Next Article in Journal
Advancements in Targeted Therapies for Colorectal Cancer: Overcoming Challenges and Exploring Future Directions
Next Article in Special Issue
The Role of Perceived Benefits in Buffering Gastrointestinal-Symptom Burden Among Post-Operative Colorectal Cancer Patients: A Six-Month Longitudinal Study
Previous Article in Journal
Diagnostic Accuracy of Contrast-Enhanced Ultrasound Compared with Contrast-Enhanced Computed Tomography in the Follow-Up of Hepatocellular Carcinoma Treated with Radiofrequency Ablation
Previous Article in Special Issue
Ifosfamide-Induced Encephalopathy in Children and Young Adults: The MD Anderson Cancer Center Experience
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Adaptation and Implementation of Self-System Therapy for Older Adults with Advanced Lung Cancer: Pilot Trial Results

1
Department of Psychiatry & Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA
2
Department of Population Health Sciences, Duke University Medical Center, Durham, NC 27710, USA
3
Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA
4
Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
*
Author to whom correspondence should be addressed.
Cancers 2025, 17(17), 2809; https://doi.org/10.3390/cancers17172809
Submission received: 24 July 2025 / Revised: 26 August 2025 / Accepted: 27 August 2025 / Published: 28 August 2025

Simple Summary

Lung cancer is a highly prevalent disease that disproportionately affects adults aged 65 and older. Existing interventions addressing the psychological burden of lung cancer are frequently inaccessible and inadequately tailored to this population’s unique needs. The aim of this pilot trial was to assess the feasibility, acceptability, and preliminary signal of Self-System Therapy (SST) for distress reduction in advanced lung cancer. Findings from this study may inform future interventions and supportive care strategies for older adults living with advanced cancer by fostering resilience, reducing distress, and improving quality of life.

Abstract

Background/Objectives: Advanced lung cancer is a highly distressing disease that negatively impacts older adults. Supportive care interventions designed for this population are scarce and often inaccessible due to competing demands and transportation access. We adapted and refined an evidence-based treatment, Self-System Therapy (SST), to address the unmet needs of older adults with advanced cancer. Methods: Guided by principles of implementation science, we conducted patient interviews, focus groups, and user testing to refine our new SST for the lung cancer (SST-LC) protocol. We then conducted a single-arm pilot trial (clinicaltrials.gov NCT04057196) for patients aged 65+ and above with Stage III or IV lung cancer (N = 30). Benchmarks for acceptability, feasibility, and preliminary changes in outcome measures were assessed. Results: Our study met the desired recruitment goals and demonstrated high treatment adherence rates (89%) and satisfaction rates (85%), indicating that SST-LC was feasible and well-received. Participants also showed reductions in distress and depression, and improvements in emotional and functional well-being from baseline to post-intervention, with effects mostly maintained at follow-up. Physical well-being, social well-being, and quality of life showed smaller, non-significant changes. Feedback from participants also suggested that SST enhanced their resilience and ability to cope with cancer-related challenges, but also indicated a preference for fewer sessions. Conclusions: SST for older adults living with advanced lung cancer is feasible and acceptable. Moreover, this supportive care intervention shows promise in addressing psychological distress, emotional well-being, and functional well-being in older adults. Future research will include testing the efficacy of SST in a larger randomized controlled trial.

1. Introduction

Cancer is a common and chronic condition that presents an inequitable burden of disease. More than half of individuals diagnosed with cancer are 65 and older, and by 2030, it is projected that 70% of all cancers will be diagnosed in this demographic [1,2]. Among this age cohort, lung cancer is the most diagnosed cancer (close to 70%) [3,4,5,6]. Lung cancer is also reported as the most psychologically distressing type of cancer compared to other cancer types [7,8]. Distressing symptoms, such as elevated levels of depression and anxiety, are commonly experienced. These symptoms are often exacerbated by impaired functioning and extensive physical symptomatology. Meta-analytic evidence suggests that behaviorally based interventions targeting emotional distress and promoting engagement in physical activity may yield positive outcomes for cancer patients, including improved mood and functioning [9,10,11].
Despite the potential benefits that older adults with advanced lung cancer may experience from behavioral interventions, there are substantial challenges in adapting such interventions for this population. Current supportive-care interventions often neglect normative aging concerns that address identity, role transitions, and changing goal structures amid physical health challenges [12,13,14]. Notably, briefer interventions (e.g., from traditional 12–16 weekly sessions reduced to 8 sessions or less) may prove to be more tolerable and less burdensome [15,16,17], as these individuals are continually experiencing rapidly changing physical health, coupled with the real threat of having a minimal amount of time to live. Thus, brief, efficacious, and accessible psychological support may offer older adults a faster “turnaround” to utilize newly learned coping strategies in daily living and enhance their quality of life.
To provide support for this population, in this study, we adapted and implemented a psychosocial behavioral intervention, Self-System Therapy (SST) [18,19], to target both physical and psychological well-being. SST is an empirically validated intervention grounded in current models of motivation and goal pursuit, that has shown efficacy in reducing distress among depressed adults [19]. SST can be summarized in four questions: What are your promotion (approach) and prevention (avoidance) goals? What are you doing to try to attain them? What is keeping you from making progress? What can you do differently? The goals of SST for lung cancer (SST-LC) are to target cancer-related distress and to enhance motivation by supporting more involvement in physical activity (linked to personal values) that offers older adults a sense of purpose and meaning in their daily lives. This paper presents the findings of our study, guided by a framework known as the Adaptome within implementation science [20], which encompasses key features of intervention refinement, such as modifying service settings, target audiences, and models of delivery, all delivered via telehealth.

