Next Article in Journal
Predictors of Higher Quality of Systematic Reviews Addressing Nutrition and Cancer Prevention
Next Article in Special Issue
A Policy Framework for Producing Age-Friendly Communities from the Perspective of Production of Space
Previous Article in Journal
Changes in the Frequency of Moderate-to-Vigorous Physical Activity and Subsequent Risk of All-Cause and Cardiovascular Disease Mortality
Previous Article in Special Issue
Socioeconomic Classes among Oldest-Old Women in South Korea: A Latent Class Analysis
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

A Methodological Quality Evaluation of Meta-Analyses on Nursing Home Research: Overview and Suggestions for Future Directions

1
Graduate School of Education, Dongkuk University, Seoul 04620, Korea
2
College of Nursing, Ewha Womans University, Seoul 03760, Korea
3
School of Nursing, University of Texas at Austin, Austin, TX 78712, USA
4
College of Nursing, Catholic University of Pusan, Seoul 43241, Korea
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2022, 19(1), 505; https://doi.org/10.3390/ijerph19010505
Submission received: 18 November 2021 / Revised: 18 December 2021 / Accepted: 23 December 2021 / Published: 3 January 2022

Abstract

:
(1) Background: The nursing home (NH) research field lacks quality reporting about meta-analyses (MAs), and most gradings of MA evidence are biased on analyzing the effectiveness of independent variables in randomized control trials. (2) Objectives: This study aimed to perform a critical methodological review of MAs in the NH research field. (3) Methods: We searched the articles from four databases (PubMed, MEDLINE, CINAHL, and PsycINFO) until 15th January 2021. We reviewed a total of 41 published review articles in the NH research field. (4) Results: The studies primarily fell into the following categories: medicine (17/41), nursing (7/41), and psychiatry or psychology (6/41); 36.6% of the reviewed studies did not use any validated MA guidelines. The lowest correctly reported PRISMA 2000 guideline item was protocol and registration (14.6%), and more than 50% of articles did not report risk of bias. Moreover, 78.0% of studies did not describe missing reports of effect size formula. (5) Discussion: NH researchers must follow appropriate and updated guidelines for their MAs in order to provide validated reviews, as well as consider statistical issues such as the complexity of interventions, proper grouping, and scientific effect-size calculations to improve the quality of their study. Future quality review studies should investigate more diverse studies.

1. Introduction

The fast-growing elderly population is creating serious problems globally, and providing appropriate care for nursing home (NH) residents is a priority issue [1]. More than 2200 studies were searched in the main search engines regarding oral and dementia care, falls, fractures, cognitive functioning, pain, restraints, infections, nutrition, mortality rates, hospital admissions, psychiatric problems, and some organizational factors in numerous health-related disciplines reporting different levels of evidence. NHs have some unique characteristics to consider, such as (a) resident- and organizational-level factors, (b) lengthy resident stays in specific NHs, and (c) randomization, which may not be possible, as most residents are vulnerable either physically or cognitively. Researchers in many disciplines have mainly studied NHs to improve resident care, including oral care, falls, fractures, cognitive functioning, pain, restraints, infections, dementia care, nutrition, mortality rates, hospital admissions, psychiatric problems, and some organizational factors in numerous health-related disciplines reporting different levels of evidence; however, it is very challenging to identify or assess NH care quality. NH researchers have been synthesizing results to translate their findings into practice for several decades. In the nursing discipline, evidence-based nursing practices integrate theory and employ clinical decision-making, judgement, and scholarly knowledge to derive the most effective and useful evidence related to specific elements of practice [1]. Transitioning nursing research to practice should be cautiously implemented with valid research conclusions derived from multiple sources.
The term meta-analysis (MA) was introduced in 1976 and is defined as organized and validated statistical processes used to compile research findings to answer specific research questions. MAs make it possible to achieve a more precise intervention effect considering the size, heterogeneity, and quality of studies with the highest levels of evidence [2]. The resulting evidence can be applied to nursing practices or to develop clinical guidelines [3]. Applying MAs in NH research offers many advantages without requiring extra data collection; for example, MAs may improve the researcher’s ability to conduct hypothesis testing, thus identifying patterns and outcomes, and can compile results with stronger estimates [4]. A traditional MA with a randomized control trial (RCT) is performed by synthesizing and combining relevant research articles to achieve the best and highest levels of answers for a specific research question [5]; however, the synthesis of observational studies has also been performed over the last 10 years in NH research. Researchers estimate the mean or effect size of intervention by statistically combining more than two research studies on the same topic [6]. It is important to use current scientific systematic reviews in order to find gaps in specific research areas, apply research-based evidence or guidelines into nursing practices, and implement policy [7]. Scholars have performed NH research using diverse research designs. However, most gradings of MA evidence are biased toward figuring out the effectiveness of independent variables of RCTs, and should now extend to an evaluation of its suitability to study populations, settings, and designs [4,8]. An RCT is considered the highest level of evidence, but RCTs may have less external validity despite their good internal validity [4]. For example, residents’ characteristics, government policies, regulations, and the financial operation of each NH are very different based on different geographical areas or countries. Additionally, it may be hard to secure a suitable sample size and study period due to the season, outbreak of infectious diseases, or residents’ deaths when applying RCTs in NH research [4]. The reporting tools of MAs with RCT designs include Assessing the Methodological Quality of Systematic Reviews 2 (AMSTAR 2) and Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 (PRISMA 2020) [9], whereas MAs for observational studies use Meta-Analysis of Observational Studies in Epidemiology (MOOSE) [10]. No study has yet performed a methodological quality assessment of systematic reviews or MAs in NH research.
There are three types of MAs that can be used according to a study’s effect size and research design: (a) intervention MA, (b) measure-of-association MA, and (c) diagnostic-test-accuracy MA [8]. Intervention MA is the method used to achieve a conclusion about an intervention’s overall effects [11]. Measure-of-association MA refers to the method of synthesizing primary studies that scholars identified through correlation or structural-equation modeling between variables [12]. Diagnostic-test-accuracy MA refers to the method of synthesizing sensitivity and specificity from multiple studies to evaluate a diagnostic test’s performance [13]
Most review articles in the healthcare field have low [14] or moderate validity for use in evaluating methodological issues [15]. The quality of systematic reviews in 107 nursing journals was lower than that of orthodontic research or research about pain, possibly due to the scholars’ failures to adhere to the validated PRISMA instrument [16]. Concerns regarding systematic reviews’ scientific qualities have increased, especially in the nursing field [17]. Only 30 out of 107 Institute for Scientific Information (ISI) nursing journals required researchers to follow the PRISMA guideline for systematic reviews or MA articles [7]. Moreover, the registration of a systematic review is now required; however, there is no available information on how many journals require prior registration of their systematic review protocol on platforms such as the Prospective Register of Ongoing Systematic Review (PROSPERO). PROSPERO is a free, publicly accessible international registration database of prospectively registered systematic reviews in health and social care, operated through the University of York (Best Practice in Systematic Reviews: The Importance of Protocols and Registration The PLoS Medicine Editors).
The interpretation of MA results should be performed with close attention since the results may suffer from methodological study weakness [18]. The purpose of this study was to perform a critical methodological review of MAs in NH research.

2. Materials and Methods

This is a critical appraisal of MAs on NHs according to the PRISMA 2020 guideline’s 27 items.

2.1. Inclusion and Exclusion Criteria

Studies published from 1990 to 2020 that met the following inclusion criteria were selected. (1) We included all published articles in English about MAs in the NH research field. (2) We included any type of research design in any academic field beyond health services (nursing, medicine, dentistry, psychology, public health, rehabilitation, pharmacology, nutrition). (3) We also included studies with combined quantitative and qualitative designs. The exclusion criteria were as follows: (1) We excluded articles written in languages other than English. (2) We excluded articles based outside the NH setting (i.e., acute settings, long-term care hospitals, community-dwelling settings).

