Personalized and collaborative use of digital measurement-based care tools enhances engagement among young adults: a mixed-methods study

Abstract

Background

Measurement-based care (MBC) enables personalised and proactive mental healthcare through regular symptom monitoring and review, allowing clinicians to make timely adjustments to clients’ interventions for improved outcomes. Yet, its uptake in youth mental health services remains minimal. This study aims to explore perceived barriers and facilitators for sustained use of MBC and potential of digital technologies to enhance its engagement in young adults.

Methods

A mixed-methods study, comprising focus groups and surveys, was conducted with young adults who had previously accessed mental health services. Template analysis was used to analyze qualitative data, and descriptive analyses were performed with quantitative data.

Results

Eighteen young adults (mean age = 21.7 years; SD = 3.4) participated in this study. Survey results showed that young adults agreed with the value of MBC in their care (15/18) and reported low rates of discomfort with progress evaluation (11/18). Focus groups revealed collaborative data review with clinicians as a key facilitator in MBC uptake, driving repeated engagement with data input and review. Participants expressed that generalized interpretation of data that does not consider individual context, and the use of standard measures that were perceived to be irrelevant to their personal treatment goals discouraged their future engagement with MBC. Digital features that improve accessibility and data interpretation were expected to enhance consistent engagement with MBC.

Conclusions

The findings indicate that the motivation and sustained engagement in MBC stem from young adults’ comprehension of how collected data fosters shared decision-making and personalize treatment. Therefore, regular, collaborative data reviews would be crucial in cultivating a sense of autonomy and purpose within MBC for young adults. This study highlights the importance of data review in enhancing the uptake of MBC, a factor that is often overlooked. By demonstrating this, the study provides a deeper understanding of motivators in MBC and valuable insights for mental health services to explore strategies that could support clinicians to integrate data review as part of routine care. To this end, one effective approach could be developing technologies that facilitate client-clinician communication and empower young adults to advocate for personalized care.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-025-12889-1.

Introduction

The increasing prevalence of mental health disorders among young adults is alarming. These disorders are characterized by heterogenous and complex symptom presentations, varying in degrees of physical comorbidities [1–3]. Pertinent to the multidimensional needs in youth, measurement-based care (MBC) has been evidenced as an effective care model that facilitates proactive and personalized mental healthcare through iterative processes of symptom monitoring and review, facilitating timely response to clients’ evolving needs in care [4–6]. MBC consists of three components: (a) regular collection of self-reported data; (b) collaborative review of data between clinicians and clients; and (c) use of data to inform treatment decision-making. These three components of MBC are designed to improve overall treatment outcomes by facilitating data-informed clinical judgments [7, 8], and minimizing the limitations of clinical intuition [9], and reducing therapeutic variability between clinicians [10]. Evidence suggests that MBC reduces symptom severity, enhances treatment engagement and efficiency, and improves therapeutic alliance [6, 11–13]. In particular, it was especially effective for individuals who were “not on track”, as the regular monitoring and feedback loop allowed clinicians to identify the stagnant process early in treatment and rapidly adapt interventions accordingly [14, 15].

Recent developments of digital technologies has elevated accessibility and effectiveness of MBC. Digital tools ease access to symptom-tracking measures for clients, and promptly analyze and interpret collected data for clinician and clients to review. Further, studies show that machine learning models integrated into digital MBC tools can improve diagnosis and prognosis of clients’ illness trajectories based on collected within-individual data [16, 17]. However, despite its evidenced clinical value, the uptake of MBC in clinical practice is suboptimal and conducted with poor fidelity [18–21].

The challenges of digital MBC implementation occur at individual, clinician, and organizational levels. For organizations, staff training and integration of a digital MBC tool into an existing database have been found to be challenging [22]. Common barriers for clinicians are time constraints [23], cost, and negative attitudes towards the use of standard measures [24, 25]. Lastly, clients’ concerns include data privacy, limited capacity of standard measures to provide a holistic representation of mental health, and risks associated with how the data may be used to limit their access to treatments [26, 27]. Notably, the uncertainty around the use of collected data was a common barrier for clients who engaged with MBC [21, 27]. Previous research indicates that while more frequent use of feedback led to greater treatment outcomes [10, 28], review and utilization of data were inconsistently conducted even during clinical trials [29, 30]. Collaborative review of clients' progress data is essential as this component of MBC provides opportunities for personalization of treatment and encourages shared decision-making [13]. Furthermore, it facilitates discussions on clients’ personal goals and needs in care which have been shown to enhance client engagement in MBC overall [21, 31–33]. Patient-centered and personalized care fostered during data review is especially important for young adults who value autonomy and collaboration in mental healthcare [32, 34].

