\nDescription
\nFor this assignment you will:
\n1. review the 2 current and trustworthy\/scholarly research articles on a relevant patient safety topic (you are not
\nto use articles\/readings reviews that you ve obtained from another student this exercise is to help you develop
\nyour skills in research) ARTICLES ARE ALREADY ATTACHED HERE. CHECK THE EMAIL OR
\nATTACHEMENT
\n2. For each article:
\na. Read the Abstract, Introduction, Discussion\/Results
\nb. Determine if this is an article that is of interest to you and offers information\/evidence that will
\ninform\/improve patients safety
\nc. For the articles you deem appropriate as above, complete the following steps.
\n3. Provide a summary (in your own words) of the information in the abstract, introduction, discussion\/results.
\nCreate a heading for each of the 3 areas, so that you instructor can clearly identify your summary.
\n4. In the summary of the abstract, identify if the article is qualitative or quantitative research.
\n5. Create a heading called implications and identify how this information can potentially enhance patient
\nsafety.
\n6. Create a heading called Personal Reflection and identify how YOU can incorporate or champion the
\nadoption of this information in your practice or care area
\n7. Review the attached rubric for a detailed breakdown on the assignment and expectations
\n8. The paper must:
\na. Utilize the APA guidelines
\nb. The paper MUST be checked for grammar and spelling prior to submitting accurate, legible and well written
\ncommunication is very important to patient safety
\nc. The paper must include a cover page and reference list
\nd. The paper must include an introduction and a conclusion
\ne. The body of the paper must be 5 6 pages double spaced
\nf. The 2 articles that you review MUST be included in a reference
\nREMINDERS: just focus on making the 5 pages for the body. I will be the one to make the cover page ans
\nreference page. I will only pay for the 5 pages for the body of essay<\/p>\n
September-October 2016 Vol. 25\/No. 5 329
\nKay Klymko, PhD, ARNP, FNP-BC, is Nurse Practitioner, Florida Health Care Plans, Daytona
\nBeach, FL.
\nLuAnn Etcher, PhD, GNP-BC, is Associate Professor, Spring Arbor University School of
\nHuman Services, Arbor, MI.
\nJoan Munchiando, BSN, RN-BC, CRRN, CMSRN, NE-BC, CDP, is Director of Specialty
\nPrograms, Nursing Administration, NICHE Co-Coordinator, Beaumont Health System, Royal
\nOak, MI.
\nMary Royse, MSN, RN, CMSRN, CDP, is Clinical Nurse Specialist for Medical & Acute Care of
\nthe Elderly Unit, Beaumont Health System, Royal Oak, MI.
\nAcknowledgments: The authors thank Therese Swann, RN, and Kelly Marie Ellsworth, who
\nprovided assistance with literature searches during their graduate programs at Wayne State
\nUniversity (Detroit, MI).
\nVideo Monitoring: A Room with a
\nView, or a Window to Challenges in
\nFalls Prevention Research
\nApproximately 1 million falls
\noccur annually in acute care
\nsettings in the United States,
\nwith incidence of 2.3-7 falls per
\n1,000 patient days (Gray-Micelli &
\nQuigley, 2012; Oliver, Healey, &
\nHaines, 2010). Wu, Keeler, Rubenstein,
\nMaglione, and Shekelle
\n(2010) reported estimated additional
\ncosts of $3,500 for a fall without
\ninjury, with costs increasing to
\n$16,500-$27,500 for additional falls
\nwithout injury or when serious
\ninjury occurs. In 2008, the Centers
\nfor Medicare & Medicaid Services
\ndesignated falls as a hospitalacquired
\ncondition (HAC) and challenged
\nhospital reimbursement for
\nHACs deemed preventable (Quigley
\n& White, 2013). Although the National
\nDatabase of Nursing Quality
\nIndicators reported falls and trauma
\ndecreased 14.7% from 2010 to 2013
\nin select hospital engagement networks,
\nwide variation remains
\nacross hospital settings.
