Comparing text mining and manual coding methods: Analysing interview data on quality of care in long-term care for older adults.

OBJECTIVES: In long-term care for older adults, large amounts of text are collected relating to the quality of care, such as transcribed interviews. Researchers currently analyze textual data manually to gain insights, which is a time-consuming process. Text mining could provide a solution, as this methodology can be used to analyze large amounts of text automatically. This study aims to compare text mining to manual coding with regard to sentiment analysis and thematic content analysis. METHODS: Data were collected from interviews with residents (n = 21), family members (n = 20), and care professionals (n = 20). Text mining models were developed and compared to the manual approach. The results of the manual and text mining approaches were evaluated based on three criteria: accuracy, consistency, and expert feedback. Accuracy assessed the similarity between the two approaches, while consistency determined whether each individual approach found the same themes in similar text segments. Expert feedback served as a representation of the perceived correctness of the text mining approach. RESULTS: An accuracy analysis revealed that more than 80% of the text segments were assigned the same themes and sentiment using both text mining and manual approaches. Interviews coded with text mining demonstrated higher consistency compared to those coded manually. Expert feedback identified certain limitations in both the text mining and manual approaches. CONCLUSIONS AND IMPLICATIONS: While these analyses highlighted the current limitations of text mining, they also exposed certain inconsistencies in manual analysis. This information suggests that text mining has the potential to be an effective and efficient tool for analysing large volumes of textual data in the context of long-term care for older adults.

The development of an automatic speech recognition model using interview data from long-term care for older adults.

OBJECTIVE: In long-term care (LTC) for older adults, interviews are used to collect client perspectives that are often recorded and transcribed verbatim, which is a time-consuming, tedious task. Automatic speech recognition (ASR) could provide a solution; however, current ASR systems are not effective for certain demographic groups. This study aims to show how data from specific groups, such as older adults or people with accents, can be used to develop an effective ASR. MATERIALS AND METHODS: An initial ASR model was developed using the Mozilla Common Voice dataset. Audio and transcript data (34 h) from interviews with residents, family, and care professionals on quality of care were used. Interview data were continuously processed to reduce the word error rate (WER). RESULTS: Due to background noise and mispronunciations, an initial ASR model had a WER of 48.3% on interview data. After finetuning using interview data, the average WER was reduced to 24.3%. When tested on speech data from the interviews, a median WER of 22.1% was achieved, with residents displaying the highest WER (22.7%). The resulting ASR model was at least 6 times faster than manual transcription. DISCUSSION: The current method decreased the WER substantially, verifying its efficacy. Moreover, using local transcription of audio can be beneficial to the privacy of participants. CONCLUSIONS: The current study shows that interview data from LTC for older adults can be effectively used to improve an ASR model. While the model output does still contain some errors, researchers reported that it saved much time during transcription.

Text mining in long-term care: Exploring the usefulness of artificial intelligence in a nursing home setting.

OBJECTIVES: In nursing homes, narrative data are collected to evaluate quality of care as perceived by residents or their family members. This results in a large amount of textual data. However, as the volume of data increases, it becomes beyond the capability of humans to analyze it. This study aims to explore the usefulness of text mining approaches regarding narrative data gathered in a nursing home setting. DESIGN: Exploratory study showing a variety of text mining approaches. SETTING AND PARTICIPANTS: Data has been collected as part of the project 'Connecting Conversations': assessing experienced quality of care by conducting individual interviews with residents of nursing homes (n = 39), family members (n = 37) and care professionals (n = 49). METHODS: Several pre-processing steps were applied. A variety of text mining analyses were conducted: individual word frequencies, bigram frequencies, a correlation analysis and a sentiment analysis. A survey was conducted to establish a sentiment analysis model tailored to text collected in long-term care for older adults. RESULTS: Residents, family members and care professionals uttered respectively 285, 362 and 549 words per interview. Word frequency analysis showed that words that occurred most frequently in the interviews are often positive. Despite some differences in word usage, correlation analysis displayed that similar words are used by all three groups to describe quality of care. Most interviews displayed a neutral sentiment. Care professionals expressed a more diverse sentiment compared to residents and family members. A topic clustering analysis showed a total of 12 topics including 'relations' and 'care environment'. CONCLUSIONS AND IMPLICATIONS: This study demonstrates the usefulness of text mining to extend our knowledge regarding quality of care in a nursing home setting. With the rise of textual (narrative) data, text mining can lead to valuable new insights for long-term care for older adults.