2.2. Information Sources and Search Strategy

We performed a systemic electronic search to evaluate published review articles in the NH research field, which we extracted from the four following scholarly health-related databases: PubMed, MEDLINE, CINAHL, and PsycINFO. The key words were “meta-analysis”, “systematic review”, “long term care”, and “nursing home”. We tailored the search strategy for each database. An example search for Pubmed is as follows: (“meta-analysis” [mh] OR “meta-analysis” [all] OR “meta-analyses” [all] OR “meta analysis” [all] OR “meta analyses” [all]) AND (“review” [pt] OR “systematic review” [all]) AND (“nursing home” [mh] OR “long term care” [all] OR “nursing home” [all]). We carried out the database search until 15 January 2021.

2.3. Study Selection and Data Extraction

We retrieved studies with the key words after the database search. Three reviewers independently screened the titles and abstracts of all articles from the initial search after excluding duplicity and non-NH settings. The reviewers obtained and examined the full texts of those articles passing the title and abstract screening. Three other reviewers resolved uncertainties or unclear methodologies through discussion. Two clinical experts in nursing and one expert in statistics coded and evaluated the clinical, methodological, and statistical parts together. Of the final included studies, we reviewed articles using a structured data-extraction strategy. Three team members independently extracted information from the included studies in a Word file, which included the title, first author, year of publication, study design, review protocol, synthesis method, and main findings. The kappa statistics value showed a high degree of agreement between the three reviewers in their decisions about the relevance of studies (kappa value = 0.89).

2.4. Planned Methods of Analysis

2.4.1. Reporting of Epidemiological and Descriptive Characteristics

We presented each item from the PRISMA checklist by either the ratio or percentage of how many of the 41 PRISMA articles were properly followed [9] (see Table 1).

2.4.2. Quality Assessment

We conducted the quality assessment (methodological systematic review) in compliance with the appropriate guideline. We evaluated a total of 41 articles on MAs in NHs by study design, the use of validated review tools, and kinds of tools. Secondly, we assessed whether the reviewed articles aligned with the 27-item PRISMA 2020 guideline (a validated checklist comprising of 27 items). The authors of this article checked each item using the Excel coding sheet and determined differences by agreement via regular e-mail and Zoom meetings. The PRISMA checklist did not fulfill some requirements. We also evaluated additional methodological and statistical issues based on the Meta-Analysis Reporting Standards (MARS) [6,58,59].

3. Results

Figure 1 presents the degree to which the reviewed articles adhered to the PRISMA checklist.
In this review, we screened a total of 1130 potentially relevant references identified through a search of bibliographic databases. After deleting duplicates and non-NH or non-long-term care facility settings (1057), the initial search yielded 73 publications. After screening abstracts, we excluded 32 references (30: systematic review only, 2: only qualitative studies). Finally, we reviewed and synthesized 41 publications.
Table 2 presents the summary of the reviewed articles. In total, 15 of 41 studies did not use any of the guidelines validated for MAs. The guidelines used in the remaining 26 studies were as follows: 17 studies used only the PRISMA guideline; 3 studies used only the MOOSE guideline; 3 studies used both the PRISMA guideline and Cochrane handbook simultaneously; 3 studies used both the PRISMA and MOOSE guidelines simultaneously.
Scholars mainly studied MAs in the NH research in the following areas: medicine (17/41 of reviewed studies) [20,25,26,28,36,38,39,40,47,48,49,50,51,52,54,57,60], nursing (7/41) [24,31,32,33,34,35,56], psychiatry or psychology (6/41) [22,30,44,45,55,61], public health (4/41) [21,27,37,46], and pharmacology (3/41) [23,42,53], followed by the areas of rehabilitation (1) [41], nutrition (1) [29], dentistry (1) [43], and nursing and dentistry (1) [19]. In the reviewed articles, some studies (12/41) examined the physical issues NH residents face, including falls, exercise, or rehabilitation issues. A few studies were conducted on NH placement, admission or mortality, death, nutrition and tube feeding, depression, oral health, cognitive function, pain management, infection, depression, or fragility. Only one study focused on the organizational characteristics of NH ownership. Most reviewed articles were classified as intervention MAs (21/41), measure-of-association MAs (21/41), and diagnostic-test-accuracy MAs (1/41). Measure-of-association represented various coefficients (including bivariate correlation coefficients and regression coefficients) that measured the strength and direction of relationships between variables [62]. These intensity or association measures could be explained in several ways, depending on the analysis. Measure-of-association in MAs assessed studies using methods such as correlation, regression, and structural-equation modeling between variables [12]. Future research should include more measure-of-association MAs in NH research. The Cochrane handbook emphasizes the intervention complexity or logic model, wherein various research types must be well classified and applied accordingly.
Among the PRISMA items, only six studies [19,21,22,23,24,25] correctly reported the item of “protocol and registration” (i.e., indicating whether a review protocol existed, if and where it can be accessed and if it was available, and providing registration information including the registration number). Only 21% of articles in the medical field reported a protocol [63]. Moreover, more than 50% of reviewed articles did not address the “risk of bias within studies” item, which was associated with former studies and was essential in calculating effect size [18,64].
Additionally, the majority of reviewed studies (32/41) did not offer an effect size variance formula [58], whereas high-impact factor journals effectively covered effect size calculations and statistical-analysis issues. The effect size variance formula is important as it tells us about normality and homogeneity assumptions [65]. Thus, concrete information on effect size computation should be reported in MAs [6,58]. Researchers used H (1/41), Q (18/41), and I2 inconsistency (29/41) statistics for heterogeneity tests. Heterogeneity means the degree of difference in the results of each single research finding [66]. Through MAs, scholars calculate the heterogeneity index so they can understand the primary factors that impact individual studies’ effect sizes [67].

