This is the first literature review of African-based studies that focuses on medication errors and adverse drug events. |
There have been limited reports on medication safety in African countries in the past, but this is rapidly increasing. |
Of all patients admitted to hospital, a median of 2.8% of adverse drug events resulted in hospital admission in the general population, ranging to as high as 5.5% in the adult population. |
Regardless of the medication use process, dosing problems were the most commonly reported type of error. |
1 Introduction
2 Methods
2.1 Definitions
2.2 Data Sources and Searches
2.3 Study Selection
2.3.1 Inclusion Criteria
2.3.2 Exclusion Criteria
2.4 Quality Assessment
2.5 Data Extraction and Statistical Analysis
3 Results
3.1 Search Results
3.2 Characteristics of Adverse Drug Event Studies
Author, year | Country | Setting | Study design | Sample size (patients), duration | Characteristics of the population | Method of detection | Assessment of ADEs | ||
---|---|---|---|---|---|---|---|---|---|
Causality | Severity | Preventability | |||||||
Aderemi-Williams, 2015 [30] | Nigeria | Medical ward | Retrospective chart review | 624, NR | Adult Male: 57.4% | Medical record review | NR | NR | NR |
Benkirane, 2009 [31] | Morocco | Medical, surgical, ICUs and EDs | Retrospective cross-sectional | 1390, 5 days | Adult and paediatric Male: 60% | Solicited information from clinicians | Begaud 1985 [81] | WHO [82] | Schumock 1992 [83] |
Benkirane, 2009 [78] | Morocco | ICU | Prospective cohort | 696, 3 months | Adult and paediatric Male: 54.6% | Daily physician rounds, monitoring for medication ordering and transcribing, solicited reports from health professionals | Begaud 1985 [81] | WHO [82] | Consensus agreement |
Cooke, 1985 [32] | South Africa | Medical ward | Prospective observational | 300, NR | Age ≥10 years Male: 50% | NR | Trunet 1980 [84] | NR | NR |
Eshetie, 2015 [33] | Ethiopia | Paediatric ward | Prospective observational | 600, 2 months | Paediatric Male: 61.8% | Chart review, ward round, patient/caregiver interview, voluntary staff report | WHO-UMC [85] | NCC MERP [24] | Schumock 1992 [83] |
Dedefo, 2016 [79] | Ethiopia | Paediatric ward | Prospective observational | 233, 1 month | Paediatric Male: 63.9% | Chart review, ward round, patient/caregiver interview, voluntary report | Naranjo [86] | NCC MERP [24] | Consensus agreement |
Jennane, 2011 [80]a
| Morocco | ICU | Prospective cohort | 63, 6 weeks | Adult Male: 59% | Clinical round, voluntary and verbal report, chart review, assessing prescriptions and transcriptions | NR | WHO [82] | NR |
Kiguba, 2017 [34] | Uganda | Medical and gynaecological wards | Prospective cohort | 762, 5 months | Adult Female: 70% | Clinical examination, medical record review, patient/caregiver/ward staff interviews | Naranjo [86] | DAIDS AE Grading Table [87] | Schumock 1992 [83] |
Letaief, 2010 [35]b
| Tunisia | Clinical departments | Retrospective cohort | 620, NR | General population Female: 53.4% | Medical record review | Wilson 1995 [88] | Wilson 1995 [88] | Wilson 1995 [88] |
Mabadeje, 1979 [36] | Nigeria | Medical wards | Prospective cohort | 360, 4 months | General population Male: 54% | Medication history interview, review of the nurses’ records and hand-over notes | NR | NR | NR |
Matsaseng, 2005 [37] | South Africa | Gynaecology ward | Retrospective chart review | 793, 9 months | NR, all female | Medical record review | Leappe 1991 [3] | Brennan 1991 [2] | Leappe 1991 [3] |
