Title: The Preferences of Breast Cancer Patients Regarding a Digital Social Care Platform
Version: 3 Date: 24 Mar 2025
Reviewer's report:
PEER REVIEWER ASSESSMENTS:
OBJECTIVE - Full research articles: is there a clear objective that addresses a testable research
question(s) (brief or other article types: is there a clear objective)?
Yes - there is a clear objective
DESIGN - Is the current approach (including controls and analysis protocols) appropriate for
the objective?
No - there are minor issues
EXECUTION - Are the experiments and analyses performed with technical rigor to allow
confidence in the results?
No - there are minor issues
STATISTICS - Is the use of statistics in the manuscript appropriate?
No - there are issues with the statistics in the study
INTERPRETATION - Is the current interpretation/discussion of the results reasonable and not
overstated?
No - there are minor issues
OVERALL MANUSCRIPT POTENTIAL - Is the current version of this work technically
sound? If not, can revisions be made to make the work technically sound?
Probably - with minor revisions
PEER REVIEWER COMMENTS:
GENERAL COMMENTS: General Comments
The manuscript presents an innovative and timely study exploring the preferences of breast
cancer patients for features of a digital social care platform using Conjoint Analysis (CA) and
a Discrete Choice Experiment (DCE). The study addresses an important gap in the literature by
focusing on patient-centered design of digital health interventions, which is increasingly relevant
in the era of digital healthcare. The use of CA, grounded in economic utility theory, is a robust
methodological choice for eliciting preferences without direct questioning, adding rigor to the
study. The findings—highlighting the significance of emotional support, informational support
(particularly via instructional videos), and esteem support—are well-aligned with existing
evidence and have practical implications for designing effective digital platforms.
Overall, the manuscript is well-written, with a clear structure and a comprehensive background
that situates the research within the broader context of breast cancer care and digital health.
However, there are several areas where clarity, methodological transparency, and discussion of
limitations could be improved to strengthen the submission. Below, I provide specific comments
on each section, followed by recommendations for revision.
Abstract
Strengths:
Concisely summarizes the study’s purpose, methods, results, and conclusions.
Highlights key findings (e.g., preference for emotional support, instructional videos) with
statistical significance, making it easy to grasp the study's impact.
Keywords are relevant and appropriate.
Weaknesses:
The abstract could better specify the sample size (158 patients) and setting (Iran) to provide
immediate context.
The phrase “almost 2.5 times more” (regarding instructional videos) is imprecise; reporting the
exact odds ratio (2.45) would enhance scientific accuracy.
The conclusion mentions “eliminate loneliness, stress, and anxiety,” but the study does not
directly measure these outcomes, only preferences. This overstates the findings.
Recommendations:
Add sample size and location: e.g., “A sample of 158 breast cancer patients in Iran
participated…”
Replace “almost 2.5 times more” with “2.45 times more likely (P<0.001)” for precision.
Revise the conclusion to align with the study’s scope, e.g., “These findings suggest digital tools
and tailored support could enhance patient engagement and quality of life.”
Background
Strengths:
Provides a thorough and well-referenced overview of the emotional, psychological, and social
challenges faced by breast cancer patients, justifying the need for social care support.
Effectively integrates literature on the role of social support and digital health, building a strong
case for the study.
The discussion of persuasive system design (PSD) and its relevance to digital health platforms
is a novel and appropriate theoretical framework.
Weaknesses:
Some statements are repetitive (e.g., the multifaceted nature of breast cancer is mentioned
multiple times), which could be streamlined for conciseness.
The transition from general social support to digital platforms feels abrupt; a clearer linkage
between traditional support and digital solutions would strengthen the narrative.
Citations are numerous but occasionally outdated (e.g., some references from 2015 or earlier);
more recent studies (2020–2024) could bolster relevance.
Recommendations:
Condense repetitive points to improve readability (e.g., combine the first two paragraphs into
a single, focused introduction).
Add a bridging sentence to connect traditional social support to digital platforms, e.g., “Given
the proven benefits of social support, digital platforms offer a scalable solution to extend these
benefits remotely.”
Update references where possible with recent literature, especially on digital health interventions
post-2020.
Review of the Literature
Strengths:
Comprehensive synthesis of prior studies on digital health applications for breast cancer patients,
with examples like “My Guide” and Twitter support groups.
Identifies a clear gap in the literature regarding patient preferences for digital platform features,
positioning the study as a valuable contribution.
The discussion of PSD principles is insightful and relevant to the study’s objectives.
Weaknesses:
Some cited studies (e.g., Buscemi et al., Wyatt et al.) lack sufficient detail (e.g., sample size,
methodology), reducing their illustrative power.
The section could better differentiate between general digital health benefits and specific social
care platform features, as the study focuses on the latter.
The gap in operationalizing PSD principles is noted but not elaborated with specific examples
of what remains unknown.
Recommendations:
Add brief details to key studies (e.g., “Buscemi et al. (n=50) found…”), to enhance credibility.
Narrow the focus to social care-specific digital interventions, distinguishing them from broader
mHealth apps.
Expand on the PSD gap with an example, e.g., “For instance, it is unclear whether patients prefer
automated reminders or peer interactions for sustained engagement.”
