The Gerontologist

Purpose: This article assesses the state of research on assisted living (AL) from 1989 to May 2004. Design and Methods: We undertook keyword searches for AL research and amplified these with searches of Web sites, conference proceedings, and follow-up inquiries. We annotated and coded the resultant items according to categories reflecting the research methods used and the topics studied. We did additional comparisons for 38 studies with quantitative data that permitted summarizing resident characteristics, settings, and entry and move-out patterns. Results: The 411 identified items ranged across a large number of topics. Qualitative studies outnumbered quantitative ones, and longitudinal studies were rare. We found little standardization in the way variables were measured, making cross-study comparisons difficult. As AL research has become more common, some items are directed at studying ways to proceed within AL as opposed to globally commenting on the worth of AL as a service sector. Implications: The research base for AL has grown rapidly but is still underdeveloped. We recommend using more consistent sets of standardized measures in AL studies and reporting analyses based on them. We also recommend fuller reporting of details on sampling, time frames, and measures in AL research

Resident outcomes in small-house nursing homes: a longitudinal evaluation of the Initial Green House Program,”

Abstract OBJECTIVES: To determine the effects of a small-house nursing home model, THE GREEN HOUSE ® (GH), on residents' reported outcomes and quality of care. DESIGN: Two-year longitudinal quasi-experimental study comparing GH residents with residents at two comparison sites using data collected at baseline and three follow-up intervals. SETTING: Four 10-person GHs, the sponsoring nursing home for those GHs, and a traditional nursing home with the same owner. PARTICIPANTS: All residents in the GHs (40 at any time) at baseline and three 6-month follow-up intervals, and 40 randomly selected residents in each of the two comparison groups. INTERVENTION: The GH alters the physical scale environment (small-scale, private rooms and bathrooms, residential kitchen, dining room, and hearth), the staffing model for professional and certified nursing assistants, and the philosophy of care. MEASUREMENTS: Scales for 11 domains of resident quality of life, emotional well-being, satisfaction, self-reported health, and functional status were derived from interviews at four points in time. Quality of care was measured using indicators derived from Minimum Data Set assessments. RESULTS: Controlling for baseline characteristics (age, sex, activities of daily living, date of admission, and proxy interview status), statistically significant differences in self-reported dimensions of quality of life favored the GHs over one or both comparison groups. The quality of care in the GHs at least equaled, and for change in functional status exceeded, the comparison nursing homes. CONCLUSION: The GH is a promising model to improve quality of life for nursing home residents, with implications for staff development and medical director roles. Alternative,'' a set of principles overlaid on existing nursing homes to flatten hierarchies, invest decision-making in residents and frontline staff, and normalize nursing home life, addressed psychosocial problems of residents, such as loneliness, boredom, helplessness, and lack of meaning .17 Eden training has been widely sought, but the few formal evaluations had unimpressive results, METHOD Design The organization sponsoring the first GH to be implemented considered that randomization of residents to the GH was unfeasible, partly because money was initially raised to relocate the first 20 residents from a locked dementia care unit. Instead, the intervention was tested in a longitudinal quasi-experimental design. Although under the same ownership and experiencing similar local conditions, Trinity is a smaller nursing home with a sub-acute capability. The Trinity group represents the ''natural history'' of residents in a traditional nursing home setting in the same region and time period. Sample Figure 1 displays the sample for each setting at each time period. Green House The GH sample comprised the 40 people who were scheduled to move to the GHs at baseline and the current GH census at each of the three follow-up periodsF6 months, 12 months, and 18 5 months. All told, 53 GH residents were eligible over the successive data collection periods, 52 of whom were in the sample. Ten of the GH sample members died over the 18-month period, and two were discharged. ( Cedars During the study period, the maximum census remaining at Cedars was 80. At baseline, a random sample of 40 residents was sought, excluding residents who were comatose, vegetative, or in end-stage palliative care; nine of the initial group approached declined to participate. In subsequent waves, to acquire as much baseline data as possible from residents who might later move to GHs, the Cedars sample was enlarged, with a goal of 70 per