Table 3.

Summary of Study Strengths and Weaknesses

Author et al (Date)	Strengths	Weaknesses
Ali & Johnson (2017)	Member checking, triangulation, peer debrief Interview guides piloted before study Audio recording plus notes on body language/nonverbal cues Reflexive journaling Inclusion of subject matter experts for discussion on practice implications	No theoretical framework Sampling methods may increase potential for bias No mention of data saturation No examination of researcher’s role as source of potential bias
Ali & Watson (2018)	Member checking, triangulation, peer debrief Interview guides piloted before study Data saturation Audio recording plus notes on body language Reflexive diary Inclusion of subject matter experts for discussion on practice implications	No theoretical framework No examination of researcher’s role as source of potential bias
Alm-Pfrunder et al. (2018)	Justification for snowball sampling Examination of researcher’s role/potential bias due to work experience in ambulance setting	No theoretical framework No mention of data saturation No triangulation, member checking
Amoah et al. (2019)	Justification for purposive sampling Data saturation reached Reflection and comparisons throughout analysis phase Discuss researcher assumptions and setting/context Other researchers confirmed analysis	No theoretical framework No member checking, triangulation
Azize et al. (2018)	Factorial survey development explained in detail, following recommendations Power analysis determined sample size	Limited description of data analysis of open-ended questions
Badger et al. (2012)	Survey pilot-tested by random sample prior to use in study	Quantitative analysis utilized only descriptive statistics No member checking, triangulation or mention of data saturation in qualitative analysis
Balakrishnan et al. (2016)	Non-consecutive convenience sampling	Nurses aware of study, possible Hawthorne effect
Barnes et al. (2011)	Interpreters for qualitative interviews not the same as interpreters used in encounters with nurses Attrition similar across groups	No theoretical framework No member checking, triangulation Data saturation not mentioned
Beckstrand et al. (2010)	Randomized sample Expert information to modify survey questions Statement around Pretested questionnaire	92.6% female, 7.4% male 48% response rate Generalizability to only AACN members
Bramberg & Sandman (2013)	Attempt to avoid hierarchy or power dynamic in focus groups Care provider participation in later steps of data analysis	No theoretical framework Data saturation not mentioned No examination of researcher’s role as source of potential bias
Chae & Park (2019)	Data saturation Analysis methods driven by theory Detailed analysis description in three phases, preparation, organization and reporting Intercoder reliability calculated using Cohen’s kappa coefficient	No theoretical framework No member checking No examination of researcher’s role as source of potential bias
Clayton (2016)	Methods driven by theory Data saturation Exclusion of close associates of research Eliminated participants with close relationship with primary investigator	No theoretical framework Limited discussion of data analysis coding, categorizing process No examination of researcher’s role as source of potential bias
Coleman & Angosta, (2017)	Methods driven by theories Member checking Written audit trail of coding and thick data analysis Author journaling, bracketing throughout all phases Data saturation Researcher’s role as potential bias discussed	39/40 participants female Little detail of interview structure Unclear if multiple authors involved in data analysis
Diamond et al. (2012)	No significant difference in Spanish proficiency by sex, age, years of experience, or attending status	Testing based on self-reported language skills 30% overlap in respondents
Eklof et al. (2015)	Analysis driven by theory	No theoretical framework No mention of data saturation No triangulation, member checking Limited data analysis description
Fatahi (2010)	Discussion of validity through attempts to maintain similar environment for all focus groups Analysis completed by authors not part of focus groups, consensus reached for validity Triangulation	No theoretical framework No mention of data saturation No examination of researcher’s role as source of potential bias
Galinato et al. (2016)	Analysis driven by theories Detailed description of coding process, attempts to minimize bias and achieve confirmability Table of themes and subthemes	No theoretical framework No mention of data saturation No member checking Authors mention credibility, transferability, dependability met but no description of methods to do so
Granhagen Jungner et al. (2019)	Use of valid and reliable survey instrument Response rate 90%	No inclusion of data generated from open-ended questions
Hendson et al. (2015)	All involved in data analysis kept journal and took field notes Modification of semistructured guide based on findings in previous focus group Peer debrief, triangulation, member checking	No theoretical framework Saturation assessed after focus groups completed
Ian et al. (2017)	Double coding with qualitative researcher	No theoretical framework Limited description of sample No examination of researcher’s role as source of potential bias
Jackson & Mixer (2017)	Triangulation- data reflected back to participants during interview Researcher role and bias addressed through bracketing of biases in field notes throughout study	No mention of data saturation Limited description of coding process No baseline of language proficiency taken
Kallakorpi et al. (2018)	Member checking Observation, nursing documentation included in analysis	No theoretical framework No mention of data saturation No triangulation No examination of researcher’s role as source of potential bias
Kaur et al. (2019)	Sample size based on power analysis Inclusion of only oncology nurse data for more generalizable analysis	100% female respondents Unknown number of providers who received initial outreach email
Machado et al. (2013)	Description of content analysis and axial coding methods	Limited description of survey instrument Use of only descriptive statistics No comparison between nursing roles (assistant vs. tech vs. RN)
McCarthy et al. (2013)	Individual transcription of interviews to gain familiarity with data by each author Individual analysis prior to consensus	No theoretical framework No data saturation or member checking or mentioned Limited discussion of coding, analysis process No examination of researcher’s role as source of potential bias
Mottelson et al. (2018)	Pretesting of questionnaire two times to ensure validity 79% response rate All departments represented Management perspective	No description of qualitative analysis for open-ended question Use of charge nurse only, no bedside RN feedback
Patriksson et al. (2019)	Survey developed from focus group findings Inclusion of all neonatal departments	41% response rate
Plaza Del Pino (2013)	Theoretical framework Data saturation Rigorous translation/back translation Mention of reflection on researchers’ biases, potential influence	No mention of triangulation or member checking Limited detail regarding coding, grouping of codes to generate themes
Rifai et al. (2018)	Pilot interview to evaluate interview guide Triangulation through group discussion, consensus	No theoretical framework No mention of data saturation No member checking No examination of researcher’s role as source of potential bias
Rosendahl et al. (2016)	Detailed coding, analysis description	No theoretical framework No data saturation No member checking No examination of researcher’s role as a source of potential bias
Ross et al. (2016)	Questionnaire based on previous research and consultation with experts	Dichotomized questions, rather than Likert scale (confident / not confident; disruptive / not disruptive) 49% response rate urban site, 50% response rate rural site
Savio & George (2013)	Pilot study to assess feasibility Pre-test of tool	No data on percent respondent participation, only final N=100 88% female participants
Seale, Rivas, Al-Sarraj et al. (2013)	Three researchers independent coding, arrival at consensus Intercoder reliability kappa 0.84	No theoretical framework No examination of researchers’ roles as source of potential bias
Seale, Rivas, & Kelly (2013)	Three researchers independent coding, arrival at consensus Intercoder reliability kappa 0.84	No theoretical framework No examination of researchers’ roles as source of potential bias
Shuman et al. (2017)	Analysis guided by theories	Limited discussion of coding/analysis process No discussion regarding sample recruitment No description of patient languages
Silvera-Tawil et al. (2018)	Appropriate quantitative statistical analysis Detailed description of app informed by qualitative data	Very limited qualitative analysis description
Skoog et al. (2017)	Pilot interviews to test interview guide Data saturation Detailed coding with category, subcategory example	No theoretical framework No member checking
Squires et al. (2017)	Rationale for use of self-assessed language proficiency Use of patient preferred language rather than based on English skills	Unable to track telephone or ad hoc interpreter use No differentiation in Chinese languages
Squires et al. (2019)	Data saturation Detailed data analysis description Simultaneous coding with consensus to reduce bias	No theoretical framework No member checking
Suurmond et al. (2017)	Analysis guided by theories Detailed coding, data analysis description	No theoretical framework No mention of data saturation No member checking
Tay et al. (2012)	Data saturation Detailed data analysis description Triangulation	No theoretical framework No member checking Mention of reflective journaling for findings, but not to decrease bias, address researchers’ roles
Taylor & Alfred. (2010)	Theoretical Framework Random sampling of RNs Inclusion of management perspective Patient documents, translated materials included in analysis	No mention of data saturation Sample size chosen prior to interviews Appears only one author coded, no member checking or triangulation
Tuot et al. (2012)	65% RN participation rate, 67% physician participation rate	Limited in overlap of pre and post-test groups (30% RN, 25% physician)
Valizadeh et al. (2017)	Member checking Follow up interview for clarification Triangulation among researchers and with experienced qualitative researchers Data saturation reached	No theoretical framework No examination of researcher’s role as source of potential bias
Watt et al. (2018)	Memo writing to create audit trail Independent coding prior to group discussion for coding	No theoretical framework No mention data saturation Limited data analysis description No member checking
Watts et al. (2018)	Use of theoretical framework Triangulation, inter-coder agreement Attempts to avoid bias through deductive approach	No mention of data saturation No member checking
Whitman et al. (2010)	100% respondent rate of lead school RNs Comparisons - urban/rural, elementary/middle/high school	“Difficulty” analyzed as yes or no question with no scale
Willey et al. (2018)	Researcher independent of data conducted initial analysis Final data synthesis by all researchers	No theoretical framework No mention of data saturation No member checking No examination of researcher’s role as source of potential bias