy in choosing optional features. Nonetheless, participants identified a multiplicity of other interindividual factors that facilitated or inhibited adherence. </sec

Participant Perceptions of Facilitators and Barriers to Adherence in a Digital Mental Health Intervention for a Nonclinical Cohort: Content Analysis

Background Digital mental health promotion interventions (MHPIs) present a scalable opportunity to attenuate the risk of mental health distress among nonclinical cohorts. However, adherence is frequently suboptimal, and little is known about participants’ perspectives concerning facilitators and barriers to adherence in community-based settings. Objective This study aimed to examine participants’ perceptions of facilitators and barriers to adherence in a web- and mobile app–based MHPI for a nonclinical cohort. Methods This qualitative study used inductive, reflexive thematic analysis to explore free-text responses in a postintervention evaluation of a 10-week digital MHPI. The intervention was administered using a web and mobile app from September to December 2018. Participants (N=320) were Australian and New Zealand members of a faith-based organization who self-selected into the study, owned a mobile phone with messaging capability, had an email address and internet access, were fluent in English, provided informed consent, and gave permission for their data to be used for research. The postintervention questionnaire elicited participants’ perceptions of facilitators and barriers to adherence during the intervention period. Results Key factors that facilitated adherence were engaging content, time availability and management, ease of accessibility, easy or enjoyable practical challenges, high perceived value, and personal motivation to complete the intervention. The primary perceived barrier to adherence was the participants’ lack of time. Other barriers included completing and recording practical activities, length of video content, technical difficulties, and a combination of personal factors. Conclusions Time scarcity was the foremost issue for the nonclinical cohort engaged in this digital MHPI. Program developers should streamline digital interventions to minimize the time investment for participants. This may include condensed content, optimization of intuitive web and app design, simplified recording of activities, and greater participant autonomy in choosing optional features. Nonetheless, participants identified a multiplicity of other interindividual factors that facilitated or inhibited adherence. </jats:sec

The Influence of Three Modes of Human Support on Attrition and Adherence to a Web- and Mobile App–Based Mental Health Promotion Intervention in a Nonclinical Cohort: Randomized Comparative Study

Background The escalating prevalence of mental health disorders necessitates a greater focus on web- and mobile app–based mental health promotion initiatives for nonclinical groups. However, knowledge is scant regarding the influence of human support on attrition and adherence and participant preferences for support in nonclinical settings. Objective This study aimed to compare the influence of 3 modes of human support on attrition and adherence to a digital mental health intervention for a nonclinical cohort. It evaluated user preferences for support and assessed whether adherence and outcomes were enhanced when participants received their preferred support mode. Methods Subjects participated in a 10-week digital mental health promotion intervention and were randomized into 3 comparative groups: standard group with automated emails (S), standard plus personalized SMS (S+pSMS), and standard plus weekly videoconferencing support (S+VCS). Adherence was measured by the number of video lessons viewed, points achieved for weekly experiential challenge activities, and the total number of weeks that participants recorded a score for challenges. In the postquestionnaire, participants ranked their preferred human support mode from 1 to 4 (S, S+pSMS, S+VCS, S+pSMS &amp; VCS combined). Stratified analysis was conducted for those who received their first preference. Preintervention and postintervention questionnaires assessed well-being measures (ie, mental health, vitality, depression, anxiety, stress, life satisfaction, and flourishing). Results Interested individuals (N=605) enrolled on a website and were randomized into 3 groups (S, n=201; S+pSMS, n=202; S+VCS, n=201). Prior to completing the prequestionnaire, a total of 24.3% (147/605) dropped out. Dropout attrition between groups was significantly different (P=.009): 21.9% (44/201) withdrew from the S group, 19.3% (39/202) from the S+pSMS group, and 31.6% (64/202) from the S+VCS group. The remaining 75.7% (458/605) registered and completed the prequestionnaire (S, n=157; S+pSMS, n=163; S+VCS, n=138). Of the registered participants, 30.1% (138/458) failed to complete the postquestionnaire (S, n=54; S+pSMS, n=49; S+VCS, n=35), but there were no between-group differences (P=.24). For the 69.9% (320/458; S, n=103; S+pSMS, n=114; S+VCS, n=103) who completed the postquestionnaire, no between-group differences in adherence were observed for mean number of videos watched (P=.42); mean challenge scores recorded (P=.71); or the number of weeks that challenge scores were logged (P=.66). A total of 56 participants (17.5%, 56/320) received their first preference in human support (S, n=22; S+pSMS, n=26; S+VCS, n=8). No differences were observed between those who received their first preference and those who did not with regard to video adherence (P=.91); challenge score adherence (P=.27); or any of the well-being measures including, mental health (P=.86), vitality (P=.98), depression (P=.09), anxiety (P=.64), stress (P=.55), life satisfaction (P=.50), and flourishing (P=.47). Conclusions Early dropout attrition may have been influenced by dissatisfaction with the allocated support mode. Human support mode did not impact adherence to the intervention, and receiving the preferred support style did not result in greater adherence or better outcomes. Trial Registration Australian New Zealand Clinical Trials Registry (ANZCTR): 12619001009101; http://www.anzctr.org.au/ACTRN12619001009101.aspx </jats:sec

