Abstract
Background:
The ‘Call for a Kit (CFAK)' initiative offers consultations for colorectal cancer (CRC) screening non-responders through person-centered, community-delivered patient navigation strategies. This study investigated CFAK's impact on tackling inequalities in CRC screening participation since the new fecal immunochemical test (FIT) implementation.
Methods:
2,360 bowel cancer screening non-responders were contacted via telephone and offered in-person or telephone consultations as part of the CFAK intervention between July 2022 and February 2023. Outcomes included uptake of the consultation offer and subsequent completion/return of a FIT kit. The intervention's effectiveness in reducing inequalities was assessed using multivariate logistic regression.
Results:
Of 2.360 individuals calls, 333 attended a consultation, requested a test kit and completed a test, equating to a 14.1% completion rate across the sample. FIT kit return was higher among individuals with Indian (22.0 vs. 13.6%; adjusted odds ratio (aOR): 2.26, 95% confidence interval (CI): 1.52–3.34; 0.001), Black, mixed, or other ethnic backgrounds than white adults. Importantly, people with disabilities (33.7 vs. 12.7%; aOR: 3.58, 95% CI: 2.49–5.14; 0.001) were more likely to return a test kit compared to people without a disability.
Conclusion:
The findings show that CFAK is more effective among marginalized groups, such as ethnic minority groups and people with learning disabilities, who are less likely to participate in bowel cancer screening when routinely invited.
Introduction
Colorectal cancer (CRC, also known as bowel cancer) is the fourth most common cancer in England and when diagnosed at an early stage, almost all patients can survive for ten years or longer (). Since 2006, the National Bowel Cancer Screening Programme (BCSP) offers all adults aged 60–74 (extended to 50 years old in 2021) the opportunity to complete a home-based stool sampling test that aims to detect bowel cancer at an early stage when no symptoms are experienced. The majority of CRC detected through screening is at early stage when treatment options are more effective. The success of screening largely depends on uptake of the test among the invited population.
Since the introduction of the easy-to-complete kit called the fecal immunochemical test (FIT), almost 7 out of 10 people participate in screening (). FIT has demonstrated an increase in uptake across all deprivation quintiles (). However, despite the significant efforts that have been made to target screening non-responders that inequalities in CRC screening participation have been persistent between the most deprived and the least deprived with over 20 percentage points difference in uptake (, ). This highlighted that population-based interventions have yet to make a significant impact on individuals who are still less inclined to take part and the structural barriers to screening are remaining. Evidence further demonstrates that people from non-white ethnic communities, do not use English as their first language, people with learning disabilities, sensory impairments () and severe mental illness () are disadvantaged across all cancer screening programmes, primarily in BCSP ().
A range of modifiable barriers contribute to these disparities. Previous systematic reviews have reported limited awareness of the test and its benefits, unclear or insufficient information in screening invitations, and practical difficulties such as uncertainty about how to complete the test or challenges receiving and returning kits (, ). These issues are often compounded for disadvantaged groups, including migrants, people with low English proficiency, and those with disabilities, who may also face additional communication, cultural and structural barriers that further hinder engagement with screening (, ).
Thus, it is important to test, develop and evaluate interventions which will improve outcomes from those who are likely to be facing health inequalities in line with the NHS England's national framework for reducing inequalities: the ‘CORE20Plus5′ framework ().
In 2015, the National Health Service (NHS) England North West commissioned a local community-engagement intervention, called: “Call for A Kit” (CFAK) in attempt to improve CRC screening uptake among GP practices with less than 60% uptake (). The CFAK is delivered by a person-centered, non-clinical health promotion team with cultural competence training within the Lancashire BCSP and parallels the key components of patient navigation interventions (). Recent systematic reviews have shown that such interventions can increase CRC screening rates, particularly among minority groups and economically disadvantaged populations (, ). CFAK involves GP practices identifying individuals who are not up to date with CRC screening. All potential individuals receive a text-message informing them that they would soon receive a phone call from the health promotion team and they can opt-out if they do not wish to receive this phone call. During the call, the health promotion team offers individuals the choice of a 15-min in-person or telephone consultation to discuss CRC screening. During the in-person consultation, barriers to CRC screening are identified and discussed. Participants are shown the screening kit and a video on how to use it. They are also offered a replacement kit if needed. Similarly, during the telephone consultation, barriers were identified and discussed, with a new replacement kit offered if needed. At the end of the consultation, the individuals are encouraged to decide if they would like to a new test kit to be requested from BCSP on their behalf. Previous evaluation of CFAK during the use of fecal occult blood test (FOBt) in 2019 found that approximately 15% of those contacted by the health promotion team ordered and returned a test kit with positive impact on those from ethnic minority backgrounds and with the majority (71.5%) opting for in-person consultations (). In 2020–2021, the intervention was paused due to the pandemic and changes within the BCSP.
The present project aimed to evaluate to what extent CFAK's intervention model continues to be effective reducing inequalities among underserved communities (e.g. those with social deprivation, disabilities and ethnic minorities) within the FIT-based CRC screening participation among previous screening non-responders. Furthermore, we assessed whether CFAK is an equitable intervention i.e. are there differences in the characteristics of individuals likely to engage with CFAK.