4. Discussion

This is the first study that scientifically assesses the methodological quality of systematic reviews used for MA studies in NH research. The scientific quality evaluation of MA studies on NHs provides reliable guidance on nursing policies and practices that improve outcomes for residents based on assessments of the quality of evidence from prior MA studies. The major benefits of MA are that it has strong statistical power with effect size and offers conclusions that individual studies often cannot reach [26]. The effect size variance formula is important as it tells us about normality and homogeneity assumptions [65]. Thus, concrete information on effect size computation should be reported in MAs [6,58]. Scholars should investigate assumptions and report scientific research findings in a scientific way to ground more valid, superior, evidence-based nursing practices for use in NH research. Scholars have studied NH research for several decades, and scientific synthesis is required to address current nursing issues, usually focusing on quality-of-care issues including pressure ulcers, falls, activities of daily living, and others.
The studies on NH that have been synthesized include various study designs, such as RCTs and observational, prevalence, diagnostic test accuracy, and association studies. Scholars must consider the most appropriate method for exploring validated reviews in NH research. Usually, NH research is performed using an observational design since researchers can investigate the process of care and reasons for missed care [19]. The JBI tool includes experimental and non-experimental designs of methodological reviews, but other critical appraisal tools are not often used due to the permission requirements [68]. Scholars mainly use PRISMA for reviews that assess the effects of interventions, prognoses, diagnoses, and prevalence [7]. However, some of the reviewed studies used PRISMA (which should not be used for observational studies) despite not having RCTs [20,27,28,29]. Unintentional inadvertence may occur when reporting reviews without adhering to valid review guidelines. For example, the APA MARS is a good guideline for association and relational MA in addition to non-RCT systematic reviews and MAs in NH fields. The APA Working Group on Journal Article Reporting Standards developed the APA MARS in 2008 after the group synthesized the Quality of Reporting of MA statement, PRISMA, MOOSE, and Potsdam Consultation on MA [58]. The Newcastle–Ottawa scale has also been used when reviewing observational studies, including case–control, prospective, and cohort studies [69]. This scale has three areas of focus (participants of study, comparison between case/controls, and evaluation of outcomes) linked with the quality concept, and it is recommended to have at least two reviewers, as the review involves quite subjective characteristics [69]. The MOOSE is a reporting guide for MAs on observational studies of epidemiology, which improves the reporting on MAs of observational studies [10]. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) initiative developed recommendations on what should be included in an accurate and complete report of an observational study. STROBE was developed to improve the reporting quality of observational studies [70]. Regarding quality assessment tools, one of the examined studies used Consolidated Standards of Reporting Trials (CONSORT) [4] to measure the methodological quality of individual studies included in the MA research. However, CONSORT is a set of recommendations related to how to report on individual studies in randomized trials, and is not actually a quality assessment tool to establish internal validity in MAs. Even though meta research is considered the highest scientific level of evidence, many potential sources of bias exist [71] including selection, performance, attrition, and detection bias, which affect internal validity. Therefore, scholars must use valid and standardized methodological quality assessment tools for the individual studies included in MA research to ensure the quality of synthesized results.
The ROB 2 is the gold standard used to evaluate the quality of RCT biases [72]. Most of the reviewed articles (11/41) [21,22,23,24,26,28,32,35,53,56,61] used the ROB, but not the ROB 2. The ROB 2 is a reorganized form of the Cochrane ROB tool, developed by the same team [73]. The tool allows researchers to simply decide if a bias exists in the reviewed research, and can be used to evaluate bias in particular result findings beyond the RCT design [73]. More unreliably, one paper used the ROB but did not use an RCT [28]. Effect size refers to the numerical index of findings and is regarded as an outcome variable in MA research [8]. Effect size usually consists of d (odds ratio) for experimental designs and R for correlational studies [8]. A specific process with calculations should be provided when reporting on effect size. Although most reviewed articles are intervention MA, the use of diagnostic MA with test accuracy is increasing in healthcare research [8]. One of the reviewed articles [30] reported on the proportion of residents with depression, which is categorized as diagnostic MA. We suggest performing diagnostic MA using the appropriate standard in order to have accurate data on the prevalence or incidence of specific disease, infectious disease, or the progress of dementia. Based on this, MA results can be applied for developing sensitive instruments for use in NH populations’ [31].
The intervention complexity of studies (intervention number and the interaction among interventions in a system’s structure) should be considered in the future, as a mixture of interventions should be applied to NH residents with a more accurate intervention estimation [74]. The interventions that were conducted to improve residents’ physical, psychological, and cognitive functions included fall prevention, nutrition, oral care, ambulant, feeding, exercise, and so on. Scholars should clearly define the research objectives, population to be studied, and scope of treatments when performing MAs to answer the research questions [74]. NHs have some unique characteristics to consider, such as (a) resident- and organizational-level factors, (b) lengthy resident stays in specific NHs, and (c) randomization. NH researchers have been synthesizing results to translate their findings into practice for several decades. In the nursing discipline, evidence-based nursing practices integrate theory and include clinical decision-making, judgement, and scholarly knowledge to achieve the most effective and useful evidence for specific elements of practice [1]. Researchers conduct and share research results on nursing practices, education, and administration. Transitioning nursing research to practice should be cautiously implemented with valid research conclusions derived from multiple sources.
Lastly, the appropriate registration of reporting guidelines before publication should be performed to improve the methodological quality using PROSPERO. Protocol registration is not a mandatory requirement in MAs, but it should be emphasized to decrease duplication among studies, and it is also supported by the National Institute for Health Research (NIHR) and PROSPERO [63,75,76,77].

Limitations

This study has some limitations, in that it did not have a PROSPERO registration number and only included articles published in English. Future studies should include more diverse research around the world to represent global citizens.

5. Conclusions and Implication

MA is one of the best scientific methods for dealing with big data. MA can be used to integrate large data into NH research, contributing to the open-science movement in research [78]. In the era of evidence-based nursing practices, NHs should prioritize deriving accurate and valid judgements for nursing practices. Thus, choosing and applying the appropriate and most conforming review tool is an important issue when reviewing articles. Researchers should use appropriate, updated quality assessment tools reflecting the study’s research design and objectives, and must consider the complexity of interventions, proper grouping, and scientific effect size calculations.

Author Contributions

Conceptualization: J.-H.S. and I.-S.S.; writing the original draft, reviewing, and editing: J.-H.S.; supervision: J.-H.S.; funding acquisition: J.-H.S.; methodology: I.-S.S.; formal analysis: I.-S.S., D.-E.J. and J.L.; investigation: D.-E.J. and J.L.; data curation: D.-E.J. and J.L.; and methodology writing: D.-E.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Research Foundation of Korea (NRF), 2021R1A2C2007104.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Conflicts of Interest

The authors have no conflict of interest to report.