Seven steps toward more transparency in statistical practice.

We argue that statistical practice in the social and behavioural sciences benefits from transparency, a fair acknowledgement of uncertainty and openness to alternative interpretations. Here, to promote such a practice, we recommend seven concrete statistical procedures: (1) visualizing data; (2) quantifying inferential uncertainty; (3) assessing data preprocessing choices; (4) reporting multiple models; (5) involving multiple analysts; (6) interpreting results modestly; and (7) sharing data and code. We discuss their benefits and limitations, and provide guidelines for adoption. Each of the seven procedures finds inspiration in Merton's ethos of science as reflected in the norms of communalism, universalism, disinterestedness and organized scepticism. We believe that these ethical considerations-as well as their statistical consequences-establish common ground among data analysts, despite continuing disagreements about the foundations of statistical inference.

A communication model for nursing staff working in dementia care: Results of a scoping review.

BACKGROUND: Communication between nursing staff and people with dementia can be challenging. According to the literature, communication is seen as a process of social- and/or informational exchange between a sender and a receiver in a context. Factors related to these elements determine the quality of communication. Insight into the factors involved in the communication process between nursing staff and people with dementia is limited and a comprehensive model of communication in dementia care is lacking. OBJECTIVES: To identify and visualize factors associated with communication between nursing staff and people with dementia. DESIGN: A scoping review of scientific literature. DATA SOURCES: Scientific articles were retrieved from the bibliographic databases of PubMed, CINAHL and PsycINFO. REVIEW METHODS: The reviewing process was directed by the Joanna Briggs guidelines for scoping reviews. Full-text articles describing the communication process between nursing staff and people with dementia were eligible for inclusion. A data extraction form was used to identify factors associated with communication. Following a directed content analysis approach, factors were categorized in one of three categories: nursing staff; people with dementia; or context. Each category was thematically analysed to identify themes and subthemes. Results were visualized into a communication model. RESULTS: The review included 31 articles; in total, 115 factors were extracted. Thematic analysis of nursing staff factors (n = 78) showed that communication is associated with professional characteristics, individual experiences, verbal- and non-verbal communication skills, communication approach and values. Factors attributed to people with dementia (n = 22) concerned client characteristics, functional status, behaviour, verbal communication skills and values. Contextual factors (n = 15) related to organization of care, time and situation. Based on these results, the Contac-d model was constructed. CONCLUSIONS: The Contac-d model gives a comprehensive overview of factors involved in the communication process between nursing staff and people with dementia, providing insight in potential starting points for communication improvement, e.g. respect for needs, identity and privacy of people with dementia, a flexible and adapted communication approach and matching language. Additionally, results suggest that an appealing location, longer duration of the interaction, and music in the surrounding may improve communication in certain situations. However, it was not feasible based on current literature to recommend what works to improve communication in which situations. Future studies should study factors and their interrelatedness in specific care situations. Authors further believe that more attention should be paid to strengths and capabilities of people with dementia and to non-modifiable factors that influence communication.

The Validity of Connecting Conversations: A Narrative Method to Assess Experienced Quality of Care in Nursing Homes from the Resident's Perspective.

It is important to assess experienced quality of care in nursing homes, as this portrays what is important to residents and helps identify what quality improvements should focus on. Connecting Conversations is a narrative method that assesses experienced quality of care from the resident's perspective in nursing homes by having separate conversations with residents, family, and professional caregivers (triads) within a learning network. This study assessed the validity of performing the narrative method, Connecting Conversations. Trained nursing home staff (interviewers) performed the conversations in another nursing home than where they were employed. In total, 149 conversations were performed in 10 nursing homes. Findings show that experts deemed the narrative assessment method appropriate and complete to assess experienced quality of care (face validity). The questions asked appeared to capture the full construct of experienced quality of care (content validity). Additionally, there was a range in how positive conversations were and first results indicated that a nursing home scoring higher on satisfaction had more positive conversations (construct validity). More data are needed to perform additional construct validity analyses. In conclusion, Connecting Conversations shows promising results for its use as a valid narrative method to assess experienced quality of care.

The opinions of radiographers, nuclear medicine technologists and radiation therapists regarding technology in health care: a qualitative study.

INTRODUCTION: New technology is continuously introduced in health care. The aim of this study was (1) to collect the opinions and experiences of radiographers, nuclear medicine technologists and radiation therapists regarding the technology they use in their profession and (2) to acquire their views regarding the role of technology in their future practice. METHODS: Participants were recruited from five departments in five hospitals in The Netherlands. All radiographers, nuclear medicine therapists and radiation therapists who were working in these departments were invited to participate (n = 252). The following topics were discussed: technology in daily work, training in using technology and the role of technology in future practice. The recorded interviews were transcribed verbatim and analysed using open and axial coding. RESULTS: A total of 52 participants (57.7% radiographer) were included, 19 men and 33 women (age range: 20-63). Four major themes emerged: (1) technology as an indispensable factor, (2) engagement, support and training in using technology, (3) transitions in work and (4) the radiographer of the future. All participants not only value technological developments to perform their occupations, but also aspects such as documentation and physical support. When asked about the future of their profession, contradictory answers were provided; while some expect less autonomy, others belief they will get more autonomy in their work. CONCLUSION: Technology plays a major role in all three occupations. All participants believe that technology should be in the best interests of patients. Being involved in the implementation of new technology is of utmost importance; courses and training, facilitated by the managers of the departments, should play a major role. Only when a constant dialogue exists between health care professionals and their managers, in which they discuss their experiences, needs and expectations, technology can be implemented in a safe and effective manner. This, in turn, might positively influence quality of care.

Older Adults' Reasons for Using Technology while Aging in Place.

BACKGROUND: Most older adults prefer to age in place, and supporting older adults to remain in their own homes and communities is also favored by policy makers. Technology can play a role in staying independent, active and healthy. However, the use of technology varies considerably among older adults. Previous research indicates that current models of technology acceptance are missing essential predictors specific to community-dwelling older adults. Furthermore, in situ research within the specific context of aging in place is scarce, while this type of research is needed to better understand how and why community-dwelling older adults are using technology. OBJECTIVE: To explore which factors influence the level of use of various types of technology by older adults who are aging in place and to describe these factors in a comprehensive model. METHODS: A qualitative explorative field study was set up, involving home visits to 53 community-dwelling older adults, aged 68-95, living in the Netherlands. Purposive sampling was used to include participants with different health statuses, living arrangements, and levels of technology experience. During each home visit: (1) background information on the participants' chronic conditions, major life events, frailty, cognitive functioning, subjective health, ownership and use of technology was gathered, and (2) a semistructured interview was conducted regarding reasons for the level of use of technology. The study was designed to include various types of technology that could support activities of daily living, personal health or safety, mobility, communication, physical activity, personal development, and leisure activities. Thematic analysis was employed to analyze interview transcripts. RESULTS: The level of technology use in the context of aging in place is influenced by six major themes: challenges in the domain of independent living; behavioral options; personal thoughts on technology use; influence of the social network; influence of organizations, and the role of the physical environment. CONCLUSION: Older adults' perceptions and use of technology are embedded in their personal, social, and physical context. Awareness of these psychological and contextual factors is needed in order to facilitate aging in place through the use of technology. A conceptual model covering these factors is presented.

[Using the RAND-36 among community-dwelling older adults can lead to an underestimation of self-reported health]. / Gebruik van de RAND-36 bij zelfstandig wonende ouderen kan leiden tot een onderschatting van de ervaren gezondheidstoestand.