Therefore, this study aims to evaluate young adults’ expectations on the use of MBC in youth mental health services [35] by identifying perceived facilitators and barriers of MBC to enhance its uptake and fidelity, which is currently underexplored. Further, the study seeks to create a deeper understanding of realization and implementation of digital solutions that are posed to enhance engagement and integration of MBC as part of young adults’ mental healthcare.

Methods

Study design and setting

This study was conducted in two phases, at the Brain and Mind Centre of The University of Sydney, Australia. In the first phase, focus groups were conducted to discuss potential factors that influence MBC engagement among young adults. In the second phase, post-workshop surveys were administered to focus group participants (FGPs) to further explore their perspectives on MBC and the role of digital technology as part of their mental healthcare. Acknowledging that sharing in group settings may not be ideal for all participants, a mixed-methods approach was chosen to enable safe and comfortable participation for all [36].

Participants and recruitment

The study was advertised via posters and student newsletters at the University of Sydney and used a snowball sampling strategy. The recruitment was done passively where potential participants could freely contact the coauthor MKC. All individuals aged between 18 and 30 years with a help-seeking history at mental health services were invited to participate in the study. Those who expressed interest were provided with detailed information on the study. All participants provided informed consent to participate.

Data collection

Focus groups

Focus groups are a qualitative research methodology that allows participants to express and build on each other’s perspectives [32, 37]. Compared to a one-on-one interview, the power imbalance between facilitators and attendees can be minimized in a group discussion, making it particularly appropriate for young adults [38].

Four focus groups were conducted between August and October 2022, facilitated by two co-authors (MKC and FI). The first focus group was conducted in a hybrid format (in-person and online via Zoom) to accommodate participants’ preferences. However, technical difficulties, including lag and poor audio quality, hindered smooth interaction between in-person and online attendees. While online participants engaged via chat and comments, facilitators found the hybrid format less effective. Consequently, subsequent focus groups were conducted in either in-person or online format, resulting in two online and one in-person focus groups.

As group discussions can lead to personal and distressful topics, at least one clinical psychologist (SM or MA) was available to provide mental health support upon request. Focus groups were conducted until data saturation was reached. All participants received a financial reimbursement for their time.

The focus group agenda and discussion questions were developed based on existing literature [32] and in consultation with young adults from the Brain and Mind Centre Lived Experience Working Group. This group consisted of culturally and linguistically diverse young adults (aged 16–30) with lived experience of mental illness [39]. This collaborative process aimed to foster a safe and open environment, identify potential gaps, and ensure the content was appropriate for the target audience [40]. Three Working Group members who wished to participate joined one of the focus groups after providing informed consent. Additionally, room agreements were collaboratively established at the beginning of each session to create a safe space for participants to express their opinions [41]. The study goals were clearly communicated during the focus groups to maintain transparency [42].

The focus groups were structured as follows. First, an introduction and ice-breaking activity were conducted to create a safe and comfortable environment for participants [41]. Then, a presentation on MBC was provided for participants to familiarise themselves with the purpose, values, and processes of MBC prior to discussing its potential barriers and facilitators. Finally, a group discussion was conducted, guided by the question schedule (Table 1).

Table 1.

Focus group question schedule

Questions
· Do you have experience with tracking in general (e.g. steps, sleep, nutrition)?
·  What facilitated your regular use of the system?
·  What are the motivating or demotivating factors for young adults to routinely monitor their symptoms?
·  What are the motivating or demotivating factors for young adults to review and discuss the collected data with therapist?
·  Which digital features do you think will facilitate the use of MBC?
·  What are the 3 essential factors for sustained use of MBC in mental healthcare?

Surveys

After each focus group, a survey was distributed to FGPs via either pen and paper or an online survey software Qualtrics. The survey collected FGPs’ demographic characteristics, perceptions of MBC, and expectations of the role of technology within mental health care. As some young adults may feel anxious to openly express their honest opinions in a group environment, the survey may have served as a preferred medium for participants to articulate their opinions privately [43, 44]. The majority of the survey questions were developed by co-authors, but the last two were adapted from existing research [45]. A copy of the survey has been provided (Additional File 1).