References

  1. Wakibi, S.; Ferguson, L.; Berry, L.; Leidl, D.; Belton, S. Teaching evidence-based nursing practice: A systematic review and convergent qualitative synthesis. J. Prof. Nurs. 2020, 37, 135–148. [Google Scholar] [CrossRef]
  2. Mudge, D.W.; Webster, A.C.; Johnson, D.W. Pro: Meta-analysis: The case for. Nephrol. Dial. Transpl. 2016, 31, 875–880. [Google Scholar] [CrossRef] [Green Version]
  3. Song, Y.; Gang, M.; Kim, S.-A.; Shin, I.-S. Review of Meta-analysis Research on Exercise in South Korea. J. Korean Acad. Nurs. 2014, 44, 459–470. [Google Scholar] [CrossRef]
  4. Frieden, T.R. Evidence for Health Decision Making—Beyond Randomized, Controlled Trials. N. Engl. J. Med. 2017, 377, 465–475. [Google Scholar] [CrossRef]
  5. Petitti, D.B. Meta-Analysis, Decision Analysis, and Cost-Effectiveness Analysis: Methods for Quantitative Synthesis in Medicine; Oxford University Press: Oxford, UK, 1994. [Google Scholar]
  6. Pigott, T.D.; Polanin, J.R. Methodological Guidance Paper: High-Quality Meta-Analysis in a Systematic Review. Rev. Educ. Res. 2020, 90, 24–46. [Google Scholar] [CrossRef] [Green Version]
  7. Tam, W.W.S.; Lo, K.K.H.; Khalechelvam, P. Endorsement of PRISMA statement and quality of systematic reviews and meta-analyses published in nursing journals: A cross-sectional study. BMJ Open 2017, 7, e013905. [Google Scholar] [CrossRef] [Green Version]
  8. Shin, I.-S. Recent Research Trends in Meta-analysis. Asian Nurs. Res. 2017, 11, 79–83. [Google Scholar] [CrossRef] [Green Version]
  9. Transparent Reporting of Systematic Reviews and Meta-Analyses. Prisma 2020 checklist. Available online: http://www.prisma-statement.org/PRISMAStatement/Checklist (accessed on 3 October 2021).
  10. Stroup, D.F.; Berlin, J.A.; Morton, S.C.; Olkin, I.; Williamson, G.D.; Rennie, D.; Moher, D.; Becker, B.J.; Sipe, T.A.; Thacker, S.B.; et al. Meta-analysis of observational studies in epidemiology: A proposal for reporting. JAMA 2000, 283, 2008–2012. [Google Scholar] [CrossRef] [PubMed]
  11. Noyes, J.; Booth, A.; Moore, G.; Flemming, K.; Tunçalp, Ö.; Shakibazadeh, E. Synthesising quantitative and qualitative evidence to inform guidelines on complex interventions: Clarifying the purposes, designs and outlining some methods. BMJ Glob. Health 2019, 4 (Suppl. 1), e000893. [Google Scholar] [CrossRef]
  12. Sandhu, J.K.; Wu, K.K.; Bui, T.-L.; Armstrong, A.W. Association between atopic dermatitis and suicidality: A systematic review and meta-analysis. JAMA Dermatol. 2019, 155, 178–187. [Google Scholar] [CrossRef] [PubMed]
  13. Freeman, S.C.; Kerby, C.R.; Patel, A.; Cooper, N.J.; Quinn, T.; Sutton, A.J. Development of an interactive web-based tool to conduct and interrogate meta-analysis of diagnostic test accuracy studies: MetaDTA. BMC Med. Res. Methodol. 2019, 19, 81. [Google Scholar] [CrossRef]
  14. Sequeira-Byron, P.; Fedorowicz, Z.; Jagannath, V.A.; Sharif, M.O. An AMSTAR assessment of the methodological quality of systematic reviews of oral healthcare interventions published in the Journal of Applied Oral Science (JAOS). J. Appl. Oral Sci. 2011, 19, 440–447. [Google Scholar] [CrossRef] [Green Version]
  15. Ma, B.; Guo, J.; Qi, G.; Li, H.; Peng, J.; Zhang, Y.; Ding, Y.; Yang, K. Epidemiology, Quality and Reporting Characteristics of Systematic Reviews of Traditional Chinese Medicine Interventions Published in Chinese Journals. PLoS ONE 2011, 6, e20185. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Tam, W.W.S.; Lo, K.K.H.; Khalechelvam, P.; Seah, J.; Goh, Y.-S.S. Is the information of systematic reviews published in nursing journals up-to-date? A cross-sectional study. BMC Med. Res. Methodol. 2017, 17, 151. [Google Scholar] [CrossRef] [Green Version]
  17. Xiong, Y. Quality appraisal of domestic reports of systematic reviews. J. Nurs. Sci. 2010, 25, 80–82. [Google Scholar]
  18. Tan, W.K.; Wigley, J.; Shantikumar, S. The reporting quality of systematic reviews and meta-analyses in vascular surgery needs improvement: A systematic review. Int. J. Surg. 2014, 12, 1262–1265. [Google Scholar] [CrossRef] [Green Version]
  19. Hoben, M.; Clarke, A.; Huynh, K.T.; Kobagi, N.; Kent, A.; Hu, H.; Pereira, R.A.; Xiong, T.; Yu, K.; Xiang, H.; et al. Barriers and facilitators in providing oral care to nursing home residents, from the perspective of care aides: A systematic review and meta-analysis. Int. J. Nurs. Stud. 2017, 73, 34–51. [Google Scholar] [CrossRef]
  20. Veronese, N.; Cereda, E.; Solmi, M.; Fowler, S.A.; Manzato, E.; Maggi, S.; Manu, P.; Abe, E.; Hayashi, K.; Allard, J.P.; et al. Inverse relationship between body mass index and mortality in older nursing home residents: A meta-analysis of 19,538 elderly subjects. Obes. Rev. 2015, 16, 1001–1015. [Google Scholar] [CrossRef] [Green Version]
  21. Brugnolli, A.; Canzan, F.; Mortari, L.; Saiani, L.; Ambrosi, E.; DeBiasi, M. The Effectiveness of Educational Training or Multicomponent Programs to Prevent the Use of Physical Restraints in Nursing Home Settings: A Systematic Review and Meta-Analysis of Experimental Studies. Int. J. Environ. Res. Public Health 2020, 17, 6738. [Google Scholar] [CrossRef] [PubMed]
  22. Fornaro, M.; Solmi, M.; Stubbs, B.; Veronese, N.; Monaco, F.; Novello, S.; Fusco, A.; Anastasia, A.; De Berardis, D.; Carvalho, A.F.; et al. Prevalence and correlates of major depressive disorder, bipolar disorder and schizophrenia among nursing home residents without dementia: Systematic review and meta-analysis. Br. J. Psychiatry 2019, 216, 6–15. [Google Scholar] [CrossRef] [Green Version]
  23. Kua, C.-H.; Mak, V.S.; Lee, S.W.H. Health Outcomes of Deprescribing Interventions Among Older Residents in Nursing Homes: A Systematic Review and Meta-analysis. J. Am. Med. Dir. Assoc. 2018, 20, 362–372.e11. [Google Scholar] [CrossRef]
  24. Vlaeyen, E.; Coussement, J.; Leysens, G.; Van Der Elst, E.; Delbaere, K.; Cambier, D.; Denhaerynck, K.; Goemaere, S.; Wertelaers, A.; Dobbels, F.; et al. Characteristics and Effectiveness of Fall Prevention Programs in Nursing Homes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. J. Am. Geriatr. Soc. 2015, 63, 211–221. [Google Scholar] [CrossRef]
  25. Zhang, X.; Wang, C.; Dou, Q.; Zhang, W.; Yang, Y.; Xie, X. Sarcopenia as a predictor of all-cause mortality among older nursing home residents: A systematic review and meta-analysis. BMJ Open 2018, 8, e021252. [Google Scholar] [CrossRef] [Green Version]
  26. Silva-Fernández, L.; Carmona, L. Meta-analysis in the era of big data. Clin. Rheumatol. 2019, 38, 2027–2028. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Costa, V.; Earle, C.C.; Esplen, M.J.; Fowler, R.; Goldman, R.; Grossman, D.; Levin, L.; Manuel, D.G.; Sharkey, S.; Tanuseputro, P.; et al. The determinants of home and nursing home death: A systematic review and meta-analysis. BMC Palliat. Care 2016, 15, 8. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Lan, S.-H.; Lu, L.-C.; Yen, Y.-Y.; Hsieh, Y.-P.; Chen, J.-C.; Wu, W.J.; Lin, L.-Y. Tube feeding among elder in long-term care facilities: A systematic review and meta-analysis. J. Nutr. Health Aging 2016, 21, 31–37. [Google Scholar] [CrossRef] [PubMed]
