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9.4 statistical analyses

A statistical analysis plan (SAP) will be developed prior to database lock. The SAP will detail all planned analyses and analytic methods. All statistical analyses will be performed using SAS or R packages. Graphical displays (e.g., bar charts, boxplots) and summary statistics (e.g., mean, median, standard deviation, interquartile range) will be used to characterize the data. Two sample t-tests or non-parametric Wilcoxon rank-sum tests will be used to compare continuous measures. Normality and variance homogeneity assumptions will be assessed, with appropriate data transformations as needed. The chi-square test will be used to evaluate associations between discrete variables. 9.4.1 MISSING DATA The analytic method for the primary endpoint will be generalized estimating equations (GEEs), which requires missing data to be missing completely at random for valid inference. We expect the rate of missing data to small and anticipate GEE analysis to be appropriate. However, if the rate of missing data is significant, we will use linear mixed effect regression (LMER) as our primary analytic approach and GEEs as a secondary approach. A review of the data will be performed prior to database lock to establish overall rates of missingness for the primary endpoint and the SAP updated if needed to reflect any changes in planned analyses. 9.4.2 ANALYSIS OF THE PRIMARY ENDPOINT We will use a model-based approach to analyze change in IMAGE-HN score from baseline to 6-month follow-up. Specifically, change in IMAGE-HN score will be modeled using a regression model with a factor for trial arm, covariates for the randomization stratification variable of site and free flap reconstruction, and pre-specified baseline covariates known to be prognostic for the primary endpoint including baseline IMAGE-HN score, gender, education, employment, tumor location, and adjuvant therapy.8,75 The selection of pre-specified baseline covariates known to be prognostic follows best practices for randomized clinical trials.103 Additionally, adjusting for the baseline score in a change-score analysis is discussed at length by Frank Harrell and James Slaughter.104 The GEE regression model was selected to account for the clustering of patients within psychologist (BRIGHT arm) or HN clinical staff member (AC arm). Our preferred model-based approach is a marginal model using GEEs because Based on the NIH Protocol Template for Behavioral and Social Sciences Research 45 subsequent inference best aligns with the trial's stated primary objective. Furthermore, GEEs are robust to variance misspecification. We will use GEEs with an identity link and an exchangeable working correlation structure. Final inference will be based on the robust sandwich estimator. The primary analysis will use the 6-month IMAGE-HN evaluable set, which eliminates unit non-response, that is, patient data where the baseline or 6-month survey is not completed. However, the potential for survey item non-response exists. There are three types of item non-response to consider: (1) the item is missing at baseline and at follow-up; (2) the item is missing at baseline but not missing at follow-up; and
(3) the item is not missing at baseline but is missing at follow-up. We expect the rate of item nonresponse at baseline to be 0% given training of study coordinators and our experience with the pilot study. In the event of item non-response at the 6-month follow-up, we adopt a conservative imputation approach to avoid inflation of treatment effect. Accordingly, we will impute the baseline value for the given item to reflect no change. As a sensitivity analysis, we will also impute the item's value from the most recent follow-up time prior to 6-months. Finally, depending on the extent of missing data, we may additionally perform sensitivity analyses using multiple imputation or treating survey total scores as interval censored. To evaluate the inferential impact of our modeling choice (GEE) and cross-sectional (as opposed to longitudinal) data analyses, the following secondary analyses will be conducted using the 6-month IMAGE-HN evaluable set:  
1. We will model change in IMAGE-HN score from baseline to 6-month follow-up using a LMER
model with a factor for trial arm, the randomization stratification variables of site and free flap reconstruction, and pre-specified baseline covariates including baseline IMAGE-HN score, gender, education, employment, tumor location, and adjuvant therapy. Cluster-specific random effects will be included assuming an exchangeable correlation structure.  
2. We will model change in IMAGE-HN score from baseline across all timepoints using GEEs and LMER models as described. Additional model terms for time (discrete), and trial arm-by-time interaction will be included.
All analyses described will be repeated using the per-protocol analysis set.  
To evaluate the inferential impact of eliminating unit non-response in our primary analysis, the following additional sensitivity analyses will be performed using the FAS: (1) any trial participant missing the 6month follow-up survey will be counted as having a 6-month total score equal to the baseline total score (no change from baseline); and (2) any trial participant missing the 6-month follow-up survey will be counted as having a 6-month total score equal to the maximum total score. Trial participants without a baseline survey will be excluded from these analyses.  
We will perform a causal mediation analysis105 to evaluate the degree to which the effect of treatment
(BRIGHT) on the primary outcome (change in IMAGE-HN scores between baseline and 6-month followup) is mediated by changes in candidate mechanism of change variables (between baseline and 3-month follow-up, covariates). We will use structural equation modeling to perform mediation analysis for each of the following mechanism of change variables: (1) BICSI Positive Rational Acceptance score;55 (2) BICSI Avoidance score;55 (3) BICSI Appearance Fixing score;55 and (4) Automatic Thoughts Questionnaire score.96 This approach allows for ease of interpretation and estimation in Mplus. Model fit will be assessed using chi-square, comparative fit index (>0.95), root mean square of approximation (<0.06),
and standardized root mean square residual (<0.08).106,107 Missing data will be handled with maximum likelihood estimation.108 If we encounter challenges in model stability, we will use Baron and Kenny's approach.109 The following regression analyses will be performed: (i) the outcome (IMAGE-HN score) is regressed on a treatment group indicator (BRIGHT, AC) to obtain a regression model measure of the intervention effect; (ii) the candidate mediator (e.g., BICSI Avoidance score) is regressed on the treatment group indicator (BRIGHT, AC) to obtain a measure of the intervention's effect on the covariate; and (iii) the outcome (IMAGE-HN score) is regressed on both the treatment group indicator (BRIGHT, AC) and the candidate mediator (e.g., BICSI Avoidance score). We will conclude that the candidate mediator in fact mediates the effects of the intervention if: (1) in both analyses (i) and (ii), the treatment group indicator is significant; and (2) in analysis (iii), the candidate mediator is significant and the coefficient estimate of the treatment group indicator is smaller in absolute value than its counterpart in analysis (i). If we detect mediation, we will consider Sobel's test to assess the significance of the mediation effect. We will examine standardized coefficients for the direct pathways and the mediation pathways to compare the strength of each. If the cluster effect is significant, we will conduct multilevel mediation analysis for partially nested data.110 The study design consideration and analytic plan follow recommended criteria to provide evidence for mechanism of change above and beyond statistical mediation.111 We will also explore mediation analysis using multiple mediators.112,113 Finally, to better understand the temporal dynamics of causal intervention effects, we will adapt Goldsmith's approach to: (1) examine the intervention effect on outcomes at different time points; (2) examine the intervention effect on hypothesized mediators at different time points; (3) examine the relation of the mediator to the outcome at different time points; and (4) determine if there is temporal variation in the mediating process.114 If there is temporal variation in the mediating process, we will fit a multilevel mediation model using the approach described by Preacher.115 9.4.4 SAFETY ANALYSES
All patients in the SAS will be evaluated for safety and toxicity. Adverse events, SAEs and will be summarized. Safety analyses will include the following summaries:
- AEs, including severity and relationship to a study intervention - SAEs, including relationship to a study intervention 9.4.5 PLANNED INTERMIN ANALYSES
N/A
9.4.6 SUB-GROUP ANALYSES Treatment heterogeneity will be evaluated by conducting the following sub-group analyses of the primary and secondary endpoints:
- Age: > 65 years vs < 65 years - Race: white vs non-white Based on the NIH Protocol Template for Behavioral and Social Sciences Research 47  
- Gender: male vs female - Education: < high school vs > high school - Employment status: disability/unemployed vs working vs retired
- Tumor location: upper aerodigestive tract cancer vs salivary/facial cutaneous cancer - Reconstruction: non-free flap reconstruction vs free flap reconstruction - Adjuvant Therapy: none vs radiation therapy/chemoradiation
9.4.7 EXPLORATORY ANALYSES
N/A
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9.5 regulatory ethical and study

9.5.1 SINGLE IRB COORDINATION The study will be conducted under a single IRB study with MUSC IRB serving as the IRB of record. The MUSC IRB will initiate the reliance agreements with each relying institution, that each relying institutionwill be responsible for performing a local context review of the study to ensure that the protocol is appropriate and reasonable for their respective study populations. The structure and organization of the study team is shown is described below. 1. **Administrative Sites.** The overall administration of the study will occur at MUSC. 2. **Data Coordinating Sites.** MUSC will serve as the data coordinating site. Study documents will originate from MUSC and be disseminated to each site. 3. **Participating Sites.** In this multisite clinical trial comparing BRIGHT with AC, eligible patients with clinically significant HNC-related BID will be recruited from MUSC, HFH, and WUSM. Study procedures and assessments will be conducted at each site as described in the protocol. 4. **Separate Laboratory and Testing Centers.** There are no separate laboratory and testing centers. 5. **Study Team Composition.** The organization of the study team is shown in **Figure 8**. For the conduct of the trial, the structure of each study team is identical (site PI, psychologist, HNC Clinical staff, and  The study will be coordinated as an sIRB study with the following communication plan. Study documents will be maintained in a HIPAA-compliant and secure shared folder (MUSC Box) to which all non-MUSC study personnel will be given download access. Interactions among sites will be coordinated through site PIs via secure email, telephone call, or video telemedicine sessions (e.g., Microsoft Teams). 9.5.2 INFORMED CONSENT PROCESS 9.5.2.1 CONSENT/ASSENT AND OTHER INFORMATIONAL DOCUMENTS PROVIDED TO
PARTICIPANTS
Consent forms describing in detail the study intervention, study procedures, and risks will be provided to the participant (either on paper or electronically as an eConsent) and documentation of informed consent will be completed prior to starting the study intervention. 9.5.2.2 CONSENT PROCEDURES AND DOCUMENTATION We will obtain full written (either via paper-based or electronic signature) informed consent from patients enrolling in the study. Informed consent will occur via face-face discussion in clinic or via telemedicine between one of the study team members designated to perform informed consent and the potential study participant. The study member will explain the elements of the informed consent form including purpose, methods, extent of the study, risks, benefits, and alternatives to potential participants. Participants will be asked to read the consent form, given appropriate time to read the document on their own, and allowed to ask any questions prior to signing it. Consents will be written in simple, easy-to-understand language and obtained on the day of enrollment by one of the study team members designated to perform informed consent. A study team member will answer any questions about the study and participants will be asked to sign the consent and HIPAA forms. All participants will sign informed consent forms before the interview (either via paper-based informed consent or electronic signature of the REDCap-based electronic informed consent). All participants will receive a copy of their informed consent and HIPAA forms for their records (either a paper copy or an emailed copy). The informed consent process will take place in a private room in a private research space at each site (if in-person) or via secure telemedicine platform (if electronic informed consent). Only the study participant will provide informed consent. The signed copy of the informed consent document will be stored in the study binder in each patient's section. Subjects will be allowed up to one week to decide whether to participate in the study. If required by the site, participants will also complete a HIPAA form at the same time using the same procedures as described above. All participants will receive a copy of their informed consent and HIPAA forms (either paper or emailed) for their records. Separate copies of the documents will be stored in the study binder under each patient's section.  
9.5.3 STUDY DISCONTINUATION AND CLOSURE
This study may be temporarily suspended or prematurely terminated if there is sufficient reasonable cause. Written notification, documenting the reason for study suspension or termination, will be provided by the suspending or terminating party to study participants, investigator, funding agency, and regulatory authorities. If the study is prematurely terminated or suspended, the PI will promptly inform study participants, the IRB, and sponsor/funding agency and will provide the reason(s) for the termination or suspension. Study participants will be contacted, as applicable, and be informed of changes to study visit schedule.  
Circumstances that may warrant termination or suspension include, but are not limited to:
- Determination of unexpected, significant, or unacceptable risk to participants - Insufficient compliance of study staff to the protocol (e.g., significant protocol violations) - Data that are not sufficiently complete and/or evaluable
The study may resume once concerns about safety, protocol compliance, and data quality are addressed, and satisfy the funding agency, sponsor, IRB, or other relevant regulatory or oversight bodies. 9.5.4 CONFIDENTIALITY AND PRIVACY Participant confidentiality and privacy is strictly held in trust by the participating investigators, their staff, the safety and oversight monitor(s), and the sponsor(s) and funding agency. This confidentiality is extended to the data being collected as part of this study. Data that could be used to identify a specific study participant will be held in strict confidence within the research team. No personally identifiable information from the study will be released to any unauthorized third party without prior written approval of the sponsor/funding agency. To help protect participant confidentiality, we will assign a unique study ID number to each subject's information in place of his/her name and will label data collection forms only with the ID number. All hard copy and electronic files will be stored appropriately using double-locked methods and password-protection. Only the study team member will have access to study records. Participant data will be collected and recorded on either a password-protected electronic data capture format REDCap or paper-based forms depending upon patient preference. For the paper collection data method, the data collection form will be labeled only with the participant's unique study ID number, and then stored within locked drawers in a locked office. The information on these paper forms will be transferred to a password-protected REDCap database such that all data will be stored in the password-protected REDCap Database. Only members of the study team will have access to the data. All research activities will be conducted in as private a setting as possible. The study monitor, other authorized representatives of the sponsor or funding agency, representatives of the IRB, regulatory agencies or representatives from companies or organizations supplying the product, may inspect all documents and records required to be maintained by the investigator, including but not limited to, medical records (office, clinic, or hospital) and pharmacy records for the participants in this study. The clinical study site will permit access to such records. The study participant's contact information will be securely stored at each clinical site for internal use during the study. At the end of the study, all records will continue to be kept in a secure location for as long a period as dictated by the reviewing IRB, Institutional policies, or sponsor/funding agency requirements. It is NIH policy that the results and accomplishments of the activities that it funds should be made available to the public (see *https://grants.nih.gov/policy/sharing.htm*). The PI will ensure all mechanisms used to share data will include proper plans and safeguards for the protection of privacy, confidentiality, and security for data dissemination and reuse (e.g., all data will be thoroughly de-identified and will not be traceable to a specific study participant). Plans for archiving and long-term preservation of the data will be implemented, as appropriate. To further protect the privacy of study participants, the Secretary, Health and Human Services (HHS), has issued a Certificate of Confidentiality (CoC) to all researchers engaged in biomedical, behavioral, clinical or other human subjects research funded wholly or in part by the federal government. Recipients of NIH funding for human subjects research are required to protect identifiable research information from forced disclosure per the terms of the NIH Policy (see https://humansubjects.nih.gov/coc/index). As set forth in 45 CFR Part 75.303(a) and NIHGPS Chapter 8.3, recipients conducting NIH-supported research covered by this Policy are required to establish and maintain effective internal controls (e.g., policies and procedures) that provide reasonable assurance that the award is managed in compliance with Federal statutes, regulations, and the terms and conditions of award. It is the NIH policy that investigators and others who have access to research records will not disclose identifying information except when the participant consents or in certain instances when federal, state, or local law or regulation requires disclosure. NIH expects investigators to inform research participants of the protections and the limits to protections provided by a Certificate issued by this Policy. 9.5.5 FUTURE USE OF STORED SPECIMENS AND DATA Data collected for this study will be analyzed and stored with the study team. After the study is completed, the de-identified, archived data will be transmitted to and stored with the study team, for use by other researchers including those outside of the study. 9.5.6 KEY ROLES AND STUDY GOVERNANCE
Principal Investigator Evan Graboyes, MD, MPH, FACS Medical University of South Carolina 135 Rutledge Ave, MSC 550 Charleston, SC 29425 843-792-0719  
  
9.5.7 SAFETY OVERSIGHT Safety oversight will be under the direction of a PI. Aggregate reviews will occur by the PI for all AEs, UPs, protocol violations, audit results, early withdrawals, whether the study accrual pattern warrants continuation/action, and endpoint data. Aggregate reviews will occur monthly. 9.5.8 CLINICAL MONITORING N/A 9.5.9 QUALITY ASSURANCE AND QUALITY CONTROL Each clinical site will perform internal quality management of study conduct, data and biological specimen collection, documentation and completion. Quality control procedures will be implemented as follows: Informed consent --- Study staff will review both the documentation of the consenting process as well as a percentage of the completed consent documents. This review will evaluate compliance with GCP, accuracy, and completeness. Feedback will be provided to the study team to ensure proper consenting procedures are followed. Source documents and the electronic data --- Data will be initially captured on source documents (see Section 9.5.10, Data Handling and Record Keeping) and will ultimately be entered into the study database. To ensure accuracy site staff will compare a representative sample of source data against the database, targeting key data points in that review. Intervention Fidelity - Consistent delivery of the study interventions will be monitored throughout the intervention phase of the study. Procedures for ensuring fidelity of intervention delivery are described in Section 6.2.1, Interventionist Training and Tracking. Should independent monitoring become necessary, the PI will provide direct access to all trial related sites, source data/documents, and reports for the purpose of monitoring and auditing by the sponsor/funding agency, and inspection by local and regulatory authorities. 9.5.10 DATA HANDLING AND RECORD KEEPING 9.5.10.1 DATA COLLECTION AND MANAGEMENT RESPONSIBILITIES Data collection will be the responsibility of the clinical trial staff at the site under the supervision of the site investigator. The investigator will be responsible for ensuring the accuracy, completeness, legibility, and timeliness of the data reported. All source documents will be completed in a neat, legible manner to ensure accurate interpretation of data. Hardcopies of the study visit worksheets will be provided for use as source document worksheets for recording data for each participant consented/enrolled in the study. Data recorded in the eCRF derived from source documents will be consistent with the data recorded on the source documents. Based on the NIH Protocol Template for Behavioral and Social Sciences Research 52 Clinical data will be entered into REDCap. The data system includes password protection and internal quality checks, such as automatic range checks, to identify data that appear inconsistent, incomplete, or inaccurate. Clinical data will be entered directly from the source documents. 9.5.10.2 STUDY RECORDS RETENTION In accordance with Health and Human Services regulation at 45 CFR 46.115(b), we will retain IRB records for at least three years. At the end of three years, records will be boxed, labeled, and sent to central storage for another three years. Research records will be retained for six years to allow evaluation and repetition by others of the results and to investigate an allegation of research misconduct. 9.5.11 PROTOCOL DEVIATIONS A protocol deviation is any variance from the protocol involving a subject or subjects that is not approved by the IRB prior to its initiation or implementation, and occurs when a member of the study team departs from the IRB-approved protocol in any way without the investigator first obtaining IRB approval (See MUSC IRB Policy HRPP 4.14).  
9.5.12 PUBLICATION AND DATA SHARING POLICY This study will be conducted in accordance with the following publication and data sharing policies and regulations: National Institutes of Health (NIH) Public Access Policy, which ensures that the public has access to the published results of NIH funded research. It requires scientists to submit final peer-reviewed journal manuscripts that arise from NIH funds to the digital archive PubMed Central upon acceptance for publication. This study will comply with the NIH Data Sharing Policy and Policy on the Dissemination of NIH-Funded Clinical Trial Information and the Clinical Trials Registration and Results Information Submission rule. As such, this trial will be registered at ClinicalTrials.gov, and results information from this trial will be submitted to ClinicalTrials.gov. In addition, every attempt will be made to publish results in peer-reviewed journals. Data from this study may be requested from other researchers 2 years after the completion of the primary endpoint by contacting Evan Graboyes, MD, MPH, FACS. Considerations for ensuring confidentiality of these shared data are described in **Section 9.5.4.** 9.5.13 CONFLICT OF INTEREST POLICY The independence of this study from any actual or perceived influence is critical. Therefore, any actual conflict of interest of persons who have a role in the design, conduct, analysis, publication, or any aspect of this trial will be disclosed and managed. Furthermore, persons who have a perceived conflict of interest will be required to have such conflicts managed in a way that is appropriate to their participation in the design and conduct of this trial. The study leadership in conjunction with the NCI has established policies and procedures for all study group members to disclose all conflicts of interest and will establish a mechanism for the management of all reported dualities of interest. 9.6 ADDITIONAL CONSIDERATIONS N/A
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9.7 abbreviations and special terms

8  2023  
| Table 9. Abbreviations and Special Terms AC Attention Control AE Adverse Event AJCC American Joint Committee on Cancer BICSI Body Image Coping Strategies Inventory BID Body Image-Related Distress CBT Cognitive Behavioral Therapy CFR Code of Federal Regulations BRIGHT Building a Renewed ImaGe after Head & neck cancer Treatment COC Certificate of Confidentiality CONSORT Consolidated Standards of Reporting Trials DSMP Data Safety Monitoring Plan eCRF Electronic Case Report Form EHR Electronic Health Record EORTC European Organisation for Research and Treatment of Cancer FAS Full Analysis Set GEE Generalized Estimating Equation GCP Good Clinical Practice HIPAA Health Insurance Portability and Accountability Act  HNC Head and Neck Cancer ICC Intracluster Correlation Coefficient ICF Informed Consent Form ICH International Council on Harmonisation  IMAGE-HN Inventory to Measure and Assess imaGe disturbancE-Head & Neck IRB Institutional Review Board ITT Intention-To-Treat LMER Linear Mixed Effect Regression MUSC Medical University of South Carolina MyCB MyChangedBody NCI National Cancer Institute NCT National Clinical Trial NIH National Institutes of Health ORHP Office for Human Research Protections PI Principal Investigator PROM Patient-Reported Outcome Measure PRMOIS Patient-Reported Outcomes Measurement Information System QOL Quality of Life RCT Randomized Clinical Trial REDCap Research Electronic Data Capture SAE Serious Adverse Event SAP Statistical Analysis Plan SAS Safety Analysis Set SF Short Form SOA Schedule of Activities SOP Standard Operating Procedure UP Unanticipated Problem   |
|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|  
Based on the NIH Protocol Template for Behavioral and Social Sciences Research 54 US United States 9.8 PROTOCOL AMENDMENT HISTORY  
| Table 10. Protocol Amendment History Version Date Description of Change   | Brief Rationale             |                                       |                       |
|---------------------------------------------------------------------------|-----------------------------|---------------------------------------|-----------------------|
| 2.0                                                                       | 8 December                  | See attached separate document        | See attached separate |
| 2022                                                                      | describing protocol changes | document describing protocol  changes |                       |
| 3.0                                                                       | 8 February                  | See attached separate document        | See attached separate |
| 2023                                                                      | describing protocol changes | document describing protocol  changes |                       |  
10 **REFERENCES**
1. Cohen EE, LaMonte SJ, Erb NL, et al. American Cancer Society Head and Neck Cancer Survivorship Care Guideline. CA Cancer J Clin 2016; 66:203-239.  
2. Nekhlyudov L, Lacchetti C, Davis NB, et al. Head and Neck Cancer Survivorship Care Guideline: American Society of Clinical Oncology Clinical Practice Guideline Endorsement of the American Cancer Society Guideline. J Clin Oncol 2017; 35:1606-1621.  
3. Fingeret MC, Nipomnick S, Guindani M, Baumann D, Hanasono M, Crosby M. Body image screening for cancer patients undergoing reconstructive surgery. Psychooncology 2014; 23:898-905.  
4. Macias D, Hand BN, Pipkorn P, et al. Association of Inventory to Measure and Assess imaGe Disturbance - Head and Neck Scores With Clinically Meaningful Body Image-Related Distress Among Head and Neck Cancer Survivors. Front Psychol 2021; 12:794038.  
5. Fingeret MC, Teo I, Goettsch K. Body image: a critical psychosocial issue for patients with head and neck cancer. Curr Oncol Rep 2015; 17:422.  
6. Fingeret MC, Yuan Y, Urbauer D, Weston J, Nipomnick S, Weber R. The nature and extent of body image concerns among surgically treated patients with head and neck cancer. Psychooncology 2012; 21:836-844.  
7. Rhoten BA, Murphy B, Ridner SH. Body image in patients with head and neck cancer: a review of the literature. Oral Oncol 2013; 49:753-760.  
8. Macias D, Hand BN, Maurer S, et al. Factors Associated With Risk of Body Image-Related Distress in Patients With Head and Neck Cancer. JAMA Otolaryngol Head Neck Surg 2021; 147:1019-1026.
9. Buckwalter AE, Karnell LH, Smith RB, Christensen AJ, Funk GF. Patient-reported factors associated with discontinuing employment following head and neck cancer treatment. Arch Otolaryngol Head Neck Surg 2007; 133:464-470.  
10. Osazuwa-Peters N, Simpson MC, Zhao L, et al. Suicide risk among cancer survivors: Head and neck versus other cancers. Cancer 2018; 124:4072-4079.  
11. Cognetti DM, Villaflor VM, Fakhry C, Miller MC, Malloy KM. Survivorship support in head and neck cancer: American Head and Neck Society survey. Head Neck 2020.  
12. Huang S, Liu HE. Effectiveness of cosmetic rehabilitation on the body image of oral cancer patients in Taiwan. Support Care Cancer 2008; 16:981-986.  
13. Chen SC, Huang BS, Lin CY, et al. Psychosocial effects of a skin camouflage program in female survivors with head and neck cancer: A randomized controlled trial. Psychooncology 2017; 26:1376-1383.  
14. Melissant HC, Jansen F, Eerenstein SEJ, et al. A structured expressive writing activity targeting body image-related distress among head and neck cancer survivors: who do we reach and what are the effects? Support Care Cancer 2021.  
15. Ellis MA, Sterba KR, Brennan EA, et al. A Systematic Review of Patient-Reported Outcome Measures Assessing Body Image Disturbance in Patients with Head and Neck Cancer. Otolaryngol Head Neck Surg 2019; 160:941-954.  
16. Graboyes EM, Maurer S, Park Y, et al. Evaluation of a novel telemedicine-based intervention to manage body image disturbance in head and neck cancer survivors. Psychooncology 2020; 29:1988-1994.  
17. Folkman S. Positive psychological states and coping with severe stress. Soc Sci Med 1997; 45:1207-1221.  
18. David D, Montgomery GH. The Scientific Status of Psychotherapies: A New Evaluative Framework for Evidence-Based Psychosocial Interventions. Clin Psychol Sci Prac 2011; 18:8999.  
19. David D, Szentagotai A. Cognitions in cognitive-behavioral psychotherapies; toward an integrative model. Clin Psychol Rev 2006; 26:284-298.  
20. Murphy R, Cooper Z, Hollon SD, Fairburn CG. How do psychological treatments work?  
Investigating mediators of change. Behav Res Ther 2009; 47:1-5.  
21. Powers MB, de Kleine RA, Smits JAJ. Core Mechanisms of Cognitive Behavioral Therapy for Anxiety and Depression: A Review. Psychiatr Clin North Am 2017; 40:611-623.  
22. Dobson KS. The science of CBT: toward a metacognitive model of change? Behav Ther 2013; 44:224-227.  
23. Hofmann SG, Asmundson GJ, Beck AT. The science of cognitive therapy. Behav Ther 2013; 44:199-212.  
24. Cash TF, Smolak L. Body Image: A Handbook of Science, Practice, and Prevention. New York:
Guilford Press, 2012:490.  
25. Kayser K, Brydon DM, Moon H, Zebrack B. Institutional capacity to provide psychosocial care in cancer programs: Addressing barriers to delivering quality cancer care. Psychooncology 2020; 29:1995-2002.  
26. Wampold BE. How important are the common factors in psychotherapy? An update. World Psychiatry 2015; 14:270-277.  
27. Graboyes EM, Hand BN, Ellis MA, et al. Validation of a Novel, Multidomain Head and Neck Cancer Appearance- and Function-Distress Patient-Reported Outcome Measure. Otolaryngol Head Neck Surg 2020; 163:979-985.  
28. Miller KD, Nogueira L, Mariotto AB, et al. Cancer treatment and survivorship statistics, 2019.  
CA Cancer J Clin 2019; 69:363-385.
29. Tota JE, Best AF, Zumsteg ZS, Gillison ML, Rosenberg PS, Chaturvedi AK. Evolution of the Oropharynx Cancer Epidemic in the United States: Moderation of Increasing Incidence in Younger Individuals and Shift in the Burden to Older Individuals. J Clin Oncol 2019; 37:15381546.  
30. Melissant HC, Jansen F, Eerenstein SE, et al. Body image distress in head and neck cancer patients: what are we looking at? Support Care Cancer 2021; 29:2161-2169.  
31. Kissane DW, Patel SG, Baser RE, et al. Preliminary evaluation of the reliability and validity of the Shame and Stigma Scale in head and neck cancer. Head Neck 2013; 35:172-183.  
32. Branch L, C. F, McQuestion M. An Investigation into Body Image Concerns in the Head and Neck Cancer Population Receiving Radiation or Chemoradiation Using the Body Image Scale: A Pilot Study. Journal of Medical Imaging and Radiation Sciences 2017; 48:169-165.  
33. Clarke SA, Newell R, Thompson A, Harcourt D, Lindenmeyer A. Appearance concerns and psychosocial adjustment following head and neck cancer: A cross-sectional study and ninemonth follow-up. Psychol Health Med 2014; 19:505-518.  
34. Chen SC, Yu PJ, Hong MY, et al. Communication dysfunction, body image, and symptom severity in postoperative head and neck cancer patients: factors associated with the amount of speaking after treatment. Support Care Cancer 2015; 23:2375-2382.  
35. Hung TM, Lin CR, Chi YC, et al. Body image in head and neck cancer patients treated with radiotherapy: the impact of surgical procedures. Health Qual Life Outcomes 2017; 15:165.  
36. Chen C, Cao J, Wang L, Zhang R, Li H, Peng J. Body image and its associated factors among Chinese head and neck cancer patients undergoing surgical treatment: a cross-sectional survey. Support Care Cancer 2019.  
37. Graboyes EM, Hill EG, Marsh CH, Maurer S, Day TA, Sterba KR. Body Image Disturbance in Surgically Treated Head and Neck Cancer Patients: A Prospective Cohort Pilot Study. Otolaryngol Head Neck Surg 2019; 161:105-110.  
38. Rhoten BA, Deng J, Dietrich MS, Murphy B, Ridner SH. Body image and depressive symptoms in patients with head and neck cancer: an important relationship. Support Care Cancer 2014; 22:3053-3060.  
39. Hopwood P, Fletcher I, Lee A, Al Ghazal S. A body image scale for use with cancer patients.  
Eur J Cancer 2001; 37:189-197.  
40. Graboyes EM, Hill EG, Marsh CH, et al. Temporal Trajectory of Body Image Disturbance in Patients with Surgically Treated Head and Neck Cancer. Otolaryngol Head Neck Surg 2020; 162:304-312.  
41. Sherman KA, Przezdziecki A, Alcorso J, et al. Reducing Body Image-Related Distress in Women With Breast Cancer Using a Structured Online Writing Exercise: Results From the My Changed Body Randomized Controlled Trial. J Clin Oncol 2018; 36:1930-1940.  
42. Jarry JL, Ip K. The effectiveness of stand-alone cognitive-behavioural therapy for body image: a meta-analysis. Body Image 2005; 2:317-331.  
43. Jarry JL, Berardi K. Characteristics and effectiveness of stand-alone body image treatments:
a review of the empirical literature. Body Image 2004; 1:319-333.  
44. Fingeret MC, Teo I, Epner DE. Managing body image difficulties of adult cancer patients:
lessons from available research. Cancer 2014; 120:633-641.  
45. Alleva JM, Sheeran P, Webb TL, Martijn C, Miles E. A Meta-Analytic Review of Stand-Alone Interventions to Improve Body Image. PLoS One 2015; 10:e0139177.  
46. Lewis-Smith H, Diedrichs PC, Halliwell E. Cognitive-behavioral roots of body image therapy and prevention. Body Image 2019; 31:309-320.  
47. Blashill AJ, Safren SA, Wilhelm Set al. Cognitive behavioral therapy for body image and selfcare (CBT-BISC) in sexual minority men living with HIV: A randomized controlled trial. Health Psychol 2017; 36:937-946.  
48. Newell RJ. Altered body image: a fear-avoidance model of psycho-social difficulties following disfigurement. J Adv Nurs 1999; 30:1230-1238.  
49. Bessell A, Brough V, Clarke A, Harcourt D, Moss TP, Rumsey N. Evaluation of the effectiveness of Face IT, a computer-based psychosocial intervention for disfigurementrelated distress. Psychol Health Med 2012; 17:565-577.  
50. Faraji J, Mahdavi A, Samkhaniyan E, Asadi SH, Dezhkam N. A review of the effectiveness of cognitive-behavioral group therapy on the reduction of body image concern in patients with breast cancer. J Med Life 2015; 8:82-86.  
51. Fadaei S, Janighorban M, Mehrabi T, Ahmadi SA, Mokaryan F, Gukizade A. Effects of cognitive behavioral counseling on body Image following mastectomy. J Res Med Sci 2011; 16:1047-1054.  
52. Hummel SB, van Lankveld J, Oldenburg HAS, et al. Efficacy of Internet-Based Cognitive Behavioral Therapy in Improving Sexual Functioning of Breast Cancer Survivors: Results of a Randomized Controlled Trial. J Clin Oncol 2017; 35:1328-1340.  
53. Lewis-Smith H, Diedrichs PC, Rumsey N, Harcourt D. Efficacy of psychosocial and physical activity-based interventions to improve body image among women treated for breast cancer: A systematic review. Psychooncology 2018; 27:2687-2699.  
54. Bessell A, Moss TP. Evaluating the effectiveness of psychosocial interventions for individuals with visible differences: a systematic review of the empirical literature. Body Image 2007; 4:227-238.  
55. Cash TF, Santos MT, Williams EF. Coping with body-image threats and challenges: validation of the Body Image Coping Strategies Inventory. J Psychosom Res 2005; 58:190-199.  
56. Ellis MA, Sterba KR, Day TA, et al. Body Image Disturbance in Surgically Treated Head and Neck Cancer Patients: A Patient-Centered Approach. Otolaryngol Head Neck Surg 2019; 161:278-287.  
57. Cho J, Fingeret MC, Huang SC, Liu J, Reece GP, Markey MK. Observers' response to facial disfigurement from head and neck cancer. Psychooncology 2018.  
58. Klimek P, Wilhelm S, Safren SA, Blashill AJ. Cognitive Behavioral Therapy for Body Image and Self-Care (CBT-BISC) among Sexual Minority Men Living with HIV: Skills-Based Treatment Mediators. Cognit Ther Res 2020; 44:208-215.  
59. Melnyk SE, Cash TF, Janda LH. Body image ups and downs: prediction of intra-individual level and variability of women's daily body image experiences. Body Image 2004; 1:225-235.  
60. Blakey SM, Reuman L, Buchholz JL, Abramowitz JS. Experiential avoidance and dysfunctional beliefs in the prediction of body image disturbance in a nonclinical sample of women. Body Image 2017; 22:72-77.  
61. Yamani Ardakani B, Tirgari B, Roudi Rashtabadi O. Body image and its relationship with coping strategies: The views of Iranian breast cancer women following surgery. Eur J Cancer Care (Engl) 2020; 29:e13191.  
62. Stefan S, Cristea IA, Szentagotai Tatar A, David D. Cognitive-behavioral therapy (CBT) for generalized anxiety disorder: Contrasting various CBT approaches in a randomized clinical trial. J Clin Psychol 2019; 75:1188-1202.  
63. van Beugen S, Ferwerda M, Hoeve D, et al. Internet-based cognitive behavioral therapy for patients with chronic somatic conditions: a meta-analytic review. J Med Internet Res 2014; 16:e88.  
64. David JM, Ho AS, Luu M, et al. Treatment at high-volume facilities and academic centers is independently associated with improved survival in patients with locally advanced head and neck cancer. Cancer 2017; 123:3933-3942.  
65. Graboyes EM, Ellis MA, Li H, et al. Racial and Ethnic Disparities in Travel for Head and Neck Cancer Treatment and the Impact of Travel Distance on Survival. Cancer 2018; 124:31813191.  
66. Implementing Cancer Survivorship Care Planning. Washington, DC: National Academies Press, 2007.  
67. Burris JL, Andrykowski M. Disparities in mental health between rural and nonrural cancer survivors: a preliminary study. Psychooncology 2010; 19:637-645.  
68. Allison PJ, Edgar L, Nicolau B, Archer J, Black M, Hier M. Results of a feasibility study for a psycho-educational intervention in head and neck cancer. Psychooncology 2004; 13:482485.  
69. Budhrani-Shani P, Chau NG, Berry DL. Psychosocial distress and the preferred method of delivery of mind-body interventions among patients with head-and-neck cancer. Patient Relat Outcome Meas 2018; 9:129-136.  
70. Wootton R, Bahaadinbeigy K, Hailey D. Estimating travel reduction associated with the use of telemedicine by patients and healthcare professionals: proposal for quantitative synthesis in a systematic review. BMC Health Serv Res 2011; 11:185.  
71. Doolittle GC, Spaulding AO. Providing Access to Oncology Care for Rural Patients via Telemedicine. J Oncol Pract 2006; 2:228-230.  
72. Agnisarman SO, Chalil Madathil K, Smith K, Ashok A, Welch B, McElligott JT. Lessons learned from the usability assessment of home-based telemedicine systems. Appl Ergon 2017; 58:424-434.  
73. Andersson G, Cuijpers P, Carlbring P, Riper H, Hedman E. Guided Internet-based vs. face-toface cognitive behavior therapy for psychiatric and somatic disorders: a systematic review and meta-analysis. World Psychiatry 2014; 13:288-295.  
74. Eldredge L, Markham C, Ruiter R, Fernandez ME, Kok G, Parcel G. Planning Health Promotion Interventions: An Intervention Mapping Approach. San Francisco, CA: Jossey-Bass, 2016.  
75. Graboyes EM, Maurer S, Balliet W, et al. Efficacy of a Brief Tele-Cognitive Behavioral Treatment vs Attention Control for Head and Neck Cancer Survivors With Body Image Distress: A Pilot Randomized Clinical Trial. JAMA Otolaryngol Head Neck Surg 2022.  
76. Hatcher RL, Gillaspy JA. Development and validation of a revised short version of the Working Alliance Inventory. Psychotherapy Research 2006; 16:12–25.  
77. Nilsen ML, Clump DA, 2nd, Kubik M, et al. Prevision of multidisciplinary head and neck cancer survivorship care during the 2019 novel coronavirus pandemic. Head Neck 2020; 42:1668-1673.  
78. Huang VW, Imam SA, Nguyen SA. Head and neck survivorship care in the times of the SARSCoV-2 pandemic. Head Neck 2020; 42:1664-1667.  
79. Greenbaum Z. How well is telepsychology working? Available at:
https://www.apa.org/monitor/2020/07/cover-telepsychology. Accessed April 8 2021.  
80. Murphy R, Calugi S, Cooper Z, Dalle Grave R. Challenges and Opportunities for enhanced cognitive behaviour therapy (CBT-E) in light of COVID-19. The Cognitive Behaviour Therapist 2020:1-31.  
81. Crawford A, Serhal E. Digital Health Equity and COVID-19: The Innovation Curve Cannot Reinforce the Social Gradient of Health. J Med Internet Res 2020; 22:e19361.  
82. Holmes C. Guide to Finding the Best Cell Phone Coverage. March 2, 2021. Available at:
https://www.whistleout.com/CellPhones/Guides/Coverage. Accessed April 1 2021.  
83. Carroll KM, Rounsaville BJ. Efficacy and effectiveness in developing treatment manuals. In:
Nezu AM, Nezu CM, eds. Evidence-Based Outcome Research: A Practical Guide to Conducting Randomized Controlled Trials of Psychosocial Interventions. New York: Oxford University Press, 2008.  
84. Freedland KE, King AC, Ambrosius WT, et al. The selection of comparators for randomized controlled trials of health-related behavioral interventions: recommendations of an NIH expert panel. J Clin Epidemiol 2019; 110:74-81.  
85. Waller G, Stringer H, Meyer C. What cognitive behavioral techniques do therapists report using when delivering cognitive behavioral therapy for the eating disorders? J Consult Clin Psychol 2012; 80:171-175.  
86. Carroll KM, Nich C, Sifry RLet al. A general system for evaluating therapist adherence and competence in psychotherapy research in the addictions. Drug Alcohol Depend 2000; 57:225-238.  
87. Hansen WB, Malotte CK, Fielding JE. The bogus pipeline revisited: the use of the threat of detection as a means of increasing self-reports of tobacco use. J Appl Psychol 1985; 70:789792.  
88. Norman GR, Sloan JA, Wyrwich KW. Interpretation of changes in health-related quality of life: the remarkable universality of half a standard deviation. Med Care 2003; 41:582-592.  
89. Pilkonis PA, Choi SW, Reise SP, et al. Item banks for measuring emotional distress from the Patient-Reported Outcomes Measurement Information System (PROMIS(R)): depression, anxiety, and anger. Assessment 2011; 18:263-283.  
90. Beck AT, Steer RA, Ranieri WF. Scale for Suicide Ideation: psychometric properties of a selfreport version. J Clin Psychol 1988; 44:499-505.  
91. Beck AT, Steer RA. Manual for the Beck Scale for Suicide Ideation. San Antonio, TX:
Psychological Corporation, 1991.  
92. Beck AT, Brown GK, Steer RA, Dahlsgaard KK, Grisham JR. Suicide ideation at its worst point:
a predictor of eventual suicide in psychiatric outpatients. Suicide Life Threat Behav 1999; 29:1-9.  
93. Hahn EA, DeWalt DA, Bode RK, et al. New English and Spanish social health measures will facilitate evaluating health determinants. Health Psychol 2014; 33:490-499.
94. Bode RK, Hahn EA, DeVellis R, Cella D, Patient-Reported Outcomes Measurement Information System Social Domain Working G. Measuring participation: the PatientReported Outcomes Measurement Information System experience. Arch Phys Med Rehabil 2010; 91:S60-65.  
95. Bjordal K, de Graeff A, Fayers PM, et al. A 12 country field study of the EORTC QLQ-C30
(version 3.0) and the head and neck cancer specific module (EORTC QLQ-H&N35) in head and neck patients. EORTC Quality of Life Group. Eur J Cancer 2000; 36:1796-1807.  
96. Netemeyer RG, Williamson DA, Burton S, Biswas D, Jindal S, Landreth S. Psychometric properties of shortened versions of the automatic thoughts questionnaire. Educational and Psychological Measurement 2002; 62:111-129.  
97. Decker SE, Nich C, Carroll KM, Martino S. Development of the Therapist Empathy Scale.  
Behav Cogn Psychother 2014; 42:339-354.  
98. Devilly GJ, Borkovec TD. Psychometric properties of the credibility/expectancy questionnaire. J Behav Ther Exp Psychiatry 2000; 31:73-86.  
99. Duggan C, Parry G, McMurran M, Davidson K, Dennis J. The recording of adverse events from psychological treatments in clinical trials: evidence from a review of NIHR-funded trials. Trials 2014; 15:335.
Based on the NIH Protocol Template for Behavioral and Social Sciences Research 64 100. Esplen MJ, Wong J, Warner E, Toner B. Restoring Body Image After Cancer (ReBIC): Results of a Randomized Controlled Trial. J Clin Oncol 2018; 36:749-756.  
101. Eldridge SM, Ashby D, Feder GS, Rudnicka AR, Ukoumunne OC. Lessons for cluster randomized trials in the twenty-first century: a systematic review of trials in primary care. Clin Trials 2004; 1:80-90.  
102. Baldwin SA, Murray DM, Shadish WRet al. Intraclass correlation associated with therapists:
estimates and applications in planning psychotherapy research. Cogn Behav Ther 2011; 40:15-33.  
103. Adjusting for Covariates in Randomized Clinical Trials for Drugs and Biological Products, Guidance for Industry, Revision 1. In: US Department of Health and Human Services FaDA, Center for Drug Evaluation and Research, Center for Biologics Evaluation and Research, ed., 2021.  
104. Harrell FE, Slaughter JC. Biostatistics for Biomedical Research. In: Slaughter FHJ, ed., 2022. 105. MacKinnon DP, Fairchild AJ, Fritz MS. Mediation analysis. Annu Rev Psychol 2007; 58:593614.  
106. Kline RB. Principles and Practice of Structural Equation Modeling. New York, NY: The Guilford Press, 2016.  
107. Hooper D, Coughlan J, Mullen M. Structural Equation Modelling: Guidelines for Determining Model Fit. Electronic Journal of Business Research Methods 2008; 6:53-60.  
108. Molenberghs G, Kenward MG. Missing Data in Clinical Studies. West Sussex, England: John Wiley & Sons, 2007.  
109. Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986; 51:1173-1182.  
110. Lachowicz MJ, Sterba SK, Preacher KJ. Investigating multilevel mediation with fully or partially nested data. Group Processes & Intergroup Relations 2015; 18:274-289.  
111. Kazdin AE. Mediators and mechanisms of change in psychotherapy research. Annu Rev Clin Psychol 2007; 3:1-27.  
112. Daniel RM, De Stavola BL, Cousens SN, Vansteelandt S. Causal mediation analysis with multiple mediators. Biometrics 2015; 71:1-14.  
113. VanderWeele TJ, Vansteelandt S. Mediation Analysis with Multiple Mediators. Epidemiol Methods 2014; 2:95-115.
Based on the NIH Protocol Template for Behavioral and Social Sciences Research 65 114. Goldsmith KA, MacKinnon DP, Chalder T, White PD, Sharpe M, Pickles A. Tutorial: The practical application of longitudinal structural equation mediation models in clinical trials. Psychol Methods 2018; 23:191-207.  
115. Preacher KJ, Zyphur MJ, Zhang Z. A general multilevel SEM framework for assessing multilevel mediation. Psychol Methods 2010; 15:209-233.