Data collection was completed when two facilitators (MKC and FI) came to an agreement that thematic saturation had been reached. Thematic saturation is a pragmatic reconceptualization of data saturation in qualitative research. It acknowledges that the definition of data saturation as ‘no new information’ does not reflect generative and interpretive nature of reflexive thematic analysis where themes can be created, merged, and discarded throughout the analytical process with no definitive endpoint [46, 47].

Data analysis

All focus groups were video-recorded and transcribed verbatim. The transcribed data were analyzed using qualitative data analysis software, NVivo 14, using the template analysis method. Template analysis uses a hierarchical coding framework yet allows flexibility to create, rename and discard codes in accordance with qualitative data collected through reflexive processes of revision and refinement [48]. Multiple coders independently perform thematic analysis then collaboratively develop and agree upon a template codebook early on in analysis. This codebook is used to analyse the rest of the qualitative data.

Codes were developed inductively, while broadly focusing on perceived barriers and facilitators of MBC. Subsequently, the two co-authors (MKC and ME) met to discuss the codes and initial themes and develop a template in consultation with the senior author (FI). As per best practices of reflexive thematic analysis, themes emerged, eliminated and merged during this processes and researchers' reflexivity played a key role in reflecting on their individual assumptions [49]. The mutable template codebook developed was used to guide subsequent analyses. One co-author (MKC) coded the remaining data. The two co-authors (MKC and ME) met frequently to iteratively refine and review new codes and themes identified from subsequent data analyses.

Results

Surveys

Participant demographics

Eighteen participants attended the focus groups and completed a survey. There were 3 to 6 participants in each focus group, and the mean duration was 93 min (SD = 18.9). Most participants were female (15/18, 83%), and their mean age was 21.7 years (SD = 3.4; range 18–29 years). The study participants were linguistically, culturally (5/18, 28%), and gender diverse (7/18, 39%) (Additional File 2).

Young adults’ perspectives on measurement-based care

In the survey responses, most participants felt confident to explain MBC to their peers (16/18) and agreed with the value of routine monitoring (15/18) (Fig. 1). Additionally, most did not find progress review confronting (11/18) and anticipated that feedback would be helpful for their mental health (13/18).

Fig. 1.

Survey results of participant’s perspectives of MBC

Previous use and perceived role of digital technology in mental health care

Twelve participants reported that they have previously used digital tools as part of their mental healthcare. Of those 12 participants, 6 reported a positive experience, 4 had neutral, and 2 reported a negative experience. Digital tools were mostly commonly used for symptom monitoring (7/12). Symptom tracking, guided mindfulness/meditation sessions, and accessible information/education on mental health emerged as the top three features that should be prioritized in digital tools (Additional File 3).

Focus groups

Three themes were developed through template analysis (Fig. 2): regular symptom monitoring, data review with clinicians, and helpful digital features. Each theme comprised several subthemes. For the first two themes, subthemes included barriers and facilitators to each component of MBC. For the third theme, subthemes focused on digital features that participants perceived would support sustained engagement with MBC.

Fig. 2.

Graphic presentation of themes developed from focus groups

Regular symptom monitoring

Majority of participants indicated that they have previously used either self-directed or clinician-guided symptom tracking. Regular symptom monitoring was perceived as a double-edged sword. While several participants expressed that it was helpful to discover new insights about their mental health from longitudinal symptom trajectories, they expressed difficulties in doing it consistently, especially when they perceived there was a lack of progress in their treatment. The following sections present potential barriers and facilitators of regular data input as part of MBC.

Barrier: the need for consistent monitoring

Participants seemed to be awared of the theoretical benefits of regular symptom tracking, including enhanced identification of symptom triggers, empirical guidance for treatment decision-making, and reinforcement of adaptive behavioral modifications. Nevertheless, substantial adherence challenges emerged across the sample. Participants reported that symptom monitoring was easy to forget, mobile notifications were often ignored, and completing the same standard measures felt repetitive. These suggested that while the conceptual value of symptom monitoring was recognized, practical implementation barriers significantly undermined sustained utilization over time.

