Abstract

Breast self-examination is the practice of a woman systematically palpating her own breasts to detect lumps or changes, promoted for much of the twentieth century as a simple, no-cost cancer-screening behavior. It is a revealing case for cognitive psychology because its adoption was driven by health beliefs rather than evidence: the Health Belief Model explains uptake through perceived susceptibility, perceived benefits, and perceived barriers, yet two large randomized trials and a Cochrane review later showed that structured self-examination does not reduce breast-cancer mortality while roughly doubling the number of benign lumps biopsied. Major guidelines consequently reversed, recommending against routinely teaching it. This article covers what the behavior is, why belief rather than data drove its promotion, what the trials found, how the recommendation changed, and why a disproven behavior persists.

Keywords: breast self-examination, health belief model, cancer screening, health behavior, signal detection

What Breast Self-Examination Is

Breast self-examination (BSE) is the practice in which a woman inspects and palpates her own breasts on a regular schedule — classically once a month — looking for lumps, thickening, or other changes that might signal breast cancer. In MeSH it is defined as the inspection and palpation of the breasts by the patient themselves, and it is filed as a health behavior, not a diagnostic procedure. That classification is the point: BSE is something a person does, a learned and repeated action governed by motivation, belief, and habit, rather than a test a clinician administers. For cognitive psychology, the interesting object is not the breast but the behavior — why someone performs it, what perceptual task it demands, and how the gap between why it was adopted and whether it works came to be measured.

The behavior has a structured form and an informal one, and the distinction matters for everything that follows. Structured BSE is the taught monthly ritual: a systematic search pattern covering the whole breast in a fixed sequence, performed on a set date. Breast awareness is the looser disposition simply to know how one's breasts normally feel and to notice change. The large trials that reshaped the recommendation tested structured BSE specifically; the softer notion of breast awareness was never the thing found ineffective, and conflating the two is the most common error in reading the evidence.

Key Takeaways
  • Breast self-examination is a health behavior — the systematic monthly palpation of one's own breasts — not a diagnostic test, so its study belongs to the psychology of why people act on health.
  • Its twentieth-century promotion was driven by belief, not evidence: the Health Belief Model explains uptake through perceived susceptibility, benefits, barriers, and self-efficacy.
  • Two large randomized trials (Shanghai, Leningrad) and a Cochrane review found that structured BSE does not reduce breast-cancer mortality.
  • It is not harmless: self-examination roughly doubles the number of benign lumps biopsied, a cost without a matching survival benefit.
  • Major guidelines reversed to recommend against teaching it, yet the behavior persists — a case study in the gap between belief-driven action and evidence.

The Health Belief Model and Why BSE Was Promoted

The reason BSE spread has less to do with oncology than with the psychology of health decisions. The dominant framework is the Health Belief Model, whose historical origins Rosenstock (1974) set out: whether a person takes a preventive health action is predicted by their perceived susceptibility to the threat, the perceived severity of its consequences, the perceived benefits of acting, and the perceived barriers to doing so. A woman who believes she is personally at risk of breast cancer, that the disease is grave, that monthly self-examination would catch it early, and that the examination costs her little, is — on this account — likely to perform it. Crucially, none of those four beliefs is the same as the action actually working; the model predicts behavior from belief, and the beliefs can be well out of step with the evidence.

Rosenstock, Strecher, and Becker (1988) later folded in self-efficacy — a person's confidence that they can execute the behavior — which matters especially for a skilled action like palpation, where uncertainty about whether one is doing it correctly is itself a barrier. Turning these constructs into measurement for breast screening was largely the work of Victoria Champion, whose revised susceptibility, benefits, and barriers scales (1999) let researchers quantify each belief and test which ones predicted whether women examined their breasts. Champion and Skinner's (2008) account of the model in its mature form made it the standard lens on screening behavior. The combined picture explains the historical enthusiasm neatly: public-health campaigns raised perceived susceptibility and benefits and lowered perceived barriers, uptake followed the beliefs, and the question of whether the behavior reduced death went, for decades, largely unasked.