time period. The added sample members at all follow-up waves were randomly selected. The final Cedars sample sizes were 67, 71, and 64 for the three follow-up waves, with refusals from three, zero, and one person, respectively. The only live discharges from Cedars were to GHs, affecting six sample members; 22 of the Cedars sample died during the study period. Trinity Trinity had a capacity of 65 beds, 15 of which were in a Medicare unit. A sample of 40 residents was sought from the non-Medicare portion of Trinity, using the same exclusion criteria as at Cedars. The Trinity sample at the three follow-up waves was 39, 36, and 37, respectively. Sixty-six people participated from Trinity; 18 sample members died over the 18 months, and four were discharged alive. Sample for Quality Indicators The sample in all three settings for quality indicators (QIs) is larger than the sample for direct data collection. It comprised all those in the settings during each of three 6-month time periods, because it used MDS records for each setting. Measures Quality of Life Eleven domains of quality of life were measured: physical comfort, functional competence, privacy, dignity, meaningful activity, relationship, autonomy, food enjoyment, spiritual well-being, security, and individuality. These domains scales comprised three to six items; each is standardized to a theoretical range of 4 to 1, by dividing the total score by the number of items. Most items used a 4-point ordinal scale (45 often, 3 5 sometimes, 2 5 rarely, 1 5 never); reverse coding was used for items so that a higher score always represented 8 better quality of life. Those unable to respond to a Likert-type scale after three attempts (due to cognitive limitations) were asked the question with a ''mostly yes'' or ''mostly no'' choice. After empirical testing, these responses were extrapolated into the 4 to 1 scale, with a score of 3.8 for the affirmative and 1.5 for the negative responses. These measures have been tested in a large sample and have reliable scale properties, test-retest reliability, and concurrent validity, and the domain scales have been shown to comprise separate but related measures of an underlying quality-of-life construct. 21 Health and Functioning Residents rated their health as excellent, very good, good, fair, or poor. Ability to perform activities of daily living (ADLs) ''in the last few months'' was measured according to selfreport using five items: bathing, dressing, transferring from bed, using the toilet, and eating. Ability to perform instrumental activities of daily living (IADLs) was measured using six items: taking medicine, using the telephone, preparing food, light housekeeping, managing money, and doing laundry. For all ADL and IADL items, residents were asked whether they did the function by themselves, got a little help, got a lot of help, did not do it at all, or were not allowed to do the task; higher scores represented greater impairment. Satisfaction Global satisfaction was measured using three items: satisfaction with your nursing home as ''a place to live,'' and as ''a place to receive care'' (both on a 4-point scale from very satisfied to very dissatisfied) and likelihood of recommending the setting to others (on a 4-point scale from very likely to very unlikely). Emotional Well-Being Emotional well-being was measured using an adaptation of a scale previously developed, 22 whereby residents were asked to rate how they had been feeling 'lately'' on 10 positive or negative emotional states: lonely, happy, bored, angry, worried, contented, sad, afraid, interested in things, and looking forward to the future; response choices were often, 9 sometimes, rarely, and never. An additive scale with a range of 10 to 40 was developed by reverse coding the negative emotions; alpha reliability was 0.74. Other Variables Also included in the data set were sex, age, and time since admission (in months). For case-mix adjustment, ADLs (bed mobility, eating, transferring, and toileting) and cognitive functioning were extracted from the MDS and calculated using methods developed previously. Quality Indicators The 24 QIs were constructed from the MDS for residents in the GH, in Cedars, and in Trinity using assessments for the following time periods: between baseline and 6 months, between 6 and 12 months, and between 12 and 18 months after the GHs were operating. (Although Cedars and GHwere a single nursing home for federal MDS reporting, the data were separated for these analyses.) The QIs were constructed by adapting methods used previously 26 to include indicator-specific clinically derived adjustors as used in evaluations of quality of several managed care programs for elderly nursing home residents. 27,28 Data Analysis Stata version 9 was used for all data analyses (StataCorp., College Station, TX). Selection effects were examined by comparing baseline characteristics (independent and dependent 10 variables) of the sampled residents who went to the GH, remained at Cedars, or were in Trinity. Outcomes were analyzed using multivariate panel regression analyses using the random-effects regression models; these used the data from the three follow-up periods over 18 months; baseline data were used only for case-mix adjustment. Wave of data collection was accounted for using dummy variables. The main independent variable was the resident's status as a GH, Cedars, or Trinity resident at the time of data collection. Data from the baseline interviews were used only to check for selection effects. All analyses for self-reported outcomes were controlled for sex, age, time since admission, baseline ADL from the MDS assessment just before the subject entered the sample, and selfreport versus proxy report. Because MDS cognitive function and proxy status were collinear, the analyses were run separately, adjusting for baseline MDS cognitive function, with almost identical results. The results that control for proxy status are therefore reported as more reflective of cognitive status at the exact time of the resident interviews. The difference in residents' quality of life between the three nursing homes were analyzed using the randomeffects Tobit model, chosen to take into account the nature of repeated measurements in this data set and floor and ceiling effects. Floor effects were absent in all quality-of-life domains except for autonomy (3%) and functional competence (17%). Ceiling effects were present in most domain scales, ranging from moderate (e.g., 24% for privacy and 32% for the food enjoyment subscale) to severe (e.g., 53% for dignity). Differences in self-reported health, satisfaction, and emotional well-being were studied using random effects Ordered Probit regression models, chosen because the measures for these analyses were ordinal. 29 Differences in self-reported ADLs and IADLs were studied using random-effects population-averaged linear models. Testing was undertaken for possible interactions between proxy status and setting (Cedars, Trinity) in all models using a post estimation Wald test. The differences in MDS QIs between GH and the other two nursing homes were 11 examined using random-effects logit regression combining data from the three follow-up periods and including dummy variables for wave of data collection. RESULTS Samples at Baseline Only two significant differences at baseline were found across the groups; residents remaining at Cedars had a significantly longer length of stay than those who went to the GHs, and the GH had more African-American residents: 25% at baseline, compared with 5% at Trinity and Cedars (Insert Effects on Resident Outcomes Quality of Life (Insert (Insert The test for possible interactions between outcomes and proxy status revealed only one significant interaction. The use of proxy informants was associated with lower meaningful activity scores for Cedars residents (-0.381 vs -0.201, P =.001). At baseline, no differences were found according to setting for any of the nine social activities measured. With the three follow-up samples combined and with the usual controls, the likelihood of participating in organized activities in the facility (e.g., games, performances, religious services) was greater at Cedars (coefficient 0.56, P 5.002) and Trinity (coefficient 0.65, P 5.001) than at the GH, but organized trips away from the setting were less likely at Cedars (coefficient _ 0.61, P 5.001) and even less likely at Trinity (coefficient _ 0.80, P<.001). The GH group was just as likely to engage in solo activities, receive phone calls and visits, take privately arranged trips from the setting, or have an overnight guest as the comparison groups. Effects on Quality of Care (Insert DISCUSSION Summary The results strongly favor the GH and suggest that it achieved its stated goals. G

The Gerontologist Using Resident Reports of Quality of Life to Distinguish Among Nursing Homes

Purpose: We used measures created to assess the quality of life (QOL) of nursing home residents to distinguish among nursing facilities. Design and Methods: We statistically adjusted scores for 10 QOL domains derived from standardized interviews with nursing home residents for age, gender, activities of daily living functioning, cognitive functioning, and length of stay, and then we aggregated them to the facility level. We compared the patterns across a sample of 40 facilities. We correlated facility characteristics with QOL scores. Results: The pattern of QOL scores for each of the 10 domains was generally consistent within a given facility. Although resident characteristics played a major role in explaining variance, there were significant effects of facilities as well. Some modest relationships were found between facility characteristics such as ownership, percentage of private rooms, and rural-urban location and facility QOL scores. No effect of facility size was detected. Implications: This article shows that it is possible to differentiate among facilities on the basis of resident self-reported QOL. On the basis of our analysis, we find that a sample of 28 residents per facility is sufficient to generate a reliable QOL score for each of the domains studied