“The biggest hindrance is doing something regularly every day at the same time.” (FGP1)

Such challenges became more prominent during the periods of poor mental health. The act of reflecting and recording their symptoms was perceived as being burdensome and effortful during low moods. Participants also expressed difficulty in facing a lack of progres, reporting feelings of defeat and hopelessness when symptom trends reflected their consistent low moods. Some participants even noted that being discouraged by symptom deterioration and feeling guilty about “not doing clinician’s homework” would rather have negative effects on their mental health. Participants recalled that these negative emotional experiences led to short term adherence to symptom tracking.

“On those particular days, it felt like I was making the choice to be sad, or like the choice was kind of made for me by having to report it. And I was like, ‘Okay, I guess I’m sad. Just give up’. Even if there was a little bit of fight left in you, you just give up at that moment.” (FGP2)

Barrier: incomplete representation of mental health

Participants showed reluctance to symptom monitoring due to concerns around potential risks of data misinterpretation. Similarly, using standard measures irrelevant to their personal concern felt meaningless and demotivating. This highlighted the crucial role of perceived relevance for sustained engagement and motivation towards repeated data input. Consistent with this, participants showed preference for idiographic (i.e., individualized) assessment measures rather than nomothetic (i.e., fixed) measures.

“It’s not really useful unless the questions are kind of like tailored to your or your experiences.” (FGP3)

Furthermore, participants perceived that the clinical utility of symptom tracking would be enhanced if trends accurately and holistically reflected their mental health status. They emphasised the value of tracking multidimensional symptoms, suggesting that this would offer a more comprehensive understanding of their mental health to clinicians. Recognizing the limitations of quantitative measures in capturing only singular aspects of their mental health, they recommended incorporating both psychological and non-psychological measures. Nominated features included sleep quality, social network, and blood markers (e.g., thyroid or iron levels). Participants deemed that such comprehensive approach, encompassing multidimensional factors known to moderate mental health, would support informed clinical judgements and improve treatment outcomes.

“My response would be dependent on other factors. I could be in a depressed mood because I have depression, but it also could be because I have a thyroid disorder that causes depression.” (FGP4)

Facilitator: new insights through longitudinal data

Participants indicated significant value in the longitudinal symptom trajectories generated through consistent monitoring, noting their utility for improving mental health understanding and management strategies. Those with prior tracking experience reported that insights derived from these data patterns, particularly the identification of symptom trends and triggers, motivated implementation of self-management techniques, including emotional regulation strategies, cognitive restructuring, and behavioral modifications. The increased self-awareness and acquisition of management skills fostered greater treatment autonomy and bolstered confidence in both prevention and management of future symptoms.

“The more information that you can learn about yourself, the more that you become aware of the different tools that might be available to you to help manage yourself. It also helps to manage your future symptoms, so, you’re better equipped to face those potential risks.” (FGP5)

Notably, participants emphasized that these knowledge gains (understanding factors that moderate their mental health and the dynamic nature of mood fluctuations) functioned as intrinsic motivators for sustaining data input, even during periods of stagnant treatment progress. Consequently, regular, collaborative data review sessions that enabled these insights were identified as important for both the initial adoption and long-term sustainability of symptom data input.

“If you have enough data over time and you can see that in the past, my mood has dipped and then it started to come out. […] Seeing the trends, you can see what could perhaps get me out of it this time?’” (FGP6)

Facilitator: purpose and goal setting

Participants emphasized the importance of being informed about the rationale and mechanism of action of MBC. Their ultimate motivation to engage in therapy was to improve their mental health, hence understanding how symptom monitoring can help to achieve this was perceived to intrigue their interest, serving as a motivator.

“Just an understanding of the benefits of doing a measurement-based care, understanding what’s going on. Knowing the value of doing a survey and what it’s going to achieve? I’m going to therapy voluntarily, and I want to get better. That’s going to motivate me towards doing it.” (FGP7)

Therefore collaborative goal setting with clinicians, wherein participants actively contributed to establishing monitoring objectives, naturally emerged as a significant facilitator. A mutual understanding of purpose and shared ownership of goals seemed to substantially enhance and sustain motivation for regular data input. This collaborative approach appeared to transform the monitoring experience from an externally imposed obligation to a meaningful partnership aligned with participants’ treatment priorities and personal agency.

“Something that we did, which I think was really good was we set goals at the beginning of every term and then at the end of every term, we’d go through, and we check off. So, this both kept me as accountable, gave me kind of what I want to do. But it’s also that I get to see that progress, and how much I’ve achieved.” (FGP4)

Data review with clinicians

Clinicians’ rapport with clients and open-mindedness during data dissemination were determining factors for participants' involvement in data review. Two subthemes were developed.