Framework of Self-System Therapy: Intervention and Refinement

The adaptome framework [20] guided our adaptation of Self-System Therapy [18,19]. Adaptome takes into account that changing contexts, as well as differences in populations, can impact and influence the delivery, implementation, and refinement of evidence-based treatment interventions [20]. We leveraged this particular framework within implementation science to support the adaptation of SST [18,19] to meet the needs of older adults with advanced lung cancer. In particular, we focused on the necessary modifications (e.g., focusing on cancer), delivery type (e.g., delivering the intervention through Zoom [21]), and session length (e.g., refining content to eliminate duplication). We used the adaptome framework [20] as a guide to structure interviews with a total of 11 older adults with lung cancer, aiming to inform the refinement of the SST intervention. Each participant was reimbursed USD 75. Interviews were primarily conducted as three focus groups (with a total of 8 participants). For participants who could not attend the scheduled focus groups due to illness, or arrived late to join the session, we offered individual interviews. We used this approach with a total of 3 participants. During interviews and focus groups, session content we reviewed focused on the impact of the cancer experience, coping with illness, and adopting behaviors that promote health and prevent maladaptive health behaviors (e.g., isolating or not exercising due to fears of dyspnea). We also discussed the number of proposed sessions for delivering SST (up to 12) including delivering the intervention individually or as a group. Participants endorsed that up to 12 sessions may seem sufficient and that individual sessions may offer a more tailored experience. Following the completion of these interviews, and gathered feedback, we conducted user testing of the developed SST for lung cancer (SST-LC) protocol with 5 participants. Participants completed the SST-LC protocol individually via telehealth (e.g., Zoom [21]). They provided feedback after each session on the feasibility of learning and applying the techniques and skills, the perceived usefulness of each skill, the use of videoconferencing as the mode of delivery, and general feedback. Finalized session content is described in Section 2.3.
Feedback during the user testing phase was used to make final revisions to the SST-LC protocol before beginning the pilot trial. Each participant in user testing was also reimbursed USD 75. We presented a summary of participant feedback to the whole study team and made decisions about any necessary adjustments to the SST-LC protocol before initiating the pilot trial. The adjustments we made included keeping sessions between 8 and 12 sessions, limiting session length to an hour, and de-emphasizing content focused solely on the experience of depression to place greater emphasis on psychological distress (more broadly), which participants identified as more relevant to their experience with cancer. In preparation for the pilot trial, an entirely separate sample was recruited (i.e., participants in the focus groups or individual interviews we excluded) to reduce bias and preserve independence in sampling.

2. Materials and Methods

2.1. Participants

Participant eligibility criteria included (1) a diagnosis of Stage III or IV lung cancer; (2) age 65 or older; (3) living at home; and (4) ability to speak and read in English. Exclusion criteria were (1) visual or hearing impairments that precluded participation and (2) severe, untreated mental illness that would preclude giving informed written consent. The eligibility criteria were the same for both the intervention development and pilot phases of the study.

2.2. Procedures

This study was approved by the Duke University Institutional Review Board (IRB number: Pro00102705; ClinicalTrials.gov: NCT04057196). Participants were purposively sampled and recruited from the Duke Cancer Institute in Durham, NC. The study team determined initial eligibility through electronic medical record review and subsequent research recruitment letters. Our clinical research coordinator then phoned eligible and interested participants to conduct a screening to determine their eligibility. All participants completed treatment sessions individually via telehealth, and tablets on loan were provided for their use (as needed). Assessments were completed at baseline, post-, and 1-month follow-up using REDCap [22]. Participants were paid USD 150 for their participation in the study, with USD 50 allocated for completing each of the three evaluations (baseline, post-intervention, and follow-up).