\nOngoing research aimed at advancing
\nmethods to detect and prevent
\nfalls is important. Although
\ngeneral antecedents to falls in hospitalized
\npatients have been reported
\n(Oliver et al., 2010), their relevance
\nin the context of emergent
\nfalls prevention technologies (e.g.,
\nvideo monitoring [VM]) is not well
\nunderstood. Understanding antecedents
\nto patient falls may facilitate
\nthe design of reliable, valid
\ntools for concurrent use with VM
\ninterventions in hospital settings.
\nMaximizing the validity and reliability
\nof a VM intervention will
\nenable further testing regarding the
\nintervention s ability to reduce falls
\nand improve outcomes.
\nPurpose
\nThe purpose of this study was to
\nexplore antecedents to falls in the
\nacute care setting from the lived
\nexperiences of a diverse sample of
\nexpert health professionals, patient
\ncare assistants (1:1 safety sitters), VM
\ntechnicians, nurses, and fall prevention
\nexperts. The following research
\nquestions guided the study: (a) How
\nare the antecedents to a preventable
\nfall in patient rooms on a medical
\nunit described (b) How do the identified
\nantecedents appear on the
\nscreen to a VM technician monitoring
\npatients on a medical unit (c)
\nWhat are the environmental conditions
\nand patient behaviors that
\nshould precipitate fall prevention
\naction during VM
\nReview of Literature
\nA review of the relevant literature
\nwas conducted using CINAHL,
\nPubMed, Scopus, and Google
\nScholar databases. Keywords included
\nfalls, fall prevention, hospital, video
\nmonitoring, and nursing research.
\nFalls have been reported to occur
\nduring times of position change
\nand ambulation, and are often
\nunwitnessed (Deandrea et al., 2013;
\nHitcho et al., 2004; Oliver et al.,
\n2010). Therefore, emerging interventions
\nusing assistive technology
\nfor fall prevention (e.g., electronic
\nsensors, infrared sensors, fall detectors,
\nbed alerts, microphones, pressure
\nsensors, floor sensors, cameras,
\nVM) are gaining attention quickly.
\nThey provide a window through
\nwhich falls can be examined in a
\nnew way, with previously obscured
\ninformation now available regarding
\nhospital-based falls and their
\nantecedents.
\nAs one of the most recent technologic
\nadvancements, VM uses inroom
\ncameras installed at vantage
\nlocations to provide real-time viewing
\nof patient activity through computer
\nvisualization, which differs
\nRReesseeaarrcchh ffoorr PPrraaccttiiccee
\nKay Klymko, LuAnn Etcher,
\nJoan Munchiando, Mary Royse
\nThis qualitative study using focus groups of hospital personnel supports
\nknown antecedents to falls in a video monitoring (VM) setting.
\nAlthough VM can improve the understanding of behaviors
\nleading to falls, further research is needed to support VM methods.
\n330 September-October 2016 Vol. 25\/No. 5
\nfrom other forms of assistive technologies
\nused to prevent falls. VM
\nstaff members are trained to view
\nthe screen, detect an impending fall
\nevent, and intervene. In a hospitalbased
\nstudy, Hardin, Dienemann,
\nRudisill, and Mills (2013) evaluated
\nthe impact of webcams with central
\nmonitoring and alarmed virtual bed
\nrails as surveillance devices. They
\nfound a significant difference
\n(p<0.05) in the fall rate per 1,000
\nadmissions. More recently, Potter
\nand co-authors (2016) analyzed
\nvideo-monitored falls in hospitalized
\npatients and found weakness
\naffecting ability to move, gait problems,
\nand occluded pathways were
\ncontributors to falls. In addition, the
\ntime between the patient beginning
\nto leave the bed and occurrence of
\nthe fall was under 2 minutes.
\nDupree, Fritz-Campiz, and Musheno
\n(2014) noted VM should be used as
\npart of a targeted solution to reduce
\nfalls in hospitalized patients who are
\nunwilling or unable to use the call
\nlight. An additional study by
\nBurtson and Vento (2015) included
\nVM as part of a fall prevention program.
\nImprovements in quality outcomes
\nand cost were demonstrated
\nover 2 years. The current study will
\nbegin to fill a gap regarding
\nantecedents to falls seen in VM, and
\nmay support development of a VM
\nintervention for further testing.