Facilitator: collaborative care

Many participants desired a sense of partnership when reviewing data with their clinicians.

The process of clinicians personally reviewing their data was considered to help them feel valued and respected as “equal players in therapy”. All participants favoured data review during treatment and desired to be actively involved in clinical decision-making. They wanted to participate in the decision-making process by providing context around their symptom scores, evaluating goals according to their circumstances and exploring future treatment strategies.

“I believe if someone reviews our data/provides input, it will make us feel more valued and heard, and then encourage us to open up more. I feel if they check up routinely and provide some statistics and specific resources to use while undergoing care would be really great.” (FGP8)

However, it was observed that most were hesitant to initiate these discussions themselves. Therefore, clinicians’ initiative to foster these discussions and their attitudes of curiosity and open-mindedness were believed to be important in facilitating active involvement of young adults during data review.

“When your clinician starts to like, ask you questions like, Is that okay? How does that sound? Would you like to try this, or should we do something else? Or have you seen this? And when they sort of bring you options, and include you in that decision making? I think that really empowers someone.” (FGP9)

Barrier: generalization when interpreting data

Although shared decision-making based on collected data was seen as empowering, participants were simultaneously concerned about the potential for clinicians to rely too heavily on the data and thus make biased or invalidating assumptions. Previous experiences of clinicians generalizing their mental health without considering their personal context was frequently reported during focus group discussions. Poor rapport stemming from these experiences seemed to hinder their future engagement in data review.

“Being able to explain that beyond what the data is showing. So of not this assumption that the clinician is going to look at that and think that everything’s horrible, but they know you are struggling, but it can be explained by x, y and Z. You need a space to actually explain that.” (FGP6)

Additionally, participants highlighted the importance of positive reinforcement from clinicians when reviewing data. A deficit-focused interpretation of data or invalidation of their perceived struggles with mental health were demotivating.

“It can be invalidating to some people, if they feel like they are not sick enough to make someone feel like […] their thing isn’t serious enough that what they are feeling.” (FGP10)

Helpful digital features

Three digital features were suggested to facilitate the use of MBC in mental healthcare. Participants wanted digital tools to improve data access, customization, and interpretation.

Accessibility and customization capacity

Accessibility was highlighted as a key feature for sustained engagement with symptom monitoring. Participants emphasized that seamless user experience, without it being “clunky”, would promote regular use of digital symptom tracking tools.

“For it to become a habit, it needs to be easy to use and enjoy.” (FGP1)

Participants’ design preferences (i.e. color, language, units of scale) varied. However, they all wanted the flexibility to choose their own personalized set of standard measures to track their mental health. Participants wanted to ensure that these measures were relevant to their mental health priorities.

“A young person needs to be able to pick how much involvement they have with it? So, they’re not just taking like one giant questionnaire that covers a bunch of stuff that isn’t relevant to them” (FGP3)

Automated reminders and encouragements

In addition to clinicians’ positive reinforcement during sessions, participants suggested that personalized encouragements tailored to their treatment progress (e.g., positive messages when deteriorating or celebratory messages when improving) could motivate regular data input. They preferred progress-based encouragements over outcome-based ones, such as congratulatory messages on the number of consecutive days of data entry rather than reaching a specific symptom score. The experience of a participant who previously used a symptom tracking app illustrates this.

“Little achievements or it’s like, ‘oh my god, I logged into the app for six days in a row’ […] Small stuff like that. It’s so dumb but so effective” (FGP3)

An automated reminder of the participant’s personal goals for recovery were deemed as motivating as these were expected to reinforce the value and purpose of symptom monitoring.

Data interpretation and visualization support

Having a sense of ownership and strong understanding their data was valued among participants. Hence, they wanted digital features to help them access and interpret collected data. These included visualization of symptom progress, explanation of questionnaire results, and guidelines on what constitutes an optimal score.

“When therapist deems it appropriate, like showing an actual figure, showing your progress […] Even if it’s just like an encouragement, and even if it’s getting worse, like actually being able to reflect, I think that’s really pretty valuable.” (FGP7)

Clinicians’ access to participants’ monitoring data was welcomed as this shared visibility was expected to allow clinicians to detect mental health fluctuations and facilitate otherwise challenging therapeutic conversations. Participants reported difficulties articulating their struggles or retrospectively recall these experiences during sessions. Consequently, participants wanted shared data access to function as an indirect communication channel, wherein deteriorating symptom metrics could alert clinicians about concerning changes without requiring explicit verbal disclosure from the participant.