2.3. Measures

Demographics. Participants provided standard demographic information, including age, sex, race and ethnicity, marital status, income, and education.
Feasibility and Acceptability. We examined feasibility metrics related to the number of participants we could recruit during the study period, with a primary goal of 30 participants in 18 months or less, as well as adherence rates among those who received and completed the SST-LC intervention skills. We also examined participant satisfaction with the content and delivery of SST-LC as a metric for acceptability.
Outcome Measures. Participants completed self-report measures at baseline, post-treatment, and follow-up. The outcome measures are summarized below.
Psychological Distress. We measured distress using the Clinical Outcomes in Routine Evaluation 10 (CORE-10) [23]. The CORE-10 measure comprises ten questions about how participants have been feeling over the past week. Each item is rated on a 5-point Likert scale ranging from 0 (“not at all”) to 4 (“most or all of the time”), yielding total scores from 0 to 40 (higher scores reflect greater distress; sample item: “I have felt anxious or tense”). Psychometric evaluations in both clinical and nonclinical adult samples demonstrate high internal consistency, with Cronbach’s α = 0.90 overall; α = 0.92 in nonclinical; α = 0.94 in clinical) and test–retest reliability of ICC = 0.81 [23].
Depression. Depression was measured using the Beck Depression Inventory (BDI-II) [24,25]. The measure has 21 items. The BDI-II is scored by summing the ratings for the 21 items. Each item is rated on a 4-point Likert scale ranging from 0 to 3, producing total scores from 0 to 63 (higher scores indicate a greater level of depression; sample item: “I get as much satisfaction out of things as I used to”). The BDI-II has high internal consistency, with Cronbach’s α = 0.91 [11], and strong test–retest reliability (r = 0.93) [24].
Quality of Life and Well-being. We used the Functional Assessment of Cancer Therapy-Lung (FACT-L) [26] to assess the overall quality of life and dimensions of well-being. The FACT-L is a 36-item measure scored on a five-point Likert scale, ranging from 0 (not at all) to 4 (very much), that measures overall quality of life (QOL) across five dimensions: physical well-being, social/family well-being, emotional well-being, functional well-being, and a lung cancer subscale. A total FACT-L score is calculated by summing the five subscales, with scores ranging from 0 to 136. The higher the score, the better the QOL. Internal consistency of the five FACT-L subscales ranges from 0.56 to 0.89 [26].
Treatment Satisfaction. The Client Satisfaction Questionnaire (CSQ-8) [27] was used to assess satisfaction with care received at post-treatment. An overall score is calculated by summing the respondent’s rating (item rating) score for each scale item (ratings are from 1 to 4). For the CSQ-8 version, scores range from 8 to 32, with higher values indicating higher satisfaction [27]; we implemented a cut-off of 26 or above to indicate high satisfaction.
SST-LC Session Content. SST consists of four main phases, an orientation, exploration, adaptation, and maintenance plan phase. Sessions can be completed within 8 sessions or extended to 12 sessions, based on patient need and in collaboration with the interventionist. For participants completing 12 sessions, one additional session was provided in each of the four phases. Session content is summarized below.
Sessions 1–3. The orientation phase introduces the goals of SST in the context of advanced lung cancer. Interventionists build rapport with older adult patients by addressing emotional challenges and fears about living with lung cancer and how that has impacted their identity and how they see themselves. Behavioral activation skills are introduced (e.g., performing a pleasant activity to help reduce distress).
Sessions 4–5. The exploration phase consists of helping patients identify the self-discrepancies they are experiencing as they relate to living with cancer and discussing their own self-efficacy to manage their psychological distress and cancer. Personal strengths and existing coping strategies are reinforced. Self-evaluation skills, such as reflective exercises, are introduced to help patients actively reflect on their behaviors and emotional responses, increasing self-awareness and confidence in managing distress and how they cope.
Sessions 6–7. The adaptation phase consists of the patient and interventionist working together to develop goals (i.e., goal-setting skills) that are both prevention-focused and promotion-focused. Examples include committing to spending at least 30 min daily engaging in an activity that reinforces their key roles (e.g., being a parent or grandparent) to preserve identity. Create a weekly plan that includes specific actions/behaviors aligned with health (exercising, eating healthy) and how they can foster their independence. Practicing specific relaxation techniques to improve their focus, increase gratitude, and promote positive emotional experiences. Reaching out to one person from their support network each week to prevent feelings of isolation and burden. These skills are adapted and tailored to the needs of the older adult to address their current life circumstances, cognitive and physical limitations, and/or personality traits.
Session 8. For the termination/maintenance plan phase, each participant along with the interventionist, develops a maintenance plan that includes a list of daily strategies (e.g., self-monitoring forms), short-term goals (e.g., becoming more active in self-rewarding activities), and long-term goals.

2.4. Analysis

Focus group and individual interviews were analyzed using thematic content analysis [28] as described earlier. User testing was primarily descriptive in finalizing study procedures. For the pilot, our primary focus was to assess acceptability and feasibility metrics, including recruitment, adherence, and satisfaction with the intervention. Secondarily, descriptive statistics, normal distribution assumptions, and paired sample t-tests (with an alpha level of 0.05) were explored to examine potential changes in outcomes from pre-, post-, and follow-up assessments using SPSS Version 29 [29]. These tests were strictly exploratory given that pilot studies are typically underpowered and are designed primarily to assess feasibility and acceptability. In addition to exploring changes in outcomes, we also explored associated effect sizes with confidence intervals, and p-values.
Sample size considerations were informed by the consolidated standards of reporting trials (CONSORT) extension for pilot trials and by behavioral research in cancer supportive care [30,31,32,33,34,35,36,37]. Consistent with recommendations for pilot trial design a sample size of 30 participants was considered appropriate to address feasibility and acceptability.