Mehta, 2008 [38] | South Africa | Medical wards | Prospective observational | 665, 3 months | Adults Female: 51% | Medical record review | WHO [89] | Temple 2004 [90] | Schumock 1992 [83] |
Mouton, 2015 [39] | South Africa | Medical wards | Cross-sectional survey | 1904, 30 days | Adult Female: 56% | Medical record review, medication history, review of prescriptions and laboratory data | WHO-UMC [85] | NA | Schumock 1992 [83] |
Mouton, 2016 [40]c
| South Africa | Medical wards | Cross-sectional survey | 1904, 30 days | Adult Female: 56% | Medical record review, medication history and review of laboratory data | WHO-UMC [85] | Temple 2004 [89] | Schumock 1992 [83] |
Oshikoya, 2007 [41] | Nigeria | Paediatric ward | Retrospective prospective | 3821, 3 years | Paediatric Male: 58% | Medical and nursing record review, prescription chart review | Jones 1982 [91] | Martínez-Mir 1996 [92] | Done, but not clear |
Oshikoya, 2011 [42] | Nigeria | Paediatric ward | Prospective observational | 2004, 18 months | Paediatric Male: 61% | Medical and nursing records review, review of prescription charts, attending clinical rounds, reports from healthcare professionals | Jones 1982 [91] | Schirm 2004 [93] | Schumock 1992 [83] |
Tipping, 2006 [43] | South Africa | Emergency unit | Prospective cross-sectional | 517, 4 months | Elderly Female: 59% | Primary physician and/or principal investigator assessment | Nebeker 2004 [94] | NR | NR |
Tumwikirize, 2011 [44] | Uganda | Medical wards | Longitudinal observational | 728, 6 months | Age > 13 years Female: 56% | History and physical examination, medical record review | Naranjo [86] | Dorman 2000 [95] | Schumock 1992 [83] |
3.2.1 Quality Assessment of Adverse Drug Event Studies
3.2.2 Frequency and Nature of Adverse Drug Events
3.2.2.1 Adverse Drug Events Causing Hospital Admissions
Author, year | Prevalence of ADE-related admission (%)b
| Incidence of ADEs during hospitalisation (%)b
| Prevalence of any suspected ADE (%)b
| Proportion of serious ADEs (%)c
| ADE-related fatality (%)b
| Preventability (%)c
|
---|---|---|---|---|---|---|
Aderemi-Williams, 2015 [30] | 6.4 | 4.3 | ||||
Benkirane, 2009 [31] | 1.4 | 4.2 | 47.5 | 0.1 | 13.2 | |
Benkirane, 2009 [78] | 11.5 | 51.8 | 0.3 | 30.0 | ||
Cooke, 1985 [32] | 4.6 | |||||
Eshetie, 2015 [33] | 0.7a
| 7.7a
| 9.0 | 0.2 | 33.0 | |
Dedefo, 2016 [79] | 7.3 | 5.9 | 0.0 | 47.0 | ||
Jennane, 2011 [80] | 12.7 | 87.5 | 3.2 | |||
Kigbua, 2017 [34] | 25.0 | 31.0 | 0.0 | 55.0 | ||
Letaief, 2010 [35] | 2.7a
| NS | NS | NS | ||
Mabadeje, 1979 [36] | 2.8 | 13.1 | ||||
Matsaseng, 2005 [37] | 9.8a
| NS | NS | NS | ||
Mehta, 2008 [38] | 6.3 | 6.3 | 8.4 | 50.4a
| 0.3a
| 46.0 |
Mouton, 2015 [39] | 2.9 | 43.5 | ||||
Mouton, 2016 [40] | 8.5a
| 23.5 |
d
| 45.0 | ||
Oshikoya, 2007 [41] | 0.4 | 0.7 | SG | 0.1 | 97.7 | |
Oshikoya, 2011 [42] | 0.6 | 1.1 | SG | 0.1 | 20.0 | |
Tipping, 2006 [43] | 14.3a
| 20.1 | ||||
Tumwikirize, 2011 [44] | 1.5 | 49.5 | 4.5 | 0.0 | 0.0 | 4.1 |
Median (IQR) | 2.8 (0.7–6.4) | 7.5 (4.3–16.1) | 8.4 (4.5–20.1) | 23.5 (9.0–50.0) | 0.1 (0.0–0.3) | 43.5 (20.0–47.0) |
3.2.2.2 Any Suspected Adverse Drug Events at Hospital Admission
3.2.2.3 Adverse Drug Events during Hospitalisation
3.2.3 Severity and Seriousness of Adverse Drug Events
3.2.4 Preventability of Adverse Drug Events
3.3 Characteristics of Medication Error Studies
Author, year | Country | Setting | Study design | Sample (e.g. no. of patients or prescriptions/charts), duration | Characteristics of sample | Method of data collection | Clinical significance assessment (yes/no, tool) | Results |
---|---|---|---|---|---|---|---|---|
Prescribing errors
| ||||||||