Beyond observing their symptom trends, participants wanted a curated information on available treatments or self-management strategies personalized to their mental health concerns. They anticipated that access to these information and discussing about these treatment options with clinicians would make them feel empowered during data review.

“And maybe if we have something where it sort of gives suggestions on like how to deal with what kind of feeling, it will keep you more informed. Then you can kind of proof of concept to your therapist, and then get like a secondary opinion rather than ‘do this.’” (FGP11)

Discussion

This study explored factors that influence young adults’ engagement with MBC in mental health services and the role of digital tools in supporting its uptake and sustained use. Survey results showed that most young adults agreed with the value of MBC and perceived that digital tools could support symptom monitoring. Template analysis of focus groups revealed three themes, regular symptom monitoring, data review with clinicians and helpful digital features. Facilitators of MBC included gaining new insights through longitudinal data and using the information to achieve personal goals in care. Notably, young adults anticipated that such facilitators would be realized through collaborative data interpretation and goal setting with clinicians. In contrast, barriers to MBC engagement were related to concerns around misrepresentation or misinterpretation of their data, which were perceived to stem from lack of collaboration in goal settingor data review. Consistent with these themes, digital features proposed to enhance engagement focused on functions that enhanced personalization (i.e. purpose reminders, and customization capacity) and clinical utility of collected data (i.e. data visualization and interpretation support). This study highlights collaborative data review as a crucial factor that could enhance MBC engagement in young adults accessing mental health services.

Data review in measurement-based care

The three components of MBC are interdependent, as the review and use of data (collectively addressed as data review hereafter) rely on data input. However, consistent symptom tracking is a well-established barrier of MBC engagement [24, 50]. Themes developed in this study presents data review as a factor that could overcome this barrier.

Data review ensures the efficacy of MBC by facilitating early detection of mental health deterioration and data-informed decision making [18, 51, 52]. However, its potential as a motivator for sustained engagement is underexplored. Collaborative data review in MBC creates opportunities for young adults to experience the value of regular, longitudinal symptom monitoring [53]. Young adults in the study perceived that positive experiences of using collected symptom data to identify triggers and strategize future treatment plans would encourage sustained engagement with MBC. Further, for data review to serve as a facilitator, it was critical that the review process focused on building shared understandings on personal goals and their current mental health conditions. Our results show that young adults value the therapeutic alliance and personalization of care achieved through collaborative data reviews.

Furthermore, a sense of autonomy emerged as an underlying driver of young adults’ engagement with MBC [32, 34]. They consistently expressed a preference towards personalized approaches to symptom monitoring, tailored to their unique needs. For example, in line with previous research, the use of idiographic measures [26] was preferred over nomothetic measures. Their suggested digital features further reinforced this emphasis on autonomy, as young adults wanted functions that would enhance their capacity as informed participants in their care (e.g. tools that provide data interpretation and exploring treatments options). Importantly, they did not view technology as a replacement for clinician interaction but rather, as a means to empower them as active participants in data review and treatment decision-making.

Implications for MBC practice

Understanding data review as a key motivator for young adults’ engagement with MBC can inform service implementation and digital MBC tool development. Findings indicate that three elements may be crucial: collaborative goal setting from the start of therapy, individualized monitoring plans, and digital MBC tools that simplify data entry.

To enhance young adults’ engagement, data review should prioritize personalization and shared decision-making. Specifically, goal setting and personalized monitoring plan (e.g. frequency and types of measures used for monitoring) should be collaboratively established from early stages of therapy and consistently reviewed throughout care to ensure that they align with client’s evolving needs. Scheduling regular review sessions to provide progress feedback and encouragements would be especially crucial for strengthening therapeutic alliance, enhancing perceived utility of symptom monitoring, and improving treatment outcomes [6, 11, 21, 54]. Additionally, digital MBC tools that support collaborative data review should be used in services to address its time-consuming nature. Key digital features include immediate data visualization [55] and personalized care recommendations generated from clients’ symptom data [56–58]. Streamlining data interpretation and translating it into actionable treatment and self-management strategies could enhance clinical utility and relevance of MBC, leading to greater client and clinician engagement.