The Influence of Three Modes of Human Support on Attrition and Adherence to a Web- and Mobile App–Based Mental Health Promotion Intervention in a Nonclinical Cohort: Randomized Comparative Study (Preprint)

BACKGROUND The escalating prevalence of mental health disorders necessitates a greater focus on web- and mobile app–based mental health promotion initiatives for nonclinical groups. However, knowledge is scant regarding the influence of human support on attrition and adherence and participant preferences for support in nonclinical settings. OBJECTIVE This study aimed to compare the influence of 3 modes of human support on attrition and adherence to a digital mental health intervention for a nonclinical cohort. It evaluated user preferences for support and assessed whether adherence and outcomes were enhanced when participants received their preferred support mode. METHODS Subjects participated in a 10-week digital mental health promotion intervention and were randomized into 3 comparative groups: standard group with automated emails (S), standard plus personalized SMS (S+pSMS), and standard plus weekly videoconferencing support (S+VCS). Adherence was measured by the number of video lessons viewed, points achieved for weekly experiential challenge activities, and the total number of weeks that participants recorded a score for challenges. In the postquestionnaire, participants ranked their preferred human support mode from 1 to 4 (S, S+pSMS, S+VCS, S+pSMS &amp;amp; VCS combined). Stratified analysis was conducted for those who received their first preference. Preintervention and postintervention questionnaires assessed well-being measures (ie, mental health, vitality, depression, anxiety, stress, life satisfaction, and flourishing). RESULTS Interested individuals (N=605) enrolled on a website and were randomized into 3 groups (S, n=201; S+pSMS, n=202; S+VCS, n=201). Prior to completing the prequestionnaire, a total of 24.3% (147/605) dropped out. Dropout attrition between groups was significantly different (&lt;i&gt;P&lt;/i&gt;=.009): 21.9% (44/201) withdrew from the S group, 19.3% (39/202) from the S+pSMS group, and 31.6% (64/202) from the S+VCS group. The remaining 75.7% (458/605) registered and completed the prequestionnaire (S, n=157; S+pSMS, n=163; S+VCS, n=138). Of the registered participants, 30.1% (138/458) failed to complete the postquestionnaire (S, n=54; S+pSMS, n=49; S+VCS, n=35), but there were no between-group differences (&lt;i&gt;P&lt;/i&gt;=.24). For the 69.9% (320/458; S, n=103; S+pSMS, n=114; S+VCS, n=103) who completed the postquestionnaire, no between-group differences in adherence were observed for mean number of videos watched (&lt;i&gt;P&lt;/i&gt;=.42); mean challenge scores recorded (&lt;i&gt;P&lt;/i&gt;=.71); or the number of weeks that challenge scores were logged (&lt;i&gt;P&lt;/i&gt;=.66). A total of 56 participants (17.5%, 56/320) received their first preference in human support (S, n=22; S+pSMS, n=26; S+VCS, n=8). No differences were observed between those who received their first preference and those who did not with regard to video adherence (&lt;i&gt;P&lt;/i&gt;=.91); challenge score adherence (&lt;i&gt;P&lt;/i&gt;=.27); or any of the well-being measures including, mental health (&lt;i&gt;P&lt;/i&gt;=.86), vitality (&lt;i&gt;P&lt;/i&gt;=.98), depression (&lt;i&gt;P&lt;/i&gt;=.09), anxiety (&lt;i&gt;P&lt;/i&gt;=.64), stress (&lt;i&gt;P&lt;/i&gt;=.55), life satisfaction (&lt;i&gt;P&lt;/i&gt;=.50), and flourishing (&lt;i&gt;P&lt;/i&gt;=.47). CONCLUSIONS Early dropout attrition may have been influenced by dissatisfaction with the allocated support mode. Human support mode did not impact adherence to the intervention, and receiving the preferred support style did not result in greater adherence or better outcomes. CLINICALTRIAL Australian New Zealand Clinical Trials Registry (ANZCTR): 12619001009101; http://www.anzctr.org.au/ACTRN12619001009101.aspx </sec