The Trial Evidence

When the question was finally asked with randomized trials, the answer was consistent and negative. Thomas and colleagues (2002) conducted the larger of the two definitive studies in Shanghai, randomizing 266,064 female factory workers to either intensive instruction in BSE with ongoing reinforcement or no instruction. After more than a decade of follow-up, breast-cancer mortality was no lower in the instruction group than in the control group. The women taught to examine themselves did detect more breast lumps — but the additional lumps were overwhelmingly benign, and finding them earlier did not translate into fewer deaths. Semiglazov and colleagues (1992) had reached the same conclusion in the USSR/WHO trial in Leningrad: systematic self-examination instruction produced no survival benefit.

Kösters and Gøtzsche's (2003) Cochrane review pooled these two trials — together enrolling about 388,000 women — and drew the field's defining verdict: there is no evidence that screening by breast self-examination reduces breast-cancer mortality, and women performing it had almost twice as many biopsies with benign results as women who did not. Hackshaw and Paul's (2003) meta-analysis, which added observational data, reached the same mortality-null conclusion while again noting the increased investigation of benign disease. The pattern is a textbook demonstration of why detecting more does not mean saving more: BSE shifts the detection criterion so that more lumps are found, but most additional detections are false alarms in the signal-detection sense — benign lesions that generate anxiety, clinic visits, and biopsies without a corresponding gain in survival.

Table 1. The randomized evidence on structured breast self-examination. Both large trials and the Cochrane review that pooled them found no reduction in breast-cancer mortality, while the examined groups underwent markedly more biopsies yielding benign results.
Study Setting & design Enrolled Mortality effect Benign-biopsy harm
Thomas et al. (2002) Shanghai; factory workers randomized to BSE instruction vs none 266,064 No reduction at >10 years More benign lumps detected
Semiglazov et al. (1992) Leningrad; USSR/WHO trial of BSE instruction ~122,000 No survival benefit More benign investigation
Kösters & Gøtzsche (2003) Cochrane review pooling both trials ~388,000 No mortality reduction Almost twice as many benign biopsies

The Guideline Reversal

The trial evidence forced a reversal in formal recommendations, and the sequence is well documented. Baxter (2001), writing for the Canadian Task Force on Preventive Health Care, issued the first major guideline to recommend against routinely teaching BSE, concluding that the evidence showed no benefit and good evidence of harm from the resulting benign biopsies. The U.S. Preventive Services Task Force (2009) followed, assigning the teaching of BSE a grade D — a recommendation against the practice — on the grounds that it does not reduce mortality and leads to additional imaging and biopsies.

The position held as the evidence was re-examined. Nelson and colleagues (2016) conducted the systematic review underpinning the Task Force's update, confirming that the BSE conclusion still stood, and Siu (2016), for the Task Force, restated the recommendation against teaching it in the current screening statement. The American Cancer Society moved in the same direction: Oeffinger and colleagues' (2015) guideline update no longer recommended BSE for women at average risk. Across independent bodies in different countries, the consensus converged — a rare and clean example of guidelines following trial data against an entrenched and popular behavior. Harvey, Miller, Baines, and Corey (1997) had earlier raised a subtler possibility within the Canadian National Breast Screening Study, that how proficiently a woman examined her breasts might relate to outcome; but the proficiency nuance never overturned the central mortality-null finding that drove the reversal.

What Breast Self-Examination Illustrates

Stripped of the clinical specifics, BSE is a case study in two cognitive-psychological phenomena. The first is the belief–behavior gap: the Health Belief Model predicts the behavior from beliefs that are themselves no guarantee of efficacy, so a behavior can achieve mass adoption on the strength of perceived benefit alone, with the actual benefit unmeasured. The second is the detection-criterion problem: palpating for a lump is a signal-detection task in which the examiner sets, implicitly, a threshold for calling a sensation suspicious. Lowering that threshold — examining more anxiously, or more often — raises the hit rate but raises the false-alarm rate faster, and in a population where most detectable lumps are benign, the marginal detection is far more likely to be a false alarm than a lethal cancer caught in time.