\nSample and Setting
\nParticipants were recruited using
\nfliers posted on the hospital unit,
\nand through announcements on
\nthe hospital website and at staff
\nmeetings. Interested persons contacted
\nprimary investigators (PIs)
\nwho were not affiliated with the
\nhospital. Hospital-affiliated personnel
\nwere invited to participate in
\nthe study if they were at least age
\n18; could speak English; had experience
\nas a patient care assistant (1:1
\nsafety sitter), VM technician, registered
\nnurse (RN) from the VM unit;
\nor were fall prevention experts. The
\nsample consisted of 34 participants
\nin four homogenous groups: fall
\nprevention experts (expert nurses,
\ngeriatricians [n=9]), RNs from the
\nVM unit (n=10), VM technicians
\n(n=6), and patient care assistants
\nthroughout the hospital (n=9).
\nThe study setting was an academic
\nmedical center in southeast
\nMichigan where VM had been
\nimplemented in five rooms to
\nenable concurrent VM of eight
\npatients. Patients were screened for
\nacceptance into a monitored bed by
\na group consisting of the administrative
\nmanager, director of specialty
\nprograms, and charge nurse.
\nAdmission criteria for VM (= age 65
\nwith acute illness putting the
\npatient at risk for\/exhibiting delirium,
\nor high risk for fall) were developed
\nin collaboration with unit
\ngeriatricians and nurse leaders.
\nFocus groups were conducted in
\na classroom at the hospital. Each
\nfocus group lasted approximately
\n60-90 minutes and followed a semistructured
\nformat. Groups were
\naudio-recorded and conducted by
\nthe PIs, who had no hospital affiliation;
\nfield notes also were written.
\nAfter a brief introduction, PIs used
\nseveral questions related to the
\nstudy s purpose (e.g., what behaviors
\npredict or precede a fall, how
\nwould those behaviors appear to a
\nVM technician, what specific
\nbehaviors would alert you to take
\naction to prevent a fall ).
\nThis study was approved by
\nWayne State University and the
\nstudy site s Human Investigation
\nCommittee and Institutional Review
\nBoard. Measures to assure confidentiality
\nof all shared content were
\nexplained through verbatim reading
\nof the informed consent followed by
\nparticipant consent before the focus
\ngroups.
\nMethods and Design
\nFocus group methodology was
\nconsistent with Morgan and Krueger s
\n(1998) inclusive approach.
\nAuthors defined the focus group as
\na research technique that collects
\ndata through group interaction on a
\ntopic determined by the researcher
\nin which the researcher s interest
\nprovides the focus, whereas the data
\nthemselves come from the group
\ninteraction (p. 7).
\nFindings
\nAntecedents to a Preventable
\nFall
\nAntecedents to a preventable fall
\nin the patients rooms had a clear
\ndemarcation. They were represented
\nby the major themes of environmental
\nfactors and behavioral representations.
\nChallenging Hazards within
\nthe Room
\nHazards in the room were environmental
\nfactors represented by
\nstructural and process issues. Structural
\nissues included characteristics
\nof the room itself and items in proximity
\nto patients. Process issues
\nwere related to events experienced
\nby patients.
\nStructural issues within the room.
\nParticipants agreed patient rooms
\nwere often crowded. As one patientcare
\nassistant noted, the walker,
\nthe computers, the table, and the
\nIV poles and the beds and it s all
\nstuffed into one room and there s
\nlike this much room (holding arms
\nup demonstrating width) to walk to
\nthe bathroom Extreme room
\ntemperatures also were reported as
\nan issue. One fall prevention expert
\nnoted, people are hot or cold,
\nthat s when they start pushing the
\nblankets, IV line see that a lot.
\nUnit noises can be foreign to
\npatients, occurring at variable times
\nand levels. As one RN described,
\n It s confusing for the VM patients
\nfor that voice (audio) to be in that
\nroom.