Agalu, 2011 [45] | Ethiopia | ICU, tertiary hospital | Cross-sectional | 69 patients (398 prescriptions), 67 days | General population Female: 55.6% | Prescription review | NR | 52.5% of prescriptions contain at least 1 error |
Ajemigbitse, 2013 [46] | Nigeria | Medical and paediatric specialties, tertiary hospital | Retrospective | 400 patients (6819 medication orders), 1 year | General population Female: 76.5% | Review of medication records | Yes, Dornan 2009 [96] | 40.9% of medication orders have errors |
Ajemigbitse, 2013 [47] | Nigeria | Medical, paediatric and private wing wards | Prospective qualitative (mixed) | 37 doctors, 6 months | NR | Prescription review and interview of prescribers | NR | 90 errors are committed by 37 doctors |
Ajemigbitse, 2014 [48] | Nigeria | Tertiary hospital | Questionnaire | 30 doctors, 3 months | NR | Structured questionnaire | NR | One quarter of respondents failed to check prescriptions with a reference source and drug interactions |
Ajemigbitse, 2016 [49] | Nigeria | Medical and paediatric wards | Pre-post | Baseline (control): 2065 medication orders, 6 months | NR | Prescription review | NR | Baseline prescribing error rate, 270/2065 (13.08%) |
Alagha, 2011 [50] | Egypt | Paediatric ward, university hospital | Pre-post | Pre: 139 patients (1417 medication orders) Post: 101 patients (1096 medication orders), 10 months | Paediatric population | Educational sessions, provision of drug use assists, designing a medication order chart, physician feedback | Yes, own tool | 78% of orders have least 1 error |
Arulogun, 2011 [51] | Nigeria | Four units (medical out-patient, general out-patient, wards, accident and emergency) | Cross-sectional (mixed) | 1866 prescriptions, NR | NR | Prescription review, observation and in-depth interview | NR | Prescription error rate, 76.3% |
Oshikoya, 2007 [52] | Nigeria | Paediatric outpatient department, university teaching hospital | Retrospective | 1944 prescriptions, 5 months | NR | Prescriptions review | NR | Prescription error rate, 62.2% |
Sada, 2015 [53] | Ethiopia | ICU of a specialised hospital | Retrospective | 220 charts (882 prescription episodes), 1 year | Age >12 years Male: 54.5% | Chart review | Yes, Bates 1995 [25] | Prevalence of 40 errors per 100 orders (359 MEs) |
Yinusa, 2004 [54] | Nigeria | Orthopaedic hospital | Retrospective | 5823 prescriptions/13,833 items, 3 months | NR | Prescription review | Yes, Neville 1989 [97] | 749 prescriptions (12.9%) contained errors; 4.5% of the prescription items have at least 1 error |
Yousif, 2011 [55] | Sudan | Multicentre (public and private hospitals and pharmacies) | Cross-sectional | 2000 prescriptions, 9 months | NR | Prescription review | Yes, Neville 1989 [97] | Only 1 prescription was considered ideal with no error; 12.2% of the prescriptions contained potentially serious errors |
Zeleke, 2014 [56] | Ethiopia | Paediatric ward, referral hospital | Cross-sectional | 136 admissions (384 medication orders), 1 month | Paediatric population Male: 61.8% | Prescription review | NR | Prescribing error rate, 58.07%; 34.70 prescribing errors in 100 patient-days |
Medication administration errors
| ||||||||
Acheampong, 2016 [57] | Ghana | Adult ED, tertiary care hospital | Cross-sectional observational | 338 patients (1332 medication administration observations), 4 months | Adult population Female: 55.9% | Direct observations of medication administration, medication order review | Yes, Chua [98] | 27.2% of all observations have MAEs but 22.8% when wrong time error is excluded |
Agalu, 2012 [58] | Ethiopia | ICU, specialised teaching hospital | Prospective cross-sectional | 54 patients (1200 medication administration observations), 6 weeks | General population Female: 55.6% | Direct observation and review of medication charts | NR | 51.8% of all observations have MAEs |
al Tehewy, 2016 [59] | Egypt | Medical wards | Descriptive observational | 237 patients (2400 medication administration observations), 3 months | Adult population Male: 60.8% | Direct observation | Yes, NCC MERP [24] | 85% of the observations had at least 1 error |
Amponsah, 2016 [60] | Ghana | Anaesthetic practice (national study) | Questionnaire | 164 physician assistants, NR | Physician assistants Male: 62.2% | Self-reporting survey | Yes, self-report | 65.5% of respondents had experienced MEs |
Amucheazi, 2009 [61] | Nigeria | University teaching hospital | Retrospective | 895 elective procedures, NR | NR | NR | NR | 5 patients (0.55%) were affected by MAEs |
Blignaut, 2017 [62] | South Africa | Medical and surgical wards, eight public hospitals | Cross-sectional observation | 315 patients (1847 medication administration observations), 7 months | NR | Direct observation, double checking | NR | 296 errors were identified (94% of patients) |
Gordon, 2004 [63] | South Africa | Department of Anaesthesia, University of Cape Town | Questionnaire | 65 anaesthetists, NR | NR | Self-reporting survey | Yes, self- report | 93.5% of respondents admitted to having administered a wrong drug or the right drug into the wrong site |
Gordon, 2006 [64] | South Africa | University of Cape Town | Questionnaire | 133 anaesthetists, NR | NR | Self-reporting survey | Yes, self-report | 94% admitted to having inadvertently administered a wrong drug; 303 wrong drug administrations |
Feleke, 2010 [65] | Ethiopia | Paediatric ward, specialised teaching hospital | Prospective | 52 patients (218 observations), 2 weeks | Paediatric population | Medication administration observations | NR | Of all observations, 89.9 % of MAEs were identified |
Feleke, 2015 [66] | Ethiopia | Inpatient departments of a referral hospital | Prospective | 263 patients (360 administration interventions), 2 weeks | Adult Female: 53.6% | Questionnaire-based interviews, observations | NR | The incidence of MAEs was 56.4%; 260 (98.8 %) of patients encountered at least 1 type of MAE |
Labuschagne, 2011 [67] | South Africa | 31 public hospitals | Questionnaire | 84 doctors, NR | NR | Questionnaire | Yes, self-report | 39.3% of participants committed at least 1 event of erroneous drug administration |
Llewellyn, 2009 [68] | South Africa | 3 tertiary care hospitals | Prospective | 30, 412 anaesthetics, 6 months | NR | Anaesthetics form | Yes, self-report | Incidence of MAEs and near-misses, 1:274; the actual error made was 1 in 460 anesthetics |
Nwasor, 2014 [69] | Nigeria | 6 secondary and tertiary hospitals | Questionnaire | 43 anaesthetists, NR | NR | Questionnaire | Yes, self-report | 56% of the respondents admitted to ever having a ME |
Oshikoya, 2013 [70] | Nigeria | Paediatric wards, public hospitals | Questionnaire | 50 nurses, NR | Paediatric nurses Female: 100% | Questionnaire | NR | 64% committed at least 1 ME |
MEs (mixed)
| ||||||||
Agu, 2014 [71] | Nigeria | Outpatient pharmacy, 14 secondary public hospitals | Prospective cohort | 6882 patients, 3 years | General population Female: 67% | Active screening programme using pharmaceutical care daily worksheet | NR | Incidence rate of MEs, 40.5 per 100 person-years |
Negash, 2013 [72] | Ethiopia | Adult ED, specialised teaching hospital | Prospective cross-sectional | 742 patient charts, 2 weeks | Adult population Male: 59% | Patient chart review, direct patient/career interview | NR | Of 2968 medication orders, 54.8% have at least 1 error (prescribing and administration) |
Kandil, 2012 [73] | Egypt | Obstetric ED, university hospital | Prospective | 10,000 women (47,192 prescriptions), 9 months | Adult, Female: 100% | Chart review, review of nurses’ notes | NR | 4.18% of prescriptions have errors of any type |
Ogunleye, 2016 [74] | Nigeria | Tertiary hospitals | Questionnaire | 2386 healthcare professionals, 6 months | Doctors, pharmacists, nurses Female: 60.7% | Questionnaire | NR | 47% self-reported at least 1 ME (of any type) |
Sabry, 2014 [75] | Egypt | 8 general wards and 3 critical units, private general hospital | Prospective | 277,661 prescribed doses, 7 months | NR | Medication review, communicate with other healthcare professions and document interventions | NR | 2.8% of doses have problems; prescribing errors, 37%; administration errors, 20%; medication overdose, 15% |
Sabry, 2009 [76] | Egypt | Surgical, medical and mixed ICUs, teaching hospital | Prospective | 220 patients, 1 year | Adult, Male: 66.8% | Observation for any medication related problems/errors | NR | 619 medication problems detected in 213 patients (only 3% were free of problems) |
Shehata, 2016 [77] | Egypt | Tertiary care teaching hospitals | Prospective | 1200 reports, 6 months | General population Male: 44% | Incident reporting | Yes, NCC MERP [24] | Prescribing errors, 54%; monitoring, 25%; administration, 16%; dispensing, 3%; transcribing, 2% |
Benkirane, 2009 [78] | Morocco | 7 ICU wards, academic and military hospitals | Prospective cohort | 696 patients, 3 months | Adult and paediatric, Male: 54.6% | Daily physician rounds, monitoring for medication ordering and transcribing, solicited reports from health professionals | Yes, NCC MERP [24] | Incidence rates per 100 admissions, 7.5; overall ME incidence rate was 7.7 per 1000 patient-days; prescribing stage, 71.1%; administration stage, 21.2%; transcribing stage, 5.7% |
Dedefo, 2016 [79] | Ethiopia | Paediatric ward | Prospective observational | 233 patients, 1 month | Paediatric Male: 63.9% | Chart review, ward round, patient/caregiver interview, voluntary report | Yes, NCC MERP [24] | 75.1 % of patients experienced at least 1 error; the incidence of MEs: 46 MEs per 100 orders, 220 MEs per 100 admissions, 51.4 MEs per 100 patient-days. Ordering stage, 45.8%; administration, 34.9%; monitoring; 8.4%; dispensing 4.1% |
Jennane, 2011 [80] | Morocco | ICU, university hospital | Prospective | 63 patients (4942 orders), 6 weeks | Adult, Male: 59% | Clinical round, voluntary and verbal report, chart review, assessing prescriptions and transcriptions | Yes, WHO [82] | The incidence of MEs: ten MEs per 100 orders, 780 MEs per 100 admissions, 967 MEs per 1000 patient-days; transcribing stage, 60%; ordering stage, 35% |
3.3.1 Quality Assessment of Medication Error Studies
3.3.2 Frequency and Nature of Medication Errors
3.3.2.1 Medication Errors (Mixed)
3.3.2.2 Prescribing Errors
3.3.2.3 Medication Administration Errors
3.3.3 Types of Medication Errors
Author, year | Types of MEs | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Wrong drug/selectiona
| Wrong frequency/duration | Omission errors | Wrong doseb
| Wrong dosage form | Wrong route | Wrong time | Wrong administration technique | Wrong rate of administration | Wrong concentration/dilution | Wrong instruction | Unauthorised order | Abbreviation and ineligible writing | Incompleteness of prescription | Othersc
| |
Prescribing errors
| |||||||||||||||
Agalu, 2011 [45] | √ | √ | √ | √ | √ | √ | |||||||||
Ajemigbitse, 2016 [49] | √ | √ | √ | √ | |||||||||||
Ajemigbitse, 2013 [46] | √ | √ | √ | √ | √ | √ | √ | √ | |||||||
Ajemigbitse, 2014 [48] | √ | √ | √ | √ | √ | √ | |||||||||
Alagha, 2011 [50] | √ | √ | √ | √ | √ | √ | √ | ||||||||
Arulogun, 201 l [51] | √ | √ | √ | √ | √ | ||||||||||
Oshikoya, 2007 [52] | √ | ||||||||||||||
Sada, 2015 [53] | √ | √ | √ | √ | √ | ||||||||||
Yinusa, 2004 [54] | √ | √ | √ | √ | |||||||||||
Zeleke, 2014 [56] | √ | √ | √ | √ | √ | ||||||||||
Medication administration errors
| |||||||||||||||
Acheampong, 2016 [57] | √ | √ | √ | √ | √ | √ | √ | ||||||||
Agalu, 2012 [58] | √ | √ | √ | √ | √ | √ | |||||||||
al Tehewy, 2016 [59] | √ | √ | √ | √ | √ | √ | |||||||||
Amponsah, 2016 [60] | √ | √ | √ | √ | |||||||||||
Blignaut, 2017 [62] | √ | √ | √ | √ | √ | √ | |||||||||
Gordon, 2004 [63] | √ | √ | |||||||||||||
Feleke, 2010 [65] | √ | √ | √ | √ | √ | ||||||||||
Feleke, 2015 [66] | √ | √ | √ | √ | √ | √ | √ | ||||||||
Llewellyn, 2009 [68] | √ | √ | √ | √ | |||||||||||
Nwasor, 2014 [69] | √ | ||||||||||||||
Oshikoya, 2013 [70] | √ | √ | √ | √ | √ | ||||||||||
MEs (mixed)
| |||||||||||||||
Agu, 2014 [71] | √ | √ | √ | √ | √ | ||||||||||
Benkirane, 2009 [78] | √ | √ | √ | √ | √ | √ | √ | √ | √ | ||||||
Dedefo, 2016 [79] | √ | √ | √ | √ | √ | √ | √ | √ | |||||||
Negash, 2013 [72] | √ | √ | √ | √ | √ | √ | √ | ||||||||
Jennane, 2011 [80] | √ | √ | √ | √ | √ | ||||||||||
Kandil, 2012 [73] | √ | √ | √ | √ | √ | √ | √ | ||||||||
Ogunleye, 2016 [74] | √ | √ | √ | √ | √ | ||||||||||
Sabry, 2014 [75] | √ | √ | √ | ||||||||||||
Sabry, 2009 [76] | √ | √ | √ | ||||||||||||
Shehata, 2016 [77] | √ | √ | √ | √ | √ | √ | √ | √ | √ |
3.3.4 Clinical Significance of Medication Errors
3.4 Factors Contributing to Medication Errors
Contributing factors | Author, year | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ajemigbitse, 2014 [48] | Ajemigbitse, 2013 [47] | Amponsah, 2016 [60] | Benikrane 2009 [78] | Dedefo, 2016 [79] | Gordon, 2004 [63] | Gordon, 2006 [64] | Labuschagne, 2011 [67] | Llewellyn, 2009 [75] | Nwasor, 2004 [69] | Oshikoya, 2013 [70] | Yousif, 2011 [55] | Shehata, 2016 [77] | Acheampong, 2016 [57] | Ogunleye, 2016 [74] | |
Individual
| |||||||||||||||
Fatigue | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | |||||
Confusion | √ | √ | |||||||||||||
Memory lapses | √ | √ | |||||||||||||
Rushing | √ | ||||||||||||||
Inadequate monitoring/reporting | √ | ||||||||||||||
Inadequate knowledge/training | √ | √ | √ | √ | √ | √ | √ | ||||||||
Rule violation | √ | ||||||||||||||
Inappropriate administration technique | √ | ||||||||||||||
Low morale | √ | √ | |||||||||||||
Work environment
| |||||||||||||||
High workload | √ | √ | √ | √ | √ | √ | |||||||||
Distraction | √ | √ | √ | √ | √ | √ | |||||||||
Busyness | √ | ||||||||||||||
Lack of resources (e.g. equipment) | √ | √ | √ | √ | |||||||||||
Time of the day | √ | ||||||||||||||
Team
| |||||||||||||||
Communication deficits | √ | √ | √ | ||||||||||||
No senior support | √ | ||||||||||||||
Task
| |||||||||||||||
Lack of documentation | √ | ||||||||||||||
Labelling deficits | √ | √ | √ | √ | √ | ||||||||||
Transcription error | √ | ||||||||||||||
Unclear prescriptions/illegible writing | √ | √ | √ | √ | |||||||||||
Multi-tasking | √ | ||||||||||||||
Unfamiliar patient | √ | √ | |||||||||||||
Look-alike drug names/labelling | √ | √ | √ | √ | √ | ||||||||||
Syringe swap | √ | √ | |||||||||||||
Misidentification of drugs/ampoules | √ | √ | √ | ||||||||||||
Careless checking/not checking | √ | √ |