Abstract
Reconstructive breast surgery aims to improve body image following mastectomy, yet many women experience ongoing body image distress (BID). The relationship between the aesthetic outcome of reconstructive surgery with BID has been underexplored in mastectomy. This study aimed to assess whether reconstruction outcome following mastectomy is associated with post-surgery BID, and to examine potential psychological risk and maintenance factors for BID above reconstruction outcome. In 49 women undergoing mastectomy with immediate breast reconstruction, we prospectively assessed hypothesized pre-surgery psychological risk factors and post-surgery maintenance factors for post-surgery BID. Reconstruction outcome was assessed via blind surgeon ratings of post-surgery photographs. Surgeon-rated reconstruction outcome was uncorrelated with BID, or with patients’ ratings of surgical outcome. Higher pre-surgery depressive symptoms and lower pre-surgery patient expectations for reconstruction predicted greater post-surgery BID, above reconstruction outcome. Post-surgery body checking also predicted greater BID, above reconstruction outcome. Results suggest that the medical team cannot assume their perception of reconstruction outcome matches the patient’s view or degree of BID. If replicated, results point to potential psychological risk and maintenance factors that are stronger predictors of post-reconstruction BID, highlighting opportunities for light-touch prevention and intervention to reduce BID after mastectomy with breast reconstruction.
Keywords: body image distress, breast cancer, breast reconstruction, mastectomy, risk factors
Breast cancer is among the most common cancers, occurring in 12% of U.S. women in their lifetime (Breastcancer.org, 2016). Mastectomy is an effective approach to prophylactic prevention and treatment of breast cancer. However, it permanently alters physical appearance and can lead to body image distress (BID) (Bai et al., 2019; Fingeret et al., 2014a; Frierson & Andersen, 2005), which may persist long-term in 30% of patients (Fingeret et al., 2014b). BID in cancer is associated with lower quality of life (Fingeret et al., 2012), sexual dysfunction (Fingeret et al., 2014a; Yurek et al., 2000), and social isolation (Fingeret et al., 2012).
To mitigate the impact of mastectomy on BID, many women pursue breast reconstruction, which rose in procedural volume by 39% from 2000 to 2016 (Liu, 2017). However, a substantial proportion of women experience persistent BID despite breast reconstruction (Frierson & Andersen, 2005). It is difficult for the medical team to anticipate which patients will experience BID post-reconstruction, hindering their ability to offer timely support.
One might assume that post-reconstruction breast appearance provides a strong index of post-surgery BID. However, in broader medical populations, extent of visible differences (e.g., burns scars) does not correlate consistently with BID (Fauerbach et al., 2006; Rose & Blakeney, 2006). Data on this relationship are largely missing for breast reconstruction. A study of 190 women with breast cancer showed that one metric of breast asymmetry (vertical extent asymmetry) measured via clinical photographs correlated with body image dissatisfaction, whereas another (horizontal extent asymmetry) did not (Teo et al., 2018). In addition to mixed results, 23% of participants in this study were assessed pre-reconstruction, making it difficult to draw clear conclusions. We therefore require further research testing the relationship between breast appearance and BID after mastectomy with breast reconstruction.
If post-reconstruction breast appearance does not explain BID, then other factors including psychological variables may contribute. To this end, a 2016 review emphasized the importance of extending beyond cross-sectional data, to prospectively understand risk for BID after mastectomy with breast reconstruction (Razdan et al., 2016).