The overall health status of the population is often measured by RAND-36 item Health Survey. In 2012, Fontys and partners started a longitudinal field study in the Netherlands. This study is aimed at identifying factors that influence the use of technology by elderly individuals in order to increase independent living. A total of 50 participants aged 70 years or older, are interviewed every eight months, for a total of four years. In addition, participants are asked to fill in several questionnaires. One questionnaire that is (partly) included is the Dutch version of the RAND-36, which includes the statement; "I am as healthy as anybody I know". Some participants who find themselves healthier than other people they know (want to) fill in an answer that indicates that they find themselves less healthy than others (e.g. "I am not as healthy as anybody, I am healthier so I answer 'definitely false'"). Hence, the Dutch version of this RAND-36 statement can lead to an underestimation of the overall health status of Dutch elderly individuals.

Finding potentially new multimorbidity patterns of psychiatric and somatic diseases: exploring the use of literature-based discovery in primary care research.

BACKGROUND: Multimorbidity, the co-occurrence of two or more chronic medical conditions within a single individual, is increasingly becoming part of daily care of general medical practice. Literature-based discovery may help to investigate the patterns of multimorbidity and to integrate medical knowledge for improving healthcare delivery for individuals with co-occurring chronic conditions. OBJECTIVE: To explore the usefulness of literature-based discovery in primary care research through the key-case of finding associations between psychiatric and somatic diseases relevant to general practice in a large biomedical literature database (Medline). METHODS: By using literature based discovery for matching disease profiles as vectors in a high-dimensional associative concept space, co-occurrences of a broad spectrum of chronic medical conditions were matched for their potential in biomedicine. An experimental setting was chosen in parallel with expert evaluations and expert meetings to assess performance and to generate targets for integrating literature-based discovery in multidisciplinary medical research of psychiatric and somatic disease associations. RESULTS: Through stepwise reductions a reference set of 21,945 disease combinations was generated, from which a set of 166 combinations between psychiatric and somatic diseases was selected and assessed by text mining and expert evaluation. CONCLUSIONS: Literature-based discovery tools generate specific patterns of associations between psychiatric and somatic diseases: one subset was appraised as promising for further research; the other subset surprised the experts, leading to intricate discussions and further eliciting of frameworks of biomedical knowledge. These frameworks enable us to specify targets for further developing and integrating literature-based discovery in multidisciplinary research of general practice, psychology and psychiatry, and epidemiology.

The effect of multimorbidity on health related functioning: temporary or persistent? Results from a longitudinal cohort study.

OBJECTIVE: Multimorbidity is known for its negative effects on health related functioning. It remains unclear if these effects are stable over time. The aim was to investigate if the relation between single morbidity/multimorbidity and health related functioning is temporary or persistent. METHODS: Data were collected as part of the Maastricht Aging Study (MAAS), a prospective study into the determinants of cognitive aging. Participants (n=1184), 24-81 years old, were recruited from a patient database in primary care (Registration Network Family Practices). Morbidity status (i.e. healthy, single morbidity or multimorbidity) and the Short Form Health Survey (SF-36) were both assessed at baseline, at 3- and 6-year follow-up. RESULTS: At baseline but not at 3- and 6-year follow-up, participants with single morbidity reported poorer physical functioning than their healthy counterparts. Multimorbidity was associated with poorer physical functioning at all measurements. Participants with multimorbidity showed a steep decrease in physical functioning between 3- and 6-year follow-up. Multimorbidity appeared to be unrelated to mental functioning. At baseline and at 3-year follow-up, participants who had a change in morbidity status reported poorer physical functioning than their healthy counterparts. CONCLUSIONS: Poorer physical functioning that accompanies multimorbidity is persistent and may even increase over time. People, who acquire one or more diseases during the 3-year follow-up, already showed poorer physical functioning at baseline compared to people who remained healthy during these years. Post-hoc analyses, using the SCL-90 as an outcome measure, did show that multimorbidity was related to depressive and anxiety complaints. However, these complaints seem to decline over time.