\nConcerns emerged regarding
\nlines attached or close to the
\npatient, who could become entangled
\nin or trip on them in getting
\nout of bed or ambulating (e.g., feeding
\ntube, suctioning equipment,
\nindwelling urinary catheter bag,
\nmonitoring line, intravenous line,
\ncall lights, phone line). One
\npatient-care assistant explained,
\n Tubing and the IV pole you
\nknow, you see someone starting to
\nget up and you know they re
\nhooked up to monitors and that s
\nlike, oh, no! In addition to lines,
\npatients may try to free themselves
\nof soiled bedding or clothing, as
\nResearch for Practice
\nSeptember-October 2016 Vol. 25\/No. 5 331
\nVideo Monitoring: A Room with a View, or a Window to Challenges in Falls Prevention Research
\none VM technician said, On midnights,
\nthey used to tell us (in staff
\neducation on fall prevention) when
\nthe patient is wet, they start trying
\nto get out of bed.
\nThe bedside table provides the
\npatient easy, routine access to personal
\nitems (e.g., cell phone, water).
\nInaccessible personal items can
\nprompt patients to reach unsafely.
\nOne patient-care assistant voiced,
\n If that s (bedside table) not near
\nthem they ll reach and then roll
\nright out\u2026
\nVulnerable times for a fall reported
\nby participants included the day
\nof admission, day of discharge, in
\nthe morning at awakening, meal
\ntimes, shift changes, and staff
\nbreaks. Night was a particular concern,
\nas one patient-care assistant
\ndescribed, when it gets dark, in
\nthe evening people that are completely
\nfine during the day just start
\ngetting a little confused and that s
\nwhen they ll get up they ll be
\nmore likely to fall.
\nProcess issues within the room.
\nPeople entering or leaving a
\npatient s room were reported to
\nincrease vulnerability to a fall. One
\nRN described asking the VM technician
\nto monitor patients more
\nclosely for about 5 minutes after she
\nleft the rooms because patients may
\nreconsider their needs and try to get
\nout of bed unattended without calling
\nfor help. Further validation was
\nprovided by another RN, who
\nremarked: How many times have
\nyou heard a nurse say, I was just in
\nthat room
\nBehavioral Phenomena
\nExhibited by Patients
\nPatient behaviors described as
\nantecedents to falls were differentiated
\nby two sub-themes: physical
\nbehaviors and psychological\/emotional
\nphenomena.
\nPhysical behaviors exhibited by
\npatients. A behavior frequently
\ndescribed by participants was restlessness.
\nOne fall prevention
\nexpert described a lot of nonpurposeful
\nbehavior like picking,
\nfidgeting; picking at blankets, picking
\nat themselves, picking at the
\nlines, picking at the bed, picking at
\nwhatever may be around them
\nbefore they decide to climb out of
\nthe bed. Participants reported,
\n The patient may sit up abruptly
\nand provide visual signals such as
\n looking around the room or a
\n dead stare into the camera as if to
\nsay, Okay, who s going to see me
\nhere, can I get away Reaching was
\nperceived to increase risk for falls,
\nwith patients described as misjudging
\nthe distance to an object. As one
\nRN explained, A patient was sitting
\nin a chair and went to reach for
\nsomething she dropped on the
\nfloor, and just over-reached and just
\nslid right out, right under the
\ntable
\nParticipants reported a pattern
\nand order of movements progressing
\nin magnitude\/required strength
\nas the patient prepared to get out
\nof bed. Initial fine movements
\n(e.g., restlessness, picking, looking
\naround) often were followed by
\nmore gross movement (e.g., sitting
\nup suddenly and straight, scooting
\nto the edge of the bed with the hips,
\nrolling over). Finally, as described
\nby one participant, the patient may
\nshow a whole body and gracious
\nroll of unprecedented strength as
\nhe or she moves out of bed.
\nIssues associated with ambulation
\nwere reported to be antecedent
\nto falls, such as improper use of
\nunfamiliar assistive devices, excessive
\nspeed in walking, foot dragging,
\nunsteadiness, syncope, and verbalizations
\nof dizziness or lightheadedness.