We identified three pre-surgery psychological risk factors of interest: depression severity, body image investment, and expectations for reconstruction outcome. First, depression severity correlates most consistently with BID after mastectomy with breast reconstruction (Fingeret et al., 2014a; Fingeret et al., 2014b; Unukovych et al., 2017). However, prior work is primarily cross-sectional and has not examined depression as a risk factor compared to post-reconstruction breast appearance. Second, broader literature (Fingeret et al., 2015) and two studies in breast cancer (Moreira & Canavarro, 2010; Teo et al., 2018) suggest that adjustment to appearance changes is tied to body image investment, or the importance of appearance on one’s self-worth. However, no prospective research has examined body image investment as a risk factor for BID compared to post-surgery breast appearance. Third, the relationship between patient expectations for breast reconstruction and BID has scarcely been examined. One cross-sectional retrospective study showed that French women reported both higher expectations and greater dissatisfaction with post-reconstruction appearance compared to English patients (Guyomard et al., 2009). To our knowledge, no prospective data exist on pre-surgery expectations as a predictor of post-reconstruction BID. A review (Pusic et al., 2012) highlights that patients often have limited information about realistic aesthetic outcomes of mastectomy with reconstruction. If expectations for postsurgical breast appearance are unrealistically high, patients may experience disappointment and greater BID (Pusic et al., 2012). Taken together, research that prospectively tests depression, body image investment, and expectations for reconstruction outcome above postsurgical breast appearance is needed.
In addition to pre-surgery risk factors, post-surgery maintenance factors may also contribute to BID. Cognitive behavioral models propose that unhelpful appearance-related beliefs and behaviors maintain BID (Cash, 2011; Reas & Grilo, 2004). For example, appearance-related beliefs (e.g., “others are talking about the appearance of my breasts”) may elicit distress and fuel time-consuming behaviors aimed at hiding or fixing appearance concerns. Maladaptive behaviors (e.g., body checking) in turn fuel further distress and unhelpful appearance-related beliefs. Data testing cognitive-behavioral maintenance models are limited in mastectomy patients. One study of breast cancer survivors showed that body checking was correlated with BID after treatment (Boquiren et al., 2013), but comprehensive appearance-related beliefs and checking behaviors were not assessed, nor was post-surgery breast appearance.
This study aimed to determine whether breast appearance after mastectomy with reconstruction, measured via blind surgeon ratings of reconstruction outcome, was significantly associated with post-surgery BID or patients’ perceptions of reconstruction outcome. Second, we tested the hypothesis that higher pre-surgery depression severity, body image investment, and patient expectations for reconstruction outcome would predict greater post-surgery BID, above surgeon-rated reconstruction outcome. Third, we tested the hypothesis that post-surgery appearance-related beliefs and behaviors would predict BID, above surgeon-rated reconstruction outcome.
Method
Participants
Participants (N=49) included adult women scheduled for mastectomy with immediate breast reconstruction at Massachusetts General Hospital. Mastectomy was performed either for removal of malignant breast tumor or prophylactically. Individuals were ineligible if they had a current psychotic disorder, manic episode, serious neurological disorder, intellectual disability, developmental disorder, or active suicidal ideation. Individuals were also excluded if their treatment plan at enrollment included current or planned radiation or chemotherapy; past radiation or chemotherapy was permitted. This exclusion criterion was established to isolate the effects of surgery on BID, given the additional effects of chemotherapy and radiation on appearance and body image (Fingeret et al., 2014b; Frierson & Andersen, 2005).
Procedures
The study was approved by the Massachusetts General Hospital Institutional Review Board. Patients scheduled for mastectomy and breast reconstruction surgeries were invited to participate. Participation involved two time points. At pre-surgery (1–6 weeks prior to mastectomy), individuals completed a screening/baseline telephone assessment to obtain informed consent and evaluate eligibility. Participants then completed self-report questionnaires. At post-surgery (approximately 3 months after reconstruction), participants completed follow-up self-report questionnaires.
Measures
Mini International Neuropsychiatric Interview (M.I.N.I. 7.0.2) (Sheehan et al., 1998)
The M.I.N.I. 7.0.2 is a reliable and valid clinician-administered psychiatric diagnostic interview based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. It was administered at baseline to assess psychiatric diagnostic eligibility criteria.
Body Image Scale (BIS) (Hopwood et al., 2001)
The BIS is a widely used, well-validated 10-question self-report measuring body image changes after cancer treatment. The BIS was our primary outcome, administered at post-surgery to evaluate BID. Summed scores range from 0 to 30; higher scores indicate greater BID. Internal consistency in the sample was strong (α=.92).
Potential clinical covariates
We assessed demographic and clinical factors via self-report that could influence post-surgery BID, to control for variables associated with the BIS in regressions. See Table 1 for covariates examined.