This is why the behavior can feel effective to the individual while being ineffective in the aggregate. A woman who finds a lump, has it checked, and learns it is benign experiences the sequence as a success — the system worked, she was vigilant. The trials measure the only outcome that distinguishes genuine from illusory benefit, death from breast cancer, and there the effect vanishes. BSE thus sits at the intersection of health-behavior theory and detection theory: a behavior sustained by a model that explains adoption without requiring efficacy, performing a perceptual task whose costs and benefits the performer is poorly placed to weigh. That the behavior persists after the evidence is in (see Current Directions) is itself a datum about how resistant belief-driven health behavior is to disconfirmation.

Figure

Figure 1

Belief drives the behavior; the trial measures the outcome.

Why breast self-examination was adopted and what the trials found Four Health Belief Model constructs — perceived susceptibility, perceived benefits, perceived barriers, and self-efficacy — feed into the decision to perform breast self-examination. The behavior is a signal-detection task that increases lumps detected, but the trials show this raises benign biopsies without reducing breast-cancer mortality. Perceived susceptibility Perceived benefits Perceived barriers Self-efficacy Performs BSE health behavior Lumps detected detection task Mortality unchanged no survival benefit Benign biopsies up false alarms, ~doubled Solid path: measured in the trials. Dashed: the hoped-for link the trials did not find.
Beliefs predict the behavior, and the behavior detects more lumps, but the detections are mostly benign; the survival benefit the model's perceived-benefit term assumed was never observed (after Rosenstock, 1974; Kösters & Gøtzsche, 2003; Thomas et al., 2002).

Interactive Demonstrations

Three demonstrations make the argument concrete: a Health Belief Model calculator that turns the four belief constructs into a predicted likelihood of performing BSE, a two-arm trial simulator that reproduces the equal-mortality, excess-biopsy pattern, and a signal-detection palpation task that shows why a lower suspicion threshold multiplies false alarms. Each is deterministic and runs entirely in the browser.

Demo 1 — Belief predicts the behavior

The Health Belief Model predicts whether a woman performs breast self-examination from four beliefs, not from whether it works. Raise perceived susceptibility, benefits, and self-efficacy, or lower the barriers, and the predicted likelihood climbs — the efficacy of the behavior never enters the calculation (Rosenstock, 1974; Champion, 1999).

feels safefeels at risk
pointlessworthwhile
unsure howconfident
nonemany
Predicted likelihood of performing BSE90%
These beliefs predict the woman is likely to perform BSE (90%). Notice what is absent: nowhere does the model ask whether breast self-examination actually reduces mortality. A public-health campaign that raises perceived benefit moves this bar whether or not the behavior works — the engine of adoption, and of the belief–behavior gap.
A schematic logistic combination of the Health Belief Model constructs (Rosenstock, 1974; Rosenstock et al., 1988; Champion, 1999), not a validated clinical score. Computed locally and deterministically; nothing is stored.

Demo 2 — The randomized trial: more biopsies, equal deaths

Two arms of equal size: one taught structured BSE, one not. Vary the cohort and the control biopsy rate, and set the BSE arm’s benign-biopsy multiplier (the Cochrane review found it close to 2×). The benign biopsies diverge and the excess scales with the cohort — while breast-cancer deaths stay identical (Thomas et al., 2002; Kösters & Götzsche, 2003).

benignbiopsies800Control1,600BSE taught+800 excess
In each arm of 100,000 women, breast-cancer deaths are the same — 120 versus 120. The BSE arm has 800 more benign biopsies. That gap is the behavior’s entire measured effect: pure cost, scaling with the population, for no lives saved.
An illustrative reconstruction of the trial pattern; mortality is held equal because that is what the trials found, and the biopsy multiplier defaults to the Cochrane review’s near-doubling (Kösters & Götzsche, 2003). Computed locally and deterministically; nothing is stored.

Demo 3 — Lowering the suspicion threshold

Palpation is a signal-detection task: the examiner sets, implicitly, how suspicious a sensation must feel before she calls it a lump worth checking. Because malignant lumps are rare (here 3% of all detectable lumps), sliding the criterion down — examining more anxiously — adds false alarms far faster than genuine catches.

benign (97%)malignant (3%)criterioncall suspicious →less suspiciousmore suspicious
Per 10,000 lumps examined at this criterion: 174 cancers caught, 939 benign lumps biopsied as false alarms, and 126 cancers still missed. Only 15.6% of the biopsies this criterion triggers actually find cancer — the rest are the harm the trials measured.
A signal-detection schematic (benign and malignant “feel” distributions separated by d′ = 1.5, 3% malignant base rate), not clinical sensitivity data: it shows why a lower criterion multiplies false alarms faster than hits. Computed locally and deterministically; nothing is stored.

Worked Example

Consider the central harm quantitatively, using the Cochrane review's anchoring finding that breast self-examination produces almost twice as many benign biopsies (Kösters & Gøtzsche, 2003). Suppose a control group of 100,000 women, examined only when symptoms bring them to a clinic, yields a benign-biopsy rate of 8 per 1,000 over the study period — that is, 800 benign biopsies. An otherwise identical group taught structured monthly BSE detects more lumps, and because almost all additional lumps are benign, its benign-biopsy rate roughly doubles to about 16 per 1,000, or 1,600 benign biopsies.

The excess is 1,600 − 800 = 800 additional benign biopsies per 100,000 women — each an invasive procedure with its attendant anxiety, cost, and small complication risk. The decisive clause is for no change in breast-cancer deaths: the trials found the mortality curves of the two arms superimposed (Thomas et al., 2002; Semiglazov et al., 1992). So the behavior's entire measured effect, at the population scale, is 800 extra harms with zero offsetting lives saved. This is the arithmetic that moved every major task force from recommending BSE to recommending against teaching it, and the trial simulator above lets the cohort size and biopsy rates be varied to see the excess scale linearly while the mortality difference stays at zero.

Discussion

Breast self-examination is unusual among health behaviors in having been both enormously popular and, when finally tested, cleanly disproven — which is exactly what makes it valuable to cognitive psychology rather than only to oncology. The Health Belief Model accounts for the adoption without ever requiring the behavior to work: susceptibility, severity, benefits, barriers, and self-efficacy are beliefs about a behavior, and a campaign that moves those beliefs moves the behavior whether or not the behavior saves lives. That is not a flaw in the model but its central and sobering lesson — behavior tracks perceived benefit, and perceived benefit can be manufactured well ahead of, or in the absence of, demonstrated benefit.

The detection-theory reading explains why the perceived benefit felt so plausible. Finding a lump is a vivid, concrete event; the woman who finds one and acts has a compelling personal narrative of vigilance rewarded, and that narrative is available regardless of whether the lump was ever going to kill her. The trials measure the one quantity that the individual experience cannot reveal — whether the whole practice shifts the mortality curve — and the answer is that it does not, while the false-alarm cost is real and large. The correct successor is not fatalism but a better-calibrated behavior: breast awareness, knowing one's own normal and reporting genuine change, which carries far less of the structured ritual's false-alarm burden. The episode stands as a caution that a health behavior's popularity, and even its intuitive mechanism, are no substitute for the randomized test of the outcome that actually matters.

Current Directions

The guideline reversal settled the question for high-income health systems, but the behavior has not disappeared, and the most active current research concerns where and why it persists. Udoh and colleagues (2020) conducted a scoping review of women's knowledge, attitudes, and practice of BSE across sub-Saharan Africa and found it still widely taught and promoted — a reasonable response to a setting where mammography and clinical breast examination are largely unavailable, so that self-examination is one of the few early-detection behaviors within reach. The persistence is therefore not simply a failure to update on the trial evidence; it reflects a different decision context, in which the comparator is not mammography but nothing at all.

This reframes the open question from does BSE work to what is the right early-detection behavior for a given health system, and it keeps the Health Belief Model in play: in low-resource settings the perceived benefits and barriers that drive BSE are genuinely different, and interventions continue to be designed around those beliefs. A parallel strand concerns the shift in high-income guidance from structured BSE to breast awareness, and whether the softer construct can retain whatever genuine early-detection value exists while shedding the false-alarm burden that condemned the monthly ritual. The through-line is that a behavior can be simultaneously wrong for one population and defensible for another, and that the belief constructs governing its uptake have to be read against the options actually available to the person holding them.

Common Misconceptions

Breast self-examination saves lives by catching cancer early.
Two large randomized trials and a Cochrane review found no reduction in breast-cancer mortality from structured self-examination (Kösters & Gøtzsche, 2003; Thomas et al., 2002). It detects more lumps, but earlier detection of mostly benign lumps did not translate into fewer deaths.
If it does not help, at least it does no harm.
It does measurable harm: women performing BSE had almost twice as many biopsies with benign results, each an invasive procedure carrying anxiety, cost, and complication risk, with no offsetting survival gain (Kösters & Gøtzsche, 2003).
Guidelines recommend against women knowing their own breasts.
The recommendation is against teaching the structured monthly ritual, not against breast awareness (Siu, 2016). Knowing one's normal state and reporting genuine change is a different, lower-false-alarm behavior that the trials never tested or condemned.
Because it was promoted for decades, it must have been based on strong evidence.
Its promotion rested on the plausibility of early detection and on belief constructs the Health Belief Model formalizes (Rosenstock, 1974), not on trial evidence — which, when gathered, did not support it. Popularity preceded, rather than followed, the data.

Glossary

Benign biopsy.
A biopsy of a breast lump that proves non-cancerous; the principal measured harm of breast self-examination, which roughly doubles their number.
Breast awareness.
The disposition to know how one's breasts normally feel and to report genuine change, distinct from the structured monthly ritual and not shown to be harmful.
Breast self-examination (BSE).
The inspection and palpation of one's own breasts on a regular schedule to detect lumps or changes; classified in MeSH as a health behavior.
Cochrane review.
A systematic review following the Cochrane Collaboration's standardized methods; the BSE review pooled the Shanghai and Leningrad trials to reach the field's defining mortality-null verdict.
Detection criterion.
In signal detection theory, the threshold of evidence at which a sensation is called a signal; lowering it raises both hits and false alarms.
False alarm.
Calling a signal present when it is absent; in BSE, judging a benign lump suspicious, which leads to a benign biopsy.
Health behavior.
An action a person takes bearing on their health; BSE is studied as one, governed by motivation and belief rather than clinician administration.
Health Belief Model (HBM).
Rosenstock's framework predicting preventive health action from perceived susceptibility, severity, benefits, and barriers, later extended with self-efficacy.
Mortality endpoint.
Death from the disease in question; the outcome the BSE trials measured and the only one that distinguishes genuine from illusory screening benefit.
Perceived barriers.
A person's sense of the costs or obstacles to a health action; one of the Health Belief Model's core predictors of whether BSE is performed.
Perceived susceptibility.
A person's belief about their own likelihood of developing a condition; a Health Belief Model construct that public-health campaigns raised to drive BSE uptake.
Randomized controlled trial (RCT).
A study design that allocates participants to intervention or control by chance; the Shanghai and Leningrad RCTs provided the decisive BSE evidence.
Self-efficacy.
Confidence in one's ability to perform a behavior; added to the Health Belief Model in 1988 and especially relevant to a skilled action like palpation.
Signal detection theory.
The framework separating sensitivity from response criterion in a detection task; it explains why anxious or frequent self-examination multiplies false alarms faster than hits.
U.S. Preventive Services Task Force (USPSTF).
An independent U.S. panel issuing evidence-based preventive-care recommendations; it assigned the teaching of BSE a grade D, recommending against it.

Key Researchers

Cornelia J. Baines

(University of Toronto). Epidemiologist and deputy director of the Canadian National Breast Screening Study, co-author of the analysis of breast self-examination technique and breast-cancer death — a central figure in the Canadian evidence that led the national task force to recommend against routinely teaching BSE. Faculty

Victoria L. Champion

(Indiana University). Nursing scientist whose Health Belief Model instruments for breast-cancer screening operationalized perceived susceptibility, benefits, and barriers, letting researchers test why women did or did not perform breast self-examination. ORCID · Faculty · Wikidata

Peter C. Gøtzsche

(Institute for Scientific Freedom). Physician-researcher and co-founder of the Cochrane Collaboration whose systematic reviews of breast self-examination and mammography screening set the modern evidentiary standard; his Cochrane review is the central source for the finding that routine BSE does not reduce breast-cancer mortality. ORCID · Wikipedia · Wikidata

Anthony B. Miller

(University of Toronto). Cancer epidemiologist who led the Canadian National Breast Screening Study, the trial infrastructure within which the effect of breast self-examination technique on breast-cancer death was analyzed — foundational to the evidence that reshaped screening guidelines. Faculty · Wikidata

Frequently Asked Questions

What is breast self-examination?

It is the practice of a woman inspecting and palpating her own breasts on a regular schedule, classically monthly, to detect lumps or changes. In MeSH it is classified as a health behavior rather than a diagnostic test, which is why cognitive psychology studies it as an action governed by motivation and belief.

Does breast self-examination reduce deaths from breast cancer?

No. Two large randomized trials in Shanghai and Leningrad and a Cochrane review that pooled them found no reduction in breast-cancer mortality from structured self-examination, despite more lumps being detected.

If it detects more lumps, how can it not save lives?

Because almost all the additional lumps are benign. Detecting more benign lesions earlier generates biopsies and anxiety without changing the number of lethal cancers caught in time, so the mortality curves of examined and unexamined groups coincide.

What harm does it actually do?

Women performing BSE had almost twice as many biopsies with benign results. Each is an invasive procedure carrying anxiety, cost, and a small complication risk, with no offsetting survival benefit: a measurable harm rather than a neutral one.

Why was it promoted for so long if it does not work?

Its promotion rested on the intuitive plausibility of early detection and on health beliefs the Health Belief Model formalizes: perceived susceptibility, benefits, and barriers. Campaigns moved those beliefs and uptake followed, decades before any trial tested the outcome.

Is there a difference between breast self-examination and breast awareness?

Yes, and it matters. Structured BSE is the taught monthly ritual with a fixed search pattern; breast awareness is simply knowing one's normal state and reporting genuine change. The trials condemned the former, not the latter.

What do current guidelines recommend?

Major bodies including the U.S. Preventive Services Task Force, the Canadian Task Force on Preventive Health Care, and the American Cancer Society recommend against routinely teaching structured breast self-examination to women at average risk.

Why does the behavior persist if it has been disproven?

Partly because belief-driven health behavior is resistant to disconfirmation, and partly because in low-resource settings where mammography is unavailable, self-examination is one of the few early-detection options within reach, so its decision context differs from that of high-income systems.

References

Baxter, N. (2001). Preventive health care, 2001 update: Should women be routinely taught breast self-examination to screen for breast cancer? CMAJ, 164(13), 1837–1846. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC81191/

Champion, V. L. (1999). Revised susceptibility, benefits, and barriers scale for mammography screening. Research in Nursing & Health, 22(4), 341–348. https://doi.org/10.1002/(SICI)1098-240X(199908)22:4<341::AID-NUR8>3.0.CO;2-P

Champion, V. L., & Skinner, C. S. (2008). The health belief model. In K. Glanz, B. K. Rimer, & K. Viswanath (Eds.), Health behavior and health education: Theory, research, and practice (4th ed., pp. 45–65). Jossey-Bass.

Hackshaw, A. K., & Paul, E. A. (2003). Breast self-examination and death from breast cancer: A meta-analysis. British Journal of Cancer, 88(7), 1047–1053. https://doi.org/10.1038/sj.bjc.6600847

Harvey, B. J., Miller, A. B., Baines, C. J., & Corey, P. N. (1997). Effect of breast self-examination techniques on the risk of death from breast cancer. CMAJ, 157(9), 1205–1212. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1228347/

Kösters, J. P., & Gøtzsche, P. C. (2003). Regular self-examination or clinical examination for early detection of breast cancer. Cochrane Database of Systematic Reviews, (2), CD003373. https://doi.org/10.1002/14651858.CD003373

Nelson, H. D., Fu, R., Cantor, A., Pappas, M., Daeges, M., & Humphrey, L. (2016). Effectiveness of breast cancer screening: Systematic review and meta-analysis to update the 2009 U.S. Preventive Services Task Force recommendation. Annals of Internal Medicine, 164(4), 244–255. https://doi.org/10.7326/M15-0969

Oeffinger, K. C., Fontham, E. T. H., Etzioni, R., Herzig, A., Michaelson, J. S., Shih, Y.-C. T., Walter, L. C., Church, T. R., Flowers, C. R., LaMonte, S. J., Wolf, A. M. D., DeSantis, C., Lortet-Tieulent, J., Andrews, K., Manassaram-Baptiste, D., Saslow, D., Smith, R. A., Brawley, O. W., & Wender, R. (2015). Breast cancer screening for women at average risk: 2015 guideline update from the American Cancer Society. JAMA, 314(15), 1599–1614. https://doi.org/10.1001/jama.2015.12783

Rosenstock, I. M. (1974). Historical origins of the health belief model. Health Education Monographs, 2(4), 328–335. https://doi.org/10.1177/109019817400200403

Rosenstock, I. M., Strecher, V. J., & Becker, M. H. (1988). Social learning theory and the health belief model. Health Education Quarterly, 15(2), 175–183. https://doi.org/10.1177/109019818801500203

Semiglazov, V. F., Moiseyenko, V. M., Bavli, J. L., Migmanova, N. Sh., Seleznyov, N. K., Popova, R. T., Ivanova, O. A., Orlov, A. A., Chagunava, O. A., Barash, N. J., Matitzin, A. N., Dyatchenko, O. T., Kozhevnikov, S. Y., Alexandrova, G. I., Sanchakova, A. V., & Musayev, B. T. (1992). The role of breast self-examination in early breast cancer detection (results of the 5-years USSR/WHO randomized study in Leningrad). European Journal of Epidemiology, 8(4), 498–502. https://doi.org/10.1007/BF00146366

Siu, A. L. (2016). Screening for breast cancer: U.S. Preventive Services Task Force recommendation statement. Annals of Internal Medicine, 164(4), 279–296. https://doi.org/10.7326/M15-2886

Thomas, D. B., Gao, D. L., Ray, R. M., Wang, W. W., Allison, C. J., Chen, F. L., Porter, P., Hu, Y. W., Zhao, G. L., Pan, L. D., Li, W., Wu, C., Coriaty, Z., Evans, I., Lin, M. G., Stalsberg, H., & Self, S. G. (2002). Randomized trial of breast self-examination in Shanghai: Final results. Journal of the National Cancer Institute, 94(19), 1445–1457. https://doi.org/10.1093/jnci/94.19.1445

Udoh, R. H., Tahiru, M., Ansu-Mensah, M., Bawontuo, V., Danquah, F. I., & Kuupiel, D. (2020). Women's knowledge, attitude, and practice of breast self-examination in sub-Saharan Africa: A scoping review. Archives of Public Health, 78, 84. https://doi.org/10.1186/s13690-020-00452-9

U.S. Preventive Services Task Force. (2009). Screening for breast cancer: U.S. Preventive Services Task Force recommendation statement. Annals of Internal Medicine, 151(10), 716–726. https://doi.org/10.7326/0003-4819-151-10-200911170-00008