\nSeveral patient-care assistants
\nindicated chair sitting also can cause
\nproblems. When patients fall
\nasleep or rest their arm over the arm
\nrest and all it takes is a slip of the
\narm and you get off balance and fall
\nforward, or push the table away
\nfrom in front of them.. , they
\nincrease their risk for fall due to
\nreduced protection from the bedside
\ntable and\/or chair arm rests.
\nPsychological and emotional behaviors
\nexhibited by patients. One RN
\ndescribed the challenge when cognitive
\nchanges occur suddenly and
\nunexpectedly (as in delirium):
\nyou have some elderly person coming
\nin with a UTI (urinary tract
\ninfection); they get that infection
\nand they re very impaired you get
\nthe infection cleared up and then
\nthey re fine again. Agitated or confused
\npatients often needed fears
\nallayed, as one VM technician
\nvoiced he s crying he wants to
\nget up he wants to go home he
\njust wanted somebody to listen. He
\nwanted somebody to understand
\nhis story and once you did that, he
\nlaid back down.
\nAntecedents Appearance
\nDuring Video Monitoring
\nParticipants generally agreed VM
\ncan provide a distorted view of reality:
\n It s not as clear you can t really
\nsee what they re doing exactly.
\nHowever, they agreed VM provided
\na view otherwise unavailable unless
\nin the room. VM distortions described
\nby participants included the
\nroom appearing far way, partial
\nvisualization of the room, patient
\nmovements appearing as slow
\nmotion, lack of clarity despite
\ninfrared capability in the dark, and
\npatient behaviors appearing accentuated.
\nThese distortions led staff to
\nrespond to observed patient behavior
\n(movement) by using audio
\ncommunication to the room or
\nsending staff to the room.
\nParticipants indicated audio communications
\nactually precipitated
\nbehaviors that could lead to a fall.
\nFor example, a sleeping patient is
\nawakened with confusion and fear
\nof the intercom voice.
\nEnvironmental Conditions
\nand Patient Behaviors
\nPrompting Action
\nParticipants identified VM antecedents
\nthat warranted increased
\nawareness or further action to avoid
\na fall. Structural environmental factors
\nincluded changes in the ambient
\nenvironment (sound and light
\nlevels, room temperature), and
\nchanges in the local environment
\n(loose or running cords, wet floors,
\npersonal care objects out of reach,
\novercrowding, room changes). Process-based
\nenvironmental factors
\nincluded changes in patterns of
\nactivity (shift change, visitors, mealtimes,
\nbeing awakened from sleep).
\nPatient-based factors prompting
\naction fell into two categories: physically
\nbased (being soiled, in pain,
\nwith sensory deficits, physiological-
\n332 September-October 2016 Vol. 25\/No. 5
\nly compromised, delirium) or psychologically\/emotionally
\nbased (dementia,
\nanxiety, presence of psychological
\ndisorders, patient unwilling
\nto follow safety parameters,
\npatient misperception of capabilities).
\nAnalysis
\nOral recordings and field notes
\nwere transcribed manually after
\neach focus group. Two PIs not affiliated
\nwith the hospital conducted
\nseparate data analyses starting with
\na first and second reading of the
\ntranscripts. Initial coding involved
\ncompressing the text based on
\nthemes (e.g., behavioral and environmental
\nconditions determined
\nto be antecedents to falls). After the
\ninitial coding scheme, a second
\nlevel of coding included an inductive
\napproach based on new knowledge
\ngained from the interviews.
\nTrustworthiness
\nLincoln and Guba s (1985) four
\ncriteria to ensure trustworthiness in
\nqualitative investigations were used
\nin this study. To assure credibility,
\nnon-hospital researchers were
\nassured by confirming the reliability
\nof the findings through comparing
\nthe consistency of the codes
\nand their thematic grouping
\nbetween the non-hospital affiliated
\nPIs. Additional peer debriefing also
\nwas obtained through a review of
\nthe collective codes\/themes by the
\nhospital PI and consultant clinical
\nnurse specialist of the research team
\nas a means to obtain further
\ninsights regarding the final thematic
\ncoding schema. Triangulation of
\nthe data also was accomplished by
\ncomparing the audio recordings of
\nthe focus groups with the field
\nnotes. Transferability of the findings
\nwas supported through use of
\npurposive sampling and the rich
\nparticipant descriptions provided in
\nthe findings. Confirmability of the
\nresults as supported by the data was
\nenhanced with a cross-comparison
\nof the decision trails used by the PIs
\nto collapse the thematic coding
\nschema. Dependability of the
\nmethodological procedures was
\nenhanced through study design
\nconsultation with an external
\nexpert in qualitative methodology.