Table 1.
Group Differences and Associations between Potential Medical Covariates with Post-Surgery Body Image Scale Scores
| Measure | n | M | SD | F / r | p |
|---|---|---|---|---|---|
|
| |||||
| Reason for mastectomya | 0.46 | .50 | |||
| Prophylactic | 8 | 5.88 | 5.69 | ||
| Breast cancer | 40 | 7.51 | 6.31 | ||
| Nipple sparing mastectomy | 0.027 | .87 | |||
| Yes | 35 | 7.32 | 5.45 | ||
| No | 14 | 7.0 | 7.79 | ||
| Mastectomy type | 5.54 | .023 | |||
| Unilateral | 16 | 10.06 | 7.27 | ||
| Bilateral | 33 | 5.86 | 5.05 | ||
| Reconstruction typeb | - | - | |||
| Implant | 45 | 7.34 | 6.19 | ||
| Autologous (flap) | 3 | 7.67 | 6.03 | ||
| Prior or current radiationc | 0.68 | .42 | |||
| Yes | 7 | 9.0 | 7.62 | ||
| No | 42 | 6.94 | 5.89 | ||
| Prior or current chemotherapyc | 0.94 | .34 | |||
| Yes | 9 | 9.11 | 7.18 | ||
| No | 39 | 6.91 | 5.92 | ||
| Surgery complications | |||||
| Yes | 10 | 8.29 | 5.23 | 0.37 | .55 |
| No | 39 | 6.96 | 6.36 | ||
| Lifetime psychiatric diagnoses | 2.73 | .11 | |||
| Yes | 28 | 8.46 | 6.38 | ||
| No | 21 | 5.59 | 5.48 | ||
| Body mass index | .064 | .80 | |||
| Normal | 26 | 7.13 | 4.47 | ||
| Overweight/Obese | 22 | 7.59 | 7.77 | ||
| Age | −.16 | .26 | |||
Note:
One participant reported her reason for mastectomy as “other” and is excluded from this analysis.
Only three participants had autologous procedures (one participant’s reconstruction type was unknown); thus, it was not feasible to examine group differences in Body Image Scale scores by reconstruction type.
Eligibility criteria excluded those with planned radiation or chemotherapy at enrollment; however, at the endpoint assessment 2 participants reported current radiation and 6 reported current chemotherapy, due to changes in treatment plans after enrollment.
Surgeon-rated reconstruction outcome
The reconstructive surgeon documents post-reconstruction breast photographs at the follow-up medical appointment. A highly experienced reconstructive breast surgeon rated aesthetic outcome for each participant’s photograph from 1 to 9 (1: “perfect outcome; no observable asymmetry, scarring or flaws,” 5: “moderate aesthetic outcome; some notable asymmetry, scarring, or flaws,” 9: “extremely poor outcome; extreme observable asymmetry, flaws or disfigurement).” The rater was blind to the identities of the patient and surgeon who performed the reconstruction.
Patient-rated reconstruction outcome
To evaluate patients’ perceptions of aesthetic outcome, participants rated their post-surgery breast appearance, using the same scale as that used for surgeon ratings.
Beck Depression Inventory-II (BDI-II) (Beck et al., 1996)
The BDI-II is a widely used, well-validated self-report scale that assesses severity of depression symptoms. Pre-surgery BDI-II was a hypothesized risk factor. The questionnaire has 21 items with a maximum score of 63. Higher scores represent higher symptoms. Internal consistency in the sample was strong (α=.85).
Breast-Q Expectations of Appearance (Version 2.0) (Pusic et al., 2009)
The Breast-Q self-report includes the Breast Reconstruction Expectation module. The 5-item Expectations of Appearance subscale, a subset of the broader Expectations module, measures pre-surgery expectations of breast appearance 1 year after reconstruction and was administered as a hypothesized risk factor for BID. Raw scores are summed and transformed using a scoring table (range: 0–100). Higher scores signify more optimistic expectations. Internal consistency in the sample was strong (α=.84).