3. Results

3.1. Demographics, Feasibility, and Acceptability Benchmarks for the Pilot Trial

A total of 30 participants were recruited and enrolled in the study. See Figure 1 CONSORT diagram. Seventy-seven percent (23/30) of participants were female, with a mean age of 69.7 years old (range 65–83 years, SD = 4.95). Most participants were White/Caucasian (86.7%) or Black/African American (13.3%). See Table 1 for a complete summary of participant demographics.
We met our recruitment feasibility goal within two years for our pilot. For our secondary feasibility benchmark, we observed an excellent adherence rate of 89% (among those who received the intervention [N = 27], 24 completed/learned all session skills). Of these 24, 11 completed at least 8 sessions, and 13 participants completed 12 sessions. Most (85%) expressed high satisfaction (as reported in the CSQ-8) with the intervention at the conclusion of SST-LC (acceptability).

3.2. Exploration of Pre-to-Post Changes in Outcome Measures

From an exploratory basis, we examined the normal distribution of each outcome using the Shapiro–Wilk test. For outcomes that were normally distributed, we conducted our analysis using paired sample t-tests; for those that were not at specific time points (either at 12 or 16 weeks), we employed Wilcoxon signed-rank tests. Both approaches yielded the same conclusions. Given that the non-normally distributed outcomes did not have extreme outliers, and that parametric tests offer greater interpretability and consistency, we report our results with paired t-tests.
In examining signal of pre-post changes in distress, we found improvements in decreasing distress from baseline to 12 weeks post-intervention (p = 0.02); with improvements maintained at 1-month follow-up (p = 0.01). We also found improvements in depression (p = 0.001), emotional well-being (p = 0.05), functional well-being (p = 0.008), physical well-being (p = 0.11), social well-being (p = 0.53), and quality of life (p = 0.06) from baseline to 12 weeks post-intervention. See Table 2 and Table 3 for our results summary, including our results at follow-up.
We also invited participants to provide feedback following the intervention through brief exit interviews. Participants suggested reducing the total number of sessions (that during the trial ranged from 8 to 12) and shared that the SST intervention had a positive impact on their perceived resilience, as well as their ability to recover from cancer-related setbacks.

4. Discussion

Concomitant with physical health declines, several psychological and quality of life needs are prevalent in older adults with advanced lung cancer, such as increased depression, existential distress, uncertainty, and identity disruption [12,37,38]. As previously noted, available supportive-care interventions often overlook the aging concerns that older adults experience during this phase of life, and the need for tailored interventions, such as SST-LC, to address how their identity, role transitions, and health goals are impacted is paramount [12,13,14,15].
To the best of our knowledge, three previous studies tested interventions specifically designed to meet the unique needs of older adults living with advanced cancer. The first was a small-scale randomized control trial (RCT) that tested telephone-delivered cognitive-behavioral therapy (CBT) for older adults either undergoing active cancer treatment or within six months post-treatment (N = 29; 63% with advanced cancer) [39]. This study showed low acceptability with small effects on anxiety and no effects on depression. The second RCT focused on enhancing hope through film and hope-focused activities for patients with terminal cancer (N = 60), which improved hope and quality of life but did not change psychological distress [40]. The third study, a large-scale RCT of Dignity Therapy (N = 326), primarily involving older adults found improvements in quality of life but no changes in psychological distress [41]. Overall, these findings underscore a need for interventions designed for older adults to target for distress in this vulnerable population.
Our results extend traditional SST [18,19] to a novel context, highlighting the intervention’s versatility in mobilizing identity renegotiation, resilience-building, and pursuit of promotion and prevention goals. Among older adults with advanced lung cancer, SST-LC is well-suited to address discrepancies between former self-concepts and current physical/emotional realities, effectively supporting individuals as they gain a renewed sense of agency, adaptive coping skills, and resiliency in the face of uncertainty.
Specifically, our pilot evaluation of SST-LC suggested that this goal-focused supportive care intervention was both feasible and acceptable for older adults with advanced lung cancer. The brief nature of SST-LC and telehealth delivery likely increased participation, as evidenced by treatment adherence (89% completed all sessions), satisfaction (85% reported high satisfaction), and tailoring treatment content to address distress when living with advanced cancer. The use of the adaptome framework resulted in successful, iterative refinements of the intervention based on participant feedback [20]. We observed sustained improvements in psychological distress, depression, and functional well-being. These signals of preliminary efficacy persisted at the one-month follow-up, demonstrating the promise of SST-LC as a viable treatment in advanced cancer.
While this pilot study provides initial evidence that SST-LC has high feasibility, acceptability, and may reduce distress, we note specific priorities for future research. While a single-arm, small-sample design may be appropriate for testing feasibility and acceptability, it is underpowered to detect clinically significant effects [42]. The sample was predominantly White and English-speaking, which limits generalizability to representative populations. Additionally, conclusions about the sustainability of the intervention effects may require longer follow-up assessments. Finally, while telehealth delivery increases accessibility, it may hinder scalability in areas with limited technology support, particularly for those without internet access, which could prove challenging in situations with limited digital infrastructure.

5. Conclusions

Given that existing interventions often overlook age-specific and life-stage needs among older populations, such as identity disruption, uncertainty, and shifting goal priorities, SST-LC’s focus on resilience, goal pursuit, and identity management is invaluable for reducing distress and improving quality of life among older adults with advanced lung cancer. The extension of this work will require a larger randomized controlled trial, with a reduced number of sessions (e.g., 6), to assess whether SST for cancer populations compared to a control condition can relieve symptoms such as distress and improve quality of life, while also identifying potential mechanisms of the intervention (e.g., self-efficacy).