  29. Cereda, E.; Pedrolli, C.; Klersy, C.; Bonardi, C.; Quarleri, L.; Cappello, S.; Turri, A.; Rondanelli, M.; Caccialanza, R. Nutritional status in older persons according to healthcare setting: A systematic review and meta-analysis of prevalence data using MNA. Clin. Nutr. 2016, 35, 1282–1290. [Google Scholar] [CrossRef]
  30. Mitchell, A.J.; Kakkadasam, V. Ability of nurses to identify depression in primary care, secondary care and nursing homes—A meta-analysis of routine clinical accuracy. Int. J. Nurs. Stud. 2011, 48, 359–368. [Google Scholar] [CrossRef]
  31. Gaugler, J.E.; Duval, S.; Anderson, K.A.; Kane, R.L. Predicting nursing home admission in the U.S: A meta-analysis. BMC Geriatr. 2007, 7, 13. [Google Scholar] [CrossRef] [Green Version]
  32. Lee, S.H.; Kim, H.S. Exercise Interventions for Preventing Falls among Older People in Care Facilities: A Meta-Analysis. Worldviews Evid. Based Nurs. 2016, 14, 74–80. [Google Scholar] [CrossRef]
  33. Li, H.-C.; Wang, H.-H.; Chou, F.-H.; Chen, K.-M. The Effect of Music Therapy on Cognitive Functioning Among Older Adults: A Systematic Review and Meta-Analysis. J. Am. Med. Dir. Assoc. 2015, 16, 71–77. [Google Scholar] [CrossRef] [PubMed]
  34. Knopp-Sihota, J.A.; Patel, P.; Estabrooks, C.A. Interventions for the Treatment of Pain in Nursing Home Residents: A Systematic Review and Meta-Analysis. J. Am. Med. Dir. Assoc. 2016, 17, 1163.e19–1163.e28. [Google Scholar] [CrossRef] [PubMed]
  35. Aliyu, S.; Smaldone, A.; Larson, E. Prevalence of multidrug-resistant gram-negative bacteria among nursing home residents: A systematic review and meta-analysis. Am. J. Infect. Control 2017, 45, 512–518. [Google Scholar] [CrossRef]
  36. Deandrea, S.; Bravi, F.; Turati, F.; Lucenteforte, E.; La Vecchia, C.; Negri, E. Risk factors for falls in older people in nursing homes and hospitals. A systematic review and meta-analysis. Arch. Gerontol. Geriatr. 2013, 56, 407–415. [Google Scholar] [CrossRef] [PubMed]
  37. Petrignani, M.; van Beek, J.; Borsboom, G.; Richardus, J.; Koopmans, M. Norovirus introduction routes into nursing homes and risk factors for spread: A systematic review and meta-analysis of observational studies. J. Hosp. Infect. 2015, 89, 163–178. [Google Scholar] [CrossRef]
  38. Comondore, V.R.; Devereaux, P.; Zhou, Q.; Stone, S.B.; Busse, J.; Ravindran, N.C.; Burns, K.E.; Haines, T.; Stringer, B.; Cook, D.J.; et al. Quality of care in for-profit and not-for-profit nursing homes: Systematic review and meta-analysis. BMJ 2009, 339, b2732. [Google Scholar] [CrossRef] [Green Version]
  39. Kojima, G. Prevalence of Frailty in Nursing Homes: A Systematic Review and Meta-Analysis. J. Am. Med. Dir. Assoc. 2015, 16, 940–945. [Google Scholar] [CrossRef]
  40. Kojima, G. Frailty as a Predictor of Nursing Home Placement Among Community-Dwelling Older Adults: A Systematic Review and Meta-analysis. J. Geriatr. Phys. Ther. 2018, 41, 42–48. [Google Scholar] [CrossRef] [PubMed]
  41. Crocker, T.; Young, J.; Forster, A.; Brown, L.; Ozer, S.; Greenwood, D.C. The effect of physical rehabilitation on activities of daily living in older residents of long-term care facilities: Systematic review with meta-analysis. Age Ageing 2013, 42, 682–688. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Wallerstedt, S.M.; Kindblom, J.; Nylén, K.; Samuelsson, O.; Strandell, A. Medication reviews for nursing home residents to reduce mortality and hospitalization: Systematic review and meta-analysis. Br. J. Clin. Pharmacol. 2014, 78, 488–497. [Google Scholar] [CrossRef] [PubMed]
  43. Sjögren, P.; Wårdh, I.; Zimmerman, M.; Almståhl, A.; Wikström, M. Oral Care and Mortality in Older Adults with Pneumonia in Hospitals or Nursing Homes: Systematic Review and Meta-Analysis. J. Am. Geriatr. Soc. 2016, 64, 2109–2115. [Google Scholar] [CrossRef]
  44. Robertson, S.; Cooper, C.; Hoe, J.; Hamilton, O.; Stringer, A.; Livingston, G. Proxy rated quality of life of care home residents with dementia: A systematic review. Int. Psychogeriatr. 2017, 29, 569–581. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Toot, S.; Swinson, T.; Devine, M.; Challis, D.; Orrell, M. Causes of nursing home placement for older people with dementia: A systematic review and meta-analysis. Int. Psychogeriatr. 2016, 29, 195–208. [Google Scholar] [CrossRef] [Green Version]
  46. Jutkowitz, E.; Brasure, M.; Fuchs, E.; Shippee, T.; Kane, R.A.; Fink, H.A.; Butler, M.; Sylvanus, T.; Kane, R.L. Care-Delivery Interventions to Manage Agitation and Aggression in Dementia Nursing Home and Assisted Living Residents: A Systematic Review and Meta-analysis. J. Am. Geriatr. Soc. 2016, 64, 477–488. [Google Scholar] [CrossRef] [PubMed]
  47. Smith, T.O.; Purdy, R.; Latham, S.K.; Kingsbury, S.R.; Mulley, G.; Conaghan, P. The prevalence, impact and management of musculoskeletal disorders in older people living in care homes: A systematic review. Rheumatol. Int. 2015, 36, 55–64. [Google Scholar] [CrossRef] [Green Version]
  48. Kuys, S.S.; Peel, N.M.; Klein, K.; Slater, A.; Hubbard, R. Gait Speed in Ambulant Older People in Long Term Care: A Systematic Review and Meta-Analysis. J. Am. Med. Dir. Assoc. 2014, 15, 194–200. [Google Scholar] [CrossRef] [PubMed]
  49. Hedrick, S.C.; Koepsell, T.D.; Inui, T. Meta-analysis of Home-Care Effects on Mortality and Nursing-Home Placement. Med. Care 1989, 27, 1015–1026. [Google Scholar] [CrossRef]
  50. Gonella, S.; Basso, I.; Dimonte, V.; Martin, B.; Berchialla, P.; Campagna, S.; Di Giulio, P. Association Between End-of-Life Conversations in Nursing Homes and End-of-Life Care Outcomes: A Systematic Review and Meta-analysis. J. Am. Med. Dir. Assoc. 2018, 20, 249–261. [Google Scholar] [CrossRef] [PubMed]
  51. Gulka, H.J.; Patel, V.; Arora, T.; McArthur, C.; Iaboni, A. Efficacy and Generalizability of Falls Prevention Interventions in Nursing Homes: A Systematic Review and Meta-analysis. J. Am. Med. Dir. Assoc. 2020, 21, 1024–1035.e4. [Google Scholar] [CrossRef] [PubMed]
  52. Zhang, X.; Dou, Q.; Zhang, W.; Wang, C.; Xie, X.; Yang, Y.; Zeng, Y. Frailty as a Predictor of All-Cause Mortality Among Older Nursing Home Residents: A Systematic Review and Meta-analysis. J. Am. Med. Dir. Assoc. 2019, 20, 657–663.e4. [Google Scholar] [CrossRef]
  53. Lee, S.W.H.; Mak, V.S.L.; Tang, Y.W. Pharmacist services in nursing homes: A systematic review and meta-analysis. Br. J. Clin. Pharmacol. 2019, 85, 2668–2688. [Google Scholar] [CrossRef] [PubMed]
  54. Shen, Y.; Chen, J.; Chen, X.; Hou, L.; Lin, X.; Yang, M. Prevalence and Associated Factors of Sarcopenia in Nursing Home Residents: A Systematic Review and Meta-analysis. J. Am. Med. Dir. Assoc. 2019, 20, 5–13. [Google Scholar] [CrossRef]
  55. Prins, A.J.; Scherder, E.J.A.; Van Straten, A.; Zwaagstra, Y.; Milders, M.V. Sensory Stimulation for Nursing-Home Residents: Systematic Review and Meta-Analysis of Its Effects on Sleep Quality and Rest-Activity Rhythm in Dementia. Dement. Geriatr. Cogn. Disord. 2020, 49, 219–234. [Google Scholar] [CrossRef]