Appearance Schema Inventory-Revised (ASI-R) (Cash et al., 2004)
The ASI-R is a psychometrically strong 20-item self-report that assesses body image investment: the extent to which participants assign self-worth and importance to their physical appearance (Cash et al., 2004). Scores are calculated as a mean and range from 1–5; higher scores represent higher investment. Internal consistency in the sample was strong (α=.85).
Body Image after Mastectomy Scale (BIMS) (Weingarden et al., 2021)
The BIMS is a self-report measure of behaviors and beliefs that may trigger or maintain BID after mastectomy. Severity scores from (1) appearance-related beliefs and (2) body checking behaviors subscales were our post-surgery measures of hypothesized maintenance factors. Each domain contains a checklist of beliefs (e.g., “I believe others are judging the appearance of my breast(s)/chest/scars”) or behaviors (e.g., “touching or feeling my breast(s)/chest repeatedly, to gauge how they look”). If a participant endorses one or more items in a domain, they rate overall severity of symptoms in that domain (0 = ‘no problem’; 10 = ‘very severe’).
Statistical Methods
Power.
Power analyses were conducted a priori using G*Power (Faul et al., 2007) for multiple regression. For 80% power to detect an effect ≥.35 at a conservative alpha=.025, 42 participants are needed with three predictors. As our final regressions included four predictors, a post-hoc analysis showed that 40 participants are needed to detect an effect ≥.35 at alpha=.05.
Preliminary analyses.
To identify clinical covariates that could impact post-surgery BID, we examined associations between demographic and clinical variables with post-surgery BIS scores, using One-Way ANOVA or Pearson’s correlations. Significant variables were included in multiple regressions as covariates, to control for potential effects.
We examined bivariate correlations between hypothesized pre-surgery risk factors (depression severity, body image investment, expectations for reconstruction outcome) and post-surgery maintenance factors (appearance-related beliefs, body checking behaviors) with post-surgery BIS scores. Variables that were significantly associated with BIS scores were included in the respective Aim 2 or 3 multiple regression; non-significant variables were dropped to preserve power. Before conducting regressions, we verified that regression assumptions were met and that no issues of multicollinearity among predictors were present.
Aim 1.
We examined Pearson correlations between surgeon-rated reconstruction outcome with (a) BIS scores and (b) patient-rated reconstruction outcome.
Aim 2.
We simultaneously regressed post-surgery BIS scores onto hypothesized pre-surgery psychological risk factors (i.e., depression severity, patient expectations), controlling for surgeon-rated reconstruction outcome and mastectomy type (unilateral vs. bilateral).
Aim 3.
We simultaneously regressed post-surgery BIS scores onto hypothesized post-surgery maintenance factors (i.e., appearance-related beliefs, body checking), controlling for surgeon-rated reconstructive outcome and mastectomy type.
Results
Sample Characteristics
Fifty-one participants initiated study procedures. Forty-nine provided primary outcome data and were included. See Table 2 for sample characteristics.
Table 2.
Sample Demographic and Clinical Characteristics
| M / n | SD / % | |
|---|---|---|
|
| ||
| Age | 51.92 | 11.48 |
| Race | ||
| White | 44 | 89.80 |
| Asian | 2 | 4.08 |
| More than one race | 1 | 2.04 |
| Other | 2 | 4.08 |
| Ethnicity | ||
| Non-Hispanic/non-Latinx | 48 | 97.96 |
| Hispanic/Latinx | 1 | 2.04 |
| Marital status | ||
| Married | 30 | 61.22 |
| Single/never married | 6 | 12.24 |
| Living with partner | 2 | 4.08 |
| Divorced/separated | 9 | 18.37 |
| Widow | 2 | 4.08 |
| Education completed | ||
| Some high school | 1 | 2.04 |
| High school diploma/GED | 2 | 4.08 |
| Some college | 6 | 12.24 |
| 2 or 4-year college degree | 16 | 32.65 |
| Some post-grad/professional | 4 | 8.16 |
| Post-grad/professional degree | 20 | 40.82 |
| Reason for mastectomy | ||
| Ductal carcinoma in-situ | 18 | 36.73 |
| Stage 1 breast cancer | 13 | 26.53 |
| Other breast cancer diagnosis | 9 | 18.37 |
| Prophylactic (e.g., BRCA mutation) | 8 | 16.33 |
| Other | 1 | 2.04 |
Preliminary Analyses
Associations between potential covariates with post-surgery BIS scores are shown in Table 1. Mastectomy type was significantly associated with post-surgery BIS scores, with a medium-large effect (η2=.105). Those who had unilateral (versus bilateral) mastectomy reported greater post-surgery BID.