Theoretical Framework
Strengths:
The adoption of PSD as a framework is well-justified and logically tied to the study’s goals of
designing persuasive digital platforms.
The categorization of 28 principles into four groups is clearly explained and linked to social
support domains.
Weaknesses:
The translation of PSD principles into specific features (e.g., “provision of messages that
strengthen belonging”) is somewhat vague and could be more concrete.
The framework is introduced late in the manuscript; integrating it earlier (e.g., in the
Background) might improve flow.
Recommendations:
Provide specific examples for each category (e.g., “Social support: offering moderated chat
rooms for peer interaction”).
Move the theoretical framework to the end of the Background section to provide earlier context
for the study’s approach.
Methods
Strengths:
The use of CA and DCE is a methodological strength, well-suited to the research question, and
rigorously implemented.
Detailed explanation of sample size calculation, inclusion/exclusion criteria, and ethical
considerations enhances transparency.
The step-by-step description of conjoint design (attributes, levels, scenario development) is
thorough and replicable.
Weaknesses:
The sample size justification is overly complex and includes multiple methods (e.g., rule of
thumb, formula), which may confuse readers. A single, clear rationale would suffice.
The piloting process (think-aloud interviews) is mentioned but lacks detail on findings or
adjustments made.
The choice of Ordered Logistic Regression is appropriate but assumes normality of residuals,
which is not verified in the results.
Recommendations:
Simplify sample size justification, e.g., “Based on Johnson and Orme’s rule (nta/c # 500), a
minimum of 62 respondents was required, but 158 were recruited to account for a 42% response
rate (Merlo et al.).”
Add a sentence on pilot findings, e.g., “Pilot testing (n=20) confirmed scenario clarity, with
minor wording adjustments made.”
Include a brief note in the Results or Methods verifying the normality assumption for residuals,
or justify its absence.
Results
Strengths:
Results are clearly presented with statistical significance (P#0.05) and meaningful coefficients/
odds ratios, aligning with the study’s objectives.
Tables are well-organized and effectively summarize key findings (e.g., Table 3’s regression
coefficients).
The focus on emotional, informational, and esteem support as top preferences is compelling and
actionable.
Weaknesses:
The non-significant finding for tangible support (P=0.075) is mentioned briefly but not explored,
missing an opportunity to discuss its implications.
Participant characteristics (Table 2) are reported but not analyzed for their influence on
preferences, limiting depth.
Marginal effects (Table 4) are insightful but lack explanation of their practical significance.
Recommendations:
Discuss the non-significant tangible support finding in the Results or Discussion, e.g., “The lack
of preference between physical help and medication reminders suggests context-specific needs.”
Analyze whether demographic factors (e.g., age, employment) influenced preferences, even
briefly, or justify their exclusion.
Clarify the meaning of marginal effects, e.g., “A 17% increase in take-up rate for instructional
videos indicates a strong patient preference for visual learning.”
Discussion
Strengths:
Effectively ties findings to existing literature, reinforcing the importance of emotional and
informational support.
Practical implications for platform design (e.g., prioritizing instructional videos) are well-
articulated and actionable.
The acknowledgment of study limitations is thorough and demonstrates reflexivity.
Weaknesses:
Some comparisons to prior studies (e.g., video education reducing distress) overstate alignment,
as this study measures preferences, not outcomes like distress.
The discussion of tangible support’s non-significance is delayed to the Discussion and could
be more robust.
Practical implementation strategies are mentioned but lack specificity (e.g., how to involve
patients in co-design).
Recommendations:
Temper outcome-related claims, e.g., replace “reduced distress” with “may support reduced
distress based on patient preferences.”
Expand on tangible support, e.g., “This may reflect a preference for emotional over practical aid
in a digital context, warranting further study.”
Add specific implementation examples, e.g., “Focus groups could identify preferred video
content, while usability testing ensures accessibility.”
Conclusion
Strengths:
Succinctly summarizes key findings and their implications for digital health design.
Highlights the broader relevance for policymakers, practitioners, and developers, enhancing
impact.
Weaknesses:
Repeats points from the Discussion without adding new insights.
The claim of “eliminating loneliness, stress, and anxiety” exceeds the study’s scope (preferences,
not outcomes).
Recommendations:
Reframe to focus on potential, e.g., “These features may help reduce loneliness and stress by
enhancing engagement.”
Add a forward-looking statement, e.g., “Future research should validate these preferences in
real-world settings.”
Overall Assessment
This is a strong manuscript with a clear contribution to the field of digital health and breast
cancer care. The methodology is rigorous, the findings are relevant, and the implications are
practical. However, minor revisions are needed to enhance clarity, align claims with evidence,
and deepen the discussion of results. I recommend acceptance with minor revisions, contingent
on addressing the points above.
Specific Revision Suggestions
Clarity and Conciseness: Streamline the Background and Abstract for brevity and precision.
Methodological Transparency: Simplify sample size justification and report pilot findings.
Results Depth: Analyze demographic influences and discuss non-significant findings earlier.
Scope Alignment: Avoid overstating outcomes (e.g., “eliminate loneliness”) and focus on
preferences.
Practicality: Provide concrete examples for implementation strategies.
REQUESTED REVISIONS:
As described above