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Challenges in conducting research on collaborative mental health care: a qualitative study.

ABSTRACT: BACKGROUND:We sought to understand poor uptake of the Primary Care Assessment and Research of a Telephone Intervention for Neuropsychiatric Conditions with Education and Resources study (PARTNERs), a pragmatic randomized controlled trial of a collaborative care intervention for people experiencing depression, anxiety or at-risk drinking. We explored primary care providers' experience with PARTNERs, and preferences regarding collaborative care models and trials. METHODS:In this qualitative study, we interviewed primary care providers across Ontario who had participated in PARTNERs, using stratified sampling to reach high-, low- and nonreferring providers in urban and rural settings. We audio-recorded, transcribed and thematically analyzed the interviews between May and December 2017, collecting and analyzing data concurrently until achieving saturation. RESULTS:We interviewed 23 primary care providers. They valued the unique availability of telephone-based coaching for patients but desired greater integration of the coach into their practice. They appreciated expert psychiatric recommendations but rarely changed their practices. Sites varied in organizational adoption and implementation of the study, including whether they designated a local champion, proactively identified eligible patients, integrated the study into existing workflows and reflected on (and revised) practices. These behaviours affected continuing awareness of the study and referral rates. INTERPRETATION:Study uptake was influenced by the limited relationship between PARTNERs coaches and primary care providers, and variable attention to leadership, training and quality improvement as vital elements of collaborative care. Study designs focusing on implementation could promote reach and penetration of novel interventions in the practice setting and more successfully advance collaborative care implementation.

SUBMITTER: Sunderji N

PROVIDER: S-EPMC6579651 | biostudies-literature | 2019 Apr-Jun

REPOSITORIES: biostudies-literature

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Challenges in conducting research on collaborative mental health care: a qualitative study.

Sunderji Nadiya N Ion Allyson A Zhu Annie A Perivolaris Athina A Rodie David D Mulsant Benoit H BH

CMAJ open 20190401 2

<h4>Background</h4>We sought to understand poor uptake of the Primary Care Assessment and Research of a Telephone Intervention for Neuropsychiatric Conditions with Education and Resources study (PARTNERs), a pragmatic randomized controlled trial of a collaborative care intervention for people experiencing depression, anxiety or at-risk drinking. We explored primary care providers' experience with PARTNERs, and preferences regarding collaborative care models and trials.<h4>Methods</h4>In this qua ...[more]

PMID: 31201177

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Project description:BackgroundHealth policy in many countries directs treatment to the lowest effective care level and encourages collaboration between primary and specialist mental health care. A number of models for collaborative care have been developed, and patient benefits are being reported. Less is known about what enables and prevents implementation and sustainability of such models regarding the actions and attitudes of stakeholders on the ground. This article reports from a qualitative sub-study of a cluster-RCT testing a model for collaborative care in Oslo, Norway. The model involved the placement of psychologists and psychiatrists from a community mental health centre in each intervention GP practice. GPs could seek their input or advice when needed and refer patients to them for assessment (including assessment of the need for external services) or treatment.MethodsWe conducted in-depth qualitative interviews with GPs (n = 7), CMHC specialists (n = 6) and patients (n = 11) in the intervention arm. Sample specific topic guides were used to investigate the experience of enablers and barriers to the collaborative care model. Data were subject to stepwise deductive-inductive thematic analysis.ResultsParticipants reported positive experiences of how the model improved accessibility. First, co-location made GPs and CMHC specialists accessible to each other and facilitated detailed, patient-centred case collaboration and learning through complementary skills. The threshold for patients' access to specialist care was lowered, treatment could commence early, and throughput increased. Treatment episodes were brief (usually 5-10 sessions) and this was too brief according to some patients. Second, having experienced mental health specialists in the team and on the front line enabled early assessment of symptoms and of the type of treatment and service that patients required and were entitled to, and who could be treated at the GP practice. This improved both care pathways and referral practices. Barriers revolved around the organisation of care. Logistical issues could be tricky but were worked out. The biggest obstacle was the funding of health care at a structural level, which led to economic losses for both the GP practices and the CMHC, making the model unsustainable.ConclusionsParticipants identified a range of benefits of collaborative care for both patients and services. However, the funding system in effect penalises collaborative work. It is difficult to see how policy aiming for successful, sustainable collaboration can be achieved without governments changing funding structures.Trial registrationClinicalTrials.gov identifier: NCT03624829.

Project description:BackgroundIntegrative health care (IHC) is an interdisciplinary blending of conventional medicine and complementary and alternative medicine (CAM) with the purpose of enhancing patients' health. In 2006, we designed a study to assess outcomes that are relevant to people using such care. However, we faced major challenges in conducting this study and hypothesized that this might be due to the lack of a research climate in these clinics. To investigate these challenges, we initiated a further study in 2008, to explore the reasons why IHC clinics are not conducting outcomes research and to identify strategies for conducting successful in-house outcomes research programs. The results of the latter study are reported here.MethodsA total of 25 qualitative interviews were conducted with key participants from 19 IHC clinics across Canada. Basic content analysis was used to identify key themes from the transcribed interviews.ResultsBarriers identified by participants fell into four categories: organizational culture, organizational resources, organizational environment and logistical challenges. Cultural challenges relate to the philosophy of IHC, organizational leadership and practitioner attitudes and beliefs. Participants also identified significant issues relating to their organization's lack of resources such as funding, compensation, infrastructure and partnerships/linkages. Environmental challenges such as the nature of a clinic's patient population and logistical issues such as the actual implementation of a research program and the applicability of research data also posed challenges to the conduct of research. Embedded research leadership, integration of personal and professional values about research, alignment of research activities and clinical workflow processes are some of the factors identified by participants that support IHC clinics' ability to conduct outcomes research.ConclusionsAssessing and enhancing the broader evaluation culture of IHC clinics prior to implementing outcomes research may be a critical step towards ensuring productive and cost-effective research programs. However, as IHC clinics are often complex systems, a whole systems approach to research should be used taking into account the multidimensional and complex nature of such treatment systems so that the results are useful and reflect real life.

Project description:BackgroundActive engagement in research by healthcare organisations and clinicians is associated with improvements in healthcare performance. Barriers to research engagement by clinician allied health (AH) professionals include competing priorities from high clinical workloads, lack of research skills and confidence, and lack of supportive research relationships. Collaboration with universities on joint clinical research projects is well recognised as a means of building health service research capacity. Research projects undertaken by students as part of their qualifying degree represent one such opportunity. However, there are few reports evaluating these collaborations from the health service perspective.MethodsA qualitative study using semi-structured interviews and thematic analysis to explore the experiences of AH professionals in the co-supervision of students completing research placements as part of their professional degree course.ResultsFourteen health service employees from six allied health disciplines described collaborations on research projects with 24 students from four different universities. Student placements and projects varied widely in length of placement, extent of collaboration, supervision structure and study design. Three overarching themes were identified in the AH professional co-supervision experience: 1) Professional growth; 2) Mismatch with expectations; and 3) Focus on the student. Project outcomes were categorised from the health system perspective. These were 1) Healthcare performance improvements, including local increases in staff clinical practice knowledge and wider contributions to the evidence base; 2) Research capacity gains within the health service, including research knowledge and skill development, collaborative linkages and opportunity for future research; and 3) Staff-centred outcomes including increased job satisfaction.ConclusionsThis study demonstrates the potential for AH professional supervision of students on research placements to contribute to healthcare performance improvements and research capacity gains within health services, alongside providing personal benefits for the AH professionals involved. Early consultation with a health service-employed research specialist may support health professional and student learning, team collaboration and project coordination for these student projects.

Project description:BackgroundCollecting longitudinal data during and shortly after pregnancy is difficult, as pregnant women often avoid studies with repeated surveys. In contrast, pregnant women interact with certain websites at multiple stages throughout pregnancy and the postpartum period. This digital connection presents the opportunity to use a website as a way to recruit and enroll pregnant women into a panel study and collect valuable longitudinal data for research. These data can then be used to learn new scientific insights and improve health care.ObjectiveThe objective of this paper is to describe the approaches applied and lessons learned from designing and conducting an online panel for health care research, specifically perinatal mood disorders. Our panel design and approach aimed to recruit a large sample (N=1200) of pregnant women representative of the US population and to minimize attrition over time.MethodsWe designed an online panel to enroll participants from the pregnancy and parenting website BabyCenter. We enrolled women into the panel from weeks 4 to 10 of pregnancy (Panel 1) or from weeks 28 to 33 of pregnancy (Panel 2) and administered repeated psychometric assessments from enrollment through 3 months postpartum. We employed a combination of adaptive digital strategies to recruit, communicate with, and build trust with participants to minimize attrition over time. We were transparent at baseline about expectations, used monetary and information-based incentives, and sent personalized reminders to reduce attrition. The approach was participant-centric and leveraged many aspects of flexibility that digital methods afford.ResultsWe recruited 1179 pregnant women-our target was 1200-during a 26-day period between August 25 and September 19, 2016. Our strategy to recruit participants using adaptive sampling tactics resulted in a large panel that was similar to the US population of pregnant women. Attrition was on par with existing longitudinal observational studies in pregnant populations, and 79.2% (934/1179) of our panel completed another survey after enrollment. There were 736 out of 1179 (62.4%) women who completed at least one assessment in both the prenatal and postnatal periods, and 709 out of 1179 (60.1%) women who completed the final assessment. To validate the data, we compared participation rates and factors of perinatal mood disorders ascertained from this study with prior research, suggesting reliability of our approach.ConclusionsA suitably designed online panel created in partnership with a digital media source that reaches the target audience is a means to leverage a conveniently sized and viable sample for scientific research. Our key lessons learned are as follows: sampling tactics may need to be adjusted to enroll a representative sample, attrition can be reduced by adapting to participants' needs, and study engagement can be boosted by personalizing interactions with the flexibility afforded by digital technologies.

Project description:BackgroundArtificial intelligence (AI) is transforming the mental health care environment. AI tools are increasingly accessed by clients and service users. Mental health professionals must be prepared not only to use AI but also to have conversations about it when delivering care. Despite the potential for AI to enable more efficient and reliable and higher-quality care delivery, there is a persistent gap among mental health professionals in the adoption of AI.ObjectiveA needs assessment was conducted among mental health professionals to (1) understand the learning needs of the workforce and their attitudes toward AI and (2) inform the development of AI education curricula and knowledge translation products.MethodsA qualitative descriptive approach was taken to explore the needs of mental health professionals regarding their adoption of AI through semistructured interviews. To reach maximum variation sampling, mental health professionals (eg, psychiatrists, mental health nurses, educators, scientists, and social workers) in various settings across Ontario (eg, urban and rural, public and private sector, and clinical and research) were recruited.ResultsA total of 20 individuals were recruited. Participants included practitioners (9/20, 45% social workers and 1/20, 5% mental health nurses), educator scientists (5/20, 25% with dual roles as professors/lecturers and researchers), and practitioner scientists (3/20, 15% with dual roles as researchers and psychiatrists and 2/20, 10% with dual roles as researchers and mental health nurses). Four major themes emerged: (1) fostering practice change and building self-efficacy to integrate AI into patient care; (2) promoting system-level change to accelerate the adoption of AI in mental health; (3) addressing the importance of organizational readiness as a catalyst for AI adoption; and (4) ensuring that mental health professionals have the education, knowledge, and skills to harness AI in optimizing patient care.ConclusionsAI technologies are starting to emerge in mental health care. Although many digital tools, web-based services, and mobile apps are designed using AI algorithms, mental health professionals have generally been slower in the adoption of AI. As indicated by this study's findings, the implications are 3-fold. At the individual level, digital professionals must see the value in digitally compassionate tools that retain a humanistic approach to care. For mental health professionals, resistance toward AI adoption must be acknowledged through educational initiatives to raise awareness about the relevance, practicality, and benefits of AI. At the organizational level, digital professionals and leaders must collaborate on governance and funding structures to promote employee buy-in. At the societal level, digital and mental health professionals should collaborate in the creation of formal AI training programs specific to mental health to address knowledge gaps. This study promotes the design of relevant and sustainable education programs to support the adoption of AI within the mental health care sphere.

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Challenges in conducting research on collaborative mental health care: a qualitative study.

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Challenges in conducting research on collaborative mental health care: a qualitative study.

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