Means and standard deviations of key study variables are shown in Table 3, along with bivariate correlations among hypothesized risk and maintenance factors with post-surgery BIS scores. Pre-surgery body image investment was not significantly correlated with post-surgery BID and was dropped from our Aim 2 regression.
Table 3.
Descriptive Statistics for Key Study Variables and Correlations of Hypothesized Risk and Maintenance Factors with Post-Surgery BIS Scores
| Measure | M | SD | r | p |
|---|---|---|---|---|
|
| ||||
| Surgeon rating of breast appearance | 4.0 | 1.96 | ||
| Patient rating of breast appearance | 3.92 | 2.01 | ||
| Body Image Distress (BIS) | 7.23 | 6.12 | ||
| Pre-Surgery Risk Factors | ||||
| Depression severity (BDI-II) | 7.06 | 5.43 | .45 | .001 |
| Patient expectations | 87.31 | 19.38 | −.44 | .003 |
| Body image investment (ASI-R) | 3.21 | 0.53 | .20 | .18 |
| Post-Surgery Maintenance Factors | ||||
| Maladaptive appearance cognitions (BIMS) | 1.70 | 1.93 | .42 | <.001 |
| Repetitive appearance checking (BIMS) | 1.92 | 2.04 | .42 | <.001 |
Note: BIS=Body Image Scale; BDI-II=Beck Depression Inventory-II; ASI-R=Appearance Schema Inventory-Revised; BIMS=Body Image after Mastectomy Scale.
Aim 1
Blind surgeon ratings of reconstruction outcome were not significantly correlated with post-surgery BID (r=.03, p=.85) or with patient-rated reconstruction outcome (r=−.02, p=.91.
Aim 2
A regression testing whether pre-surgery risk factors (depression severity, patient expectations) predicted post-surgery BID above and beyond surgeon-rated reconstruction outcome and mastectomy type was significant, F(4, 39)=5.14, p=.002, R2 = .35. Greater pre-surgery depression and lower patient expectations for reconstruction significantly predicted greater post-surgery BID with moderate effects, even when accounting for surgeon-rated reconstruction outcome and mastectomy type (see Table 4).
Table 4.
Multiple Regression Results for Aim 2 (Pre-Surgery Predictors of Post-Surgery Body Image Distress) and Aim 3 (Post-Surgery Maintenance Factors for Body Image Distress)
| Predictor | Estimate | SE | 95% CI | Std. Estimate | p | |
|---|---|---|---|---|---|---|
| LL | UL | |||||
|
| ||||||
| Aim 1 | ||||||
| Mastectomy type | −3.16 | 2.03 | −7.26 | 0.94 | −0.24 | 0.13 |
| Surgeon rating of breast appearance | −0.40 | 0.48 | −1.37 | 0.57 | −0.12 | 0.41 |
| Depression severity (BDI-II) | 0.33 | 0.16 | 0.003 | 0.66 | 0.30 | 0.048 |
| Patient expectations | −0.093 | 0.045 | −0.18 | −0.002 | −0.29 | 0.044 |
| Aim 2 | ||||||
| Mastectomy type | −1.84 | 1.72 | −5.32 | 1.64 | −0.15 | 0.29 |
| Surgeon rating of breast appearance | −0.13 | 0.41 | 0.96 | 0.70 | −0.042 | 0.76 |
| Maladaptive appearance beliefs (BIMS) | 0.88 | 0.48 | 0.047 | 1.84 | 0.29 | 0.072 |
| Repetitive appearance checking (BIMS) | 0.94 | 0.44 | −0.082 | 1.85 | 0.33 | 0.040 |
Note: BDI-II=Beck Depression Inventory-II; BIMS=Body Image after Mastectomy Scale.