Further research is needed to develop user-friendly digital MBC tools that enhance client-clinician interaction, collaborative care, and shared decision-making. This could include integration of an alert tool that detects and informs clinicians when clients report unforeseen changes in symptom trajectories [59, 60], and development of machine learning models that dynamically predict and recommend symptom monitoring frequency for clients based on their symptom variability and severity [61]. Additionally, automatically generating personalized feedback or self-help strategies matched to their symptom data could prompt clients to take actions to alleviate their symptoms immediately, especially in between appointments. Development of these tools should involve user-centered design and participation from various stakeholders to ensure smooth integration of feedback into clinical workflows [28, 62].

Limitations

Participants in this study were recruited within a university setting, which may have influenced the outcomes in several ways. Beyond limiting socioeconomic diversity, the sample likely reflected a specific subgroup of young adults—those more likely to have a university education, be within a narrower age range, and have an interest in research. These factors may have shaped their engagement with the study and perspectives they shared. Additionally, the majority of focus group attendees were female. While the proportion of help-seeking females is slightly higher in real-world settings [63], future studies should aim to oversample male participants and those from diverse cultural backgrounds to understand how MBC engagement varies across gender, race, and ethnicity. Such an approach would help design digital MBC tools for populations that are less likely to seek help, ultimately addressing disparities in mental health resource utilization and improving accessibility for underserved groups. Secondly, the focus group method may have limited the richness of information compared to an interview format. However, conducting interviews would not have allowed multiple perspectives to develop. Furthermore, since only a few participants used MBC before participating in the study, the focus group method enabled participants to brainstorm potential moderators and build on other peoples’ opinions. For future studies, semi-structured interviews of champions in each focus group may allow for a deeper inspection of individual perspectives.

Conclusions

This study demonstrates how collaborative data review could be a powerful motivator for young adults’ engagement with MBC in mental health services. Our findings reveal that its value may extend beyond its role in ensuring treatment efficacy, highlighting its potential for overcoming a key barrier to MBC, consistency required in symptom tracking. A sense of autonomy and personalized care, fostered through collaborative data interpretation and goal setting, could empower young adults to become active participants in MBC. Future research should focus on refining digital MBC tools to enhance client-clinician interactions, communication, and shared decision-making to ultimately improve mental health outcomes.

Abbreviations

FGP

Focus group participant

MBC

Measurement-based care

Authors’ contributions

MKC conceptualized and designed the work, performed analysis, interpreted data and drafted the manuscript. MKC and ME conducted data analyses, and ME and FI reviewed all analyses. All authors (MKC, ME, SM, FI, AH, SJH, ES, AP, and IBH) substantively revised and approved the final version of the manuscript.

Funding

The funding sources of this study have had no input into the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. This work was supported by the Medical Research Future Fund Applied Artificial Intelligence in Health Care grant [MRFAI000097]. IBH was supported by an NHMRC Research Fellowship (511921). FI was supported by the Bill and Patricia Richie Foundation. MKC was supported by Research Training Program Scholarship funded by the Australian government.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This project was approved by the Northern Sydney Local Health District Human Research Ethics Committees (HREC/17/HAWKE/480) and conducted in accordance with the Standards for Reporting Qualitative Research [64]. This research conducted on humans and/or human data, or material adhered to the Helsinki Declaration [65].

Consent for publication

Not applicable.

Competing interests

IBH is the Co-Director, Health and Policy at the Brain and Mind Centre (BMC) University of Sydney. The BMC operates an early-intervention youth services at Camperdown under contract to headspace. He is the Chief Scientific Advisor to, and a 3.2% equity shareholder in, InnoWell Pty Ltd which aims to transform mental health services through the use of innovative technologies.

A/Prof Elizabeth Scott is Principal Research Fellow at the Brain and Mind Centre, The University of Sydney. She is Discipline Leader of Adult Mental Health, School of Medicine, University of Notre Dame, and a Consultant Psychiatrist. She was the Medical Director, Young Adult Mental Health Unit, St Vincent’s Hospital Darlinghurst until January 2021. She has received honoraria for educational seminars related to the clinical management of depressive disorders supported by Servier, Janssen and Eli-Lilly pharmaceuticals. She has participated in a national advisory board for the antidepressant compound Pristiq, manufactured by Pfizer. She was the National Coordinator of an antidepressant trial sponsored by Servier. No other competing interests were reported.