  56. Cao, P.-Y.; Zhao, Q.-H.; Xiao, M.-Z.; Kong, L.-N.; Xiao, L. The effectiveness of exercise for fall prevention in nursing home residents: A systematic review meta-analysis. J. Adv. Nurs. 2018, 74, 2511–2522. [Google Scholar] [CrossRef]
  57. Lan, S.-H.; Lu, L.-C.; Lan, S.-J.; Chen, J.-C.; Wu, W.-J.; Chang, S.-P.; Lin, L.-Y. Educational intervention on physical restraint use in long-term care facilities—Systematic review and meta-analysis. Kaohsiung J. Med. Sci. 2017, 33, 411–421. [Google Scholar] [CrossRef]
  58. APA Publications and Communications Board Working Group on Journal Article Reporting Standards. Reporting standards for research in psychology: Why do we need them? What might they be? Am. Psychol. 2008, 63, 839–851. [Google Scholar] [CrossRef]
  59. Liew, N.Y.; Chong, Y.Y.; Yeow, S.H.; Kua, K.P.; San Saw, P.; Lee SW, H. Prevalence of potentially inappropriate medications among geriatric residents in nursing care homes in Malaysia: A cross-sectional study. Int. J. Clin. Pharm. 2019, 41, 895–902. [Google Scholar] [CrossRef]
  60. Sawka, A.M.; Boulos, P.; Beattie, K.; Papaioannou, A.; Gafni, A.; Cranney, A.; Hanley, D.A.; Adachi, J.D.; Papadimitropoulos, E.; Thabane, L. Hip protectors decrease hip fracture risk in elderly nursing home residents: A Bayesian meta-analysis. J. Clin. Epidemiol. 2007, 60, 336–344. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  61. Folkerts, A.-K.; Roheger, M.; Franklin, J.; Middelstädt, J.; Kalbe, E. Cognitive interventions in patients with dementia living in long-term care facilities: Systematic review and meta-analysis. Arch. Gerontol. Geriatr. 2017, 73, 204–221. [Google Scholar] [CrossRef]
  62. Tamarelle, J.; Thiébaut, A.; de Barbeyrac, B.; Bébéar, C.; Ravel, J.; Delarocque-Astagneau, E. The vaginal microbiota and its association with human papillomavirus, Chlamydia trachomatis, Neisseria gonorrhoeae and Mycoplasma genitalium infections: A systematic review and meta-analysis. Clin. Microbiol. Infect. 2018, 25, 35–47. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Tawfik, G.M.; Giang, H.T.N.; Ghozy, S.; Altibi, A.M.; Kandil, H.; Le, H.-H.; Eid, P.S.; Radwan, I.; Makram, O.M.; Hien, T.T.T.; et al. Protocol registration issues of systematic review and meta-analysis studies: A survey of global researchers. BMC Med. Res. Methodol. 2020, 20, 213. [Google Scholar] [CrossRef]
  64. Shantikumar, S.; Wigley, J.E.M.; Hameed, W.; Handa, A. A survey of instructions to authors in surgical journals on reporting by CONSORT and PRISMA. Ann. R. Coll. Surg. Engl. 2012, 94, 468–471. [Google Scholar] [CrossRef]
  65. Hedges, L.; Olkin, I. Statistical Methods for Meta-Analysis; Academic Press: Cambridge, MA, USA, 1985. [Google Scholar]
  66. Sharps, P.W.; Campbell, J.; Baty, M.L.; Walker, K.S.; Bair-Merritt, M.H. Current evidence on perinatal home visiting and intimate partner violence. J. Obstet. Gynecol. Neonatal Nurs. 2008, 37, 480–491. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  67. Bowblis, J.R.; Roberts, A.R. Cost-Effective Adjustments to Nursing Home Staffing to Improve Quality. Med. Care Res. Rev. 2018, 77, 274–284. [Google Scholar] [CrossRef]
  68. Vardell, E.; Malloy, M. Joanna Briggs Institute: An Evidence-Based Practice Database. Med. Ref. Serv. Q. 2013, 32, 434–442. [Google Scholar] [CrossRef]
  69. Luchini, C.; Stubbs, B.; Solmi, M.; Veronese, N. Assessing the quality of studies in meta-analyses: Advantages and limitations of the Newcastle Ottawa Scale. World J. Meta-Anal. 2017, 5, 80–84. [Google Scholar] [CrossRef]
  70. Vandenbroucke, J.P.; von Elm, E.; Altman, D.G.; Gøtzsche, P.C.; Mulrow, C.D.; Pocock, S.J.; Poole, C.; Schlesselman, J.J.; Egger, M.; STROBE Initiative. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and elaboration. Int. J. Surg. 2014, 12, 1500–1524. [Google Scholar] [CrossRef] [Green Version]
  71. Murad, M.H.; Montori, V.M.; Ioannidis, J.P.; Jaeschke, R.; Devereaux, P.J.; Prasad, K.; Neumann, I.; Carrasco-Labra, A.; Agoritsas, T.; Hatala, R.; et al. How to read a systematic review and meta-analysis and apply the results to patient care: Users’ guides to the medical literature. JAMA 2014, 312, 171–179. [Google Scholar] [CrossRef]
  72. Luchini, C.; Veronese, N.; Nottegar, A.; Shin, J.I.; Gentile, G.; Granziol, U.; Soysal, P.; Alexinschi, O.; Smith, L.; Solmi, M. Assessing the quality of studies in meta-research: Review/guidelines on the most important quality assessment tools. Pharm. Stat. 2020, 20, 185–195. [Google Scholar] [CrossRef]
  73. McGuinness, L.A.; Higgins, J.P.T. Risk-of-bias VISualization (robvis): An R package and Shiny web app for visualizing risk-of-bias assessments. Res. Synth. Methods 2021, 12, 55–61. [Google Scholar] [CrossRef]
  74. Thomas, J.; Petticrew, M.; Noyes, J.; Chandler, J.; Rehfuess, E.; Tugwell, P.; Welch, V.A. Chapter 17: Intervention complexity. In Cochrane Handbook for Systematic Reviews of Interventions (Version 6.1); Higgins, J.P.T., Thomas, J., Chandler, J., Cumpston, M., Li, T., Page, M.J., Welch, V.A., Eds.; John Wiley & Sons: Hoboken, NJ, USA, 2020. [Google Scholar]
  75. Booth, A.; Clarke, M.; Ghersi, D.; Moher, D.; Petticrew, M.; Stewart, L. An international registry of systematic-review protocols. Lancet 2011, 377, 108–109. [Google Scholar] [CrossRef]
  76. National Institute for Health Research. PROSPERO Is Fast-Tracking Registration of Protocols Related to COVID-19. Available online: https://www.crd.york.ac.uk/prospero/ (accessed on 3 August 2021).
  77. Catalá-López, F.; Alonso-Arroyo, A.; Page, M.; Hutton, B.; Ridao, M.; Tabares-Seisdedos, R.; Aleixandre-Benavent, R.; Moher, D. Reporting guidelines for health research: Protocol for a cross-sectional analysis of the Equator Network Library. BMJ Open 2019, 9, e022769. [Google Scholar] [CrossRef] [PubMed]
  78. Gurevitch, J.; Koricheva, J.; Nakagawa, S.; Stewart, G. Meta-analysis and the science of research synthesis. Nature 2018, 555, 175–182. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Flow diagram of the review selection on nursing home research.
Figure 1. Flow diagram of the review selection on nursing home research.
Ijerph 19 00505 g001
Table 1. PRISMA Checklist.
Table 1. PRISMA Checklist.
PRISMA Item Number
1st Author, YearTitle 1Structured SummaryRationaleObjectivesProtocol and RegistrationEligibility CriteriaInformation SourcesSearchStudy SelectionData Collection ProcessData ItemsRisk of Bias in Individual StudiesSummary MeasuresSynthesis of ResultsRisk of Bias Across StudiesAdditional AnalysesStudy SelectionStudy CharacteristicsResults of Individual StudiesResults of Individual StudiesSynthesis of ResultsRisk of Bias Across StudiesAdditional AnalysisSummary of EvidenceLimitationsConclusionsFunding
Hoben et al., 2017
[19]
OOOOOOOOOOOOOOOOOOOOOOOOOOO
Veronese et al., 2015
[20]
OOOOOOOXOOXXOOOOOOOOXOOOOO
Brugnolli et al., 2020
[21]
OOOOOOOOOOOOXOOXXOOOOOOOOOO
Fornaro et al., 2020
[22]
OOOOOOOOOOOOOOOOOOOXOOOOOOO
Kua et al., 2019
[23]
OOOOOOOOOOXOOOOOOOXOXOOOOX
Vlaeyen et al., 2015
[24]
OOOOOOOOXOOXOOOOOOXOOOOOOO
Zhang et al., 2018
[25]
OOOOOOOOOOOOOOOOOOOOOOOOOOO
Silva at el., 2013
[26]
OOOOXOOOOOXXOXXOOOXOXXOXOX
Costa et al., 2016
[27]