A Web- and Mobile App–Based Mental Health Promotion Intervention Comparing Email, Short Message Service, and Videoconferencing Support for a Healthy Cohort: Randomized Comparative Study

BackgroundThe rapid increase in mental health disorders has prompted a call for greater focus on mental health promotion and primary prevention. Web- and mobile app–based interventions present a scalable opportunity. Little is known about the influence of human support on the outcomes of these interventions.ObjectiveThis study aimed to compare the influence of 3 modes of human support on the outcomes (ie, mental health, vitality, depression, anxiety, stress, life satisfaction, and flourishing) of a 10-week, Web- and mobile app–based, lifestyle-focused mental health promotion intervention among a healthy adult cohort.MethodsParticipants were recruited voluntarily using a combination of online and offline advertising. They were randomized, unblinded into 3 groups differentiated by human support mode: Group 1 (n=201): standard—fully automated emails (S); Group 2 (n=202): standard plus personalized SMS (S+pSMS); and Group 3 (n=202): standard plus weekly videoconferencing support (S+VCS), hosted by 1 trained facilitator. Participants accessed the intervention, including the questionnaire, on a Web-based learning management system or through a mobile app. The questionnaire, administered at pre- and postintervention, contained self-reported measures of mental well-being, including the “mental health” and “vitality” subscales from the Short Form Health Survey-36, Depression Anxiety and Stress Scale-21, Diener Satisfaction With Life Scale (SWLS), and Diener Flourishing Scale.ResultsOf 605 potential participants, 458 (S: n=157, S+pSMS: n=163, and S+VCS: n=138) entered the study by completing registration and the preintervention questionnaire. At post intervention, 320 out of 458 participants (69.9%; S: n=103, S+pSMS: n=114, and S+VCS: n=103) completed the questionnaire. Significant within-group improvements were recorded from pre- to postintervention in all groups and in every outcome measure (P≤.001). No significant between-group differences were observed for outcomes in any measure: mental health (P=.77), vitality (P=.65), depression (P=.93), anxiety (P=.25), stress (P.57), SWLS (P=.65), and Flourishing Scale (P=.99). Adherence was not significantly different between groups for mean videos watched (P=.42) and practical activity engagement (P=.71). Participation in videoconference support sessions (VCSSs) was low; 37 out of 103 (35.9%) participants did not attend any VCSSs, and only 19 out of 103 (18.4%) attended 7 or more out of 10 sessions. Stratification within the S+VCS group revealed that those who attended 7 or more VCSSs experienced significantly greater improvements in the domains of mental health (P=.006; d=0.71), vitality (P=.005; d=0.73), depression (P=.04; d=0.54), and life satisfaction (P=.046; d=0.50) compared with participants who attended less than 7.ConclusionsA Web- and mobile app–based mental health promotion intervention enhanced domains of mental well-being among a healthy cohort, irrespective of human support. Low attendance at VCSSs hindered the ability to make meaningful between-group comparisons. Supplementing the intervention with VCSSs might improve outcomes when attendance is optimized.Trial RegistrationAustralian New Zealand Clinical Trials Registry (ANZCTR): 12619001009101; http://www.anzctr.org.au/ACTRN12619001009101.aspx</jats:sec