\nLimitations
\nThe sample was restricted to selfselected
\ngroups of individuals.
\nParticipants also represented one
\nhospital setting. The study lacked a
\nfocus group of patients who had
\nexperienced a hospital fall.
\nDiscussion
\nVideo-monitoring technology
\nprovides an intervention not previously
\navailable to healthcare
\nproviders. This study was a beginning
\nelucidation of the appearance
\non a VM screen of many of the
\nknown antecedents to falls in
\npatient rooms. Focus group participants
\nin this study identified
\nantecedents to hospital falls generally
\nconsistent with patient-specific
\nfactors and environmental risk factors
\nas previously identified in the
\nliterature; this expanded prior work
\non knowledge of antecedents
\n(Deandrea et al., 2013; Oliver et al.,
\n2010) and confirmed its relevancy
\nin a VM inpatient environment.
\nNursing Implications
\nThis study s findings may inform
\nnurses who are planning to implement
\na VM intervention in their
\nhospitals. Although the Morse Fall
\nScale was demonstrated as effective
\nin predicting falls when used in a
\nVM inpatient setting (Hardin et al.,
\n2013), neither that scale nor the
\nSTRATIFY falls risk assessment tool
\nwas designed as a decisional aid for
\ndetermining the best strategy to
\nprevent falls for at-risk individuals.
\nMoreover, neither of these assessment
\ntools includes an indicator
\n(e.g., specific diagnosis of delirium
\nor dementia) that may guide the
\ndecision to use a VM intervention
\nversus a different modality (e.g., 1:1
\nsafety sitter). Nurses may believe
\nthese diagnoses are appropriate for
\na VM intervention, but this study
\nsuggests nurses must remain cautious
\nwhen initiating audio communications
\nfrom the VM central
\nstation to patients who are prone to
\ndifficulty with dual-tasking (e.g.,
\ncognitive aging or impairment).
\nFurther investigations are needed
\non the characteristics of patients
\nwho may be best served by VM.
\nConclusion
\nThe availability of VM in inpatient
\nunits provides new opportunities
\nto understand how known
\nantecedents are viewed and prompt
\naction in the context of a VM intervention.
\nThe findings from this
\nstudy add to existing knowledge,
\nwhich can be applied to developing
\nand refining VM interventions to
\nprevent falls. Further investigations
\nconducted with real-time VM designed
\nto describe and validate
\nreported antecedents to falls are
\nneeded, despite the inherent methodological
\ndifficulties in designing
\nand conducting VM research studies
\n(Hardin et al., 2013). Additionally,
\nfurther investigation of
\nwhat constitutes an appropriate,
\nsafe VM intervention response is
\nwarranted in light of the finding
\nthat certain VM intervention
\nresponses (audio speaker to the
\npatient) may trigger a fall in some
\npatients. Until then, nurses will
\nneed to consider carefully personal
\ncharacteristics of patients when
\nadmitting patients to a VM unit and
\nresponding to potential antecedents
\nto falls detected during a VM
\nintervention.
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\nClinical Geriatric Medicine, 26(4), 751-
\n766. doi:10.1016\/j.cger.2010.07.005
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\nindividual use.<\/p><\/p>\n","protected":false},"excerpt":{"rendered":"
Description For this assignment you will: 1. review the 2 current and trustworthy\/scholarly research articles on a relevant patient safety topic (you are not to use articles\/readings reviews that you ve obtained from another student this exercise is to help Read More …<\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-95826","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts\/95826","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/comments?post=95826"}],"version-history":[{"count":0,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts\/95826\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/media?parent=95826"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/categories?post=95826"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/tags?post=95826"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}