OOOOXOOOOOOOXOOXOOOXOOXOOOO
Lan et al., 2017
[28]
OOOXOOXOOOXOOOOOOXOOOOOOX
Cereda et al., 2016
[29]
OOOOXOOOOOXXOXOOOOOOXOOOOO
Mitchell et al., 2011
[30]
OOOOXXOOOOXXXOXOXOOOXOOOOO
Gaugler et al., 2007
[31]
OOOOXOOOOOXXOOOOOOOOXOOOOO
Lee et al., 2017
[32]
OOOOXOOOOOOOOXXOOOXOXXOXOO
Li et al., 2015
[33]
OOOOXOOXXXXXOXXOOOOOXXOOOX
Knopp-Sihota et al., 2016
[34]
OOOOXOOOOOOOXOXXOOOXOXOOXOO
Aliyu et al., 2017
[35]
OOOOXOOOOOOXOOOOOOXOOOOOOX
Deandrea et al., 2013
[36]
OOOOXOOOOOXXOXXOOOXOXXOXOO
Petrignani et al., 2015
[37]
OOOOXOXOOOXXXXXOOOOOXXOOOO
Comondore et al., 2009
[38]
OOOOXOOOOOOXOOOOOOOOOOOOOOO
Kojima, 2015
[39]
OOOOXOOOOOXXOXXOOOOOXXOOOX
Kojima, 2018
[40]
OOOOOOOOXOXXOOXOOOOOOOOOOX
Crocker et al., 2013
[41]
OOOOXXXXXXXXXXXXOOOOOOOOOOO
Wallerstedt et al., 2014
[42]
OOOOXOOOOOOOXOXOOOOOOXOOOOO
Sjögren et al., 2016
[43]
OOOOXOOOOOXXXOXOOXOOOXXOOOO
Robertson et al., 2017
[44]
OOOOOXOXXXXXXOOOOOXXOOOO
Toot et al., 2017
[45]
OOOOXOOOXXXXXXXOOOOOXXOOOX
Jutkowitz et al., 2016
[46]
OOOOOOOOOOOOOOOOOOOOXOOOOO
Smith et al., 2016
[47]
OOOOXOOOOOOXOXXOOOOXOXXOOOO
Kuys et al., 2014
[48]
OOOOXOOOXOOXOOOOOOOOOOXOOOX
Hedrick et al., 1989
[49]
OOOOXXOXXXXXOXXOOOOOXXOOOX
Silvia et al., 2019
[50]
OOOOOOOOOOOOOOXOOXOOOXXOOOX
Gulka et al., 2020
[51]
OOOOXXOXXXXXOXXOOOOOXXOOOX
Zhang et al., 2019
[52]
OOOOOOOOOOOOOOXOOXOOOXXOOOX
Shaun et al., 2019
[53]
OOOOOOOOOOXXOXXOOOXOXXOOOX
Shen et al., 2019
[54]
OOOOOOOOOOXXOXXOOOXOXXOOOX
Prins et al., 2020
[55]
OOOOOOOOXOOOOOOOOOXOOOOOOO
Cao et al., 2017
[56]
OOOOOOOXOOOOOOXXOOXOOOOOOO
Lan et al., 2017
[57]
OOOOXOOOOOOXOXXOOOOOXXOOOX
Note. O: well-followed; ▲: followed but not completed well; X: did not follow.
Table 2. Summary of Included Studies.
Table 2. Summary of Included Studies.
1st Author, Year
Field
Included Study Design (Numbers)Review DesignSynthesis MethodFindings
Hoben et al., 2017
[19]
Nursing, dentistry
Qualitative and Quantitative (45)PRISMA and MOOSE guideline
-
A thematic analysis
-
Random-effects models with STATA 13.1 METAPROP module
-
Freeman–Tukey double arcsine transformation
-
I2
Barriers: residents resisting care, care providers’ lack of knowledge/education/training in providing oral care, general difficulties in providing oral care, lack of time, general dislike of oral care, Fall prevention interventions decreased the lack of staff.
Veronese et al., 2015
[20]
Medicine
Observational cohort studies (36)PRISMA and MOOSE guideline
-
DerSimonian–Laird random-effects model
-
Cochrane I2 statistics
-
Stratified analysis
-
Meta-regression analysis
-
Publication bias assessed
Being underweight had a significant effect on mortality caused by infections.
Brugnolli et al., 2020
[21]
Public Health
RCT, quasi-experimental design study (12)Cochrane handbook,
PRISMA
-
I2 statistics
-
Random or fixed effect model
Educational programs and other supplementary interventions should be effective, but the heterogeneous operative definition of physical restraints can make data generalization difficult.
Fornaro et al., 2020
[22]
Psychiatry
Either naturalistic studies or interventional studies (36)PRISMA and MOOSE
-
I2 statistics
-
Cochran’s Q test
Pooled prevalence rate of major depressive disorder was 18.9%.
Kua et al., 2019
[23]
Pharmacology
RCT (41)PRISMA
-
Cochran’s Q test
-
Random effects model
-
I2 statistics
-
Subgroup analysis
Deprescribing interventions significantly reduced the number of residents with potentially inappropriate medications by 59%.
Vlaeyen et al., 2015
[24]
Nursing
An original or a priori secondary analysis of individual-level or cluster RCT (13)PRISMA
-
Random effects approach
-
I2
-
Subgroup analysis
-
Sensitivity analysis
There was no significant effect of the intervention on fallers or falls.
Zhang et al., 2018
[25]
Medicine
Prospective cohort studies (6)MOOSE
-
I2 statistics
-
Cochran’s Q test
Sarcopenia showed positive association with a risk for all-cause mortality.
Silva at el., 2013
[26]
Medicine
RCT (12)PRISMA
-
Random effects model
-
I2
Exercise has a preventive effect on falls. This effect of mixing several types of exercises was stronger for 1–3 months or for more than 6 months, with a frequency of at least 2–3 times per week.
Costa et al., 2016
[27]
Public Health
Retrospective cohort studies
(26)
PRISMA
-
Random effects model
-
I2
-
Stratified analysis
-
RevMan version 5.2
Determinants of nursing home versus hospital death:
multidisciplinary in-home palliative care, preference for home death, cancer diagnoses, early referral
to palliative care, not living alone, presence of a caregiver, and the caregiver’s coping skills.
Lan et al., 2017
[28]
Medicine
Comparative analysis, cross-section, case–control,
prospective, retrospective design (13)
PRISMA
-
RevMan version 5.3
-
Q and I2 test
-
Random-effect model (DerSimonian and Laird method)
-
Fixed-effects model (Mantel–Haenszel method)
-
Z-test
Lower levels of hemoglobin and creatinine were shown in tube-fed patients.
Cereda et al., 2016
[29]
Nutrition
Any type of non-interventional trial (240)PRISMA
-
DerSimonian–Laird random-effect model
-
Cochran’s Q and I2 statistics
-
Meta-regression
-
Stratified analysis
-
STATA 13.1
Prevalence of malnutrition: community 3.1%, outpatients 6.0%, home-care services 8.7%, hospital 22.0%, nursing homes 17.5%, long-term care 28.7%, rehabilitation/sub-acute care 29.4%.
Mitchell et al., 2011
[30]
Psychology
Any Studies Design (22)N/A
-
Random effects model
-
Sensitivity analysis
-
Statsdirect, Stata10
-
Bayesian curve analysis
Practice/community nurses and hospital nurses correctly identified 26.3% and 43.1% of depressed and 94.8% and 79.6% of the non-depressed people, respectively.
Nursing home nurses correctly identified 45.8% of people with depression and 80.0% of the non-depressed.
Gaugler et al., 2007
[31]
Nursing
Observational Studies (12)N/A
-
Random effect model
-
Cochran’s Q-statistic
-
Subgroup analysis
-
Sensitivity analysis
-
Meta-regression
Significant predictors of nursing home admission were three or more activities of daily living dependencies, cognitive impairment, and prior nursing home use.
Lee et al., 2017
[32]
Nursing
Randomized Controlled Trials (RCT) (21)N/A
-
Review Manager, v.5.3
-
Random effects model
-
Cochrane Q and I2 statistics
-
Mantel–Haenszel, inverse variance methods
-
Subgroup analysis
-
Sensitivity analysis
Exercise had a preventive effect on the fall rate. Combined exercise effect with other fall interventions was stronger on the rate of falls and number of fallers.
Exercise interventions resulted in reduced rate of falls.
Li et al., 2015
[33]
Nursing
RCT or non-RCT
(16)
PRISMA
-
MetaView Review Manager Version 5.2
-
Random effect model
-
I2
No significant improvement in the short-term effects of music therapy.
Knopp-Sihota et al., 2016
[34]
Nursing
Controlled Trials
(14)
The Cochrane Collaboration, PRISMA
-
The Cochrane Collaboration software program
-
Random effect model
-
Fixed-effect model
-
I2
-
Subgroup analysis
Non-analgesic treatment and control groups showed no statistical differences.
Aliyu et al., 2017
[35]
Nursing
Observational studies (12)MOOSE
-
Random effects model
-
I2
-
Subgroup analysis