Author Contributions

Conceptualization, K.R. and T.J.S.; methodology, K.R. and T.J.S.; software, K.R.; formal analysis, K.R.; research data collection, K.F.; writing—review and editing, K.R., A.A., J.R., K.F., L.S.P. and T.J.S.; funding acquisition, K.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was primarily funded by the Duke Roybal Center, grant number P30AG064201 and the National Cancer Institute, grant number K08CA258947.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (Ethics Committee) of Duke University Health IRB (protocol code Pro00102705, 8/2019).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Our data are available upon request pending approvals from our Institutional Review Board. If interested, please e-mail the corresponding author.

Acknowledgments

We would like to thank the research participants and staff who made this work possible.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
SSTSelf-System Therapy
SST-LCSelf-System Therapy for Lung Cancer
QOLQuality of Life
FACT-LFunctional Assessment of Cancer Therapy-Lung
CORE-10Clinical Outcomes in Routine Evaluation-10
BDI-IIBeck Depression Inventory
CSQ-8The Client Satisfaction Questionnaire-8
ICCIntraclass correlation coefficient

References

  1. Smith, B.D.; Smith, G.L.; Hurria, A.; Hortobagyi, G.N.; Buchholz, T.A. Future of Cancer Incidence in the United States: Burdens Upon an Aging, Changing Nation. J. Clin. Oncol. 2009, 27, 2758–2765. [Google Scholar] [CrossRef]
  2. Kadambi, S.; Loh, K.P.; Dunne, R.; Magnuson, A.; Maggiore, R.; Zittel, J.; Flannery, M.; Inglis, J.; Gilmore, N.; Mohamed, M.; et al. Older adults with cancer and their caregivers—Current landscape and future directions for clinical care. Nat. Rev. Clin. Oncol. 2020, 17, 742–755. [Google Scholar] [CrossRef] [PubMed]
  3. Bravo-Iñiguez, C.; Perez Martinez, M.; Armstrong, K.W.; Jaklitsch, M.T. Surgical Resection of Lung Cancer in the Elderly. Thorac. Surg. Clin. 2014, 24, 371–381. [Google Scholar] [CrossRef]
  4. Howlader, N.; Noone, A.M.; Krapcho, M.; Garshell, J.; Miller, D.; Altekruse, S.F.; Kosary, C.I.; Yu, M.; Ruhl, J.; Tatalovich, Z.; et al. SEER Cancer Statistics Review, 1975–2012; National Cancer Institute: Bethesda, MD, USA, 2014. Available online: https://seer.cancer.gov/archive/csr/1975_2012/ (accessed on 1 May 2025).
  5. Venuta, F.; Diso, D.; Onorati, I.; Anile, M.; Mantovani, S.; Rendina, E.A. Lung Cancer in Elderly Patients. J. Thorac. Dis. 2016, 8 (Suppl. S11), S908–S914. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  6. National Cancer Institute. Cancer Stat Facts: Lung and Bronchus Cancer. Surveillance, Epidemiology, and End Results Program. Available online: https://seer.cancer.gov/statfacts/html/lungb.html (accessed on 2 July 2025).
  7. Zabora, J.; BrintzenhofeSzoc, K.; Curbow, B.; Hooker, C.; Piantadosi, S. The prevalence of psychological distress by cancer site. Psychooncology 2001, 10, 19–28. [Google Scholar] [CrossRef]
  8. Rose, S.; Boyes, A.; Kelly, B.; Cox, M.; Palazzi, K.; Paul, C. Lung Cancer Stigma Is a Predictor for Psychological Distress: A Longitudinal Study. Psychooncology 2021, 30, 1137–1144. [Google Scholar] [CrossRef]
  9. Soong, R.Y.; Low, C.E.; Ong, V.; Sim, I.; Lee, C.; Lee, F.; Chew, L.; Yau, C.E.; Lee, A.R.; Chen, M.Z. Exercise Interventions for Depression, Anxiety, and Quality of Life in Older Adults with Cancer: A Systematic Review and Meta-Analysis. JAMA Netw. Open 2025, 8, e2457859. [Google Scholar] [CrossRef] [PubMed]
  10. Evans Webb, M.; Murray, E.; Younger, Z.W.; Goodfellow, H.; Ross, J. The Supportive Care Needs of Cancer Patients: A Systematic Review. J. Cancer Educ. 2021, 36, 899–908. [Google Scholar] [CrossRef] [PubMed]
  11. Kumar, B.; Htaa, M.T.; Kerin-Ayres, K.; Smith, A.L.; Lacey, J.; Browne, S.B.; Grant, S. Living Well with Advanced Cancer: A Scoping Review of Non-Pharmacological Supportive Care Interventions. J. Cancer Surviv. 2024, 1–2. [Google Scholar] [CrossRef]