Methods
Study design
This is a service evaluation study using observational anonymised data collected as part of CFAK. We evaluated the call logs of the CFAK intervention across 27 GP practices in Lancashire, between July 2022 and February 2023.
Participants
Data included men and women registered with one of the 27 participating practices who had not returned their CRC screening FIT kit within 18 weeks of their most recent invitation and had not opted out of the CFAK intervention. CFAK eligible individuals were identified by GP practices using data available from their clinical systems.
Data collection
The health promotion team kept a call log for every participant included in the study. The log was more detailed than the one used in the previous evaluation (8) and had two sections: one for collecting demographic information from the clinical system and another for tasks and outcomes.
In the first section, the log recorded the GP practice's postcode, used to calculate the Index of Multiple Deprivation (), and the first three elements of the individual's postcode to determine their region. It also included the individual's gender, ethnicity (White, Indian, Pakistani, Black, mixed, or other), disabilities (learning, physical, mental health, sensory disabilities, or long-term illnesses), and age range (60–64, 65–69, and 70–74).
The second section recorded the day and time of each attempted call, whether the call attempt was successful (i.e., telephone answered by the participant), and whether the participant agreed to participate in CFAK. For those who agreed to participate, their preference for an in-person or telephone consultation was documented. Additionally, the log recorded whether they subsequently attended a consultation and whether a test kit was ordered, completed, and returned, with the latter being checked 13 weeks after issuing the replacement. Finally, those who answered the telephone were asked why they did not return their kit for the most recent screening round.
Outcomes
The primary outcome was the proportion of participants who returned a test kit following their CFAK consultation. Secondary outcomes included the proportion of participants who answered the phone, accepted the CFAK invitation, opted for an in-person or telephone consultation, and the main reasons given for not participating in the previous screening round.
Statistical analysis
No formal sample size calculation was done. This exploratory evaluation aimed to understand the impact of the CFAK intervention after FIT was implemented. The sample size was based on the number of GP practices participating during the study period using this particular call log. Multivariate logistic regression was used to assess the effectiveness of CFAK to facilitate FIT kit return among participants from marginalized groups, compared with respective counterparts. The effectiveness of the intervention was assessed on an intention-to-treat basis, as well as a per protocol basis. In the intention-to-treat model, all participants the health promotion team attempted to contact were included. In the per protocol model, only those the team were successfully able to contact, and agreed to participate in CFAK, were included.
Multivariate logistic regression models were also used to assess variation for secondary outcomes, i.e. the proportion of individuals from marginalized groups, and respective counterparts, who were successfully contacted, agree to participate in CFAK, opted for a telephone consultation, opted for a face-to-face consultation, attended a telephone consultation, attended a face-to-face consultation, and requested a test kit. The regression models included gender, age, ethnicity, disability, IMD quintile, and the region where the individual lived as covariates. Descriptive statistics were used to report the frequency of reasons for non-completion of previous FIT screening round, overall sample, and by ethnic group, and disability status. All statistical analyses were conducted using Stata/IC version 16.0 (StataCorp LP, College Station, TX, USA).
Results
Sample characteristics
Table 1 shows that most non-responders targeted by CFAK in July 2022–February 2023 were male (58.1%), aged between 60 and 64 (51.8%), lived in Blackburn (41.3%), had a White ethnic background (59.0%), and had no disabilities (93.1%). Indian (11.7%) and Pakistani (17.5%) individuals constituted the most frequent ethnic minorities.
Table 1
| Variable | N | (%) |
|---|---|---|
| Gender | ||
| Female | 989 | (41.9) |
| Male | 1,371 | (58.1) |
| Age | ||
| 60–64 | 1,223 | (51.8) |
| 65–69 | 766 | (32.5) |
| 70–74 | 371 | (15.7) |
| Ethnicity | ||
| White | 1,392 | (59.0) |
| Indian | 277 | (11.7) |
| Pakistani | 412 | (17.5) |
| Black, mixed or others | 43 | (1.8) |
| Unknown | 236 | (10.0) |
| Disability | ||
| No | 2,197 | (93.1) |
| Yes | 163 | (6.9) |
| Area level deprivation | ||
| IMD quintile 5 [3–698] | 636 | (26.9) |
| IMD quintile 4 [1,236–1,940] | 361 | (15.3) |
| IMD quintile 3 [1,987–4,071] | 465 | (19.7) |
| IMD quintile 2 [5,521–7,612] | 532 | (22.5) |
| IMD quintile 1 [10,382–13,575] | 366 | (15.5) |
| Region where patient lives | ||
| Blackburn | 975 | (41.3) |
| Blackpool | 618 | (26.2) |
| Preston | 45 | (1.9) |
| Liverpool | 641 | (27.2) |
| Wigan | 81 | (3.4) |
Description of the study sample (N = 2,360).
IMD quintiles are calculated based on the rank of the GP practice which ranges from 1 (the most deprived area) to 32,844 (the least deprived area).
Participant flow
Figure 1 shows that, of the 2,360 non-responders who were called, 1,242 (52.6%) were contacted successfully (answered the call). Of these, 249 (20.1%) declined the invitation to participate in CFAK, 696 (56.0%) accepted an in-person consultation, and 297 (23.9%) opted for a telephone-based consultation. Of the in-person consultations, 475 (68.3%) attended. Approximately half of those who attended an in-person consultation ordered and returned a test kit (239/475, 50.3%). Phone-based consultations contributed an additional 84 completed test kits (84/267, 31.5%).
Figure 1
Answering the phone call and preference for consultation (REACH)
The adjusted regression results in Table 1 indicate that individuals aged 70–74 were more likely to answer the phone than individuals aged 60–64 (59.7 vs. 50.9%; adjusted odds ratio (aOR) 1.40, 95% confidence interval (CI) 1.08–1.82; p = 0.011). Similarly, those of Indian ethnic background were more likely to answer than those of White British background (64.3 vs. 56.7%; aOR 1.60, 95% CI 1.18–2.17; p = 0.003), as were individuals with a disability compared with individuals without a disability (96.3 vs. 50.6%; aOR 23.18, 95% CI 10.16–52.86; p < 0.001). Conversely, individuals from less deprived areas were less likely to answer the phone (quintile 1: 48.1 vs. quintile 5: 55.7%; aOR 0.46, 95% CI 0.31–0.69; p < 0.001 and quintile 2: 49.1 vs. quintile 5: 55.7%; aOR 0.57, 95% CI 0.38–0.86; p = 0.007).
Supplementary Table S2 in the online supplementary file shows that individuals with Indian or Pakistani ethnic backgrounds, or those with disabilities, were more likely to accept the invitation to participate in CFAK compared with those of White ethnicity or no disability (Indian: 88.2 vs. 76.3%; aOR: 2.50, 95% CI: 1.45–4.31; p = 0.001; Pakistani: 87.7 vs. 76.3%; aOR: 2.21, 95% CI: 1.35–3.62; p = 0.002; disability: 90.5 vs. 78.4%; aOR: 3.77, 95% CI: 2.11–6.76; p < 0.001). In contrast, individuals aged 70–74 were less likely to accept an invitation compared to those aged 60–64 (68.3 vs. 82.5%; aOR: 0.42, 95% CI: 0.29–0.62; p < 0.001), as were participants from Liverpool compared with those from Blackburn (71.4 vs. 84.3%; aOR: 0.41, 95% CI: 0.25–0.67; p < 0.001).
Regarding consultation type preferences, Supplementary Table S3 in the online supplementary file shows that individuals with Indian or Pakistani ethnic backgrounds were more likely to prefer an in-person consultation compared with those of a White background (77.1 vs. 66.0%; aOR: 2.38, 95% CI: 1.46–3.89; p = 0.001 and 74.9 vs. 66.0%; aOR: 2.10, 95% CI: 1.35–3.27; p = 0.001). Similarly, those with disabilities were more likely to prefer in-person consultations compared with those without disabilities (78.2 vs. 68.7%; aOR: 1.80, 95% CI: 1.16–2.80; p = 0.009), and those living in Liverpool were more likely to prefer in-person consultations compared with those living in Blackburn (77.1 vs. 68.0%; aOR: 2.28, 95% CI: 1.31–3.95; p = 0.003).
FIT order and return
Intention-to-treat analysis
Tables 2 and 3 shows the results of the primary analysis. Ordering a test kit was positively associated with being of Indian (45.5 vs. 30.1%; aOR: 2.49, 95% CI: 1.81–3.41; p < 0.001) or Pakistani background (37.6 vs. 30.1%; aOR: 1.62, 95% CI: 1.22–2.16; p = 0.001) compared to White, or having a disability (73.0 vs. 27.4%; aOR: 7.40, 95% CI: 5.10–10.74; p < 0.001). Conversely, individuals with unknown ethnic backgrounds (1.7 vs. 30.1%; aOR: 0.04, 95% CI: 0.02–0.12; p < 0.001), or those living in Liverpool instead of Blackburn (23.7 vs. 36.2%; aOR: 0.69, 95% CI: 0.49–0.99; p = 0.042), were less likely to order a test kit. A similar pattern was observed for returning test kits. Individuals with Indian (22.0 vs. 13.6%; aOR: 2.26, 95% CI: 1.52–3.34; p < 0.001), Black, mixed, or other ethnic backgrounds (27.9 vs. 13.6%; aOR: 2.65, 95% CI: 1.29–5.43; p = 0.008), or those with disabilities (33.7 vs. 12.7%; aOR: 3.58, 95% CI: 2.49–5.14; p < 0.001) were more likely to return a test kit than those with White ethnicity or no disability. In contrast, those with unknown ethnic backgrounds (0.9 vs. 13.6%; aOR: 0.06, 95% CI: 0.02–0.26; p < 0.001) or living in Liverpool (13.6 vs. 17.0%; aOR: 0.52, 95% CI: 0.33–0.82; p = 0.005) instead of Blackburn were less likely to return a test kit.
Table 2
| Variable | N | N | (%) | Unadjusted model | Adjusted model | ||
|---|---|---|---|---|---|---|---|
| OR | 95% CI | aOR | 95% CI | ||||
| Overall | 2,360 | 1,242 | (52.9) | – | – | – | – |
| Gender | |||||||
| Female | 989 | 535 | (54.1) | Ref. | Ref. | ||
| Male | 1,371 | 707 | (51.6) | 0.904 | 0.767–1.064 | 0.900 | 0.749–1.081 |
| Age | |||||||
| 60–64 | 1,223 | 622 | (50.9) | Ref. | Ref. | ||
| 65–69 | 766 | 399 | (52.1) | 1.050 | 0.877–1.259 | 1.033 | 0.846–1.261 |
| 70–74 | 371 | 221 | (59.7) | 1.424 | 1.125–1.802** | 1.403 | 1.081–1.822* |
| Ethnicity | |||||||
| White | 1,392 | 790 | (56.7) | Ref. | Ref. | ||
| Indian | 277 | 178 | (64.3) | 1.370 | 1.048–1.791* | 1.599 | 1.178–2.172** |
| Pakistani | 412 | 227 | (55.1) | 0.935 | 0.749–1.167 | 1.097 | 0.841–1.432 |
| Black, mixed or others | 43 | 20 | (46.5) | 0.663 | 0.361–1.218 | 0.755 | 0.403–1.412 |
| Unknown | 236 | 27 | (11.4) | 0.098 | 0.065–0.149** | 0.092 | 0.060–0.142** |
| Disability | |||||||
| No | 2,197 | 1,112 | (50.6) | Ref. | Ref. | ||
| Yes | 163 | 157 | (96.3) | 26.818 | 11.816–60.864** | 23.178 | 10.164–52.856** |
| Area level deprivation | |||||||
| IMD quintile 5 [3–698] | 636 | 354 | (55.7) | Ref. | Ref. | ||
| IMD quintile 4 [1,236–1,940] | 361 | 187 | (51.8) | 0.856 | 0.661–1.109 | 0.622 | 0.440–0.878** |
| IMD quintile 3 [1,987–4,071] | 465 | 264 | (56.8) | 1.046 | 0.822–1.332 | 0.897 | 0.678–1.187 |
| IMD quintile 2 [5,521–7,612] | 532 | 261 | (49.1) | 0.767 | 0.609–0.967* | 0.568 | 0.376–0.859** |
| IMD quintile 1 [10,382–13,575] | 366 | 176 | (48.1) | 0.738 | 0.570–0.955* | 0.459 | 0.306–0.688** |
| Region where patient lives | |||||||
| Blackburn | 975 | 530 | (54.4) | Ref. | Ref. | ||
| Blackpool | 618 | 332 | (53.7) | 0.975 | 0.796–1.193 | 1.156 | 0.839–1.591 |
| Preston | 45 | 20 | (44.4) | 0.672 | 0.368–1.226 | 0.949 | 0.472–1.907 |
| Liverpool | 641 | 318 | (49.6) | 0.827 | 0.677–1.009 | 1.267 | 0.925–1.735 |
| Wigan | 81 | 42 | (51.8) | 0.904 | 0.574–1.423 | 1.620 | 0.938–2.797 |
| N | – | – | – | 2,360 | – | 2,360 | – |
Binary logistic regression on answering phone call (N = 2,360).
*p < 0.05;
**p < 0.01.
CI, confidence interval; IMD, index of multiple deprivation; OR, odds ratio.
IMD quintiles are calculated based on the rank of the GP practice which ranges from 1 (the most deprived area) to 32,844 (the least deprived area).
Table 3
| Variable | Ordering a test kit | Returning a test kit | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Unadjusted model | Adjusted model | Unadjusted model | Adjusted model | |||||||
| (%) | OR | 95% CI | aOR | 95% CI | (%) | OR | 95% CI | aOR | 95% CI | |
| Overall | (30.6) | (14.1) | ||||||||
| Gender | ||||||||||
| Female | (29.5) | Ref. | Ref. | (13.0) | Ref. | Ref. | ||||
| Male | (31.3) | 1.087 | 0.910–1.299 | 1.000 | 1.000–1.000 | (14.9) | 1.165 | 0.919–1.478 | 1.042 | 0.808–1.344 |
| Age | ||||||||||
| 60–64 | (30.1) | Ref. | Ref. | (14.2) | Ref. | Ref. | ||||
| 65–69 | (31.7) | 1.080 | 0.888–1.312 | 1.019 | 0.823–1.261 | (14.1) | 0.990 | 0.764–1.282 | 0.947 | 0.722–1.242 |
| 70–74 | (29.7) | 0.979 | 0.759–1.262 | 0.906 | 0.685–1.199 | (13.8) | 0.961 | 0.686–1.345 | 0.901 | 0.632–1.285 |
| Ethnicity | ||||||||||
| White | (30.1) | Ref. | Ref. | (13.6) | Ref. | Ref. | ||||
| Indian | (45.5) | 1.938 | 1.490–2.520** | 2.487 | 1.813–3.411** | (22.0) | 1.798 | 1.301–2.483** | 2.257 | 1.524–3.342** |
| Pakistani | (37.6) | 1.401 | 1.113–1.763** | 1.624 | 1.222–2.159** | (16.8) | 1.280 | 0.948–1.730 | 1.353 | 0.937–1.954 |
| Black, mixed or others | (39.5) | 1.518 | 0.815–2.828 | 1.785 | 0.937–3.401 | (27.9) | 2.464 | 1.244–4.882** | 2.651 | 1.294–5.431** |
| Unknown | (1.7) | 0.040 | 0.015–0.108** | 0.043 | 0.016–0.117** | (0.9) | 0.054 | 0.013–0.221** | 0.063 | 0.015–0.257** |
| Disability | ||||||||||
| No | (27.4) | Ref. | Ref. | (12.7) | Ref. | Ref. | ||||
| Yes | (73.0) | 7.166 | 5.008–10.253** | 7.398 | 5.095–10.740** | (33.7) | 3.515 | 2.482–4.979** | 3.576 | 2.487–5.144** |
| Area level deprivation | ||||||||||
| IMD quintile 5 [3–698] | (34.0) | Ref. | Ref. | (17.0) | Ref. | Ref. | ||||
| IMD quintile 4 [1,236–1,940] | (31.9) | 0.909 | 0.690–1.197 | 0.758 | 0.529–1.087 | (15.5) | 0.898 | 0.631–1.277 | 0.770 | 0.492–1.205 |
| IMD quintile 3 [1,987–4,071] | (35.5) | 1.069 | 0.832–1.375 | 0.887 | 0.665–1.184 | (13.6) | 0.766 | 0.547–1.073 | 0.618 | 0.424–0.901* |
| IMD quintile 2 [5,521–7,612] | (25.0) | 0.648 | 0.502–0.837** | 0.751 | 0.481–1.172 | (11.3) | 0.621 | 0.443–0.872** | 0.842 | 0.481–1.476 |
| IMD quintile 1 [1,0382–1,3575] | (25.1) | 0.653 | 0.490–0.870** | 0.679 | 0.442–1.045 | (12.6) | 0.703 | 0.484–1.019 | 0.772 | 0.456–1.305 |
| Region where patient lives | ||||||||||
| Blackburn | (36.2) | Ref. | Ref. | (18.0) | Ref. | Ref. | ||||
| Blackpool | (30.7) | 0.782 | 0.631–0.970* | 1.197 | 0.854–1.678 | (13.4) | 0.709 | 0.534–0.941* | 0.971 | 0.630–1.496 |
| Preston | (22.2) | 0.503 | 0.246–1.029 | 0.710 | 0.315–1.604 | (11.1) | 0.571 | 0.222–1.469 | 0.679 | 0.243–1.901 |
| Liverpool | (23.7) | 0.548 | 0.438–0.685** | 0.694 | 0.488–0.987* | (9.8) | 0.498 | 0.366–0.677** | 0.519 | 0.329–0.820** |
| Wigan | (19.8) | 0.434 | 0.247–0.761** | 0.700 | 0.362–1.355 | (8.6) | 0.432 | 0.196–0.955* | 0.552 | 0.227–1.341 |
| N | – | 2,360 | – | 2,360 | – | – | 2,360 | – | 2,360 | |
Binary logistic regression on ordering and returning a test kit (intention-to-treat analysis, N = 2,360).
Per protocol analysis
Out of the 743 individuals who received either an in-person or phone consultation, 721 (97.0%) ordered a test kit, and 333 (46.2%) returned it (see Supplementary Table S4 in the online supplementary file). Ordering a test kit was less likely for those who attended an in-person consultation compared to a phone consultation (95.6 vs. 99.6%; aOR: 0.06, 95% CI: 0.01–0.53; p = 0.011) and for those with unknown ethnic backgrounds compared to White ethnic backgrounds (80.0 vs. 97.7%; aOR: 0.02, 95% CI: 0.01–0.65; p = 0.027). Returning a test kit was more likely for those who attended in-person instead of a phone consultation (54.2 vs. 32.6%; aOR: 2.46, 95% CI: 1.76–3.43; p < 0.001; see Supplementary Table S5 in the online supplementary file).
Main reason mentioned for not participating in the previous screening round
Supplementary Table S5 in the online supplementary file shows that out of the 1,265 people who answered the phone, 960 (75.9%) provided the main reason for not participating previously. The three most frequently mentioned reasons were indifference toward cancer screening (196/960; 20.4%), missing the test kit, either because they did not receive it or misplaced it (161/960; 16.8%), and not knowing how to use the test kit (151/960; 15.8%). Overall, the majority of respondents (525/960; 54.7%) cited practical barriers such as missing the test kit, lack of information, mental or physical health issues, being busy, or being unavailable as their main reasons for not participating. Supplementary Tables S6, S7 in the supplementary file indicate that among respondents of Indian, Pakistani, Black, mixed, or other ethnic backgrounds, the primary reasons for initial non-participation were past issues such as missing test kits (83/333; 24.9%), indifference toward screening (67/333; 20.1%), and information gaps (59/333; 17.7%). For respondents with disabilities, the main reasons cited were health issues (28/147; 19.0%), lack of information (27/147; 18.4%), and missing test kits (24/147; 16.3%).
Discussion
Summary of main findings
This study evaluated whether CFAK as a non-clinical health promotion intervention has continued to address inequalities in CRC screening participation. The findings from this latest evaluation showed that CFAK acceptability is higher among ethnically diverse communities (i.e. Indian, Black, mixed, or other ethnic backgrounds) and those with disabilities which further parallels the proportion of test orders as well as their returns from these marginalized communities. These findings demonstrate that CFAK continues to be effective at addressing inequalities in cancer screening with impact on specific underserved communities in Lancashire, in the Northwest of England.
Comparisons with previous literature
Our findings are comparable with the previous evaluation testing the effectiveness of the CFAK intervention with the gFOBt () which reported an overall return rate of 15.3% (n = 1,651/10,772), which is slightly higher than the rate seen in this study (i.e., 14.1%, n = 333/2,360). This difference may have emerged from the positive impact of the FIT implementation which resulted with most GP practices to have an uptake over 60%. Thus, those which are now being targeted by CFAK are potentially from areas with wider health inequalities and this potentially explains the different compositions of the two CFAK samples. For instance, the non-responders in this study are more ethnically diverse and economically deprived. Additionally, similar to the previous evaluation, we found that in-person consultations were more effective, as test kits were more likely to be returned by those who attended in-person rather than over the phone consultation. While the analysis showed that individuals with Indian or Pakistani ethnic backgrounds and/or disabilities were more likely to choose in-person consultations, the call log did not capture reasons for their preferences. Future studies could explore these preferences to improve the intervention.
Furthermore, this evaluation included factors associated with answering the initial phone call, shedding light on who the intervention is more likely to reach and whether it is equitable. The results showed that 1 in 2 calls are not picked up by the target population with greater difficulties with engaging potential first-time invitees screening at age 60–64. The results also showed while older people are more likely to answer the phone call, their acceptability to attend CFAK is lower in comparison. Future research should explore strategies to improve this, such as optimizing call times or using alternative contact methods, like text messages and automated booking systems to CFAK clinics among people aged 60–64. This would likely reduce future inequalities arising from non-participation in screening as evidence demonstrates tackling barriers at first-time participation would support continuous participation of this biennial screening programme ().
Additionally, the analysis of the main reasons for not participating in the previous screening round revealed several practical barriers, such as missing test kits or lack of information. These barriers were also frequently mentioned by individuals from ethnic backgrounds and those with disabilities and are in line with findings from previous studies (–). The unpublished qualitative evaluation of CFAK patient experience with a sub-sample of CFAK attendees (n = 12) further support the quantitative evaluation findings. We identified that CFAK was effective demystifying beliefs around bowel cancer screening as well as giving advice for how to complete the test kit which highlighted the educational component of patient navigation interventions (). The qualitative evaluation further showed that CFAK addresses three main barriers to screening: not knowing how to complete the kit, low awareness of screening purposes, and fear of future outcomes. CFAK's person-centered approach involves using lay terms, preferred language and gender, and giving patients the choice of in-person or telephone consultations. This allows non-responders to make informed decisions about screening participation, which contributes to a positive experience and in return addresses barriers to screening participation reported by screening non-responders.
Strengths and limitations
The main strength of this project is that it is an evaluation of an accomplished community engagement intervention in primary care which has previously demonstrated its effectiveness. This has subsequently informed further data collection to be included in this evaluation such as the extended call logs with additional sociodemographic information such as disability status, the capture of the main reasons for not taking part in screening. As a result, the strength of this dataset includes the diverse sample of non-responders, with over 40% of the sample being non-White. This allows the differentiation and comparison between ethnic groups which is often a limitation of evaluating the impact and representativeness of randomized controlled trials ().
However, this evaluation study has several limitations that warrant further research. Firstly, the observational nature of this study limits our ability to make causal inferences. This is due to the project being a service evaluation of an existing health promotion programme implemented in the English National Health Service in Lancashire. It is not known the actual impact of CFAK on screening uptake or coverage as the data captured only represents those who were targeted and invited to CFAK. To better assess CFAK's effectiveness, future studies should employ an experimental design that compares CFAK with no intervention or alternative interventions. Second, the relatively small sample size limited the statistical analysis, necessitating the grouping of some ethnic groups and disabilities due to small cell counts. Third, we only had access to GP practice postcodes to estimate area deprivation. Fourth, as in the previous study, no detailed data on the content of in-person and phone consultations were recorded. However, the similarity in our results suggests that the consultations were consistent across studies. Fifth, although Lancashire's population diversity is similar to the UK average [81.7% White, 9.3% Asian, 4.0% Black, 2.9% Mixed, and 2.1% Other (21)], the results may not be applicable to regions with significantly different population diversity. Therefore, CFAK might not have the same acceptance and outcomes in addressing inequalities elsewhere. Future research should evaluate CFAK in different locations to improve the generalizability of the findings. Lastly, while the analysis included characteristics of individuals less likely to engage with CFAK (e.g., those who did not answer phone calls), we have limited information on whether these individuals eventually completed a screening test kit. In 2021–2022, self-referral test kits requested within a year of the initial CRC screening invitation only accounted for 2% of the total population invited to participate. To our knowledge, there is no evidence on how many kits were returned. Consistent with previous suggestions for improving this evaluation's robustness, trial methodology is needed to understand the extent to which CFAK contributes to improving CRC screening targets in England among non-responders.
Recommendations for future research and practice
Future research should explore the key components of these consultations to better understand the most frequently discussed barriers (). The analysis of the main reasons for not participating in previous screenings suggests that CFAK should address not only practical barriers, such as missing test kits, lack of information, mental or physical health issues, and forgetfulness, but also psychological barriers like indifference to screening and fear. Given CFAK's demonstrated effectiveness in addressing inequalities in CRC screening compared to population-based interventions, it is important to further investigate the components that contribute to its success, such as cultural competence training and non-clinical structure. Future research should delve deeper into the CFAK model to understand its relevance and applicability in reducing inequalities in broader preventive health contexts, using implementation science. Additionally, future evaluations of the intervention could involve the assessment of the cost-effectiveness. A recent systematic review has shown that studies the use of patient navigation services as part of routine patient care are not only cost-effective in international settings (). Given the high dropout rate during the stage of contacting non-responders, future studies should test interventions, such as prenotification text messages, to increase response rates. Previous studies have demonstrated that these interventions can be effective in enhancing engagement (). Lastly, the preference for phone-based consultations highlights the need to compare their effectiveness with in-person consultations. Given the higher costs of in-person clinics and potential restrictions on access to GP practices during the ongoing COVID-19 pandemic (, ), a randomized comparison and cost-effectiveness analysis would be valuable.
Conclusion
In conclusion, this study shows that the CFAK intervention was successful in getting 14.1% of the non-attenders targeted to participate in the CRC screening programme. Importantly, CFAK holds promise in engaging non-responders, especially ethnic minorities and individuals with disabilities, and thereby reduce important inequalities in participation.
Statements
Data availability statement
The data analyzed in this study is subject to the following licenses/restrictions: the data that support the findings of this study are available from the corresponding author upon reasonable request. Requests to access these datasets should be directed to Sandro Tiziano Stoffel, s.stoffel@unibas.ch.
Ethics statement
Ethical approval was not required for the studies involving humans because the evaluation was conducted as part of a service improvement initiative, and therefore, ethical approval was not required in accordance with our institution's guidelines. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required from the participants or the participants' legal guardians/next of kin in accordance with the national legislation and institutional requirements because the study was part of a service evaluation.
Funding
The author(s) declared that financial support was received for this work and/or its publication. Financial support for this study was provided by Rugby HUB, NHSE Lancashire and Lancashire BCSP and North West Cancer Research Inequalities project grant (CI2023.04). Shahida Hanif was supported by the National Institute for Health Research Applied Research Collaboration North West Coast (ARC NWC). The views expressed in this publication are those of the author(s) and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care. The funding agreements ensured the authors' independence in designing the study, interpreting the data, writing, and publishing the report. The BCSP CFAK project is funded by Lancashire BCSP/NHSE and NHS Improvement (North West). It is a joint project delivered and supported by BCSP Lancashire and the Community Voluntary Services Blackburn (CVS).
In memoriam
The authors would like to dedicate this manuscript to Sadiq Patel, one of the key leaders and early adopters of the Lancashire BCSP CFAK, who sadly passed away in October 2024. Sadiq Patel led the implementation of the CFAK clinics in Lancashire which made significant contributions to addressing bowel cancer inequalities in this region.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The authors RK, YH, and CV declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcacs.2026.1518293/full#supplementary-material
References
1.
CancerResearch UK. (2024). Bowel Cancer Statistics. Available online at: https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/bowel-cancer (Accessed October 08, 2024).
2.
UKGovernment. (2022). Bowel Cancer Screening: Annual Report 2021 to 2022. Available online at: https://www.gov.uk/government/publications/bowel-cancer-screening-annual-report-2021-to-2022/bowel-cancer-screening-annual-report-2021-to-2022 (Accessed October 08, 2024).
3.
MossSMathewsCDayTJSmithSSeamanHESnowballJet al. Increased uptake and improved outcomes of bowel cancer screening with a faecal immunochemical test: results from a pilot study within the national screening programme in England. Gut. (2017) 66:1631–44. doi: 10.1136/gutjnl-2015-310691
4.
HirstYStoffelSBaioGMcGregorLvon WagnerC. Uptake of the english bowel (colorectal) cancer screening programme: an update 5 years after the full roll-out. Eur J Cancer. (2018) 103:267–73. doi: 10.1016/j.ejca.2018.07.135
5.
YoungBRobbKA. Understanding patient factors to increase uptake of cancer screening: a review. Future Oncology. (2021) 17:3757–75. doi: 10.2217/fon-2020-1078
6.
KerrisonRSJonesAPengJPriceGVerneJBarleyEAet al. Inequalities in cancer screening participation between adults with and without severe mental illness: results from a cross-sectional analysis of primary care data on english screening programmes. Br J Cancer. (2023) 129:81–93. doi: 10.1038/s41416-023-02249-3
7.
UKGovernment. (2022). Nhs Bowel Cancer Screening: Identifying And Reducing Inequalities. Available online at: https://www.gov.uk/government/publications/nhs-bowel-cancer-screening-identifying-and-reducing-inequalities/nhs-bowel-cancer-screening-identifying-and-reducing-inequalities (Accessed October 08, 2024).
8.
DresslerJJohnsenATMadsenLJRasmussenMJorgensenLN. Factors affecting patient adherence to publicly funded colorectal cancer screening programmes: a systematic review. Public Health. (2021) 190:67–74. doi: 10.1016/j.puhe.2020.10.025
9.
Le BonniecAMeadeOFredrixMMorrisseyEO'CarrollREMurphyPJet al. Exploring non-participation in colorectal cancer screening: a systematic review of qualitative studies. Soc Sci Med. (2023) 329:116022. doi: 10.1016/j.socscimed.2023.116022
10.
MertenJWPomeranzJLKingJLMoorhouseMWynnRD. Barriers to cancer screening for people with disabilities: a literature review. Disabil Health J. (2015) 8:9–16. doi: 10.1016/j.dhjo.2014.06.004
11.
NHSEngland. (2023). Core20PLUS5: National Healthcare Inequalities Improvement Programme. Available online at: https://www.england.nhs.uk/about/equality/equality-hub/national-healthcare-inequalities-improvement-programme/core20plus5/ (Accessed October 08, 2024).
12.
CommunityCVS. (n.d.). Call For a Kit Clinics (CFAKC's). Available online at: https://www.communitycvs.org.uk/index-html/bowel-cancer-screening-programme/call-for-a-kit-clinics-cfakcs/ (Accessed July 25, 2024).
13.
FreemanHP. The origin, evolution, and principles of patient navigation. Cancer Epidemiol Biomarkers Prev. (2012) 21:1614–17. doi: 10.1158/1055-9965.EPI-12-0982
14.
MuliiraJKD'SouzaMS. Effectiveness of patient navigator interventions on uptake of colorectal cancer screening in primary care settings. Jpn.J Nurs Sci. (2016) 13:205–19. doi: 10.1111/jjns.12102
15.
SunnyARustveldL. The role of patient navigation on colorectal cancer screening completion and education: a review of the literature. J Cancer Educ. (2018) 33:251–59. doi: 10.1007/s13187-016-1140-0
16.
StoffelSTMcGregorLHirstYHanifSMorrisLvon WagnerC. Evaluation of the call for a kit intervention to increase bowel cancer screening uptake in Lancashire, England. J Med Screen. (2022) 29:166–71. doi: 10.1177/09691413221089184
17.
UKGovernment. (2019). English Indices of Deprivation 2019. Available online at: https://www.gov.uk/government/statistics/english-indices-of-deprivation-2019 (Accessed March 30, 2024).
18.
LoSHWallerJVrintenCvon WagnerC. Micro actions in colorectal cancer screening participation: a population-based survey study. BMC Cancer. (2015) 15:1–8. doi: 10.1186/s12885-015-1465-9
19.
HanifSJeffersonRLKerrisonRStoffelSTRowleySMorrisLet al. Understanding patient experiences of a community-based intervention to improve bowel screening uptake: a mixed-method evaluation of Call for a Kit clinics. BMJ Open. (2026) 16:e109731. doi: 10.1136/bmjopen-2025-109731
20.
JullJWhiteheadMPetticrewMKristjanssonEGoughDPetkovicJet al. When is a randomised controlled trial health equity relevant? development and validation of a conceptual framework. BMJ open. (2017) 7:e015815. doi: 10.1136/bmjopen-2016-015815
21.
GovernmentDigital Service. (2024.). Population of England and Wales. Ethnicity Facts and Figures. Available online at: https://www.ethnicity-facts-figures.service.gov.uk/uk-population-by-ethnicity/national-and-regional-populations/population-of-england-and-wales/latest/ (Accessed January 16, 2025).
22.
CoronadoGDNyongesaDBPetrikAFThompsonJHEscaronALYoungerBet al. Randomized controlled trial of advance notification phone calls vs. text messages prior to mailed fecal test outreach. Clin Gastroenterol Hepatol. (2021) 19:2353–60. doi: 10.1016/j.cgh.2020.07.053
23.
LimJBroughanJCrowleyDO'KellyBFawsittR. Burke MC, et al. COVID-19′s impact on primary care and related mitigation strategies: a scoping review. Eur J Gen Pract. (2021) 27:166–75. doi: 10.1080/13814788.2021.1946681
24.
HelsperCWCampbellCEmeryJNealRDLiLRubinGet al. Cancer has not gone away: a primary care perspective to support a balanced approach for timely cancer diagnosis during COVID-19. Eur. J. Cancer Care. (2020) 29. doi: 10.1111/ecc.13290
Summary
Keywords
cancer screening, fecal immunochemical test, health promotion, inequalities, intervention, non-attenders
Citation
Stoffel ST, Hanif S, Morris L, Kerrison R, Hirst Y and Von Wagner C (2026) Are community-delivered patient navigation interventions the answer for targeting colorectal cancer screening inequalities? Findings from Lancashire's “Call for a KIT” intervention. Front. Cancer Control Soc. 4:1518293. doi: 10.3389/fcacs.2026.1518293
Received
28 October 2024
Revised
09 February 2026
Accepted
13 March 2026
Published
10 April 2026
Volume
4 - 2026
Edited by
Pei Shang, Mayo Clinic, United States
Reviewed by
Jasmine Giovannoli, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Italy
Jelena Maksimenko, Riga Stradiņš University, Latvia
Updates
Copyright
© 2026 Stoffel, Hanif, Morris, Kerrison, Hirst and Von Wagner.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Sandro Tiziano Stoffel, sandro.stoffel@unibas.ch; Christian Von Wagner, c.wagner@ucl.ac.uk
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.