-
Sensitivity analysis
Prevalence for MDR-GNB colonization: 27%.
Deandrea et al., 2013
[36]
Medicine
Prospective study design (24)The Cochrane Collaboration
-
RevMan version 4.3.2
-
Random effect models
-
Sensitivity analysis
-
x2 test
Nursing home residents: history of falls, walking aid use and moderate disability.
Hospital inpatients: history of falls.
Petrignani et al., 2015
[37]
Public Health
Observational studies (58)N/A
-
Random effects model
-
SAS 9.3 and CMA
Transmission was associated with bedside care and exposure to vomit.
Comondore et al., 2009
[38]
Medicine
Observational studies and RCT
(82)
N/A
-
Random effects models
-
x2 test and I2
-
Meta-regression random effects model
-
Sensitivity analysis
-
Subgroup analysis
Not-for-profit facilities delivered higher-quality care than did for-profit facilities: more or higher staffing quality, lower pressure ulcer prevalence.
Kojima, 2015
[39]
Medicine
Cross-sectional or observational studies (9)N/A
-
Cochran’s Q statistic
-
Random effects model
-
I2
-
Fixed-effects model
-
Publication bias (Egger and Begg tests)
-
Stata IC 13, StatsDirect
Prevalence of frailty and prefrailty was 52.3% and 40.2%, respectively.
Kojima, 2018
[40]
Medicine
Original longitudinal studies (5)MOOSE guideline
-
Mantel–Haenszel method
-
Cochran’s Q test
-
I2
-
Fixed-effects model
-
Random-effects model
-
Publication bias (Egger and Begg tests)
-
Review Manager 5.2, StatsDirects version 2.8
-
Subgroup analysis
Both frailty and prefrailty predicted nursing home placement significantly.
Crocker et al., 2013
[41]
Rehabilitation
RCT (13)N/A
-
Random-effects models
ADL independence improved by 0.24 in standard units.
Wallerstedt et al., 2014
[42]
Pharmacology
RCT and non-RCT
(12)
The Regional Health Technology Assessment Centre in the Region Västra Götaland, Sweden
-
RevMan version 5.1
-
Mentel–Haenszel method in a random-effects model
-
I2
-
Sensitivity meta-analysis
Medication review does not reduce mortality or hospitalization.
Sjögren et al., 2016
[43]
Dentistry
RCT (5)N/A
-
Mantel–Haenszel method random-effects model
-
Fisher exact test
Dental personnel given oral care interventions decreased mortality from healthcare-associated pneumonia. Nurse-given oral care interventions showed no statistically significant difference.
Robertson et al., 2017
[44]
Psychiatry
Quantitative studies (17)PRISMA
-
Stats direct version 3
-
DerSimonian Laird method based on a random effects model
No difference between global proxy rated quality of life.
Toot et al., 2017
[45]
Psychology
RCT, cohort studies, epidemiological studies, case–control studies, systematic reviews, descriptive studies (26)PRISMAN/ARisk factor of nursing home placement: impairments in activities of daily living.
Jutkowitz et al., 2016
[46]
Public health
RCT (19)N/A
-
Knapp–Hartung random effects model
-
I2 statistics
-
Sensitivity analysis
No strong evidence to support effectiveness of care-delivery interventions on managing agitation and aggression.
Smith et al., 2016
[47]
Medicine
Quantitative and qualitative studies (24)PRISMA
-
I-consistency
-
Subgroup analysis
Prevalence of musculoskeletal pain was 30.2%.
Kuys et al., 2014
[48]
Medicine
Any quantitative design studies (34)N/A
-
Fixed and random effects model
-
FMetafor package version 1.7-0
-
Cochran’s Q test
-
Meta-regression
No association between gait speed and covariates.
General-pace gait speed was 0.475 m/s and maximal pace speed was 0.672 m/s.
Hedrick et al., 1989
[49]
Medicine
RCT and quasi experimental studies (13)N/A
-
Woolf’s method
-
Loglinear modeling
-
Logistic regression
-
Odd man out method
Small beneficial effect of home care.
Silvia et al., 2019
[50]
Medicine
Qualitative and Quantitative (16)PRISMA
-
Random effects model
-
Meta-regression
EOL conversations between health care professionals and family had a positive effect on family’s decision to limit or
withdraw life-sustaining treatments.
Gulka et al., 2020
[51]
Medicine
RCT (36)N/A
-
Random effects model
-
I2 statistics
-
Subgroup analysis
Fall prevention interventions decreased
the number of falls,
fallers, and
recurrent fallers.
Zhang et al., 2019
Medicine
[52]
Any quantitative design studies (14)N/A
-
Cochran’s Q test
-
Random effects model
-
I2 statistics
-
Subgroup analysis
-
Sensitivity analysis
Residents with frailty were at an increased risk of mortality compared to those without frailty.
Shaun et al., 2019
[53]
Pharmacology
RCT and Cross-sectional studies and retrospective studies
(42)
N/A
-
Random effects model
-
I2 statistics
Pharmacist-led services reduced the mean number of falls among residents.
Shen et al., 2019
[54]
Medicine
All kinds of studies (16)PRISMA
-
Random effects model
-
I2 statistics
-
Cochran’s Q test
Prevalence of EWGSOP in women and men was 46% and 43%, respectively.
Malnutrition was the independent factor of EWGSOP.
Prins et al., 2020
[55]
Psychology
Experimental research design study (27)N/A
-
I2 statistics
-
Cochran’s Q test
-
Random effects model
Sensory stimulation improved nocturnal behavioral restlessness in terms of both sleep duration and continuation. The effect on the number of awakenings, RAR, and daytime sleep was not significant.
Cao et al., 2017
[56]
Nursing
RCT (9)Cochrane handbook,
PRISMA
-
I2 statistics
-
Cochran’s Q test
Exercise had no effect on fall prevention in nursing home residents.
Lan et al., 2017
[57]
Medicine
RCT (10)PRISMA
-
Fixed-effects (Mantel–Haenszel)
-
Random effects (DerSimonian and Laird) models
-
Subgroup analysis
-
Meta-regression
-
Cochran’s Q-statistic
-
I2
Physical restraint use was significantly lower in the experimental (education) group.
Note. MOOSE: Meta-analysis of Observational Studies in Epidemiology; PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analysis; N/A: not available.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Shin, I.-S.; Shin, J.-H.; Jang, D.-E.; Lee, J. A Methodological Quality Evaluation of Meta-Analyses on Nursing Home Research: Overview and Suggestions for Future Directions. Int. J. Environ. Res. Public Health 2022, 19, 505. https://doi.org/10.3390/ijerph19010505

AMA Style

Shin I-S, Shin J-H, Jang D-E, Lee J. A Methodological Quality Evaluation of Meta-Analyses on Nursing Home Research: Overview and Suggestions for Future Directions. International Journal of Environmental Research and Public Health. 2022; 19(1):505. https://doi.org/10.3390/ijerph19010505

Chicago/Turabian Style

Shin, In-Soo, Juh-Hyun Shin, Dong-Eun Jang, and Jiyeon Lee. 2022. "A Methodological Quality Evaluation of Meta-Analyses on Nursing Home Research: Overview and Suggestions for Future Directions" International Journal of Environmental Research and Public Health 19, no. 1: 505. https://doi.org/10.3390/ijerph19010505

APA Style

Shin, I. -S., Shin, J. -H., Jang, D. -E., & Lee, J. (2022). A Methodological Quality Evaluation of Meta-Analyses on Nursing Home Research: Overview and Suggestions for Future Directions. International Journal of Environmental Research and Public Health, 19(1), 505. https://doi.org/10.3390/ijerph19010505

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop