Psychosocial eHealth in Advanced Lung Cancer

Being diagnosed with cancer impairs many areas of a person's life. Although efficacious educational, emotional and social interventions exist in this regard, they often reach few survivors and late. This project, carried out by a specialized centre in cancer care and health research, will study the effectiveness, costs, and utility associated with a digital ecosystem tailored to meet the needs of patients with advanced lung cancer. This solution bridges the gap between patients and professionals to offer health services precisely when they are needed. The project is developed in the first year of an advanced lung cancer diagnosis, comparing the effects of the digital ecosystem with usual care in terms of their capacity to improve various psychosocial indicators. A comparative economic analysis will be carried out as well, to prove the cost-utility of the digital ecosystem presented.

Palliative Care (PC) for patients with advanced life-limiting diseases and the management of their symptoms during the trajectory of illness has evolved considerably (Clark, 2007). PC is conceptualized as an approach to improve the quality of life of patients and their relatives "through the prevention and relief of suffering by means of early identification and impeccable assessment and treatment of pain and other physical, psychosocial and spiritual problems". In recent years, survival rates have increased for most cancer diagnoses, in both early and advanced stages. Therefore, patients suffering a disease considered incurable are living longer with cumulative psychosocial comorbidity derived from both the illness itself and its associated treatments. The American and European societies for medical oncology have recently recommended integrating early psychosocial PC into standard oncological practice for patients with metastatic or advanced stage diseases like lung cancer (LC) in their professional guidelines. This decision has been recently supported by meta-analytic results as well. Those studies show that palliative interventions including physical and psychological aspects have beneficial effects on patients, both on short-term quality of life and in general symptom burden. Despite the advantages of such integrated PC interventions, healthcare systems usually encounter several barriers to implementing psychosocial care in palliative settings, like in advanced LC. The most typical include poor early detection of such needs; long waiting lists; and mobility restrictions, with many patients unable to attend visits in person. The literature strongly suggests that emotional distress is associated with worse quality of life, lower adherence to oncological treatments and adoption of unhealthy lifestyles. Actually, it is also demonstrated that stress reduction may even extend survival years. Since LC patients show great symptom variability, erratic evolution and high emotional impact along with a limited prognosis, it is urgent to increase the currently small proportion of patients with early screening, close and intensive monitoring and prompt referral to PC teams. To this aim, new approaches in psychosocial PC are needed to overcome the barriers experienced today. In the last years, two main actions have been proposed to improve the implementation of psychosocial care in PC, placing a focus on its accessibility and efficiency. For example, recent studies have introduced earlier stepped (low to high intensity) and adaptive treatments as an ingenious and sensible response to the challenge of offering proper psychosocial interventions, with high cost-effectiveness in cancer. Another comprehensive action is to make use of Information and Communication Technologies (ICT). ICT has emerged in the last few years as an innovative resource to set this new wave of health practices in motion, with an exponential increase in its use and implementation during the COVID pandemic, to guarantee continuity of care in vulnerable advanced cancer patients. ICT have also shown their capability to overcome most of the limitations expressed in conventional care settings. These tools have provided faster and more intense follow-up options to monitor patients' warning signs, facilitating better communication between patients and professionals, and also leveraging cheaper and more accessible clinical treatments compared to traditional alternatives, even at the end of life. Nevertheless, the few studies comparing ICT and usual psychosocial interventions have found mixed effectiveness results so far. Recently, ONCOMMUN, a European proposal for creating an e-health ecosystem (https://oncommun.eu/), has combined these two promising actions to facilitate early psychosocial care in an online and stepped psychosocial program. ONCOMMUN has shown promising preliminary results on breast cancer (BC) and a high potential for therapeutic application in advanced and palliative settings, like LC. The first level of care in this program is an online screening and monitoring tool, followed by a patient's campus comprising educational interventions (second level), a psychosocial support community (third level), and psychotherapeutic treatment groups through videoconference (fourth level). The current project has been designed as a randomized non-inferiority controlled trial to compare an e-health ecosystem of psychosocial care, based on the ONCOMMUN proposal, against traditional in-person psychosocial treatment in PC during advanced LC. Our group proposes the development and adaptation of this digital ecosystem by integrating screening and monitoring tools with educational and psychological interventions, building upon the results of its recent implementation in BC. This innovative e-health ecosystem intends to foster healthy experiences, integrating a four-stepped psychosocial program of early PC focused on patients with a diagnosis of non-small cell lung carcinoma (NSCLC) at advanced stages (III and IV). OBJECTIVES (3 years) General To offer early detection and tailored treatment of psychosocial and physical needs of advanced LC survivors. To implement and assess an online stepped ecosystem for psychosocial and educational screening, monitoring and care, through the use of an e-health platform specifically developed for advanced LC patients. Specific objectives To compare the capacity of the digital ecosystem to detect and deliver early psychosocial care compared to treatment as usual. To improve or cushion the consequences of the advanced lung cancer course and treatment in terms of emotional distress, demoralization and quality of life. To explore the potential mediating and facilitating role of spirituality in an optimal psychosocial adaptation. To study the cost-utility associated with both interventions in terms of Quality-Adjusted Life Years (QALY), through the estimation of patients' use of additional health services, their degree of pharmacological adherence, intake of psychotropic medication, and time spent in disability leaves. To disseminate to cancer patients, professionals and the general public the results of the study. Procedure and data acquisition Development of an LC platform: LC platform will be adapted from the BC platform and fed by the results of the pilot LC system and focus groups with professionals and patients. The LC solution will share a set of structural items (e.g., measurement instruments, instant symptom management), to which specific resources for LC will be added. Patients' experience will be at the centre of this development stage to maximize usability and understanding of all resources. Validation with users: Patients with advanced LC diagnosis will be invited to participate by their medical team. If interested, they will be contacted by our group and a face-to-face meeting will be scheduled, where the study will be described and informed consent signed in case of acceptance. Participants will be then randomized to 1) e-health ecosystem or 2) usual psychosocial care by an external researcher blind to the research questions and treatment conditions, using a random sequence of numbers generated by REDCap software. In the eHealth ecosystem group, participants lacking equipment will be offered webcams and tablets as needed. There are specific processes of the system that will only apply to ICOnnecta't branch as they will measure the platform usability and their associate emotional state during the study (see Interventions section below). All other measures will be administered from T0 to T3 through a professional online survey platform compliant with the latest European General Data Protection Regulation (GDPR; EC/2016/679). Data collection and analysis Two databases will be created: The first one will associate participants' identifiable personal data (e.g., names, patient ID) with an alphanumeric code, and will be saved in an encrypted external hard drive stored in a key-protected closet within the office of the PI. The second database, created via REDCap system, will record all data to be analyzed making use of alphanumeric codes and will be stored in a secure collaborative cloud also GDPR-compliant. This procedure will allow us to conduct the analyses anonymously. Data will be monthly downloaded from REDCap and backed up in a second encrypted external hard drive. Every 3 months one researcher will conduct a data integrity check. While online systems automatically keep a registry of users' access, a notebook will remain next to the hard drives for researchers authorized by PIs to record their name, date and time when drives are retrieved and returned. Finally, the information collected through the eHealth ecosystem will also be stored in a GDPR-compliant server. Descriptive results will be provided for sociodemographic and clinical variables, as well as for education, usability and satisfaction indicators, while between-group differences will be assessed with Student's t-test and chi-square tests as appropriate. Multilevel linear models (MLM) will be used to compare both groups in outcome variables, while effect sizes (Hedges' g) will be reported and non-inferiority tested. For QALY analyses, results from the EQ-5D-3L will be used together with costs associated with professional salaries, adherence, infrastructure, psychotropic medication and sick leaves. The effect of any potential confounding variable will be analyzed. Analyses will be conducted using SPSS v24.021 (IBM SPSS Statistics 21, 2017) by the IDIBELL biostatistics department.

Lung Cancer, Nonsmall Cell, Stage IIIA, Lung Cancer Non-Small Cell Stage IIIB, Lung Cancer Non-Small Cell Stage III, Lung Cancer Stage IV, Lung Cancer

Psychooncology, Psychosocial care, Palliative care, eHealth, Continuity of patient care, Telemedicine, Well-being, Psychosocial Functioning, Patient Engagement, Emotional Distress, Quality of Life, Health Knowledge, Attitudes, Practice, End of life care

Non-inferiority randomized trial testing two experimental conditions: 1) ehealth ecosystem, 2) usual psychosocial care. Assessment of main outcomes are conducted at recruitment (T0), 3 months from T0 (T1), 6 months from T0 (T2), and 9 months from T0 (T3). Hence, the design is 2 (treatment conditions) X 4 (assessments). The whole project's methodology adheres to the principles of Responsible Research and Innovation (RRI). The sample size has been estimated with the support of the R software (R Core Team, 2020), setting a non-inferiority margin of 5 points in the Hospital Anxiety and Depression Scale (Vaganian et al., 2020), with power at 80% and one-tailed α of 2.5%. A dropout rate of 25% was assumed. It was anticipated that 152 participants were necessary (n = 76 per arm) to ensure that a two-sided 95% confidence interval would exclude the non-inferiority threshold.

Patients will be monitored allowing the delivery of timely and personalized care via a 4-level program: Screening and psychosocial monitoring through a mobile application where patients have a messaging system to contact their psychologist and reference nurse. Psychoeducation and health education campus, where patients can consult videos and online resources developed by health professionals, containing scientifically validated information. Psychosocial support community where patients can share doubts, fears, and experiences with other patients with advanced lung cancer. This private social network is monitored by team specialists when necessary. Online group psychotherapy of 8 weekly sessions of 90 minutes based on Meaning-Centered Group Psychotherapy (MCGP; Breitbart et al., 2010). Patients at this level will be on a waiting list, so the pool starts when there are 4-8 users available.

This group will receive standard psychosocial care for cancer survivors at ICO Hospitalet center led by a clinical psychologist. It consists of 7 individual sessions of 45-60 minutes, scheduled every 2-3 weeks during 9 months and focused on emotional support and psychoeducation. Moreover, they will be offered the education materials from the 2nd step of the platform, as they are compiled in a website open to all patients and relatives.

Screening and monitoring: weekly administration of an emotional state thermometer. If the score is >5, participants are asked to complete the HADS. If HADS' score >10, step 2 is assigned. The same procedure is followed for steps 3 & 4. Participants remain in each step for 2 weeks, and all level changes are preceded by a videoconference with a health professional Online psychoeducation campus: displays co-constructed videos and posts developed by health professionals and patients about LC diagnosis and treatment aspects. Online support community: anonymous survivors with LC diagnoses are included. Professionals and patient mentors supervise and foster debate, peer support, and resolve health Q&As. Weekly online group psychotherapy led by a clinical psychologist and composed of eight 90-minute sessions. Eligible users are placed on a waiting list, starting when 5-6 users are available.

Usual psychosocial care for cancer survivors at ICOHospitalet centre led by a clinical psychologist. Usual psychosocial care consists of 7 individual sessions of 45-60 minutes, with 2-3 weeks of space between sessions, based on Individual Meaning-Centered Psychotherapy (IMCP) for Patients With Advanced Cancer (Breitbart et al., 2012). Moreover, they will be offered the education materials from the 2nd step of the platform, as they are compiled on a website open to all patients and relatives.

Emotional distress will be assessed through the Hospital Anxiety and Depression Scale (HADS; Zigmond & Snaith, 1983). The HADS measures symptoms of anxiety and depression and consists of 14 items: seven items for the anxiety subscale (HADS Anxiety) and seven for the depression subscale (HADS Depression). HADS Anxiety focuses mainly on symptoms of generalized anxiety disorder and HADS Depression is focused on anhedonia, the main symptom of depression. Each item is scored on a response scale with four alternatives ranging between 0 and 3. Higher scores means higher levels of depression and anxiety.

Assessment will be conducted at baseline and at 3 months, 6 months and 9 months to assess change from baseline

Spirituality will be assessed through the Functional Assessment of Chronic Illness Therapy - Spiritual Well-Being (FACIT-Sp; Peterman et al., 2002). This scale includes factors of meaning, peace and faith, assessed through 12 items rated on a 0-4 Likert scale. The overall score ranges between 0 and 48, and between 0 and 16 for each subscale, where higher scores are indicative of greater spiritual well-being.

Assessment will be conducted at baseline and at 3 months, 6 months and 9 months to assess change from baseline

Demoralization will be measured through the Demoralization Scale (DS-II; Kissane et al., 2004). The DS-II is a 3-point response, self-report scale comprising 16 items and 2 subscales: distress and coping ability, and meaning and purpose. Scores <10 indicate no demoralization, between 10-19 moderate demoralization, and >20 severe demoralization.

Assessment will be conducted at baseline and at 3 months, 6 months and 9 months to assess change from baseline

Health-Related Quality Of Life (HRQOL) will be assessed through the Functional Assessment of Cancer Therapy-Lung (FACT-L; Cella et al., 1995). The FACT-L is a 36-item, lung cancer-specific instrument that also includes the symptom-based Lung Cancer Sub-scale (LCS). It has 36 items organized into 5 subscales: 1) physical well-being, 2) functional well-being, 3) social/family well-being, 4) emotional well-being and 5) lung cancer. Responses are scored on a Likert-type scale ranging from 0 (not at all) to 4 (very much). Higher scores correspond to a better quality of life.

QoL will be measured through the European Quality of Life Scale (EQ-5D-3L; EQ-5D User Guides, 2021). The EQ-5D-3L consists of 2 pages: the EQ5D descriptive system and the EQ visual analogue scale (EQ VAS). The EQ-5D-3L descriptive system comprises the following five dimensions: mobility, self-care, usual activities, pain/discomfort and anxiety/depression. Each dimension has 3 levels: no problems, some problems, and extreme problems. The EQ VAS records the patient's self-rated health on a vertical visual analogue scale of 100 points where the endpoints are labelled 'Best imaginable health state' and 'Worst imaginable health state'.

Assessment will be conducted at baseline and at 3 months, 6 months and 9 months to assess change from baseline

Symptom management will be measured through the Edmonton Symptom Assessment System (ESAS-r; Carvajal et al., 2012). ESAS-r is an instrument that is commonly used both in PC and in advanced cancer situations. It has 10 visual numerical scales that assess physical and psychological symptoms. Patients choose the number that best represents the intensity of each symptom on a scale of 0 to 10.

Medication adherence will be measured through the Simplified Medication Adherence Questionnaire (ARMS-e; Kripalani et al., 2009). The ARMS-e assesses medication adherence in patients with chronic conditions in 12 self-reported items with 4 response possibilities: never, sometimes, most of the time and always. Lower overall scores correspond to better adherence.

Assessment will be conducted at baseline and at 3 months, 6 months and 9 months to assess change from baseline

Users' satisfaction with the platform will be measured through a 0-10 Visual Analogic Scale (VAS). Higher scores correspond to higher satisfaction.

Platform's usability will be asked to users through a 0-10 Visual Analogic Scale (VAS). Higher scores correspond to higher usability.

Emotional wellbeing will be measured through an emotional thermometer (ET; Harju et al., 2019) using a Visual Analogue Scale (VAS) (0-10). Higher scores correspond to higher well-being.

Inclusion Criteria: Being adult (≥18 years) LC diagnosis in advanced stages -III-IV Access to internet and user-level experience Reading and writing skills in Spanish Exclusion Criteria: Current major depressive episode Risk of self-harm Active psychotic symptoms Substance abuse

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