Aim 3
A regression testing whether post-surgery maintenance factors (appearance-related beliefs, body checking behaviors) predicted post-surgery BID above and beyond surgeon-rated reconstruction outcome and mastectomy type was significant, F(4, 41)=5.60, p=.001, R2 = .35. More severe post-surgery body checking, but not appearance-related beliefs, significantly predicted greater post-surgery BID, above surgeon-rated reconstruction outcome and mastectomy type, with a moderate effect (see Table 4).
Discussion
Many women who undergo mastectomy with breast reconstruction experience persistent postsurgical BID, yet it is difficult to anticipate who will experience ongoing distress. Whereas the medical team might expect that BID corresponds with aesthetic outcomes, in the broader medical literature BID often does not correlate with objective appearance (Fauerbach et al., 2006; Rose & Blakeney, 2006). It is important to understand whether this finding extends to breast cancer surgery. Alternatively, factors beyond reconstruction outcome – including psychological factors – may contribute to postsurgical BID. We sought to test the relationship between surgeon-rated reconstruction outcome with post-surgery BID and patients’ views of reconstruction outcome (Aim 1), and to identify pre-surgery psychological risk factors (Aim 2) and post-surgery maintenance factors (Aim 3) for post-surgery BID, above and beyond surgeon-rated reconstruction outcome.
Aim 1 results clarify and extend one prior study’s mixed results (Teo et al., 2018). Findings provide some of the first evidence that – perhaps counterintuitively – the medical team cannot anticipate patients’ post-reconstruction BID based on the aesthetic outcome of their surgery, nor can they assume their perception of reconstruction outcome matches the patient’s view. Clinicians should therefore gauge BID by evaluating patient-reported outcomes post-surgery.
Aim 2 results showed that women with higher depression severity and lower expectations for post-reconstruction breast appearance experienced significantly greater BID 3 months after reconstruction, with moderately strong effects. These factors predicted post-surgery BID above and beyond surgeon-rated reconstruction outcome and mastectomy type (unilateral vs. bilateral), which were non-significant.
Depression results offer additional prospective evidence to existing studies (Fingeret et al., 2014a; Fingeret et al., 2014b). Expectation results identify a novel prospective risk factor, albeit in the opposite direction as hypothesized or documented in a prior cross-sectional, retrospective study (Guyomard et al., 2009). We found that women with lower expectations for post-reconstruction breast appearance experienced greater BID, with moderately strong effects – potentially reflecting a self-fulfilling prophecy. This relationship between expectations and BID cannot be better explained by depression as a third variable influencing both expectations and BID, as depression was included in the regression model. Unexpectedly, body image investment, shown previously to be associated with BID (Moreira & Canavarro, 2010; Teo et al., 2018), was not significantly associated with BID at the bivariate correlation level. The magnitude of this association was weak; therefore, we may have been underpowered to test this variable.
With replication, prospective risk factor results underscore opportunities for screening and early intervention. The medical team can administer a brief depression measure prior to surgery and speak to patients with elevated scores about light-touch interventions (e.g., focused cognitive-behavioral skills for depressive symptoms) that may benefit them during treatment. Likewise, the medical team can elicit patients’ expectations for post-reconstruction breast appearance. For patients with low expectations, the medical team can offer more optimistic, while remaining realistic, expectations for the aesthetic outcome of surgery, to instill hope. For instance, it may be useful to share photograph examples of outcomes from patients with similar diagnoses and treatments. Indeed, prior research shows that satisfaction with preparatory information is associated with less regret about the decision to pursue breast reconstruction (Sheehan et al., 2007).
Aim 3 results testing maintenance factors provide novel information that post-surgery body checking predicts greater BID, even when accounting for surgeon-rated reconstruction outcome and mastectomy type. Appearance-related beliefs were marginally significant (p = .07).
With replication, Aim 3 results underscore potential intervention targets. Patients experiencing BID at longer-term follow-up may benefit from learning simple cognitive-behavioral skills including ritual prevention to reduce time-consuming checking behaviors and cognitive restructuring to identify and modify unhelpful appearance-related beliefs. With minimal training, non-mental health specialists (e.g., nurses) can learn to teach these skills in 1–2 sessions, opening the opportunity for light-touch, in-house interventions for post-surgery BID.
Limitations and Future Directions
Results should be interpreted bearing in mind limitations. First, sample characteristics may limit the generalizability of findings. Data were collected from a single site and the sample reflected the patient pool in the hospital (i.e., homogenous in terms of race, ethnicity, and educational status). Eligibility criteria also excluded patients whose treatment plan at enrollment involved current or future chemotherapy or radiation, which impact appearance and body image, or delayed reconstruction, which affects the recovery timeline and process. Therefore, introducing these variables would make it difficult to identify risk factors for BID caused by mastectomy, specifically. A tradeoff to this decision was that it limited our sample to women with earlier stage cancer or genetic predispositions for cancer and immediate reconstruction procedures. BID may be even more salient for those with later stage diagnoses, given the compounding effects of chemotherapy and radiation on body image (e.g., hair loss, breast disfigurement). Second, although we set our sample size through a priori power analyses, our sample was small and we were likely underpowered to detect less frequent medical covariates (e.g., autologous procedures, non-nipple-sparing mastectomy) or weaker predictors such as body image investment. Replication in a larger, more racially and medically diverse sample will extend initial findings. Third, causal relationships can only be established using an experimental design; the present design is correlational. To lessen this limitation, we tested and controlled for potential confounding demographic and clinical variables, to reduce the likelihood that third variables explain observed relationships. Fourth, while this study extends the literature as one of few prospective studies, our follow-up period was 3 months. Some BID, checking behaviors, and unhelpful appearance-related thoughts are expected within this post-surgical time frame, and certain aesthetic outcomes may be in flux at 3 months post-reconstruction (e.g., scar and wound healing). The present study offers initial findings and future studies that follow participants for a longer post-surgery window (e.g., 1 year) will extend results.
Conclusion
Results suggest that the medical team cannot assume their perception of reconstruction outcome matches the patient’s view or degree of BID; rather, clinicians should gauge post-surgery BID by evaluating patient-reported outcomes. Results also lay the foundation for future work that further tests risk and maintenance factors for post-reconstruction BID and underscores potential opportunities for prevention and intervention.
Funding and Role of the Funder:
Research reported in this publication was supported by the President and Fellows of Harvard College Kaplen Fellowship (Weingarden); President and Fellows of Harvard College Livingston Award (Weingarden); and the National Institute Of Mental Health of the National Institutes of Health under Award Number K23MH119372 (Weingarden). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or President and Fellows of Harvard College. The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Footnotes
Conflict of Interests: Dr. Weingarden receives salary support from Koa Health, Inc. and has been a presenter for the Massachusetts General Hospital Psychiatry Academy in educational programs supported through independent medical education grants from pharmaceutical companies. Dr. Wilhelm is a presenter for the Massachusetts General Hospital Psychiatry Academy in educational programs supported through independent medical education grants from pharmaceutical companies; she has received royalties from Elsevier Publications, Guilford Publications, New Harbinger Publications, Springer, and Oxford University Press. Dr. Wilhelm has also received speaking honoraria from various academic institutions and foundations, including the International Obsessive Compulsive Disorder Foundation, the Tourette Association of America, and the Centers For Disease Control and Prevention. In addition, she received payment from the Association for Behavioral and Cognitive Therapies for her role as Associate Editor for the Behavior Therapy journal, as well as from John Wiley & Sons, Inc. for her role as Associate Editor on the journal Depression & Anxiety. Dr. Wilhelm has also received honoraria from One-Mind for her role in PsyberGuide Scientific Advisory Board. Dr. Wilhelm is also on the Scientific Advisory Board for Koa Health, Inc and Noom, Inc. Dr. Wilhelm has received research and salary support from Koa Health, Inc. Other authors report no conflicts.
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