  12. Verduzco-Aguirre, H.C.; Babu, D.; Mohile, S.G.; Bautista, J.; Xu, H.; Culakova, E.; Canin, B.; Zhang, Y.; Wells, M.; Epstein, R.M.; et al. Associations of Uncertainty With Psychological Health and Quality of Life in Older Adults With Advanced Cancer. J. Pain Symptom Manag. 2021, 61, 369–376. [Google Scholar] [CrossRef]
  13. Marosi, C.; Köller, M. Challenge of cancer in the elderly. ESMO Open 2016, 1, e000020. [Google Scholar] [CrossRef] [PubMed]
  14. Velaithan, V.; Tan, M.M.; Yu, T.F.; Liem, A.; Teh, P.L.; Su, T.T. The Association of Self-Perception of Aging and Quality of Life in Older Adults: A Systematic Review. Gerontol. 2023, 64, gnad041. [Google Scholar] [CrossRef]
  15. Trevino, K.M.; Stern, A.; Prigerson, H.G. Adapting Psychosocial Interventions for Older Adults with Cancer: A Case Example of Managing Anxiety from Cancer (MAC). J. Geriatr. Oncol. 2020, 11, 1319–1323. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  16. O’Keefe, K.; Chen, M.; Lesser, K.J.; DuVall, A.S.; Dils, A.T. Treating Mental Health and Quality of Life in Older Cancer Patients with Cognitive Behavioral Therapy: A Systematic Review and Meta-Analysis. Int. J. Environ. Res. Public Health 2024, 21, 881. [Google Scholar] [CrossRef]
  17. Nelson, C.J.; Saracino, R.M.; Roth, A.J.; Harvey, E.; Martin, A.; Moore, M.; Marcone, D.; Poppito, S.R.; Holland, J. Cancer and Aging: Reflections for Elders (CARE): A Pilot Randomized Controlled Trial of a Psychotherapy Intervention for Older Adults with Cancer. Psychooncology 2019, 28, 39–47. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  18. Vieth, A.Z.; McGraw, K.; Holland, J.M.; Kadden, R.M.; Grawe, K.; Strauman, T.J. Self-System Therapy (SST): A Theory-Based Psychotherapy for Depression. Clin. Psychol. Sci. Pract. 2003, 10, 245–268. [Google Scholar] [CrossRef]
  19. Strauman, T.J.; Vieth, A.Z.; Merrill, K.A.; Kolden, G.G.; Woods, T.E.; Klein, M.H.; Papadakis, A.A.; Schneider, K.L.; Kwapil, L. Self-system therapy as an intervention for self-regulatory dysfunction in depression: A randomized comparison with cognitive therapy. J. Consult. Clin. Psychol. 2006, 74, 367–376. [Google Scholar] [CrossRef] [PubMed]
  20. Chambers, D.A.; Norton, W.E. The Adaptome: Advancing the Science of Intervention Adaptation. Am. J. Prev. Med. 2016, 51, 121–131. [Google Scholar] [CrossRef]
  21. Zoom Video Communications Inc. Zoom, Version 5.0 through 5.80; Zoom Video Communications: San Jose, CA, USA, 2024. Available online: https://zoom.us (accessed on 27 August 2025).
  22. Harris, P.A.; Taylor, R.; Thielke, R.; Payne, J.; Gonzalez, N.; Conde, J.G. Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. J. Biomed. Inform. 2009, 42, 377–381. [Google Scholar] [CrossRef] [PubMed]
  23. Barkham, M.; Bewick, B.; Mullin, T.; Gilbody, S.; Connell, J.; Cahill, J.; Mellor-Clark, J.; Richards, D.; Unsworth, G.; Evans, C. The CORE-10: A short measure of psychological distress for routine use in the psychological therapies. Couns. Psychother. Res. 2013, 13, 3–13. [Google Scholar] [CrossRef]
  24. Dozois, D.J.A.; Covin, R. The Beck Depression Inventory-II (BDI-II), Beck Hopelessness Scale (BHS), and Beck Scale for Suicide Ideation (BSS). In Comprehensive Handbook of Psychological Assessment, Vol. 2. Personality Assessment; Hilsenroth, M.J., Segal, D.L., Hersen, M.H., Eds.; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2004; pp. 50–69. [Google Scholar]
  25. Beck, A.T.; Steer, R.A.; Brown, G.K. Manual for the Beck Depression Inventory-II; Psychological Corporation: San Antonio, TX, USA, 1996. [Google Scholar] [CrossRef]
  26. Butt, Z.; Webster, K.; Eisenstein, A.R.; Beaumont, J.; Eton, D.; Masters, G.A.; Cella, D. Quality of life in lung cancer: The validity and cross-cultural applicability of the Functional Assessment Of Cancer Therapy-Lung scale. Hematol. Oncol. Clin. N. Am. 2005, 19, 389–420. [Google Scholar] [CrossRef]
  27. Attkisson, C.C.; Greenfield, T.K. Client Satisfaction Questionnaire-8 and Service Satisfaction Scale-30. In The Use of Psychological Testing for Treatment Planning and Outcome Assessment; Maruish, M.E., Ed.; Lawrence Erlbaum Associates, Inc.: Mahwah, NJ, USA, 1994; pp. 402–420. [Google Scholar]
  28. Braun, V.; Clarke, V. Using Thematic Analysis in Psychology. Qual. Res. Psychol. 2006, 3, 77–101. [Google Scholar] [CrossRef]
  29. IBM Corp. IBM SPSS Statistics for Windows, Version 29.0; IBM Corp.: Armonk, NY, USA, 2022. [Google Scholar]
  30. Eldridge, S.M.; Chan, C.L.; Campbell, M.J.; Bond, C.M.; Hopewell, S.; Thabane, L.; Lancaster, G.A. CONSORT 2010 Statement: Extension to Randomised Pilot and Feasibility Trials. BMJ 2016, 355, i5239. [Google Scholar] [CrossRef]
  31. Browne, R.H. On the Use of a Pilot Sample for Sample Size Determination. Stat. Med. 1995, 14, 1933–1940. [Google Scholar] [CrossRef] [PubMed]
  32. Julious, S.A. Sample Size of 12 per Group Rule of Thumb for a Pilot Study. Pharm. Stat. 2005, 4, 287–291. [Google Scholar] [CrossRef]
  33. Teresi, J.A.; Yu, X.; Stewart, A.L.; Hays, R.D. Guidelines for Designing and Evaluating Feasibility Pilot Studies. Med. Care 2022, 60, 95–103. [Google Scholar] [CrossRef]
  34. Winger, J.G.; Ramos, K.; Kelleher, S.A.; Somers, T.J.; Steinhauser, K.E.; Porter, L.S.; Kamal, A.H.; Breitbart, W.S.; Keefe, F.J. Meaning-Centered Pain Coping Skills Training: A Pilot Feasibility Trial of a Psychosocial Pain Management Intervention for Patients with Advanced Cancer. J. Palliat. Med. 2022, 25, 60–69. [Google Scholar] [CrossRef]
  35. Somers, T.J.; Abernethy, A.P.; Edmond, S.N.; Kelleher, S.A.; Wren, A.A.; Samsa, G.P.; Keefe, F.J. A Pilot Study of a Mobile Health Pain Coping Skills Training Protocol for Patients with Persistent Cancer Pain. J. Pain Symptom Manag. 2015, 50, 553–558. [Google Scholar] [CrossRef]
  36. Plumb Vilardaga, J.C.; Winger, J.G.; Teo, I.; Owen, L.; Sutton, L.M.; Keefe, F.J.; Somers, T.J. Coping Skills Training and Acceptance and Commitment Therapy for Symptom Management: Feasibility and Acceptability of a Brief Telephone-Delivered Protocol for Patients with Advanced Cancer. J. Pain Symptom Manag. 2020, 59, 270–278. [Google Scholar] [CrossRef]
  37. Polanski, J.; Jankowska-Polanska, B.; Rosinczuk, J.; Chabowski, M.; Szymanska-Chabowska, A. Quality of Life of Patients with Lung Cancer. OncoTargets Ther. 2016, 9, 1023–1028. [Google Scholar] [CrossRef]
  38. Arrieta, Ó.; Angulo, L.P.; Núñez-Valencia, C.; Dorantes-Gallareta, Y.; Macedo, E.O.; Martínez-López, D.; Alvarado, S.; Corona-Cruz, J.-F.; Oñate-Ocaña, L.F. Association of Depression and Anxiety on Quality of Life, Treatment Adherence, and Prognosis in Patients with Advanced Non-small Cell Lung Cancer. Ann. Surg. Oncol. 2012, 20, 2793–2795. [Google Scholar] [CrossRef] [PubMed]
  39. Trevino, K.M.; Stern, A.; Hershkowitz, R.; Kim, S.Y.; Li, Y.; Lachs, M.; Prigerson, H.G. Managing Anxiety from Cancer (MAC): A Pilot Randomized Controlled Trial of an Anxiety Intervention for Older Adults with Cancer and Their Caregivers. Palliat. Support. Care 2021, 19, 135–145. [Google Scholar] [CrossRef] [PubMed]
  40. Duggleby, W.D.; Degner, L.; Williams, A.; Wright, K.; Cooper, D.; Popkin, D.; Holtslander, L. Living with Hope: Initial Evaluation of a Psychosocial Hope Intervention for Older Palliative Home Care Patients. J. Pain Symptom Manag. 2007, 33, 247–257. [Google Scholar] [CrossRef]
  41. Chochinov, H.M.; Kristjanson, L.J.; Breitbart, W.; McClement, S.; Hack, T.F.; Hassard, T.; Harlos, M. Effect of Dignity Therapy on Distress and End-of-Life Experience in Terminally Ill Patients: A Randomised Controlled Trial. Lancet Oncol. 2011, 12, 753–762. [Google Scholar] [CrossRef]
  42. Leon, A.C.; Davis, L.L.; Kraemer, H.C. The Role and Interpretation of Pilot Studies in Clinical Research. J. Psychiatr. Res. 2011, 45, 626–629. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Study Flow CONSORT Diagram for Recruitment and Enrollment.
Figure 1. Study Flow CONSORT Diagram for Recruitment and Enrollment.
Cancers 17 02809 g001
Table 1. Demographic Characteristics of Pilot Trial Participants (N = 30).
Table 1. Demographic Characteristics of Pilot Trial Participants (N = 30).
Individual CharacteristicsNN%MeanStandard Deviation
Age 69.774.95
GenderMale723.3
Female2376.7
RaceAfrican American or Black413.3
White2686.7
EthnicityNot Hispanic30100.0
Hispanic00.0
EducationLess than high school00.0
High school degree or GED516.7
Some college or technical school930.0
4-year college degree620.0
Post-baccalaureate degree1033.3
MaritalMarried2191.3
Not married but living with a partner28.7
IncomeLess than USD 20,000310.3
USD 20,000–USD 39,999310.3
USD 40,000–USD 59,999827.6
USD 60,000–USD 79,999413.8
USD 80,000–USD 99,999620.7
USD 100,000–USD 120,999310.3
USD 121,000 or more26.9
Children under the age of 18No2996.7
Yes13.3
Table 2. SST-LC Pilot Trial Summary of Outcome Changes from Baseline to 12 Weeks.
Table 2. SST-LC Pilot Trial Summary of Outcome Changes from Baseline to 12 Weeks.
Mean (SD)Baseline to 12 Weeks Post-Intervention (N = 23)
Outcome VariableBaselinePost-TreatmenttdfpCohen’s d95% CI for d
[Lower, Upper Bound]
Distress14.55 (3.93)12.67 (3.62)2.46220.022 *0.51[0.07, 0.94]
Depression9.41 (6.09)6.17 (6.07)3.63220.001 *0.76[0.28, 1.2]
FACT
Dimensions
Emotional Well-being17.83 (3.89)18.65 (2.95)−2.04220.05 *−0.43[−0.849, 0.006]
Physical Health
- Functional
Well-Being
18.04 (5.18)21.41 (5.08)−2.89220.008 *−0.60[−1.04, −0.15]
Physical Health
- Physical
Well-Being
23.03 (4.08)24.30 (3.81)−1.67220.11−0.35[−0.77, 0.08]
Social
Well-Being
23.09 (5.66)23.66 (3.48)0.64220.530.13[−0.28, 0.54]
Quality of Life102.22 (16.71)109.12 (16.0)−1.95220.06−0.41[−0.83, 0.02]
Note. Results from these paired sample t-tests are exploratory. Cohen’s d: small effect = 0.20; medium effect = 0.50; large effect = 0.80. CI = Confidence Interval. * p < 0.05.
Table 3. SST-LC Pilot Trial Summary of Outcome Changes from Baseline to 16 Weeks.
Table 3. SST-LC Pilot Trial Summary of Outcome Changes from Baseline to 16 Weeks.
Mean (SD)Baseline to 16 Weeks Post-Intervention (N = 21)
Outcome VariableBaselineFollow-Up tdfpCohen’s d95% CI for d
[Lower, Upper Bound]
Distress14.55 (3.93)12.30 (3.60)2.74200.013 *0.59[0.13, 1.06]
Depression9.41 (6.09)6.13 (5.10)3.27200.004 *0.71[0.23, 1.19]
FACT
Dimensions
Emotional Well-being17.83 (3.89)19.48 (2.94)−2.90200.009 *−0.63[−1.10, −0.16]
Physical Health
- Functional
Well-Being
18.04 (5.18)19.75 (5.62)−1.21200.24−0.26[−0.69, 0.17]
Physical Health
- Physical
Well-Being
23.03 (4.08)22.94 (4.57)0.92200.370.20[−0.23, 0.63]
Social
Well-Being
23.09 (5.66)23.07 (4.03)1.30200.210.28[−0.16, 0.72]
Quality of Life102.22 (16.71)106.30 (17.51)−0.46200.65−0.10[−0.53, 0.33]
Note. Results from these paired sample t-tests are exploratory. Cohen’s d: small effect = 0.20; medium effect = 0.50; large effect = 0.80. CI = Confidence Interval. * p < 0.05.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Ramos, K.; Ayaz, A.; Riley, J.; Faircloth, K.; Porter, L.S.; Strauman, T.J. Adaptation and Implementation of Self-System Therapy for Older Adults with Advanced Lung Cancer: Pilot Trial Results. Cancers 2025, 17, 2809. https://doi.org/10.3390/cancers17172809

AMA Style

Ramos K, Ayaz A, Riley J, Faircloth K, Porter LS, Strauman TJ. Adaptation and Implementation of Self-System Therapy for Older Adults with Advanced Lung Cancer: Pilot Trial Results. Cancers. 2025; 17(17):2809. https://doi.org/10.3390/cancers17172809

Chicago/Turabian Style

Ramos, Katherine, Aliza Ayaz, Jennie Riley, Kaylee Faircloth, Laura S. Porter, and Timothy J. Strauman. 2025. "Adaptation and Implementation of Self-System Therapy for Older Adults with Advanced Lung Cancer: Pilot Trial Results" Cancers 17, no. 17: 2809. https://doi.org/10.3390/cancers17172809

APA Style

Ramos, K., Ayaz, A., Riley, J., Faircloth, K., Porter, L. S., & Strauman, T. J. (2025). Adaptation and Implementation of Self-System Therapy for Older Adults with Advanced Lung Cancer: Pilot Trial Results. Cancers, 17(17), 2809. https://doi.org/10.3390/cancers17172809

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop